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The pulp and paper industry is a high energy consuming and polluting sector, and carbon emissions emitted from this sector are worthy of attention. This article, based upon an analysis of China’s Pulp and Paper Industry (CPPI), provides estimates of each of the following: carbon emissions from energy consumption, pre-treatment sector, combustion of condensed black liquor, and methane emitted from incomplete aerobic digestion during sewage treatment of CPPI. During the study period (2005–2012), total CO 2 emissions ranged from 126.0 Mt to 155.4 Mt. Energy consumption was estimated to be the largest source of carbon emissions, however, due to the application of the local emission inventory rather than the IPCC inventory, energy consumption decreased by 4.7%, a lower percentage than was calculated in a previous study. According to this study’s estimation, the emissions caused by the recovery of biomass energy contributed 26–29% of the total CO 2 emissions. CH 4 generated from sewage treatment accounted for 9–11% of the total carbon emissions. The CO 2 intensity dropped during the study period, which reflected the improvement of energy efficiency in the pulp and paper industry. The outcome of this study provides not only detailed information about CPPI’s carbon emissions, but also a calculation framework for studying carbon emissions from pulp and paper sector in the other regions. It suggests that the local carbon emissions inventory should be used for estimating carbon emissions and to reduce the fossil fuel energy, increase energy recovery from biomass, and that promoting cleaner production is essential to achieve a low carbon development of the pulp and paper industry. [ABSTRACT FROM AUTHOR]

• We incorporate spatial factors affecting carbon emissions as drivers into the RF-CA model. • We change the constraints in the CA model for land use change prediction. • We predicted the land use change of Shanghai in 2025 under a low-carbon scenario. As global climate change intensifies, climate protection is important for the sustainable development of human society. In the process of urbanization and industrialization, carbon dioxide emissions are an important factor contributing to global warming. Therefore, modelling projections of future urban land use under low-carbon scenarios are essential for sustainability policy development. Few studies have focused on the impact of carbon emissions on urban land use change in Shanghai, as current research has primarily concentrated on developing methods for urban land use modelling. This paper utilizes a cellular automata (CA) simulation model based on the Random Forest (RF) algorithm to select various spatial variables of carbon emissions as the driving factors that affect urban land use changes. These variables include traffic location factors, economic development factors, electricity consumption, and population density. In this study, remote sensing imagery of urban nighttime lighting is also used to construct a simulation model of land use types in Shanghai. The model is then used to analyze the contribution of carbon emission constraints to urban land use changes. Actual historical land use data from 2013 and 2019 are used for validation, and the prediction model is used to predict land use outcomes under different low-carbon scenarios in 2025. The model is validated by simulating multiple intra-city land use maps for 2019 (kappa = 0.88, OA=92.71 %). The method of out-of-bag error from the random forest is used to evaluate the significance of carbon emission constraints. Using the validated model, the constraints in the CA model are changed to predict the land use simulation results of Shanghai in 2025 under different low-carbon scenarios. In terms of significance, factors such as distance to power plants, distance to major roads, real GDP, and population density can all have a significant impact on changes in urban land use. By selecting the low-carbon scenario with the most appropriate thresholds for each driver, it is possible to obtain the land use simulation results of Shanghai in 2025 under the optimal low-carbon scenario, while ensuring the high accuracy of the RF-CA model and simultaneously reducing the impact of factors on the city's overall carbon emissions. This paper provides a scientific base for urban planners and scholars to thoughtfully design urban land use while cutting down on carbon emissions. Furthermore, it can aid government agencies in establishing associated planning approaches. [ABSTRACT FROM AUTHOR]

The climate crisis is recognized as one of the world's most serious concerns, posing a threat to environmental, social, and economic growth. However, previous work has failed to address the dynamic effects through which economic growth may affect green growth and climate crisis. In this research, we take a closer look at the impact of carbon emissions, eco-innovation adoption, and international collaboration on economic growth and the influence of economic growth on green growth. This paper used the generalized method of moments (GMM) for 54 African countries from 2010 to 2019, allied with an imbalanced panel of 540 observations. This paper finds a positive relationship between carbon emissions, eco-innovation international cooperation, and economic growth with p-values lower than 0.047. Our study discovers economic growth's robust and positive impact on green growth with a p-value of 0.009. This research finds a three-pronged mediating effect of economic growth between its driving factors and green growth. Lastly, this paper furnishes new visions into the argument over economic growth versus green growth. It informs policymakers of the need to pay attention to the growing effect of eco-innovation driving factors on attaining sustainable and greener growth and climate crisis mitigation. [ABSTRACT FROM AUTHOR]

The urgent need to address climate change has led to global efforts towards achieving carbon neutrality. However, it is crucial to recognize the existence of carbon inequity, where certain regions or communities bear a disproportionate burden of carbon emissions compared to others. This paper explores the concept of carbon inequity and highlights the importance of considering driving factors in the pursuit of just energy transition. By examining the socioeconomic, environmental, and policy-related factors that contribute to carbon emissions, a comprehensive understanding of the underlying causes of carbon inequity is gained. The study emphasizes the need to address systemic issues such as economic development patterns, industrial structures, energy consumption habits, and social inequalities that perpetuate carbon inequity. It further discusses the significance of collaborative and inclusive approaches to carbon reduction, focusing on bridging the gap between regions with high and low carbon emissions. Policy implications are derived to guide decision-makers in formulating effective strategies for achieving carbon neutrality while ensuring equity and fairness. By considering both the overarching goal of carbon neutrality and the distributional aspects of carbon emissions, a more holistic and equitable approach can be adopted to accelerate the transition to a sustainable and low-carbon future. • It is crucial to recognize the existence of carbon inequity to address climate change. • This paper explores the concept and importance of carbon inequity of just energy transition. • Policy implications are derived to guide decision-makers while ensuring equity and fairness. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of climate change and technological innovation on economic growth, energy consumption, and carbon emissions by using annual observations of a wide range of variables of Asian and European countries from 1996 to 2021. The study uses a dynamic GMM model and reveals significant regional heterogeneity and time-varying effects of technological innovation on economic growth. Technological innovation plays a more substantial role in promoting sustainable economic growth in European countries compared to Asian countries. The study also uncovers a spatial linkage and dependence between climate change and technological innovation. The technological transfer from European countries has increased energy consumption and carbon emissions in Asian countries, leading to abnormal climate change. The paper underscores the importance of targeted technological innovation strategies in Asian countries to improve energy efficiency and mitigate climate change. The study also confirms the EKC hypothesis with an observed inverted U-shaped relationship between economic growth and carbon emissions. • There is a strong linkage among energy consumption, carbon emissions, climate change, and technological innovation. • Technological innovation plays a more significantly positive role for economic growth in European countries. • Technological innovation has a significant positive correlation on fossil energy consumption in Asia, while is negative in Europe. • The extreme climate changes lead to higher energy consumption in both Asian and European countries, while the technological innovation is the opposite. [ABSTRACT FROM AUTHOR]

The climate crisis and related events are often in the headline in recent years. The climate agreements reflected these concerns and called the researchers' attention to the urgent need for climate mitigation and adaptation policies. Many countries made new commitments during the latest United Nations Climate Conference (COP26) in November 2021 in Glasgow. In turn, scientists and experts worry that new pledges are not ambitious enough. The first environmental regulation was ratified in Great Britain in 1863. Later, the industrial and agricultural revolution stimulated pollution and brought about the emergence of environmental issues. The first agreement aiming to mitigate environmental pollution and stabilize greenhouse gas concentrations in the atmosphere was the United Nations Framework Convention on Climate Change (UNFCCC), adopted at the Rio Earth Summit in 1992. Behind the European Union, the contribution of the biggest polluter countries to climate change is also significant. The objective of the paper is to investigate the explanatory factors of CO 2 emission, focusing on the contribution of economic growth, agriculture, and trade along with free trade and climate agreements on climate change in Non-European Union member states, including the biggest emitters in the past two decades. In addition, it investigates the role of specific free trade agreements in emission cuts. The results showed an increase in CO 2 emissions in third countries, the reduction in the impact of agricultural export on greenhouse gas emissions, underlining the potential hidden effect of trade-related emissions between 2000 and 2018. NAFTA was encouraged while EFTA, ASEAN and MERCOSUR reduced emission growth. The USA, China, and Russia have the highest responsibility in controlling climate change. The findings reflect the limited progress and implementation of climate and trade policies and agricultural-related emissions in Non-EU countries. • Confirmed the validity of the U-shaped EKC curve in Non-EU countries. • Economic development stimulates while agricultural development reduces CO 2 emission. • Agricultural export has a sinking impact on GHGs in the rest of the world. • NAFTA encouraged while EFTA, MERCOSUR and ASEAN hindered CO 2 emission. • The USA, China, Russia have the highest responsibility in controlling emission. [ABSTRACT FROM AUTHOR]

