research project on capital structure

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5 Capital Structure and Financing Decisions

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• Published: December 2010
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This chapter reviews the findings of academic surveys of corporate executives indicating how firms make capital structure and financing decisions. The chapter compares the survey findings to the theoretically correct methods and applications described and recommended in the academic literature. The chapter describes five theoretical capital structure models: static tradeoff, pecking order, signaling, agency cost, and neutral mutation. It then reviews the survey literature that tests the connections between these normative theories and corporate practice. Some survey studies find evidence that one or more theories tend to explain capital structure decisions. Other surveys find evidence that financial planning rules-of-thumb (e.g. financial flexibility, long-term survivability, and impact on security prices) are the primary guides for firms making capital structure decisions. While most studies discussed here focus on large U.S. firms, many focus on non-U.S. firms, and small U.S. firms.

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• Corporate Finance
• Corporate Finance Basics

Optimal Capital Structure Definition: Meaning, Factors, and Limitations

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and behavioral finance. Adam received his master's in economics from The New School for Social Research and his Ph.D. from the University of Wisconsin-Madison in sociology. He is a CFA charterholder as well as holding FINRA Series 7, 55 & 63 licenses. He currently researches and teaches economic sociology and the social studies of finance at the Hebrew University in Jerusalem.

What Is Optimal Capital Structure?

The optimal capital structure of a firm is the best mix of debt and equity financing that maximizes a company’s market value while minimizing its cost of capital. In theory, debt financing offers the lowest cost of capital due to its tax deductibility. However, too much debt increases the financial risk to shareholders and the return on equity that they require. Thus, companies have to find the optimal point at which the marginal benefit of debt equals the marginal cost.

Key Takeaways

• An optimal capital structure is the best mix of debt and equity financing that maximizes a company’s market value while minimizing its cost of capital.
• Minimizing the weighted average cost of capital (WACC) is one way to optimize for the lowest cost mix of financing.
• According to some economists, in the absence of taxes, bankruptcy costs, agency costs, and asymmetric information, in an efficient market, the value of a firm is unaffected by its capital structure.

Investopedia / Michela Buttignol

Understanding Optimal Capital Structure

The optimal capital structure is estimated by calculating the mix of debt and equity that minimizes the weighted average cost of capital (WACC) of a company while maximizing its market value. The lower the cost of capital, the greater the present value of the firm’s future cash flows, discounted by the WACC. Thus, the chief goal of any corporate finance department should be to find the optimal capital structure that will result in the lowest WACC and the maximum value of the company (shareholder wealth).

According to economists  Franco Modigliani and  Merton Miller , in the absence of taxes, bankruptcy costs, agency costs, and asymmetric information, in an efficient market, the value of a firm is unaffected by its capital structure.

Optimal Capital Structure and WACC

The cost of debt is less expensive than equity because it is less risky. The required return needed to compensate debt investors is less than the required return needed to compensate equity investors, because interest payments have priority over dividends, and debt holders receive priority in the event of a liquidation. Debt is also cheaper than equity because companies get tax relief on interest, while dividend payments are paid out of after-tax income.

However, there is a limit to the amount of debt a company should have because an excessive amount of debt increases interest payments, the volatility of earnings, and the risk of bankruptcy. This increase in the financial risk to shareholders means that they will require a greater return to compensate them, which increases the WACC—and lowers the market value of a business. The optimal structure involves using enough equity to mitigate the risk of being unable to pay back the debt—taking into account the variability of the business’s cash flow .

Companies with consistent cash flows can tolerate a much larger debt load and will have a much higher percentage of debt in their optimal capital structure. Conversely, a company with volatile cash flows will have little debt and a large amount of equity.

Determining the Optimal Capital Structure

As it can be difficult to pinpoint the optimal capital structure, managers usually attempt to operate within a range of values. They also have to take into account the signals their financing decisions send to the market.

A company with good prospects will try to raise capital using debt rather than equity, to avoid dilution and sending any negative signals to the market. Announcements made about a company taking debt are typically seen as positive news, which is known as debt signaling . If a company raises too much capital during a given time period, the costs of debt, preferred stock, and common equity will begin to rise, and as this occurs, the marginal cost of capital will also rise.

To gauge how risky a company is, potential equity investors look at the debt/equity ratio . They also compare the amount of leverage other businesses in the same industry are using—on the assumption that these companies are operating with an optimal capital structure—to see if the company is employing an unusual amount of debt within its capital structure.

Another way to determine optimal debt-to-equity levels is to think like a bank. What is the optimal level of debt a bank is willing to lend? An analyst may also utilize other debt ratios to put the company into a credit profile using a bond rating. The default spread attached to the bond rating can then be used for the spread above the risk-free rate of a AAA-rated company.

Limitations of Optimal Capital Structure

Unfortunately, there is no magic ratio of debt to equity to use as guidance to achieve real-world optimal capital structure. What defines a healthy blend of debt and equity varies according to the industries involved, line of business, and a firm's stage of development, and can also vary over time due to external changes in interest rates and regulatory environment.

However, because investors are better off putting their money into companies with strong balance sheets, it makes sense that the optimal balance generally should reflect lower levels of debt and higher levels of equity.

Theories on Capital Structure

Modigliani-miller (m&m) theory.

The Modigliani-Miller (M&M) theorem is a capital structure approach named after Franco Modigliani and Merton Miller. Modigliani and Miller were two economics professors who studied capital structure theory and collaborated to develop the capital structure irrelevance proposition in 1958.

This proposition states that in perfect markets, the capital structure a company uses doesn't matter because the market value of a firm is determined by its earning power and the risk of its underlying assets. According to Modigliani and Miller, value is independent of the method of financing used and a company's investments.  The  M&M theorem  made the two following propositions:

Proposition I

This proposition says that the capital structure is irrelevant to the value of a firm. The value of two identical firms would remain the same and value would not be affected by the choice of financing adopted to finance the assets. The value of a firm is dependent on the expected future earnings. It is when there are no taxes.

Proposition II

This proposition says that the financial leverage boosts the value of a firm and reduces WACC. It is when tax information is available. While the Modigliani-Miller theorem is studied in finance, real firms do face taxes, credit risk, transaction costs, and inefficient markets, which makes the mix of debt and equity financing important.

Pecking Order Theory

The pecking order theory focuses on asymmetrical information costs. This approach assumes that companies prioritize their financing strategy based on the path of least resistance. Internal financing is the first preferred method, followed by debt and external equity financing as a last resort.

Modigliani, Franco, and Merton H. Miller. " The Cost of Capital, Corporation Finance and the Theory of Investment ." The American Economic Review , vol. 48, no. 3, 1958, pp. 261-297.

Modigliani, Franco, and Merton H. Miller. " The Cost of Capital, Corporation Finance and the Theory of Investment ." The American Economic Review , vol. 48, no. 3, 1958, pp. 268-271.

Modigliani, Franco, and Merton H. Miller. " The Cost of Capital, Corporation Finance and the Theory of Investment ." The American Economic Review , vol. 48, no. 3, 1958, pp. 271-276.

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ISSN : 0969-9988

Article publication date: 2 June 2021

Issue publication date: 31 May 2022

With the majority of highway projects in China having entered their operational phases, the maintenance and repair of the pavement is receiving increasing attention. One problem that needs to be addressed urgently is that of how to raise the proper funds for highway maintenance to ensure the sustainable operation of the project. To this end, the aim of this study is to investigate the capital demand for operation and maintenance of a project by means of a refinancing scheme, in order to reduce the possibility of project bankruptcy and to enhance the economic value of the project.

Design/methodology/approach

Based on an analysis of the dynamic complexity of the highway pavement maintenance system, a Markov model is used to predict pavement performance, and an optimal capital structure decision model is proposed for highway public–private partnership (PPP) project refinancing, using the method of system dynamics (SD). The proposed model is then applied to a real case study.

Results show that the proposed model can be used to predict accurately the dynamic changes in the demand for road maintenance funds and refinancing during the period of operation, before making the optimal decision for the refinancing capital structure.

Originality/value

Although many scholars have studied the optimal refinancing capital structure of PPP projects, the dynamic changes inherent in the demand for maintenance funds for highway PPP projects are seldom considered. Therefore, in the approach used here the influence of the dynamic change of road maintenance capital demand on refinancing is investigated, and SD is used for the optimal capital structure decision-making model of highway PPP project refinancing, to make the decision-making process more reasonable and scientific.

• Highway PPP project
• Highway pavement performance
• Refinancing capital structure
• System dynamics
• Markov model

Hou, W. and Wang, L. (2022), "Research on the refinancing capital structure of highway PPP projects based on dynamic capital demand", Engineering, Construction and Architectural Management , Vol. 29 No. 5, pp. 2047-2072. https://doi.org/10.1108/ECAM-05-2020-0321

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Copyright © 2021, Emerald Publishing Limited

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McKinsey Global Private Markets Review 2024: Private markets in a slower era

At a glance, macroeconomic challenges continued.

McKinsey Global Private Markets Review 2024: Private markets: A slower era

If 2022 was a tale of two halves, with robust fundraising and deal activity in the first six months followed by a slowdown in the second half, then 2023 might be considered a tale of one whole. Macroeconomic headwinds persisted throughout the year, with rising financing costs, and an uncertain growth outlook taking a toll on private markets. Full-year fundraising continued to decline from 2021’s lofty peak, weighed down by the “denominator effect” that persisted in part due to a less active deal market. Managers largely held onto assets to avoid selling in a lower-multiple environment, fueling an activity-dampening cycle in which distribution-starved limited partners (LPs) reined in new commitments.

About the authors

This article is a summary of a larger report, available as a PDF, that is a collaborative effort by Fredrik Dahlqvist , Alastair Green , Paul Maia, Alexandra Nee , David Quigley , Aditya Sanghvi , Connor Mangan, John Spivey, Rahel Schneider, and Brian Vickery , representing views from McKinsey’s Private Equity & Principal Investors Practice.

Performance in most private asset classes remained below historical averages for a second consecutive year. Decade-long tailwinds from low and falling interest rates and consistently expanding multiples seem to be things of the past. As private market managers look to boost performance in this new era of investing, a deeper focus on revenue growth and margin expansion will be needed now more than ever.

Perspectives on a slower era in private markets

Global fundraising contracted.

Fundraising fell 22 percent across private market asset classes globally to just over $1 trillion, as of year-end reported data—the lowest total since 2017. Fundraising in North America, a rare bright spot in 2022, declined in line with global totals, while in Europe, fundraising proved most resilient, falling just 3 percent. In Asia, fundraising fell precipitously and now sits 72 percent below the region’s 2018 peak.

Despite difficult fundraising conditions, headwinds did not affect all strategies or managers equally. Private equity (PE) buyout strategies posted their best fundraising year ever, and larger managers and vehicles also fared well, continuing the prior year’s trend toward greater fundraising concentration.

