environmental issues project work methodology

Global Environmental Change: Research Pathways for the Next Decade (1999)

Chapter: 8 observations, observations, introduction.

The U.S. Global Change Research Program (USGCRP) has responsibilities to observe, document, and understand global change and to predict it to the extent possible. The USGCRP does this by concentrating on five science areas: seasonal-to-interannual variability, decadal-to-centennial variability, atmospheric chemistry and ultraviolet-B radiation, ecosystems, and human dimensions—areas described in the previous chapters. By far the largest share of USGCRP funding goes to making observations to accomplish both the aims of the science areas and those of observing and documenting global change.

This chapter constitutes the link between the scientific foundation established in Chapter 2 , Chapter 3 , Chapter 4 , Chapter 5 , Chapter 6 through Chapter 7 and the course of action now required. The scientific foundation for each of the six primary science areas—biology and biogeochemistry of ecosystems, seasonal-to-interannual climate change, decadal-to-century climate change, atmospheric chemistry, paleoclimate, and the human dimension of global change—consists of a statement of the following: scientific character of the problem, selected case studies, key unanswered scientific questions, lessons learned in the course of scientific research over the past decades, and research imperatives.

The research imperatives are central. They connect theory and observation, defining the specific observations that are required. They connect priorities and resources and science with public policy. They separate, as direct experience has shown, success and failure. Together with consideration of the lessons learned, they establish the foundation for an effective scientific analysis of the Earth system.

Several basic scientific approaches, which set observational demands, can be distinguished: testing specific hypotheses—hypotheses that seek to define mecha-

nisms, whether chemical, biological, or physical, that control the Earth system and its climate; defining the degree to which the Earth system has changed and is changing over periods of years, decades, centuries, and millennia; and (c) exploring largely uncharted regions, which may be defined geographically, mechanistically, or in other scientific terms. In the course of establishing an observational approach it is essential not to lose sight of this distinction.

There are also important distinctions in the required datasets for the different disciplines. These distinctions are the basis of fundamental “cultural” differences in the architectures selected for specific observational approaches. For example, observations are obtained in different ways to address questions about different phenomena, such as the following:

Ice cover changes as a function of time on seasonal-to-decadal scales.

Free radicals at the parts-per-trillion level in the troposphere and the stratosphere.

Vegetation pattern changes in terrestrial systems and oceanic systems.

Secular trends in atmospheric temperature with an accuracy of 0.1 K, as a function of altitude, latitude, longitude, and season.

Mesoscale meteorological events tied to global-scale variations such as the El Niño-Southern Oscillation (ENSO).

Observations required for each of these phenomena are not obtainable through a single solution, such as a single global network of ground-based observations or an ensemble of space-based remote sensors. While considerable intrinsic programmatic pressure exists for a “unified ” solution to Earth observations, the scientific context speaks strongly for a flexible and adaptive aggregate of techniques that attack specifics, whether of long-term trends or of mechanisms that control the Earth system.

A series of examples in Chapter 2 , Chapter 3 , Chapter 4 , Chapter 5 , Chapter 6 through Chapter 7 also represented a broad spectrum between observational constraint and theoretical speculation. The scientific method is pursued in an effective and vital manner when the fundamental design of the observational approach is matched to the calculated observables such that specific mechanisms, fundamental to the system, are tested directly. Models are very powerful when used in this context (see Chapter 10 ). They are central partners with observations in the course of proving or disproving fundamental assumptions.

This report approaches the problem of observations as a synthesis, working from scientific research needs to observational implementation. It has always been assumed that building a global observing system would serve the needs of most of the science components of the USGCRP. Indeed, a parallel activity is taking place (Global Climate Observing System, GCOS) to design a global observing system for climate to satisfy both scientific and monitoring needs. 1 Parallel efforts are under way for the ocean (Global Ocean Observing System) and

the land surface (Global Terrestrial Observing System); the climate modules of these systems are identical to the ocean and land modules of GCOS. However, it is our impression that there is no guarantee that such an observing system, even if it could be built at this time, would (or could) satisfy research needs. By designing a multiuse observing system for research purposes and then adapting it to meet global observing and monitoring system needs, there is some assurance that both research and monitoring needs will be met in an orderly manner. The model used here depends first on satisfying the needs of the science areas of the USGCRP, transitioning those parts of the system that can be made operational and then seeing how close to a global observing system we have come.

OBSERVATIONS REQUIRED FOR THE SCIENCE ELEMENTS OF THE USGCRP

As stated, the issue of observations is approached here in a synthetic manner. Scientific research needs were examined in Chapter 2 , Chapter 3 , Chapter 4 , Chapter 5 , Chapter 6 through Chapter 7 . For each element described in those chapters the observational implications of those research needs are examined. These implications are examined in this section at the level of detail representing the state of the science in each of the subject areas. Given the disciplinary breadth of the USGCRP, the requirements are quite heterogeneous in both content and method of presentation. For example, observational requirements for the Global Ocean-Atmosphere-Land Surface (GOALS) program are detailed in another National Research Council report that is in press and are only summarized here. For other elements, such as the biology and biogeochemistry of ecosystems area, arguments leading to the observational requirements are repeated here for clarity. This chapter is also limited to discussion of observational needs and not the technology to supply those needs.

Of particular interest is the degree of commonality among the observational requirements of the science elements, despite the disciplinary differences. For example, the need to observe radiatively active gases in the atmosphere is common to atmospheric chemistry, ecosystems, and decadal to centennial climate change research areas. Observations of streamflow, atmospheric and sea surface temperatures, and precipitation are emphasized across science elements. These common needs are not necessarily surprising, but they do emphasize the importance of such basic long-term measurements for the disciplines of global change.

Biology and Biogeochemistry of Ecosystems

The Research Imperatives for ecosystems research, as defined in Chapter 2 , are:

Land surface and climate. Understand the relationships between land surface processes and weather prediction and between changing land cover and climate change.

Biogeochemistry. Understand the changing global biogeochemical cycles of carbon and nitrogen.

Multiple stresses. Understand the responses of ecosystems to multiple stresses.

Biodiversity. Understand the relationship between changing biological diversity and ecosystem function.

Research on global ecosystem processes motivates four broad classes of observations and experimental studies, shown below. As noted in Chapter 2 , large-scale measurements in ecology tend to support all of the research imperatives above in a crosscutting fashion, with any one measurement set helping to test a variety of hypotheses. Ties of these measurement areas to the research imperatives are shown in Table 2.2 . The four key measurement areas are time series observations of ecosystem state; land use and land cover change; site-based networks; and measurements of diversity, functional diversity, and ecosystem function.

Time Series Observations of Ecosystem State

Global time series of vegetation and phytoplankton state, derived from the National Oceanic and Atmospheric Administration's (NOAA) Advanced Very High Resolution Radiometer (AVHRR) and Coastal Zone Color Scanner sensors, for land and ocean, respectively, have proven their value in understanding the seasonal and spatial characteristics, interannual variability, and trends of large-scale biogeochemistry and biophysical processes. 2 Space-based measurements of ecosystem state are fundamental in determining the link of terrestrial ecosystems to climate, the biogeochemistry of the land and oceans, and the impacts of climate and other disturbances. While measurements of “greenness” and ocean color are not direct ecological properties, they have proven to be highly correlated with spatiotemporal dynamics of ecosystems. Recent work 3 highlights both the utility of these records and the dependence of the science on long and consistent records. Stable calibration and removal of the atmospheric signals of ozone, water vapor, and aerosols are critical to detecting ecological signals. While there is ample room for innovation in land surface remote sensing, stable calibration and correction impose stringent requirements on the sensor or sensors deployed. New instruments, while adding new capabilities, must also be “backwards compatible” to preserve time series. Atmospheric correction requires that coincident observations to quantify water, ozone, and aerosols be available for use in land surface retrieval algorithms. Spatial and temporal resolution for time series instruments are typically a compromise between sufficiently high spatial resolution to resolve ecosystem structure (0.25 to 1 km 2 ) and swath width and data rate limitations associated with near-daily coverage. High temporal coverage is needed to ensure adequate sampling of seasonality, especially in cloudy environ-

ments. These requirements apply generally for both terrestrial and marine ecosystems; marine ecosystems add additional instrument requirements to avoid saturation by sun glint or high reflection. Data for land cover change require higher spatial but lower temporal resolution.

Land Use and Land Cover Change

Changing land use and land cover are fundamental drivers of global change and direct reflections of human activity and impacts. Land use changes have profound effects on the biogeochemistry of carbon, infrared active gases, photochemically active gases, and aerosol production (via dust and biomass burning). Land use changes also affect hydrology and erosion and, by changing surface albedo and energy exchange, can have direct effects on climate. People often create highly heterogeneous landscapes, mosaics that can encompass activities with highly divergent effects on ecological processes. The spatial arrangement of landscapes can affect exchanges of water and associated solutes and particulates in freshwater and coastal margin areas, with land cover at the land-water margins having substantial effects on water chemistry. The arrangement of landscapes also affects biological diversity, invasibility, and extinctions. Data on land cover and its change over time must thus capture the spatial scales of natural and human patterns. Space-borne sensors with resolutions from a few square meters to tens of square meters have proven to meet these needs. 4 Sensors with two to seven spectral bands are adequate for land cover mapping, although new technology employing spectrometers, 5 radar, or lidar has great potential. As in measuring ecosystem state, “backwards compatibility” must be preserved to continue existing time series when new technology and capability are introduced.

Site-Based Networks

In situ measurements of ecological processes tend to be highly multivariate. In terrestrial systems, understanding a measurement of CO 2 flux and determining net primary productivity (NPP) require sampling multiple plant parts (leaves, wood, roots), often of several life forms (e.g., co-occurring grasses, shrubs, and trees). The plant parts are then analyzed for carbon and nitrogen. Understanding spatial variations in gradients of atmospheric CO 2 , 13 CO 2 , CO 18 O, or O 2 requires a network of measurement sites over large areas. To understand this process, leaf physiology, soil microbial processes, water fluxes, and other variables must be determined. Parallel issues arise in marine ecosystems regarding trophic dynamics and transport. At many sites, measurements are made as part of an experimental design including controls and various manipulations (e.g., of nutrients, species composition, disturbance frequency). These measurements are the essence of ecological data: the satellite and other geographic data serve to knit together disparate process studies in space and time. While there is much

interest in a common set of quantities in ecological site studies (quantities such as CO 2 , trace gas and water fluxes, NPP, nutrient availability, and species composition and diversity), achieving consensus on a core set of measurements, standard methods, and data formats is just beginning. No global-scale experimental design implementing such sites is in place to sample marine and terrestrial ecosystems, although such a design is proposed by the International Geosphere-Biosphere Programme (IGBP), using long baseline transects across ecological gradients. A high priority of global ecosystem science is to develop a network of appropriately sited atmospheric concentration and isotope, flux, and ecological process sites. Both the overall experimental design and the suite of measurements and methods must be decided. Minimally intrusive measurements (e.g., flux measurements) and manipulations (e.g., of CO 2 concentration) must be components of such a network design.

Recent advances in hyperspectral measurements made directly and remotely have established that remote sensing of foliar chemistry will be an important element in producing large-scale spatially explicit estimates of forest ecosystem function. During the past decade, a number of studies were conducted to determine if data from the National Aeronautic and Space Administration's 10-nm spectral resolution Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) could be used to make canopy nitrogen and lignin measurements. AVIRIS channels in the visible and infrared regions were correlated to field-measured foliar nitrogen and lignin. 6 Estimates of canopy foliar nitrogen were used as input to the primary production model 7 to determine ecosystem productivity at the Harvard Forest, in Massachusetts. At Blackhawk Island, AVIRIS-derived foliar lignin was used to determine nitrogen mineralization rates using a relationship observed by Wessman et al. (1998). These and other results suggest that direct measurement of forest canopy chemistry characteristics, based either on field measurements or via remote sensing, may provide simple, direct scalars of current forest productivity potential. In the coming decade, a space-based system will replace AVRIS, and the application of these techniques can be made at research sites globally.

Measurements of Diversity, Functional Diversity, and Ecosystem Function

The issue of diversity and species composition changes has emerged as a critical topic for global change in recent years. It is clear that the functional diversity of the Earth's biota is a first-order control over global ecosystem function, but how changes to the biota will affect global ecosystem function still is a young research topic. 8 Designing a global observing system and network of experimental studies, analogous to those described above for biogeochemical fluxes, is premature; the necessary monitoring and manipulations at global scales are currently far from obvious. But a major exploratory effort involving manipulations, studies of ecosystem function in the face of ongoing invasions, extinctions, species range shifts, and global monitoring of species diversity, invasion,

and extinction rates are all needed. These exploratory studies will lay the groundwork for a more systematic attack. The foundation for systematic study and monitoring of changing diversity and functional diversity must be laid quickly and a global research program put in place.

Key Measurements for Ecosystem Studies

Based on these considerations, the tables below present time- and space scales of critical in situ ( Table 8.1 ) and remotely sensed ( Table 8.2 ) measurements for terrestrial and marine ecosystem studies. These tables present examples of issues, measurements, and timescales, but they are not exhaustive.

Seasonal to Interannual Climate

Chapter 3 sets forth three broad Research Imperatives: ENSO prediction research, global monsoon research, and land surface exchanges, downscaling, and terrestrial hydrology research. These imperatives, as in other chapters, frame the observational requirements.

ENSO Prediction Research Imperative

The ENSO prediction process—predicting aspects of sea surface temperature (SST) and corollary variables—requires data to initialize the coupled models and data to evaluate the skill of the predictions. Because SST is the crucial variable to predict, weekly fields of SST at the 1° × 1° level are absolutely essential. These observations are currently provided by AVHRR, combined with in situ drifters to pin down the absolute values and gradients of SST.

The key variables for initializing the model are the state of the atmosphere and the density state of the upper ocean. The state of the atmosphere does not seem to be as critical for initialization, since the model atmospheric state rapidly adjusts to the initial SST. In any case, the state of the atmosphere is provided by the twice-daily analyses from the operational weather prediction models.

The internal state of the upper ocean can be assessed in two separate ways: directly by temperature-measuring instruments, on a line connecting a surface mooring to a bottom anchor, or indirectly by applying observed heat and momentum fluxes over the ocean component of the coupled model for a long period of time (usually exceeding 20 years). In practice, salinity is very difficult to measure and does not make a major contribution to the initial thermal state, so the direct method measures only temperature. The indirect method depends primarily on measuring the momentum fluxes with the heat fluxes parameterized, so that only the surface winds are used in the calculation.

Currently, ocean models are initialized by combining the two methods above, assimilating both the long-term history of the wind fields and the currently ob-

TABLE 8.1 Time and Space of key IN Situ Measurements for terrestrial and Marine Ecosystem Studies

TABLE 8.2 Time- and Space Scales for Key Remotely Sensed Observations for Ecosystems Studies

tained thermal state of the upper ocean, to arrive at an optimal estimate of the ocean's current thermal state. The subsurface ocean data are provided by a network of 70 moored TAO (tropical atmosphere-ocean) arrays in the tropical Pacific Ocean (providing approximately 2° of meridional resolution and 15° of longitudinal resolution) and by the ongoing XBT network. These same moorings measure winds, but, since the full TAO array has been in existence for only two years or so, historical winds must be obtained from the Comprehensive Ocean-Atmosphere Data Set, gathered from individual ship reports from volunteer observing ships.

Because the ENSO observing system described in Chapter 3 measures the quantities needed to initialize the ocean component of the predictions, it is vital that this array be continued. The ENSO observing system was designed on the basis of the scales of variability of the winds. It may turn out that either fewer or more moorings are required to optimize prediction skill.

Other quantities also prove useful for initialization:

Sea surface height, as measured by satellite altimetry and tide gauge stations scattered around the islands and coasts of the tropical Pacific.

Currents measured on the equator where geostrophy is more problematic.

Cloud cover and solar irradiance reaching the surface.

Precipitation in those areas in and surrounding the tropical Pacific (and remotely in the areas that ENSO affects) to evaluate the skill of precipitation predictions.

Upper-level water vapor to evaluate the effect of seasonal to interannual variability, as opposed to greenhouse feedback, of this quantity.

The overall recommendation, therefore, is to maintain global SST measurements and maintain the ENSO observing system, especially the TAO array.

Global Monsoon Research Imperative

The GOALS program has devoted much effort to defining the observational requirements for global seasonal to interannual predictions. These requirements are summarized in Table 8.3 . Note that variables are listed in priority order. Not surprisingly, there is virtually complete overlap between these variables and those identified as important in pursuing the other seasonal to interannual research imperatives identified in the following section. Only the variable of land surface energy fluxes is not identified both below and in the following section.

Land Surface Exchanges, Downscaling, and Terrestrial Hydrology Research Imperatives

The primarily hydrological observational datasets needed to support research imperatives in the areas of land surface exchanges, downscaling, and terrestrial hydrology can be described as follows.

TABLE 8.3 State and External (or Forcing) Variables * That Must Be Measured for the GOALS Program

At the same time that the policy-making community seeks guidance and advice on interpreting the impact of global hydrological change, the basic monitoring of hydrological fluxes, through data provided by observational networks for discharge and water quality, remains fragmented at best. Developing regions of the world, by their very nature subject to the direct and immediate effects of rapid anthropogenic change, lack the infrastructure to adequately monitor the status of their water resources. Even in traditionally well-monitored regions such as the United States, there has been a substantial decline in land-based monitoring capacity. 9 In addition, there has been an assault on open access to basic hydro-meteorological datasets for global change research, aided in large measure by

commercialization. 10 The World Meteorological Organization's Global Runoff Data Center in Koblenz, Germany, holds information on nearly 3,000 discharge monitoring stations. However, in accordance with the wishes of the donor nations, access to this information is restricted and no transfer of the complete global dataset or substantial portions of it are possible. A recent UNESCO (United Nations Educational, Scientific, and Cultural Organization) publication and related digital data bank of approximately 1,000 discharge monitoring stations 11 represents the last digitized global data bank of river runoff that is freely available to the global change community (at Oak Ridge National Laboratory Data Acquisition and Archive Center). Lamentably, its last data entry is for 1991.

A set of long-term index stations should be identified, some of which should be as free from the effects of upstream regulation and diversions as possible. In the United States the logical responsible agency would be the U.S. Geological Survey (USGS). However, the funding method currently used for the USGS stream gauge network is not necessarily consistent with the needs of a climate network (e.g., only about 10 percent of USGS stations are funded from the agency's core funds; the remainder are funded cooperatively with state agencies and by other federal agencies for operational purposes). Moreover, there is a significant need for this information on a global scale, which poses a difficult operational and political challenge. This topic of in situ riverine information is important and should be addressed.

Precipitation

Station data. The United States must maintain existing long-term stations within the National Climatic Data Center (NCDC) cooperative network, particularly the subset of stations that make up the Hydroclimatic Data Network and the U.S. Historical Climate Network. Precipitation measured at first-order stations has recently undergone radical changes and considerable technical problems, making these networks even more important.

Radar precipitation data. The National Center for Environmental Prediction has recently started to archive a merged WSR88-D (Doppler radar)/gauge product (4-km resolution) that covers most of the United States. The suitability of these data for climatological purposes needs to be evaluated, and steps must be taken to ensure the security of the long-term archive of the data and to ensure that the data are freely available to the scientific community. From a more global perspective, the recent Tropical Rainfall Measurement Mission (TRMM) launch holds great promise for tropical regions.

Surface Radiation

Only a very small number of stations now operate in the continental United States that collect a full suite of surface radiation observations (the SURFRAD

network). The adequacy of this network for studies of seasonal to interannual variability should be evaluated.

Point observations. Prior to the recent National Weather Service (NWS) modernization, snow water equivalent point observations were collected across the United States at NWS stations and archived at the NCDC. Since NWS 's modernization, snow water equivalent measurements are only monitored at selected NWS forecast offices and are now considered supplementary data. This has significantly decreased data coverage.

Snow water equivalent point observations are collected primarily at Natural Resources Conservation Service Snow Telemetry sites in mountainous areas of the western United States. The suitability of these sites for long-term climate studies needs to be evaluated (the longest records from these stations date only to the mid-1980s). Snow depth measurements are collected at a few thousand NCDC cooperative stations. The feasibility of using some subset of these stations to measure snow water equivalent should be evaluated. The objective is to achieve a much more uniform spatial distribution of station-based observations.

Areal extent. The NOAA National Operational Hydrological Remote Sensing Center and the National Environmental Satellite, Data, and Information Service (among other entities) produce satellite-based snow areal extent measurements of the continental United States and the world. These products are currently used for operational purposes but could prove extremely valuable for assessing such interactions as those between the continental extent of seasonal snow cover and large-area circulation patterns. Steps should be taken to ensure that these data are climatologically useful.

Algorithms. Satellite remote sensing algorithms to estimate snow water equivalent in a manner suitable for global studies (e.g., spatial resolutions of tens of kilometers) have been improved and may be suitable for seasonal to interannual timescale studies, notwithstanding problems remaining for forested areas. These products need to be assessed and archived at (or through) the National Snow and Ice Data Center.

Wind and Humidity

Although wind and humidity data are collected at NCDC surface airways stations, many of the records are affected by station and instrument changes, and their use for climatological purposes is problematic. Nonetheless, they are critical for computing potential evapotranspiration, and they provide reference values for approaches that can lead to spatial estimates (e.g., modeling combined with atmospheric profile data or analysis fields). Thus, more attention should be given

to the climatological value of these observations. On global scales it would be extremely useful if a far richer network of wind observations, particularly over oceans, could be achieved.

Surface Air and Skin Temperature

Observations of surface air temperature are critically important to predict evapotranspiration and snow accumulation and melt. Surface air temperature measurements are routinely collected at NCDC cooperative observer stations, as well as NWS manned observing stations. Because air temperature tends to have much higher spatial correlation locally than, for instance, precipitation, maintenance of an adequate station precipitation network should assure adequacy of surface air temperature measurements, provided that these variables are coincidentally collected. Direct observations of surface (skin) temperature are much more problematic. Surface observations have generally only been collected in research projects and are difficult to interpret. Nonetheless, skin temperature is a state variable predicted by most land surface schemes (some schemes predict an effective vegetation temperature as well). Thus, these measurements might be updated also. Satellite sensors and algorithms can produce global estimates of skin temperature at time frequencies as high as daily; a ground network could play a critical role in validating and calibrating the long-term spatial records that are now being acquired. The role of Earth Observing System (EOS) PM-1 and subsequently the temperature sounding made by the National Polar-Orbiting Operational Environmental Satellite System (NPOESS) should be particularly valuable; however, there must be a consistent connection between EOS and NPOESS (and the European system of polar-orbiting platforms).

Surface Energy Fluxes

Direct observations of surface energy fluxes (latent, sensible, and ground heat flux) have been collected almost exclusively in conjunction with research programs (e.g., the First International Land Surface Climatology Project Field Experiment, the Hydrological and Atmospheric Pilot Experiment). Recent advances in instrumentation may permit routine long-term operation of eddy correlation and other systems. A commitment has been made, for example, to continue long-term operation of some of the Boreal Ecosystem-Atmosphere Study tower flux sites. The feasibility of long-term operation of surface flux sites should be assessed to represent such features as major vegetation types in the United States and perhaps globally.

Soil Moisture

Soil moisture plays a key role in partitioning net radiation into latent, sensible, and ground heat fluxes, particularly in summer. Many studies have indi-

cated the potential importance of feedbacks between soil moisture and climate, especially in the interior of the northern hemisphere continents in summer. Therefore, observation of soil moisture is of great importance, through ground- or satellite-based observing systems or both. A few networks in the continental United States collect ground-based point observations of soil moisture, including networks of the Illinois Water Survey and the Oklahoma Mesonet. While there are questions about how point observations of soil moisture can be interpreted in the context of small-scale spatial variability and about the lack of standard instruments, synoptic-scale events are well captured. With regard to remote sensing, both active and passive microwave sensors have shown potential in estimating near-surface soil moisture. Furthermore, in combination with modeling, these surface observations might be extended to greater depth. Many issues remain, and problems of soil moisture estimation from satellite sensors are themselves the subject of ongoing research. Nonetheless, the success of these efforts is critically important for seasonal to interannual prediction and should be highlighted.

Knowledge of seasonal and interannual variability in vegetation properties is critical to understanding links between the land surface and climate at seasonal to interannual timescales. Satellite-based estimates of vegetation properties, such as leaf area index and greenness, are now fairly widely used in numerical weather prediction models. EOS-era developments (e.g., the Moderate Resolution Imaging Spectroradiometer, MODIS) will almost certainly improve the quality of these products. Again, however, it is essential that a consistent transfer of observing be achieved as we move from NASA (morning and afternoon observations from MODIS) to NOAA and EUMETSAT (European Organization for the Exploitation of Meteorological Satellites)-provided observations. There must be sufficient stability and accuracy in the operational instruments to maintain the time series begun by MODIS, and there must be adequate instrumental overlap to ensure that the operational measurement systems are calibrated against the EOS measurements. Furthermore, a long-term global archive of seasonal variations in vegetation properties must be preserved, along with sufficient metadata to resolve questions about any effects of changes in instruments.

Decadal to Centennial Climate Change

The following Research Imperatives ( Chapter 4 ) are required to advance most efficiently our understanding of decadal to centennial (dec-cen) climate variability and change.

Natural climate patterns. Improve knowledge of decade-to-century-scale natural climate patterns, their distributions in time and space, optimal

characterization, mechanistic controls, feedbacks, and sensitivities, including their interactions with, and responses to, anthropogenic climate change.

Climate system components. Address those issues whose resolution will most efficiently and significantly advance our understanding of decade-to-century-scale climate variability for specific components of the climate system.

Anthropogenic perturbation. Improve understanding of the long-term responses of the climate system to the anthropogenic addition of radiatively active constituents to the atmosphere and devise methods of detecting anthropogenic phenomena against the background of natural decade-to-century-scale climate variability.

Paleorecord. Extend the climate record back through data archeology and paleoclimate records for time series long enough to provide researchers a better database with which to analyze decade-to-century-scale patterns, specifically to achieve a better understanding of the nature and range of natural variability over these timescales.