The main challenge for most African countries is to find an alternative source of funding that can meet the needs of present generation without jeopardizing the needs of the future generations. Indeed, budgetary pressures are as defaults and economic recessions, combined with difficulties in accessing financial markets, which are often triggered by a series of sovereign debt restructurings and defaults, and have led some resource-rich African countries to turn to resource-backed loans to finance infrastructure projects to achieve long-term sustainable development goals. In this paper, we use the entropy balancing method to test whether resource-backed loans have a causal impact on the ecological efficiency of human development of African economies. Across a battery of robustness checks, the estimation results indicate that resource-backed loans have a positive and statistically significant impact on ecological efficiency of human development. Nonetheless, when resource-backed loans are disaggregated to run the regressions, we find that oil-backed loans and minerals resource-backed loans increase ecological efficiency of human development while cocoa and tobacco resource-backed loans are negatively associated to ecological efficiency of human development. The main findings of the study suggest that resource-backed loans agreements in general, and cocoa and tobacco in particular, should include strict clean development provisions and the implementation of actions to mitigate the negative environmental impact of these loans for borrowing countries. [ABSTRACT FROM AUTHOR]

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]

Renewable energy has demonstrated a significantly greater increase in its share of total energy consumption than carbon emissions in recent decades. This rise in renewable energy consumption did not effectively mitigate climate change, as evidenced by the accelerated rate of climate change. This paper aims to determine the cause of this failure by examining the total effect centrality and mediating effects of renewable energy in economic systems in the short run and long run. The total effect centrality and mediating effects of renewable energy illustrate the evolution of its overall impact on the major variables of an economic system and its role in mediating the indirect effects of these variables on carbon emissions, respectively. The study employs a recently developed network analysis that is a pioneer in the estimation of the time-varying total effect centrality and time-varying mediating effects of renewable energy, while also accounting for its cross-associations among all variables in a network. The study derives three conclusions by examining the three countries with the highest carbon emissions in their respective regions: the United States in North America, China in Asia, and Germany in Europe. First, renewable energy has become an essential element of economic systems, having a substantial total effect centrality on macroeconomic systems and, by way of its mediating effects, substantially mitigating the indirect effects of major macroeconomic variables on carbon emissions in the short run. Second, the total effect centrality and mediating effects of renewable energy diminish in the long run, indicating that its capacity to effectively mitigate climate change remains constrained in structural terms. Third, the long-term decline in total effect centrality rises by 0.3, 0.7, and 0.4 for the United States, Germany, and China, respectively. In the same nations, the long-term decline of mediating effects rises by 0.2, 0.4, and 0.2, respectively. The study provides pertinent policy recommendations on how to augment the total effect centrality and mediating effects of renewable energy in economic systems. [Display omitted] • Explains why renewable energy failed in curbing the accelaration of climate change. • Introduces the 'total effect centrality' of renewable energy in economic systems. • Illustrates the time-varying mediation role of renewable energy in economic systems. [ABSTRACT FROM AUTHOR]

In the context of the global response to climate change, methanol is receiving widespread attention as a potentially clean, renewable fuel. In this paper, the effects of injection timing and split injection strategy on the combustion process and emissions were investigated in methanol engines. The effect of mixture control on the ignition delay period was studied in detail. The results showed that when the injection timing was advanced to 95 °CA bTDC, the ignition delay period and combustion duration period were reduced by 28.96 % and 6.14 %, respectively. When the injection timing was delayed, the NO X emissions of the methanol engine were significantly reduced by 6.13 %–20.39 %. The use of split injection strategy enables the formation of a reasonably stratified fuel-air mixture in the cylinder. Under the optimized split injection strategy, the combustion duration was shortened by 0.93 %–14.58 %. The ignition delay period of the IT105S2 was shortened by 28.62 % compared with that of the original engine. In addition, the reasonable split injection strategy can effectively reduce the emission of formaldehyde and unburned methanol. This study provides an optimization direction for the application of methanol in the internal combustion engine for high efficiency and clean combustion. [Display omitted] • Split injection strategies and injection timing are studied on methanol engines. • NO X emission decreased by 6.13 %∼20.39 % as the injection timing is delayed. • Split injection facilitates the formation of a reasonably stratified mixture. • Combustion duration was reduced by 0.93 %∼14.58 % with split injection. • The formaldehyde and unburned methanol were reduced with spilt injection. [ABSTRACT FROM AUTHOR]

Abstract: A number of empirical methods have been developed to study China's sectoral carbon emissions (CSCE). Measuring these emissions is important for climate change mitigation. While several articles have reviewed specific methods, few attempts conduct a systematic analysis of all the major research methods. In total 807 papers were published on CSCE research between 1997 and 2017. The primary source of literature for this analysis was taken from the Web of Science database. Based on a bibliometric analysis using knowledge mapping with the software CiteSpace, the review identified five common families of methods: 1) environmentally-extended input-output analysis (EE-IOA), 2) index decomposition analysis (IDA), 3) econometrics, 4) carbon emission control efficiency evaluation and 5) simulation. The research revealed the main trends in each family of methods and has visualized this research into ten research clusters. In addition, the paper provides a direct comparison of all methods. The research results can help scholars quickly identify and compare different methods for addressing specific research questions. [ABSTRACT FROM AUTHOR]

Air traffic has increased by about 60% between 2011 and 2019 and climate forcers from aviation have also increased, resulting in a strong impact on climate change. It is well established that CO 2 is the largest climate forcing component connected with aviation and its impact is now well calculated and documented. However, other climate forcers such as nitrogen oxides (NO and NO 2), although not considered as greenhouse gases by the Kyoto Protocol, have a significant indirect impact on climate change. Post-combustion of the most common fossil fuel, Jet A-1, results in emissions of carbon dioxide (CO 2), water vapor (H 2 O), volatile organic compounds (VOCs), sulfate ions (SO 4 2−), carbon monoxide (CO), nitrogen oxides (NO x) and soot. Soot and water vapor emissions can trigger the formation of contrails-cirrus. Due to differences in lifetimes, temperature, pressure, humidity, and reactivity, all these climate forcers have not the same impact on climate change. Since 80% aviation fuel is burned during the cruise phase, this paper aims to improve the environmental assessment of the altitude emissions of the Jet A-1 fossil fuel, using Life Cycle Assessment (LCA) methodology. This method is a reference for calculating the environmental impact of air transport emissions. However, when it comes to assessing the impact of emissions at altitude, LCA models only take into account the impact of CO 2 on climate change. New global warming potentials (GWP) and emission indices (EI) of climate forcing components related to air traffic were therefore included in our calculations to estimate the climate impact I CC at two different time horizons. In this paper, we show that the inclusion of non-CO 2 effects results in an increase in the I CC at the 100- and 20-year THs of 115% and 517%, respectively. This considerable increase illustrates the crucial role of short-lived climate forcers that may have a greater impact when a shorter time horizon of 20 years is chosen. • Life cycle assessment study taking into account the climate forcers related, with direct and indirect impacts. • The inclusion of non-CO 2 climate forcers from jet fuel combustion results in an increase in climate impact. • For a 100-year time horizon, the environmental impact of fossil jet combustion is primarily due to CO 2 (47.0%). • For a 20-year time horizon, NOx and contrails-cirrus account for the largest share of the climate impact (86.5%). • It is important to use both the 100- and 20-year THs to evaluate their impact on climate change. [ABSTRACT FROM AUTHOR]

