Search

Reducing carbon dioxide (CO 2) emissions in the iron and steel industry plays a crucial role in addressing global climate change. One significant technological solution for reducing CO 2 emissions in iron and steel production is the recycling of waste heat. Hot air sintering has the potential to decrease CO 2 emissions from flue gas by reusing hot flue gas in the production process. This can result in a reduction in the consumption of fossil fuels. Usually, the relationship between the hot air temperature and the carbon content determines the CO 2 emission reduction effect. In order to meet the demand for reducing CO 2 emissions, this paper thoroughly investigates the mechanism of CO 2 reduction by hot air sintering through sintering pot experiments. It precisely establishes the correlation between hot air temperature and carbon content, and suggests strategies for effectively managing hot air sintering based on scientific principles. The results show that hot air sintering achieves a reduction in CO 2 emissions by enhancing fuel combustion heat utilization and heat substitution. On the one hand, the heat of the sinter bed surface layer is increased, which improves the mineralization conditions and increases the sintered mineral quantity and quality, thus reducing the CO 2 emission by 4.4%; on the other hand, the waste heat is returned to the sinter bed to replace part of the fuel combustion heat, thus reducing the CO 2 emission by 17.7%. The experimental results show that the best carbon reduction effect is achieved at a hot air temperature of 300 °C and a solid fuel ratio of 4.7% (labelled T300-C47), which reduces carbon emissions by 17.7% and improves the quality of the sintered minerals. Combined with the actual production, in the range of 200–300 °C hot air, by increasing the hot air temperature to replace the solid fuel with equal heat can realize the hot air sintering to reduce CO 2 emissions and improve the sintering production. The research provides theoretical guidance for the clean production of iron and steel sintering and energy saving and carbon reduction. [ABSTRACT FROM AUTHOR]

Abstract Given the fast-paced world economy, increasing carbon dioxide (CO 2) emissions have caused serious concern regarding global warming. Many studies have examined the nexus between CO 2 emissions and economic growth and inconsistent results are provided. Limited evidence suggests that different time periods under investigation could be a source of inconsistency, but there lacks of a thorough analysis. This paper systematically focuses on the evolutionary characteristics of the nexus to explore the influence of time periods. The panel data are reorganized by considering different time periods in various countries, and an intelligent data-driven approach, symbolic regression, is applied to discover models for each period without predefined structure and parameters. Three issues (Does the time period matter? What are the trends in different time periods? What are the applicable scopes of the models?) have been addressed in this paper. The results reveal the evolutionary nature of the nexus and it is verified that an intrinsic time period distinction does generate extrinsic inconsistency. The detailed dynamics of models indicate that the optimal models tend to be more complex as the time periods are extended. For countries with different locations and income levels, the applicable scopes of the four superior models (monotonically increasing, inverted U-shaped, inverted N-shaped, and M-shaped) vary in different time periods. The findings highlight that the effect of time periods cannot be ignored and the models should not be applied unconditionally when conducting empirical research. Finally, several policy implications are provided, which are critical for the balance of economic growth and CO 2 emissions, particularly in some developing countries. Highlights • The inconsistency of nexus between CO 2 emissions and economic growth is examined. • The intrinsic time period difference does generate extrinsic nexus inconsistency. • The effect of time period is verified from geographic and socioeconomic aspects. • Rich evidence is revealed for the evolutionary nature of the relationship. [ABSTRACT FROM AUTHOR]

Abstract Water supply systems have a significant environmental and energetic impact due to the large amount of energy consumed in water pumping and water losses. The safe and efficient operation of these systems is crucial, where digital tools, such as monitoring, hydro-informatics, and optimization algorithms, are key approaches that can play an important role on support decisions. This paper presents a hybrid optimization method to improve the energy efficiency of a water supply system towards a more sustainable water management concerning the water-energy nexus. A genetic algorithm was used to optimize the pumping schedule during the day. Knowing the water consumption a priori , it is possible to define the optimal pump status for a specific timeframe (e.g. every 1 h), minimizing the operation costs, and also the energy consumption and associated carbon dioxide emissions. Knowledge-based mechanisms, like introducing known feasible solutions in the population and selective mutation mechanisms, were introduced in order to boost the algorithm convergence. A model of the water network developed in the hydraulic simulator EPANET was used to evaluate the solutions. All the physical constraints of the water supply system (e.g. hydraulic compliances) and water demands must be met for each solution, including the level limits of the water storage tanks. From the obtained solutions, it is found that optimizing the pump scheduling can improve the energy efficiency up to 15% in average (maximum of 25%) comparatively to the real operation, although this value can severely decrease if a conservative approach is assumed of maintaining more water stored in the tanks (low-risk approach). Similar improvements were achieved for cost and carbon dioxide emissions. Besides knowledge-based mechanisms, the analysis of the water storage risk was also an innovative outcome of this paper. Finally, digital tools can be used to optimize the system with minimal investment in equipment or physical intervention, although optimal solutions depend on water availability, water demand, and water storage risk. Highlights • Optimal pumping reduces up to 25% of the energy consumption and carbon emissions. • Improving water systems efficiency contribute to sustainable consumption patters. • Using the risk level in the water tanks may be crucial in costs reduction. • Digital water systems are becoming crucial sustainability tools. • Knowledge-based mechanisms in optimization can improve solutions exploitation. [ABSTRACT FROM AUTHOR]

Abstract China is under great pressure to reduce CO 2 emissions (CEs). Meanwhile, China's economy is more reliant on domestic consumption (particularly household consumption) than on exports. So, to achieve large-scale CEs' reduction for China, there is urgent need to study the CO 2 emissions from household consumption (CEs HC). Based on the environmentally extended Multiregional Input-Output model, this paper not only calculates both the direct CO 2 emissions from household consumption (DCEs-CH) and the indirect CO 2 emissions from household consumption （ICEs CH）at the provincial level in China, but also splits ICEs CH into domestic and foreign CEs. The findings of this paper are as follows: (1) between 2002 and 2012, CEs HC in China increased significantly, by 2.27 times, from 1306.17 Mt in 2002 to 2971.01 Mt in 2012. The CO 2 emissions from urban household consumption (CEs UHC) in China accounted for 75% of the total CEs HC in 2012. (2) The per capita CEs HC in China increased from 1.02 t/person in 2002 to 2.19 t/person in 2012. There was a prominent disparity in the total CEs and per capital CEs HC among the provinces in China. The per capita CEs HC were larger in provinces with a higher level of urbanization and higher per capita income. (3) The large-scale interprovincial transfer of ICEs caused by household consumption mainly occurred either within the Yangtze River Delta, the Pearl River Delta, and the Jing-Jin-Ji region or among these three regions. In addition, to service the household consumption, the energy-abundant provinces transferred a considerable amount of CEs to eastern coastal provinces. To achieve CEs' reduction, consumption-based strategies, such as lifestyle changes, should be required in parallel with strategies to reduce emission intensities on the producer side in China. Urban households should take more responsibility for the reduction of CEs in China. The interprovincial "Carbon leakage" should be taken into account when making policies for CEs' reduction in China. [ABSTRACT FROM AUTHOR]

Abstract Cities do play significant roles in tackling global environmental changes. Decoupling economic growth from environmental pressures is critical for global sustainable development, however, few studies pay attention to the decoupling analysis at city level. This paper conducts a comparative study of the decoupling performance of economic output from CO 2 emissions between Beijing and Shanghai, the top two cities in China. In this paper, the decoupling trends and the decoupling effects are explored from a sectoral perspective, by combining the Tapio decoupling elasticity and the logarithmic mean Divisia index (LMDI) model. The results show that Beijing and Shanghai both experienced weak decoupling in construction, expansive negative decoupling in transport, expansive coupling in trade, and weak decoupling in others over the period 2000–2015. Moreover, agriculture appeared strong decoupling in Beijing, and recessive decoupling in Shanghai; industry showed strong decoupling in Beijing, and weak decoupling in Shanghai. The decoupling effects showed different magnitudes and patterns in industrial sectors between Beijing and Shanghai. Overall, per-capita GDP and population growth inhibited the decoupling, while energy intensity, industrial share, energy mix accelerated the decoupling process. Highlights • The decoupling of sectoral economic output from carbon emissions in Beijing and Shanghai are investigated. • Beijing's industry enjoyed better decoupling performance than Shanghai's industry. • Transport should be put more emphasis in further decoupling efforts. • Energy intensity is crucial effect accelerating the decoupling process. [ABSTRACT FROM AUTHOR]