Long-term observational system. Ensure the existence of a long-term observing system for a more definitive observational foundation to evaluate decade-to-century-scale variability and change. Ensure that the system includes observations of key state variables as well as external forcings.

The foundation for recent progress in ENSO research was laid by careful diagnosis of ENSO pattern variability (see Chapter 3 ). 12 Similarly, understanding and predicting decadal-to-centennial (dec-cen) variability to a large extent depend on knowledge of climate patterns on these longer timescales. Logically, we might expect that the response of the Earth system to anthropogenic forcing would be manifested in and/or obscured by these patterns. Thus, one particular important concern is the interactions between natural variability and anthropogenic change.

For greater predictive capability it is essential to understand those processes operating in the various components of the climate system that are relevant to dec-cen variability. Because of the difficulty of directly observing phenomena of interest in dec-cen studies, in contrast to weather or seasonal to interannual studies, the importance of component process understanding is magnified.

With respect to anthropogenic perturbation, it is particularly important to closely monitor the rate and distribution of source functions of the radiatively active gases being added to the atmosphere. These external forcings, which cannot be readily predicted, can then be properly introduced and diagnosed in the predictive model studies. Such models are the primary available means for forecasting anthropogenic change and for guiding diagnostic and attribution studies and sampling efforts. It is therefore critical to adopt an incremental long-term

observing system whose characteristics and targeted variables can evolve in parallel with our rapidly improving understanding. The importance of a comprehensive long-term observing system has been endorced by several international bodies, including the World Climate Research Program (WCRP) (see Box 8.1 ).

Many of the issues defined here require observing systems that do not yet exist or to which no long-term commitment has yet been made. An example is the need to monitor solar irradiance: current data have come from relatively short-term satellite missions that have no operational (long-term) mandate (see the case study later in this chapter). Measurements from different missions observing simultaneously are in significant disagreement, and the magnitude of the offset is of the same order as greenhouse forcing. Addressing decadal-to-centennial solar variability, as discussed above, requires a plan for long-term calibrated solar irradiance measurements across the solar spectrum.

Finally, as previously indicated, dec-cen research is in its early stages, with new insights, findings, and directions arising rapidly. The long-term sampling strategy and optimal measurement set is evolving with these advances as well. At this stage, then, it is imperative that we begin (or in a few cases continue) consistent monitoring of the most fundamental state variables (e.g., atmospheric temperature and moisture profiles, ocean surface temperature and salinity values) and monitoring of those variables specifically relevant to climate system components to initialize (including via assimilation), force, and diagnose model components and variables.

Atmospheric Observations

The physical system.

The physical state of the atmosphere, regardless of the mechanisms influencing this state, is at the very core of what we call climate. Atmospheric temperature and moisture content, pressure, winds, and cloud cover (the main factor controlling the surface radiation balance) must all be monitored. The spatial distribution of this monitoring can be improved with time to span the globe eventually at the relevant spatial scales, but initially a concerted effort must be made to monitor those variables at current weather station locations.

As the concentration of greenhouse gases increases in the atmosphere, the atmosphere clearly must respond in some manner to accommodate the change in radiative forcing. The atmosphere may respond by warming to some degree, it may change its vertical distribution of moisture and cloud cover, or some combination of these. All of the state variables must be monitored, including their vertical distributions through the troposphere and lower stratosphere, to evaluate the nature of anthropogenic and natural changes. One of the most hotly debated topics in modern climatology is how atmospheric moisture distribution will change in response to the addition of greenhouse gases and therefore whether, or by how much, this moisture response will moderate the temperature response. Thus, it is not enough to measure temperature simply because temperature has been the initial focus of the greenhouse debate.

Atmospheric observations must be collocated with those stations established to monitor surface conditions. This need directly follows from the fact that most, if not all, dec-cen atmospheric variability and change are in response to changes in slower components of the climate system, such as land, ice, and ocean. These components represent the lower boundary of the atmosphere. In many cases, atmospheric changes strongly covary with changes at the surface. To evaluate, diagnose, and attribute dec-cen change, such covariation must be captured in a manner that facilitates analysis and evaluation of hypotheses that describe the coupled mechanisms driving and modulating long-term variability.

Process studies and related field efforts must be directed to improving our understanding and parameterization of surface-atmosphere interaction. Obviously, it is through this boundary interaction that slower-scale components communicate their influences to the atmosphere. Appropriate parameterization of these phenomena is therefore essential, since modeling efforts are the primary tool we have for forecasting future change. We also need better parameterization of clouds, including their distribution and feedback processes, because their treatment in models may prove crucial in predicting long-term climate responses to changes in radiative forcing, as well as other feedback influences associated with variability and change. These parameterizations are currently a primary limitation in existing models.

The Chemical System

The radiative effects of aerosols, direct and indirect, are poorly constrained. Cloud processes, although they occur on far shorter than decadal timescales, are a major uncertainty in predicting future radiation balances. Parameterizations need to be improved.

Carbon cycle questions require a CO 2 measurement strategy that accounts for the hierarchy of scales, both temporal and spatial, inherent in ecosystem processes and their controls. Atmospheric concentration data must allow the identification and quantification of regional sources and sinks and their responses to climate fluctuations and human perturbations. This information will permit integration over regional scales of fluxes and feedback processes that can be measured, understood, and modeled on smaller spatial and temporal scales. Isotopic data allow distinguishing between oceanic and biospheric sinks on regional scales and have provided significant insight into the regional carbon balance. Ratios of O 2 to N 2 in the global atmosphere provide an independent constraint on the balance between net terrestrial and oceanic sinks. The same scaling and measurement issues are almost identical for N 2 O and CH 4 , and their biogeochemical budgets can be tackled together with a measurement program suitable for CO 2 .

Enormous progress in assessing trace gas budgets could be achieved if a method could be developed or refined to directly measure air-sea gas exchange rates. Promising methods are air measurements with eddy correlation and/or eddy accumulation. Such measurements would eventually lead to a realistic understanding of the processes controlling the rate of gas exchange and therefore to a parameterization that could be applied with confidence worldwide. Existing climatologies of the partial pressure differences between the air and the water for many gases could then be turned into maps of gas exchange, making oceanic data into a much more compelling constraint on the atmospheric budget and closing the open boundary of surface oceanic gas budgets.

Ocean Observations

Various types of ocean observations are needed to study the dec-cen variability associated with the primary known patterns of atmospheric climate variability: periodic (decadal) temperature, salinity, oxygen, and tracer sections; velocity profile surveys and repeat sections (starting with World Ocean Circulation Experiment sections); and higher-frequency time series stations (starting with past and present weather ship stations). These measurements will allow better quantitative description of the ocean's participation in dec-cen variability, especially in light of the slowly propagating SST and subsurface anomalies that have revealed the ocean's dec-cen variability as more than stationary patterns. We must extend these surveys into southern hemisphere regions as the nature of the deccen variability begins to be revealed.

These sections and time series stations provide the baseline against which the long-term response and change of the ocean can be measured, and they provide the basic observational set from which serendipitous discoveries about the ocean's role in climate change have been realized. In addition, the time series data have been invaluable in studying the ocean's response to atmospheric forcing and its feedback to the atmosphere. These findings are of particular importance because surface layer interaction and response dictate the volume of water in direct communication with the atmosphere. Even a small change in this volume can lead to a significant change in SST, given the same magnitude of surface forcing. The time series stations are the only series available that allow appropriate development, diagnosis, and improvement of these parameterizations.

Continued satellite data are needed for global coverage of sea surface height, SST, winds, and ocean color, but for these data to be useful, corresponding ground-truth ocean observations also are needed. Particular data of interest concern the heat budget. A concerted effort is required to improve estimates of heat flux divergence and heat storage and their variabilities from subsurface ocean data, eliminating disparities between those estimates and air-sea heat exchange estimates. Various subsurface floats and moorings are particularly helpful to supplement shipboard measurements for this study.

Sea level change is another important observational challenge. The Intergovernmental Panel on Climate Change (1996) estimates that sea level in the year 2100 will be 46 to 72 cm higher than today (36 to 53 cm when the effects of sulfate aerosols are included). A range is given because each projection presumes a specific scenario for increase in greenhouse gasses. To validate these predictions, better monitoring of global sea level change and its components will be needed. The prospects for sea level monitoring are good. A global network of sea level stations (Global Sea Level Observing System) is being implemented. Land movements will be measured at some of these stations with satellite geodesy and gravimetric techniques. Satellite altimetry is another important tool coming into use to measure global sea level rise.

Cryosphere Observations

Critical cryosphere-related observations for climate patterns on decadal to centennial timescales include long-term monitoring of surface salinity along with SST, since salinity represents the dominant control on the density of seawater in high-latitude regions. Also, measurements of the sea ice fields themselves, including motion fields and ice thickness, are required to determine the freshwater transports and buoyancy fluxes associated with the ice fields. This freshwater transport has been implicated in driving major changes, even mode shifts in the global thermohaline circulation. Finally, consistent monitoring of iceberg calving and an observational system for determining ice basal melt or growth (e.g., through temperature/salinity moorings across the floating ice shelves) must be established to better determine the freshwater budget. Both field and satellite studies are needed to refine the mass budgets of the Greenland and Antarctic ice sheets. Onsite studies that have focused on ice flow, melting, and calving should be continued and extended. Water vapor flux divergence observations will help pin down the source of the ice sheets' mass. A laser altimeter on a polar-orbiting satellite is needed to augment existing radar altimetry. These satellite data will provide accurate estimates of ice sheet volume and give early warning of possible ice sheet collapse. As in the case of ice, the distribution of snow fields, including thickness and spatial extent, must be monitored. The response of snow distribution to climate change has been hypothesized as being important in surface-climate feedbacks as well as in climate change diagnostics.

Finally, the ocean-atmosphere-ice interaction, particularly the ice or snow surface energy balance (including surface albedo and ocean-ice, ice-cloud, and snow-cloud feedbacks), must be addressed through detailed process studies to improve parameterizations of these processes in climate models.

Land and Vegetation Observations

Observations of changes in land surface characteristics, including surface vegetation, are essential for research goals in both ecosystems and dec-cen climate. Observational requirements are discussed in detail in the section on ecosystems earlier in this chapter. Changes in land surface properties alter not only the distribution of surface reservoirs and the surface-atmosphere exchange of radiatively active gases but also albedo and even surface stress and evapotranspiration efficiency, and the last two both influence the hydrological cycle. This serves as an external forcing to the planet that cannot be predicted and must be introduced into the models as they occur to properly maintain the models' surface forcing conditions.

Long-term monitoring of near-surface aerosol distributions is also needed; these distributions may induce stationary changes in the surface radiation bal-

ance, which may lead to large-scale circulation moderation through stable gradient perturbations.

Hydrological Observations

Precipitation is the key hydrological variable. For most studies of dec-cen variability and its effects, global fields of precipitation over timescales of 10 to 100 years are essential. We have no such global instrumental records currently. TRMM is an important first step, but global data are needed. To relate precipitation to global boundary conditions, it is necessary to simultaneously measure SST, vegetative ground cover and soil moisture, and sea and land ice and snow. Nearly every theory of anthropogenic warming finds an increased rate of the hydrological cycle and possible alteration of atmospheric distributions of moisture and of the frequency, intensity, and distribution of rainfall (including severe rainfall events). Thus, monitoring of the surface distribution of precipitation and evaporation must begin. This monitoring includes that over the oceans, where changes in the precipitation minus evaporation balance alter the surface salinity budget, which in high latitudes has been implicated in altering the thermohaline circulation (and driving internal oscillations on dec-cen timescales in ocean models).

Atmospheric Chemistry

Four primary Research Imperatives set the observational demands for this area:

Secular trends in the intensity of ultraviolet radiation that the Earth receives.

Source molecules for climate change.

Secular trends in photochemical oxidants.

Aerosol radiative forcing and climate change.

Stratospheric Ozone and Ultraviolet Radiation Research Imperative

A central issue of atmospheric chemistry is to define and predict fluctuations and secular trends in the intensity of ultraviolet radiation that the Earth receives. Along with temporal trends in ultraviolet intensity reaching the ground, it is also imperative to address the mechanisms and processes responsible for controlling the transport, photochemical production, and catalytic loss of ozone in the global stratosphere. (The issue of tropospheric ozone is treated below.) The observational priorities in this area, therefore, are observed changes in column ozone itself, transport of chemical species, photochemical transformations, and fundamental laboratory diagnostics of molecular processes.

Define the Intensity of Ultraviolet Radiation that the Earth Receives

Priority: Observe the total column density of ozone from orbit with daily global coverage and accuracy of ±5 percent, such that an uninterrupted record is sustained. These observations must have a precision adequate to detect a trend of 1.5 percent change per decade. Observe the concentration of ozone with altitude resolution of 3 km between 10 and 25 km, such that secular trends in upper-tropospheric and lower-stratospheric ozone can be tracked with an accuracy of 3 percent per decade. From the ground, obtain observations of ultraviolet-B flux, accurate to ±2 percent and precise to ±1 percent at 30 stations worldwide, strategically placed, with 20 in the northern hemisphere, and 10 in the southern hemisphere.

Predict Fluctuations and Secular Trends in Ultraviolet Radiation

Priority: Determine, via tracer and meteorological observations, the residence time and trajectories of air parcels at different altitudes, latitudes, and seasons in the stratosphere, using tracers CO, SF 6 , CFC-11, N 2 O, N 2 , CO 2 , O 3 , NO y , and H 2 O, obtained simultaneously, with spatial resolution of 0.1 km, accuracy of ±2 percent, precision of ±1 percent, and a grid size the same as spatial resolution.

Priority: Determine the mechanisms responsible for exchange of material between the troposphere and stratosphere. Understanding of the exchange of mass and chemical constituents between the stratosphere and troposphere is essential for identifying the relevant chemical processes and relationships among chemistry, dynamics, and radiation that dominate processes in both the stratosphere and the troposphere. Significant progress has occurred in the theory of stratospheretroposphere exchange in the past several years, 13 but this advance has served primarily to clarify what must be done to analyze this key transitional region scientifically and to demonstrate that further progress will depend largely on critical observations, particularly in the tropics. Such observations will require high spatial resolution (0.1 km in horizontal and vertical) simultaneous measurements of H 2 O resolved into its three phases and the isotopes of H 2 O, O 3 , CO 2 , CO, N 2 O, CH 4 , upward- and downward-looking lidar for detection of aerosols and cirrus, the upward and downward radiance in the visible and infrared at 1 cm -1 spectral resolution with the ability to scan the view direction to any angle in the plane perpendicular to the platform velocity vector, solar tracking that allows absorption measurements in the visible and infrared, upward- and downward-looking polarimetry, microwave temperature profiling above and below the platform, and simultaneous observations of meteorological fields and a complete suite of particle measurements. These observations must be focused first in the tropics, using long-duration (24- to 40-hour) trajectories that span the altitude

region from 10 to 22 km, which can lock to surfaces of constant potential temperature (constant entropy) and then to surfaces of maximum gradient in species such as CO observed in real time.

Priority: Determine the destruction rates for ozone in the stratosphere as a function of altitude, latitude, and season by observation of the rate-limiting radicals (NO 2 , NO, HO 2 , OH, CIO, BrO) and determine the response of the atmosphere to imposed changes by obtaining the derivative of each rate-limiting radical with respect to changes in nitrogen, hydrogen, chlorine, bromine, aerosol reactive surface area, water vapor, and temperature through 80 percent of the ozone column (i.e., up to 26 to 28 km). This goal requires simultaneous observations of reservoir species (HONO 2 , N 2 O 2 , ClONO 2 , HCl, H 2 O, BrONO 2 ), long-lived tracers (CO 2 , N 2 O, CH 4 , SF 6 , chlorofluorocarbons [CFCs], CO), ultraviolet fluxes into the volume element observed, infrared radiance and flux, particle number, surface area and mass as a function of size, chemical composition as a function of size, and meteorological variables, including pressure, temperature, wind velocity, potential temperature, and potential vorticity. As described in Chapter 5 , these observations must be obtained with a spatial resolution of 0.1 km, with simultaneous observation of tracers, reservoir species, and ultraviolet flux. It is critical to extend these observations to extreme conditions, such as the polar winter and tropical tropopause. The accuracy of these observations should be ±5 percent for radicals and ±1 percent for tracers. Grid size should be the same as spatial resolution.

Priority: Make observations of the Arctic. In the past five years the loss of ozone in the late-winter/early-spring Arctic vortex has grown rapidly worse, reaching levels of depletion approaching 30 percent in column ozone, as discussed in Chapter 3 . This observed behavior is similar to that of the Antarctic in the early 1980s. Analysis of the cause of this rapid erosion requires high-resolution observations (0.1 km in the horizontal and vertical) between the altitudes of 10 and 25 km of radical and reservoir species (OH, HO 2 , NO, NO 2 NO 2 , Cl, ClO, BrO, ClONO 2 , ClOOCl, HCl, HONO 2 , N 2 O 5 , H 2 O, O 3 ); tracers (CO 2 , CO, N 2 O, CH 4 , CFCs, SF 6 , NO y ); aerosol and particle composition, surface area, and mass as a function of size; spectrally resolved upwelling and downwelling radiation in the ultraviolet, visible, and infrared; continuous absorption measurements in the ultraviolet, visible, and infrared ranges by tracking of the Sun from the platform; and microwave temperature profiling above and below the platform. The trajectories of the experiments are critical. The platform must operate for long durations (24 to 40 hours) in regions of very cold temperatures (down to 170 K) under nighttime conditions and must follow Lagrangian trajectories through the cooling and warming cycles of the volume element on surfaces of constant potential temperature. The data analysis must be executed in real time and used to direct the aircraft trajectory.

Priority: Determine by a combination of laboratory and in situ observations the mechanisms and rates for the homogenous and heterogeneous chemical reactions and the photolysis processes that dictate the rates of chemical transformation in the stratosphere.

Greenhouse Gases Research Imperative

A dominant issue for global change is to characterize the origin, transformation, and removal of infrared active species in the atmosphere, the source molecules for climate change, requiring the following observations.

Priority: Determine the flux of CO 2 from the primary systems (ocean, tropical, temperate, high-latitude terrestrial, Arctic, Antarctic, industrial, agricultural) as a function of season, with spatial resolution of 0.5 km. Grid density is a function of region. Over oceans, ice sheets, and arid regions, resolution should be 50 km in the horizontal, with monthly sampling, except for over the oceans, which should be sampled weekly. Tropical regions should be sampled at 10-km horizontal resolution monthly, except during transition seasons. Industrial regions should be sampled at 5-km horizontal resolution twice monthly. Vertical resolution should be 1 km in all regions.

Priority: Determine the concentrations of CO 2 , CH 4 (including its carbon isotopes), O 2 , and tracers from ground level to the tropopause as a function of latitude, altitude, and season over each of the primary regions of the globe (oceans, jungles, industrial, agricultural, arid, polar, etc.). Measurements should be taken at 30 ground sites worldwide, with accuracy of ±0.25 percent for CO 2 , ±1 ppm for isotopes of CO 2 , and ±0.25 ppm for O 2 . Airborne measurements of CO 2 should be taken for the tropopause, with an accuracy of ±0.5 ppm, at 1 km resolution.

Resolution of these measurements would vary from 1 km in tropical, industrial, and agricultural regions to 5 km over the oceans and arid regions to 10 km over the ice sheets. The vertical resolution required would be 0.1 km throughout, with weekly sampling.

Priority: Pursue a consistent strategy for observations of O 3 from the ground to the lower stratosphere as a function of altitude, season, and characteristic region.

Required resolution of these measurements should be 0.5 km in industrial regions (weekly sampling); 1 km over agricultural regions (generally weekly but monthly during the winter); 1 km over tropical regions (weekly); 5 km over arid regions (monthly); 10 km over the ice sheets (monthly); and 50 km over the oceans (twice monthly). Vertical resolution required would be 1 km throughout. Accuracy of these measurements should be to ±5 percent and precision to ±2 percent.

Priority: Establish the distribution of H 2 O and, through tracers that include the isotopes of water, the mechanisms that control the distribution of H 2 O in the middle to upper troposphere as a function of altitude, season, and characteristic region. These observations should have a spatial resolution of 0.1 km, accuracy of ±5 percent, and precision of ±2 percent.

Horizontal grid scale should be 5 km in the tropics, 10 km in the subtropics, 50 km in the midlatitudes, and 100 km in the high latitudes. Vertical resolution should be 1 km in all regions, with weekly sampling.

Photochemical Oxidants Research Imperative

There are three types of pressing problems about the photochemistry of oxidants in the troposphere. The first is the problem of fundamental oxidation pathways. Critical unanswered questions concern the oxidation of organic compounds to stable products, the oxidation of reduced sulfur to sulfates that are central to acidity and to particle formation and growth, the oxidation of nitrogen compounds to nitrates, the direct oxidation of organisms and subsystems of organisms, and the oxidation of biomass. The second issue is the production of infrared active gases that control the Earth's climate. A significant component of this problem centers on ozone in the troposphere, but because of the coupling between chemical and dynamical time constants in this region, the problem involves other species, such as water in all its phases and isotopes, aerosols (the subject of the fourth research imperative immediately below), methane, and nitrous oxide. Still, a third problem is the control of oxidant export/import across international boundaries, that is, the coupling between regional and global scales. We address the three categories in order.

Oxidation Pathways in the Troposphere

Priority: Establish the sources, photochemical transformations, meteorological control, and deposition of trace oxidants (notably OH, NO 3 , O( 1 ), Cl, O 3 , Br) in various regions of the troposphere (e.g., boundary layer, continental regions, industrial regions, biomass-burning regions, western tropical Pacific, Arctic).

Priority: Analyze the sources, photochemical transformations, meteorology, and deposition of the chemical species that control the relationships among volatile organic compounds (VOCs), NO x , and ozone in the major urban centers of the United States. Obtain simultaneous observations of the moderately long-lived species with a chemical lifetime between 1 hour and 1 year (NO, NO 2 , O 3 , CO, SO 2 , H 2 O 2 , DMS [dimethyl sulfide], HONO 2 , VOCs, peroxyacetylnitrate (PAN), and aerosols), short-lived species (OH, HO 2 , NO 3 , CH 3 O 2 ), long-lived tracers (CH 3 Br, CH 3 CCl 3 , CH 4 , N 2 O, CFCs), and meteorological variables (temperature,

relative humidity, wind speed and direction), with required spatial and temporal coverage. Data on aerosol chemical composition are essential and must include particle carbon, particulate matter, sulfate, organic carbon, and elemental carbon. The requirements for spatial and temporal resolution will be specific to a given urban area because they are a sensitive function of topography and chemical composition, but diurnal data must be routinely secured as a function of altitude from the ground to above the boundary layer, with airborne platforms that are guided by real-time observations and the associated trajectory calculations defining air mass motion and residence times.

Production of Infrared Active Gases that Control Climate

Ozone is recognized to be an important component in the radiative balance of the Earth in the critical region of the tropopause. 14 It is also recognized to be increasing in the upper troposphere 15 and to be strongly linked to photochemical production via hydrogen and nitrogen radicals. 16 The upper troposphere is thus central to the link between the production of infrared gases and climate. From the perspective of scientific strategy, the upper troposphere is ideally suited for critical photochemical experiments because it provides an in situ laboratory with chemistry representative of the troposphere and yet is simple enough to reach closure on a range of experiments testing key hypotheses. There are several regions that should receive particular attention in the selection of trajectories. For example, the region that lies between Africa and Brazil, dominated by biomass-burning products, constitutes a profoundly different source region than the largely pristine region of the western tropical Pacific. The polluted continental regions and their wake regions in the Pacific rim are distinct from the Arctic upper troposphere. It has been clearly demonstrated that using the large dynamic range in species afforded by these regional differences, with the proper complement of tracers and careful real-time analysis of the meteorological fields, provides decisive causal links to be tested and established.

Priority: It is currently hypothesized (1) that ozone is catalytically produced in the upper troposphere via cycles involving radicals in the nitrogen and hydrogen families; (2) that NO x is supplied by organic nitrates (PAN, etc.) and converted to nitric acid on roughly the overturning timescales of the upper troposphere; and (3) that HO x is supplied by photolysis of relatively insoluble organic precursors such as acetone and methyl hydroperoxide. These hypotheses must be tested. Observations are therefore required of the short-lived and catalytically active radicals (OH, HO 2 , CH 3 O 2 , CH 3 C(O)O 2 , NO, NO 2 , and NO 3 ); the precursor species that may also be products (H 2 O, acetone, CH 2 O, CH 3 OO 3 , PAN, CH 4 , and solar ultraviolet spectrally resolved); the product/reservoir species (HOOH, HONO, HONO 2 , HOONO 2 , N 2 O 5 ); the sink species that are also local tracers

(CO, CO 2 ); the lower-tropospheric tracers (ethane, propane, biomass-derived CH 3 Cl, C 2 H 2 , CO, CO 2 , soot, pollution-derived C 2 Cl 4 , CFCs, lightning-derived NO y , aircraft-derived CO 2 , NO y ); and stratospheric tracers (N 2 O, CO 2 , NO y , SF 6 , CFCs, condensation nuclei).

These observations are required with a spatial resolution of 0.1 km in both vertical and horizontal dimensions, over trajectories that scan from sea level to the lower stratosphere. The observations must track specific air masses linking the source regions to the upper-tropospheric domain. This need demands supporting dynamical calculations that set the meteorological context and real-time analysis of the simultaneously obtained data to locate the boundaries of the air mass. This experimental strategy is Lagrangian but also contains an Eulerian component for vertical transections. Companion studies in the laboratory are a critical component of this research. A broad class of both homogeneous and heterogeneous molecular processes must be studied over the temperature range of 150 to 280 K in the 100-to 500-Torr pressure range.