Abstract Physical, Regulatory and Brand value risks due to climate change challenges are foreseen by businesses globally. This paper is oriented towards these challenges and prepared a comprehensive Greenhouse gases (GHG) footprint plan and identification of mitigation opportunities for ONGC, a fortune 500 and national oil company of India. Internationally recognized standards and guidelines like Greenhouse Gas Protocol, ISO-14064, and American Petroleum Institute compendium have been referred for quantifying carbon emissions in nearly real 400 + operation control facilities. The GHG inventory is based on Operational Control approach to identify the boundary for which emissions are to be quantified and two significant scopes of emissions viz Direct Emissions and Indirect Emissions are identified and quantified. The quantification concluded that GHG emission footprint for the year 2016–17 is in the range of 9 million tons of CO 2 equivalent. GHG emissions mainly account due to stationary combustion, fugitive emissions and wastewater treatment, which share the around 56% of total emissions. Another 24–26% of emissions are contributed due to flaring, processes by glycol dehydrator, acid gas removal units, and by electricity purchased from the grid. As a result, it has been found that ONGC emits 187 kg CO 2 e emissions per tonne throughput and also compared with its global peer organizations. At the organization level, "Key Industrial Sites" have been identified as contributing higher GHG emissions and accordingly key "hot-spots," a list of 15 GHG mitigation opportunities have been proposed in the paper. Two GHG mitigation initiatives based on solar energy and bioenergy application undertaken at ONGC has also been briefed on case studies. Highlights • Comprehensive carbon footprint plan and identification of mitigation opportunities for Oil and Natural Gas Corporation (ONGC), a fortune 500 and national oil company of India. • Guidelines like Greenhouse Gas Protocol, ISO-4064 and American Petroleum Institute compendium are referred for quantifying carbon emissions from direct and indirect sources. • Green policy, incentives and mandatory compliance. • CO2e emissions per tonne throughput and also compared with its peer global organisations. • Key hot-spots, with a list of 15 GHG mitigation opportunities. [ABSTRACT FROM AUTHOR]

Given the increasingly severe challenges of global climate change and sustainable development, accurate prediction of daily carbon dioxide (CO 2) emissions has become crucial. However, current research on real-time daily forecasts remains relatively scarce, often limited to annual predictions and point estimates. This paper proposes an innovative integrated model, based on quantile regression and Attention-Bidirectional Long Short-Term Memory (BILSTM), specifically designed for probabilistic prediction of daily carbon emissions. Testing the model on daily carbon emission data from major carbon-emitting countries including China, the United States, India, Russia, and Italy has demonstrated its superior performance across various metrics, including mean squared error (MSE), mean absolute error (MAE), coefficient of determination (R2), and normalized average width of prediction intervals (PINAW), compared to other benchmark models. This achievement not only highlights the model's effectiveness in predicting daily carbon emissions but also provides policymakers with a powerful tool for real-time monitoring and assessment of carbon emissions. Furthermore , the application of probabilistic forecasting methods enables decision-makers to gain a more comprehensive understanding of the potential range of future carbon emissions, providing strong support for the formulation of targeted policies. [ABSTRACT FROM AUTHOR]

The intensification of global climate change has led to a widespread consensus on carbon reduction, with the power industry being the principal contributor to carbon emissions necessitating an inevitable transition of its energy structure. Concomitantly, the escalating frequency of natural disasters caused by extreme weather presents formidable challenges to both secure power supply and the low-carbon transition of the power system. To fulfill the developmental requirements of a low-carbon power system and address the carbon emission risks imposed by natural disasters, this paper proposes a bi-level model for generation expansion planning (GEP) that incorporates constraints on the carbon emission trajectory and the influence of natural disasters. The planning-level model optimizes investment costs of various generation technologies and energy storage (ES), as well as the overall operational expenses over the planning period, with an objective to minimize them. It incorporates carbon emission trajectory constraints and policy constraints, such as carbon peaking, carbon neutrality and renewable energy (RE) penetration rates, in order to optimize the planning installed capacity of power sources. The operational-level model aims to minimize typical daily operating costs while also simulating power unit outputs in routine and disaster scenarios. A case study is conducted in a disaster-prone province in southern China to analyze the power generation expansion planning and the trajectory of carbon emissions from 2020 to 2060 under different scenarios. The simulation results show that compared to thermal power, the planning scheme mainly focused on RE with ES is better suited to achieve the goal of a low-carbon transition of the power grid. Moreover, after considering natural disasters, the cost and carbon emissions of power system planning are higher, and the risk of carbon emissions increases with the severity of disasters. • A multi-time scale bi-level low-carbon GEP model is proposed. • Natural disaster scenarios and low-carbon policy constraints are considered in the GEP model. • Carbon emission trajectory of the planned power system is estimated and introduced as a constraint into the GEP model. • Evaluation indicators that comprehensively consider low-carbon performance and economic feasibility are proposed. [ABSTRACT FROM AUTHOR]

Climate change has steadily gained attention as the global economy has grown more quickly, preventing continued high-quality economic growth. In this context, the eco-innovation concept has recently risen to the top of the list of academic research topics since it is a crucial tool that combines reduced environmental effects with a favourable socioeconomic impact. Nevertheless, the environmental situation is not improving despite the increasing eco-innovation level. From one perspective, instead of concentrating on how eco-innovation lessens carbon emissions, this research explores the indirect effect of carbon emissions on the GDP-eco-innovation nexus. From another perspective, since FDI might lessen harmful pollution, this research analyses the indirect effect of FDI on the economic growth-eco-innovation nexus. Therefore, this paper highlights the relationship between eco-innovation and economic growth (GDP), considering the dual mediating roles of carbon emissions and FDI. First, we examine the effects of GDP on eco-innovation activities in nine MENA countries from 2000 to 2019 using the geographic Durbin model based on spatial panel data. Second, this paper analysed the dual mediating effect of carbon emissions and FDI using the spatial stepwise regression model. The findings of this paper are as follows: (i) GDP positively impacts eco-innovation activities, and (ii) carbon emissions and FDI mediate the GDP-eco-innovation nexus. Therefore, GDP, FDI, and carbon emissions are significant drivers of eco-innovation. This research represents an essential step towards a better understanding of the need to support the transition to sustainability. [ABSTRACT FROM AUTHOR]

Aviation is among one of the fastest-growing sources of greenhouse gas emissions (GHG). Thus, transitioning into a more low-carbon approach for future sustainable growth in the airline industry is necessary. Inspired by European Union's GHG emissions trading system that allows automobile makers to "pool" their carbon emissions, we study three emission pooling scenarios for the airline industry. Under the EU emissions trading system (EU ETS), passenger and cargo airlines such as Lufthansa and FedEx can either (1) pay a premium for each ton of carbon dioxide equivalent (CO 2 eq) they fall short of free allowances (Pay Premium Strategy) or (2) buy allowances from other industries in the EU ETS market (Market-Based Strategy) (3) partnership with other airlines to "pool" their carbon emissions (Cooperative Strategy). These three approaches correspond to different market structures. The latest strategy has a co-opetition relationship between airlines: traditional airlines operating older aircraft purchase emission allowances from airlines operating newer aircraft. The purpose of this paper is to examine the conditions for airlines' paying penalties, purchasing allowances from the ETS market, or cooperation. We demonstrate that the EU ETS will always be detrimental to airlines using older aircraft. A hefty premium may effectively induce airlines to pursue a low-carbon transition plan. Our study shows that the ETS is not a silver bullet; it only works when the premium mechanism is designed properly and a fair market for emission allowances is available. • This study investigates four emission pooling models for the airline industry. • The purpose of this paper is to examine the conditions for airline cooperation. • This study's findings can be insightful for both traditional airlines and sustainable airlines. [ABSTRACT FROM AUTHOR]

• This paper aimed to investigate the interactions between land use cover (LUC) and climate change (CC). • The results showed that the interactions between LUC and CC are both direct and indirect. • Arable and rangeland use changes affect CO2 emission in both direct and indirect ways. • Rising rangelands and reducing forest areas have indirectly increased surface temperature. • CC mitigation policies should be followed by considering both direct and indirect effects. Humanity deals with several challenges in this century such as climate change, land use, and land use/cover change (LUCC). Determining the patterns, developments, and consequences of LUCC issues for the livelihoods of people, especially poor people, is very important. Therefore, this paper aims to investigate the interactions between LUCC and climate change over the period of 1966–2015 (50 years) as a complex system at the global level. CO 2 emissions and surface temperature are considered as the main indicators of climate change (CC). The data were analyzed in time-oriented (time-based) and local or place-oriented (country-based) manners. The results showed that arable and rangeland use changes (LUC) affect CO 2 emissions in both direct and indirect ways. However, the direct effect of rangeland use change is positive, and its indirect effect is negative. In addition, deforestation has increased CO 2 emissions indirectly. LUCC can also change the ability of the ecosystem to deliver services to people, including biodiversity and other resources such as food, fiber, water, etc. Therefore, it is critical to determine the patterns, trends, and impacts of LUCC on CC. Thus, CC mitigation policies should be followed by considering both direct and indirect effects. Without a doubt, this will be realized when the decision and policymakers have a better understanding of the structure and interaction between CC, LUCC, and their components as a whole system. [ABSTRACT FROM AUTHOR]