Abstract Natural resource endowment has a significant influence on manufacturing structure which in turn influences CO 2 emissions. This paper investigates the effect of the rationalization and upgrading of manufacturing structure on carbon dioxide emissions in China, based on the perspective of natural resource dependence. The results of the STIRPAT model on provincial panel data of the manufacturing sector from 2003 to 2014 show that manufacturing structure rationalization and upgrading will help curb CO 2 emissions, while such effects are restricted by a region's reliance on natural resources. The panel threshold model estimations further indicate that the greater the ratio of industrial output to GDP, the weaker the restricting effect of resource dependence on the emissions reduction of manufacturing structure. These findings reveal that the development strategies of manufacturing structural rationalization and upgrading that aim to reduce emissions depend on the level of a region's resource dependence and industrialization. Highlights • The STIRPAT model and panel threshold model are employed in this paper. • Manufacturing structure rationalization and upgrading will help to curb carbon dioxide emissions. • The emissions reduction effect of structural transformation is affected by resource dependence. • A higher degree of industrialization can weaken the restricting effect of resource dependence. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we adopt a non-radial directional distance function to analyze the efficiency and shadow price of CO 2 emissions of coal-fired power plants. Using a sample of Shanghai's 20 coal-fired power plants, we find that the efficiency performance of power plants remained steady during the period 2007–2010. On average, the carbon abatement costs of Shanghai's power plants increased from 20.58 yuan/ton to 39.67 yuan/ton during 2007–2010. Although the average shadow price of the power plants increased during the period, the price was still well below shadow prices for the energy consumption of the industries, and a little lower than the trading price in the ETS markets. In addition, the paper discusses the implications of the findings. [ABSTRACT FROM AUTHOR]

The energy demand and CO 2 emissions of the steel processing industry are a global challenge. During conventional steel processing, the treatment of iron ore and steel in a molten state heavily contributes to this problem. This paper provides an in-depth investigation of the benefits and technical requirements of an alternative processing pathway with minimal energy and CO 2 burdens. Our proposed method, scrap metal consolidation (SMC) by rolling , is adapted from roll bonding, a scalable metal bonding technique, commonly used for niche composite applications to achieve material properties unattainable by monolithic alloy design. SMC transforms steel scrap into hot rolled steel in solid state without melting. Based on pre-published high-fidelity industrial data, we determined that processing hot rolled steel from scrap in the solid state would consume 94% less energy compared to the primary steel processing route with 94% less CO 2 burden. Compared to conventional recycling methods, the energy savings of SMC would be 86%, with an 84% decrease in CO 2 emissions. The proposed method is described in detail, and the process windows for AISI 1008 mild steel and SS304 stainless steel were determined in terms of rolling temperature and reduction using a lab-scale rolling mill at a temperature range of 700–1100 °C. The formability of the consolidated mild steel is also evaluated via the hemisphere punch test, a standard industrial test for assessing the formability of sheet metals. While the fracture height of consolidated specimens is in the 9.27–10.62 mm range, the monolithic sample has a fracture height of 10.34 mm. The test results show that the consolidated sheets have comparable formability to monolithic specimens. These investigations altogether demonstrate that SMC-by-rolling is a feasible and environmentally sustainable alternative for conventional steelmaking or recycling processes. [Display omitted] • Solid-state consolidation of steel scrap uses 94% less energy than primary processing. • Compared to recycling, scrap metal consolidation saves 84% of process CO 2 emissions. • Process boundaries for mild and stainless steel follow a reverse S-curve trend. • Test results exhibit comparable formability for roll-bonded and monolithic samples. • Most sheet metal forming operations don't cause opening stress, reducing failure risk. [ABSTRACT FROM AUTHOR]

The aim of this paper is to analyze the main determinants of the economic acceptability of four Green Technologies (GTs): alternative fuel vehicles, energy savings in residential buildings, smart meters and renewable electricity, using a meta-analysis on a sample of 35 selected papers, which provided 245 primary data. This approach allows detecting relationships across heterogeneous studies, avoiding the subjectivity of qualitative surveys. We implement a new two-step procedure. First, we compute a measure of the implicit price for a kilogram of CO2 avoided (PCO2), homogenizing the usable information for the GTs considered. Second, we conduct a meta-regression using the computed PCO2 values to estimate the socio-economic determinants' impact. In general, our results show a wide degree of acceptability for GTs which is stronger among European citizens. In particular, it emerges that, on average, the estimated PCO2 is positive for the GTs considered, and additional positive effects exist when respondents are confronted with an explicit reference to quantitative targets in terms of CO2 abatement, a clear proposal for payment timing, and a specific renewable electricity mix. These results indicate that information and transparency are crucial to spur GTs deployment. Therefore, to support GTs’ market penetration, public and private institutional stakeholders, have to provide “ad hoc” information to the end users, setting a clear and suitable system of prices to increase the economic value end users place on GTs. [ABSTRACT FROM AUTHOR]

E-commerce has emerged through digital platforms and Internet construction as an important way to achieve low-carbon development in China. To evaluate the mitigation effect of e-commerce, this paper conducts a quasi-natural experiment in terms of the pilot policy of national e-commerce demonstration cities (NEDC) to explore the changes in CO 2 emissions of 270 cities from 2004 to 2017 in China. We also check the asymmetry, mechanism effects and heterogeneity. The results show that the treated cities reduce CO 2 emissions by 4.1% due to the NEDC pilot policy compared to the untreated cities. The estimated results pass the parallel trend test, robustness tests, and the Goodman-Bacon decomposition. Moreover, the NEDC pilot policy increases the CO 2 emissions of treated cities by promoting economic growth (scale effect), and decreases the carbon emissions of treated cities by upgrading the industrial structure (structural effect) and increasing the technological innovation level (technical effect). Furthermore, the CO 2 mitigation effects of the NEDC pilot policy are significantly concentrated in the higher quantiles. Finally, the NEDC pilot policy has significantly negative effects on CO 2 emissions in "postage-free regions," southern China, and cities with large e-commerce sales. The results of this paper provide theoretical and practical references for China to achieve low-carbon development. • Evaluating the impact of pilot policies of national e-commerce demonstration cities (NEDC) on carbon emissions in China. • The NEDC pilot policy reduces carbon emissions of treated cities by 4.1%. • The NEDC pilot policy reduces carbon emissions through structural and technical effects. • The emission-reduction effects are significant at the higher quantiles. • The impact of the NEDC pilot policy on carbon emissions is obviously heterogeneous. [ABSTRACT FROM AUTHOR]

Under the background of "double carbon", ecological water has become one of the significant resources to ensure the healthy and sustainable development of the regional ecological environment. And the ecological water consumption prediction is a prerequisite for optimizing water supply structures. Considering the impact of CO 2 emissions on ecological water consumption, the FGM(1,1) model was firstly used to predict CO 2 emissions considered as an impact factor in this paper. Then, an adjacent accumulative grey multivariate convolution model (AGMC(1,N)) was combined with the Average Weakening Buffer Operator (AWBO) to predict the annual ecological water consumption of 30 provinces (municipalities and autonomous regions) in China. The results show that the AGMC(1,N) model combined with the AWBO has better prediction effect. In addition, in the next decade, only six provinces in the northern region will have a decreasing trend in ecological water consumption. However, the other provinces are showing an upward trend. The ecological water consumption trends deviate from the CO 2 emission trends in 12 provinces. The research results are beneficial for the formulation of the ecological water consumption policies and the achievement of the dual carbon goals. [ABSTRACT FROM AUTHOR]

In order to probe collaborative environmental governance (CEG) in China's "1 + N" policy framework for carbon peak and carbon neutrality, this paper applies the Actor-network theory (ANT) as an analytical framework to explore carbon reduction policy coordination. We then model ANT's relations with an evolutionary game theory (EGT) model to examine the evolutionarily stable strategies in CO 2 emission reduction by various actors including the central government, local governments, commercial banks, and polluting enterprises. Our objective is to examine policy coordination as the key enabler for governing success via an ANT-based mechanism design in China's institutional context. Combining the strength of ANT with a four-party EGT model, we investigate how to improve policy coordination to mobilize the actor-network for promoting CEG. Simulations are conducted to examine the effectiveness of policy coordination involving multiple policy instruments for controlling carbon emissions. The central government fulfills leadership in translating the interests of other actors and shaping the desired collaborative network. Without proper coordination, environmental policies may counteract each other. Government transfers and subsidies have direct impacts, but in the long run enhanced competitiveness and profitability of enterprises represent the intrinsic key to CEG success. From a methodology perspective, policy simulation in an EGT framework represents a novel addition to the research toolbox that expands ANT. [ABSTRACT FROM AUTHOR]