The numerator effect persisted

Despite a marked recovery in the denominator—the 1,000 largest US retirement funds grew 7 percent in the year ending September 2023, after falling 14 percent the prior year, for example 1 “U.S. retirement plans recover half of 2022 losses amid no-show recession,” Pensions and Investments , February 12, 2024. —many LPs remain overexposed to private markets relative to their target allocations. LPs started 2023 overweight: according to analysis from CEM Benchmarking, average allocations across PE, infrastructure, and real estate were at or above target allocations as of the beginning of the year. And the numerator grew throughout the year, as a lack of exits and rebounding valuations drove net asset values (NAVs) higher. While not all LPs strictly follow asset allocation targets, our analysis in partnership with global private markets firm StepStone Group suggests that an overallocation of just one percentage point can reduce planned commitments by as much as 10 to 12 percent per year for five years or more.

Despite these headwinds, recent surveys indicate that LPs remain broadly committed to private markets. In fact, the majority plan to maintain or increase allocations over the medium to long term.

Investors fled to known names and larger funds

Fundraising concentration reached its highest level in over a decade, as investors continued to shift new commitments in favor of the largest fund managers. The 25 most successful fundraisers collected 41 percent of aggregate commitments to closed-end funds (with the top five managers accounting for nearly half that total). Closed-end fundraising totals may understate the extent of concentration in the industry overall, as the largest managers also tend to be more successful in raising non-institutional capital.

While the largest funds grew even larger—the largest vehicles on record were raised in buyout, real estate, infrastructure, and private debt in 2023—smaller and newer funds struggled. Fewer than 1,700 funds of less than $1 billion were closed during the year, half as many as closed in 2022 and the fewest of any year since 2012. New manager formation also fell to the lowest level since 2012, with just 651 new firms launched in 2023.

Whether recent fundraising concentration and a spate of M&A activity signals the beginning of oft-rumored consolidation in the private markets remains uncertain, as a similar pattern developed in each of the last two fundraising downturns before giving way to renewed entrepreneurialism among general partners (GPs) and commitment diversification among LPs. Compared with how things played out in the last two downturns, perhaps this movie really is different, or perhaps we’re watching a trilogy reusing a familiar plotline.

Dry powder inventory spiked (again)

Private markets assets under management totaled $13.1 trillion as of June 30, 2023, and have grown nearly 20 percent per annum since 2018. Dry powder reserves—the amount of capital committed but not yet deployed—increased to $3.7 trillion, marking the ninth consecutive year of growth. Dry powder inventory—the amount of capital available to GPs expressed as a multiple of annual deployment—increased for the second consecutive year in PE, as new commitments continued to outpace deal activity. Inventory sat at 1.6 years in 2023, up markedly from the 0.9 years recorded at the end of 2021 but still within the historical range. NAV grew as well, largely driven by the reluctance of managers to exit positions and crystallize returns in a depressed multiple environment.

Private equity strategies diverged

Buyout and venture capital, the two largest PE sub-asset classes, charted wildly different courses over the past 18 months. Buyout notched its highest fundraising year ever in 2023, and its performance improved, with funds posting a (still paltry) 5 percent net internal rate of return through September 30. And although buyout deal volumes declined by 19 percent, 2023 was still the third-most-active year on record. In contrast, venture capital (VC) fundraising declined by nearly 60 percent, equaling its lowest total since 2015, and deal volume fell by 36 percent to the lowest level since 2019. VC funds returned –3 percent through September, posting negative returns for seven consecutive quarters. VC was the fastest-growing—as well as the highest-performing—PE strategy by a significant margin from 2010 to 2022, but investors appear to be reevaluating their approach in the current environment.

Private equity entry multiples contracted

PE buyout entry multiples declined by roughly one turn from 11.9 to 11.0 times EBITDA, slightly outpacing the decline in public market multiples (down from 12.1 to 11.3 times EBITDA), through the first nine months of 2023. For nearly a decade leading up to 2022, managers consistently sold assets into a higher-multiple environment than that in which they had bought those assets, providing a substantial performance tailwind for the industry. Nowhere has this been truer than in technology. After experiencing more than eight turns of multiple expansion from 2009 to 2021 (the most of any sector), technology multiples have declined by nearly three turns in the past two years, 50 percent more than in any other sector. Overall, roughly two-thirds of the total return for buyout deals that were entered in 2010 or later and exited in 2021 or before can be attributed to market multiple expansion and leverage. Now, with falling multiples and higher financing costs, revenue growth and margin expansion are taking center stage for GPs.

Real estate receded

Demand uncertainty, slowing rent growth, and elevated financing costs drove cap rates higher and made price discovery challenging, all of which weighed on deal volume, fundraising, and investment performance. Global closed-end fundraising declined 34 percent year over year, and funds returned −4 percent in the first nine months of the year, losing money for the first time since the 2007–08 global financial crisis. Capital shifted away from core and core-plus strategies as investors sought liquidity via redemptions in open-end vehicles, from which net outflows reached their highest level in at least two decades. Opportunistic strategies benefited from this shift, with investors focusing on capital appreciation over income generation in a market where alternative sources of yield have grown more attractive. Rising interest rates widened bid–ask spreads and impaired deal volume across food groups, including in what were formerly hot sectors: multifamily and industrial.

Private debt pays dividends

Debt again proved to be the most resilient private asset class against a turbulent market backdrop. Fundraising declined just 13 percent, largely driven by lower commitments to direct lending strategies, for which a slower PE deal environment has made capital deployment challenging. The asset class also posted the highest returns among all private asset classes through September 30. Many private debt securities are tied to floating rates, which enhance returns in a rising-rate environment. Thus far, managers appear to have successfully navigated the rising incidence of default and distress exhibited across the broader leveraged-lending market. Although direct lending deal volume declined from 2022, private lenders financed an all-time high 59 percent of leveraged buyout transactions last year and are now expanding into additional strategies to drive the next era of growth.

Infrastructure took a detour

After several years of robust growth and strong performance, infrastructure and natural resources fundraising declined by 53 percent to the lowest total since 2013. Supply-side timing is partially to blame: five of the seven largest infrastructure managers closed a flagship vehicle in 2021 or 2022, and none of those five held a final close last year. As in real estate, investors shied away from core and core-plus investments in a higher-yield environment. Yet there are reasons to believe infrastructure’s growth will bounce back. Limited partners (LPs) surveyed by McKinsey remain bullish on their deployment to the asset class, and at least a dozen vehicles targeting more than $10 billion were actively fundraising as of the end of 2023. Multiple recent acquisitions of large infrastructure GPs by global multi-asset-class managers also indicate marketwide conviction in the asset class’s potential.

Private markets still have work to do on diversity

Private markets firms are slowly improving their representation of females (up two percentage points over the prior year) and ethnic and racial minorities (up one percentage point). On some diversity metrics, including entry-level representation of women, private markets now compare favorably with corporate America. Yet broad-based parity remains elusive and too slow in the making. Ethnic, racial, and gender imbalances are particularly stark across more influential investing roles and senior positions. In fact, McKinsey’s research  reveals that at the current pace, it would take several decades for private markets firms to reach gender parity at senior levels. Increasing representation across all levels will require managers to take fresh approaches to hiring, retention, and promotion.

Artificial intelligence generating excitement

The transformative potential of generative AI was perhaps 2023’s hottest topic (beyond Taylor Swift). Private markets players are excited about the potential for the technology to optimize their approach to thesis generation, deal sourcing, investment due diligence, and portfolio performance, among other areas. While the technology is still nascent and few GPs can boast scaled implementations, pilot programs are already in flight across the industry, particularly within portfolio companies. Adoption seems nearly certain to accelerate throughout 2024.

Private markets in a slower era

If private markets investors entered 2023 hoping for a return to the heady days of 2021, they likely left the year disappointed. Many of the headwinds that emerged in the latter half of 2022 persisted throughout the year, pressuring fundraising, dealmaking, and performance. Inflation moderated somewhat over the course of the year but remained stubbornly elevated by recent historical standards. Interest rates started high and rose higher, increasing the cost of financing. A reinvigorated public equity market recovered most of 2022’s losses but did little to resolve the valuation uncertainty private market investors have faced for the past 18 months.

Within private markets, the denominator effect remained in play, despite the public market recovery, as the numerator continued to expand. An activity-dampening cycle emerged: higher cost of capital and lower multiples limited the ability or willingness of general partners (GPs) to exit positions; fewer exits, coupled with continuing capital calls, pushed LP allocations higher, thereby limiting their ability or willingness to make new commitments. These conditions weighed on managers’ ability to fundraise. Based on data reported as of year-end 2023, private markets fundraising fell 22 percent from the prior year to just over $1 trillion, the largest such drop since 2009 (Exhibit 1).

The impact of the fundraising environment was not felt equally among GPs. Continuing a trend that emerged in 2022, and consistent with prior downturns in fundraising, LPs favored larger vehicles and the scaled GPs that typically manage them. Smaller and newer managers struggled, and the number of sub–$1 billion vehicles and new firm launches each declined to its lowest level in more than a decade.

Despite the decline in fundraising, private markets assets under management (AUM) continued to grow, increasing 12 percent to $13.1 trillion as of June 30, 2023. 2023 fundraising was still the sixth-highest annual haul on record, pushing dry powder higher, while the slowdown in deal making limited distributions.

Investment performance across private market asset classes fell short of historical averages. Private equity (PE) got back in the black but generated the lowest annual performance in the past 15 years, excluding 2022. Closed-end real estate produced negative returns for the first time since 2009, as capitalization (cap) rates expanded across sectors and rent growth dissipated in formerly hot sectors, including multifamily and industrial. The performance of infrastructure funds was less than half of its long-term average and even further below the double-digit returns generated in 2021 and 2022. Private debt was the standout performer (if there was one), outperforming all other private asset classes and illustrating the asset class’s countercyclical appeal.

Private equity down but not out

Higher financing costs, lower multiples, and an uncertain macroeconomic environment created a challenging backdrop for private equity managers in 2023. Fundraising declined for the second year in a row, falling 15 percent to $649 billion, as LPs grappled with the denominator effect and a slowdown in distributions. Managers were on the fundraising trail longer to raise this capital: funds that closed in 2023 were open for a record-high average of 20.1 months, notably longer than 18.7 months in 2022 and 14.1 months in 2018. VC and growth equity strategies led the decline, dropping to their lowest level of cumulative capital raised since 2015. Fundraising in Asia fell for the fourth year of the last five, with the greatest decline in China.

Despite the difficult fundraising context, a subset of strategies and managers prevailed. Buyout managers collectively had their best fundraising year on record, raising more than $400 billion. Fundraising in Europe surged by more than 50 percent, resulting in the region’s biggest haul ever. The largest managers raised an outsized share of the total for a second consecutive year, making 2023 the most concentrated fundraising year of the last decade (Exhibit 2).

Despite the drop in aggregate fundraising, PE assets under management increased 8 percent to $8.2 trillion. Only a small part of this growth was performance driven: PE funds produced a net IRR of just 2.5 percent through September 30, 2023. Buyouts and growth equity generated positive returns, while VC lost money. PE performance, dating back to the beginning of 2022, remains negative, highlighting the difficulty of generating attractive investment returns in a higher interest rate and lower multiple environment. As PE managers devise value creation strategies to improve performance, their focus includes ensuring operating efficiency and profitability of their portfolio companies.