• A review of country-level environmental policy indicators and proxies. • Analysis of the impediments to constructing and transforming indicators for researchers, policy-makers, and investors. • Novel bridging of machine-enhanced methods with environmental policy. • New research avenues are opened up to drive more effective policy feedback. Quantitative environmental policy indicators are useful for modeling the impact of environmental policy on the economy. They can be important tools for policy-makers, companies, investors, and researchers alike. Well-crafted environmental policies lead to cleaner environments whilst encouraging innovative behaviour to stimulate green growth and 'win-wins' for the economy and the environment. Such win-win policies are increasingly sought out by policymakers, evidenced in the growing number of green 'new deals' and 'net zero' carbon emissions pledges at a national level. But there is a gap between the needs for environmental policy data and the supply of reliable indicators and indexes. This disconnect has negative consequences for policy feedback as well as the inducement of potential innovators of environmental technologies. While there are now a wide range of indicators and indexes, these largely remain inadequate for various reasons. This is disappointing considering the immense progress that has been made in machine learning and pattern discovery methods—methods that are already fully deployed in other research disciplines. Such automated techniques can limit human biases which currently plague the environmental indicator's scholarship. Against this backdrop, the main objective of this paper is to highlight how researchers can carefully collect these data and augment the effectiveness of environmental policy indicators. This is an important research area that, apart from a handful of studies, is not sufficiently developed. [ABSTRACT FROM AUTHOR]

In 2022, Saudi Arabia's anthropogenic greenhouse gas emissions amounted to 810 million tons of CO 2 e. The country has pledged to cut its emissions by 278 million tons of CO 2 e per year by 2030. This paper contributes a modeling view on the climate-related effects of various energy policies on the Saudi energy system. We use an energy system model designed to represent seven sectors in the Saudi economy. In addition to a baseline, which entails the continuation of current domestic policies, we look at a scenario that incorporates some of the plans announced by the Saudi government. We also examine the baseline scenario with a cap on total CO 2 emissions equal to those exhibited with the announced plans. The model then makes the necessary decisions to abate CO 2. We find that the energy system contributes 130 million tons of CO 2 e to the nationally determined contribution amount in 2030. Also, a non-prescriptive scenario that caps energy-system CO 2 emissions produces the same emissions reductions as the announced plans while lowering the present cost by 2030 by $70 billion. The corresponding implicit marginal abatement cost of CO 2 approaches 35 $/tonCO 2 by 2045. This cost would displace around half of crude and fuel oil use in the Saudi energy system. • Saudi Arabia plans to cut annual greenhouse gas emissions by 278 million tonsCO 2 e. • We use a multi-sector model built from the ground up for Saudi Arabia. • The energy system can contribute 130 million tons of CO 2 e in reductions in 2030. • We find a scenario that achieves GHG abatement at a lower cost than official plans. • The marginal value attributed to CO 2 approaches 35 $ per tonCO 2 by 2045. [ABSTRACT FROM AUTHOR]

• Forecasting-test framework for long-term power system planning. • Coal-fired generators can be completely withdrawn from the power system by 2060. • China's power capacity mix will transition to wind and solar generators dominated. • Biomass and gas-fired generators will take on the role of reserved generators. • The timing of achieving China's zero-coal power system may be advanced or delayed. Facing the challenges of climate deterioration, environmental pollution, and energy shortages, China has put forward the goals of "carbon dioxide peaking and carbon neutrality", and the electricity sector will be the key area and the main direction of carbon emissions reduction. To prospect China's power system and explore the potential for establishing China's zero-coal power system in the future, this paper proposes a forecasting-test framework for long-term power system planning. We predict, evaluate, and analyze China's power system from 2025 to 2060 using the proposed forecasting-test framework. During this process, the power capacity mix and the electricity generation mix of China's power system will gradually transition from coal-fired generators dominated to wind and solar generators dominated. Moreover, the roles of different generators and energy storages are illustrated through the seasonal comparison and sensitivity analysis of the installed capacity of generators. The results indicate that coal-fired generators can be completely withdrawn from the power system, confirming the feasibility and possibility of achieving China's zero-coal power system by 2060. Although the timing may be advanced or delayed in different scenarios, achieving China's zero-coal power system will require exercising nationwide planning and making joint efforts of various sectors from now on. [ABSTRACT FROM AUTHOR]

Given the significant energy consumption and carbon emissions associated with buildings, there is increasing interest in improving sustainability of building operations to reduce impact on climate change. A common goal is to operate buildings as "net-zero" energy users in which all energy consumed by the building is balanced against renewable energy purchased from the grid or produced on site. To achieve net-zero status, many buildings will require significant retrofit so as to both reduce energy consumption in the absolute sense and provide the remainder without consuming fossil fuels. Thus, multi-year planning is required to ensure that goals can be met on time. In addition, due to the inherent uncertainty associated with energy consumption and generation, actually achieving net-zero energy use may require discretionary curtailment actions to be taken, and deciding whether such actions are necessary can be challenging. To address these challenges, we propose in this paper a design optimization and operational planning strategy to make the decisions needed to achieve sustainability goals in buildings. The strategy can be applied to schedule design changes over a long horizon to meet annual targets, and it can also be applied in closed loop on a shorter horizon to determine whether curtailment is needed to stay on track. We discuss the formulation of the optimization problem, solution methods, and modeling approaches for key parameters. Application of the strategy is illustrated via examples. Overall, this approach will help automate planning that is often done manually, allowing buildings to take a significant leap forward toward achieving their sustainability goals. • Achieving sustainability goals in buildings requires multi-year planning. • The required design and operational decisions can be made via optimization. • Key problem parameters can be obtained from data-driven modeling. • The strategy allows sustainability goals to be met at minimum cost. [ABSTRACT FROM AUTHOR]

• Collections of basic research for urban spatial planning. • Literatures of urban agglomerations, urban size, urban compactness, and urban form on carbon emission. • Urban spatial structure and carbon emissions research from a multi-ecosystem interaction framework. Carbon emission reduction is one of the key factors in global climate change and should be an important component in urban planning and management. A full understanding of the relationship between carbon emissions and urban spatial structure is necessary. This paper presents the research on this relationship from the perspectives of urban agglomeration, urban size, urban compactness, and urban form. The results revealed that: (1) there is still a lack of research on the spatial structures of urban agglomerations and their relationship with carbon emissions, so it is urgent to conduct indicators system design and empirical research; (2) two-dimensional indicators have frequently been used to describe urban form and urban compactness, but three-dimensional indicators, such as volume ratio and floor height, are also important indicators for policymaking; (3) higher urban complexity, irregularity, and fragmentation were believed to contribute to urban carbon emissions because of the lack of continuity and connectivity. This paper also proposes a comprehensive analytical framework for examining urban spatial structures and carbon emissions. We position the research on the relationship between urban spatial structure and carbon emissions as a bridge between human ecosystems and natural ecosystems. [ABSTRACT FROM AUTHOR]

• Developing countries face the dual challenges of industrialising and 'catching up' while mitigating CO 2 emissions. • Medium- and high-technology manufacturing is associated with lower emissions than low-technology manufacturing, with differences varying by the income levels of countries. • A shift to more technology-intensive manufacturing could be one aspect of environmentally sustainable industrialisation in developing countries. Industrialisation is an important engine of growth and 'catch up', but also associated with harmful carbon dioxide emissions and hence with climate change. This poses a challenge for sustainable industrial development, particularly for late industrialisers on how to industrialise while also mitigating carbon dioxide emissions. This paper investigates the effect of technology intensity across manufacturing industries on carbon dioxide emissions: are medium- and high-technology manufacturing industries less emissions-intensive than low-technology manufacturing industries in developing countries? The paper analyses this relationship for a panel of 68 developing and emerging economies over the period 1990–2016, by adapting the environmental Kuznets curve and the stochastic effect by regression on population, affluence and technology approaches. Using two alternative measures of emissions and estimating generalised method of moments model, the results show that medium- and high-technology manufacturing industries are associated with lower carbon dioxide emissions than low-technology manufacturing industries. The results also show that these differences vary by the income levels of countries. These findings have important policy implications, suggesting that a shift towards more technology-intensive manufacturing production processes may be a more environmentally sustainable industrialisation path for developing countries. [ABSTRACT FROM AUTHOR]

