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In the backdrop of growing global concern on escalating CO₂ emission leading to climate disorder and controversy between economic growth and environment, this study undertakes a decomposition analysis of the top 20 emitters of the world during 1992–2016 with two objectives: to identify the relative contribution of the major driving factors in CO₂ emission and to comprehend the role and performance of sectoral energy consumption pattern in changing the emission level.

The paper uses variance analysis method to perform two stage decomposition: first, it decomposes emission into the major driving factors, and, secondly, it also decomposes fossil fuel intensity of different sectors into fuel mix and energy intensity effects, which are new in the literature.

The results indicate that aggressive pursuit for economic growth, particularly by developing countries, is the major reason behind unprecedented emission growth, with income effect, fossil fuel intensity effect and population effect having substantial roles. Considerable decline in dependence on fossil fuel, coupled with rising emissions, signifies that emission intensity is still to be harnessed. Sectoral decomposition shows that while fossil fuel intensity has declined in residential sector, it has remarkably shot up in industry, transport and commercial sectors. On the other hand, sectoral energy intensity has declined, particularly due to favourable performances of transport and commercial sectors.

The detailed country-wise sectoral analysis identifies the sectors with favourable contribution in curtailing emission and lends a direction to other countries for policy making.

This study contributes by incorporating multi-country sectoral segregation in decomposition analysis. It focuses not only on energy intensity, but on the effect of energy substitution in each sector as well. It identifies the sectors that have lowered their dependence on fossil fuel to highlight that emission can effectively be dealt with through a prudent choice of fuel mix.

This paper aims to clarify the CO₂ emissions of global construction industries under the consideration of different patterns of international trade and thus to draw a comprehensive picture for understanding the international paths of CO₂ transfer to global construction industries.

This research inventories the CO₂ emissions induced by the final demand of 15 economies for construction products and explores the CO₂ intensities of these economies based on a multi-regional input–output model. This paper further decomposes CO₂ emissions into four components based on different patterns of international trade to estimate the roles of four patterns of international trade in shaping the environmental pressures from global construction industries.

The results indicate that the CO₂ intensities of the construction industries in Russia, India and China were higher than those in other economies, and the CO₂ intensities of global construction industries experienced a decline over the years 2000–2014. The decomposition analysis demonstrates that domestic and foreign CO₂ emissions accounted for 42.67 and 54.23%, respectively, of the CO₂ emissions of the construction industries in the 15 economies during the period 2000–2007. Although the major part of the CO₂ emissions of the construction industries come from domestic production systems, the final demand for construction products in the 15 economies caused substantial emissions in other economies. Further decomposition by upstream industrial production source indicates that 58.65% of domestic emissions and 66.53% of foreign emissions can be traced back to the electricity industry.

Although the major patterns of CO₂ emissions of the construction industry have been identified in this paper, the difficulty of understanding the relationship between upstream production industries or countries and the construction industry deserves more attention in the future research.

Previous research on inventorying CO₂ emissions has generally been limited to evaluating the impact of industrial consumption activities on national or global emission accounting, tending to ignore the effects of different international trade patterns on the change in industrial CO₂ emissions. This research is the first attempt to account for and decompose the CO₂ emissions of global construction industries under consideration of the effects of different patterns of international trade on environmental pressures. The decomposition and upstream industrial distributions of different patterns of CO₂ emission provide a comprehensive picture for better understanding of the emission pattern and source of the CO₂ emissions of global construction industries. The research outcomes reveal how the final demand of a country for construction products induces CO₂ emissions in both domestic and foreign systems, thus providing basic information and references for policy adjustment and strategy design in relation to mitigation of climate change and sustainable development.

This paper aims to better understand the linkage between CO₂ emitters and industrial consumers. The border-crossing frequency is applied to calculate the average number of steps that a country takes in relation to the CO₂ emissions of its construction industry. The maximum border-crossing frequency and declining speed of CO₂ transfer are used to reveal the relationship between the length of production chains and the transfer efficiency of construction products.