Developing green materials for infrastructure construction is of vital importance for sustainable development. Limestone calcined clay cement (LC3) is an appropriate alternative for the reduction of CO 2 emissions and resource consumption in the cement industry. Recycled concrete aggregate (RCA), seawater and sea sand are potentially advantageous from a sustainability perspective, especially in coastal regions. Fiber-reinforced polymer (FRP) bars with excellent corrosion resistance are ideal alternative materials for steel bars in a corrosive environment. In this paper, a new type of green concrete structure incorporating LC3, seawater, sea sand, RCA, and FRP bars was investigated, and the performance was assessed to verify the considerable sustainable advantages while considering life cycle cost and environmental impacts. The results showed that the proposed LC3 concrete exhibited lower environmental impacts: compared with traditional concrete, and the CO 2 and energy consumption of LC3 concrete were reduced by 32%–41.7% and 23.3%–28%, respectively. Although the initial cost was higher for LC3 and CFRP bars, this disadvantage could be offset by their longer service life and lower maintenance costs during their life cycle. Compared with traditional RC structures, the total cost, CO 2 and energy consumption in the life cycle were reduced by 39%, 30.5%–65.4%, and 18.5%–58.9% for the LC3 concrete structure, respectively. In contrast to the life cycle cost, the LC3 replacement ratio had a negative effect on the environmental indices for the LC3 concrete and structure. Considering the promising advantages in economy and environmental impact, the proposed LC3 concrete and structure provides an effective approach for the sustainable development of the construction industry. • A type of green concrete structure incorporating LC3, seawater, sea sand, RCA, and FRP bars. • LC3 concrete exhibits lower environmental impacts, decreased as the LC3 replacement ratio increases. • LC3 concrete structure shows excellent environmental and economic advantages. [ABSTRACT FROM AUTHOR]

Cereal grains are widely used as staple foods, therefore ensuring a steady supply of food globally requires cereal production, and South Asia contributes significantly to this endeavor. However, the global food system is thought to be responsible for around one-fourth of all greenhouse gas (GHG) emissions, with grain production being a major contributor to this system. With the increasing need for food, especially cereal grains, it is difficult to reduce GHG emissions from food production on limited land. However, the cereal production - land use - agricultural GHG emissions nexus has been disregarded in earlier studies which needs to be identified for the sustainable food production system. Therefore, this research aims to assess the interactions between agricultural GHG emissions, food production index, and land usage on cereal production in South Asia. This study employs the Fully Modified Ordinary Least Square (FMOLS) model as a baseline model for a panel data set of 1990–2020 and further checks the validity via Dynamic Ordinary Least Square (DOLS) and robust least square procedure to tackle the endogeneity, serial correlation, and outlier issues. Findings confirm that growing the food production index and land usage boosts cereal grain production in South Asia, whereas rising agricultural CO 2 emissions lessen output in the long run. In this paper, we also deploy Dumitrescu and Hurlin's (2012) panel causality test to prove a dual causal connection between the food production index, land use, and cereal food production. From a policy perspective, the findings indicate the necessity of integrating green agro-technology into land cultivation practices in order to achieve increased grain production and mitigate GHG emissions originating from the agricultural sector. [ABSTRACT FROM AUTHOR]

Meeting energy needs and ensuring ecological sustainability are important tasks for policymakers. In particular, changing the energy mix used in daily electricity generation can have a major effect on ecological conditions, and this is a previously neglected research topic. Therefore, this paper aims to investigate the influence of daily electricity generation from nuclear power and renewables on the achievement of carbon neutrality targets in the four largest nuclear power countries (i.e., the U.S., China, France, and Russia). The study applies the wavelet-transform coherence (WTC), quantile-on-quantile regression (QQR), and Granger causality in quantiles (GCQ) approaches for the period from January 2, 2019 to December 29, 2022. The outcomes present that electricity generation from nuclear energy reduces carbon (CO 2) emissions only in Russia, while hydropower generation does not contribute to CO 2 emission reduction in any country. Solar electricity generation decreases CO 2 emissions in different quantiles in the U.S. and Russia, while electricity generation from wind power reduces CO 2 emissions in the U.S. and France. The empirical outcomes also reveal that expanding solar, wind, and nuclear power in the energy mix can enhance the potential of the U.S., France, and Russia to achieve carbon neutrality and secure a sustainable future. However, China is using nuclear and renewables inefficiently regarding carbon neutrality. Therefore, the empirical evidence for China is highly controversial compared to former studies. [Display omitted] • The study examines renewable and nuclear electricity effect on carbon neutrality. • The study focuses on top four major nuclear power countries. • The study applies nonlinear approaches by using high-frequency (daily) data. • Renewable and nuclear electricity have time, frequency, & quantile-varying effect. • The best electricity source change according to each country. [ABSTRACT FROM AUTHOR]

This paper implements the multi-criteria design optimization of three-dimensional reinforced concrete frame building structures, considering aspects such as the realistic design of the elements, including foundations within the structural assembly, or considering the soil-structure interaction. The criteria for a more comprehensive sustainable approach are related to environmental, constructive, and durability aspects. The environmental factor is measured through CO 2 emissions, considering its capture due to concrete carbonation. The use of multi-objective strategies is evident in solving the multi-criteria problem. Still, it is also proposed to formulate this problem with a single function containing all the criteria to solve it as a single-objective optimization problem. Strategies are also offered to perform multi-objective optimization based on Kriging metamodels. Several alternatives for multi-criteria decision-making are explored. The results show that multi-objective metamodel-based optimization is a good strategy for solving this problem. Alternatively, the results of the single-objective optimization of the multi-criteria problem are very satisfactory. The solutions obtained are analyzed according to the type of optimization and the decision-making criteria. Optimized solutions significantly improve the sustainability indexes compared to traditional design. Multi-criteria optimization contributes significantly to achieving these indexes. Therefore, the proposed methodology allows for the sustainable design of any reinforced concrete frame structure. It highlights the importance of integrating more encompassing formulations and advanced optimization techniques into traditional design procedures to adopt cleaner production practices in the construction sector. Finally, several promising lines of research are presented. • Multi-criteria optimization of a 3D RC frame building structure. • Single and multi-objective optimization of the multi-criteria problem. • Kriging-based multi-objective optimization is a valuable alternative. • Single-objective optimization of multi-criteria problem is quite effective. • The proposed methodology allows for an encompassing sustainable design of RC structures. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a methodology to measure the environmental co-benefits of transport initiatives, defined here as carbon emissions in conjunction with local air pollution. An evaluation tool was developed and then tested on the case of the Delhi metro. The metro is an extensive rail project spanning the Indian capital, which is also the world's first rail based Clean Development Mechanism (CDM) project. However, it has also been a flashpoint in urban policy-making in the city in recent years. This analysis identifies the co-benefits based on the current situation as well potential co-benefits based on increased ridership and altering mode share contributions. The paper then discusses the challenges faced in the quantification process and the practical implications of achieving increased co-benefits. The paper highlights issues of data quality as well as data access, whilst identifying that factors peripheral to the project itself can have a critical effect in achieving co-benefits from large scale transport infrastructure projects in developing countries. [Copyright &y& Elsevier]

Because of the increasing international trade, monitoring tools are required that quantify and analyze CO 2 emissions at a global level. This paper contributes to this literature by adopting a consumer-oriented approach and using two tools based on Multi-Regional Input-Output tables, i.e., the Global Emissions Chains (GECs) and the Global Emissions Trees (GETs). The GEC is proposed with an industry-level perspective so as to provide detailed information about the extent to which the final demand of an industry of a country drives indirect CO 2 emissions by any industry of any other country. The GET is defined as a simplified graphical structure of the GEC, which includes only the industries providing the highest contribution of CO 2 emissions. The tools are described and new indices are developed with the aim of conducting multiple analyses with different purposes. Applications are given with specific emphasis to the different analyses that can be carried out. In particular, the GEC and the GET of a specific Italian industry are presented and comparisons with GECs and GETs of different countries are discussed. How to use the tools to develop more effective decarbonization strategies at both country and global levels is also described. • Two tools to map CO 2 emission flows at the global level are proposed: GECs and GETs. • The Global Emission Chains highlight indirect CO 2 emissions driven by final demand. • The Global Emission Trees graphically show the most relevant part of GECs. • Indices to analyze both tools and provide further information are designed. • Applications of both tools can drive effective decarbonization strategies. [ABSTRACT FROM AUTHOR]