Deal activity volume and count fell sharply, by 21 percent and 24 percent, respectively, which continued the slower pace set in the second half of 2022. Sponsors largely opted to hold assets longer rather than lock in underwhelming returns. While higher financing costs and valuation mismatches weighed on overall deal activity, certain types of M&A gained share. Add-on deals, for example, accounted for a record 46 percent of total buyout deal volume last year.

Real estate recedes

For real estate, 2023 was a year of transition, characterized by a litany of new and familiar challenges. Pandemic-driven demand issues continued, while elevated financing costs, expanding cap rates, and valuation uncertainty weighed on commercial real estate deal volumes, fundraising, and investment performance.

Managers faced one of the toughest fundraising environments in many years. Global closed-end fundraising declined 34 percent to $125 billion. While fundraising challenges were widespread, they were not ubiquitous across strategies. Dollars continued to shift to large, multi-asset class platforms, with the top five managers accounting for 37 percent of aggregate closed-end real estate fundraising. In April, the largest real estate fund ever raised closed on a record $30 billion.

Capital shifted away from core and core-plus strategies as investors sought liquidity through redemptions in open-end vehicles and reduced gross contributions to the lowest level since 2009. Opportunistic strategies benefited from this shift, as investors turned their attention toward capital appreciation over income generation in a market where alternative sources of yield have grown more attractive.

In the United States, for instance, open-end funds, as represented by the National Council of Real Estate Investment Fiduciaries Fund Index—Open-End Equity (NFI-OE), recorded $13 billion in net outflows in 2023, reversing the trend of positive net inflows throughout the 2010s. The negative flows mainly reflected $9 billion in core outflows, with core-plus funds accounting for the remaining outflows, which reversed a 20-year run of net inflows.

As a result, the NAV in US open-end funds fell roughly 16 percent year over year. Meanwhile, global assets under management in closed-end funds reached a new peak of $1.7 trillion as of June 2023, growing 14 percent between June 2022 and June 2023.

Real estate underperformed historical averages in 2023, as previously high-performing multifamily and industrial sectors joined office in producing negative returns caused by slowing demand growth and cap rate expansion. Closed-end funds generated a pooled net IRR of −3.5 percent in the first nine months of 2023, losing money for the first time since the global financial crisis. The lone bright spot among major sectors was hospitality, which—thanks to a rush of postpandemic travel—returned 10.3 percent in 2023. 2 Based on NCREIFs NPI index. Hotels represent 1 percent of total properties in the index. As a whole, the average pooled lifetime net IRRs for closed-end real estate funds from 2011–20 vintages remained around historical levels (9.8 percent).

Global deal volume declined 47 percent in 2023 to reach a ten-year low of $650 billion, driven by widening bid–ask spreads amid valuation uncertainty and higher costs of financing (Exhibit 3). 3 CBRE, Real Capital Analytics Deal flow in the office sector remained depressed, partly as a result of continued uncertainty in the demand for space in a hybrid working world.

During a turbulent year for private markets, private debt was a relative bright spot, topping private markets asset classes in terms of fundraising growth, AUM growth, and performance.

Fundraising for private debt declined just 13 percent year over year, nearly ten percentage points less than the private markets overall. Despite the decline in fundraising, AUM surged 27 percent to $1.7 trillion. And private debt posted the highest investment returns of any private asset class through the first three quarters of 2023.

Private debt’s risk/return characteristics are well suited to the current environment. With interest rates at their highest in more than a decade, current yields in the asset class have grown more attractive on both an absolute and relative basis, particularly if higher rates sustain and put downward pressure on equity returns (Exhibit 4). The built-in security derived from debt’s privileged position in the capital structure, moreover, appeals to investors that are wary of market volatility and valuation uncertainty.

Direct lending continued to be the largest strategy in 2023, with fundraising for the mostly-senior-debt strategy accounting for almost half of the asset class’s total haul (despite declining from the previous year). Separately, mezzanine debt fundraising hit a new high, thanks to the closings of three of the largest funds ever raised in the strategy.

Over the longer term, growth in private debt has largely been driven by institutional investors rotating out of traditional fixed income in favor of private alternatives. Despite this growth in commitments, LPs remain underweight in this asset class relative to their targets. In fact, the allocation gap has only grown wider in recent years, a sharp contrast to other private asset classes, for which LPs’ current allocations exceed their targets on average. According to data from CEM Benchmarking, the private debt allocation gap now stands at 1.4 percent, which means that, in aggregate, investors must commit hundreds of billions in net new capital to the asset class just to reach current targets.

Private debt was not completely immune to the macroeconomic conditions last year, however. Fundraising declined for the second consecutive year and now sits 23 percent below 2021’s peak. Furthermore, though private lenders took share in 2023 from other capital sources, overall deal volumes also declined for the second year in a row. The drop was largely driven by a less active PE deal environment: private debt is predominantly used to finance PE-backed companies, though managers are increasingly diversifying their origination capabilities to include a broad new range of companies and asset types.

Infrastructure and natural resources take a detour

For infrastructure and natural resources fundraising, 2023 was an exceptionally challenging year. Aggregate capital raised declined 53 percent year over year to $82 billion, the lowest annual total since 2013. The size of the drop is particularly surprising in light of infrastructure’s recent momentum. The asset class had set fundraising records in four of the previous five years, and infrastructure is often considered an attractive investment in uncertain markets.

While there is little doubt that the broader fundraising headwinds discussed elsewhere in this report affected infrastructure and natural resources fundraising last year, dynamics specific to the asset class were at play as well. One issue was supply-side timing: nine of the ten largest infrastructure GPs did not close a flagship fund in 2023. Second was the migration of investor dollars away from core and core-plus investments, which have historically accounted for the bulk of infrastructure fundraising, in a higher rate environment.

The asset class had some notable bright spots last year. Fundraising for higher-returning opportunistic strategies more than doubled the prior year’s total (Exhibit 5). AUM grew 18 percent, reaching a new high of $1.5 trillion. Infrastructure funds returned a net IRR of 3.4 percent in 2023; this was below historical averages but still the second-best return among private asset classes. And as was the case in other asset classes, investors concentrated commitments in larger funds and managers in 2023, including in the largest infrastructure fund ever raised.

The outlook for the asset class, moreover, remains positive. Funds targeting a record amount of capital were in the market at year-end, providing a robust foundation for fundraising in 2024 and 2025. A recent spate of infrastructure GP acquisitions signal multi-asset managers’ long-term conviction in the asset class, despite short-term headwinds. Global megatrends like decarbonization and digitization, as well as revolutions in energy and mobility, have spurred new infrastructure investment opportunities around the world, particularly for value-oriented investors that are willing to take on more risk.

Private markets make measured progress in DEI

Diversity, equity, and inclusion (DEI) has become an important part of the fundraising, talent, and investing landscape for private market participants. Encouragingly, incremental progress has been made in recent years, including more diverse talent being brought to entry-level positions, investing roles, and investment committees. The scope of DEI metrics provided to institutional investors during fundraising has also increased in recent years: more than half of PE firms now provide data across investing teams, portfolio company boards, and portfolio company management (versus investment team data only). 4 “ The state of diversity in global private markets: 2023 ,” McKinsey, August 22, 2023.

In 2023, McKinsey surveyed 66 global private markets firms that collectively employ more than 60,000 people for the second annual State of diversity in global private markets report. 5 “ The state of diversity in global private markets: 2023 ,” McKinsey, August 22, 2023. The research offers insight into the representation of women and ethnic and racial minorities in private investing as of year-end 2022. In this chapter, we discuss where the numbers stand and how firms can bring a more diverse set of perspectives to the table.

The statistics indicate signs of modest advancement. Overall representation of women in private markets increased two percentage points to 35 percent, and ethnic and racial minorities increased one percentage point to 30 percent (Exhibit 6). Entry-level positions have nearly reached gender parity, with female representation at 48 percent. The share of women holding C-suite roles globally increased 3 percentage points, while the share of people from ethnic and racial minorities in investment committees increased 9 percentage points. There is growing evidence that external hiring is gradually helping close the diversity gap, especially at senior levels. For example, 33 percent of external hires at the managing director level were ethnic or racial minorities, higher than their existing representation level (19 percent).

Yet, the scope of the challenge remains substantial. Women and minorities continue to be underrepresented in senior positions and investing roles. They also experience uneven rates of progress due to lower promotion and higher attrition rates, particularly at smaller firms. Firms are also navigating an increasingly polarized workplace today, with additional scrutiny and a growing number of lawsuits against corporate diversity and inclusion programs, particularly in the US, which threatens to impact the industry’s pace of progress.

Fredrik Dahlqvist is a senior partner in McKinsey’s Stockholm office; Alastair Green  is a senior partner in the Washington, DC, office, where Paul Maia and Alexandra Nee  are partners; David Quigley  is a senior partner in the New York office, where Connor Mangan is an associate partner and Aditya Sanghvi  is a senior partner; Rahel Schneider is an associate partner in the Bay Area office; John Spivey is a partner in the Charlotte office; and Brian Vickery  is a partner in the Boston office.

The authors wish to thank Jonathan Christy, Louis Dufau, Vaibhav Gujral, Graham Healy-Day, Laura Johnson, Ryan Luby, Tripp Norton, Alastair Rami, Henri Torbey, and Alex Wolkomir for their contributions

The authors would also like to thank CEM Benchmarking and the StepStone Group for their partnership in this year's report.

This article was edited by Arshiya Khullar, an editor in the Gurugram office.

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Study on carbon emissions towards flange connection joints of assembled steel structures

• Open access
• Published: 20 May 2024
• Volume 2 , article number  6 , ( 2024 )

Cite this article

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• Jinyang Guo 1 ,
• Yanxia Zhang 1 , 3 ,
• Mingzhao Zheng 2 ,
• Xi Zhao 1 &
• Binglong Wu 1  

In order to comply with the trend of global climate change, countries are gradually promoting energy conservation and emission reduction, and prefabricated buildings have become one of the main paths for the construction industry to develop towards carbon peaking and carbon neutrality goals. This paper takes the box-shaped column flange connection achieved by plug welding-core sleeve in the dormitory building of Tongzhou Campus of the Affiliated High School of Capital Normal University in China as the research object. Based on the consumption quota of prefabricated construction projects and the actual project quantity, the carbon emissions of steel structure column connection joints at different phases are calculated by the emission factor method, and it is proposed that the production consumption of building materials plays a key role in energy conservation and emission reduction. This paper concludes that the box-shaped column flange connection achieved by plug welding-core sleeve in the construction phase of an assembled steel building emits 49.5% less carbon dioxide than a conventional full fusion-welded joint. And the reason for the high carbon emissions of the latter is mainly from the amount of materials and machinery required for full penetration welding. It further affirms the green and environmental protection effect of the assembled steel structure plug welding-core sleeve flange connection joint in actual projects, and provides a reference for related research.