Priority: These observations in the upper troposphere must be extended downward, first to include the midtroposphere and then to tie the analysis to the boundary layer. The observational array shares a great deal in common with that of the upper troposphere/lower stratosphere: observations of the short-lived and catalytically active radicals (OH, HO 2 , CH 3 O 2 , CH 3 C(O)O 2 , NO, NO 2 , and NO 3 ), the precursor species that may also be products (H 2 O, acetone, CH 2 O, CH 3 OO 3 , PAN, CH 4 , and solar ultraviolet spectrally resolved), the product/reservoir species (HOOH, HONO, HONO 2 , HOONO 2 , N 2 O 5 ), and the lower-tropospheric tracers (ethane, propane, biomass-CH 3 Cl, C 2 H 2 , CO, CO 2 , soot, pollution-C 2 Cl 4 , CFCs, lightning-NO y , aircraft-CO 2 , NO y ), stratospheric tracers (N 2 O, CO 2 , NO y , SF 6 , CFCs, condensation nuclei). These observations require a spatial resolution of 0.1 km in both the vertical and the horizontal dimensions, over trajectories that scan from sea level to the lower stratosphere.

Regional-Scale Links Across International Boundaries

International relations are increasingly entangled in disputes over the transfer of airborne pollutants across boundaries, transfers that initiate profound changes in oxidant, aerosol, acidic, and particulate deposition rates as a function of economic development, economic cycle, season, meteorological, and other conditions. These disputes are both acute and complex, involving the coupling of chemical, biological, and physical processes and demanding a high level of scientific proof under legislative or judicial scrutiny.

Priority: The high concentrations of ozone, sulfur, reactive nitrogen, VOCs, soot, PAN, and so forth are created both in focused urban regions and in more

distributed regions (metro-agro-plexes) that depend sensitively on the particular blend of industrial activity, agricultural product, moisture level, temperature, and national and local infrastructure and priorities. The observational requirements are specific for the species and the trajectories, though the specifics may vary for specific national boundaries. The canonical suite of simultaneous in situ observations obtained with 0.1-km resolution is O 3 , NO, NO 2 , OH, VOCs, HONO 2 , HO 2 , CH 3 OCH 3 , PAN, DMS, SO 2 , H 2 SO 4 , HCl, aerosol composition, number, size, and mass as a function of size, and tracers, specifying the region of origin of the air mass.

Aerosol Radiative Forcing and Climate Change Research Imperative

This imperative requires definition of the production and loss mechanisms, distribution, and optical properties of aerosols. Observations must be directed at processes that control aerosols from the fine scale to the global scale. Specifically, observations must clarify the following: (1) mechanisms controlling the rates of production of aerosols from those gases that are relevant to both direct and indirect forcing; (2) processes controlling the evolution of aerosols, including growth, activation to cloud drops, and wet and dry removal; (3) relations between aerosol optical depths and aerosol properties; (4) roles of specific chemical classes of aerosols, such as organics, in direct and indirect forcing; and (5) cloud-activating properties of different classes of ambient aerosols.

The character of scientific analysis in addressing the aerosol problem is critical to achieving progress because of the close but complex linking among chemical, biological, and physical processes. In particular, a critical strategy is to establish the relationship between key dependent variables (such as aerosol light scattering and absorption coefficients, number concentration of cloud condensation nuclei [CCN], etc.) and the major independent variables and then to test that functional dependence over a large dynamic range of variables. This strategy shares much in common with the approach of analyzing the structure of stratospheric ozone photochemistry, taking the form of the systematic analysis of partial derivatives linking dependent and independent variables. The explicit observation of these derivatives, or response function, provided the key evidence that overturned central tenets in ozone chemistry; it is the approach required in the field of aerosol chemistry.

This point is directly addressed in another report, Aerosol Radiative Forcing and Climate Change, 17 which casts the problem in terms of carefully designed “closure experiments”—experiments in which an overdetermined set of observations is obtained, and the measured value of a dependent variable is compared with the value calculated from measured values of the independent variables. This approach requires fundamental restructuring of both the observations and the architecture of the modeling effort. The key point is that, through a sequence of these analyses comparing calculated and observed variables and their associ-

ated derivatives, the fundamental mechanisms hypothesized to control the system can be tested.

Priority: Develop closure experiments with selected temporal and spatial resolution. For example, point measurements of aerosol number concentration and chemical composition as a function of particle size can be used to calculate simultaneously observed aerosol light scattering and absorption coefficients and the number concentration of CCN; and column measurements of the vertical profile of aerosol light scattering and absorption coefficients with simultaneously observed radiative fluxes that can be tested against measurements of aerosol optical thickness of the entire column and aerosol optical properties and with radiative fluxes at the top of the atmosphere. 18

Priority: Pursuit of vertical column experiments that link nadir-viewing satellite observations of spectrally resolved absolute radiance with surfaced-based, column-integrated radiation measurements and in situ observations of aerosol chemical composition as a function of size, spectrally resolved upwelling and downwelling radiance (solar and infrared), light scattering (total and hemispheric backscatter), vertical distributions of aerosol backscattering, and meteorological/ state variables as a function of altitude. 19

Priority: Development of the Lagrangian approach to testing closure between dependent and independent variables, where the observing platform moves with the volume element under analysis. Specifically, the evolution of aerosols in an air mass tagged with inert chemical tracers should be tracked with defined initial conditions, boundary conditions, and reaction rates, with the dependent variables being the time-dependent chemical and microphysical properties of the aerosol particles. Obtain simultaneous in situ observations of deviations of aerosol size, surface area, and chemical composition, SO 2 , DMS (dimethyl sulfide), OCS (carbonyl sulfide), OH, HONO 2 , H 2 O, temperature, infrared and visible radiation field at 1 cm -1 resolution in selected trajectories that define the evolution of aerosols, from the source region to regions characterized by large and small aerosol optical depths, such as biomass burning, pristine, and industrial regions.

Priority: Obtain aerosol fields on a global basis from orbit, including the tropospheric distribution.

Priority: Map the size distribution, phase, and gas-phase environments of liquid/ solid particles in the upper troposphere and lower stratosphere, with simultaneous observations of SO 2 , H 2 SO 4 , DMS, OCS, OH, HONO 2 , NO 2 , NO, H 2 , temperature, and the radiation field, as a function of angle at 1 cm -1 resolution. These observations should be obtained in a Lagrangian reference frame.

Priority: Use multiplatform field campaigns that can effectively span the required dependent and independent variables in question, for example, the link between sources of anthropogenic SO 2 and sulfate aerosol or between organic aerosols and soot from biomass burning and radiative forcing—subjects also addressed by another NRC (1996) report. The oxidation rates and conversion efficiencies of SO 2 should also be observed. The necessary measurements include the following:

SO 2 and H 2 SO 4 , nitrates, soot, organics, and trace metal concentrations.

Photochemically active trace species concentrations.

Short-timescale measurements of both sub- and supermicron nonsea salt sulfate and organics.

Mass size distributions of aerosol chemical species.

Number size distributions from 3 nm to 10 nm in diameter.

Dynamic factors such as entrainment rates, turbulent transport to and from the surface, and mixing depths (see NRC, 1996).

Priority: Marine sulfur chemistry is directly tied to the formation of global-scale aerosol fields. These fields in turn are tied to both planetary albedo in the lower-troposphere boundary layer and the genesis of subvisible cirrus and visible cirrus, which are critical to the trapping of thermal infrared in the middle/upper troposphere. A nested set of hypotheses constitute the foundation of our understanding of marine sulfur chemistry:

Climate is substantially affected by the radiation budget.

The radiation budget is substantially influenced by atmospheric aerosols, both directly by scattering and indirectly by the influence of condensation nuclei on cloud radiative properties.

Aerosols in the marine atmosphere are largely of natural origin.

The source of natural marine aerosol is the oxidation of reduced sulfur species.

DMS is the primary marine-reduced sulfur species.

New particle formation occurs mainly in convective outflow regions above the marine boundary layer (MBL).

DMS is oxidized in the marine atmosphere largely by OH, with a contribution from NO 3 in high NO x environments.

DMS oxidation leads to SO 2 with varying efficiency; SO 2 in turn is oxidized to H 2 SO 4 , which can homogeneously nucleate to form new particles.

While these tenets are plausible, they must be tested to establish the foundation of marine sulfur aerosol chemistry, its coupling to climate, and thus its link to human activity. Critical observations include the following:

Direct spectrally resolved measurements of the flux divergence in the atmosphere, coupled with simultaneous aerosol and condensation nuclei measurements in clear air, cloudy air, and regions of cloud formation.

Observations of new particle formation and identification of the major regions of new particle formation.

Observations of reduced sulfur oxidation, including key intermediates and radical species, demonstrating quantitatively the coupling between DMS and aerosol precursors.

Laboratory observations of the DMS oxidation mechanism, including direct observation of key radical intermediates under the conditions of temperature, pressure, and composition covering the range found in the marine atmosphere. In addition, continued developments in observational technology are critical to advancing the understanding of atmospheric chemistry (see Box 8.2 ).

Paleoclimate

Paleoclimate research over the past several decades has been essential in establishing the context of global changes observed during the course of the instrumental record. It has also pointed to the following research streams.

Research Imperatives

Global changes of the past. Document how the global climate and the Earth's environment have changed in the past and determine the factors that caused the changes. Explore how this knowledge can be applied to understand future climate and environmental change.

Anthropogenic influences. Document how the activities of humans have affected the global environment and climate and determine how these effects can be differentiated from natural variability. Describe what constitutes the natural environment prior to human intervention.

Limits of the global environment. Explore the question of what the natural limits are of the global environment and determine how changes in the boundary conditions for this natural environment are manifested.

Climate forcing factors and controls. Document the important forcing factors that are and will control climate change on societal timescales (season to century). Determine what the causes were of the rapid climate change events and rapid transitions in climate state.

Observational Implications

To pursue these research streams implies several directions for the observational efforts in paleoclimate research. Insights from such records as ice cores, coral bands, and tree rings have led to a number of principles related to observational stategy:

A global array of highly resolved continuous, precisely dated, multivariate paleoclimate records that sample the atmosphere, ocean, cryosphere, and land should be developed. For the identification of environmental change over the past two millennia, annual to decadal resolution will be required and for longer timescales decade-to-century-scale resolution. Continuously sampled and precisely dated records are essential. Tree ring and more recently ice core studies have set a standard of annually resolved dating that should be adhered to wherever possible. Multiproxy paleorecords should be developed wherever possible to maximize interpretations. The primary purpose of this global array should be to specify change over critical regions and during critical periods. For example, a major focus should include investigation of the frequency and extent of rapid

climate change events (millennial to ENSO range) and to identify the controls on them.

Long paleodata series (centennial to millennial scale) should be complemented by spatial arrays of shorter records (decades) to enhance record interpretations and allow differentiation of local versus regional and wider environmental signals.

Integration and detailed calibration of paleodata and observational series will be essential. This approach will allow hindcasting of the relatively short timescale observational series. With coupled instrumental/paleodata series it will be possible to specify the frequency and magnitude of variability for major atmospheric circulation systems (eg., ENSO, North Atlantic Oscillation, North Pacific Oscillation) and extreme events (e.g., droughts, floods).

Paleoclimate and observational series should be coupled with process studies to specify controls on climate behavior. Ground-based and remote observing systems afford a unique tool for studying process. Such studies should be closely integrated with existing observational sites and regions from which valuable paleodata series may be collected. Future ground-based stations and satellite observations should be planned with paleodata in mind.

A clear demonstration of the “natural state of environmental variability” is needed as a baseline for assessing the influence of anthropogenic forcing on climate change. This will require the collection and interpretation of a broad array of paleodata series that capture variability in the physical, chemical, and biological boundary conditions down to regional and in some cases locally specific areas over several timescales.

Human Activities

Social, economic, and health observations are critical to global change research. Because human activities drive and are affected by global change, accurate observation (at different timescales) and understanding of these activities provide critical inputs to various fields of physical, chemical, and biological research on global change, as well as a basis for developing the end-to-end understanding of global change processes needed to inform policy decisions.

Current Uses of Observations of Human Activity

Observations of human activity are already in use in several fields of global change research. An important example is in research on the determinants and consequences of land use and land cover change. This has been designated a core research topic by the IGBP and the International Human Dimensions Programme on Global Environmental Change and was a NASA research initiative in 1998. Most land use research teams are using satellite data to provide biophysical measures of land cover. In addition, ground-based observations of human activ-

ity from a variety of sources are being linked to satellite data. 20 For example, district-level data from the Brazilian population and agricultural censuses are being used to model the causes of deforestation, 21 and combinations of individual-, household-, and village-level longitudinal data are being joined to biophysical data at the village level to study how deforestation in Northeast Thailand is linked to household-level human activities, including migration. 22 Each such research approach makes sense in the context of the region under examination and the substantive questions being addressed, but the diversity of social and economic data makes comparison and aggregation across regions difficult.

Data on agricultural inputs and management (e.g., tillage practices) are important to understanding such global change processes as carbon sequestration in soils. In the United States these data are reported at a county or state scale, so they cannot be reliably matched with spatially referenced soil and climate data in order to model the effects of agricultural practices on carbon sequestration or to examine the determinants of these agricultural practices. More spatially explicit data on the relevant human activities are collected in some European countries but are virtually nonexistent in developing countries.

Data on energy production and consumption have provided a critical input to the past decade of global change research. Detailed annual data on fossil fuel production for all of the countries of the world, developed primarily by the fossil fuel industries, are translated into carbon emissions based on measured and estimated values of energy content and carbon to energy ratios of each fuel. Uncertainty in global estimates of the total annual carbon emissions is estimated to be a few percent, while errors in year to year differences are much smaller. 23

A similar key role is being played by data on the production of CFCs and nitrogen fertilizer and on nitrogen and sulfur oxide emissions in fossil fuel combustion. Many of the human source terms, however, are not well understood. Among these are carbon dioxide emissions associated with natural gas production, leakage rates of methane from the global natural gas production and distribution system, sources of methane arising from animal husbandry and rice cultivation, and sources of atmospheric nitrous oxide arising from managed ecosystems.

As the above examples and others in Chapter 7 indicate, efforts are increasing to link social, economic, and health data to biophysical data to improve understanding of the human dimensions of global change. However, a number of important observational issues must be addressed in the next decade. Some of these are similar to those in the biophysical sciences, and some are unique to human dimensions. This section focuses on those that are unique to human dimensions research, including the lack of involvement in USGCRP participation by key federal agencies, data comparability across political boundaries, georeferencing of social science data, and confidentiality issues that arise with human observations.

Observational Issues for the Next Decade

Usgcrp participation and data on human activities.

In the United States the lead federal agencies involved in collecting domestic social, economic, and health data are the Bureau of the Census, the Department of Education, the Labor Department, the Department of Agriculture, and various branches of the Department of Health and Human Services, such as the Centers for Disease Control and the National Institutes of Health. The U.S. Agency for International Development (USAID) has been the lead U.S. agency funding social data collection in many parts of the developing world. For all of these agencies their primary reasons for collecting social, economic, and health data do not involve issues central to global change research, nor did many of these agencies participate in the USGCRP during the first decade. This disconnect between those responsible for collecting (or funding the collection of) social, economic, and health data and those designing and maintaining global change observational facilities is present in many other countries around the world; the United States is not unique.

One result is that the vast majority of research on the human causes and consequences of global change has used social, economic, and health datasets that were not developed with global change scientific questions in mind. There are exceptions, of course, but the vast majority of scientists working on the human dimensions of global change have had to do the equivalent of repeatedly retrofitting remote sensors. There are numerous examples of scientific ingenuity involved in these efforts, and we anticipate this will continue. However, it is now time to take stock of the situation. Are the present social, economic, and health observational systems adequate for understanding the human dimensions of global change? What are the costs and benefits of bringing the federal agencies responsible for the bulk of the social, economic, and health data into the USGCRP? What human dimensions of global change research needs are not being met by current observational strategies? What is the potential for combining the collection of data on human activities and biophysical processes in the same settings, such as the NSF-funded Long-Term Ecological Research sites? In short, the time is ripe for an end to end review of the current situation and the observational needs for research on the human dimensions of global change.

Data Comparability Across Political Boundaries

Atmospheric and oceanic observational systems tend to impose a common data-gathering protocol across political boundaries, but for many reasons comparability issues often arise with social, economic, and health data. Perhaps the

most obvious is language. With few exceptions, social, economic, and health data are obtained from human beings, using verbal or written communications to convey crucial concepts. As one moves from one language to another, some concepts become easier to convey and some more difficult. If a concept is difficult to convey in a given language, the quality of data collected in that language will be reduced. This is not a matter of poor translations, although that is sometimes an issue. Rather, it is embedded in the structure and nature of language. Since global research on human activities necessarily involves crossing language boundaries (which often overlap with political boundaries), additional effort is required to ensure comparability.

Social, economic, and health data are not collected by a global agency. Rather, they are collected by countries, organizations (such as hospitals or businesses), or by local nongovernmental agencies. To ensure comparability across collecting units, there must be coordination and a willingness on the part of everyone to cooperate. Frequently, local interests and the goal of comparability diverge. In the United States, for example, the collection of such basic demographic data as births and deaths is the responsibility of states, with the National Center for Health Statistics being responsible for coordination. For a variety of state-level reasons, there is variation across states in the collection of various items on birth and death certificates.

Comparability typically increases if one organization is paying for data collection and works to ensure comparability. The experience of the World Fertility Survey (WFS) is instructive. In the 1970s, when global population growth rates were substantially higher than they are today (resulting from substantial mortality declines but lagging fertility declines), an effort was launched to collect and analyze comparable data to further understanding of the determinants of fertility levels and variation. A total of 61 countries completed fertility surveys under the direction and coordination of the International Statistical Institute. The effort was the first attempt to collect global data on such an important issue using survey approaches. Funding for this effort came primarily from USAID, which restricted its use to developing countries. Low-fertility countries were expected to pay for their own surveys, and 20 low-fertility countries participated. The effort in developing countries produced datasets that were remarkably comparable, but comparability in developed countries was inadequate. 24

The implications of the WFS experience need to be carefully considered in the context of global change research. It is now a given that better understanding is needed of the role of human agency in global change, and the word “global” needs to be emphasized. At present, relevant human dimensions data are being collected locally. Sometimes, local data are being used for local case studies; sometimes, local data are aggregated to the global scale, with various forms of imputation for those local areas not providing the relevant data. Both approaches can have problems, and it is time to systematically assess the strengths and weaknesses of the current situation.

Georeferencing Social, Economic, and Health Data

At its core, studying global change requires acknowledgment of the complexity of the global system and linking data across the various subsystems. Geographic information systems (GISs) have been providing an increasingly powerful tool for such linking. 25 Coordinate systems (e.g., longitude and latitude) provide a mechanism for linking across datasets, or GIS layers, that may have been collected at different times or with different observational techniques.

Historically, obtaining precise locational information has not been a high priority for those responsible for collecting social, economic, and health data. Typically, locational data have come under the purview of those responsible for the operational aspects of data collection. For example, census takers need addresses of dwelling units in order to conduct the census. By georeferencing social, economic, and health data, such human dimensions data could be more meaningfully linked to biophysical data. For example, modifying disease statistics (e.g., those supplied by the World Health Organization or the Centers for Disease Control) to include precise observations of spatial (e.g., longitude, latitude, altitude) and temporal (month and season) parameters for geotemporal referencing would allow integration of those observations with other observations of global change. The recent debate on the implications of global warming for the spread of infectious diseases would be resolved scientifically at a quicker pace if such spatial and temporal health data were already available.

Georeferencing social, economic, and health data would involve changes in the manner in which such data are collected and distributed. Some changes might be relatively minor. An example would be releasing the exact geographic boundaries for data that refer to an administrative unit, such as a district or subdistrict. Others will be more challenging, such as knowing the geographical locations where an individual's behavior might have an impact. The human dimensions research community is at a juncture where a careful assessment of georeferencing needs and capabilities is needed. Both costs and consequences need to be assessed. One possible consequence, breaching confidentiality, is addressed below.

Confidentiality Issues in Social, Economic, and Health Data

Data collection from humans often raises issues of confidentiality that may not arise with other global change observational systems. Sometimes confidentiality is protected by law. For example, information collected from specific individuals and households in the U.S. census cannot be publicly released until there is a reasonable expectation that most or all of those who participated in the census are dead. Thus, there is public access to the manuscript forms from the 1890 census but not the 1990 census. Alternatively, sometimes confidentiality is protected by an explicit or implicit agreement between those collecting the data

and those providing the data. Either way, maintaining confidentiality is a characteristic of most social, economic, and health data systems, and without continued provision of confidentiality in human observational systems, the ability to collect human dimensions data would be severely compromised.

Confidentiality is maintained by a variety of mechanisms. One approach is to not make the data publicly available. Another is to strip away all identifying information, including georeferencing information. Yet another is to aggregate to levels sufficient to protect confidentiality beyond a reasonable doubt. Putting precise locational information into public use microdatasets would make it very easy for anyone to know the identity of specific individuals, households, or organizations. It would, in essence, provide a road map. Such activities by U.S. government data agencies would be unacceptable. Yet the scientific case for providing locational information so that human dimensions data can be linked to other global change observational systems is compelling. A careful review is needed to see if the confidentiality of individuals, households, and organizations can be protected while simultaneously advancing the scientific needs of the global research community.

The past decade has witnessed considerable scientific progress in understanding the human dimensions of global change (see Chapter 7 ). A major impediment to progress in understanding of the human causes and consequences of global change is the inadequacy of the observational base for the needed research. The time is now ripe for a systematic assessment of the role and needs for social, economic, and health data in global change research. Such an assessment should pay particular attention to issues of comparability, georeferencing, confidentiality, and relevance. Are current observational systems adequate and, if not, what is needed?

A MULTIPURPOSE, MULTIUSE OBSERVING SYSTEM FOR THE USGCRP: ELEMENTS OF SYSTEM DESIGN

Up to now, the observations taken for the six science areas have not been coordinated among themselves to form a single unified multiuse observing system. Nor has the path been clear from such a multiuse observing system to a permanent global monitoring system. Here, we describe the rationale and process by which an integrated multiuse observational system can be designed to serve the four science areas and explore the problems and opportunities involved in moving to the design and implementation of a permanent global observing system. We begin first with some overarching remarks that set additional constraints on or add information to the system design process.

Style of Observation

An observation can be taken for many different purposes. An exploratory observation is one taken in the spirit of exploration—no firm scientific rationale can be given for it because there are not enough data to make a scientific argument for a measurement. Such observations are very hard to come by (it is almost impossible for an investigator to propose such a measurement), yet all knowledge begins with exploratory measurements and every research program should include them. There are regions of the ocean that have never been measured, as well as parts of the upper atmosphere, and the land surface.

A critical measurement is one that tests a specific hypothesis. While common in particle physics, in which most accelerator experiments are specifically designed to test aspects of the current theory, these measurements are relatively rare in geophysics and even more rarely successful. Contradictory as it may seem, a program of observations can be hypothesis driven, even though a critical measurement may not exist.

A measurement can be made to document the secular change of some relevant climatic quantity, such as global surface temperature or upper-tropospheric humidity, for the purpose of documenting some aspect of global change and for providing the data to compare to models. Such a measurement could be critical if a prediction of such changes has been precise and unambiguous, but this rarely happens in geophysics because it is hardly possible to control the surroundings of a measurement.

Measurements can be taken as part of a forecast-analysis cycle, and these would generally be classified as an operational measurement. These measurements tend to be taken in a regular and systematic manner as input to an ongoing prediction system. While not performed (or funded) as research, such measurements can be extremely valuable since they make available to the research community observations that could (or would) not be supported through research—the upper-air observing network is a good example of this.

Some measurements are taken mainly to validate other measurements. Examples are measurements of SST from drifting buoys taken to calibrate the operational AVHRR satellite measurements of surface radiance. Because the satellite measurements are subject to cloud obscurations and are affected by aerosols in the atmosphere, which are not carefully measured, the in situ measurement of SST provides an absolute measure from which the satellites can derive global SST on a regular basis.

Some measurements are taken in a regular and systematic manner and, while serving the purpose for which they are taken, do not have the accuracy or reliability for some different purpose. An example is the upper-air network, which by itself has been incapable of documenting small temperature changes in the upper atmosphere. Increasing the accuracy or reliability of such measurements leaves

them acceptable for their original purpose while making them useful for a different purpose.

Finally, there are proxy measurements of climate, usually from remnants of organic or inorganic materials stored in isolated natural formations, preserving records of past climates. Examples are deep-sea sediment cores, coral cores, ice cores, boreholes, and materials from old packrat middens. These kinds of records require great care in application to produce a record of physical quantities—a record that is often hard to interpret because the records (may) represent a single site but are invaluable because of the window they provide to the past.

Research Observations and Operational Observations

An operational system is one that is put in place to fulfill a specific societal purpose, generally requiring the regular and systematic delivery of a product in a specified cycle that has time constraints on its delivery. The purpose of the operational system may be the most commonly recognized one—weather prediction—or it may be for security (both civilian and military), resource discovery and management, disaster discovery and management (e.g., for fires and earthquakes), or various other commercial or societal purposes (the stock market ticker is a rapid operational measurement; the decennial census is a slow one). The measurement part of the system can be sited on a single platform or facility (e.g., a satellite), an aggregation of platforms (the upper-air rawinsonde network or the oceanic mooring array), or a complex combination of both.

A research measurement is usually designed to answer a specific scientific question and is usually finite in duration. What distinguishes an operational measurement from a research measurement is the absolute operational need to deliver a measurement regularly in a given time. This requirement has a number of consequences: there must be redundancy in the system in case a link or platform fails; there must be ongoing calibration, since the observation is to be used continually as part of a system and the consequences of incorrect information are serious; and there are changes in the system only as an improvement in response to the purpose for which it is taken. There can also be less emphasis on the longer-term absolute accuracy because forecasts may be based on relative accuracy or simply not require as great an accuracy of measurement as certain scientific measurements might demand. This tension or difference in purpose can be seen in the measurement program for weather forecasting versus the issue of detecting climate change.