This paper investigates a location problem of public charging stations for electric vehicles with the objective of CO 2 emissions minimization through massive GPS-enabled trajectory data. The problem considers two distinct features, including CO 2 emissions generated in round trips to charging stations and remaining electricity restrictions on charging decisions. A data-driven and particle swarm optimization-based intelligent optimization approach is developed to handle this problem. We then present how to implement this approach by using taxi trip data in Chengdu, China as case data and explore how much data could reflect effectively the travel patterns of an area. The results of case study show that one-week taxi trip data are sufficient to handle the investigated problem. The results also validate the necessity of considering two realistic features, including CO 2 emissions in round trips to charging stations and remaining electricity restrictions on charging decisions, in charging station location problems. It can lead to (1) the reduction of daily CO 2 emissions captured by about 0.14–0.37 ha of forests in one year, and (2) 0.85%–2.64% more charging demands being satisfied per day. Flowchart of the proposed intelligent approach. Image 1010 • A location problem of public charging stations based on GPS-enabled trajectory data is studied. • A data-driven PSO-based intelligent optimization approach is proposed. • One-week data could reflect the travel patterns of a region well. • The impacts of two important realistic features are considered. [ABSTRACT FROM AUTHOR]

The household sector of China is responsible for 11.7% of national energy consumption and 12.6% of carbon dioxide (CO 2) emissions in 2015. Thus, revealing the determinants of household CO 2 emissions (HCE) is extremely important for national efforts towards emissions mitigation. In this context, this paper investigates the driving forces behind national and regional HCE changes employing a temporal Logarithmic Mean Divisia Index (LMDI) model. It also analyses interregional discrepancies in HCE using a spatial LMDI model. This study decomposes the changes or discrepancies of national and regional HCE from 2000 to 2015 into seven key factors. The temporal analysis indicates that household income is the predominant determinant explaining the increase of HCE, whereas energy intensity is the crucial determinant contributing to the mitigation of HCE. The spatial analysis reveals that the number of households and energy intensity are primary driving forces accountable for growing discrepancies in HCE, followed by household income, energy structure and carbon emission coefficient. The analysis also suggests that resourceful and economically developed regions generally have larger potential for mitigation of HCE. The study concludes with some policy recommendations based on the results. [ABSTRACT FROM AUTHOR]

Abstract As significant contributors to global carbon dioxide (CO 2) emissions, the international construction sector is under great pressure to mitigate CO 2 emissions and slow global warming more aggressively. The aim of this study is to measure and compare the sectoral CO 2 emission linkages and their structures in the construction sectors of 41 countries over 1995–2009 by combing a hybrid multi-regional input–output (MRIO) model and the hypothesis extraction method. The backward and forward CO 2 emission linkages indicate that the international construction sector plays a significant role in importing CO 2 emissions from upstream industries, while the export of CO 2 emissions to downstream industries is relatively minimal. Four fundamental linkage elements show that the net backward CO 2 emission linkages account for the largest proportion, followed by the mixed and net forward CO 2 emission linkages, while the mixed backward CO 2 emission linkages are relatively small. The leading CO 2 emission inflows are from the energy, resource and raw-material sectors. The outflows from the construction sector are mainly to the real estate and public utilities sectors. Based on these findings, the paper puts forward countermeasures for the global construction sector to improve energy efficiency, promote industrial structure upgrading and improve the policy system for greenhouse gas emission reduction. [ABSTRACT FROM AUTHOR]

Abstract This paper investigates the neglected potential of carbon dioxide (CO 2) emissions reduction from highway maintenance projects. Conventional assessment (CA) on fuel combustion of off-road equipment during maintenance, and a comprehensive life cycle assessment (LCA) on the materials production, fuel production, traffic delay and maintenance equipment were conducted for four typical maintenance schemes in a real highway project in China, through Microsoft spreadsheet models, VISSIM and CMEM model. The focus of the case study was to understand the magnitude and source of the gap of CO 2 emissions assessment results between LCA and CA. In this study, we also checked scenarios that apply a few mitigation options from several industrial sectors in four typical maintenance schemes to investigate how significant potential for decarbonization of the highway maintenance might be neglected without using LCA. Results suggest that there exists an obvious gap between the total CO 2 emissions per lane per kilometer of CA and that of LCA, and the gap is even up to 22 times of the CA results in this specific case study. Traffic delay caused by the lane closure has the largest contribution to the gap, while the shares of materials production and fuel production match. The scenarios analysis of mitigation strategies associated with the transport sector and other industrial sectors indicates that the LCA model could effectively identify the dominant inputs and CO 2 emissions outputs of individual maintenance process in the complicated transport system, while CA may neglect or underestimate the potential for adopting some mitigation strategies, especially for mitigation options from other industrial sectors. Highlights • The neglected potential for carbon dioxide emissions reduction from highway maintenance project in China are explored. • The gap of CO 2 emissions calculation results between LCA and Conventional assessment (CA) are examined. • The magnitude and sources of the above gap are analyzed. • The practicability of LCA in assessing mitigation options from industrial sectors on the transport systems are identified. [ABSTRACT FROM AUTHOR]

Abstract Carbon emissions from the Chilean public transport sector have doubled between 2000 and 2013. Thus, the need to find alternative clean-air solutions is becoming increasingly critical. With this in mind, this paper addresses a solution to the aforementioned problem by studying the conversion of both taxis and "colectivos" (public taxis with defined routes) into electric vehicles (EV) to be used in the Chilean public transport sector. In Chile, 80% of taxis are Nissan V16s, meaning that all of these vehicles will be replaced and end up in landfills within the next 5–8 years. This study presents an option to give a second life to these vehicles, addressing environmental and financial issues. It compares emissions from the Nissan V16's conventional internal combustion engine (ICE) with an equivalent electric conversion prototype. Furthermore, it analyses the CO 2 emissions from the EV that has been fully charged by the Chilean grid as well as one that has been charged by a solar photovoltaic system. A solar recharging station for EV taxis is designed, taking advantage of the high levels of solar radiation in Chile. The results show that EV conversion does not lead to real environmental benefits, in comparison to its ICE equivalent, when it is charged with the grid. However, the results also show a considerable decrease in cost and CO 2 emissions per km travelled when using solar energy to charge the batteries. Future challenges include identifying solutions to cope with solar intermittence and minimizing CO 2 emissions during periods of low radiation. Highlights • Conversion of ICE taxis into EVs in Chile. • Comparison of emissions of the Nissan V16 ICE with its electric conversion prototype. • Design of solar charging stations considering solar irradiation available in Chile. • Conversion does not show benefits when EV charged from electricity grid in comparison to ICV. • Results show decrease in running cost and CO2 emissions when EV charged from solar electricity. [ABSTRACT FROM AUTHOR]

Abstract With a greater awareness of responsibility for the environment and the need to sustain profitability in a competitive market, reverse logistics has become a key part of supply chain management. This paper therefore seeks to consider the designing and planning of a green forward and reverse logistics network, through a mixed integer linear programming model. The model is applied to a multi-stage, multi-product, and multi-objective problem whereby the first objective is to minimize the cost of operations, processes, transportation, and fixed costs of the establishment. The second objective is to minimize the amount of CO 2 emissions based on the gram unit, while the third is to optimize the number of machines in the production line. For validation, the model is applied to the home appliance industry through several test problems. In terms of the solution methodology, an epsilon-constraint method is developed as the area of optimization in order to obtain a set of Pareto solutions. Finally, sensitivity analysis is conducted to understand the effects of changes in the demand, cost, and rate of return of the used product, on the objective function values. Highlights • The proposed model considers both forward and reverse green logistics integrally. • Minimization of the number of machines in the production line as objective function is proposed. • An epsilon-constraint method is applied to solve green forward and reverse logistics model. • In order to validate the obtained solutions, sensitivity analysis is provided. • The model and solution approach is validated through a real home appliances case study. [ABSTRACT FROM AUTHOR]

Abstract Most existing works using a displacement estimation method to estimate the CO 2 emissions abated by wind energy are based on the current operating principles of the power system. They consider a fixed displacement emission factor since wind energy is assumed to replace high-carbon generation. This method may be unsuitable in the long run when the energy mix of most countries becomes more decarbonised. Consequently, wind energy would replace those technologies becoming increasingly predominant in the future, i.e. lower polluting fossil fuels such as natural gas and even other less competitive low-carbon technologies. In order to consider this effect, this paper proposes a new method that estimates a range of potential CO 2 emissions abated by wind energy based on two dynamic displacement emission factors, which are periodically updated according to the evolution of the future energy mix. Such factors represent an upper and a lower limit of CO 2 emissions avoided. The method is validated in the case study of the European Union over the period 2015–2050. The results show that the annual displacement emission factor by wind energy may vary from about 422 to 741 t CO 2 /GWh in 2015 to around 222–515 t CO 2 /GWh in 2050. The total CO 2 abatement ranges from about 6600 to 13100 Mt CO 2 in the period 2015–2050. Highlights • A new method to estimate the potential CO 2 abatement of wind energy is proposed. • New dynamic displacement emission factors consider future decarbonisation of the energy mix. • A case of study is analysed: The European Union over the period 2015–2050. • CO 2 abatement in Europe may range from about 6600 to 13100 Mt CO 2 during 2015–2050. [ABSTRACT FROM AUTHOR]