为了顺应全球气候变化趋势，各国正逐步推动节能减排，其中，装配式建筑成为建筑业实现碳达峰和碳中和目标的主要途径之一。本文以中国首师大附中通州分校宿舍楼中箱形柱塞焊-芯筒式法兰连接节点为研究对象，基于装配式建筑工程消耗量定额及实际项目工程量，通过排放因子法计算钢结构柱连接节点在不同阶段的碳排放量，并提出建材生产消耗在节能减排中起到关键作用。本文研究得出，在装配式钢结构建造阶段，由于全熔透焊所需额外的焊接材料及机械能耗，箱形柱塞焊-芯筒式法兰连接节点碳排放量比传统的全熔透焊节点减少了49.5%的二氧化碳排放，进一步验证了装配式钢结构塞焊-芯筒式法兰连接节点在实际项目中起到的绿色环保作用，为相关研究提供参考依据。

Avoid common mistakes on your manuscript.

1 Introduction

With the rapid development of the world economy, the high consumption of energy resources and the impact of environmental pollution continue to plague the world's ecological civilization. In order to comply with the global climate change trend and China's national conditions, China has put forward a clear goal of carbon neutrality. In 2022, China's total carbon emissions were about 12.1 Gt CO 2 , accounting for 33% of the global total [ 1 ]. However, the total carbon emissions of buildings in China in 2020 were 5.08 billion t CO2 2 , accounting for 51% of the national carbon emissions [ 2 ].

Currently, there are extensive research studies on carbon emissions across various types of constructions. This encompasses studies on commercial and residential buildings [ 3 ], low-carbon communities [ 4 ], rural buildings [ 5 ], prefabricated buildings [ 6 , 7 ], among others. Studies have been conducted on various stages of construction, encompassing the materialization phase [ 8 ], the construction process [ 9 ], and the steel production stage [ 10 ]. Presently, there seems to be a relative dearth of research concerning carbon emissions specifically related to prefabricated steel structures. With the rapid development of prefabricated steel structure buildings, the extensive use of steel will intensify the energy consumption of prefabricated steel structure buildings, resulting in an increase in carbon emissions [ 11 ]. Prefabricated steel structures will become an important source of greenhouse gas emissions. Therefore, it is of great and urgent significance for the low-carbon development of prefabricated steel structure buildings to fully study the carbon emission problem of prefabricated steel structure column connection joints, and to explore the carbon reduction development advantages of prefabricated steel structure construction compared with traditional steel structure construction.

The construction industry is recognized as a significant contributor to global carbon emissions, often ranking among the top three sectors in this regard [ 12 ]. Scholars worldwide have extensively researched methodologies for calculating carbon emissions in buildings. These methodologies primarily encompass the input–output method, process-based method, and hybrid approaches [ 13 ]. Scholars summarize the current research hotspots of carbon emissions from public buildings (CEPB) into five categories: (1) theoretical research and simulation modeling; (2) energy systems; (3) materials; (4) public building renovation; (5) The main factors leading to the decrease of CEPB [ 14 ]. Huang et al. [ 15 ] conducted research on carbon emission policies and carbon emission calculations in different countries around the world and across the country. Panagiotis Chastas et al. [ 16 ] towards zero emission and zero energy buildings, literature reviews highlight the importance of embodied energy and embodied carbon emissions. There are also studies discussing how to reduce carbon emissions in the manufacturing and construction industries by applying carbon reduction technologies [ 17 , 18 ], analyzing the carbon footprint of manufacturing systems and construction processes [ 19 ], exploring appropriate carbon calculation tools [ 20 ], reviewing environmental impact reduction strategies [ 21 ], the carbon reduction potential of implementing digital (Industry 4.0) concepts in manufacturing [ 22 ]. Steel is the main material of prefabricated steel structure buildings, and it is also the main source of carbon emissions in building materials. Bernardino D’Amico et al. [ 23 ] used a computational tool based on an optimization framework that considered the embodied carbon in the amount of steel used in building structures. Li et al. [ 24 ] and Ren et al. [ 25 ] researched and analyzed the influencing factors of carbon emissions in the iron and steel industry and low-carbon technologies, and put forward the development approach for the reduction of greenhouse gas emissions in China's iron and steel industry. Chen et al. [ 26 ] explored how the existing literature can effectively reduce the carbon emissions of steel structure building products from a cradle-to-site perspective. Due to the increasing use of steel structures in modern buildings, the demand for steel is also increasing. How to reduce the carbon emissions of steel has attracted the attention of more scholars.

In recent years, most of the research on carbon emissions from prefabricated buildings has focused on prefabricated concrete, precast and cast-in-place components, and high-rise and low-rise assembled buildings, etc. Emanuele Bonamente et al. [ 27 ] and Susan Abed Hassan et al. [ 28 ] conducted research on greenhouse gas emissions (carbon footprint) and primary energy consumption (energy footprint) of multi-storey buildings in Italian companies and Iraq, respectively. Dong et al. [ 29 ] used a life cycle assessment (LCA) model to calculate the carbon emissions of a private residential building in Hong Kong, and concluded that precasting can reduce carbon emissions by 10% per cubic meter of concrete. Mo et al. [ 30 ] analyzed an office building with an assembly rate of 96.8% in Hangzhou, Zhejiang. The total measured carbon emissions of the research object was \(2265.73 t C{O}_{2}e\) , which was \(22 kg C{O}_{2} e/{m}^{2}\) lower than that under the non-prefabricated method. Guo et al. [ 31 ] concluded that when enterprises determine the prefabrication range of 35–40% of prefabricated buildings, they can obtain the maximum carbon reduction effect at the minimum cost. Jack C. P. Su et al. [ 32 ] developed a system to evaluate the carbon emissions and costs of product designs, helping companies optimize assembly processes to minimize carbon emissions. However, there are very few studies on carbon emissions based on fabricated steel structures. Patricia González-Vallejo et al. [ 33 ] studied the carbon footprint of metal structure projects in Romania and concrete structure projects in Spain, and concluded that metal structure buildings have a greater impact on the economy and the environment than reinforced concrete buildings. You et al. [ 34 ] compared the differences in CO 2 emissions between brick-concrete structures and steel–concrete structures in urban residential buildings. Zhu et al. [ 35 ] calculated the carbon emissions of the steel structure residential project of Hangxiao Steel Structure Co., Ltd. in the whole life cycle of the building. Xu et al. [ 36 ] conducted a life cycle assessment of the carbon emissions of classical types of long-span structures, considering both space frame structures with bolted spherical joints and space frame structures with welded hollow spherical joints.

To explore the potential advantages of energy efficiency and emission reduction in prefabricated steel structures, this study examines prefabricated steel structural column connection joints. Currently, the primary connection methods for these joints include flange connection joints and full penetration welding connection joints. For steel building joints, welding can provide some strength and stiffness, but the construction time is long and generates large carbon emissions and pollution. For steel–concrete structures, steel–concrete bonding is generally used [ 37 ], which provides better integrity, and concrete bonding usually requires less energy than welding, which may reduce carbon emissions during construction. The choice of the specific connection method has to take into account the design specification, assembly process and environmental impact. The innovative flange connection joints eliminate on-site welding, reducing both welding material usage and mechanical energy consumption. This addresses the inefficiency and high energy consumption associated with on-site welding, presenting significant carbon emission reduction benefits. Conducting a carbon emission assessment for these joints quantifies their energy-saving effects, providing empirical support for the sustainable development of prefabricated steel structures. A comprehensive exploration of the structural aspects, performance, and construction techniques of steel column connection joints contributes to improving the construction efficiency of prefabricated steel structures, reducing energy consumption and material wastage, advancing the industrialization of steel structures in China, and fostering sustainable development. In this team, Yanxia Zhang et al. [ 38 ] proposed a box-shaped column flange connection achieved by plug welding-core sleeve. The term "plug welding" refers to the plug welding of the lower column during the factory processing of prefabricated components, there is no welding on the construction site, all connections are bolted. Additionally, Zhang et al. [ 39 ] compiled Technical Standard for Fully Bolted Assembled Steel Structures of Multi-High-Rise Storey Buildings (T/CSCS 012–2021) , and this paper is permitted to conduct carbon emission-related research on this joint. In the actual fabricated steel structure project, the connection joint has the advantages of ensuring the rigid connection performance at the joint, realizing high-efficiency assembly of box columns, saving engineering costs, and has the advantages of low pollution, green energy saving. Wu et al. [ 40 ] studied the carbon emission characteristics of various welding processes. In contrast, the traditional full penetration welding joints have disadvantages such as high energy consumption and large pollution, which leads to large carbon emissions and low efficiency in the construction of traditional steel structures.

As one of the construction industrialization development paths, prefabricated buildings are the primary means by which the construction industry can achieve its carbon peaking and neutrality goals. Therefore, it is necessary to conduct a comprehensive study on the carbon reduction of fabricated steel structures in actual projects. This paper focuses on the dormitory building project of the Tongzhou Campus of the Affiliated High School of Capital Normal University, and adopts the quota-based carbon emission factor method to calculate the carbon emissions of the steel column connection joints at different phases of the assembled steel structure building. It also compares the carbon emissions in the construction phase with the traditional full-fusion welded connection joints, provides technical support for the subsequent energy saving and emission reduction of assembled steel buildings, and promotes the sustainable development of assembled steel buildings.

The research object has the advantages of typical application, suitable conditions, convenient analysis, and practicality that it reflects. At the same time, based on the concept of comparative analysis, from the perspective of different phases of the entire life cycle of steel column connection joints, different types of joints, and the entire building, different calculation ranges are established and the differences in joint member data are compared and analyzed in depth. At last, the advantages of low-carbon construction of flange connection joints of fabricated steel structures are discussed to serve as a reference for the development of low-carbon fabricated steel structures.

2 Backgrounds

The construction project at the Tongzhou Campus of the Affiliated High School of Capital Normal University represents Beijing's initial adoption of fully bolted prefabricated steel structures without welding. Therefore, selecting the flange connection joint as the subject of study holds paramount significance. Given the widespread application of prefabricated construction in the building industry and its pivotal role within the overall prefabricated construction system, this joint has also been applied in the new outpatient and emergency medical technology building of Shougang Hospital of Peking University and the second phase of Shenzhen New Energy Vehicle Industrial Park, improving the overall performance, construction speed, and energy efficiency of prefabricated steel structures. This choice aligns with national policy directives aimed at achieving industrialization and sustainability goals, while also bearing practical relevance for various construction endeavors.

In this paper, the dormitory building of Tongzhou Campus of the Affiliated High School of Capital Normal University is used as the calculation model (Fig.  1 ). The main structural members of the dormitory building all adopt the steel frame structure system. The assembled steel building adopts box-shaped column flange connection achieved by plug welding-core sleeve, the splicing position is at the top of the 1st floor underground, the top of the 2nd floor above ground, the top of the 4th floor and the top of the 6th floor, and contains a total of 160 box-shaped column flange connections achieved by plug welding-core sleeve. Since the joint installation components have been processed and fabricated in the factory, only manual bolt installation is required during the on-site construction phase, which reduces the material consumption of welding and mechanical fuel consumption compared to the conventional steel column connection joint full penetration welding process, resulting in greater carbon reduction benefits.

Dormitory building calculation model

Therefore, this study utilizes the dormitory building as a model project for carbon emission analysis. Considering the construction involving the box-shaped column flange connection achieved by plug welding-core sleeve employed in the current project development, this joint configuration was selected as the focus of this research. By collecting statistical data concerning construction, materials, and equipment, carbon emissions are accounted for in various stages of building. By comparing the data results from different scenarios, suggestions conducive to energy-saving, emission reduction, and sustainable development in prefabricated steel structures are proposed.