This paper maps the CO₂ transfer that accompanies global production chains using the frequency of border crossing in the production processes of construction products. As the basic analysis framework, a multi-regional input–output model is adopted to analyse the average border-crossing frequency of CO₂ transfer. Additionally, indicators including the maximum border-crossing frequency and declining speed of CO₂ transfer are employed. Also, the maximum border-crossing frequency and declining speed of CO₂ transfer are used to reveal the relationship between the length of production chains and the transfer efficiency of construction products.

The results indicate that 85.49% of the CO₂ in construction products needs to be processed in at least one country, reflecting that direct trade is the major pattern of transfer of CO₂ from primary producers in global construction industries. The maximum border-crossing frequency is 4.88 for 15 economies, meaning that construction products cross the international borders up to 4.88 times before they are absorbed by the final users. The scale of the average border-crossing frequency ranged from 1.16 to 1.87 over 2000–2014, indicating that the original construction products crossed the international borders at least 1.16 times to satisfy the final demand of the consuming countries.

The data from the economic MRIO tables in the WIOD are only available until 2014, which is a limitation for conducting this research in recent years.

The fragmentation of production is not only reshaping global trade patterns, but also leading to the separation of CO₂ emitters and final consumers in production chains. A growing number of studies have focussed on the impact of production fragmentation on accounting for regional and national CO₂ emissions, but little research has been done at the scale of a specific industry. The major contribution of this paper lies in mapping the CO₂ emissions that accompany the production chains of construction products from the perspectives of both magnitude and length. Additionally, this paper is the first to propose using maximum border-crossing frequency and declining speed to analyse the characteristics of global production chains induced by the final demand of major economies for construction products.

Purpose – This study provides insight on how Sub-Sahara African (SSA) countries can ameliorate the impact of environmental pollution in the face of increasing inflow of multinational corporations (MNCs).Design/methodology/approach – An analytical model describing the role of institutions in reducing the environmental impact of MNCs was formulated and analysed for a sample of 43 SSA countries (1996–2010) using descriptive and the System Generalised Method of Moments techniques.Findings – It was found that the ‘tragedy’ of environmental pollution can be ‘managed’ if there are strong institutional framework especially regulatory quality and government effectiveness that will drive environmental policies and make MNCs to comply to the tenets of corporate social responsibility (CSR) in host countries. The study also established that the environmental hazards in the previous year will occur in the current year, but with strong institutions in place, it will be at a decreasing rate. How increase in trade, inflow of MNCs and population growth affect the current extent of environmental pollution was underscored.Research limitation – Aggregated data on the variables were utilised, and thus the results were dependent on the reliability of the data. Examining how MNCs respond to CSR with respect to environmental issues in SSA can be taken up in future studies using micro-data. This will complement this study and further establish the impact of MNCs activities on the environment in SSA.Originality/value of chapter – The relevance of institutions in regulating the behaviours of MNCs with regards to environmental pollution in SSA was emphasised.

The calculation of buildings’ carbon footprint (CFP) is an important basis for formulating energy-saving and emission-reduction plans for building. As an important building type, there is currently no model that considers the time factor to accurately calculate the CFP of hospital building throughout their life cycle. This paper aims to establish a CFP calculation model that covers the life cycle of hospital building and considers time factor.

On the basis of field and literature research, the basic framework is built using dynamic life cycle assessment (DLCA), and the gray prediction model is used to predict the future value. Finally, a CFP model covering the whole life cycle has been constructed and applied to a hospital building in China.

The results applied to the case show that the CO₂ emission in the operation stage of the hospital building is much higher than that in other stages, and the total CO₂ emission in the dynamic and static analysis operation stage accounts for 83.66% and 79.03%, respectively; the difference of annual average emission of CO₂ reached 28.33%. The research results show that DLCA is more accurate than traditional static life cycle assessment (LCA) when measuring long-term objects such as carbon emissions in the whole life cycle of hospital building.