Nature of an Observing System

An observing system consists of an architecture composed of various observational components and the interfaces connecting them. The design of the system reflects its purpose, the resources required to fulfill that purpose, and the

resources available to implement the system. The design of the observing system is established by its users to maximize the system's utility in accomplishing the various purposes of its users. The system may be subject to various constraints, the most common being cost.

The purpose of the observing system may be unique, satisfying the needs of a single user or having the same purpose for a number of users. In the latter case (a single-purpose multiuser observing system), the design, implementation, and evaluation of the observing system proceed according to a common objective requiring cooperation among the users for funding and management but not requiring tradeoffs depending on differing objectives.

An observing system having multiple purposes is much more complex, generally requiring a cyclic design-implementation-evaluation procedure. This procedure only makes sense when the observing system is to be in place for long periods of time, so that a number of repetitions of the cycle can take place. The USGCRP has a set of scientific challenges; it has monitoring requirements with multiple-agency participation, and a research enterprise involving hundreds of university, government, and private-industry scientists—any observing system it puts into place is clearly a multipurpose, multiple-user observing system.

Design of an Observing System

The purpose of designing a system, rather than simply letting it grow haphazardly, is to optimize its utility among the users and minimize its cost—most likely some combination of the two. The complexity of the design increases as the objectives and number of users increase. Without such a design, it is likely that large amounts of money will be invested in taking observations, with no guarantee that the research objectives of the USGCRP are fulfilled or that the community of users feels satisfied in having their needs respected. The observing system needed to satisfy the stated aim of the USGCRP for monitoring is an even more difficult problem because the timescale of monitoring is effectively infinite: the monitoring system is to be considered a permanent observing system. To optimize the scientific utility of the observations needed by the many participants in the USGCRP, a rational process should be undertaken—the system design of a multiuser, multipurpose observing system.

A central aim in the design process is to achieve “maximum” scientific utility, subject to the inevitable constraints of funding, while being responsive to other demands for observations. The penalties for failing to design such a system are the loss of public trust; excessive costs and fragmentation of the observations that are taken; loss of vision of the scientific enterprise seeking to solve deeply interrelated problems; and, ultimately, scientific opportunities missed by the lack of cooperation among the different science areas. If there is one thing that a system design does ensure it is cooperation: every stage of a system design requires cooperation among scientists, engineers, and funding agencies.

The elements of a system design process are as follows:

Determine the quantities needed based on the scientific research objectives of the USGCRP. The quantities to be measured for the science areas of the USGCRP must be identified, and the accuracies to which they must be measured must be stated in terms of the scientific questions and objectives. A specific scientific rationale must be given for each measurement proposed, so that the scientific importance of the measurements can be recognized. All of the scientific users must be represented in this process and their needs evaluated on the basis of scientific priorities alone.

Conduct a system engineering design study based on the scientific requirements of all users. The possible instruments, platforms, strategies, and architectures for the system should be identified and the commonalties and conflicts among the users analyzed, using a consistent set of scientific criteria based on the scientific rationale presented by the users. The engineering design must take into account the possibilities of improved or lower-cost instruments and platforms over the lifetime of the observing system. The final design must ensure that the totality of the observations does indeed respond to the totality of the scientific needs.

Develop an implementation process and priorities based on the engineering design and the practicalities imposed. Once the engineering design is completed, the next step is beginning a consistent implementation process, consisting of the assignment and acceptance of responsibilities for the different parts of the system, a set of priorities by which the different parties can make implementation decisions, a set of incentives and disincentives for encouraging successful performance and punishing poor performance, and a management or coordination structure whereby the entire process is kept moving and decisions can be made. The implementation process is subject to practical constraints. Practicalities can be imposed externally (funding, infrastructure) or internally (lack of vision, aversion to cooperation), but only players not subject to internal constraints should be players in the implementation process.

Appraise how well the implemented system meets scientific objectives in its actual performance. A set of performance measures and evaluation criteria should be decided on in advance. Evaluation of the observing system must be carried out with reference to how the actual observing system as deployed meets the objectives of the science areas, subject to the practical constraints imposed on the system.

Changes should be considered in the implemented observing system reluctantly and only under well-defined circumstances. The reasons for changing a research observing system are that the original system is not meeting its design

criteria, that newer and better technologies make some components obsolete, that scientific problems get solved to such an extent that the full suite of measurements originally proposed is no longer needed, or that new opportunities present themselves.

CASE STUDIES

Some perspective on the nature of multiuse observing systems can be gained by examination of the history of monitoring several crucial global change variables. While there have been some notable successes in long-term monitoring, such as the flask sampling network for CO 2 and other greenhouse gases, there are also examples of disappointing results in trying to obtain long-term consistent climate records. Two cases are examined here—that of the monitoring of solar output by satellite and that of recording cloudiness over the United States.

Solar Output

The ultimate source of energy for the entire climate system is the output of energy from the Sun. While the mean solar irradiance at the position of the Earth is about 1,367 W/m 2 , the output of the Sun is variable over both long and short timescales. Much of the short-term variability is in the ultraviolet and is strongly absorbed by ozone in the stratosphere. This directly affects the temperature of the stratosphere, which in turn affects the rates of the chemical reactions that determine the concentration of ozone. Other parts of the spectrum are absorbed lower in the atmosphere by clouds, aerosols (both sulfate and carbonaceous), water vapor, and other minor constituents. Because the variability of these constituents affects the solar beam as it traverses the atmosphere, only by measuring the solar constant at the top of the atmosphere can the solar beam 's true variability be known.

On longer timescales—say, over an 11-year sunspot cycle—the variability in the solar constant is on the order of 1 W/m 2 . On still longer timescales, the variability in the solar constant can be as large as 4 to 5 W/m 2 , as gauged by comparison to other Sun-like stars, which translates to less than 1 W/m 2 at the top of the atmosphere (irradiance must be multiplied by albedo and divided by four, since the area of the Earth is one-quarter the intercepted disc). The effect of such variability on the Earth's climate is not completely known, but if the sensitivity to radiative variations at the tropopause is 1.5 to 4.5 K for a 4 W/m 2 change (corresponding to a doubling of CO 2 ), variations on the order of a few tenths of a degree of global temperature can be forced by solar output variations on decadal timescales. Because globally averaged temperature is of this order, one cannot exclude the possibility that solar variability is the cause of decadal climate variations. Precise long-term measurement of the solar constant, accurate to 1 W/m 2 or less, is essential for testing this hypothesis. The case for accurate long-term measurements of the solar output is overwhelming and has been argued for by the

USGCRP and by every major intemational climate program. For example, an NRC panel 26 recently gave as its prime recommendation: “Monitor the total and spectral solar irradiance from an uninterrupted, overlapping series of spacecraft radiometers employing in-flight sensitivity tracking.”

In commenting on this recommendation, the report provided the following illuminating discussion:

This primary recommendation is particularly challenging and probably will not be achieved because of the dearth of access to space. A series of small spacecraft dedicated to solar monitoring could provide the necessary data. Overlapping observations are required to cross-calibrate measurements by different instruments whose inaccuracies typically exceed the true solar variability. Simultaneous observations from different instruments provide important validation that real variability, rather than instrumental degradation, is being measured and provide the redundancy needed to preserve the database in the case of instrument failure. Improved radiometric long-term precision and calibration accuracies would contribute to a more reliable solar forcing record. In lieu of spacecraft dedicated to solar monitoring, it may be possible to use NOAA or Defense Meteorlogical Satellite Program (DMSP) operational satellites, for which overlapping is a feature of the design. 27

Figure 8.1 shows the current state of long-term measurements of the solar constant by satellite. Clearly, the measurement error between satellite instruments is far greater than what is needed. Commitments simply have not been made to the continuity and calibration of a series of measurements that scientists deem essential to understanding of long-term climate change.

Long-Term Variations and Changes of Clouds in the United States

Few elements of the atmosphere are more fundamental to understanding climate and its impacts on ecosystems and human systems than cloud amount and height. The specification of cloud cover is one of the most sensitive parameters in general circulation models, which are used to study climate. The legacy of measuring and reporting cloud frequency and height during the twentieth century is inconsistent with the importance of this fundamental element of the climate system.

Prior to the advent of commercial aviation, cloud amount was reported at least twice daily at several hundred NWS offices throughout the country. In these reports, observers were instructed to summarize the state of cloud amount during the night (sunrise observations) or the day (sunset observations). Most of the stations also had a sunshine switch that measured the amount of direct sunshine, 28 enabling scientists to detect any systematic biases between the two measurements. The advent of commercial aviation, however, required observers to ob-

FIGURE 8.1 Total solar irradiance measurements, 1978 to 1996. Daily mean values and uncertainties shown for the Earth Radiation Budget (ERB), Earth Radiation Budget Satellite (ERBS), and Active Cavity Radiometer Irradiance Monitor (ACRIM) I and II experiments. SOURCE: Willson (1997). Courtesy of the American Association for the Advancement of Science.

serve cloud amount, type, and height of cloud bases each hour of the day. It is shown that during this transition more clouds were observed relative to the sunshine instrument, 29 suggesting that observers noted more clouds when they were required to search the skies each hour, compared with summarizing cloud amount during the previous 12 hours. Simultaneous with the hourly reports, the observers often moved from city offices to airport locations. At some locations a city office remained open, enabling cross-comparisons of cloud reports. During the time of rapid transition of stations to airport locations, a new sunshine recorder was introduced, with substantially different characteristics than the previous instrument, 30 thereby making it more difficult to quantify the effect of station relocations and changes in observing procedures.

At the outset of the USGCRP, another major change in cloud observing occurred. Automated lidar measurements were replacing human observers. These automated measurements were unable to detect clouds above 12,000 feet, which introduced a major discontinuity in the cloud observing network. A potential solution was to use geostationary satellites to detect clouds above 12,000 feet. Although methods were developed to identify broad categories of cloud amount—

such as clear, scattered, broken, and overcast—these categories were much broader than those typically reported by human observers. Moreover, the combination of automated lidar reports and geostationary satellite estimates indicated fewer overcast and more clear conditions compared with human observers. This result may have been overcome with appropriate transfer functions, but the cloud algorithm from the geostationary methods depended on an NWS “first guess” field of their operational model. A major change in this model produced still another bias in the record.

At this time, there is no suitable replacement for human observations of cloud amount at the several hundred sites across North America that had been reporting cloud amount and height for many decades. In response, the NWS has made an effort to continue both manual and automated cloud measurements at a selected number of stations for an indefinite period. Unfortunately, these cloud reports appear in a supplementary coded field message and are often missing.

Conclusions from Case Studies

As the above case studies demonstrate, there are a number of instances in which observing systems have faltered in delivering a consistent and calibrated record of global change. There are also some indications that many of the same problems may continue to appear in both ground-based and satellite observations relied on by virtually all of the science elements. For example, support for NOAA's Cooperative Observing Network, which is the basis for many of the longest surface temperature and precipitation records, continues to be a matter of concern. It also appears increasingly likely, based on current plans, that there will be a substantial gap between the end of the EOS PM-1 mission and the launch of the NPOESS. Such a gap would lead to data omissions and offsets in many of the data streams important for global change.

TOWARD A PERMANENT OBSERVING SYSTEM

Clearly, the USGCRP has the responsibility to observe, document, understand, and predict, to the extent possible, future changes in the global environment. The demonstration of, for example, secular trends in the Earth's climate requires analysis at the forefront of science and statistical analysis. Model predictions have been available for decades, but a clear demonstration of the validity of such predictions—a demonstration that would convince a reasonable critic on cross-examination—is not yet available. This lack is not in itself either a statement of failure or a significant surprise. It is, however, a measure of the intellectual depth of the problem and the need for carefully orchestrated long-term observations. The requirements for accuracy, continuity, calibration, in-flight standards, documentation, and technological innovation of long-term trend analysis are elsewhere described 31 and are endorsed by this report. See Box 8.3 for a summary of

observational issues raised over a number of years in other NRC reports. While a complete discussion of observing selected variables is given in a collection of papers, 32 we extract 10 principles that have emerged to provide the guiding considerations that underlie the USGCRP's responsibility for observing, documenting, and understanding global climate change.

Principles of Long-Term Climate Monitoring

The effects on the climate record of changes in instruments, observing practices, observation locations, sampling rates, and so forth must be known prior to implementing the changes. This information can be ascertained through a period of overlapping measurements between old and new observing systems or sometimes by comparing the old and new observing systems with a reference standard. Site stability for in situ measurements, in terms of both physical location and changes in the nearby environment, should also be a key criterion in site selection. Thus, many synoptic network stations, primarily used in weather forecasting

but that provide valuable climate data, together with all dedicated climatological stations intended to be operational for extended periods, must be subject to such a policy.

The processing algorithms and changes in these algorithms must be well documented. Documentation of these changes should be carried along with the data throughout the data-archiving process.

Knowledge of instrument, station, and/or platform history is essential for data interpretation and use. Changes in instrument sampling time, local environmental conditions for in situ measurements, and any other factors pertinent to the interpretation of observations and measurements should be recorded as a mandatory part of the observing routine and archived with the original data.

In situ and other observations with a long uninterrupted record should be maintained. Every effort should be applied to protect the datasets that have provided long-term homogeneous observations. “Long term” with regard to space-based measurements is measured in decades, but for more conventional measurements long term may be a century or more. Each element of the observation system should develop a list of prioritized sites or observations based on their contribution to long-term monitoring.

Calibration, validation, and maintenance facilities are a critical requirement for long-term climatic datasets. Climate record homogeneity must be routinely assessed, and corrective action must become part of the archived record.

Wherever feasible, some level of “low technology” backup to “high-technology” observing systems should be developed to safeguard against unexpected operational failures.

Data-poor regions, those variables and regions that are sensitive to change, and key measurements with inadequate spatial and temporal resolution should be given the highest priority in the design and implementation of new climate observing systems.

Network designers and instrument engineers must be provided with long-term climate requirements at the outset of network design. This step is particularly important because most observing systems have been designed for purposes other than long-term climate monitoring. Instruments must have adequate accuracy, with biases small enough to document climate variations and changes.

Much of the development of new observational capabilities, as well as much of the evidence supporting the value of those observations, stems from research-oriented needs or programs. The lack of stable long-term commitment to these observations and the lack of a clear transition plan from research to operations are two frequent limitations in the development of adequate long-term monitoring capabilities. The difficulties of

securing a long-term commitment must be overcome if the climate observing system is to be improved in a timely manner with minimum interruption.

Data management systems that facilitate access, use, and interpretation are essential. Mechanisms that facilitate user access (directories, catalogs, browse capabilities, availability of metadata on station histories, algorithm accessibility and documentation, etc.) and quality control should guide data management. International cooperation is critical for successful management of data used to monitor long-term climate change and variability.

The remainder of this section concentrates on the transition from a research-focused observing system to a permanent operational component within the observing system of the USGCRP for global environmental monitoring. This transition is an essential objective for the next decade of the USGCRP. a Some of the considerations below are relevant to all observing systems, whether space based or in situ, and are independent of platform. However, there is a particular challenge—the transition from the NASA polar platform series to the NOAA NPOESS series—that raises certain unique challenges that must be recognized.

The Essential Transition: From Research to Long-Term Monitoring

A monitoring system is needed to detect secular change in the global environment. Even for research purposes alone, the system must be in place long enough to see a few cycles of the changes. For the dec-cen and biogeochemical components of the USGCRP, this implies an observational system with a very long lifetime. Moreover, from an operational point of view of tracking changes in the environmental state of our planet, a system is needed essentially for the duration of the perturbations and responses. Obviously, such a multipurpose monitoring system would fulfill important research needs; however, its cost is likely to be significant, particularly when integral costs are considered and not just annual costs. Therefore, it must satisfy operational purposes if it is to be sustained. An essential shift is needed within the federal government: the federal government must recognize that monitoring the changes in the global environment on significantly longer timescales than demanded by operational meteorology is in the forefront of the national interest.

For an observing system to be permanent, then, it must have some operational requirement. While in theory it is conceivable that some agency will adopt the rigors of accepting climate monitoring as an operational requirement, in

practice the monitoring of climate variability is not currently an operational requirement of the USGCRP nor is there an agency of the U.S. government that accepts climate monitoring as an operational requirement and is committed to it as a goal. The current designs for a global observing system by the GCOS and the Global Ocean Observing System 33 seem unattainable in practice because of the lack of such an operational mandate for any existing agency or the USGCRP.

The prospects for a permanent observing system therefore seem to rest on three possibilities:

The USGCRP accepts environmental global change-focused monitoring as an operational necessity and makes the institutional changes needed to enforce the discipline that operational requirements demand.

A new coordinating mechanism is created that has operational climate monitoring as a founding requirement.

The permanent observing system is built using a quite different paradigm —that of coherence and evolution.

This paradigm sees individual components of the observing system growing out of research but being shifted into operations, each for its own purpose. As the system evolves, different parts of it may be operationalized for entirely different reasons. Thus, some parts of the ocean may be monitored for seasonal to interannual prediction, some for fish management, some for fish detection, some for pollution detection, and so on. The evolution process may take many years and only at some time in the future will it be appropriate to see what capabilities it has and what incremental measurements are needed to go from a congeries of individual measurements to an ocean observing system.

One of the difficulties in implementing the new paradigm is the necessity of converting research funding to operational funding. A research program can maintain a permanent observing system only when the system is relatively cheap and does not inhibit other research objectives. When there is an operational need for a system, funding must not come from research sources, else the building of a permanent observing system could gradually impoverish the research enterprise.

The paradigm still requires an institutional commitment to coordinate the various elements into the ultimate observing system, but it postpones the need for coordinated funding and thus allows (but does not guarantee) the coordination to evolve over the many years that would undoubtedly be required for this to occur. If we evolve the needed observational system as recommended, a system design study still will be needed. b There is a danger that without careful planning the system might contain a collection of instruments that do not together yield an adequate observing system to the scientific challenges, particularly those on the

longer-term issues like ecosystems and climate from decades to centuries. A system design will give at least one measure of what is needed and, importantly, what is not.

A key issue that initializes both the system design and beginning the evolution process is the current and forthcoming satellite research missions: the EOS AM-1 and EOS PM-1 NASA polar platforms, the Advanced Earth Observing Satellite platforms from Japan, and the current ERS-1, ERS-2, and the future ENVISAT polar platforms from Europe as well as several more specialized research missions (e.g., TOPEX-Poseidon [Ocean Topography Experiment], TRMM, and the future Earth System Science Pathfinders). Another force on the process is the convergence discussions in which NOAA and the U.S. Department of Defense (DoD) (the Air Force) are converging the current Television and Infrared Observation Satellite (TIROS) and Defense Meteorological Satellite Program (DMSP) systems, respectively, in which they will go from a four platform system in sun-synchronous orbits (equatorial crossings at early morning, midmorning, and two in the afternoon) to a two-platform system (an early morning and an afternoon equatorial crossing). This is the planned NPOESS. Taking over the important midmorning slot will be the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) with its meteorological operational (METOP) polar platform.

There are several difficulties in going from the research missions to the operational missions.

The current phasing of the EOS AM-1 and EOS PM-1 and the NPOESS schedule produces a potentially significant observational gap. This gap is currently increasing because of the longevity and reliability of the current assets (e.g., the TIROS and DMSP systems on orbit and in construction). What is to be done to appropriately fill the gap is not clear.

The linkage between EOS AM-1 and the METOP midmorning platform of EUMETSAT is even murkier than that between NASA and the U.S. operational satellite agencies (NOAA and DOD).

It is crucial for global change research and monitoring that future operational satellites should, to the extent practical, have the qualities necessary for global change science identified in this report. To resolve these difficulties and move onto a course that is sustainable and meets the long-term observational challenge posed by global change will require political courage and strong and continued leadership by all parties. It will not be easy; it is, however, essential.

1. Karl et al. (1995a).

2. Sellers et al. (1997), Fung et al. (1987), Myneni et al. (1997), Potter et al. (1993), Randerson et al. (1997), Braswell et al. (1997).

3. Braswell et al. (1997), Myneni et al. (1997).

4. Skole and Tucker (1993).

5. Wessman et al. (1998).

6. Martin and Aber (1997).

7. Aber and Federer (1991).

8. Vitousek et al. (1997), Braswell et al. (1997).

9. Wahl et al. (1995).

10. Kanciruk (1997).

11. Vörösmarty et al. (1996).

12. Rasmussen and Carpenter (1982).

13. E.g., Holton et al. (1995).

14. See Intergovernmental Panel on Climate Change (1995).

15. See Logan (1994).

16. See Wennberg et al. (1998).

17. National Research Council (1996).

19. Ibid., Russell et al. (1994).

20. National Research Council (1998b).

21. Wood and Skole (1998).

22. Entwistle et al. (1998).

23. Marland and Boden (1997).

24. Cleland and Scott (1987).

25. National Research Council (1997).

26. National Research Council (1994a).

28. Karl and Steurer (1990).

30. Quinlan (1985).

31. Karl et al. (1995a).

32. Karl et al. (1995b).

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How can we understand and rise to the environmental challenges of global change? One clear answer is to understand the science of global change, not solely in terms of the processes that control changes in climate and the composition of the atmosphere, but in how ecosystems and human society interact with these changes. In the last two decades of the twentieth century, a number of such research efforts—supported by computer and satellite technology—have been launched. Yet many opportunities for integration remain unexploited, and many fundamental questions remain about the earth's capacity to support a growing human population.

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• Research imperatives and strategies for investigators in the areas of atmospheric chemistry, climate, ecosystem studies, and human dimensions of global change.
• The context of climate change, including lessons to be gleaned from paleoclimatology.
• Human responses to—and forcing of—projected global change.

This book offers a comprehensive overview of global change research to date and provides a framework for answering urgent questions.

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• Published: 25 August 2022

Structured output methods and environmental issues: perspectives on co-created bottom-up and ‘sideways’ science

• Richard Taylor   ORCID: orcid.org/0000-0002-3915-2920 1 ,
• John Forrester   ORCID: orcid.org/0000-0001-7231-113X 1 ,
• Lydia Pedoth   ORCID: orcid.org/0000-0001-5429-687X 2 &
• David Zeitlyn   ORCID: orcid.org/0000-0001-5853-7351 3  

Humanities and Social Sciences Communications volume  9 , Article number:  292 ( 2022 ) Cite this article

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Participatory methods for researching human–environmental interactions seek detailed inputs on all manner of issues, but the outputs are often only understandable to the technically literate. On the other hand, participatory methods that involve the co-design of structured outputs (maps, models, games, stories, etc.) can be used to represent and integrate the knowledge and views of participants authentically and can be interpretable to both ‘scientist’ and ‘non-scientist’ alike, thereby creating ‘sideways’ rather than top-down or bottom-up perspectives. This paper is both a methodological paper and a treatise that looks at some of the theory underpinning such approaches, drawing on the theory of citizen or ‘bottom-up’ stakeholder engagement in science but also co-created engagement, emphasising the learning and trust-building benefits of this ‘sideways’ engagement. It describes how some established and novel methods (participatory agent-based modelling; co-constructing computer games; and participatory social network mapping), can be used to engage stakeholders in iterative, constructivist communication, allowing researchers and stakeholders to co-create a structured ‘reality’ separate from the reality it represents. We discuss how such approaches support and contribute to scientific outputs that better represent participants’ reality. Our findings show that, when applied to ecosystem services, agricultural adaptation and disaster risk management, such representations provide communication opportunities and spaces for reflection and constructivist learning. The structured outputs allow stakeholders—both participant and researcher—to ‘mirror’ their human-environmental system to collaboratively think about gaps and problems in understanding.

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Negotiating the ethical-political dimensions of research methods: a key competency in mixed methods, inter- and transdisciplinary, and co-production research

Co-creation in citizen social science: the research forum as a methodological foundation for communication and participation

Participatory action research

Introduction.

Theorists of the public engagement with scientific matters have long emphasised both complexity (Gregory and Miller, 1998 : passim ) and the need for participation (Fuller, 1997 ). Others deal with the politics of what is going on in such interactions in a wide-ranging manner (Fischer, 2000 ) or the high-level analysis of tensions between theoretical ideals and practical considerations such as provided by Delgado et al. ( 2011 ), who analyse approaches to public engagement in nanotechnology. The science of the environment, and its governance, is both complicated and complex: by ‘science’ we just mean knowledge (for example, Ziman, 2000 ); while ‘complicated’ simply refers to many possibilities within the system, and ‘complexity’ here relates specifically to issues such as non-linearity, feedback, and the possibility of unintended consequences (for example, Ramalingam et al., 2008 ), thus better understanding of the scientific issues and their interactions with their constituency—that is the environment itself but also the people who live in and manage that environment—is required. Public policy analysts have referred to these types of issue and their associated problems as “messy” (Ackoff, 1974 ); “wicked” (Rittel and Webber, 1973 ; McConnell, 2018 ); or even “super wicked” (Levin et al., 2012 ; Forrester et al., 2019a ). They also emphasised that a plurality of parties is invested in these problems, being “equally equipped, interested, and/or entitled to judge the solutions” (Rittel and Webber, 1973 ). Other analysts focus on the greater need for pluralistic ‘peer-review’ of science knowledge and have advocated wider stakeholder engagement under conditions of “post-normal science” (Funtowicz and Ravetz, 1991 ; Kasemir et al., 2003 ; Andersson et al., 2010 ). This has also on occasion resulted in participatory exercises where ‘bottom-up’ analyses are cast almost as a critique of the scientific hegemony (Potts, 2004 ; Wynne, 1996 ; Yearley, 2000 ). These analyses also further unpack the relationship of the public or citizen stakeholder (i.e., participants whose primary stake is through being a local resident and knowledge-stakeholder) with and in the production of science.

On the other hand, Rodela et al. ( 2012 ) find limited evidence of the involvement of stakeholders in empirical research on social learning in environmental management contexts. They also find that researchers tend not to disclose ontological positions that guide methodological choices. Moreover, researchers frequently move between more than one theoretical or philosophical perspective (Rodela et al., 2012 ). Different methods might also be creatively combined under different ontological and epistemological positions (Barbrook-Johnson and Carrick, 2021 ). We suspect that this is increasingly the case in participatory research into human-environmental issues (given the diversity of aims and methods employed—see Moon and Blackman, 2014 ).