Coal-fired electricity generation accounts for more than 10 Gt, or roughly 30 %, of global CO 2 emissions, with the majority of coal-fired generation capacity located in developing countries. It is possible to significantly reduce emissions from older, expensive and inefficient coal plants at less than US$10/tCO 2 e. However, in the absence of suitable business models and financing options, accelerated coal decommissioning may not transpire. Several business models have been tested, such as policy-based closure, buyout, and repurposing, and swapping for renewables. Features of different models can be combined to develop hybrid models. This paper develops typologies for alternative business models so that the available options can be clearly understood and compared. The paper also discusses the potential merits and drawbacks of each model. Rather than offering definitive answers on a suitable approach for coal transition. the paper aims to collate the experience thus far and highlight questions that require further examination. [ABSTRACT FROM AUTHOR]

Voluntary corporate environmental disclosure has increased significantly in the last decade. However, the increase in environmental disclosure has also been accompanied by the social questioning of its veracity. Previous studies have mainly focused on the determinant factors behind corporate decisions to disclose environmental data, with only limited consideration of both carbon performance and the veracity of the information disclosed. Based on an international sample of firms from 12 countries, this paper analyzes the impact of regulative pressures related to climate change on the likelihood of companies engaging in greenwashing. The results show that the number of regulations related to climate change negatively influences the propensity of firms to engage in greenwashing. Furthermore, firms in countries with stringent climate-related regulations are less likely to participate in greenwashing practices. This paper adds to the existing literature concerning greenwashing by demonstrating that institutional theory can deliver further insights into the explanation of corporate greenwashing behavior. This is the first study to incorporate international climate-related regulations into the analysis of corporate greenwashing. It also provides a new method for identifying greenwashing firms, based on their carbon performance and disclosure. • Countries' climate-related laws negatively influence corporate greenwashing. • Stricter climate-related regulations reduce greenwashing practices of firms. • The study provides a new method for the identification of greenwashing firms. [ABSTRACT FROM AUTHOR]

To mitigate climate change and achieve sustainable development, Chinese governments have introduced "1+N" "dual-carbon" policy system aimed at reducing CO 2 emissions, transforming energy structures and controlling pollution. An effective policy mix and synergy is crucial for achieving the emission reduction targets and for ensuring the effectiveness of the policies, and it is therefore of great practical importance to provide a pathway for policy synergy based on assessing policy effectiveness. This paper selects three policies, namely the carbon Emission Trading System (ETS), Coal Control and Clean Utilization (CCCU), and Green Financial Reform and Innovation Pilot Zone (GFPZ), sets up ten scenarios, adopts difference-in-differences (DID) models to evaluate the impact, and give a pathway for policy synergy. The results show that ETS, CCCU, and GFPZ policies have significant positive effects on carbon emission reduction, energy structure transformation, and industrial environmental pollution control, respectively; CCCU has synergistic effects with ETS and GFPZ policies in controlling coal consumption and increasing the completion of industrial pollution control investments, respectively; while GFPZ policies have conflicting effects with CCCU and ETS in reducing carbon emissions and coal consumption, the GFPZ policy has conflicting effects with CCCU and ETS in reducing carbon emissions and controlling coal consumption. Finally, the study proposes a phased policy support system around carbon emission reduction in the power generation industry, energy structure transformation, and industrial environmental pollution control before 2030 and from 2030 to 2060. [ABSTRACT FROM AUTHOR]

The industrial sector has significantly contributed to global climate change and urban air pollution while driving economic development. This paper takes the synergistic CO2 and SO2 emission reduction in China's industrial sector as an entry point quantifies the synergistic CO2 and SO2 emission reduction effect using the Kaya extension model and analyzes the synergistic emission reduction expansion mechanism in depth. It is found that the synergistic effect of CO2 and SO2 in the industrial sector is prevalent in most provinces in China. Every 10,000 tons of CO2 emission reduction leads to 1600 tons of SO2 emission reduction. Regional heterogeneity also clarifies that there are differences in synergistic emission reduction among different provinces, with most regions having a significant positive effect of synergistic emission reduction, while a small number of regions have an inverse effect, and direct SO2 reduction measures should be considered separately. The interaction effect analysis found that energy efficiency improvement in the industrial sector is the critical path to synergistic effect enhancement. At the same time, R&D expenditure and fixed asset investment have a weak effect on synergistic emission reduction. The interaction of the three factors can synergize the emission reduction effect by more than twice. The study's findings can be used as a reference for China's industrial sector to achieve the goal of reducing pollution and carbon emissions and for the practice of regional synergistic emission reduction, as well as for the formulation of international synergistic emission reduction policies. [ABSTRACT FROM AUTHOR]

In the debate between proponents of green growth and degrowth, the core issue is whether decoupling carbon emissions and resource use from GDP growth is possible, and if so, possible at a rate fast enough to achieve policy goals such as global warming of maximum 1.5 °C or 2 °C. In this paper, the claims by degrowth scholars on the limits of decoupling growth and carbon emissions are critically examined by assessing the economic and climate consequences of their claims. It is claimed that their pessimistic view on decoupling is not based on robust arguments but rather mystifications of what decoupling is. Following the assumptions by leading degrowth scholars – that decoupling (decrease of the emission intensity of GDP) are unlikely to be larger than 4% and that levels of GDP need to converge in a degrowing world – indicates that the 1.5 °C target is ruled out altogether and that in order to reach the 2 °C target, the economies of the global north would have to be reduced with over 90% and for middle income countries with around 70%. This appears as very unlikely to happen. Yet, there might be alternatives, which are discussed by sketching a realist and dynamic theory of decoupling. • The pessimist assumptions on decoupling by some degrowth scholars presuppose an economic collapse of unseen magnitude • Alternatively, stringent climate goals such as 1.5 °C, are not attainable • These pessimist assumptions are, however, not based on robust arguments, and ways to demystify decoupling is discussed [ABSTRACT FROM AUTHOR]

Carbon emission trading mechanism is an important market-based instrument to address global climate change. The auction ratio and price of carbon emission allowances (CEA) are cores of the carbon emission trading mechanism. What combination of CEA auction ratio and auction price is most conducive to carbon emission reduction for emission control enterprises? There are still relatively few studies conducted on this issue, and there is no clear answer from the views of theory and practice. In this paper, the AIM/Enduse model was used to analyze the changes and differences of installed power capacity, power supply, energy consumption and carbon emissions in the Guangdong-Hong Kong-Macao Great Bay Area (GBA) with different combinations of CEA auction ratios and prices. Moreover, the best pathway of energy transition was explored in the power industry of the GBA, and the best combination of CEA auction ratios and prices was identified in the GBA. The results show that: (1)The carbon emission constraint starts to work only when the auction ratio of CEA is increased to 50% and the auction price is increased to 60 CNY/ton (Scenario p 3). When the auction ratio of CEA is 100% and the auction price reaches 120 CNY/ton (Scenario p 5), a low-carbon transition of the power sector in the GBA can be achieved. (2) Under scenario p 5 , the total cost of power transition rises and then falls. And the cost of carbon in the power sector increases exponentially as the auction ratio of CEA and the auction price rise. However, the growth in the cost of power supply is relatively flat, which shows that appropriate carbon trading mechanism can improve the economic benefits of power sectors. With the increase of installed capacity of clean low-carbon energy generation and power supply, as well as the decrease of local power cost in the GBA, the proportion of outsourcing power can be appropriately reduced in the future, with an aim to reduce the external dependence of electricity to ensure the security of energy supply. In the end, it suggests that cities in the GBA should give full play to their regional advantages and establish a unified carbon emission trading market in the GBA as soon as possible. This study provides a theoretical basis for the supplementation and improvement of China's carbon emission trading mechanism. • What is the best combinations of CEA auction ratios and auction prices in the GBA? This paper gives a clear answer. • The best transition pathway of the power industry under technological progress and carbon trading policy was suggested. • With the decrease of local power cost, the proportion of outsourcing power can be appropriately reduced in the future. • Provides a theoretical basis for the supplementation and improvement of China's carbon emission trading mechanism. [ABSTRACT FROM AUTHOR]