The flange connections achieved by plug welding-core sleeve is located at the beam-column joint connection, and the specific structure is shown in Fig.  2 . Among them, the upper column and the lower column are equipped with flange plates and connected by high-strength bolts; a core cylinder is set in the column at the splicing of the upper and lower columns, and a spacer is set in the corresponding position. The cross section of the core cylinder is octagonal, and the thickness of its wall plate is greater than the thickness of the column wall plate according to the force at the joint. The core sleeve is manufactured in the factory with a negative tolerance of 1 mm ~ 2 mm and preassembled in the factory to ensure smooth installation of the connection joint in the field. Additionally, to ensure a reliable connection between the core sleeve and the column wall, tapping bolt holes are located on the upper column, while corresponding plug welding holes are created at the respective positions on the lower column.

Detail of flange connection achieved by plug welding-core sleeve

The prototype was taken from the steel column splicing joint of the dormitory building of Tongzhou Campus of the Affiliated High School of Capital Normal University. In this paper, a two-story high steel column is analyzed as a unit, and the calculation is conducted for the building's typical size joint, with a total height of 7400 mm, of which the upper column is 3700 mm, the lower column is 3700 mm, and the cross-sectional size of the column is 500 × 500 × 22 × 22 mm. The size of the flange plate is 740 × 740 × 30 mm, the upper and lower flanges are connected by 20 M24 high-strength bolts. The detailed drawing of the core sleeve is shown in Fig.  3 .

Detailed diagram of core sleeve /mm

3 Methodology

3.1 parameters affecting carbon emissions, 3.1.1 activity level data and sources.

Activity level data, often referred to as carbon source data, represents energy consumption [ 41 ]. The prototype specimen for this study is derived from the steel structure column connection joint within the dormitory building at the Tongzhou Campus of the Affiliated High School of Capital Normal University. The required activity-level data collection encompasses machinery usage and labor statistics necessary across various phases, including steel column fabrication, installation, transportation, and dismantling involved in the construction process of the dormitory building. Since some of the activity data such as construction material transportation are not suitable for use on to individual objects, the uniform specification data in the Consumption Quotas for Building Construction and Decoration Works [ 42 ] are used for calculation. In this paper, data such as activity level and construction of production process of flange connection joints are compiled by collecting project purchase list and settlement information. The statistical indicators of the project are shown in Table  1.

3.1.2 Carbon emission factor data

The carbon emission factor refers to the emission of some greenhouse gases, mainly CO 2 , per unit of activity, and also includes the emission of methane (CH 4 ) and nitrous oxide (N 2 O). The International Energy Agency (IEA) unifies the emissions of various greenhouse gases as carbon dioxide equivalent CO 2 e. There is no measured carbon emission factor in this study, so carbon emissions are represented by carbon dioxide equivalent CO 2 e. For the steel production phase, the carbon emission factors for steel components in this study were determined according to the activity data collection and calculation methods provided in the Methodology and Reporting Guide for Greenhouse Gas Emissions of Chinese Steel Producers (for Trial Implementation) [ 43 ]. In addition, for the activity level data of construction material transportation, building construction and dismantling phases, this paper adopts the carbon emission factors provided by the Standard for Building Carbon Emission Calculation (GB/T 51366–2019) [ 44 ], as well as the data from foreign studies such as the IPCC Guidelines for National Greenhouse Gas Inventories , and the carbon emission factors that can be referred to in published domestic papers, which are more relevant for this assembled steel column splicing joint.

3.2 Calculation range

3.2.1 carbon emissions greenhouse gas range.

According to the International Energy Agency (IEA), the emissions of various greenhouse gases are unified as carbon dioxide equivalent (CO 2 e), so the carbon emissions in this study are also quantitatively analyzed according to CO 2 e, and the carbon emission factors are also expressed as carbon dioxide equivalent for greenhouse gas emissions.

3.2.2 Accounting boundaries

For the carbon emission calculation of the box-shaped column flange connections achieved by plug welding-core sleeve, the scope of the accounting system includes the joint in each phase of building material processing and transportation, building construction and construction, and demolition, with the carbon emission calculation time boundary of the construction phase from the start of the project to the completion and acceptance of the project, and the carbon emission calculation time boundary of the demolition phase from the demolition to the demolition dismemberment and transportation out from the floor. Using CO 2 e as the greenhouse gas accounting boundary, the carbon emission size of this steel column splicing joint was calculated and evaluated. The building material processing to construction phase of this joint belongs to the materialization phase of the assembled steel structure, which is the whole process of the bill of quantities from the extraction and processing of materials, transportation, construction and building to the completion of delivery. Since the calculation of carbon emission for the box-shaped column flange connections achieved by plug welding-core sleeve is too frequent for multiple sub-component projects one by one, the quantity consumption quota for the work of assembled construction is referred to, and the sub-component projects are grouped into component fabrication, component installation, personnel activities, and mechanical equipment energy consumption.

3.3 Calculation method

The 2006 IPCC Guidelines for National Greenhouse Gas Inventories issued by the Intergovernmental Panel on Climate Change (IPCC) proposed three carbon emission calculation bases [ 45 ], and this paper adopts the emission factor method proposed therein. According to other studies related to carbon emissions of buildings in the context of carbon neutrality target, there are also input–output method, material balance method and other calculation models.

The input–output method is a top-down calculation approach suitable for predicting the direction and extent of changes in targets based on inputs and outputs over a period. It measures direct and indirect carbon emissions. However, this method lacks in-depth analysis of specific processes and faces challenges in data collection, resulting in significant uncertainty in the calculated results. These factors render it unsuitable for carbon emission calculations in this study.

The material balance method involves a comprehensive analysis of carbon material flows, requiring thorough tracking and assessment of inputs and outputs. This method is intricate and involves substantial work due to its complexity. It is suitable for calculating carbon emissions across entire ecosystems or specific processes. However, the characteristics of connections in prefabricated steel structures pose challenges when employing this methodology.

The carbon emission factor method refers to a technique where the quantity of emitted gases per unit product in normal technical, economic, and managerial conditions is statistically calculated to derive the total emissions using average values. This method requires clear data on carbon emission activities and emission coefficients, often focusing on activity level data and emission factors. In the case of connections in prefabricated steel structures, where the primary material is steel, the involved processes are relatively straightforward. The input–output material types are singular, and the carbon content remains relatively stable, resulting in fewer uncertainties. Compared to other methods, this approach is more conducive to evaluating the individual contribution of specific joints within a building towards energy conservation and emission reduction. It offers a more objective reflection of the actual carbon emissions from steel column joints to a certain extent.

For the carbon emission calculation of the box-shaped column flange connections achieved by plug welding-core sleeve, which is the subject of this paper, the emission factor method is adopted as the carbon emission calculation model commonly used at present. China's Standard for Building Carbon Emission Calculation (GB/T 51366–2019) , which was promulgated and implemented based on IPCC guidelines, has a higher value of use for China's existing buildings and energy carbon emission factors in line with China's national conditions. In addition, this paper also refers to the Assessment Standard for Green Building (GB/T 50378–2019) [ 46 ] promulgated by the Ministry of Housing and Urban–Rural Development, the Guidelines for the Preparation of Provincial Greenhouse Gas Inventories (for Trial Implementation) [ 41 ] promulgated by the National Development and Reform Commission and other relevant national standards and specifications that are in line with China's greenhouse gas inventory. The specific formula and symbols are as follows:

3.3.1 Component fabrication phase

The steel structure column joint serves as a prefabricated component. This study refers to the engineering quantity list of the steel column production phase in the quota, hence, the carbon emissions in this phase stem from emissions produced by materials, labor, and machinery. According to the Standard for Building Carbon Emission Calculation and relevant research papers, the carbon emissions in the steel column production phase should be calculated according to the following formula:

\(C_{zz}\) ——Carbon emissions from individual joint during the fabrication phase of steel columns;

\(C_{jci}\) ——Carbon emissions of \(ith\) building materials production;

\(C_{zp}\) ——Carbon emissions from steel column assembly phase;

\(T_{i}\) ——Consumption of \(ith\) material in the fabrication phase of steel columns;

\(MF_{i}\) ——Carbon emission factor of the \(ith\) material;

\(T_{r}\) ——Consumption of man-days during the fabrication phase of steel columns;

\(RF_{i}\) ——Carbon emissions per unit workday of labor;

\(E_{zz,i}\) ——Total energy use of the \(ith\) type in the construction phase of the building \((kWh \ or \ kg)\) ;

\(EF_{i}\) ——Carbon emission factor for energy type \(i(kgC{O}_{2}e/kg \ or \ kgC{O}_{2}e/kWh)\) ;

\(Q_{zz}\) ——Quality of individual joint in the fabrication phase of steel columns \((t)\) ;

\(T_{i,j}\) ——The \(jth\) type of construction machinery shift consumption consuming the \(ith\) type of energy;

\(R_{j}\) ——The \(jth\) type of construction machinery unit shift consumption energy usage.

3.3.2 Construction phase

The carbon emission in the construction phase of the building includes the carbon emission generated from the completion of the construction of each sub-component and the carbon emission generated from the construction process of each measure project. For the construction phase of steel splicing joint, according to the Standard for Calculation of Carbon Emission of Buildings and relevant research papers, the calculation of carbon emission in the construction phase of buildings should be calculated according to the following formula:

\(C_{jz}\) ——Carbon emissions from individual joints during the construction phase of steel columns;

\(T_{r}\) ——Consumption of man-days during the construction phase of steel columns;

\(T_{i}\) ——Consumption of material \(i\) in the building construction phase;

\(E_{jz,i}\) ——Total energy use of the \(ith\) type in the construction phase of the building \((kWh \ or \ kg)\) ;

\(Q_{jz}\) ——Single joint volume in building construction phase \((t)\) ;

3.3.3 Building material transportation phase

The transportation of materials in prefabricated construction can be categorized into the transport of prefabricated components and other building materials. For building materials, short to medium-distance transportation commonly utilizes road transport. Due to the fewer construction materials involved in prefabricated steel structure connection joints, it's challenging to individually assess the transportation distances of specific building materials based on actual circumstances. Hence, this study calculates the transportation of steel and metal components based on the Consumption Quotas for Building Construction and Decoration Works metal transport table. For other (non-metal) construction materials, the transportation distances primarily rely on average distances from referenced research outcomes and national-level average transportation distances for major construction materials [ 47 ].

The primary focus of this study is on construction materials such as steel, bolts, and non-metals. Due to the fact that the equipment required for construction is not only used in the fabrication and installation of steel column joints but also in steel beams and other sub-projects, it is challenging to differentiate the carbon emissions from transportation of this equipment. Furthermore, due to the absence of relevant quota data, this aspect has not been taken into consideration.