In this context, we believe that there is a pressing need for not just better methodologies for better public engagement but also for a better social science understanding of the theory behind such methodologies: what is the legitimacy of citizen involvement in creating better understanding and how can it be improved. We ask: How do social science theories about interaction, communication and learning between researchers and stakeholders help deepen understanding of practices and methods of participatory engagement, and how can the co-designed outputs help create better science-informed communication? This paper is both a methodological paper and a treatise that examines theory connected to methodology, and thus there are both “what” and “how” research questions.

Our work was originally conceived of as a method to bring about a more active scientific citizenship as a critique of scientific hegemony (Irwin, 1995 ; Forrester, 1999 ). In this paper we show how this can be achieved through adaptation of formal methods of representation (maps, models, games—the detailed expressions of which can only be understood by experts) to make them more useful to others—such that a non-expert could recognise in them the complex and messy realities of environmental issues and their problems. Structured output methods involve individual and group exercises where participants engage with co-created outputs to represent and elaborate their views, ideas and beliefs and hence learn together. They are not focus group exercises, interactive workshops, policy dialogues or other meetings that involve consultation or discussion on policies or planning decisions.

The structured output delineates a system that is the subject of the investigation. A minimum requirement for a structured output is that there is an output, which stands alone or apart from that which is being described. Participants are experts and other knowledge stakeholders (often bridging different types of evidence). The perception of and commitment to such an exercise likely depends on the legitimacy of the actor who invites the participants to join (Voinov and Bousquet, 2010 ). Thus, the initiation and early engagement is important for the later credibility of a process that aims “to build more equity and confidence in a heterogeneous group of people by providing a framework to share knowledge, cultural and traditional principles, access to power and status, ability to communicate and interact” (ibid). We present three examples of structured outputs in this paper. The paper is not, however, a report of those projects but rather a treatise on how and why these approaches are and can be used. We argue that such representations provide communication opportunities, and that our work contributes to the literature on science-informed communication, including that pertaining to environmental risks.

Risk managers and planners face increasingly complex problems (including wickedness and messiness) and difficult choices. Participatory research approaches can help support transdisciplinary/post-normal knowledge production and facilitate useful communication processes in situations where scientific expertise has no hegemony: that is where science advice—and other policy discourses—are necessary voices, but not the only voice. Such situations involve human agency and ‘the environment’ and can be observed as the interaction between stakeholders or agents and some other ‘actor’ in the widest Latourian sense (Latour, 2005 ), but also through “observable events and interactions between people and objects” (Zeitlyn and Just, 2014 , p. 9). This includes understanding the process of communication (for example, Fuller, 1997 ; Jensen and Holliman, 2009 ) and the interplay between communication, participation, and policy (Collier & Toomey, 1997 , 175 ff ).

Participatory methods that produce structured outputs not only generate new empirical evidence, but also allow participants to become better aware of their own context. They allow the creation of a space for reflection, which can help ameliorate the sometimes confrontational nature of some participatory processes, by focusing attention on the created object (i.e., the structured output). Further, the use of a drawn output (for example, Cinderby and Forrester, 2005 ; Forrester et al., 2015 ) creates a clear common language often less prone to ambiguity. Furthermore, the use of such structured outputs also helps to unpick and ‘map’ some of the mess surrounding common human–environmental issues, exploring the range and diversity of beliefs not only of citizen public but also of the officials representing statutory and governmental agencies. Yet, there is a need to better understand how different participatory research methods can support communication and learn about such underlying beliefs, all of which contribute to complexity and wickedness.

The methodologies we are concerned with produce structured outputs that can function as boundary objects. These are entities “shared by several different communities but viewed or used differently by each of them” (Star, 1989 ). Such objects have “different meanings in different social worlds but their structure is common enough to more than one world to make them recognisable, a means of translation” (Star and Griesemer, 1989 ). Use of structured outputs of participatory processes as boundary objects helps avoid the problem of having to “infer what must be in their minds” (Bailey, 1991 , p. xiv). Their use can operate as a common language to facilitate translation across and between social domains. Further, a boundary object such as a highly structured output can help move the model/created understanding away from being ‘simply’ a metaphor (Ravetz, 2003 ) for the real world with the concomitant problems such may bring (Norgaard, 2010 ). It does this by maintaining a recognised link to known and lived realities on the part of those drawing the object—that is the stakeholders/participants. Furthermore, such ‘structured outputs’ have the virtue of apparent precision and through that precision can be used to clarify understandings that are not easily observable empirically, and are otherwise difficult to elicit (Forrester et al., 2014 ; Taylor et al., 2014 ; Forrester et al., 2015 ; Matin et al., 2015 ). Thus, communication is facilitated not only through interaction of stakeholders with different understandings but between the stakeholders and the tool of investigation , the structured output (see also Forrester et al., 2019b ). We argue that this communication would not have taken place to the same degree or at all if these types of approaches had not been employed. The boundary object—if it is representing citizens’ own knowledge—also provides a re-framing of what are sometimes otherwise disempowered voices, can help build trust and understanding between different stakeholders.

Methodology

This paper shows how three differing methodologies producing structured outputs have been used, appraises their contribution to participatory projects, and then relates these practical experiences to the relevant theory (about interaction, communication and learning between researchers and stakeholders) outlined above. We investigate participatory applications of agent-based modelling (P-ABM); computer games (P-Games); and participatory social network mapping (P-SNM) in environment and development-focused projects to understand the opportunities offered by each to the facilitation of the communication as well as the elicitation of stakeholder knowledge to the benefit not only of researcher stakeholders and their projects, but also of participant stakeholders and the communities they represent (i.e., both top-down and bottom-up concurrently: what we call a sideways approach). These methods are briefly described using the different projects in which they were initially applied, namely: Whole Decision-Network Analysis for Coastal Ecosystems (WD-NACE) on the south Kenya coast; OxGAME in Cameroon; and part of the Building Resilience Amongst Communities in Europe (emBRACE) project, which took place in Südtirol in northern Italy. This paper argues that to foster better communication of environmental issues using participatory approaches we need methods where the full complexity of understanding might be understood and harnessed. We aim to make methodological contributions to the literature on the beneficial use of multiple methods spanning qualitative and quantitative assessment (for example, Crossley, 2010 ; Forrester et al., 2015 ; Mallampalli et al., 2016 ). Further, we seek to locate these methods within a realist anthropological understanding (Zeitlyn and Just, 2014 ) of the drivers, motives, and learning outcomes of stakeholders which, we believe, will contribute a strong social science basis for participatory/citizen engagement in environmental and ecological science with lessons that are applicable to science communication more widely.

In this paper we present reflections of researchers involved in these three cases, each of which used different participatory methodologies and each within mixed methods projects, drawing on material collected with stakeholders focusing on whether and how interactive and constructivist communication occurred in the process of using these methods. Each method is different, but all share several important characteristics. Table 1 outlines the projects and the related methods. All projects have a minimal common methodology, which makes them comparable for the purposes of this paper, which may best be summarised as the use of structured outputs for communication and dialogue, and which leverages the communication potential of participatory research methods in various ways. The overall implications of using these types of methodologies are discussed later.

Table 1 shows some relevant data on each of the mixed method projects. All the projects involved multiple stakeholders at a range of levels of environmental governance and thus both provided and facilitated cross-stakeholder communication. The projects also took an inclusive standpoint on who is a participant/stakeholder (Forrester et al., 2008 , p. 3); communication was always paramount, with learning tacit or implicit, whether by the researchers or the stakeholders, or both. The final (right-hand side) column describes the main “knowledge production practices” within the project following Rodela et al. ( 2012 : Table 1 ). The four dimensions/philosophical perspectives are ‘positivist’: belief that empirical observation informs knowledge production and universal truths; ‘interpretive’: belief that reality is socially constructed and context-dependent as is the knowledge that actors use to engage with it; ‘critical’: belief that realities should be understood through the lens of power relations; ‘post-normal’: belief that knowledge is multifaceted and needs to be validated with extended stakeholder communities (Rodela R et al., 2012 ; Moon and Blackman, 2014 ). All projects were interpretative (due to the methodology itself) and two had post-normal elements of learning because of the transdisciplinary nature of the conceptions of the projects. For us, transdisciplinary research interlinks various scientific knowledge production processes with the development of solutions for addressing current societal issues or challenges. Thus, while each project/method incorporated some different assumptions, concepts, and outlooks, which constrains comparative analysis, for the purposes of this paper how research questions are described, and the data and validation aspects of research are standardised with respect to the three methods being described: agent-based modelling; gaming simulations; and participatory social network mapping.

The subjective matter of research spans several areas of environmental research including ecosystem services and development (P-ABM and Games exemplars) and disaster risk management (P-SNM exemplar). Each example deals with stakeholder or citizen engagement in environmental science processes or governance. We describe the main goals as well as the methodological approach in each, and we provide information about the participants. Our focus is upon the beneficial communication outcomes of using structured-output participatory methodologies between researchers and community participants at multiple levels. Each example increases the sum of (scientific) knowledge but also contributes to a wider ‘sideways’ participatory agenda by increasing and improving both researcher and citizen knowledge and understanding.

P-ABM—the WD-NACE project

The WD-NACE project, piloted participatory agent-based models to help reveal how coastal stakeholders—working individually and within social networks—generate, share, and select knowledge before finally acting upon it. These interactions produce feedbacks that pose challenges to the sustainability of ecosystem provisioning and livelihoods. It was an opportunity for researchers and stakeholders to learn about Ostrom’s ( 1990 ) ‘design principles’ for collective management of common pool resources, a seminal theoretical contribution. WD-NACE centred on the South Kenya coast where decentralisation of responsibility had given rise to a new type of village-level management actor called the Beach Management Unit (BMU), with the aim of improving the management of fisheries around reef ecosystems (see King, 2000 ; Oluoch and Obura, 2009 ). The WD-NACE case employed a participatory modelling approach (Barreteau et al., 2003 ; Étienne, 2006 ). This follows a methodology pioneered by the ‘Companion Modelling’ group, involving “co-construction of conceptual models that represent visually multiple viewpoints and can be employed as mediating, discursive objects that promote collective learning processes” (see http://www.commod.org ). The project worked with BMU members, local government and other coastal community representatives. Workshops, each with around 30 participants, were conducted over three days in two locations: central Mombasa (district governance, BMU representatives and NGOs), and Ukunda (BMU and fisher/fish traders from Msambweni district). Participants shared their economic, social and behavioural data and used this to ‘map’ the social networks involved in resource decisions. This provided conceptual models of a community’s area and of its governance.

The next stage of WD-NACE was to represent the behaviour of actors in ‘code’ using the NetLogo platform (Wilensky and Rand, 2015 ), which provided a means to simulate and visualise aspects of fishers’ routines. The co-created pilot ABM was then taken back to a second set of ‘feedback’ workshops. Kenyan fishers, government policymakers and policy advisors were invited to check on how well the ABM matched their experiences or not, to suggest improvements, and to test whether it could be used by them to investigate policies aimed at reducing poverty and managing ecosystems sustainably. This was followed up with the development of further models enabling participants to explore different scenarios informed by coastal stakeholders themselves (see Supplementary Material for details) Footnote 1 .

Games—OxGame

The goal of OxGAME, a participatory gaming experiment in the Republic of Cameroon, was to create a tool to help an experienced anthropologist discuss future agricultural adaptation strategies with farmers and experts, moving beyond empty platitudes about uncertain futures in ways that allow robust and demonstrable documentation. The project sought ways to access tacit knowledge and generate new knowledge without explicitly asking questions. The computer-based gaming environment indirectly asks questions that the participants address by participating in game-play. In OxGAME, UK-based researchers worked with local researchers to create a simulation of a basic farm ecosystem (soil with fertility that declined when farmed, invading weeds, forest, etc.). The game required players to decide which crops to plant, when, and how much of their farm to plant with what.

The goal was to look after the crops as they grew, harvest them, sell them at a market, and spend any surplus cash after meeting the costs of living. Challenges were also added: invading cows destroying crops; bushfires; illness; and extra mouths to feed. Initial versions of the model were tried by local farmers to calibrate each parameter, for example how long it takes to prepare a hectare of the field for planting; the price range of manioc; how frequently cows destroy crops; what can be bought with surplus cash; and the cost of different goods. The game also recorded in its log file each decision made by the player. The pilot simulation game was played by six to eight farmers (previously unfamiliar with computers let alone computer-based simulations or games) each morning for 10 days, after which the model was updated with their feedback. The game was introduced in Mambila (the local language) as being ‘a game which is like farming’: researchers were deliberately non-directive about its goals. The farmers quickly understood the game; one reason may be the highly visual representation of the researchers’ understanding which the computer platform allows. The first question asked was always: “what is wrong with this game?” (and by implication, what is wrong with the researchers’ understanding). Replies were detailed and often numeric: for example, the number of days it takes a child to clear a hectare was much less than the initial estimate; also, significant details had been omitted such as the fact that picking coffee requires a costly spray to kill venomous ants; and so on. The output is a model that is much more nuanced, including variables that none of anthropologists, local informants when explicitly asked or local agricultural development staff had mentioned as being significant.

P-SNM—the emBRACE project

In what looks on the surface to be a very different case, the authors used social network mapping to investigate the role of community disaster response networks in Südtirol, Italy, as part of the Europe-wide emBRACE project. The importance and the value of social networks are well known (Putnam, 1993 ; Aldrich, 2008 ) particularly in preparing for and dealing with disasters by providing access to resources at a critical time, diffusing information among individuals, and creating trustworthiness (Aldrich, 2012 ). A social network map was constructed through consideration of the actors, the links between them, the attributes of the actors, and boundary conditions of the network determining the inclusion and exclusion of actors (Cumming et al., 2010 ). The goal was to visualise and better understand the social networks in the immediate response phase to a landslide that happened in the small alpine municipality of Badia in Northern Italy, in particular, to see whether there was any observable difference between the ‘official’ risk management network and that involved in the response phase immediately after the event (amongst the affected population). In this case, the network map was the structured output of research—where, similar to the ABM and the gaming approaches above, both the process of creating the map and its subsequent employment provided opportunities for communication, learning and engagement between stakeholders. Combining mapping with interviews offered the opportunity to study networks as both structure and process at the same time (Edwards, 2010 ). Initially, a population survey was conducted, asking residents, which organisations they would contact in case of a landslide happening. The answers of all respondents ( n  = 1074) were visualised in a social network map, which showed significant complexity but also clearly indicated who the key actors were in the minds of the affected population (Pedoth et al., 2019 ).

In a further complementary step, this data (the community map) was validated and discussed with the identified risk-management actors and a qualitative network mapping exercise was also carried out through individual interviews with them ( n  = 10, on-average one hour discussions) focusing on how, and with whom, they shared information in the aftermath of the disaster. As the starting point of the mapping was a blank sheet of paper, the stakeholder and the researcher were at the same level. This participatory mapping, accompanied by the narratives of the interviewees, allowed a deeper understanding of what is “going on” within the network of emergency responders (Crossley, 2010 ).

Thus, across the three methods, a first step is that each methodology allows the stakeholders to present data or knowledge to each other, which is then used to co-create the structured output (the map or model); the co-creation of knowledge is one of the main strengths of such an approach. In a second step, both stakeholder and researcher engage with the structured output in a way that allows participants to reflect upon it directly and, on equal terms, have a constructive dialogue. The structured output (aka “mode-2 object” (Nowotny et al., 2001 , 147ff; Forrester et al., 2002 )) created does not assume a priori that one kind of information or perspective is more important than any other. Participatory mode-2 knowledge production can be thought of as the production of knowledge, which could not have been created by a single expertise (cf. Funtowicz and Ravetz ( 1991 ) “post-normal science”). Thus, the ‘data’ analysed include both qualitative and quantitative; technical scientific information and citizen information; the structured output and participants’ reflections upon it; and the authors’ reflections on the process as data.

Results and discussion

As this paper sets out to provide a treatise on how and why these sorts of methodologies are and can be used it does not, therefore, provide full results of those projects per se. Rather, we suggest that drawing upon “the cross-disciplinary nature of drawing as a language” Footnote 2 these projects taken together show that representational elements of structured subjective methodologies—especially when considered as boundary objects—allow opportunities for engagement with and learning from stakeholders. We start this section by discussing and comparing results across the 3 projects, in the context of relevant methods and theories. Then we turn our attention to the overall implications for participatory research methodology. The practices we describe of using formal representations to better gather the views, ideas, and beliefs of knowledge stakeholders are not new (see Barreteau et al., 2003 ; Étienne, 2006 ). There are also insightful expositions of how and why individual methodologies can be used with stakeholders (for example, Voinov and Bousquet, 2010 ). Our contribution builds on this work by discussing the merits of structured output methodologies taken together and the differences and similarities in knowledge production practices and communication processes they support. We end this section by highlighting our insights and added value to this literature.

Summarising and comparing results

In our P-ABM example, modelling with stakeholders—such as was used on the South Kenya Coast—helps understand linkages and illustrate dynamic feedback loops at the local level, thus making explicit various facets of complexity. Model demonstrations with stakeholders emphasised the aggregate impacts of changes. For example, the model was used to explore the effect of changing the number of large boats on fisher incomes and on fish stock levels (see Supplementary Material for details). This also helped stakeholders think about ways in which different model outcomes are sensitive to input assumptions. Differences were discussed between two different management scenarios in relation to fisher income: contrasting communal versus private ownership of boats. Participants offered ideas of how to improve the accuracy of the model with respect to issues such as incorporating government regulations concerning illegal fishing gear and suggested connecting the model to weather predictions and sea conditions. At the final workshop of WD-NACE in Kenya, it was agreed that it would be important for resource managers to understand such models and use them as thinking and learning tools. Using computer-based models proved very popular with fishers and other stakeholders, and this improved everyone’s understanding of which data are needed, and which feedbacks of the linked system are understood least. From the perspective of the ‘recipients’ of the original project in Kenya as discussed here—fishers along the south Kenyan coast—that work has continued through several subsequent projects.

Furthermore, our P-ABM case illustrates how a systems approach can facilitate synthesising existing knowledge about ecosystem services—sense-making, or ‘making sense’ in other words. During the participatory modelling in Kenya, one fisher was reported as saying “Ah, now I understand why KMFRI [the Kenyan Marine & Fisheries Research Institute] are always asking us how many baskets of seagrass we collect”. The fisher had not—until prompted to consider the whole ecosystem by modelling it—made the link between undisturbed seagrass availability and its role as a nursery habitat for marine species. He made that link himself through working through the model (one of many models uses; see Epstein, 2008 ; Taylor et al., 2014 , for other suggested uses).

Whilst piloting the participatory games with Cameroonian farmers we used the same NetLogo platform as used for the ABMs (in Kenya). However, we found it not well suited for a gaming interface. Unlike ABMs, games seem to work better when they resemble the users’ reality, for example with respect to their village and the surrounding farmland. This extra burden of visual representation of details, along with writing data to a log file in order to record players’ decisions and trying to capture the screen as a video (using NetLogo replay module) meant that performance was an issue. Nonetheless, by the end of the project each player had run through 20 years of game time. The log files were used to discuss and learn why players had taken identifiable strategies. In the game, most players had realised that it was necessary to invest in coffee before moving to palm oil, the profits from which could enable the purchase of the most sought-after luxury items (tin roofs and motorbikes). Discussions focused on why some options were not taken in the game, for example selling products to a market outside of the village: even in a ‘game’ this option was not taken because in real life the farmers would not trust others to take the food to market and return with the proceeds—signalling that participants were imputing complex real-life factors into their game decisions and actions. The NetLogo source was shared with Cameroonian colleagues (from several Universities in Cameroon) who continue to develop similar approaches; it and the logfiles are available at: https://zenodo.org/record/259340 .

Although the use of P-SNM involved a different interface—and a different substantive issue—it allowed similar engagement with and learning from stakeholders acting at different levels of governance (from parochial up to provincial levels), with different roles and responsibilities, and with different levels of expertise (volunteers, officials, and decision-makers). Using different mapping approaches at different steps enabled researchers to gain an outsider view of the network in terms of the structure of the whole network (which could not be seen by any individual actor), but also to gain a perception of the network from an “ insider’s view, including the content, quality and meaning of ties for those involved” (Edwards, 2010 ). This process, together with the involvement of stakeholders starting from the design of the study and followed by iterative interaction, resulted in a real and reciprocal exchange in contrast to what often is criticised as merely data and knowledge extraction in disaster research (Le De et al., 2015 ).

However, in this case, the use of P-SNM and the topic of information exchange took place in a milieu often dominated by technical assessment and numerical data. What was observed may be what Spiekermann et al. ( 2015 ) describe as different existing types of knowledge and the need to pass from data and information towards knowledge and wisdom. This is well reflected in the quote from an official of the provincial administration:

We have a lot and probably enough data and information about hazards and risks. What is the challenge now and for the future is to share, communicate and ‘activate’ this information; how to bring it out to the people and engage with them. This goes beyond our expertise as technicians and we therefore need to include people with different backgrounds and expertise in ‘social issues’ in order to get a step further in risk management.

The learning exchanges using mapping generated interest that contributed to a follow-up project in Badia and other municipalities (financed by the stakeholders and authorities themselves), and a training course on social research methods for the technicians. Inclusion of different voices in risk management and the use of communication methods better grounded in social science is a way to overcome the limitations of the knowledge deficit model of communication—the idea that what is needed is better information (namely, expert knowledge) and better delivery to close a presumed gap in knowledge. Although reducing ignorance over scientific issues is important, risk communication is usually more complex than this model implies. Moreover, a risk communication process is more likely to be successful when it responds to concerns of the public when it is not seen as a ‘one-way’ transfer, and “is thus transformed from a means of distributing information to a vehicle for mutual learning and deliberation” (Engdahl and Lidskog, 2014 , p. 706).

Structured subjective methodologies, such as social network mapping, agent-based modelling, and ‘developments’ of computer-based ABMs such as gaming simulations elucidated in this paper excel at representing ‘social issues’ in different ways. We are not arguing that computer simulations on their own will provide instant solutions to this official’s need for a step further. Other methodologies—especially other highly structured methodologies such as Q-methodology (for example, Donner, 2001 ; Eden et al., 2005 ; Webler, Danielson and Tuler, 2009 ; Cuppen et al., 2010 ; Forrester et al., 2015 ) and participatory mapping (see the section “Introduction”) are useful adjuncts to co-creating knowledge using computer-based simulations.

A key point is that there are subjective criteria to which various stakeholders refer to implicitly. These influence not only individual perceptions but also how ideas are communicated (see Étienne, 2006 , Fig. 1). For instance, in our P-SNM case, the activity required participants to state who is part of the network for disaster response and for disaster recovery, and the significance of actors and links (their power, responsibilities, etc.). Throughout, the ‘sorting process’ necessitated by structuring data allows for—indeed forces—key stakeholders to confront their own personal beliefs in a way not always considered by them within their day-to-day work and often not facilitated by other forms of engagement. It necessitates both researcher and participant to consider their own beliefs and how they ‘really understood’ the issues (Forrester et al., 2015 ). The structured way of collecting, representing, and presenting data allowed these findings to become clear in a way that more traditional qualitative methodologies might not.

Implications for participatory research methodology

The three examples show interactive and constructivist communication occurring in a range of settings. In the remainder of this section, we discuss the main methodological lessons learnt. Initially, however, it is worth highlighting the fact that these apparently different approaches have two similar underpinnings: firstly, they are all explicitly or implicitly part of the participatory science movement in that they all share a belief that the ‘citizen’ has something to contribute to the science process (cf. Irwin, 1995 ; Collier and Toomey, 1997 ; Jensen and Holliman, 2009 ) and that these contributions are critical. In other words, they all go beyond simple ideas of democracy; simple economics; and trust; to include the logic of improvement to scientific knowledge itself (cf. Forrester 1999 , 320ff). Secondly, they have in common the production of a structured ‘reality’—separate and separable from the reality it represents. Such a structured output is both a boundary object and a useful heuristic device allowing learning processes and possibilities not offered in the same way by other participatory methodologies that do not produce such an output.

Thus, the type of methodologies explored in this paper can all be said to ‘re-frame’ stakeholder knowledge to make it interpretable to technical expertise; while vice versa, they can be used to help stakeholders understand technical expertise, and further, they can be used to allow both to explore the lived realities of human–environmental interactions.

When stakeholders see the value of the structured output, and their own role in the process, this contributes to building trust. However, “trust does not develop through information and the uptake of knowledge but through emotional involvement and sense-making” (Engdahl and Lidskog, 2014 , p. 703). Trust seems to be created when scientific information is distilled and its essential meaning is agreed upon collectively, often using informal opportunities to do so (Scott and Taylor, 2019 , p. 14). Therefore, a process is required beyond ‘simple communication’ and that process must facilitate making sense of issues. According to Kompridis ( 2011 ), possibilities in public policy are a function of the sense-making vocabularies we develop; vocabularies that facilitate and constrain how we interpret issues, communicate possibilities, and contribute to change. We suggest that this overarching approach, and maybe even some of the methods described above, help facilitate making sense of issues. It is more than trust and language: the processes we have described of undertaking ‘sideways engagement’ mean that stakeholders can legitimately feel an ownership of the maps and models that have been co-produced rather than information being extracted to be processed by experts or produced solely by communities themselves.

Different aspects of the methodology can be adapted to suit the subject of enquiry, the kinds of participants involved and the nature of the interaction. Notably, new technologies can help to make the structured outputs themselves more engaging, and their employment more rigorous. Further, they can contribute to learning (arguably one result of communication) by participants and researchers, non-technical-expert stakeholders, and technical experts. In particular, if we accept that learning can be brought about by acquiring, modifying, reinforcing, or synthesising either existing knowledge or beliefs then we can see that each of the three methods discussed above probably have differing abilities to bring about communication/learning in a different milieu. This suggests not only tailoring participatory methods to suit particular learning requirements but also using suites of methods. So, for example, in the Borderlands study on flooding (see Forrester et al., 2015 ; Bracken et al., 2016 ) semi-structured interviews were used alongside Q-Methodology and participatory mapping, and in the ABM exemplar described above the ABMs were part of a wider project using interviews, life histories, and social network mapping. The use of ABMs combined with role-playing games for environmental assessment and stakeholder learning has been developed through the ‘Companion Modelling’ approach (Barreteau et al., 2003 ; Étienne, 2006 ). This paper is not advocating any one methodology, so this discussion should be taken holistically. It is further important to remember it reflects usage in the specific project exemplars described (see Table 1 ) although relevance to the wider participatory agenda should be clear: context is important and other applications may differ (e.g., used for extractive or purely science-led engagement). Furthermore, we take no firm line distinguishing between the researcher and the researched when it comes to where learning can and should occur.