[Display omitted] • Transform office buildings towards whole-life minimum carbon. • Integrated optimisation of retrofitting plan and operating schedules. • 44%, 74% and 68% decline in whole-life costs, carbon and energy after retrofitting. • 4–51% saving in whole-life carbon emission compared to design optimisation strategy. • 10% saving in whole-life carbon emission compared to operating optimisation strategy. The state-of-the-art retrofitting strategies generally use either passive or active measures to reduce carbon emissions during its operating stage. The coordination among a range of passive and active energy devices is not considered while the concept of whole-life carbon emission minimisation is not introduced. To overcome these three research gaps and to transform existing office buildings toward minimum whole-life carbon emissions, an integrated passive and active retrofitting approach is proposed. Through two inter-related design optimisation and operating optimisation processes, the set of retrofitting options can be identified to achieve overall optimal economic, energy, and environmental performance. The first research gap, lack of simultaneous consideration of various active and passive retrofitting measures, is solved by the whole system simulation of a range of active and passive refurbishment measures. The second research gap, lack of coordination among a range of active energy devices, is solved by iteratively determining the optimal operating schedules of active energy devices with overall retrofitting plan at the design stage. The third research gap, lack of whole-life carbon emission minimisation, is solved by simultaneously minimising both embodied and operating carbon emissions. A real three-floor office building acquiring retrofitting is used to test the effectiveness of this integrated passive and active retrofitting approach. Compared to the building at its current status, there could be 44%, 74% and 68% reduction in lifelong costs, carbon emissions and energy usages if the proposed retrofitting strategy is adopted. Compared to retrofitting the building using the state-of-the-art "design optimisation only" strategy, the proposed retrofitting approach can reduce 5.36%-34.37% whole-life energy consumption and 4.31%-51.10% carbon emissions. Compared to retrofitting the building using the state-of-the-art "operating carbon emission only" strategy, there is 11.92%, 10.55%, and 10.48% reduction in whole-life cost, energy usage and carbon emissions, respectively. Therefore, this paper is innovative in an aspect that minimum whole-life carbon emissions can be reached through integrated design of passive and active retrofitting measures. It can provide building owners, energy engineers and decision-makers with insightful building retrofitting solutions to tackle the energy crisis and climate change problems. This proposed retrofitting approach can also be modified to provide guidance in designing new low-carbon buildings. [ABSTRACT FROM AUTHOR]

Schematic illustration of the double-layer PDRC coating. [Display omitted] • The idea of introducing masking layer for double-layer PDRC coating is proposed. • PDRC coating achieves high solar reflectivity (94.0%) at a thin thickness. • The PDRC coating reduces the indoor temperature of container room by 5.0 °C. • The prepared PDRC coating can realize large-scale long-time outdoor applications. The realization of spontaneous sub-ambient cooling in daytime typically requires the solar reflectance and thermal emittance of passive daytime radiative cooling (PDRC) material to be > 90%. Toward real-world applications, however, to achieve high optical performance and excellent durability, PDRC coating is often cost-prohibitive due to its high thickness (500 μm or higher). To solve the contradiction between high optical performance and thin thickness of PDRC coating, the idea of introducing masking layer for PDRC coating is proposed in this paper to prepare the water-based double-layer PDRC coating and explore its long-term outdoor application potential. The PDRC coating can achieve high solar reflectance (94.0%) and "atmospheric transparent spectrum window" emittance (93.0%), while the thickness and cost are only 40% and 60% of existing water-based PDRC coating. The PDRC coating shows efficient cooling performance when applied as the external coating of large temporary buildings, with maximum temperature reduction of 20.8 °C and 5.0 °C on the roof/indoor, which are equal to or greater than recorded values. The 150-day large-scale outdoor application shows that the coating has excellent durability, which offers a reference for the long-term outdoor application of PDRC coating. The application of the PDRC coating on rooftops of containers can achieve a cooling energy savings of up to 15.3% compared to conventional steel roofs, translating to an annual energy savings of 413.2 MJ and a reduction of approximately 114 kg in carbon dioxide emissions, which provide compelling evidence for the ability of PDRC coating to mitigate carbon emissions and address global climate change. [ABSTRACT FROM AUTHOR]

Global warming may cause the average atmospheric temperature to exceed 2 °C by the end of this century, instigating climate change and adversely affecting human lives. Emissions of carbon dioxide (CO 2) should be reduced to overcome the problems of global warming and climate change. The applications of negative emission technologies (NETs) are proposed to reduce terrestrial CO 2 and are identified as one of the prominent options for the energy system transition. Most negative emission technologies require energy to function, which has to be produced from additional energy sources. Understanding the interdependence of the energy sources and NETs for planning the carbon-constrained energy sector is essential. A novel graphical approach, founded on the concepts of Pinch Analysis, to decarbonize the energy sector is purported in this paper. The proposed method determines the minimum integration of negative emission technologies required to attain the allowed CO 2 emission limit while satisfying the energy demand. Four different examples are used to show the applicability of the suggested approach with different NETs: carbon capture and sequestration (CCS), bioenergy with carbon capture and storage (BECCS), and direct air capture (DAC). In these examples, renewable-based energy sources, fossil-based energy sources, as well as energy-producing negative emission technologies are used as compensatory energy sources. The proposed graphical approach has the potential to be used as a planning tool to decarbonize the energy sector involving interdependent energy sources and NETs. [Display omitted] • Negative emission technologies help decarbonize the energy sector. • Identified dependence between the energy sector and negative emission technologies. • A graphical method is proposed to integrate negative emissions technologies. • Determined minimum compensatory energy for adopting negative emission technologies. • The proposed graphical approach provides insight into the overall systems planning. [ABSTRACT FROM AUTHOR]

Global warming, climate change, and resource depletion have forced us to reconsider energy usage and efficiencies over the last few decades. Residential and commercial buildings are both large energy consumers, so improving energy and material usage efficiency in this sector is a common research topic. According to a recent study, the Building Sector (BS) accounts for 40% of greenhouse gas emissions. The primary objective of this paper is to examine and assess the potential of Renewable Energy Systems (RES) and their combinations for enhancing energy efficiency in the BS. Specifically, the focus will be on converting low energy-efficient buildings into highly efficient ones. The potential of the RES and their combinations for the BS is evaluated based on payback durations, energy generation, and reduction of CO 2 emissions. The optimization flow charts for the RES, feasibility studies, commercialization road maps of energy storage systems and the necessity of control mechanisms for enhancing RES efficiency were discussed. Additionally, the technology drawbacks are discussed, along with various innovative techniques recommended to direct future study in this area. Finally, this article assists the audience clear idea in the selection of the right combination of potential RES based on different conditions to achieve deep decarbonization in BSs. • Buildings sector (BS) responsible for 40% of GHG emissions. • Study assesses potential of Renewable Energy System (RES) in BS. • RES evaluated on payback, energy generation, and CO 2 reduction. • Optimization, feasibility and commercialization studies were discussed. • Article recommends right RES combinations for deep decarbonization in BS. [ABSTRACT FROM AUTHOR]

This paper studies the relationship between income inequality and carbon emissions in the United States between 1929 and 2019. We contribute to the literature by studying if and how the relationship has varied over time. To this end we estimate a band spectrum regression model and a smooth-varying coefficients model. Our results show that higher inequality was associated with lower emissions during the early part of the sample and higher emissions towards the end of the sample. • Whether the level of inequality affects carbon dioxide emssions is unclear. • We test the association between income inequalty and carbon dioxide emissions. • We find that the relationship varies over time. • Changes in consumption patterns may partially explain the time varying effects. [ABSTRACT FROM AUTHOR]

“Low-carbon” is well acknowledged as one of the key factors contributing to sustainable urban development, and also an effective approach for tackling climate change. Since the building sector accounts for a high proportion of carbon emissions, the construction is regarded as one of the most potential industry to reduce carbon emissions. However, there is no standardized indicator to measure carbon performance in the construction industry. As a result, the choice of various indicators may result in significantly different carbon performances which determine whether an industry is considered truly “low carbon”. In this paper, the current indicators for assessing carbon performance in the construction industry are reviewed. The pros and cons of the current indicators are also highlighted. The problems of using the current indicators are discussed, and these problems are often related to accuracy of indicator, data availability and definitions of specific terms. Suggestions are made to focus on carbon emissions at building operation stage first as it accounts for a significant amount of carbon emissions during the whole building life-cycle. It should be highlighted that embodied emissions of buildings are also important during the whole building life-cycle. However, due to the challenges in data acquisition for calculating embodied emissions, attention should be paid more to the operational stage first as smart meters can be used to facilitate data collection processes. The findings provide clues for industry practitioners to develop an indicator which is more practical in use to assess carbon performance in the construction industry. [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]