This research established a carbon emission calculation model that covers the life cycle of hospital building and considered time factor, which enriches the research on carbon emission of hospital building, a special and extensive public building, and dynamically quantifies the resource consumption of hospital building in the life cycle. This paper provided a certain reference for the green design, energy saving, emission reduction and efficient use of hospital building, obviously, the limitation is that this model is only applicable to hospital building.

This study aims to explore the interplay between CO2 emissions, financial development (FD) and foreign direct investment (FDI) in Asia-Pacific and Oceania. It also aims to understand short- and long-term impacts, emphasizing the role of FDI, FD and FD’s moderating effect on the FDI–CO2 relationship.

Using a 21-year panel data set (2000–2020) from 44 countries, the study employs the pooled mean group-autoregressive distributed lag (PMG-ARDL) model supplemented by the Dumitrescu–Hurlin panel causality test. This method assesses the complex dynamics and offers a robust analysis of short- and long-term effects in the Asia-Pacific and Oceanian context.

Long-term results indicate that FDI coupled with FD and FD’s moderating effect on FDI significantly contributes to CO2 emissions. Short-term relationships are more complex and lack statistical significance. FD positively moderates the FDI–CO2 relationship in the long run.

For investors, policymakers and stakeholders in Asia-Pacific and Oceania, the study highlights the importance of considering environmental impacts in investment decisions. The insights into the role of FDI and FD help craft policies and strategies for environmental sustainability.

Socially, this research emphasizes the necessity of a balanced approach to economic development, considering the potential long-term environmental consequences. Policymakers and stakeholders may use these findings to guide discussions and actions to achieve sustainable and socially responsible development in this dynamic region.

The findings contribute original insights into the essential relationships among FDI, FD and CO2 emissions in a diverse region like Asia-Pacific, enhancing the understanding of environmental implications in regions experiencing rapid economic growth.

A variety of gases, including water vapor (H2O), carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), add to the radiative forcing of Earth's atmosphere, meaning that they absorb certain wavelengths of infrared radiation (heat) that is leaving the Earth and thus raise the temperature of its atmosphere. Since glass has the same effect on the loss of heat from a greenhouse, these gases are known as “greenhouse” gases. It is fortunate that these gases are found in the atmosphere; without its natural greenhouse effect, Earth's temperature would be below the freezing point, and all waters on its surface would be ice. However, for the past 100 years or so, the concentrations of CO2, CH4, and N2O in the atmosphere have been rising as a result of human activities. An increase in the radiative forcing of Earth's atmosphere is destined to cause global warming, superimposed on the natural climate cycles that have characterized Earth's history.

This study aims to fill the gap in existing studies that have analyzed the drivers of carbon dioxide (CO₂) emissions. The author investigate the long-run effects of energy types, urbanization, financial development and, the interaction between urbanization and financial development on CO₂ emissions.

Stochastic impacts by regression on population, affluence and technology model served as the framework for empirical modeling. Using annual time-series data for Tunisia, autoregressive distributed lag bounds test was used to examine the cointegration of the variables. Also, the fully modified ordinary least squares was used to estimate the emission effect of the explanatory variables. Further investigations were done using the principal component analysis and variance decomposition analysis.

Income, urbanization, trade and financial development exert upward pressure on CO2 emissions. However, the interaction between urbanization and financial development reduces the emission of CO2. Furthermore, primary energy use, energy intensity, electricity consumption and fossil fuel consumption have positive effects on carbon emission, while combustible renewables and waste, and electricity production from natural gas have negative effects on carbon emission.

The policy implication/recommendation indicates that the financial sector’s authorities can combat carbon emission by properly regulating the development and activities of the financial sector in urban areas in Tunisia. The promotion of the development and usage of cleaner energy is recommended to help reduce carbon emission. Policymakers need to promote environmentally friendly economic growth and development agenda.

The contribution of this study to the environmental degradation literature is that it offers evidence from Tunisia, which has not received much empirical attention. It also examines the effect of various forms of energy usage on carbon emission. To the best of the author’s knowledge, this is the first study to examine the interaction effect between urbanization and financial development on carbon emission. Also, if not the first, this study is among the earliest to use the principal component analysis as a part of the prediction of the carbon emission effect of energy variables.