According to the Carbon Emission Calculation Standard for Buildings , the carbon emission of this connection joint in the transportation phase of building materials should be calculated according to the following formula:

\(C_{ys}\) —— Carbon emissions from the transportation of building materials \((kgC{O}_{2}e)\) ;

\(M_{i}\) —— Consumption of major building materials \((t)\) ;

\(D_{i}\) —— The average transportation distance of the \(ith\) building material \((km)\) ;

\(T_{i}\) —— Carbon emission factor per unit weight of transportation distance under the transportation mode of the \(ith\) building material \([kgC{O}_{2}e/(t\cdot km)]\) .

3.3.4 Building demolition phase

The carbon emissions during the demolition phase encompass building dismantling and transportation of debris. As the current status of the project's buildings remains undemolished, data pertaining to the demolition processes are unavailable for collection. Therefore, the carbon emissions for this phase will be estimated through simplified calculations.

According to Ju et al. [ 48 , 49 ] , the energy consumption during the demolition phase of a building constitutes 90% of the energy consumption during the construction process. Therefore, the carbon emissions during the building demolition phase contribute 90% of the carbon emissions during the installation and construction phase. The carbon emissions from the transportation of demolition debris are estimated to be 90% of those generated during the transportation of construction materials [ 47 ]. Carbon emissions from the demolition phase should be calculated according to the following formula:

\({C}_{cc}\) —— Carbon emissions from steel column joints during the building demolition phase \((kgC{O}_{2}e)\) .

4 Calculation results of emission factor method

With reference to the specified parameter range and calculation method, carbon emission calculation and result analysis are carried out for the box-shaped column flange connection achieved by plug welding-core sleeve using the collated member material, dimensions and other data.

4.1 Calculation of carbon emissions by phase

4.1.1 steel column joint fabrication phase.

The subject of this study is the internal sleeve-type flange connection joints of steel box columns, primarily composed of upper and lower columns, flange plates, high-strength bolts, and octagonal inner sleeves. The inner sleeve flange joints and their connection to the steel columns are factory-processed, with on-site construction focusing solely on the installation of high-strength bolts at the flange plates of the upper and lower columns. This process achieves efficient vertical assembly and promotes green construction practices. This section focuses on the fabrication process of steel structure column joint connections, primarily involving: plug welding between the core sleeve and the lower column wall, tapping bolt alignment between the upper column and the core sleeve, and initial fastening using high-strength bolts (manually). Specific data regarding activity levels were referenced from the Consumption Quotas for Building Construction and Decoration Works steel column fabrication consumption table. The calculated total mass of the finished steel column joint in the model amounts to \(2808.05 kg\) , with the steel column itself weighing \(2443.50 kg\) .

As the Consumption Quotas for Building Construction and Decoration Works already factors in material wastage, this study references the consumption data from its steel column fabrication table. This is coupled with the volumetric details and material quantities from the structural diagram of the column joint components for computation. According to Yang [ 50 ], national standards specify a \(6\mathrm{\%}\) wastage rate for steel material production, while finished steel structures do not account for wastage. Hence, this paper calculates the carbon emissions of steel material during the building material production stage by multiplying the finished quality of steel used in both types of joints by \(1.06\) . Based on a company's standard Welding Material Consumption Quota Standard (Q/HZ MB103-79) and the research conducted by Huang et al. [ 51 ], calculations were made concerning the plug welding process. The quantity of plug welding holes and the required volume of deposited metal were used to calculate the necessary materials such as welding rods, wires, and associated mechanical energy, which were then incorporated into the carbon emission inventory for this phase.

In accordance with the Consumption Quota for Assembly Building Construction [ 52 ] among the steel column installation quota, the amount of installation work is calculated by the quality of the finished components in accordance with the size of the design drawings, and does not deduct the quality of a single area \(\le {0.3m}^{2}\) of the hole, welding, rivets, bolts do not increase the quality. Therefore, the fabrication process of single steel structure column splicing joint is calculated according to \(\le 3t\) . The material is Q345B steel, M24 high strength bolts. Utilizing Eqs. ( 1 )- ( 4 ), the carbon emissions inventories for steel structure column joint fabrication phase are detailed in Tables 2 and 3 .

According to the report published by the IEA in 2022, our annual per capita carbon emissions in 2017 were about 7.56 t. Therefore, the artificial carbon emission factor at that time was calculated to be 6.90 kgCO 2 e/workday [ 56 ]. For fossil fuel carbon emission calculation, the fuel consumption needs to be multiplied by the default net calorific value of that fuel, i.e., the average low calorific value (e.g., the default net calorific value of diesel is \(42522 kJ/kg\) ), and then multiplied with the unit calorific value carbon emission factor to find the carbon emission. For power-consuming machinery, the total power consumption needs to be multiplied with the power carbon emission factor of the regional power grid data built at the time of construction, where the power carbon emission factor is taken from the North China regional power grid \(2017\) annual emission factor of \(0.9680 tC{O}_{2}/MWh\) , to find the carbon emission of power-consuming machinery. From the aforementioned carbon emission inventory, it can be deduced that the total carbon emissions for the steel column fabrication stage amount to \({C}_{zz} = 1911.22 kg\) . This includes \(167.02 kg\) from manual labor, \(1049.10 kg\) from materials, and \(695.11 kg\) from machinery. It is evident that material-related carbon emissions contribute to over \(54.8\mathrm{\%}\) in this phase, while machinery accounts for \(36.4\mathrm{\%}\) of the emissions.

4.1.2 Steel column joint construction phase

The construction project of Capital Normal University's Tongzhou Campus adopts prefabricated steel structures with fully bolted connections, ensuring efficient assembly of the steel framework. The construction phase for steel column connection joints involves solely the use of high-strength bolts at the flange of the upper and lower columns. Reference was made to the bolt installation data table in the engineering consumption quota [ 42 ] to calculate the consumption of labor, materials, and machinery, considering the required quantity of high-strength and tapping bolts for a single joint. According to Eqs. ( 5 )- ( 6 ), the carbon emission inventories during the construction phase of a single steel structure column joint are presented in Table  4 and 5 .

According to the above data, the total carbon emission in the construction phase of steel structure column joint is \(155.90 kg\) , of which the mechanical carbon emission is \(137.41 kg\) , the artificial carbon emission is \(8.70 kg\) , and the material carbon emission is \(9.79 kg\) . From the data, it can be seen that the mechanical carbon emission in the construction phase of a single steel structure column joint accounts for the carbon emission of the whole phase is more than \(73\%\) .

4.1.3 Building material transportation phase

This study is based on the actual transportation distance of building materials, and the list of work volume in the transportation phase is referred to the quota for the transportation phase of metal components in the Consumption Quotas for Building Construction and Decoration Works . Considered by the processing plant to the construction site, the metal structure transportation is divided into category I (steel column) and category II (high-strength bolts and other fragmentary components) for this joint. The origin of category I components is Hangxiao Steel Structure Co., Ltd., and the transportation distance is 1264 km. The origin of category II components is Handan, Hebei, and the transportation distance is 452 km.

The inventory measurement unit is 10 tons, and there's no need to factor in losses for the finished prefabricated components. Therefore, the consumption for an individual steel structure column joint is calculated based on the quality of finished steel materials. Furthermore, the carbon emissions from the transportation of non-metal materials were also taken into consideration. Regarding the transportation of construction equipment, as the torque wrench used for this steel column joint is challenging to investigate in terms of actual transportation method and constitutes a small proportion, it has not been taken into account. Due to the fact that cranes are not limited to lifting steel columns and the challenges in accurately quantifying carbon emissions from actual transportation data, this aspect has not been taken into consideration.

Based on the average energy consumption data for Chinese road transportation [ 57 ] and Yang's study [ 50 ] on the diesel truck's energy consumption per ton-kilometer, the diesel road transportation carbon emission factor is determined to be \(0.176 kgC{O}_{2}e/(t\cdot km)\) . According to Eq. ( 7 ), the carbon emission list in the transportation phase is shown in Tables  6 and 7 .

Based on the above inventory, the total carbon emissions for the transportation phase of the steel structure column joint can be calculated as \({C}_{ys}=1517.02 kg\) . Among them, the carbon emission in the transportation phase of the first class member steel column is \(1513.76 kg\) , accounting for more than \(99.9\%\) . Due to the minimal proportion of miscellaneous components such as bolts within the studied components and their varying transportation distances, the carbon emissions during the transportation phase for these secondary components are exceedingly low. The carbon emissions from other non-metal materials are also very minimal.

4.1.4 Building demolition phase

Because the prefabricated steel structure building was not dismantled, relevant data for the demolition phase could not be gathered. Hence, carbon emissions for this phase were estimated in a simplified manner. Based on the calculations above, the carbon emissions for the steel column flange joint during the construction and transportation phases are \(155.90 kg\) and \(1517.02 kg\) , respectively. According to Eq. ( 8 ), the calculated carbon emissions for the dismantling phase of a single steel structure column joint amount to \({C}_{cc}=1505.63 kg\) .

4.2 Carbon emissions from single steel column connection joints

The carbon emissions at various phases of the box-shaped column flange connection achieved by plug welding-core sleeve are illustrated in Fig.  4 . Combining the calculated data analysis, the total carbon emissions for a single steel structure column joint amount to \(5089.77 kg\) , primarily stemming from the steel column fabrication phase. This is attributed to the significant carbon emissions from material consumption during this phase, accounting for over \(54.8\%\) of the emissions in that phase. The carbon emissions during the transportation phase constitute the second-largest contribution to the overall carbon emissions. This is attributed to the extensive transportation distance and the excessive material requirement for individual prefabricated steel structure column joint components. The proportion of carbon emissions in each phase is depicted in Fig.  5 . Concerning the carbon emissions of this box-shaped column flange connection achieved by plug welding-core sleeve joint, the carbon emissions from the steel column fabrication phase constitute \(67.5\%\) of the total. The contributions to carbon emissions, from greatest to least, are as follows: steel column fabrication phase > transportation phase > dismantling phase > construction phase.

Carbon emissions at each phase of the box-shaped column flange connections achieved by plug welding-core sleeve

Carbon emission ratio of each phase of box-shaped column flange connections achieved by plug welding-core sleeve

5 Discussion

5.1 comparison with full penetration welded joints.

In this section, the model for calculations is based on the Sunshine Hall project in Nangang District, Harbin [ 58 ]. The structure of this project comprises entirely of steel, with the primary steel columns being box-shaped and constructed using Q235B steel plates designed for high-rise buildings. The on-site installation of steel columns involves fully penetration welded joints. We proceed to calculate the carbon emissions associated with the construction data of these joints. The steel column quantity for full penetration welded column joints remains consistent with flange joints. Additionally, the full penetration welded joints lack a core sleeve and flange plate, featuring an additional partition plate, ear plate, and connecting plate. The dimensions of the ear plate and connecting plate are referenced from the 16G519 Multi-story Civil Steel Joint Detailed Drawings [ 59 ]. The calculated total steel mass for the finished full penetration welded steel column joint amounts to \(2573.14 kg\) . The specimen joint configuration is shown in Fig.  6 :

Full penetration welding box column connection joint structure [ 58 ]

5.1.1 Steel column joint fabrication phase

In the carbon emission calculations for the full penetration welded joint, the primary difference compared to the carbon emissions of the box-shaped column flange connection achieved by plug welding-core sleeve joint lies in the welding process. This specifically involves the mechanical usage and welding material quantity during the steel structure construction phase. The carbon emission inventories for the steel column fabrication phase are shown in Tables  8 and 9 .