In the fight against global climate change, improving energy efficiency and reducing related emissions are critical to mitigating sustainability issues such as global warming. In this regard, technological progress is known to improve energy efficiency and reduce related emissions. However, previous sustainability studies on Africa have paid less attention to energy and emission efficiency convergence among countries, along with the contribution of technological progress to the continent's sustainability. Accordingly, this paper develops a novel framework that assesses energy and emission efficiency convergence, gauges technology inequality, identifies the barriers to technology diffusion, and explores the factors influencing energy and emission efficiency convergence in Africa. The proposed framework incorporates Data Envelopment Analysis (DEA), several economic convergence concepts, a K-means clustering model, the concept of efficiency Gini coefficient, and a group-based inequality decomposition method. We empirically covered 39 African countries from 2006 to 2018. The results show that African countries are, on average, 71.1% energy efficient and 65.3% CO 2 emission efficient, leaving more room for energy saving and emissions reduction. Second, there is strong evidence of convergence in energy and emission efficiencies in Africa. Third, despite the observed convergence process, there is significant heterogeneity between two research groups (i.e., low-and high-efficiency groups of countries) in terms of energy and emission efficiencies, with persistent technology inequality suggesting a lower contribution of environmental technological advancements to the continent's sustainability. Furthermore, cross-group inequality is the primary barrier to technology diffusion. Fourth, regional cooperation accelerates the convergence process in the two efficiency indicators. While economic development, industrial structure, and renewable energy consumption (REC) tend to favor energy and emission efficiency growth, rising foreign direct investment (FDI) and energy prices have a negative impact. Meanwhile, the effects of energy prices, FDI, and REC on emission efficiency are insignificant. Based on our findings, we discussed policy implications to promote energy and emission efficiency convergence and narrow environmental technology gaps. • Convergence in Total-factor energy and emission efficiency in Africa is explored. • Technology inequality across African countries is measured. • There is strong evidence of convergence in TFEE and TFCEE in Africa. • A persistent technology inequality is found among African countries. • Cross-group efficiency inequality is the main barrier to technology diffusion. [ABSTRACT FROM AUTHOR]

By 2050, aviation emissions are forecasted to account for 25% of the global carbon budget. Thus, in addition to airlines' sustainability efforts, individual consumer action is needed in order to reduce the environmental impact of air travel. The purpose of this paper is to investigate to what extent consumers value environmental sustainability when selecting flights in terms of the trade-off between cost, time, comfort, and CO 2 emissions. Hence, a choice-based conjoint survey was conducted to understand the monetary, temporal, and comfort trade-offs consumers are willing to make for a reduction in CO 2 emissions in both short-haul and long-haul flights. The 426 collected responses were analysed using conditional logistic regressions. The results indicate that air travellers are willing to pay more (6.7–21.2 €/100 kg) or travel longer (13–41 minutes/100 kg) to reduce the environmental impact of their trip. Moreover, displaying CO 2 emissions as a percentage of an individual's annual carbon budget increased air travellers' perceived monetary and temporal value of environmental sustainability, to 11.8–26.3 €/100 kg and 22–65 minutes/100 kg respectively. • Displaying flights' environmental impact affects stated consumer behaviour. • Air travellers indicate they are willing to pay more for an eco-friendlier flight. • Flyers indicate they are willing to travel longer to reduce flight emissions. • Displaying CO 2 emissions as % of person's annual carbon budget shows better results. • Transparent information on emissions can lead to more sustainable flying behaviour. [ABSTRACT FROM AUTHOR]

There is anxiety that has been rising vis-à-vis the climate changes in the entire world. Notwithstanding this, the primary purpose of this paper is to examine the board characteristics and carbon emission performance. This study applied the fixed effect model, 2SLS, and multiple regression analyses data from 220 non-financial listed companies on the BSE index and covering a period of 7 years from FY 2014-15 to FY 2020-21. The estimated results confirmed that board size, board meetings, board gender diversity, CEO duality, and ownership concentration have a negative association with carbon emission performance. In addition, board independence and the environmental committee are found to be positively associated with carbon emission performance based on 2 SLS and multiple regression analyses, and these results imply that they improve carbon performance. Overall, this study's shreds of evidence suggest that governing boards tend to pay attention to company's carbon performance and without mitigating original carbon performance is not likely to reduced GHGs emissions. This study's outcomes have significant implications for policymakers, corporate bodies, creditors, and regulators regarding the efficiency of corporate governance mechanisms in communicating climate change risks. However, corporate boards can use these results to find positive aspects of companies and formulate possible corporate governance modifications in relation to carbon policies. [Display omitted] [ABSTRACT FROM AUTHOR]

For making earlier realization on peak carbon dioxide emissions and carbon neutrality, hydropower development in countries all over the world can effectively reduce the Greenhouse Gas (GHG) emissions and solve the problem of global climate change. This paper proposes a novel Optimized initial condition and Seasonal division based Grey Seasonal Variation Index (OSGSVI) model to accurately predict the hydropower generation in some countries. Firstly, for enhancing the fitting accuracy, the initial condition is optimized based on the weighted average methods and the data grouping with OSVI is utilized by seasonal divisions. Secondly, an OSGSVI model is established coupled optimization on both optimized initial conditions and seasonal divisions. Thirdly, the Whale Optimized Algorithm (WOA) is employed to determine estimated parameters to further enhance the fitting accuracy for the hydropower generation. Finally, the experimental results of the prediction study show that three error measure values are all the smallest in all the fitting results and the MAPE values are converged before 30 iterations by utilizing our proposed model when compared with a set of baseline prediction models. It demonstrates the superiority of our proposed model over the others on the fitting accuracy with fast-convergence for the hydropower generation in these selected countries. • An OSGSVI model is proposed to accurately predict the hydropower generation. • The model uses the seasonal data grouping and OGSVI to enhance the predictive accuracy. • The WOA is proposed to further improve the predictive accuracy. [ABSTRACT FROM AUTHOR]

The Belt and Road Initiative was proposed by China in 2013 to promote the interconnected development and prosperity of all participating countries. In the context of global response to climate change, understanding the embodied carbon transfer change along economic trade before and after the Belt and Road Initiative is essential to reduce carbon overall emission. In this paper, we used a multi-regional input-output model to study the embodied carbon transfer in trade between the Belt and Road countries that have signed cooperation documents with China from 2004 to 2017. The results showed that from 2004 to 2017, the growth rate that China's carbon emissions imported from other Belt and Road Initiative countries was about 1.9 times that of its exports. From 2004 to 2017, the proportion of China's carbon imports from other Belt and Road countries in China's total carbon imports increased from 3.41% to 3.73%, and exports decreased from 6.52% to 6.03%. In both 2004 and 2017, Electricity, Gas and Water sector, Heavy Industry sector, Transport sector were the three largest carbon transfer sectors in China's multilateral trade. In 2017, the embodied carbon transfer by multilateral trade among other Belt and Road countries except China increased by 15.53% compared with 2004. By comparing the characteristics of carbon transfer between China and the Belt and Road countries from 2004 to 2017, this study will provide insights for carbon emission reduction policy setting of Belt and Road Initiative countries. • We took countries that have signed documents with China as research objects. • MRIO model was used to analyze the carbon transfer change from 2004 to 2017. • The embodied carbon transfer in 2017 of BRI increased by 15.53% compared with 2004. • The growth rate of China's carbon imports from BRI was 1.9 times that of exports. [ABSTRACT FROM AUTHOR]

As the climate is warming up and climate disasters occur more frequently, China's carbon peak and carbon neutrality targets are gaining attention, with provinces starting to set carbon peak targets and constantly exploring low carbon economic development opportunities. However, the existing evaluation index system mainly focuses on low carbon cities and green cities, and there is no evaluation index system for carbon peak and carbon neutrality. This study adopts a combination of theoretical and empirical research and draws on domestic and international research results to construct the first index system for evaluating China's provincial carbon peak and carbon neutrality. The evaluation index system includes 18 indicators from three dimensions: climate ambition, low carbon status, and emissions trends. Using this index system, we calculated the carbon peak and carbon neutrality indices of 30 Chinese provinces. Further, the 30 provinces were classified into six categories, and corresponding policy recommendations for achieving the "Dual carbon" targets were put forward. The evaluation index system constructed in this paper can provide a reference for future carbon peak and carbon neutrality assessments. By disclosing the integrated index of each province, we hope to effectively curb the increasing local carbon emissions; avert inaction in areas with good natural endowments; and motivate the advancement of the latter, to boost the implementation of the "Dual carbon" targets coherently for the whole country. [Display omitted] • An integrated evaluation system on China's Provincial "Dual carbon" was proposed. • 30 provinces in mainland China were ranked based on the integrated index. • 6 groups were classified to show provincial differences on dual carbon performance. • Policy recommendations to fulfill China's climate commitment were put forward. [ABSTRACT FROM AUTHOR]