Researchers who use and who wish to use bottom-up approaches could reap great benefits from the ‘sideways’ communicative potential of methods such as we describe, with highly structured outputs, which function as boundary objects, especially those methods that cope well with qualitative as well as quantitative analyses (a.k.a. Q 2 ). This can be used to better understand complex systems, producing structured outputs, which help to create space for learning and contribute to better outcomes. Multiple and mixed methods can be used to promote increased participation in scientific research and in resource/environmental management. They enable participatory science projects to go beyond a purely scientific literacy agenda (cf. Bonney et al., 2009 ) and widen participation in scientific knowledge co-creation (cf. Irwin, 1995 ; Nowotny et al., 2001 ). This, of course, requires a re-thinking of what is knowledge (cf. Nowotny et al., 2001 ) and, further, some theory of the citizen’s ‘social’ is required in order to understand better what is happening. The projects above—taken together—show how even “partial” (Zeitlyn, 2009 ) pictures of ‘reality’—if we have enough confidence in those bits we do recognise (see Carpenter et al., 2009 )—can be used to start to build better understanding, and thus knowledge, and thus a ‘better’ citizen-engaged science and through its policy and action.

We argue that for each of the three projects described above, by creating a structured output an appreciation of the ‘mess’ is created, allowing us to derive a better understanding of the relationship between different parts of human–environmental systems. This is a result of sorting and sense-making processes implicit in the methods. The outputs also facilitate better communication between stakeholders with different or competing understandings of—and engagement with—human–environmental systems and, thus, result in better science (i.e., knowledge). They also address some of the issues related to the complicated nature of the problems inherent in human–environmental systems and the place of these methods within communication—and learning—processes. The primary approach in each case has been to integrate local stakeholder knowledge, provide access to technical data, encourage greater participation in decision making and overall create a dialogue between local stakeholders, planners, environmental modellers, and policymakers with the ultimate aim to improve decision outcomes for local communities (within the context of human–environmental systems). Participation in this sense has a normative as well as a pragmatic focus. Not only is it important that people’s voices are heard (cf. Irwin, 1995 , Ch. 5), but through using ‘maps and models’ we argue that people become more fully aware of their context and are able to see how their and others’ understanding of the environment overlap or differ.

Modelling also provided a structured way of communication that facilitated co-learning among stakeholders at different levels of decision-taking. For example, the interest and wide range of participants in the ABM pilot project in Kenya exceeded researchers’ expectations, and they were able to share knowledge across and within domains with direct resource users, government actors and researchers by using ABMs. Further, the simulation gaming approaches were orientated to generating new knowledge to help address uncertainty associated with climate and other challenges. Another example of this is provided in a discussion of the use of simulation games to make actors think about uncertainty (van Pelt et al., 2015 ): they conclude “[c]ommunicating uncertainty is thus a delicate task that needs to take into account the opposing discourses about the concept. The simulation game as boundary object fulfils such a role as it allows for communicating about uncertainty without explicitly referring to the concept” (van Pelt et al., 2015 , p. 50).

Added value (new insights and confirming existing perspectives)

An important insight with producing structured outputs from participatory processes is the way they allow interactive and constructivist communication and learning about emergent issues: this is particularly evident with the agent-based modelling and gaming simulation approaches as these methodologies are designed to work with complexity (Epstein, 1999 ; Neumann, 2009 ). Rodela et al. list four possible approaches or ‘dimensions of learning’ relating to knowledge production: “positivist”, “interpretative”, “critical” and “post-normal” ( 2012 : Table 1 ). We suggest a modification, that we might add alongside these the additional dimension of ‘generative’ learning. This new category covers learning arising from the use of simulation, simulation thus becoming its “most used mode of enquiry” (Rodela et al., 2012 ).

By making the perspectives underpinning the methodologies clearer, we aim to close the gap between theory and practice. Using suites of methods in different types of combinations is a developing practice, and these practices also frequently address how the representations or outputs of the methods can be understood by participants and by extended peer/peer-review communities as audiences. Our work contributes to this area by investigating the knowledge production practices associated with different structured output methodologies and their implications. We also relate our experiences to the relevant social theories attempting to explain how citizens, managers and researchers communicate and learn about environmental issues. Empirical evidence is required both to develop the ideas and to inspire new applications and further new ideas. It is hoped that this paper provides some foundation to continue that debate. This is required to avoid practice progressing on incomplete or insufficient understanding.

Our work focuses specifically on the outputs of participatory research and their utility when co-design is part of the methodology. We found that structured output methodologies can utilise multiple platforms, switching platforms to re-frame data/knowledge so as to make it easily communicable to—and interpretable by—a new audience. Awareness of audiences and their needs can help tailor which methodology is suitable in any given situation. Some methods look very similar and the differences between them quite subtle. For instance, Games and P-ABM appear to be similar but they fulfil different roles. Games generally rest on relatively fewer assumptions than ABMs. Games make fewer assumptions because they leave many decisions to the players (in their responses to the game), while other methods such as P-SNM may involve no a priori assumptions at all. On the other hand, a game may involve repeated tasks that can quickly become mundane and fail to challenge or keep the attention of players. Also, often a game is a simplification of a scientific model (which can be used for validation or for data collection) but in participatory modelling users/stakeholders can also be involved in developing the model. This ‘co-construction’ or ‘co-production’—although time-consuming—allows stakeholders and researchers to collaborate to gain a shared understanding and co-learning can occur.

Use of participatory methods can generate positive feedback from stakeholders involved in the projects, particularly those which used a co-design approach such as in the P-SNM emBRACE case in Italy and the Kenyan modelling studies. In emBRACE, for example, researchers were requested to present their outputs to a broader public within the provincial administration in order to widen the discussion. Based on collaboration and exchange going beyond project life cycles, and requests from stakeholders to undertake further activities together (in Italy and in Kenya), we can confirm that the use of structured outputs can trigger critical discussion and open the door for the acceptance of these types of methods. Where co-design does not happen although communication and co-learning by some may result, the wider uptake of the approach may be slower (see Cook et al., 2016 arguing that there are powerful barriers to the uptake of natural flood management ideas among some policy actors).

Finally, we anticipate the economic and societal impact of these activities can be encouraged even further by promoting structured outputs (boundary objects/mode-2 objects) as seen above and by adopting open data and open source tools where these are available. This latter was also piloted in the case study in Cameroon where repositories containing the structured output and associated data (e.g., log files) were shared, providing an avenue for collaboration, and making learning outcomes observable to other partners.

Across a number of areas where environmental science meets environmental governance, structured output stakeholder engagement methods can help co-create knowledge of human-environmental systems through the co-construction (using processes we call ‘sideways engagement’) of structured outputs that function as ‘boundary objects’. The method of engagement is nuanced and can be considered in its own right as well as its communication and learning potential. It involves knowledge production practices that go beyond a single expertise and unlock different perspectives and potential emerging insights and solutions.

The main ideas that have emerged in practice include the importance of building trust early in the process, treating each participant as equal knowledge contributor and user. In this light an advantage is where critique can be deflected onto the structured output (and on the specifics) rather than the actor. However, trust also needs to be built in the methodology, and as a result in its output. Co-created structured outputs where each participant can recognise their input in the output are useful. Structured outputs can also be employed very effectively as empirical communication tools across levels of governance and between ‘citizens’, ‘managers’ and ‘scientists’. Bottom-up methods offer the opportunity to get the citizens/local residents’ message across, and there is a normative imperative for doing so. In sideways engagement the process is different in that scientists are involved in creating the outputs of the [citizen] engagement. Bringing scientists and stakeholders together and looking sideways—or laterally—at the problem is the first step towards sideways science, that is, a co-created knowledge or a co-created science.

The lessons from these cases using structured outputs leave us in a position where work aimed at understanding complex issues allows us to increase communication and learning about environmental issues. Constructivist learning, based on solid structured communication platforms, employing structured subjective methods can both clarify different positions on the issue and, by activating new knowledge, can augment what each partner can bring to the table.

It has been argued that structured outputs can be used to iteratively compare and re-compare with reality in order to improve our understanding of the latter (Forrester et al., 2019b ): this paper rather suggests that such methods produce a structured ‘reality’/object separate and separable from the reality, which it purports to represent as a boundary/mode-2 knowledge object and that this ‘object’ can also be used to both include a bottom-up (citizen) understanding and also to look at the issues ‘sideways’. Key is that insight is gained by co-producing a heuristic output and by discussing that output using the highly structured participatory processes described above.

Crucially, so long as the method allows us to co-create an appropriate structured output with stakeholders, this provides the heuristic device and fulfils the criteria we need. We have shown that this process can allow the exploration of many aspects critical to both good environmental science and good governance. These include identifying potentially unhelpful directions of development (avoiding potentially unsustainable, maladaptive, and non-resilient futures). The highly structured outputs (be it model; game; or map) allows stakeholders and researchers to clarify and talk across disciplinary and sectoral ‘silos’ (e.g., about defining and visualising system boundaries) and they also foster critical reflection amongst stakeholders.

We conclude by answering the last part of our introduction’s question first: the outputs work as boundary objects to facilitate sense-making across different groups of stakeholders on the substantive issues and reciprocal communication between technical and local expertise. This requires continued adaptation of the methods and practices (e.g., data produced and platforms used) and potentially diversifying the philosophical/theoretical frameworks applied; researchers do need to think about the theoretical implications of how the methods are used. When these issues are addressed, the outputs can be used with greater legitimacy to communicate and justify standpoints, and allow stakeholders to create mirrors of their systems that can be used collaboratively to communicate and think better about gaps, problems, and come up with new strategies for adaptive governance of—and learning about—the environment.

Data availability

One dataset generated in emBRACE is not publicly available due to confidentiality of the respondents’ information. Further datasets are from model simulations and the codes are available. Other data from the 3 projects including workshop reports and other data gathered for the research are available from the corresponding author upon reasonable request.

Links to model codes are available: NetLogo model codes are at: http://modelingcommons.org/browse/one_model/3435 ; Modelling4all model codes: http://m.modelling4all.org/m/?frozen=tB3AfKKQQMU_z2Uxm2E14f&MforAllModel=1 .

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Acknowledgements

We are deeply indebted to Åsa Swartling (SEI) and Romina Rodela (Södertörn University) for many comments on a much earlier (and differently focussed) version of this paper. We are also eternally grateful to Neela Matin who contributed so much to projects described in this paper. We would also like to thank Howard Noble, Annemarieke de Bruin, Sarah West, and Steve Yearley for contributions to and comments on different previous versions of this paper. The WD-NACE project was funded by the UK’s Ecosystem Services for Poverty Alleviation (ESPA) programme under grant NE/I00288X/1; we are grateful to Stephen Oluoch, David Obura and staff of CORDIO East Africa. The OxGAME project was supported by the University of Oxford Fell Fund; the authors are indebted to Eric Fotsing (Universities of Dschang and Yaoundé), Eric Kameni (Ecole Normale Superieure, Yaoundé), the Institute of Mambila Studies for help and assistance, Howard Noble and Ken Kahn for programming support. The emBRACE project was funded through the EU’s Framework Programme 7 (FP7) under grant contract 283201. We appreciate the contributions of colleagues who worked on the project and give a special thanks to the Geological Department of the Autonomous Province of Bolzano and the municipality of Badia for their support and collaboration.

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Taylor, R., Forrester, J., Pedoth, L. et al. Structured output methods and environmental issues: perspectives on co-created bottom-up and ‘sideways’ science. Humanit Soc Sci Commun 9 , 292 (2022). https://doi.org/10.1057/s41599-022-01304-3

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Environmental Evidence volume  8 , Article number:  24 ( 2019 ) Cite this article

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Qualitative research related to the human dimensions of conservation and environment is growing in quantity. Rigorous syntheses of such studies can help develop understanding and inform decision-making. They can combine findings from studies in varied or similar contexts to address questions relating to, for example, the lived experience of those affected by environmental phenomena or interventions, or to intervention implementation. Researchers in environmental management have adapted methodology for systematic reviews of quantitative research so as to address questions about the magnitude of intervention effects or the impacts of human activities or exposure. However, guidance for the synthesis of qualitative evidence in this field does not yet exist. The objective of this paper is to present a brief overview of different methods for the synthesis of qualitative research and to explore why and how reviewers might select between these. The paper discusses synthesis methods developed in other fields but applicable to environmental management and policy. These methods include thematic synthesis, framework synthesis, realist synthesis, critical interpretive synthesis and meta-ethnography. We briefly describe each of these approaches, give recommendations for the selection between them, and provide a selection of sources for further reading.

Qualitative research related to the human dimensions of conservation and environment is growing in quantity [ 1 , 2 ] and robust syntheses of such research are necessary. Systematic reviews, where researchers use explicit methods for identifying, appraising, analysing and synthesising the findings of studies relevant to a research question, have long been considered a valuable means for informing research, policy and practice across various sectors, from health to international development and conservation [ 3 , 4 , 5 , 6 , 7 ].

The methodological development of systematic reviews took off in the 1980s, initially with a strong focus on the synthesis of quantitative data. The exploration of specific methods for qualitative synthesis started to grow a decade or so later [ 8 , 9 ]. Examples addressed questions related to the lived experience of those affected by, and the contextual nuances of, given interventions. The methodology for the synthesis of quantitative research appears to have been adapted for environmental management for the first time in 2006 and has been developing since [ 10 , 11 ]. However, guidance in the field for those producing or interested in working with qualitative evidence synthesis still does not exist.

To date, the vast majority of systematic reviews in environmental management are syntheses of quantitative research evidence that evaluate the effectiveness of an intervention or the impact of an activity or exposure [ 12 ]—here called systematic reviews of quantitative evidence. These typically aggregate relatively homogenous outcome measures from similar interventions or exposures to create a more precise and accurate summary estimate of an overall effect [ 13 , 14 ].

Current debates about systematic reviews of quantitative evidence in other fields point out that such reviews, while they address essential questions about the magnitude of effects or impacts, cannot help us answer other policy- and practice-relevant issues [ 15 , 16 ]. In addition, the complexity within studies on impacts of environmental actions or exposures, and in studies of environmental management initiatives, will mean that a simple aggregation of study findings will only mask important differences and enable us to predict very little about what might happen to whom (human or otherwise) in any set of given circumstances. Here we argue that qualitative evidence syntheses can add value to environmental research and decision-making. Systematic reviews that make use of qualitative research can provide a rigorous evidence base for a deeper understanding of the context of environmental management. They can give useful input to policy and practice on (1) intervention feasibility and appropriateness (e.g., how a management strategy might best be implemented? What are people’s beliefs and attitudes towards a conservation intervention? ); (2) intervention adoption or acceptability (e.g., what is the extent of adoption of a conservation intervention?; What are facilitators and barriers to its acceptability? ); (3) subjective experience (e.g., what are the priorities and challenges for local communities? ); and (4) heterogeneity in outcomes (e.g., what values do people attach to different outcomes? For whom and why did an intervention not work? ) [ 8 , 15 , 17 , 18 ].

In common with individual studies of quantitative research, individual qualitative studies may be subject to limitations, in terms of their breadth of inquiry, conceptual reach and/or methodology or conduct. Projects that systematically find, describe, appraise and synthesise qualitative evidence can provide findings that are more broadly applicable to new contexts [ 19 ] or explanations that are more complete [ 20 ]. Such qualitative evidence syntheses (QES) may stand alone, be directly related to a systematic review of quantitative evidence on a related question(s) or may be part of mixed methods multi-component reviews that aim to bring two distinct syntheses of evidence together.

In spite of its value, there is a limited discussion on the synthesis of qualitative research evidence in the environmental field and tailored methodological guidance could usefully address how to:

conduct syntheses of evidence so as to go beyond questions of effectiveness or impact;

use synthesis to identify explanations for and produce higher levels of interpretation of the phenomena under study;

include rich descriptive and often heterogeneous evidence from different research domains; and

combine and link qualitative and quantitative evidence.

The objective of this paper is to present a brief overview of different methodological options for the synthesis of qualitative research developed in other fields (such as health, education and social sciences) and applicable to environmental management practice and policy. A selection of sources for further reading, including those that expand on how to identify, describe and appraise evidence for QES is also included. Before describing the different synthesis options, we briefly explore the nature of environmental problems and management to explain the context for QES in this field.

The context of environmental policy, management, and research

Environmental and conservation problems are wicked, highly complex, and embedded in ecological as well as social systems [ 21 , 22 , 23 , 24 ]. The complexity stems from several sources: (1) a high level of uncertainty; (2) large temporal and spatial scale; (3) cross-sectoral and multi-level spanning; and (4) the irreversibility of potential damages [ 25 , 26 ]. The loss of global biodiversity or changes in the global climate system [ 27 , 28 ] can illustrate this complexity: our knowledge about these systems is imperfect, a multiplicity of actors is associated with them (see, e.g., [ 22 , 25 ]); their impacts span from local to global levels and the damages potentially cannot be repaired [ 29 , 30 , 31 ]. On top of this, interventions to address these challenges are themselves often complex, in that they are made up of many interacting components and are introduced into and rely upon social systems for their implementation [ 32 ].

Instead, the dynamic nature and complexity of environmental problems, and their possible solutions call for the use and integration of scientific knowledge from several and different disciplinary domains. This need is reflected already in the interdisciplinary nature of environmental research that occurs at the level of theory, methods and/or data [ 33 , 34 , 35 , 36 ]. Environmental research is frequently based on observational studies [ 37 ]. Studies are commonly developed around a well-defined theoretical and a geographical boundary, with the aim to develop a comprehensive understanding of the chosen phenomena. However, this means that such research produces highly heterogeneous evidence scattered across different contexts [ 38 ].

These issues related to the type and nature of environmental evidence imply that systematic review methods need to include a plurality of different approaches [ 39 ]. Adding qualitative and mixed methods evidence synthesis to the systematic review toolbox may be vital in cases where context is very important, complexity and heterogeneity is the norm, and where a more in-depth understanding of the views and experiences of various actors can help to explain how, why and for whom an intervention does or does not work [ 18 ]. These methods can further aid in the understanding of success and failure of environmental interventions through the analysis of implementation factors. Furthermore, they can also help in describing the range and nature of impacts, and in understanding unintended or unanticipated impacts [ 40 ].

What is qualitative evidence synthesis (QES)?

Qualitative evidence synthesis refers to a set of methodological approaches for systematically identifying, screening, quality appraisal and synthesis of primary qualitative research evidence. Various labelling terms have been used (see Box 1 ).

It should be noted here that QES is distinct from two other categories of reviews that have been labelled as ‘qualitative’. The first category contains narrative summaries of findings from studies with quantitative data. Here, the original intention was to use quantitative synthesis methods (e.g., meta-analysis) but that was not possible due to, for example, the heterogeneity between studies. Review authors in the second category have the intention to use a narrative approach to synthesis of quantitative data right from the start. Neither of these two review categories is discussed further here.

Box 1 Definitions and labels

Qualitative research refers to a wide range of different kinds of research studies that tend to collect and analyse qualitative data, to organise and interpret the results and produce findings that are largely narrative in form (see also [ 41 ]).

Qualitative data typically refers to textual data (although other types of data, such as visual data, can be produced during the research process). Data are obtained through recording of, for example, e.g., individual or group interviews, or observations of behaviours.

Qualitative evidence synthesis (QES) is an umbrella term that encompasses a set of various methodological approaches for systematically identifying, screening, quality appraising and synthesising primary qualitative research evidence.

Other generic terms used for qualitative evidence synthesis:

Systematic review of qualitative research

Qualitative systematic reviews

Meta-synthesis

Qualitative research synthesis

An overview of QES approaches

In common with methods for systematic reviews of quantitative evidence, there are a number of stages of the systematic review process which are followed in most QES approaches, including (1) question formulation, (2) searching for literature, (3) eligibility screening, (4) quality appraisal, (5) synthesis and (6) reporting of findings. However, the methods used within each of these stages varies, depending on the specific review approach adopted with its epistemology and relation to theory.

QES approaches lie on an epistemological continuum between idealist and realist positions and can be positioned anywhere between the two extremes ([ 16 , 42 , 43 ], see Fig.  1 ). Idealist approaches to synthesis operate under the assumption that there is no single ‘correct’ answer, but the focus is in understanding variation in different conceptualisations [ 43 ]. They are less bound by pre-defined procedures and have open review questions allowing for constantly emerging concepts and theories [ 44 ]. In these iterative approaches, any stage of the review process may be revisited as the ideas develop through interaction with the evidence base. The iterations are recorded, described and justified in the write-up. These approaches may aim to create a model or theory that increases our understanding of what might hinder or facilitate the uptake of a policy or a program, or how a phenomenon operates and is experienced. Approaches on the realist side of the continuum assume that there is a single independent and knowable reality, and review findings are understood as an objective interpretation of this reality [ 43 , 45 ]. The review questions are closed and fixed, and the reviews follow strict formal linear methodological procedures. These approaches usually aim to test existing theories ([ 43 ], see Fig.  1 ).

(Source: Gough et al. [ 43 ])

Dimensions of difference in review approaches

QES approaches may also vary in the way they address and understand the importance of the context and so, they can be multi-context or context-specific. Multi-context reviews aim at an exhaustive sampling of literature to include diverse contexts, e.g., different geographical, socio‐cultural, political, historical, economic, ecological settings. Such reviews are currently common in systematic reviews of quantitative evidence. Context-specific QES use selective sampling and focuses on only one context to provide specific understanding to a targeted audience and develop theories that are specific to the local setting (see [ 46 ]).

In the following sub-sections, we give an overview of five commonly used qualitative synthesis methods: thematic synthesis, framework synthesis, realist synthesis, critical interpretative synthesis and meta-ethnography [ 47 , 48 ]. Table  1 shows the main purpose of the method, a type of the review question and a type of evidence commonly used in the synthesis stage (qualitative or mixed) and key readings. Anyone wanting to undertake a review should keep in mind that each method might imply a specific approach to review stages (from literature search to critical appraisal) and the key readings listed in Table  1 should be checked for specific advice.

• Framework synthesis

Framework synthesis uses a deductive approach and it has been used for the syntheses of qualitative data alone (e.g., [ 49 ]), as well as by those undertaking mixed methods syntheses [ 50 , 51 ]. Framework synthesis has been grouped along with other approaches that are less suitable for developing explanatory theory through interpretation or making use of rich reports in study findings. The approach can be seen as one means of exploring existing theories [ 42 ]. Framework synthesis begins with an explicit conceptual framework. Reviewers start their synthesis by using the theoretical and empirical background literature to shape their understanding of the issue under study. The initial framework that results might take the form of a table of themes and sub-themes and/or a diagram showing relationships between themes. Coding is initially based on this framework. This framework is then developed further during the synthesis as new data from study findings are incorporated and themes are modified, or further themes are derived. The findings of a framework synthesis usually consist of a final, revised framework, illustrated by a narrative description that refers to the included studies. The initial conceptual framework in framework synthesis is seen as providing a “scaffold against which findings from the different components of an assessment may be brought together and organise” ([ 52 ]:29). The approach builds upon framework analysis, which is a method of analysing primary research data that has often been applied to address policy concerns [ 53 ].

Six stages of framework synthesis are generally identified: familiarisation, framework selection, indexing, charting, mapping and interpretation. In the familiarisation stage reviewers aim to become acquainted with current issues and ideas about the topic under study. The involvement of subject experts in the team can be particularly helpful at this stage. The next stage, framework selection, sees reviewers finalising their initial conceptual framework. Here some argue for the value of quickly selecting a ‘good enough’ existing framework [ 52 ], rather than developing one from a variety of sources. An indexing stage then sees reviewers characterising each included study according to the a priori framework. In the charting stage reviewers analyse the main characteristics of each research paper, by grouping characteristics into categories related to the framework and deriving themes directly from those data. During the mapping stage of a framework synthesis, derived themes are considered in the light of the original research questions and the reviewer draws up a presentation of the review’s findings. The interpretation stage, as with much research, is the point at which the findings are considered in relation to the wider research literature and the context in which the review was originally undertaken.

Framework synthesis is relatively structured and therefore able to accommodate quite large amounts of data. Like thematic synthesis (see below), researchers using this method often seek to provide review output that is directly applicable to policy and practice. This method can be suitable for understanding feasibility and acceptance of conservation interventions. A variation of the method, the ‘best-fit synthesis’ approach, might help if funder timescales are extremely tight [ 54 ]. A review by Belluco and colleagues [ 55 ] of the potential benefits and challenges from nanotechnology in the meat food chain is a recent example of framework synthesis. Here reviewers coded studies to describe the area of the meat supply chain, using a pre-specified framework. Belluco’s team interrogated their set of 79 studies to derive common themes as well as gaps—areas of the framework where studies appeared not to have been conducted.