Similarly according to Eqs. ( 1 )-( 4 ), the total carbon emissions for the full penetration welded steel column fabrication phase amount to \({C}_{zz}=1832.40 kg\) . This includes \(167.02 kg\) from labor, \(995.32 kg\) from materials, and \(670.06 kg\) from machinery. Materials accounted for \(54.3 \%\) of the carbon emissions from the fabrication of the steel columns, and machinery accounted for \(36.6 \%\) of the carbon emissions from this phase.

5.1.2 Steel column joint construction phase

The carbon emission inventories for the construction phase of the full penetration welded steel columns are shown in Tables  10 and 11 .

Based on Formula ( 5 )- ( 6 ), the carbon emissions for the full penetration welded steel column joint during the construction phase amount to \({C}_{jz}=308.84 kg\) . This comprises \(69.84 kg\) from labor, \(79.35 kg\) from materials, and \(159.65 kg\) from machinery. Machinery contributes the most to the emissions in this phase, accounting for \(51.7 \%\) of the total emissions.

5.1.3 Building material transportation phase

Following the same transportation method as with flange joints, the carbon emissions during the transportation phase for steel and fragmentary metal components were computed using engineering quotas. Similarly, other materials were calculated based on average energy consumption and transportation distances for road transport. The carbon emission inventory for the construction phase of full penetration welded steel columns is illustrated in Tables  12 and 13 .

Based on the inventories above, utilizing Eq. ( 7 ), the total carbon emissions during the transportation phase for full penetration welded steel column joints amount to \({C}_{ys}=1388.06 kg\) . Among these, the carbon emissions for Type I components in steel column transportation phase amount to \(1387.12 kg\) , constituting over \(99.9\%\) of the total.

5.1.4 Building demolition phase

From the calculations above, it's evident that the carbon emissions for the steel column flange joint during the construction phase and transportation phase are 308.84 kg and 1388.06 kg, respectively. According to Eq. ( 8 ), the calculated carbon emissions for the dismantling phase of a single steel structure column joint amount to \({C}_{cc}=1527.21 kg\) ."

5.2 Comparison of carbon emissions under individual components

Based on the carbon emission inventories of the two steel column joint types, the carbon emissions during the fabrication phase of the full penetration weld joints amounted to \(1832.40 kg\) , with a final joint mass of \(2573.14 kg\) . Hence, the average carbon emission rate per 1 kg of this joint stands at \(71.21\%\) . Meanwhile, the carbon emissions during the fabrication phase of the box-shaped column flange connections achieved by plug welding-core sleeve amounted to \(1911.22 kg\) , with a final joint mass of \(2808.05 kg\) , resulting in an average carbon emission rate per 1 kg of the full penetration weld joint at \(68.06\%\) .

Comparing the carbon emission rates per unit of individual components reveals that during the steel column fabrication phase, the carbon emissions per 1 kg of full penetration welded joint exceed those of flange joints by 4.6%. This is attributed to the slightly higher steel usage during the fabrication of flange joints, despite the additional plug welding process considered in their design at the prefabrication plant, resulting in a lower average carbon emission rate. Specific data regarding carbon emissions during this phase is detailed in Fig.  7 .

Comparison of carbon emissions of two types of joints during the steel column fabrication phase

During the steel column construction phase, the carbon emissions for the full penetration weld joints amounted to \(308.84 kg\) , whereas the box-shaped column flange connections achieved by plug welding-core sleeve emitted \(155.90 kg\) of carbon. Similarly, the average carbon emission rate per \(1kg\) full penetration welded connection joint can be found to be \(12.00\%\) and \(5.55\%\) for flange connection joint.

After standardizing the two components to the same unit measurement of 1 ton, the carbon emission per unit during the construction phase amounted to \(120.02 kgCO2e/t\) for the full penetration weld joints, and \(55.52 kgCO2e/t\) for the box-shaped column flange connections. The carbon emissions from full penetration welded joints exceed those from flange joints by \(116.2\%\) . This is due to the fact that during the construction phase assembly, the flange steel column connection joints only require the installation of high-strength bolts at the upper and lower flange plates. In contrast, the full penetration welded joints necessitate on-site welding of the upper and lower columns, resulting in increased material consumption and mechanical energy consumption, leading to higher carbon emissions. The specific carbon emission data for this phase are illustrated in Fig.  8 :

Comparison of carbon emissions of two types of joints during the steel column construction phase

During the transportation phase of steel columns, the carbon emissions for full penetration welded joints amount to 1388.06 kg, while for the plug welding-core sleeve flange connection joints, the carbon emissions are 1517.02 kg. Similarly, the average carbon emission rate per 1 kg of full penetration welded joint is calculated at 53.94%, whereas for the flange connection joint, it stands at 54.02%. It is evident that the carbon emissions during the transportation phase of both types of joints are nearly identical, primarily sourced from steel column transportation, accounting for 99.9%. Specific data regarding carbon emissions during this phase is detailed in Fig.  9 .

Comparison of carbon emissions of two types of joints during the steel column transportation phase

During the demolition phase of steel columns, the carbon emissions for full penetration welded joints amount to 1527.21 kg, whereas for the plug welding-core sleeve flange connection joints, the carbon emissions are 1505.63 kg. Similarly, the average carbon emission rate per 1 kg of full penetration welded joint is calculated at 59.35%, while for the flange connection joint, it stands at 53.62%. The flange connection joint exhibits a lower carbon emission rate during the demolition phase, primarily due to fewer emissions during the construction phase.

By comparing the above data, it is evident that the flange connection joint exhibits a lower average carbon emission rate during both steel column fabrication and demolition phases compared to the full penetration welded joint. Both joints show nearly identical carbon emission rates during the component transportation phase. Furthermore, during the steel column construction phase, the flange joint demonstrates significantly lower carbon emissions compared to the full penetration welded joint. As depicted in the graph, this difference in construction phase emissions is primarily due to variations in material consumption and mechanical energy consumption. So the use of assembled steel plug welding-core sleeve flange connection joint in the actual building construction effectively follows the energy-saving and emission reduction policy, not only the performance has been improved, the steel structure components have been improved and optimized, the energy utilization rate has also been enhanced, and further developed into green buildings.

5.3 Analysis of carbon emission results for different joints under the whole building

The construction plan of the dormitory building of Tongzhou Campus of the Affiliated High School of Capital Normal University is shown in Fig.  10 , and the section drawing is shown in Fig.  11 . Given that the analysis is conducted on a per-unit basis considering two-story high steel columns, the carbon emissions calculation for the joint connections is uniformly performed based on the selected joint dimensions. The splicing locations are at the top of the first basement floor, the top of the second floor above ground, the top of the fourth floor and the top of the sixth floor, containing a total of 160 box-shaped column flange connections achieved by plug welding-core sleeve.

Plan drawing of dormitory building of Tongzhou Campus of the Affiliated High School of Capital Normal University

Section of Tongzhou Branch of Capital Normal University Affiliated High School Dormitory building

For the entire dormitory building with box-shaped column flange connections achieved by plug welding-core sleeve, the carbon emissions from the steel column fabrication, component transportation, steel column installation, and building demolition phases for all joints were calculated. The total carbon emissions for the flange connection joints amounted to \(814.36 t\) .

If the entire dormitory building were to utilize full penetration welded joints, the carbon emissions for these joints in the dormitory would be calculated similarly. It's noteworthy that based on practical application in this dormitory project, considering the interruption in welding due to inclement weather, as well as actual efficiency gains, the full bolted connection method saved a total of 179 days. Within these additional days, the full penetration welded joints would generate extra carbon emissions, including the usual electricity and water consumption for regular living and office purposes, and notably, the carbon emissions generated by three tower cranes used in the actual project. Thus, focusing solely on the electrical consumption of these crane units, the calculated additional total carbon emissions for the three cranes over 179 working days amount to \(138.29 t\) . Consequently, if the entire dormitory building were to adopt full penetration welded joints, the total carbon emissions for these joints would be \(947.33 t\) .

If we disregard any potential delays in the construction period and focus solely on the entire dormitory building's construction phase, the total carbon emissions from all box-shaped column flange joints achieved by plug welding-core sleeve connection amount to \(155.90 t\) . If all individual steel column joints in the units were replaced with full penetration welded steel column joints, the carbon emissions for these joints during the dormitory building's construction phase would reach \(308.84 t\) . This reflects an additional \(152.94 t\) of carbon emissions compared to the box-shaped column flange joints achieved by plug welding-core sleeve connection, which accounts for an increase of \(98.1\%\) in carbon dioxide emissions. Hence, the adoption of box-shaped column flange joints achieved by plug welding-core sleeve connection in prefabricated steel structure buildings instead of traditional full penetration welded steel column joints has significantly contributed to energy conservation and emission reduction.

Regarding the carbon emissions from the steel column joints of the dormitory building, the total carbon emissions for the plug welding-core sleeve flange joint amount to \(814.36 t\) , while the total carbon emissions for the full penetration welded joint reach \(947.33 t\) . The carbon emissions from the full penetration welded joints surpass those from the flange joints by 132.97 tons. This discrepancy is primarily due to the lower carbon emissions during the construction phase of the flange joints and the indirect carbon emissions saved from the reduced construction period.

6 Conclusions and future outlook

6.1 summary of carbon emissions from prefabricated steel structure connection joints.

This study concludes that in prefabricated steel structures, the carbon emissions during the construction phase from box-column plug welding-core sleeve flange joints reduce by 49.52% compared to the traditional full penetration welded joints. The carbon emission accounting data demonstrates the green and low-carbon advantages of flange connection joints in actual projects, which not only have a greater energy saving and emission reduction effect, but also a higher energy utilization rate, indicating a shift in the direction of green buildings for prefabricated steel structures.

This paper takes the box-shaped column flange connection achieved by plug welding-core sleeve in the dormitory building of Tongzhou Campus of the Affiliated High School of Capital Normal University as the research object. Based on the consumption quota of prefabricated construction projects and the actual project quantity, the carbon emissions of steel structure column splicing joints in steel structure buildings at different phases are calculated by the emission factor method. Concluded as follow:

The carbon emissions for a single unit of the box-column plug welding-core sleeve flange joint are \(1911.22 kg\) during the steel column fabrication phase, \(155.90 kg\) during the joint construction phase, \(1517.02 kg\) during component transportation, and \(1505.63 kg\) during building demolition. The contribution of carbon emissions from a single steel structure column joint decreases in the following order: fabrication phase > transportation phase > demolition phase > construction phase.

In the steel column fabrication phase, the carbon emission rate of the flange connection joint is \(68.06\%\) , while the full penetration welded joint registers at \(71.21\%\) . Despite the additional plug welding process in the design consideration of the flange joint, its average carbon emission rate remains lower.