In 2001, the Intergovernmental Panel on Climate Change's Third Assessment Report revealed an important increase in the level of consensus concerning the reality of human-caused climate warming. The scientific basis for global warming has thus been sufficiently established to enable meaningful planning of appropriate policy responses to address global warming. As a result, the world's policy makers, governments, industries, energy producers/planners, and individuals from many other walks of life have increased their attention toward finding acceptable solutions to the challenge of global warming. This laudable increase in worldwide attention to this global-scale challenge has not, however, led to a heightened optimism that the required substantial reductions in carbon dioxide (CO2) emissions deemed necessary to stabilize the global climate can be achieved anytime soon. This fact is due in large part to several fundamental aspects of the climate system that interact to ensure that climate change is a phenomenon that will emerge over extensive timescales.

Although most of the warming observed during the 20th century is attributed to increased greenhouse gas concentrations, because of the high heat capacity of the world's oceans, further warming will lag added greenhouse gas concentrations by decades to centuries. Thus, today's enhanced atmospheric CO2 concentrations have already “wired in” a certain amount of future warming in the climate system, independent of human actions. Furthermore, as atmospheric CO2 concentrations increase, the world's natural CO2 “sinks” will begin to saturate, diminishing their ability to remove CO2 from the atmosphere. Future warming will also eventually cause melting of the Greenland and Antarctic ice sheets, which will contribute substantially to sea level rise, but only over hundreds to thousands of years. As a result, current generations have, in effect, decided to make future generations pay most of the direct and indirect costs of this major global problem. The longer the delay in reducing CO2 and other greenhouse gas emissions, the greater the burden of climate change will be for future life on earth.

Collectively, these phenomena comprise a “global warming dilemma.” On the one hand, the current level of global warming to date appears to be comparatively benign, about 0.6°C. This seemingly small warming to date has thus hardly been sufficient to spur the world to pursue aggressive CO2 emissions reduction policies. On the other hand, the decision to delay global emissions reductions in the absence of a current crisis is essentially a commitment to accept large levels of climate warming and sea level rise for many centuries. This dilemma is a difficult obstacle for policy makers to overcome, although better education of policy makers regarding the long-term consequences of climate change may assist in policy development.

The policy challenge is further exacerbated by factors that lie outside the realm of science. There are a host of values conflicts that conspire to prevent meaningful preventative actions on the global scale. These values conflicts are deeply rooted in our very globally diverse lifestyles and our national, cultural, religious, political, economic, environmental, and personal belief systems. This vast diversity of values and priorities inevitably leads to equally diverse opinions on who or what should pay for preventing or experiencing climate change, how much they should pay, when, and in what form. Ultimately, the challenge to all is to determine the extent to which we will be able to contribute to limiting the magnitude of this problem so as to preserve the quality of life for many future generations of life on earth.

Reductions in emissions intensity have been expressed in commitments of many countries’ intended nationally determined contribution. Energy structure adjustment is one of the main approaches to reduce carbon emissions. This paper aims to study the causal relationship between carbon emission intensity and energy consumption structure in China based on path analysis.

After data collection, this paper performs correlation analysis, regression and path analysis.

Correlation results display clear collinearity among energy structure variables. Regression finds that coal, oil, natural gas and technology can be used as indicators for carbon intensity while primary electricity has been excluded. Path analysis shows that coal had the largest direct and positive impact on emission intensity. Natural gas had a positive direct and negative indirect effect through its negative relationship with coal on emission intensity. Technology has the largest negative elasticity while all fossil energies are positive. Results indicate a negative effect of energy structure adjustment on China’s national carbon intensity.

Given the major role of China in global climate change mitigation, significant future reductions in China’s CO₂ emissions will require transformation toward low-carbon energy systems. Considering the important role in mitigating global climate change, China needs to transition toward a low-carbon energy system to significantly reduce its carbon intensity in the future.