• Thematic synthesis

Thematic synthesis draws on methods of thematic analysis for primary qualitative research and is a common approach to qualitative evidence synthesis in health and other disciplines [ 56 ]. Examples in the literature range from more descriptive to more interpretative approaches. Findings from the included studies are either extracted and then coded or, increasingly, full-texts of the eligible studies are uploaded into appropriate software (e.g., NVIVO or EPPI-reviewer) and coded there. These codes are used to identify patterns and themes in the data. Often these codes are descriptive but can then be built up into more conceptual or theory-driven codes. Initial line-by-line descriptive coding groups together ideas from pieces of text within and across the included papers. Similarities and differences are then grouped together into hierarchical codes. These are then revisited, and new codes developed to capture the meaning of groups of the initial codes. A narrative summary of the findings, describing these themes is then written. Finally, these findings can be interpreted to explore the implications of these findings for the context of a specific policy or practice question that has framed the review. The method is therefore suitable for addressing questions related to effectiveness, need, appropriateness and acceptability of an intervention [ 16 ] and usually from the point of view of the targeted groups (e.g., local communities, conservation managers, etc.). Similar to systematic reviews of quantitative research, this method attempts to retain the explicit and transparent link between review conclusions and the included primary studies [ 56 ]. There are only a few examples of reviews in the environmental management field that have explicitly applied thematic synthesis. For instance, Schirmer and colleagues [ 57 ] use “thematic coding” [ 56 ] (within the approach they call qualitative meta-synthesis) to analyse the role of Australia’s natural resource management programs in farmers’ wellbeing. Haddaway and colleagues [ 58 ] use thematic synthesis to define the term “ecotechnology”.

• Meta-ethnography

This method was developed by Noblit and Hare [ 59 ] and originally applied to the field of education. The method was further improved in the early 2000s by Britten and colleagues [ 60 ] who applied it to health services research and has since been used for increasing numbers of evidence synthesis, particularly in health research and other topic areas.

Meta-ethnography is an explicitly interpretative approach to synthesis and aims to create new understandings and theories from a body of work. It uses authors’ interpretations (sometimes called second-order constructs, where the quotes from study participants are first-order constructs) and looks for similarities and differences at this conceptual level. It uses the idea of “translation” between constructs in the included studies. This involves juxtaposing ideas from studies and examining them in relation to each other, in order to identify where they are describing similar or different ideas.

This method includes seven stages: (1) identification of the intellectual interest that the review might inform; (2) deciding what is relevant to the initial interest; (3) reading the studies and noting the concepts and themes; (4) determining how the studies are related; (5) translating studies into one another; (6) synthesising translations; and (7) communicating review findings [ 59 ]. There are three main types of synthesis (stages 5 and 6): reciprocal translation, refutational translation, and line of argument. Different findings within a single meta-ethnography may contain examples of one or all of these approaches depending on the nature of the findings within the included studies. Reciprocal translation is used where concepts from different studies are judged to be about similar ideas, and so can be “translated into each other”. Refutational translation refers to discordant findings, where differences cannot be explained by differences in participants or within a theoretical construct. A line of argument can be constructed to identify how translated concepts are related to each other and can be joined together to create a more descriptive understanding of the findings as a whole. This method is therefore very well suited to produce new interpretations, theories or conceptual models [ 61 , 62 ]. In the conservation, this method could be used to understand how, for example, local communities experience conservation interventions and how this influences their acceptance of conservation interventions. Head and colleagues [ 63 ] used meta-ethnography to understand dimensions of household-level everyday life that have implications for climate change mitigation and adaptation strategies.

Critical interpretive synthesis

The critical interpretive synthesis approach was originally developed by Dixon-Woods and colleagues [ 64 ]. Review authors using this approach [ 64 ] are interested in theory generation while being able to integrate findings from a range of study types, and empirical and theoretical papers. Further, this method can integrate a variety of different types of evidence from quantitative, qualitative and mixed methods studies. We included critical interpretative synthesis in our paper because this method is often used for synthesis of qualitative evidence.

In the overall synthesis a coherent framework is usually presented, showcasing a complex network of interrelating theoretical constructs and the relationships between them. The framework partly builds on existing constructs as reported in the different studies and introduces newly derived, synthetic constructs generated through the synthesis procedure itself. Reported themes are then gradually mapped against each other to create an overall understanding of the phenomenon of interest. This is similar to developing a line of argument in a meta-ethnography (see above). Critical interpretive synthesis distinguishes itself from other approaches such as formal grounded theory [ 65 , 66 ] and meta-ethnography by adopting a critical stance towards findings reported in the primary studies, the assumptions involved, and the recommendations proposed. Rather than taking the findings for granted, review authors involved in critical interpretive synthesis “critically question the entire construction of the story the primary-level authors told in their research reports” [ 17 ]. They would potentially critique recommendations based on, e.g., ethical or moral arguments, such as the desirability of a particular rollout of an intervention. This method is therefore very well suited for understanding of what may have influenced proposed solutions to a problem [ 64 ] and to examine the constructions of concepts [ 67 ]. In the environmental field, this method could, for example, be applied to understand how different narratives influence environmental practice and policy or to critically assess new forms of conservation governance and management. Explicit examples of critical interpretive synthesis review projects applied to the broad area of environmental sciences are currently non-existent to our knowledge. However, there are a few related examples from health studies, such as review on environmentally responsible nursing [ 68 ]. In that review, authors justify the use of critical interpretative synthesis mainly by the ability of this method to synthesise diverse types of primary studies in terms of their topic and methodology.

• Realist synthesis

Realist synthesis is a theory-driven approach to combining evidence from various study types. Originally developed in 2005 by Ray Pawson and colleagues [ 69 ], it is aimed at unpacking the mechanisms for how particular interventions work, for whom and in which particular context and setting. It is included here because it is increasingly used for synthesising qualitative data, although data can be both qualitative and quantitative.

Realist synthesis has been developed to evaluate the integrity of theories (does a program work as predicted) and theory adjudication (which intervention fits best). In addition, it allows for a comparison of interventions across settings or target groups or explains how the policy intent of a particular intervention translates into practice [ 69 ].

The realist synthesis approach is highly iterative, so it is difficult to identify a distinct synthesis stage as such. The synthesis process usually starts by identifying theories that underpin specific interventions of interest. The theoretical assumptions about how an intervention is supposed to work and what impact it is supposed to generate are made explicit from the start. Depending on the exact purpose of the review, various types of evidence related to the interventions under evaluation (potentially both quantitative and qualitative) are then consulted and appraised for quality. In evaluating what works for whom in which circumstances, contradictory evidence is used to generate insights about the influence of context and so to link various configurations of context, mechanism and outcome. Conclusions are usually presented as a series of contextualised decision points. An example of a realist synthesis in the environmental context is the one from McLain, Lawry and Ojanen [ 70 ] in which the evidence of 31 articles examine the environmental outcomes of marine protected areas governed under different types of property regimes. The use of a realist synthesis approach allowed the review authors to gain a deeper understanding of the ways in which mechanisms such as perceptions of legitimacy, perceptions of the likelihood of benefits, and perceptions of enforcement capacity interact under different socio-ecological contexts to trigger behavioural changes that affect environmental conditions. Another example from the environmental domain is the review by Nilsson and colleagues [ 71 ] who applied a realist synthesis to 17 community-based conservation programs in developing countries that measured behavioural changes linked to conservation outcomes. The RAMESES I project ( http://www.ramesesproject.org ) offers methodological guidance, publication standards and training resources for realist synthesis.

Choosing the appropriate QES method

Here we explain the criteria for the selection of different QES methods presented in this paper.

There are several aspects to be considered when choosing the right evidence synthesis approach [ 42 , 67 , 72 ]. These include the type of a review question, epistemology, purpose of the review, type of data, and available expertise including the background of the research team and resource requirements. Here, we briefly discuss the more pragmatic aspects to be considered. For a detailed discussion of other criteria we refer the reader to the work of Hannes and Lockwood [ 67 ], and Booth and colleagues [ 42 , 72 ].

Particularities of the evidence

As noted above, environmental problems are complex and involve a high degree of uncertainty. Environmental research is often inter- and transdisciplinary and involves, for example, the use of contested and/or diverse concepts and terms, as well as heterogeneous datasets. Thus, it is very important to understand if the QES method is fit-for-purpose and if it will result in the expected and desired synthesis outcomes. More complex and contextual outcomes are expected from the idealist methods (such as critical interpretative synthesis or meta-ethnography) (Fig.  1 and Table  1 ), which offer insights to policy or practice only after further interpretation. In contrast, more concrete and definitive outcomes can be expected from more realist methods (such as thematic synthesis) [ 67 ]. The type of evidence to be synthesised (e.g., qualitative or mixed, see Table  1 ) is yet another aspect needing consideration when choosing the synthesis method.

Background of the researchers and the review team

Researchers should consider their methodological backgrounds and epistemological viewpoints, to make sure they have appropriate expertise as well as experience in the review team when choosing the method. Some more complex methods (such as realist synthesis) may require specific skills (e.g., a familiarity with the realist perspective), and larger teams of researchers with different disciplinary backgrounds. Such methods may also require that the researchers are more familiar with the content of the research they review. Other methods (such as thematic or framework synthesis) can be done in a smaller team of researchers who do not necessarily have deeper subject expertise.

Resource requirements

Requirements for review funding will obviously depend on the resource requirements, i.e. a number of researchers to be involved, the time needed to conduct a review, costs associated with access to a specific data analysis or review management software, and access to literature. Some methods may be more resource demanding. Multi-component mixed method reviews, for example, requires expertise in both qualitative and quantitative synthesis methods, as well as the allocation of time for producing more than one parallel and/or consecutive syntheses. Other methods, such as framework synthesis, are maybe less resource-consuming (needing comparatively fewer people over less time) as long as initial frameworks have already been developed and are uncontentious. The issue of time spent on a review also depends on the breadth of the research question and the extent of the literature.

Challenges and points of contestation

Whilst QES can be valuable for environmental practice and policy, readers should be aware of several well-known challenges that might also appear problematic when QES approaches are used for the synthesis of environmental qualitative research. Here we summarise some of the most important ones including conceptual and methodological heterogeneity in primary research studies, issues with quality appraisal and transparency in reporting.

Qualitative evidence is likely to be situated in different disciplines, theoretical assumptions, and general philosophical orientations [ 73 ]. For aggregative less interpretative methods (such as framework synthesis), this poses a challenge in terms of comparability during the synthesis stage of the review process. In case of more interpretive approaches (e.g., meta-ethnography), such diversity is often seen as an asset rather than a problem as the translation of one study to another [ 74 ] allows for a comparison of studies with different theoretical backgrounds.

As with systematic reviews of quantitative evidence, critical appraisal of study validity is perhaps one of the most contested stages of the QES review process [ 75 ]. Quality appraisal (and the extent to which it matters) likely depends on the methodological approach. For example, framework and thematic syntheses assess the reliability and methodological rigour of individual study findings and may exclude methodologically flawed studies from the synthesis. Meta-ethnography or critical interpretative synthesis assess included studies in terms of content and utility of their findings, level to which they inform theory and include all studies in the synthesis [ 16 ].

Finally, reviews can be often criticised for lack of transparency and unclear or incomplete reporting. However, to ensure that all the important decisions related to the review conduct are reported at the sufficient level of detail, there are reporting standards applicable for QES such as ENTREQ [ 76 ] and ROSES [ 77 ]. Additionally, RAMESES are reporting standards developed specifically for realist syntheses [ 78 ] and the EMERGE project developed reporting standards for meta-ethnographies ([ 79 ], http://emergeproject.org ). These standards aim to increase transparency and hopefully drive up the quality of the review conduct [ 80 ].

Additional methodological options: Linking quantitative and qualitative evidence together

In the following paragraphs, we briefly present an additional methodological option that could be, for example, useful for the synthesis of complex conservation interventions and is suited to address some of the above challenges (such as methodological heterogeneity).

Namely, in some cases, synthesis of only one type of study findings (either qualitative or quantitative) might not be sufficient to understand multi-layered or complex interventions or programs typical for the environmental sector. The mixed methods review approach has been developed to link qualitative, mixed and quantitative study findings in a way to enhance the breadth and depth of understanding phenomena, problems and/or study topics [ 81 , 82 ]. Mixed methods reviews is a systematic review in which quantitative, qualitative and primary studies are synthesized using both quantitative and qualitative methods [ 81 ]. The data included in such a review are the findings or results extracted from either quantitative, qualitative or mixed methods primary studies. These findings are then integrated using a mixed method analytical approach [ 17 ].

This approach allows us to study how different (intervention) components are related and how they interact with each other [ 83 ]. Apart from studying the effectiveness of interventions, these reviews include qualitative evidence on the contextual influence, applicability and barriers to implementation for these interventions. For example, topics covered by reviews that link qualitative and quantitative data are the impact of urban design, land use and transport policies and practices to increase physical activity [ 84 ]; the socio-economic effects of agricultural certification schemes [ 85 ]; the impact of outdoor spaces on wellbeing for people with dementia [ 86 ]. Qualitative and quantitative bodies of evidence can point to different facets of the same phenomena and enrich understanding of it. In a review on protected area impacts on human wellbeing [ 87 ], it is revealed that qualitative findings were not studied quantitatively and only once combined in a synthesis these two evidence bases could provide a complete picture of the protected area impact.

Conclusions

Synthesis of qualitative research is crucial for addressing wicked environmental problems and for producing reliable support for decisions in both policy and practice. We have provided an overview of methodological approaches for the synthesis of qualitative research, each characterised by different ways of problematising the literature and level of interpretation. We have also explained what needs to be considered when choosing among these methods.

Environmental and conservation social science has witnessed an accumulation of primary research during the past decades. However, social scientists argue that there is a little integration of qualitative evidence into conservation policy and practice [ 33 ], and this suggests that there is a ‘synthesis gap’ (sensu [ 88 ]). This paper, with an overview of different methodological tools, provides the first guidance for environmental researchers to conduct synthesis of qualitative evidence so that they can start bridging the synthesis gap between environmental social science, policy and practice. Furthermore, introduced examples may inspire reviewers to adapt existing methods to their specific subject and, where necessary, help develop new methods that are a better fit for the field of environmental evidence. This is especially important as currently used methods in synthesis of environmental evidence fall short on utilising the potential of qualitative research that translates into lack of a deeper contextual understanding around implementation and effectiveness of environmental management interventions, and disregard the diversity of perspectives and voices (e.g., indigenous peoples, farmers, park managers) fundamental for tackling wicked environmental issues.

Availability of data and materials

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Acknowledgements

We thank the BONUS Secretariat for covering article processing fees. BM thanks to Mistra Council for Evidence-based Environmental Management (EviEM) and BONUS RETURN for allocated time to draft this manuscript. RG is partially supported by the National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care South West Peninsula.

Article processing fees were covered by BONUS RETURN. BONUS RETURN project is supported by BONUS (Art 185), funded jointly by the EU and Swedish Foundation for Strategic Environmental Research FORMAS, Sweden’s innovation agency VINNOVA, Academy of Finland and National Centre for Research and Development in Poland.

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Biljana Macura

Institute of Agricultural and Environmental Sciences, Estonian University of Life Sciences, Kreutzwaldi 5, 51006, Tartu, Estonia

Monika Suškevičs

European Centre for Environment and Human Health, University of Exeter Medical School, Truro, UK

Ruth Garside

Social Research Methodology Group, Faculty of Social Sciences, KU Leuven, Leuven, Belgium

Karin Hannes

EPPI-Centre, Department of Social Science, UCL Institute of Education, London, UK

Rebecca Rees

School of Natural Sciences, Technology and Environmental Studies, Södertörn University, 14189, Huddinge, Sweden

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Laboratory of Geo-Information Science and Remote Sensing, Wageningen University, 6708 PB, Wageningen, The Netherlands

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BM and MS developed the framework for and edited the end version of this paper. All authors (BM, MS, RG, KH, R. Rees and R. Rodela) wrote substantial pieces of the manuscript. RG, KH, R. Rees and R. Rodela commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Macura, B., Suškevičs, M., Garside, R. et al. Systematic reviews of qualitative evidence for environmental policy and management: an overview of different methodological options. Environ Evid 8 , 24 (2019). https://doi.org/10.1186/s13750-019-0168-0

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Study Mumbai

ICSE, CBSE study notes & home schooling, management notes, solved assignments

EVS Project (Class 11 ICSE): FYJC

February 27, 2022 by studymumbai Leave a Comment

EVS Project for ICSE Class 11 (FYJC) students.

Guidelines for writing project report

It is mandatory for the students to write project reports according to the following guidelines. A reference list of project topics is usually provided by the school/college. Evaluation of Project work is done according to the guidelines.

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Selection of the project topic (Introduction) : Student is expected to write briefly about the subject and the reasons for selecting the particular topic. Brief history, new updated information, current status of the topic should be included in introduction.

Importance of topic : Student has to write the precise importance of project work by identifying the present environmental, scientific and social value of the project topic.

Objectives of the project work : This should have the write up on what you will do in the project work and must write the appropriate objectives. The objectives of the project work should be in proper manner.

Project work methodology : A short description of how the information will be obtained under the practical approach. It is necessary to use a variety of data collection methods which includes survey, questionnaire, interviews, experiments, field observations, site visits, etc. The students should generally consider their local environmental issues for the project work (but not limited to). So that they can identify and formulate solutions to the problems surrounding them. Students should be encouraged to illustrate the problems of the selected environmental issue. Encourage use of the newspapers / self-drawn pictures/ photographs of the issues taken by the students themselves.

Observations : The data / information obtained from the selected topic should be depicted in the form of observation tables, graphs and brief points. The next part – conclusion is based on the observations recorded.

Analysis of data : It is an important step to analyze/evaluate the observations based on a various numerical or statistical methods, e.g. Mean, mode, median, correlation, average, percentage etc. Based on this analysis it becomes more accurate and effective. By this method, you can effectively indicate the numerical values through graphs, histograms, and images.

Results & Conclusions : The results should have interpretation and inference of the data / information obtained.

• Topic: Make a list of people who have worked in Maharashtra for environment conservation and document the work done by them.
• Topic: What is an Ecological Pyramid? Explain all the ecological pyramids given in the notes.
• Topic: Enlist some Do’s and Don’ts during respiratory group of diseases. What precautions should we take in case of current Covid-19 Pandemic?
• Topic: Collect the information about “Nobel Peace Prize” winner Environmentalists (at least two) and write about the work done by him/her and what message you get from this information.
• Topic: Collect the information regarding any one of the nationally recognized movements related to the environment and prepare a short report on it.

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Facility for Rare Isotope Beams

At michigan state university, international research team uses wavefunction matching to solve quantum many-body problems, new approach makes calculations with realistic interactions possible.

FRIB researchers are part of an international research team solving challenging computational problems in quantum physics using a new method called wavefunction matching. The new approach has applications to fields such as nuclear physics, where it is enabling theoretical calculations of atomic nuclei that were previously not possible. The details are published in Nature (“Wavefunction matching for solving quantum many-body problems”) .

Ab initio methods and their computational challenges

An ab initio method describes a complex system by starting from a description of its elementary components and their interactions. For the case of nuclear physics, the elementary components are protons and neutrons. Some key questions that ab initio calculations can help address are the binding energies and properties of atomic nuclei not yet observed and linking nuclear structure to the underlying interactions among protons and neutrons.

Yet, some ab initio methods struggle to produce reliable calculations for systems with complex interactions. One such method is quantum Monte Carlo simulations. In quantum Monte Carlo simulations, quantities are computed using random or stochastic processes. While quantum Monte Carlo simulations can be efficient and powerful, they have a significant weakness: the sign problem. The sign problem develops when positive and negative weight contributions cancel each other out. This cancellation results in inaccurate final predictions. It is often the case that quantum Monte Carlo simulations can be performed for an approximate or simplified interaction, but the corresponding simulations for realistic interactions produce severe sign problems and are therefore not possible.

Using ‘plastic surgery’ to make calculations possible

The new wavefunction-matching approach is designed to solve such computational problems. The research team—from Gaziantep Islam Science and Technology University in Turkey; University of Bonn, Ruhr University Bochum, and Forschungszentrum Jülich in Germany; Institute for Basic Science in South Korea; South China Normal University, Sun Yat-Sen University, and Graduate School of China Academy of Engineering Physics in China; Tbilisi State University in Georgia; CEA Paris-Saclay and Université Paris-Saclay in France; and Mississippi State University and the Facility for Rare Isotope Beams (FRIB) at Michigan State University (MSU)—includes  Dean Lee , professor of physics at FRIB and in MSU’s Department of Physics and Astronomy and head of the Theoretical Nuclear Science department at FRIB, and  Yuan-Zhuo Ma , postdoctoral research associate at FRIB.

“We are often faced with the situation that we can perform calculations using a simple approximate interaction, but realistic high-fidelity interactions cause severe computational problems,” said Lee. “Wavefunction matching solves this problem by doing plastic surgery. It removes the short-distance part of the high-fidelity interaction, and replaces it with the short-distance part of an easily computable interaction.”

This transformation is done in a way that preserves all of the important properties of the original realistic interaction. Since the new wavefunctions look similar to that of the easily computable interaction, researchers can now perform calculations using the easily computable interaction and apply a standard procedure for handling small corrections called perturbation theory.  A team effort

The research team applied this new method to lattice quantum Monte Carlo simulations for light nuclei, medium-mass nuclei, neutron matter, and nuclear matter. Using precise ab initio calculations, the results closely matched real-world data on nuclear properties such as size, structure, and binding energies. Calculations that were once impossible due to the sign problem can now be performed using wavefunction matching.

“It is a fantastic project and an excellent opportunity to work with the brightest nuclear scientist s in FRIB and around the globe,” said Ma. “As a theorist , I'm also very excited about programming and conducting research on the world's most powerful exascale supercomputers, such as Frontier , which allows us to implement wavefunction matching to explore the mysteries of nuclear physics.”

While the research team focused solely on quantum Monte Carlo simulations, wavefunction matching should be useful for many different ab initio approaches, including both classical and  quantum computing calculations. The researchers at FRIB worked with collaborators at institutions in China, France, Germany, South Korea, Turkey, and United States.

“The work is the culmination of effort over many years to handle the computational problems associated with realistic high-fidelity nuclear interactions,” said Lee. “It is very satisfying to see that the computational problems are cleanly resolved with this new approach. We are grateful to all of the collaboration members who contributed to this project, in particular, the lead author, Serdar Elhatisari.”

This material is based upon work supported by the U.S. Department of Energy, the U.S. National Science Foundation, the German Research Foundation, the National Natural Science Foundation of China, the Chinese Academy of Sciences President’s International Fellowship Initiative, Volkswagen Stiftung, the European Research Council, the Scientific and Technological Research Council of Turkey, the National Natural Science Foundation of China, the National Security Academic Fund, the Rare Isotope Science Project of the Institute for Basic Science, the National Research Foundation of Korea, the Institute for Basic Science, and the Espace de Structure et de réactions Nucléaires Théorique.

Michigan State University operates the Facility for Rare Isotope Beams (FRIB) as a user facility for the U.S. Department of Energy Office of Science (DOE-SC), supporting the mission of the DOE-SC Office of Nuclear Physics. Hosting what is designed to be the most powerful heavy-ion accelerator, FRIB enables scientists to make discoveries about the properties of rare isotopes in order to better understand the physics of nuclei, nuclear astrophysics, fundamental interactions, and applications for society, including in medicine, homeland security, and industry.

The U.S. Department of Energy Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of today’s most pressing challenges. For more information, visit energy.gov/science.

An integrated methodology for green human resource management in construction industry

• Green Technology and Industrial Revolution 4.0 for a Greener Future
• Published: 31 May 2022
• Volume 30 , pages 124619–124637, ( 2023 )

Cite this article

• Saeid Sadeghi Darvazeh 1 ,
• Farzaneh Mansoori Mooseloo 1 ,
• Samira Aeini 2 ,
• Hadi Rezaei Vandchali 3 &
• Erfan Babaee Tirkolaee   ORCID: orcid.org/0000-0003-1664-9210 4  

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Today, by increasing public awareness about environmental issues and pressures from governments and other stakeholders, companies have dealt with environmental challenges more than ever. This paper focuses on environmentally sustainable performance using an integrated methodology based on meta-synthesis, Delphi, and structural equation modeling (SEM) techniques which are utilized in different phases. In the first phase, an in-depth review of green human resources management (GHRM) literature is conducted based on the meta-synthesis method, and as a result, 38 codes are extracted. Next, to adapt and customize the codes with the nature of the construction industry, 2 rounds of Delphi method are implemented to extract the expert judgment from a panel of 15 industry professionals, resulting in 21 codes in 7 categories. To validate the developed methodology, a dataset from 33 Iranian construction companies are collected along with 15 factors in 5 categories determined using SEM. The findings reveal that among 9 main GHRM components extracted from the literature, just 5 components including green recruitment and selection, green performance management, green-reward, green-based employee empowerment, and green training have significant and positive relationships with GHRM. Finally, managerial insights, limitations, and future research directions are discussed.

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Green Behaviors and Innovations: A Green HRM Perspective to Move from Traditional to Sustainable Environmental Performance

Green human resource management research in emergence: a review and future directions.

Green human resource management: a need of time and a sustainable solution for organizations and environment

Avoid common mistakes on your manuscript.

Introduction

In recent decades, global warming and climate change have had profound impacts on people’s lives which demands more attention to the environmental issues from companies (Mishra, 2017 ; Jabbour and de Sousa Jabbour, 2016 ). Furthermore, the mounting pressures from various stakeholders such as consumers, governments, and environmental activists have forced companies to initiate environmentally friendly practices (Mousa and Othman, 2020 ). Companies need to increase their abilities to address stakeholders’ environmental concerns to be profitable and survive in the long term (Kawakami et al. 2015 ; Gardas et al. 2019 ; Walker et al., 2014 ). The incorporation of environmental issues in companies’ strategic tasks can increase their competitive advantage and lead to sustainable development (Govindan et al., 2013 ; Sarkar et al., 2020 ; Vandchali et al., 2021a, 2021b).