During the steel column construction phase, the carbon emission per ton for the plug welding-core sleeve flange joint is \(55.52 kgC{O}_{2}e/t\) , while for the full penetration welded joint, it stands at \(120.02 kgC{O}_{2}e/t\) . The carbon emission of the full penetration welded joint surpasses that of the plug welding-core sleeve flange joint by \(116.2\%\) . This increase is primarily attributed to the welding materials required for construction and the mechanical energy consumption, whereas the box-column plug welding-core sleeve flange joint only necessitates bolt installation during construction.

Regarding the carbon emissions during the transportation phase, the carbon emission rates of the flange connection joint and the full penetration welded joint are nearly identical.

Regarding the demolition phase, the carbon emission rate of the flange connection joint is \(53.62\%\) , while that of the full penetration welded joint is \(59.35\%\) . The flange connection joint exhibits a lower carbon emission rate during the demolition phase, mainly due to reduced carbon emissions during the steel column construction phase.

For all steel column joints in the entire dormitory building, the total carbon emissions for the plug welding-core sleeve flange joints are \(814.36 t\) , while those for the full penetration welded joint amount to \(947.33 t\) . The total carbon emissions for the flange connection joint are reduced by \(132.97 t\) compared to the full penetration welded joint. This reduction is primarily due to lower carbon emissions during the flange connection joint construction phase and the indirect carbon emissions saved by reducing the construction duration.

6.2 Limitations of the study

Incomplete database of carbon emission factors and evolving trends. This insufficiency in the carbon emission factor database, coupled with the diverse range of building materials and machinery, signifies a continual evolution in the magnitude of carbon emission factors. Thus, there is an urgent need for a comprehensive and adaptable database of carbon emission factors to enhance the efficiency of energy conservation and emissions reduction in prefabricated construction.

Limitation in research scope. The study's focus on steel structural column connection joints within dormitory buildings limits its breadth, preventing comparative analysis of carbon emissions from these joints across similar structures. Expanding the number of research cases is imperative to analyze the favorable trends in energy conservation and emissions reduction associated with these joints in diverse prefabricated construction projects.

Data collection challenges and authenticity. The study conducted carbon emission calculations based on engineering consumption norms, complemented by some verified actual consumption data. However, the collection of on-site construction data posed significant challenges, impeding the precision and clarity of carbon emission calculations. Thus, a more focused effort on data collection is necessary to enhance the accuracy and lucidity of carbon emission assessments.

Shortcomings in demolition phase estimation. The calculation of carbon emissions during the demolition phase relied on empirical estimations from other studies due to the absence of actual building demolition. Consequently, there exists a slight discrepancy between these estimations and the real scenarios. Considering steel's high recycling coefficient as a construction material, additional empirical data is imperative at this stage to refine and render the carbon emission calculation methodology more reasonable and accurate.

6.3 Future prospects

The future focus of this study will center on the following aspects:

Optimization of carbon emission factors and methodology. Continued attention will be given to the selection of carbon emission factors, integrating existing software standards to refine and improve the efficiency and outcomes of the carbon emission factor methodology.

Expanding the scope of study. The future endeavors will not only focus on optimizing the efficient energy-saving construction of steel structural column connections but will also explore broader potential carbon reduction advantages in other aspects of prefabricated steel structural buildings. For other structural buildings such as steel- concrete structures, the selection of building material quality can also be optimized to extend the structural life cycle; the use of renewable materials as building materials is recommended to reduce carbon emissions from construction waste; and different structural construction solutions can be optimized to improve the efficiency of the construction process and to reduce unnecessary construction carbon emissions.

Enhancement of data collection. Future efforts will be directed towards refining the collection of data, particularly focusing on acquiring actual consumption data related to labor and machinery during both the factory prefabrication phase and on-site construction. This emphasis aims to ensure the authenticity and rationality of the data acquired for analysis.

Optimization of demolition and recycling phase calculation. Future endeavors will focus on exploring more rational and accurate methodologies for calculating carbon emissions during the demolition and recycling phases. This exploration will heavily rely on additional empirical data to enhance the precision of estimations and refine the calculation process.

These future endeavors will contribute to furthering research in the realm of low-carbon development in prefabricated construction, enhancing the feasibility and accuracy of energy-saving and emission reduction methods.

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All relevant data can be provided as request.

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Acknowledgements

Thanks to everyone who has helped in the writing of this paper.

This research was funded by National Natural Science Foundation of China, grant number 51778036 and Joint Program of Beijing Natural Science Foundation and Education Commission, grant number KZ201910016018.

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Conceptualization, Jinyang Guo, Yanxia Zhang and Mingzhao Zheng; Data curation, Jinyang Guo, Mingzhao Zheng and Binglong Wu; Formal analysis, Jinyang Guo, Yanxia Zhang, Mingzhao Zheng and Xi Zhao; Funding acquisition, Yanxia Zhang; Investigation, Jinyang Guo; Methodology, Jinyang Guo, Yanxia Zhang and Mingzhao Zheng; Project administration, Yanxia Zhang; Resources, Yanxia Zhang and Mingzhao Zheng; Supervision, Yanxia Zhang; Validation, Jinyang Guo, Yanxia Zhang, Mingzhao Zheng and Binglong Wu; Visualization, Jinyang Guo and Xi Zhao; Writing – original draft, Jinyang Guo; Writing – review & editing, Yanxia Zhang, Mingzhao Zheng, Xi Zhao and Binglong Wu.

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Guo, J., Zhang, Y., Zheng, M. et al. Study on carbon emissions towards flange connection joints of assembled steel structures. Low-carbon Mater. Green Constr. 2 , 6 (2024). https://doi.org/10.1007/s44242-024-00036-8

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Published : 20 May 2024

DOI : https://doi.org/10.1007/s44242-024-00036-8

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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.

  PRESS RELEASE:

66 New Food and Beverage Industry Planned Project Reports – Modest Decline in April 2024

Research confirms 66 new projects as compared to 73 in march 2024.

Source: Industrial SalesLeads Inc   |   Thu, 16 May 2024, 07:00:28 EDT

JACKSONVILLE BEACH, Fla., May 16, 2024 (SEND2PRESS NEWSWIRE) — Industrial SalesLeads announced today the March 2024 results for the new planned capital project spending report for the Food and Beverage industry. The Firm tracks North American planned industrial capital project activity; including facility expansions, new plant construction and significant equipment modernization projects. Research confirms 66 new projects as compared to 73 in March 2024.

The following are selected highlights on new Food and Beverage industry construction news .

Food and Beverage Project Type

• Processing Facilities – 41 New Projects
• Distribution and Industrial Warehouse – 26 New Projects

Food and Beverage Project Scope/Activity

• New Construction – 22 New Projects
• Expansion – 16 New Projects
• Renovations/Equipment Upgrades – 31 New Projects
• Plant Closing – 6 New Projects

Food and Beverage Project Location (Top 10 States)

California – 7

Illinois – 6

Ohio – 5

Florida – 4

Indiana – 4

Michigan – 3

Ontario – 3

Texas – 3

Wisconsin – 3

Colorado – 2

Largest Planned Project

During the month of March, our research team identified 5 new Food and Beverage facility construction projects with an estimated value of $100 million or more.

The largest project is owned by Daisy Brand, who is investing $708 million for the construction of a 750,000 sf processing and warehouse facility in BOONE, IA. They are currently seeking approval for the project.

Top 10 Tracked Food and Beverage Projects

SOUTH DAKOTA:

Startup dairy company is planning to invest $191 million for the construction of a processing facility in KINGSBURY COUNTY, SD. They have recently received approval for the project.

Nutritional product mfr. is planning to invest $128 million for the expansion, renovations, and equipment upgrades on their processing, laboratory, office, and storage facilities at 5101 Spaulding Plaza SE and 7575 Fulton Street E. in ADA, MI. They are currently seeking approval for the project.

Chocolate mfr. is planning for the renovation and equipment upgrades on a recently acquired 700,000 sf processing, warehouse, and office facility at 1 Hershey Dr. in SMITHS FALLS, ON. They are currently seeking approval for the project.

Dairy company is planning to invest $84 million for the expansion and equipment upgrades on their processing facility in WINCHESTER, VA. They have recently received approval for the project.

Food processing company is planning to invest $65 million for a 120,000 sf expansion, renovations, and equipment upgrades on a processing facility at 2295 E. 55th St. in CLEVELAND, OH. They are currently seeking approval for the project. Construction is expected to start in Summer 2024.

Startup snack food mfr. is planning to invest $55 million for the construction of an 80,000 sf processing facility at 250 Northcutt Rd. in LIMESTONE, ME. They have recently received approval for the project. Construction is expected to start in Summer 2024, with completion slated for late Fall 2025.

Cheese mfr. is planning for the renovation and equipment upgrades on a 310,500 sf warehouse facility in CALEDONIA, WI. They are currently seeking approval for the project.

CALIFORNIA:

Frozen food mfr. has recently agreed to pre-lease 204,000 sf of cold storage warehouse space in TULARE, CA. They will relocate a portion of their operations from NEVADA upon completion in Fall 2024.

Animal feed mfr. is planning to invest $12 million for the construction of a 100,000 sf warehouse facility in CRAWFORD TOWNSHIP, OH. They have recently received approval for the project.

RHODE ISLAND:

Food service distributor is planning for the renovation and equipment upgrades on a recently leased 84,000 sf processing facility at 100 Higginson Ave. in LINCOLN, RI. They will relocate their operations upon completion.

About Industrial SalesLeads, Inc.

Since 1959, Industrial SalesLeads, based in Jacksonville, FL is a leader in delivering industrial capital project intelligence and prospecting services for sales and marketing teams to ensure a predictable and scalable pipeline. Our Industrial Market Intelligence, IMI identifies timely insights on companies planning significant capital investments such as new construction, expansion, relocation, equipment modernization and plant closings in industrial facilities. The Outsourced Prospecting Services, an extension to your sales team, is designed to drive growth with qualified meetings and appointments for your internal sales team. Visit us at salesleadsinc.com.

Each month, our team provides hundreds of industrial reports within a variety of industries, including:

• Industrial Manufacturing
• Food and Beverage
• Power Generation
• Pulp Paper and Wood
• Oil and Gas
• Mining and Aggregates
• Research and Development
• Distribution and Supply Chain
• Pharmaceutical
• Industrial Buildings
• Waste Water Treatment
• Data Centers

Learn more: https://www.salesleadsinc.com/industry/food-and-beverage/

News Source: Industrial SalesLeads Inc

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STORY FILED UNDER: Food and Beverage | AP | Business | Construction and Building | Florida Business | Jacksonville Business | Reports and Studies

planned capital project spending report

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ABOUT THE NEWS SOURCE: Industrial SalesLeads Inc

Since 1959, Industrial SalesLeads, based in Jacksonville, FL is a leader in delivering industrial capital project intelligence and prospecting services for sales and marketing teams to ensure a predictable and scalable pipeline. Our Industrial Market Intelligence, The company identifies timely insights on companies planning significant capital investments such as new construction, expansion, relocation, equipment modernization and plant closings in industrial facilities.

More Information: https://www.salesleadsinc.com/

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REFERENCES: Food and Beverage News, Industrial SalesLeads, Food and Beverage Industry Planned Projects, warehouse, material handling, logistics, distribution center, manufacturing, industrial, food and beverage | ID:118458