Abstract The negative appraisals of the impact of airline industry on climate change have forced the industry to become greener. Over the past several decades, CO 2 emissions in the airline industry have increased considerably, thereby adversely affecting the environment. Therefore, airlines are seeking different approaches to reduce the environmental degradation. In this paper, we study cruise speed control to achieve this goal by reducing CO 2 emissions while studying passenger service level. We use some indicators to measure the passenger service level in the airline industry. These indicators create a conflict between CO 2 emissions and passenger service level. We develop a bi-objective mixed-integer non-linear programming model to integrate flight scheduling, aircraft-path assignment, and gate assignment with the aim of reducing CO 2 emissions while increasing passenger service level. Based on a real problem, the model can lead to 11% and 31% improvement in CO 2 emissions and passenger service level, respectively. The model is NP-hard. Therefore, we develop a new constructive heuristic method, and we also use the multi-objective simulated annealing algorithm and extend this algorithm to enhance its performance. We also use the design of experiment and Taguchi method to optimize the algorithms parameters. Finally, we evaluate the proposed methods based on information retrieved from major U.S. airlines. [ABSTRACT FROM AUTHOR]

Abstract Logistics performance plays an important role in green supply chain management that leads to environmental sustainability. The objective of this paper is to analyze the nexus between logistics performance and environmental degradation using data obtained from 42 Asian countries between 2007 and 2016. The system-generalized method of moment (GMM) regression model was used to investigate the data from Asian countries collectively and the four sub-regions of Asia. The estimates show that the logistics performance is significantly related to environmental degradation. International shipment in logistics performance index (LPI) significantly decreases CO 2 emissions while timeliness of logistics significantly intensifies the CO 2 emissions in Asian countries. Other sub-categories in LPI such as tracking and tracing, services quality and competence, infrastructure quality, and efficiency of customs also have a significant impact on the environment in different sub-regions of Asia. Industrialization and urbanization both increase CO 2 emissions in Asian countries while trade openness decreases CO 2 emissions. The results indicate a significant association between logistics performance and environment that accentuates the priorities on environmental sustainability and green supply chain management in Asian countries. Highlights • Identified the impact of logistics performance on the environment from an international perspective. • The efficiency of international shipment in Asia has negative effects on environmental degradation. • The timeliness of logistics significantly intensifies CO 2 emissions in the Asian countries. • Logistics performance indicators have a different impact on the environment in the four sub-regions of Asia. • Urbanization, trade openness and industrialization have significant inferences on the environment in Asian countries. [ABSTRACT FROM AUTHOR]

Abstract: This article provides an introduction to this Special Issue of Journal of Cleaner Production (JCLP), which contains thirteen, carefully selected articles from the 12th Conference, “Process Integration, Modelling and Optimisation for Energy Saving and Pollution Reduction” – PRES''09. This issue builds upon the multi-year co-operation between the PRES conference planners and the JCLP. The articles cover important subjects of increased efficiency in energy generation and usage and in improvements in industrial process optimisation. The first group of five papers focuses upon recent advances in emissions reduction and the resulting energy penalties. The second group of four papers deals with improving the efficiency and reliability in the utilisation of renewable energy, where hydrogen and biodiesel are the key energy carriers. The final group of three papers focus on process integration challenges of sustainable energy systems and upon the challenges of industrial/societal integration of sustainable energy systems into regional sustainable development planning. [Copyright &y& Elsevier]

Abstract: This editorial introduces and provides an overview of this Special Issue dedicated to papers from the 7th conference Process Integration, Modelling and Optimisation for Energy Saving and Pollution Reduction – PRES 2004. It contains 10 selected papers. The first three papers address important features of cleaner production – renewable resources, CO2 emissions and Life Cycle Assessment. The second group of papers addresses cleaner production approaches to batch processed. The third set of papers studies reduction of emissions from industrial production including SO x and NO x . The last paper focuses upon minimisation of wastewater from industrial production. [Copyright &y& Elsevier]

In waste management, the assessment of CO 2 emissions offers the possibility to evaluate and compare the environmental impact of different waste treatment processes. Here, we compare the performance of waste incineration with alternative thermal treatment scenarios and recycling scenarios to the primary production of materials to analyze the respective CO 2 emissions. The aim is to determine whether thermal and material recycling of waste results in (net) CO 2 surpluses or reductions, thus, showing whether it makes sense for climate ambitions to recover waste, thermally or materially. A case study of an internationally active waste management company in Austria is analyzed, conducting a life cycle assessment of its thermal and material waste recycling. On thermal waste treatment the core of the analysis is the comparison with primary energy sources. Using waste as an energy source, especially in cement plants and the paper industry, has proven to be an effective technology for reducing CO 2 emissions. We also find current practices in material recycling to be of lower CO 2 emissions than alternative primary material supply. Scaling results to the national level we find that for the case of Austria current waste management practices have the potential to save an equivalent of 2.6% of Austria's total CO 2 emissions (all sectors) for thermal fractions and an equivalent of 1% for material recycling. [Display omitted] • CO 2 emission impact of thermal waste treatment replacing fossils in basic industry. • CO 2 emission impact of material waste recovery relative to primary production. • Quantification for full scale Central European waste management company. • Life Cycle Assessment to compare waste treatment methods. • Thermal and material recovery can reduce CO 2 emissions significantly. [ABSTRACT FROM AUTHOR]

The adoption of plug-in electric buses are seen as a promising alternative to reduce greenhouse gas (GHG) emissions in the public transport system. Although from an operational point of view this type of vehicles are zero-emissions, the upstream phase contribution can be considerably high in regions with high carbon grid intensities. This paper presents a simulation study to evaluate the energy consumption and the corresponding well-to-wheels (WTW) CO 2 emissions of conventional diesel, parallel hybrid and battery electric buses. The test case is the island of Tenerife, an isolated power system highly dependent on fossil-fuels for power generation. Validated models of the aforementioned propulsion architectures were simulated over five representative cycles, covering city and intercity lines with noticeable differences in terms of driving behaviour, distance and gradient. Although battery electric buses present energy consumption reductions of 70% compared to conventional powertrains, the large carbon grid intensity of the island has a negative effect on their potential to reduce WTW CO 2 emissions. The results evince that parallel hybrids provide the largest benefit to abate WTW CO 2 emissions, reaching a reduction figure of 38% compared to its conventional diesel counterpart. [ABSTRACT FROM AUTHOR]

Electric mobility is being studied as a possible solution for reducing the environmental impact associated to the transportation sector. However, there is a huge ongoing debate among scholars and practitioners on the extent to which Electric Vehicles perform better in terms of greenhouse gases emissions against Internal Combustion Engine Vehicles, and especially on the variables that affect such performance. To the best of our knowledge, most of the studies addressing the topic mainly focus only on some specific phases of a vehicle's life cycle, such as vehicle manufacturing and use, while comprehensive evaluations of the greenhouse gases emissions during a vehicle's life cycle are quite rare. Therefore, the paper aims to develop a comprehensive evaluation framework in order to estimate the environmental impact associated to Electric Vehicles and Internal Combustion Engine Vehicles, by adopting a Life Cycle Assessment approach. The evaluation framework is then adopted to estimate the environmental impact associated to Electric Vehicles and Internal Combustion Engine Vehicles in four different scenarios, each one assuming different countries in which the phases of a vehicle's life cycle take place. Results show that CO 2 emissions over the Electric Vehicle's life cycle are lower than the ones associated to a comparable Internal Combustion Engine Vehicle in all the scenarios analysed. Moreover, the analysis highlights: (i) the huge impact on a vehicle's CO 2 emissions associated to the geographical location in which the upstream phases of the vehicle supply chain take place (mainly for Electric Vehicles); (ii) the primary impact played by the use phase on the Electric Vehicles CO 2 emissions, followed by the vehicle and battery manufacturing ones. Both evidences reinforce the impact of the energy mix on the environmental performance of Electric Vehicles, as further confirmed by the sensitivity analysis. The paper contributes to the extant literature by reaffirming the better environmental performance of Electric Vehicles compared to Internal Combustion Engine Vehicles in terms of CO 2 emissions over the whole life cycle, also providing policymakers with useful suggestions for the promotion of Electric Vehicles as a means to tackle environmental issues. [ABSTRACT FROM AUTHOR]