Addressing the environmentally sustainable performance issues, and promoting green organizations, is a sustainable human resource management (HRM) approach that ensures the sustainable development of organizations and can be achieved by adopting new ecological techniques by using innovative strategies and the human capital of organizations (Chams and García-Blandón, 2019 ). However, companies need to have competent employees who have passion, knowledge, and skills to manage environmental issues. Integrating green management and HRM can be considered a green revolution in traditional principles of HRM, motivating the scientific society in the field of green human resource management (GHRM) (Ansari et al., 2021 ; Al-Ghazali and Afsar, 2021 ; Nejati et al., 2017 ; Jabbour, 2011 and 2013 ; Dutta, 2012 ; Gholami et al., 2016 ; Sarkis, 2012 ; Yu et al., 2020 ). Effective environmental management and a company’s competitiveness are dependent on HRM (Ehnert, 2009 ; Phipps et al., 2013 ; Pohjola, 2001 ). GHRM is defined in HRM practices, including green employment, green learning, green performance, and green services compensation (Zaid et al., 2018a ). Masri and Jaaron ( 2017a , b ) defined GHRM in terms of HRM actions that lead to increased HR commitments to sustainable environmental practices (Masri and Jaaron, 2017a , b ). GHRM is an approach to extend the scope of HRM applications to minimize the damages that may be caused by the activities of the firms in all business processes (Zaid et al., 2018b ).

The employees’ environmentally friendly behavior will improve the companies’ sustainable performance (Lo et al., 2012 ). GHRM practices affect employees’ environmentally friendly behavior to achieve environmental sustainability (Kim et al., 2019 ). Implementing GHRM practices can ensure the success of the environmental performance of an organization that has a key role in developing organizational sustainability (Pham et al., 2020a ). GHRM practices as an approach for sustainable development objectives of the organization facilitate the implementation of green practices and policies by various practices of compensation, recruitment, rewards, and exit policies (Nisar et al., 2021a , b ). Greening an organization is a novel shift that requires commitment from both the management and the employees. It does not happen only by practices affected by GHRM but also by the improvement of green behaviors among the members of an organization (DuBois and Dubois, 2012 ).

Recently, many academicians and practitioners have focused on the importance of employing competent, qualified, and skillful employees as an effective way to achieve sustainable performance through GHRM (Yong et al., 2019a , b ). Reviewing the related literature shows that manufacturing and service companies use GHRM to improve their sustainable environmental performance (Raut et al., 2020 ). Scholars and practitioners such as Ghouri, Mani, Khan, Khan, and Srivastava ( 2020 ), Siyambalapitiya et al. ( 2018 ), Gilal et al. ( 2019 ), and Nisar et al. ( 2021a , b ) tried to extend the GHRM practices into the different manufacturing and service industries. Ghouri et al. ( 2020 ) assessed the key determinants of GHRM and investigate its impact on environmental performance and business performance in the Malaysian manufacturing industry. Siyambalapitiya et al. ( 2018 ) proposed a model for GHRM in Sri Lanka’s tourism industry; Gilal et al. ( 2019 ) extended GHRM practices into the higher education institutions. Recently, Nisar et al. ( 2021a , b ) investigated the role of green intellectual capital and pro-environmental behavior in Malaysian hotels. An integrated data envelopment analysis (DEA) and life cycle assessment (LCA) technique were offered by Tavana et al. ( 2021 ) to conduct the performance measurement in green construction management.

The construction industry is known for its high impact on the environment which ingests more than 40% of the total global energy and results in more than 40% of total global GHG emissions (Yin and Li, 2019 ). However, there is a lack of research in finding the appropriate GHRM initiatives in the construction industry (Buckly and Kalarickal, 2005; Takahashi, 2009; Shinkareva et al., 2020). The construction certainly harms the environment; it can arise from the non-green human behaviors toward environmental degeneration. Organizations can reduce environmental degradation by expanding the scope of GHRM practices (Yong et al., 2019a , b . Construction companies have always been on the front line as a result of the environmental impacts caused by their construction activities (Luciano et al., 2021 ). This motivates them to increase their environmental practices to address environmental concerns. Therefore, there is a need for paying attention to GHRM in the construction industry. This paper designs a model for GHRM in the field of construction to maintain equal opportunities for current and future generations to effectively use environmental resources. The main contributions of the paper are outlined as follows:

Designing a GHRM model for the construction industry,

Enriching the GHRM literature by developing GHRM for the construction industry,

Using a hybrid approach based on meta-synthesis, Delphi, and SEM method to design and verify the GHRM model for the construction industry,

Providing managerial insights to the companies in the construction industry to reach sustainable performance by presenting a model of effective GHRM factors in the construction industry.

The rest of this paper is structured as follows: in the “ Literature review ” section, the GHRM literature is reviewed and related components are defined. The research methodology and the related phases are presented in the “ Research methodology ” section. In the “ Data analysis and presenting the findings ” section, the data are analyzed and the GHRM model is developed. Finally, conclusions, managerial insights, and future directions are presented in the “ Discussion and conclusions ” section.

Literature review

Using the meta-synthesis method, GHRM literature from 2011 to 2021 is extensively reviewed. Although the starting date of using GHRM-related concepts in the construction industry refers to 2004 by Tam et al. ( 2004 ), the number of papers before 2011 is very low. Therefore, the year 2011 was selected as the starting point for collecting the relevant data and the year 2021 was selected as the endpoint. This specific duration has been employed to include the most recent research studies in view of the increase in publications that have addressed this highly important topic. The results of the literature review are elaborated in the following sections.

Green human resource management

With the formation of the HRM term, Jackson et al. ( 2011 ) conducted the first specific HRM review. They highlighted the critical role of HRM activities in assisting leading companies to move towards environmental policies and strategies. However, the number of works in this field has increased in recent years. Table 1 provides several definitions of GHRM in different studies.

According to the above-mentioned definitions by various authors, GHRM consists of traditional HR operations (e.g., job evaluation, employment, education, performance, and rewards measurement) in which the main focus is on environmental purposes and strategic aspects of the HRM (Jabbour et al., 2010 ). By focusing on the environmental criteria, Raut et al. ( 2020 ) analyzed the HR performance in the electronic service sector in India. Using the interpretive structural modeling method (ISM method) and the MICMAC analysis, they found that green organizational culture and green development and education are the most effective green human resources in India’s electronic service sector. Singh et al. ( 2020 ) investigated the impacts of GHRM on 309 active small and medium-sized companies. The results showed a significant relationship between GHRM and environmental performance. Yong et al. ( 2019a , b ) reviewed the GHRM literature from 2007 to 2019 and by reviewing 70 papers, they found that GHRM has significant impact on the individual and organizational environmental performances. Furthermore, there has been more interest in analyzing GHRM in developing countries. Siyambalapitiya et al. ( 2018 ) identified GHRM practices, which impacted environmental management in the Sri Lanka tourism sector. The results showed that green employment is the most important factor in their environmental management system. Masri and Jaaron ( 2017a , b ) examined the impacts of GHRM on manufacturing companies in Palestine. They reviewed 110 manufacturing companies including food, chemical, and medicines manufacturers to recognize the effective practices of GHRM in environmental performance. The qualitative part of the research identified 6 components of the GHRM, including green employment, green education and development, green performance management, green rewards and service compensation, green empowerment and participation, and green organizational culture management. The quantitative part of their research showed that the “green employment” and “green learning and development” factors had the highest and the lowest impacts on the companies’ environmental performance. Rayner and Morgan ( 2018 ) evaluated the employees’ environmental knowledge and measured their understanding of their ability, motivation, and opportunities. Collecting data from 394 employees of 5 Australian companies, they found that positive environmental ability, motivation, and opportunity might lead to green behavior, and it is more common at home compared to being at work. Tang et al. ( 2018 ) designed a tool for measuring five components of GHRM including green employment, green education, green performance management, green paying and rewards, and green participation. Dumont et al. ( 2017 ) investigated the impacts of GHRM practices on green behavior by highlighting the intermediary role of the green organizational atmosphere and individual green values. They collected data from a Chinese and an Australian multinational company. The results showed that the green organizational atmosphere and individual green values have direct and indirect impacts on the green behaviors of the employees. Arulrajah et al. ( 2016 ) reviewed the respective green twelve tasks of HRM including the job description, job analysis, HR planning, employment, choices, inculcation, performance measurement, education and development, disciplinary management, health, and safety management, and employee’s communication.

Components of GHRM

A review of GHRM literature demonstrated that 9 GHRM components such as green organizational culture, green recruitment, and selection, green employee involvement, green employee empowerment, green performance management, green reward, health and safety management, green discipline management, green training, and development are the widely used components. Table 2 provides more details about the GHRM components.

Research methodology

The present study aims to present a model for contributing factors of GHRM in the construction industry. As shown in Fig. 1 , this study used a mixed-method including meta-synthesis, Delphi, and SEM methods, to design a model for GHRM in the construction industry. The proposed methodology can lead to more reliable and valid results through utilizing the strengths and mitigating the weaknesses of qualitative and quantitative methods. Furthermore, it can provide detailed and contextualized insights into qualitative data and also generalizable and externally valid insights into quantitative data. As demonstrated in the first phase (cf. “ Literature review ” section), an in-depth literature review was conducted through the meta-synthesis method to identify GHRM contributing factors. In the second phase, Delphi method is used in two rounds to present the initial GHRM model. Finally, in the last phase, SEM methods based on partial least square (PLS) are employed to validate the initial model. In the following, the implementation steps of each phase are described. Figure 1 also explains the three phases of the research.

General framework of the research

Identifying GHRM factors through the meta-synthesis method

Using seven steps of the Sandelowski and Barroso (2016) pattern in the first phase, we identified GHRM components from the related literature between 2011 and 2021. The steps of the meta-synthesis method are presented in the following:

Determining research question : The first step of the meta-synthesis method is to develop the main research question.

Reviewing the literature in a systematic way : After determining the relevant keywords, a comprehensive search is performed at a specific time interval for relevant articles in various databases such as Web of Science and Scopus.

Evaluating and selecting the suitable papers : A tool used for evaluating the quality of primary perusal of the qualitative research is called critical appraisal skills programme (CASP) tool. The papers were first evaluated and rated based on 10 criteria/questions as shown in Table 3 . The maximum score of every criterion/question was considered 5. Then, the sum of the scores that each paper earned was calculated accordingly and the papers which the sum of their scores was less than 25 were eliminated.

Extracting results : In this step, we used a research question to extract the relevant codes from the selected papers.

Analyzing and synthesizing the qualitative findings : After extracting the codes, it is time to analyze, synthesize, and categorize the identified codes.

Quality control : This step is about assessing the validity and internal reliability of the study’s results. The validity of the research and coding process was assessed by academicians and industry experts. To assess the internal reliability of the coding process Cohen’s Kappa coefficient was used.

Presenting the findings : This is the final step of the suggested meta-synthesis and the findings from the previous steps are presented. The main finding of this study; i.e., the GHRM model in the construction industry is represented by Fig. 5 .

Adopting and customizing the identified GHRM factors with the construction industry through the Delphi method

In this phase, we utilized the experience of 15 industry experts with at least 10 years of experience in the field of the construction industry and GHRM principles in two rounds:

Round 1. Surveying the industry experts’ opinion about the degree of relevance of extracted factors with the construction industry using 1 to 10. The purpose of this round is to eliminate those codes which are irrelevant or less relevant to the activities in the construction industry. Firstly, a list of the extracted codes was given to the experts. Next, the experts were asked to select the components which are compatible with the industry. Then, the sum of every code’s score, which is equivalent to the sum of the experts’ votes, was calculated. Those codes in which the sum of votes was less than the average votes received from the experts were eliminated from the list.

Round 2. Surveying the industry experts’ opinion about the importance of each criterion using 1 to 5 . In this round, it was asked from the experts to specify the degree of necessity and importance of the remained codes which may lead to achieving the research purposes.

Validating the proposed model using SEM method

Finally, we validated the proposed model using SEM and second-order confirmatory factor analysis. To this end, we surveyed 229 managers from 33 Iranian construction companies using a 5 points Likert scale questionnaire. Then, we presented the final model of GHRM for the construction industry by conducting to the following steps:

Step 1. Measurement model : To assure that SEM can be effectively applied to our model, the validity and reliability of the results are examined. Composite reliability ( CR  ≥ 0.7) and average variance extracted ( AVE  ≥ 0.5) are two required factors for the convergent validity and construct correlation (Lin and Huang, 2009 ). The difference between measures of a construct and other constructs’ measures will be compared via the convergent validity. To assess the divergent validity of the survey instrument, we used a matrix that the square root of AVE for each construct is placed in the main diagonal of the matrix and correlation among the constructs is reported at bottom of the main diagonal. If the square root of AVE for a construct is greater than the correlation coefficient of the construct with other constructs, then the divergent validity will be accepted.

Step 2. Structural model : The structural model is utilized to evaluate the relationship between the latent variables. To test the relationship between the latent variables, we ran a bootstrapping procedure with a resampling rate of 500 (Hair et al., 2017 ) to obtain the t values. If the t value between two constructs is larger than |1.96|, then the relationship between them will be significant (Esposito Vinzi et al., 2010 ).

Data analysis and presenting the findings

We analyzed findings in 3 consecutive phases using the three above-mentioned methods and the results are elaborated in the following sections.

Data analysis using the meta-synthesis method

The primary green HRM model is developed by reviewing papers from the related literature using the meta-synthesis method in 7 steps.

Step 1 . Since we intended to find the various components of a suitable GHRM model, we developed our research questions as:

What is the suitable GHRM model for the construction industry?

Step 2 . We focused on English-written papers during the 10 recent years (2011 to 2021). The books, thesis, and conference proceedings papers were not included in this study’s statistical population. The main keywords employed by this study include green human resource management, green HRM, green human resource, human factors, green practices, green training, and environmental HRM.

Step 3 . As a result of evaluating the papers through the CASP, 39 papers are selected for further analysis. As shown in Fig. 2 , the procedure of filtering papers was based on their title, abstract, methodology, and the full content of papers.

Refinement of the papers using the CASP method

Steps 4 and 5 . After selecting the suitable papers, we used research questions to related extract codes from the texts. By reviewing 39 selected papers, we identified 44 primary codes which were categorized into 9 concepts.

Step 6 . To evaluate the extracted codes, 2 experts’ opinions were utilized. The study’s processes were considered with 10 questions which had a scale that consisted of 4 choices (1 = weak, 2 = middle, 3 = good, and 4 = excellent) by two experts, and Cohen’s kappa coefficient among the opinions of the experts was calculated by SPSS-26 software as shown in Table 4 . Cohen’s kappa coefficient is 0.706, and it indicates the reliability of the study’s results.

Step 7 . The extracted model from the literature, which consists of 38 codes and 9 concepts, is presented in Fig. 3 .

Primary model of GHRM (extracted from literature)

Delphi method for screening and adaption of the GHRM components

In this phase, the Delphi method in two rounds is used to investigate GHRM codes with the nature of the construction industry’s activities. The following sections provide more information about the two rounds of the Delphi method:

Round 1 . In this round, those codes in which the sum of votes was less than 8.71 were eliminated from the list. As shown in Table 5 , we see that in the first round, C 14 , C 21 , C 24 , C 25 , C 32 , C 33 , C 34 , C 41 , C 45 , C 46 , C 71 , C 72 , C 73 , and C 93 codes were eliminated from the list due to their incompatibilities with the nature of the construction industry’s activities. The second round was begun with the 24 remaining codes.

Round 2 . In the second round, it was asked from the experts to specify the degree of necessity and importance of the 24 codes which may lead to achieving the GHRM purposes and then lead to sustainable environmental performance. Table 6 shows the 5 points Likert scale with corresponding verbs. Then, the completed questionnaire from each expert is collected, and the results are presented in Table 7 . The second round aimed to identify the important key codes in which the experts had a minor disagreement. Therefore, we used the coefficient of variation (CV), and the CV among experts’ votes was calculated. Finally, the codes whose CV was more than the average of the total CVs (number 0.1921) were eliminated. In the final step, 3 codes that there was a major disagreement among the experts were eliminated, and further analysis was performed with 21 remaining codes.

Structural equation model to validate the proposed model

I. Measurement model . As shown in Table 8 , all CR values are greater than 0.7, and the values of AVE are more than 0.5. This indicates that the convergent validity of the questionnaire is acceptable. As shown in Table 9 , all the values in the main diagonal are greater than the values at the bottom of the main diagonal. This indicates the divergent validity of the survey instrument is acceptable.

In addition to the acceptable value of the Cronbach’s alpha for this study, we used the factor loading in the PLS method to evaluate the reliability of the questionnaire. The results showed that the coefficients of factor loading among measures and corresponding constructs are more than 0.4, indicating the reliability of the survey instrument is acceptable.

II. Structural model . After receiving acceptable results for the measurement of reliability and validity, the relationships among the latent variables are analyzed via the structural model. Figure 4 shows the coefficients among the latent variables.

t coefficients

As shown in Fig. 4 , t coefficients among two constructs including green organizational culture (C 1 ) and green involvement (C 3 ) are less than 1.96, which represent no significant relationship between them. Except for the two mentioned constructs, t coefficients among the other first and second-ordered constructs are more than 1.96, indicating a significant relationship between these constructs. By eliminating the green organizational culture construct (C 1 ) and green education and development construct (C 3 ), the final GHRM model in the construction industry is presented in Fig. 5 .

Final model of GHRM in the construction industry

Discussion and conclusions

The originality of this paper lies in the presentation of a GHRM model for the construction industry that is the first GHRM model which is applied in the construction industry. This model indicates the contributing components in GHRM for the construction industry. To construct this model, an in-depth literature review is conducted and contributing components of GHRM were identified and the primary model of GHRM was presented. Then, using the Delphi method in two rounds, the GHRM components were adopted and customized with the construction industry. Finally, to validate the GHRM model, the data were collected from the managers of the construction industry through the questionnaire and were analyzed using SEM and SmartPLS3 software. In the rest of the paper, we discuss theoretical contributions, managerial implications, as well as study limitations and some future directions.

Theoretical contributions

The findings indicated that among 9 main GHRM components extracted from the literature, just 5 components including green recruitment and selection, green performance management, green reward, green-based employee empowerment, and green training have statistically significant and positive relationships with GHRM. The findings imply that green recruitment is one of the basic and the most important components of GHRM that can influence the other components. Considering green criteria in recruitment can lead companies to environmentally sustainable performance through hiring employees who are aware of the environmental issues. This finding agrees with Masri and Jarron (2017), Zhang et al. ( 2019 ), and Yong et al. ( 2020 ). It has been also discussed and demonstrated by many other researchers such as Samar Ali et al. ( 2019 ), Graczyk-Kucharska et al. ( 2021 ), Das et al. ( 2020 , 2021 ), Mondal and Roy ( 2021 ), Midya et al. ( 2021 ), Tirkolaee and Aydın ( 2021 ), Dabic-Miletic et al. ( 2021 ), and Jahani et al. ( 2021 ).

The results of data analysis revealed that there is a significant and positive relationship between green performance management and GHRM. Clarifying green criteria in evaluating employees’ performance and emphasizing green criteria in performance assessment can force employees to improve their environmental performance. Besides, providing regular feedback is one of the factors influencing continuous improvement in environmental performance. These findings are in line with Zaid et al. ( 2018b ), Masri and Jaaron ( 2017a , b ), and Harvey et al. ( 2013 ). Green performance and appraisal can guide employees to achieve the desired environmental performance (Ahmad, 2015 ). Providing regular feedback will enhance employees’ environmental knowledge and skills that have a significant effect on improving environmental performance (Arulrajah et al., 2016 ; Jackson et al., 2011 ).

The finding implies that there is a significant and positive relationship between green reward and GHRM. Among the other GHRM practices, reward is often considered the most important practice that can bring the company’s interest and employee’s interest closer together (Jackson et al., 2011 ). In some cases, just monetary and non-monetary rewards can motivate employees to improve their environmental performance (Danish, and Usman, 2010 ). This finding of the current study supports Renwick, Redman, and Maguire’s ( 2013 ) finding of the effect of reward on increasing employees’ willingness to improve their environmental performance. To encourage employees to participate in the company’s environmental strategies, managers not only should consider rewards for innovative environmental performance but also they have to consider rewards for innovative environmental suggestions (Masri and Jaaron, 2017a , b ).

The finding of this study demonstrated that green-based employee empowerment is one of the main components of GHRM in the construction industry. This finding agrees with Daily et al. ( 2012 ) and Masri and Jaaron ( 2017a , b ). Some practices such as teamwork by increasing the employees’ awareness about environmental issues can empower them and improve their environmental performance (Boiral, 2009 ; Masri and Jaaron, 2017a , b ; Jabbour, 2011 ). One way to empower employees regarded environmental issues is to involve them in formulating corporate environmental strategies (Yong et al., 2020 ). Holding workshops can increase employees’ environmental performance. Also, encouraging employees to participate in the company’s greening programs can help to hear the voice of employees and may make a big improvement in the company’s environmental performance.

The data analysis results indicated a significant and positive relationship between green training and GHRM. Green training can provide the necessary knowledge for employees about environmental issues (Jabbour, et al., 2010 ). Yong et al. ( 2020 ) found a significant and positive relationship between green training and employees’ environmental performance by conducting a study on 112 Malaysian manufacturing companies. Green training has a positive impact on employees’ environmental knowledge and performance and can be used when the companies want to change employees’ attitudes and increase awareness about environmental issues (Sammalisto and Brorson, 2008 ). In this study, the knowledge of employees about environmental issues in construction companies was at a low level. There is a need to provide a training opportunity for employees and give the priority to green training programs as the first and fundamental step to achieve environmentally sustainable performance.

Managerial implications

Aside from the theoretical contribution of our research, there are several managerial implications that can help the practitioners to make effective environmental policies in order to reach environmentally sustainable performance in their companies. This section provides the key points for managers of construction companies. According to the managers of Iranian construction companies, there are not enough knowledge and awareness about environmental issues in the construction industry. In other words, when the construction company managers want to implement GHRM practices, they do not know how and from where they should start to implement GHRM practices. From a practical perspective, the model presented in this study can be used as a roadmap for the managers of construction companies to increase their companies’ environmentally sustainable performance. The final proposed model indicates the effective factors of GHRM practices including green recruitment and selection, green performance management, green reward, green-based employee empowerment, and green training in the construction industry. Therefore, according to the presented model, managers can decide about investing in which areas to gain maximum results about implementing GHRM practices.

The result of this research revealed that “green reward” is the most effective factor of GHRM. Therefore, it is proposed to the managers of construction companies to motivate employees to improve their green performance or provide innovative environmental suggestions. According to the model, “green performance management” was identified as the second effective factor of GHRM. Therefore, the managers of Iranian construction companies should improve employees’ green performance through determining green criteria in performance assessment and giving regular feedback on their environmental performance. The construction industry in Iran is reported to have poor knowledge and awareness about environmental issues, therefore, the government should give the first priority to environmental issues in the construction industry by providing infrastructures and opportunities for green training. Inviting some experts from leading countries in order to teach environmental issues to Iranian employees is proposed.

Limitations and future directions

Although the main goal of this paper was addressed as expected, and the first GHRM model for the construction industry was presented, there are some limitations. For instance, the main limitation of the current study, which is the reason for the next limitation, is the use of cross-sectional data to evaluate and test the proposed model. The data used in this research were collected over a period of time, therefore, it was not possible to access the objective data. For example, in this study, there was no longitudinal data to evaluate the outputs of green training or green reward in construction companies. Because so far, no evaluation has been done on the results of holding green training and the data only reflects the opinion of managers in this regard. Therefore, it is suggested that in future research, if possible, longitudinal and multi-sectional data be used to test the proposed model.

Since the data were collected from 33 Iranian construction companies, the results of this study may not be generalizable to other industries. Therefore, a cross-country study may enhance the generalizability of the findings and may affect the results. Besides, we suggest future research test the proposed model by collecting data from other industries and comparing the results with the results of this research. Furthermore, in future research, the effect of GHRM components on sustainable performance can be examined and using importance-performance map analysis, the existing gaps between current and ideal situations of each of the GHRM components can be identified. Then, according to the location of each component in the importance-performance matrix, some practical strategies to eliminate or reduce gaps can be proposed. Finally, in future research in order to weigh and prioritize the contributing factors of GHRM, multi-criteria decision-making methods such as AHP and BWM can be used.

Conclusions

In developing countries such as Iran, housing is one of the most important concerns of people and governments. Therefore, the construction industry contributes to providing fair conditions for people to have housing as one of their basic needs. On the other hand, the lack of familiarity of construction industry managers with environmental issues led the authors to examine the current state of the construction industry in terms of environmental issues and provide some practical solutions to achieve the ideal conditions. Given the prominent role of human resources in this industry, we examined a model of GHRM was examined for the construction industry.

In fact, a hybrid approach including three phases was utilized to design and test a GHRM model in the construction industry. Using the meta-synthesis approach in the first phase, an in-depth and extensive review was conducted on the related GHRM literature. As a result, a three-level model of green supply chain management concepts and codes including 9 components and 38 indicators was designed as the initial model. In the second phase, to adapt and customize the initial model with the nature of the activity of the studied industry, the Delphi method was used. During two rounds of repetition in the Delphi method, a total of 2 concepts and 17 codes were removed from the initial model process and the third phase began with 7 concepts and 21 remaining codes. Using the SEM method in this phase, a three-level model of GHRM in the construction industry is developed which includes 5 main components. It implies that HR managers in construction companies should focus on green recruitment and selection, green performance management, green reward, green-based employee empowerment, and green training to achieve sustainability.

Despite the limitations, this work is the first study that considered GHRM in the construction industry can have a significant role in the sustainability of Iranian construction companies. Furthermore, many of the findings in the present study throw up interesting contradictions to the existing literature. For example, the finding of this study indicated that green organizational culture has no significant role in GHRM in the construction industry. Thus, there is a need for future research in this industry in other developing or developed countries and compare the findings with our findings to resolve barriers to sustainable construction as much as possible (Pham et al., 2020b ).

Author contribution

SSD: formulating idea, writing, methodology, and investigation. FMM: methodology, writing, and original draft preparation. SA: validation, literature review, and software. HRV: reviewing, supervision, and investigation. EBT: editing, supervision, and investigation.

Data availability

Not applicable.

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Darvazeh, S.S., Mooseloo, F.M., Aeini, S. et al. An integrated methodology for green human resource management in construction industry. Environ Sci Pollut Res 30 , 124619–124637 (2023). https://doi.org/10.1007/s11356-022-20967-8

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Received : 30 January 2022

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DOI : https://doi.org/10.1007/s11356-022-20967-8

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