The issue of climate change has become an increasing concern for the international community. At the same time, climate change and, particularly, global warming affects the amount of energy required in China and the structure of this demand, thereby influencing the amount of CO 2 (carbon dioxide) emissions produced. To investigate the possible influence of climate change on China's CO 2 emissions, this paper utilizes the degree-day method to calculate the heating degree days (HDD) and cooling degree days (CDD) in 29 provinces in China from 1995 to 2011. A series of appropriate econometric models are subsequently estimated to measure the impact of climate change on CO 2 emissions per capita. To enhance the explanatory power of the estimation results, several indicators, such as income per capita, industry structure, urbanization rate and population density, are incorporated in the estimation equations as control variables. The estimation results indicate that the feedback effect of climate change on China's carbon emissions is statistically significant but not large in magnitude. During the sample period between 1995 and 2011, approximately 1.687% of China's increased total CO 2 emissions could be attributed to climate change. Moreover, the impacts of climate change on different regions of China are notably different. For example, the influence of HDD on CO 2 emissions per capita are most significant in the middle and southern regions, while the impacts of CDD are most significant in the eastern and northern regions. However, there is no obvious evidence that climate change has affected CO 2 emissions in the western region. [ABSTRACT FROM AUTHOR]

Smoke from inefficient biomass cookstoves contributes to global climate change and kills approximately four million people per year. Credits for reduced carbon emissions can potentially subsidize fuel-efficient cookstoves that reduce these harmful effects. Understanding the accuracy of different methods of monitoring stove usage is useful to measure the effects of cookstove programs and to target carbon credits. This paper compares four methods of measuring stove usage: hours cooked (derived from a predictive logistic regression of stove usage monitors and observations of stoves in use); number of people cooked for reported in household food diaries; fuel weight used gathered in a kitchen performance test; and household air pollution using mean 24-hour concentrations of particulate matter collected with particulate air monitors. We find statistically significant positive correlations between five out of six of these pairs of measures. While the correlations are positive, the explanatory power of each measure for another is weak. The weak correlations emphasize the importance of using multiple measures to track changes in stove use for both researchers and carbon auditors. [ABSTRACT FROM AUTHOR]

• Constructing a new welfare function considering economy, equity and ecology. • Optimizing carbon emission pathways from multiple perspectives. • Focusing on the emission pathways in China achieving the ambitious targets. With the increasing climate warming, reducing carbon emissions has gradually become a consensus around the world. However, the process of carbon emission reduction will inevitably lead to the transformation of economic structure, industrial structure and energy structure, which will bring huge changes in economic output, employment and other aspects, thus affecting the overall social welfare and equity. Therefore, it is particularly important for each country to determine a scientific and effective carbon emission pathway which take into account both social development and climate targets. As the largest carbon emitter, China has put forward the targets of carbon peak and carbon neutrality. In this regard, the corresponding carbon emission reduction scenarios are designed according to the new situation of China's emission reduction in this paper, firstly. Furthermore, under the premise of maximizing social welfare, an optimization model which integrating economic growth-equity-environment is developed to determine China's emission pathways under different scenarios from 2020 to 2050. Besides quantitatively showing the future total amount and peak value of carbon emissions under different scenarios, the results can also identify its evolution pathway over time. Therein, the peak under most scenarios will concentrate in 2025–2030, which is about 10.7 to 11.8 billion tons. With the increasingly stringent constraints on carbon emission reduction, the cost of emission reduction will increase correspondingly, but the overall social welfare will increase slightly. Finally, our findings provide practical guidance on achieving carbon emission reduction and enlightenments on policymaking. [ABSTRACT FROM AUTHOR]

Production of mature oil fields emits significant amount of CO 2 related to circulation and handling of large volumes of gas and water. This can be reduced either by (1) using a low-carbon energy source and/or (2) reducing the volumes of the non-hydrocarbon produced/injected fluids. This paper describes how improved oil recovery techniques can be designed to reduce CO 2 intensity (kgCO 2 /bbl oil) of oil production by efficient use of the injectants. It is shown that CO 2 emissions associated with injection of chemicals is strongly influenced by water cut at the start of the project, extent of the water cut reduction, and chemical utilization factor defined as the volume of produced oil per mass or volume of the injectant. As an example, for the oil field considered in this study, 3–8% reduction in water cut can result in 50–80% reduction in its CO 2 intensity. In addition to the incremental oil production with lower CO 2 intensity, the earlier implementation of enhanced oil recovery methods can extend the lifetime of the mature fields if carbon emission cut-offs are applied. In case of CO 2 enhanced oil recovery (EOR), the large storage potential for CO 2 can significantly reduce the overall CO 2 emissions of oil, albeit at a large energetic cost. For CO 2 EOR using CO 2 captured from gas power plants, improving the utilization factor from 2 bbl/tCO 2 to 4 bbl/tCO 2 can reduce the CO 2 intensity of the produced oil from 120 kgCO 2 /bbl to 80 kgCO 2 /bbl (33% reduction). [Display omitted] • Improved oil recovery methods can lead to cleaner production of oil. • Efficient utilization of injectants is key to reduce CO 2 emissions from operations. • CO 2 enhanced oil recovery reduces total CO 2 intensity of oil by 80%. • Cleaner production of hydrocarbon fields extends their lifetime. • Earlier implementation of EOR techniques lowers overall CO 2 footprint of fields. [ABSTRACT FROM AUTHOR]

Low carbon manufacturing is of growing importance due to the severity of energy shortage and increasing energy costs, as well as a series of environmental problems, i.e., climate change and global warming. This paper investigates the potential of process parameter optimization to minimize carbon emissions during machine processing. A process model of CNC machining is first presented to scope the system boundaries for energy footprint and process efficiency. A multi-objective optimization model is then proposed to explore the impact of cutting speed and feed rate on carbon emissions and processing time. The benefit of the approach is illustrated through a case study of a CNC cylindrical turning process. [ABSTRACT FROM AUTHOR]

• We propose a technology-adjusted investment-based emissions accounting (TIBA). • TIBA targets the emissions responsibility of multinational enterprises (MNEs). • TIBA rewards the home regions that transfer clean technology to host regions. • TIBA may reduce global CO 2 emissions by up to 3,762 Mt in 2016. The achievement of global warming limits below 2 °C and 1.5 °C requires deeper involvement of nonstate and subnational actors. In this paper, we focus on multinational enterprises (MNEs) and propose a new technology-adjusted investment-based emission accounting (TIBA) system that considers the technology gap between parent companies and their foreign affiliates. Specifically, TIBA rewards the home regions that transfer clean technology to host regions through MNEs to reduce global emissions and penalizes home regions that expand with high emission intensities through MNEs to increase global emissions. Under the TIBA system, the economies with high outward foreign direct investment stocks are assigned significantly higher responsibilities of emissions than under the production-based accounting (PBA), such as the United States, major European economies, Japan, and Canada. However, the increases in responsibilities differ sharply, depending on their investing regions and industries, as well as the technology transfers. Moreover, our measurements suggest that ideal technology transfers under TIBA would reduce emissions by up to 3,762 Mt, accounting for ∼16% of global Carbon Dioxide emissions from industrial processes involving fossil fuel combustion in 2016. This implies that there is room for improvement in low-carbon technology transfers through MNEs to combat global climate change. Thus, we argue that TIBA targets an efficient policy that highlights the role of MNEs. [ABSTRACT FROM AUTHOR]

As the first legally binding global agreement on climate change, the Paris Agreement aims to limit long-term global warming to less than 2 °C, preferably below 1.5 °C compared to pre-industrial levels. Road transport, as one of the primary sources of energy consumption and carbon emissions, has great potential for energy conservation and emission reduction in achieving the climate goals. However, current approaches cannot efficiently reduce road travel, making it challenging to decarbonize in the transport sector. Therefore, in this paper, we propose STRICTs, a blockchain-enabled motor vehicle restrictive and trading system based on the carbon emissions cap. STRICTs allows automated carbon emission auditing and carbon emission violation punishment without relying on third-party escrow. Through a decentralized enforcer, STRICTs also enables carbon permit trading reliably and transparently. Finally, we implement a proof-of-concept prototype of the system based on Hyperledger Fabric and conduct experiments for comprehensive performance evaluation through CO2 Emission by Vehicles dataset. The experiment results show the practically affordable performance of STRICTs. [Display omitted] • Carbon emission calculation and carbon emission permit allocation method is developed. • Vehicle data chain is built to guarantee the reliability and correctness of collected vehicle data. • Restrictions on carbon emission allowance is presented to reduce carbon emissions. • A smart-contract-based decentralized enforcer is proposed to audit user's carbon emission behavior. [ABSTRACT FROM AUTHOR]