Carbon taxes have been proposed as a major instrument to mitigate carbon emissions and promote an energy transition to low carbon sources. However, its adoption remains politically challenging, particularly amid rising inflation and energy prices. Despite the need for more aggressive action on carbon mitigation to reach the Paris Agreement goals, few countries in Latin America have adopted carbon taxes and the tax levels are relatively low. A key concern for these countries, is to adequately assess the tradeoffs between stricter emission goals and the potential negative economy wide as well as sectoral and distributive impacts. In this context, in this paper we first propose a step by step approach to enhance an existing dynamic Computable General Equilibrium (CGE) model for Chile based on OECD's Green model. The contribution of this research is twofold. Firstly, emission factors are estimated and the development of the electricity sector is aligned with the expectations of decision makers. As a result, credible emission and energy sector development forecasts are generated by the model, that are in line with what policymakers expect to happen based on other bottom-up engineering models. Secondly, this baseline is then used in the CGE model to examine the use of a carbon tax to reach Chile's first Nationally Determined Contribution. The required tax level is determined together with CO2 emissions and the economywide, sectoral and distributive impacts. The results allow concluding about the applicability of carbon taxes and possible complementary measures. [ABSTRACT FROM AUTHOR]

Life cycle inventory (LCI) data for hot mix asphalt (HMA) concrete pavements is largely missing in Brazil, despite the fact that HMA is the material used in 99% of the Brazilian road network. To overcome this deficiency and carry out life cycle assessment (LCA) studies in this area, Brazilian researchers have continuously resorted to background data based on the international context and hypothetical scenarios. However, these practices have not contributed to environmentally favorable decisions, as little information with national and local representativeness is being incorporated in LCI analyses of asphalt material. This study focused on the collection of primary LCI data for the stages of production of raw materials, manufacturing of asphalt mixture, and construction of a pavement in the context of the Amazon region. Four HMA dosages were studied in a reference (real) and an alternative scenario considering two types of filler: Portland cement and limestone powder. As expected, the stages of production of inputs and manufacturing of the asphalt mixture were the most impactful, representing, in the case study, 98% of the total CO2 emissions and 86% of the embodied energy. The most critical inputs were Portland cement in the production of raw materials, and heavy fuel in the manufacturing of asphalt. The use of light fuel and adoption of preventive maintenance in the plant promoted a reduction of 19% in the environmental impacts of the manufacturing stage. The incorporation of limestone powder in place of Portland cement promoted a decrease of 42% in the total emission of CO2 and embodied energy. • The paper aims to disseminate the primary data of CO2 emission in the Amazon, Brazil. • The paper aims to disseminate the primary data of incorporate energy in the Amazon, Brazil. • LCI calculated for pebble and sand available in the Amazon region. • The use of light fuel provided a reduction of 19% of the environmental impacts in the machining stage. • The use of limestone powder promoted a decrease of 42% in emission of CO2 Asphalt Pavements. [ABSTRACT FROM AUTHOR]

In this paper, we model the greenhouse gas (GHG) intensity of the electric grid in Ontario, Canada, at different temporal resolutions from 2010 through 2018. We developed a stochastic approach to estimate the lifecycle GHG emissions from each type of source of electricity, by assigning uncertainties to critical parameters (carbon dioxide (CO 2), methane and nitrous oxide emissions, and global warming potentials (GWP)), based on variations reported in the literature. The annual mean lifecycle GHG emissions from electricity generated in the province has declined from 175 to 58 g CO 2 e/kWh from 2010 to 2018, considering the GWP time horizon of 100 years. The downward trend is largely associated with the phasing out of coal plants, coupled with the gradually reduced use of natural gas plants, and the increased participation of nuclear and renewables in the mix over the years. We were also able to identify large variations in the lifecycle GHG emissions across months and hours: higher values are generally associated with demand peaks registered in the months of summer and winter, and daily from 5 to 8 p.m. The method employed for the analysis in this paper can serve as a benchmark for other studies on the lifecycle GHG emissions from electricity at various levels (national, provincial, regional, etc.). The Ontario-specific data obtained can serve as a basis for the evaluation of the lifecycle of various activities and sectors within the province. At the corporate level, companies reporting the GHG emissions of their projects and products can improve their estimates by capturing the variations of emissions from electricity generation at the various temporal resolutions. Image 1 • We used hourly generation data to model GHG intensity of electricity in Ontario. • Emissions from electricity declined from 175 to 58 g CO 2 e/kWh from 2010 to 2018. • Higher emissions are due to demand peaks: summer and winter, daily from 5 to 8 p.m. • Hourly GHG intensity varies by a factor of 4–5 within a single year. • Data obtained are useful for LCA practitioners, policy makers and companies. [ABSTRACT FROM AUTHOR]

It is clear that an increase in gases, due to fossil energy consumption, in the atmosphere has been causing greenhouse effect influencing the world's temperature. The effect of renewable usage, on the other hand, on global warming is not very clear. For instance, the influence of wind energy usage on Greenhouse Gas (GHG) has been a controversial research topic for the last two-three decades. Throughout some empirical analyses, some researches reached no evidence that wind can reduce global warming, as some other researches observed that the wind has proven to have a positive impact on environmental quality by lowering CO 2 emissions. This paper, on the other hand, reveals that wind usage can influence GHG positively or negatively at different time periods. By observing the monthly period 1989:1–2017:8, this paper examines the effect of wind energy usage on GHG emissions for the variables of wind energy consumption, coal consumption, natural gas consumption, other renewable energy consumption, and total energy consumption interrelated carbon dioxide (CO 2) emissions. This research launches the methodology of Morlet wavelet coherence analysis allowing a researcher to conduct the analyses of variables in both time and frequency dimensions. The research also performed Monte Carlo simulations with 1000, 2500, 5000 and 10000 replications to reach significant outputs. The paper, therefore, (a) observes whether there exists causality between the variables within the whole sample and all sub-samples together with other interrelated control variables, (b) monitors the significant causalities (co-movements) at different time frequencies, (c) hence, determines the potential influence of wind energy usage on CO 2 emissions at different time periods corresponding to different time frequencies. This paper eventually detects three significant emergent outcomes. The first outcome is that the increase in CO 2 led to enlarged use of wind energy for the periods 1999, 2001–2002, and 2015–2017. The second outcome is that wind energy consumption diminished the CO 2 emissions for the period 2015–2017. The 1st and 2nd outputs are obtained at 5% significance level. The third outcome is that the wind power turbines intensified the emissions during the periods 1991–2004 (at10% significance) and 1999–2002 (at 5% significance) in the US. This research later suggests therefore that policy makers consider the consumption of wind energy to reduce CO 2 emissions. • Observes the impact of wind energy power consumption on CO 2 emissions in the US. • Employs wavelet coherency and partial wavelet coherency analyses. • Reveals that wind power consumption contributes to CO 2 emissions for the period 1991-2005. • Yields that wind power consumption diminishes CO 2 emissions after 2015 in the US. [ABSTRACT FROM AUTHOR]

This paper examines the asymmetric and long-run effect of energy productivity on the quality of the environment in Finland. Finland, as one of the Nordic countries, is a major contributor to the global drive to achieve decarbonization by 2050. In effect, this study seeks to contribute to the strides by querying the extent to which shocks in energy productivity make or mar the sustainability of the Finland environment from 1990:Q1 to 2019:Q4. The other impacts of financial development, economic growth, and trade openness are considered in the model estimated by using the novel hidden panel cointegration and nonlinear autoregressive distributed lag (NARDL) methodology. The results reveal a significant asymmetric equilibrium cointegration relationship among the variables over long-run time horizons; energy productivity utilization enhances the quality of the environment in Finland over the long run while trade openness, financial development, and economic growth contribute to environmental degradation in Finland in the long term. In particular, a 1% positive and negative fluctuation in energy productivity lowers carbon emissions by 1.79442% and 0.84799% in the long term. Whereas 1% change in trade openness, financial development, and economic growth trigger CO 2 emissions (CO 2 E) by 1.15298%, 0.271365%, and 2.93402% in Finland's economies. The results of the frequency domain causality model corroborate the NARDL results. On the basis of these empirical findings, this study suggests that policymakers in Finland should consider the asymmetric behavior among these variables in setting their trade, environmental, growth, and energy policies. [Display omitted] • The effect of energy productivity on environmental degradation in Finland is examined. • Nonlinear ARDL, Fourier ADL cointegration and frequnecy domain causality tests are employed. • Energy productivity leads to lower environmental degradation in Finland. • Energy productivity causes environmental sustainability at different frequencies. [ABSTRACT FROM AUTHOR]

Rising global temperatures in the Arabian Peninsula region caused by climate change have increased the demand for air conditioning, resulting in more electricity consumption and CO 2 emissions. This paper treats Qatar as a representative country for understanding the effect of future regional warming on the electricity demand and CO 2 emissions We first develop a model that relates daily electricity demand with temperature. By combining this model with temperature projections from the CMIP6 database (bias adjusted and statistically downscaled) and population and GDP projections from four shared socioeconomic pathways (SSPs), we can calculate Qatar's demand for electricity until the end of the century. The model identifies an average sensitivity of +4.2%/°C for the electricity demand and projects an increase in electricity demand by 5–35% due to warming alone at the end of this century. The model suggests that under SSP1-2.6, warming-induced CO 2 emissions could be offset by carbon intensity improvements. Furthermore, under SSP5-8.5, assuming no carbon intensity improvement, future warming could add 20–35% of CO 2 emissions per year by the end of the century, with half of the electricity demand related to more frequent hot days. We further found that the temperature effect on power demand and CO 2 emissions is small compared to the effects from socioeconomic factors such as population, GDP, and carbon intensity. • Data-based model to predict electricity demand from daily temperature regionally. • Projection of power demand with CMIP6 temperature projections for different SSPs. • Inclusion of the effect of the evolution of the population and the GDP on the demand. • Assumption on the evolution of the carbon intensity to deduce the CO 2 emissions. • Application to Middle East countries and implication for global temperatures. [ABSTRACT FROM AUTHOR]

Understanding the drivers and peaks of CO 2 emissions at the provincial level plays a crucial role in achieving the goals of China's CO 2 emissions peak by 2030. This research combines the spatial-temporal Logarithmic Mean Division Index with scenario analysis to empirically explore the drivers and peaks of CO 2 emissions in 30 provinces in China during 1997 and 2020, considering COVID-19 effects. The results show that the energy structure has replaced the energy intensity as the main factor of emission reduction in 2020. The CO 2 emission driving mechanism at the provincial level is different from that at the country level. The population restrains the CO 2 emissions in Heilongjiang, Sichuan, and Guizhou. The energy structure increases CO 2 emissions in Hainan, Ningxia, Shanxi, and Xinjiang. The role of driving factors to CO 2 emissions varies greatly among provinces. The population effect is strong in Shandong, Guangdong, and Henan. The economic effect is significant in Shanghai, Jiangsu, and Tianjin. The energy intensity effect is remarkable in Shanxi, Ningxia, and Inner Mongolia. The energy structure effect is profound in Shanxi, Inner Mongolia, and Henan. Based on our findings, China's CO 2 emissions peak will occur in 2030 and 2025 under baseline and green development scenarios. Many provinces have already reached their peaks, including Chongqing, Yunnan, Beijing, Tianjin, Qinghai, Shanghai, Jilin, Hubei, Heilongjiang, Hebei, Sichuan, Anhui, Guizhou, and Henan. However, Xinjiang and Shanxi will not reach their peaks by 2030. Based on the findings, this paper put forward several policy implications. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic lockdowns led to a sharp drop in socio-economic activities in China in 2020, including reductions in fossil fuel use, industry productions, and traffic volumes. China's economy suffered a serious negative effect from COVID-19. However, there is a "positive effect" on CO 2 emissions reduction. Here, for the first time, this paper constructs a new model named "Weighted Multi-regional Hypothetical Extraction Method (WMHEM)" based on a multiregional input-output model. It not only solves the problems of traditional HEM methods such as improper use of assumptions, excessive reliance on industry intermediate input, but also accurately reflects the impact of external shocks on the inter-industry linkages. By using the monthly economic data of each provinces in China during COVID-19 (except Hong Kong，Macao and Taiwan) an the latest Multi-regional input-output tables, the "economic negative effect" and "CO 2 emission positive effect" under COVID-19 in China are measured. Results show that COVID-19 lockdown was estimated to have reduced China's CO 2 emissions substantially between January and March in 2020, with the largest reductions in February. With the spread of coronavirus controlled, China's CO 2 emissions rebounded in April. In addition, key emission reduction sectors and key development encouraged sectors are selected by combining "economic negative effect" and "CO 2 emission positive effect" during COVID-19. Therefore, policies recommendations are put forward based on forward and backward linkages respectively which are from two ends of the supply chain to turn pandemic-related CO 2 emissions declines into firm climate action. • COVID-19 has negative effects on economy, but positive effects on CO 2 emissions. • A new model is used to measure economic and CO 2 emission effects during COVID-19. • Hubei had the biggest economic and CO 2 emission effects on China due to COVID-19. • Economic and CO 2 emission effects of COVID-19 are combined to select key sectors. [ABSTRACT FROM AUTHOR]

This paper studies the link between carbon dioxide (C O 2 ) emissions and income inequality in France over 1980–2018, focusing on the choice of income inequality indicators in use. To do so, we use a new source of data on net (post-tax and transfer) income inequality indicators using net Gini and Atkinson indexes. We also use market (pre-tax and transfer) income inequality indicators utilizing the market Gini index and share of market income earned by the richest 10% of the population. Using the autoregressive distributed lag (ARDL) model, we find that income inequality has a different impact on C O 2 emissions, depending on the income definition used for estimated disparities. Furthermore, the ARDL test shows that the market inequality coefficients are non-significant. However, net inequality indicators reduce C O 2 emissions, and these results are consistent with the marginal propensity to emit theories, where some inequality could remain necessary to environmental quality. • Investigate the relationship between income inequality and C O 2 emissions in France, using alternative income inequality indicators. • We apply the method of ARDL for estimations. • We find that the relationship between income inequality and C O 2 emissions varies with income inequality measure. • Empirical findings suggest ensuring environmental policies besides income redistribution policy. [ABSTRACT FROM AUTHOR]

This paper aims to explore whether the female share on the boards of directors of companies influences CO2 emissions in both developed and emerging markets. Furthermore, the influence of cultural diversity on the board of directors on CO2 emissions is analysed. A sample of companies belonging to the MSCI and MSCI Emerging Market indices in Europe over ten years (2010–2019) was analysed using regression models with panel data. The results demonstrate that in both developed and developing markets, the ratio of women to men on the board of directors is inversely related to the company's CO2 emissions, which support legitimacy theory in two aspects: it fulfils the right to equality and non-discrimination for women, and it also reduces CO2 emissions. In general, cultural diversity had a negative influence on CO2 emissions. This research is relevant for policymakers and managers seeking to improve sustainability and equality policies in companies. If gender equality in corporate monitoring roles is environmentally beneficial for the planet, legislators will support quota policies. In addition, shareholders will have an incentive to implement gender equality policies, as they will legitimise the company in the eyes of society, which has economic benefits. On a practical level, this work will contribute to achieving gender equality in corporate governance and improve the understanding of factors influencing CO2 emissions to the environment. This study contributes to previous research since it is the first time that developed and emerging countries have been analysed with the same methodology in relation to gender and CO2 emissions. Moreover, this research differentiates between emission-sensitive and insensitive sectors, and it is the only study to carry out a sector-by-sector and a country-by-country analysis. Furthermore, cultural diversity on corporate boards has been scarcely studied so far in relation to CO2 emissions. • Gender diversity on boards of directors is associated to lower CO2 emissions. • Cultural diversity on boards of directors is positively related to CO2 emissions. • Improving gender balances on board of directors is a sustainable strategy. • Gender equality policies on corporate boards favor climate action and life on land. • Legal gender quotas on corporate boards contribute to good health and well-being. [ABSTRACT FROM AUTHOR]

Abstract: Despite the importance that environmental management systems have in the environmental policy agenda, the debate on their effectiveness to improve environmental performance (e.g. the reduction of polluting emissions) is still open among researchers and practitioners. Furthermore, no previous quantitative works have addressed the comparative study of the effectiveness of the two main reference standards that set requirements for an environmental management system: the international standard ISO 14001 and the European EMAS scheme. In order to fill this gap, this research paper investigates the impacts of EMAS and ISO 14001 on the reduction of carbonic anhydride emissions on 229 energy intensive plants in Italy. By applying a rigorous statistical method, the results suggest that the implementation of an environmental management system in energy intensive industries has a clear influence on environmental performance both in the short and in the long term, but a different effect of ISO 14001 and EMAS on environmental performance occurs. [Copyright &y& Elsevier]

As the world's largest carbon emitter, China faces serious air pollution problems. Given that both carbon dioxide and air pollutants mainly come from burning of fossil fuels, the coal-to-gas policy has received widespread attention as a way to steer the public towards cleaner energy. However, inflexibility in the early implementation of the coal-to-gas policy caused a shortage of natural gas, and thus had negatively influenced households' lives. Considering the importance of clarifying the economic and environmental impacts of the coal-to-gas policy, this paper employs a dynamic recursive computable general equilibrium (CGE) model and sets different substitution scenarios, to simulate the impacts of the coal-to-gas policy on gross domestic product (GDP), sectoral output, trade, carbon emission reduction, and air quality improvement. The simulation results show that the long-term damage to GDP will be weaker than the short-term one, and carbon emissions would be reduced by 280 and 300 million tons in 2030 under the high and full substitution scenarios, respectively. The emissions of air pollutants (SO 2 and NO x) would also decrease significantly. Moreover, our results indicate that it is feasible to increase the substitution ratio in a stepwise manner and eventually achieve full substitution, which can not only effectively avoid shortages of natural gas, but also promote the coordinated control of carbon dioxide and air pollution emissions. • Coal-to-gas policy is a more effective way to reduce CO 2 emissions than SO 2 and NO x emissions. • The full alternative scenario with a step-by-step substitution approach should be adopted. • Coal-to-gas policy will reduce GDP, and the long-term impact is weaker than the short-term impact. • Some subsidies or tax incentives could be given to exports of resource-intensive goods. [ABSTRACT FROM AUTHOR]

The development of China's highway infrastructure has led to a rapid increase in carbon dioxide (CO 2) emissions while facilitating social and economic development. This paper introduces highway mileage and CO 2 emissions into the traditional production density model, using agglomeration as a mediating variable, to theoretically discuss the path through which highway infrastructure influences CO 2 emissions. We then use the spatial Durbin model (SDM) to verify the explanatory power of the expanded production density model based on panel data of China's 278 cities from 2003 to 2016. Empirical results indicate that (1) there is an inverted U-shaped relationship between highway infrastructure and CO 2 emissions in both local and peripheral cities; (2) highway infrastructure affects local CO 2 emissions through the agglomeration pathway but impacts CO 2 emissions in peripheral cities mainly through the spatial spillover effect of highway infrastructure; and (3) the U-shaped impact of highway infrastructure on CO 2 emissions in western China is diametrically opposed to the results for the east, the central region and the total sample. Therefore, China needs to fully consider the environmental effects of agglomeration to formulate a global emission reduction strategy when building highway infrastructure. Moreover, strategies based on the different stages of highway infrastructure development should be enacted and should be part of a spatially synergistic joint emission reduction mechanism while considering the characteristics of regional development. • The study extends the production density model and verifies the explanatory power. • The spatial correlation between variables is tested by the spatial Durbin model. • Regional heterogeneity is discussed, and the reasons for this are analysed. • The results are corrected using GS2SLS with slope as an instrumental variable. • Related policy recommendations are made for low carbon development in China. [ABSTRACT FROM AUTHOR]

The implementation of environmental regulation needs to consider not only pollution control but also its impact on economic growth. Using the provincial panel data in China from 2000 to 2017, this paper constructs dynamic spatial panel models and employs system GMM approach to evaluate the nonlinear and spatial effects of environmental regulation on economic growth and CO 2 emissions, respectively. The results suggest that, first, environmental regulation presents a significant "N"-shaped effect on economic growth and an inverted "N" effect on CO 2 emissions at the national level and in the eastern and central regions; while the effects are both"N"-shaped in the western region. Second, environmental regulation presents significant spatial effects on economic growth and CO 2 emissions. The enhancement of regional environmental regulation helps the economic growth and CO 2 emissions reduction in neighboring provinces at the national level and in the eastern and central regions, however, the spatial effects are opposite in the western provinces, proving the co-exists of "race to the top" and "race to the bottom" strategies of environmental regulation competition among China's regions. Third, the effects of environmental regulation on economic growth and CO 2 emissions are affected by FDI, and the moderating effect of FDI is regional heterogenous. • Building a dynamic spatial panel model based on the spatial spillover theory. • Proving an "N"-type effect of environmental regulation on economic growth. • The effect of environmental regulation on CO 2 emissions is regionally different. • Environmental regulation affects the role of FDI on economy and CO 2 emissions. • The spatial spillover effects of environmental regulation are proved. [ABSTRACT FROM AUTHOR]

Abstract: In China, Rapid economic growth has stimulated fast urban expansion and rural household income and consumption expenditure. In current paper, an input–output method is used to determine the impact of China’s increased urban and rural household consumption on carbon emissions. The results shows that the direct and indirect CO2 emission from household consumption accounted for more than 40% of total carbon emissions from primary energy utilization in China in 1992–2007. The population increase, expansion of urbanization and the increase of household consumption per capita all contribute to an increase of indirect carbon emissions, while carbon intensity decline mitigates the growth of carbon emissions. Therefore, at the domestic level, household consumption is of great significance for CO2 emission, which could be mitigated through changing the composition of goods and services consumed by households, and switching to consumption pattern of less carbon-intensive products. The government must consider the substantial contribution of household consumption to carbon emissions when China is encouraging consumption in order to address the current global financial crisis. [Copyright &y& Elsevier]

Abstract: Energy conservation is a key measure for reducing CO2 emissions. However, realising the emission reduction potential of an energy conservation investment depends on many factors, such as energy prices. The EU emissions trading scheme has made the investment analysis more complicated and increased the economic value of operational flexibility under fluctuating carbon prices. The different operational options in industrial energy production complicate the estimation of CO2 reduction potential in the investment phase. Increasing operational flexibility enables optimisation in the economic dimension, which may lead to less than optimum CO2 reduction. In our case study, which analysed the effects of an energy conservation investment made in the pulp and paper industry, the deviation from the expected emission reduction was around 30% over the period from 2000 to 2007. However, it seems that with high carbon prices, increasing operational flexibility has no significant effect on the carbon emissions. In policy-making, the freedom of action that is made possible by increasing operational flexibility should be taken into account when evaluating the contribution of an individual energy efficiency investment towards meeting the national targets for energy efficiency improvement and CO2 emission reduction. [Copyright &y& Elsevier]

While the deployment of technological innovation was able to avert a devastating global supply chain fallout arising from the impact of ravaging COronaVIrus Disease 19 (COVID-19) pandemic, little is known about potential environmental cost of such achievement. The aim of this paper is to identify the determinants of logistics performance and investigate its empirical linkages with economic and environmental indicators. We built a macro-level dataset for the top 25 ranked logistics countries from 2007 to 2018, conducting a set of panel data tests on cross-sectional dependence, stationarity and cointegration, to provide preliminary insights. Empirical estimates from Fully Modified Ordinary Least Squares (FMOLS), Generalized Method of Moments (GMM), and Quantile Regression (QR) model suggest that technological innovation, Human Development Index (HDI), urbanization, and trade openness significantly boost logistic performance, whereas employment and Gross Fixed Capital Formation (GFCF) fail to respond in such a desirable path. In turn, an increase in the Logistic Performance Index (LPI) is found to worsen economic growth. Finally, LPI exhibits a large positive effect on carbon emissions, which is congruent with a strand of the literature highlighting that the modern supply chain is far from being decarbonized. Thus, this evidence further suggest that more global efforts should be geared to attain a sustainable logistics. • Examining 25 topmost Logistics Countries on many fronts. • Technological innovation, HDI, urbanization, and trade openness spur logistic performance. • Logistic performance does not improve with employment rate and Gross Fixed Capital Formation. • Logistic performance increases carbon dioxide emissions. [ABSTRACT FROM AUTHOR]

Agricultural sector is the basic industry supporting the construction and development of national economy. With the continuous deterioration of agricultural pollution, measuring and understanding agricultural total factor productivity (AGTFP) is the important premise to achieve agricultural green development and clean production. Regarding carbon emissions and agricultural non-point source pollution (ANSP) as undesired outputs, this paper applies a three-stage Data Envelopment Analysis (DEA) method combined with the Slack-Based Measure (SBM) model to eliminate the influences of environmental factors and random errors and explore the real AGTFP of 30 provinces in China from 2000 to 2017.On this basis, the spatial distribution and dynamic changes of AGTFP before and after adjustment are further discussed to seek the underlying reasons. The empirical results demonstrate that AGTFP is lower when carbon emissions and ANSP are both considered, and it decreases from east to west in StageⅠbut the Northeast region surpasses the East to achieve the highest productivity after removing the interferences. Moreover, China's AGTFP has been restricted by the external environment, and superior external environment disguises the poor management efficiency of Beijing and Shanghai. Therefore, some policy implications to balance agricultural environment and economic development are proposed. [Display omitted] • Non-point source pollution and CO 2 are integrated to measure agricultural green efficiency. • A three-stage SBM-DEA approach is employed to calculate the real agricultural green total factor productivity. • Different environmental factors have different effects on the slack of agricultural inputs. • China's agricultural green total factor productivity is restricted by the external environment. [ABSTRACT FROM AUTHOR]