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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 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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

Several studies have shown the benefits of using timber in the construction sector in terms of climate change, which has received the support of decision-makers. However, few studies focus on other environmental indicators. The environmental impacts (i.e., such as human health, ecosystem quality, and resources) of material substitutions, consequence of the increasing use of wood, are still lacking in the literature. Studies that compare different structural materials focus either on a single building or on one structural system that would be representative on a larger scale. However, the environmental benefits of some projects are not easily extrapolated to the scale of a given region with a variety of architectures. Higher-order effects, beyond the building scale, can indeed imply changes in the resource availability according to the unconstrained suppliers and resources. The objective of this paper is to assess the life cycle environmental consequences of wood substitutions at a regional scale for the non-residential construction sector. The increasing use of wood structures for non-residential buildings in the province of Quebec (Canada) is used as a case study. The method includes the development of material substitution factors by comparing several structures. The substitution factors show that, on average, wood can replace, simultaneously, 0.59 and 4.54 times the weight of steel and concrete, respectively. However, steel substitution has more advantages than concrete substitution. Among the tested parameters, the variability of the material substitution factors implies more uncertainties in the results. The originality of our study lies in the limitations that may change the conclusions drawn from the substitution at a large scale. With three substitution scenarios for four impact categories, the results showed an advantage of using wood in seven of the twelve combinations. The ecosystem quality indicator is the most unfavorable and shows opposite trends to climate change, human health, and resource indicators. Considering average material substitution factors combined with the maximum potential use of wood in non-residential (NR) structures in Quebec in 2050, wood can contribute to avoid 2.6 Mt of carbon dioxide equivalent (CO 2 eq.). This amount is equivalent to 3.5% of Quebec's CO 2 eq. emission reduction target by 2050 compared to 1990. • The environmental consequences of wood substitution at the regional level for the non-residential sector are assessed. • The average scenario suggests that the use of wood can avoid up to 2.62 Mt of CO 2 eq. in 2050. • The variability of material substitution factors implies the greatest variability in the results. • With three substitution scenarios for four impact categories, the results showed an advantage for wood increased use in seven of the twelve combinations. [ABSTRACT FROM AUTHOR]

Universities, the important locations for scientific research and education, have the responsibility to lead ecological civilization and low carbon transition. Ecological footprint evaluation (EFE) is usually used to measure sustainability of campuses. Although it can provide guidance and reference for overall campus planning, it lacks effective significance for individual behavior, especially when the reduction of carbon emissions is the aim. On the other hand a possible solution can be represented by machine learning. It can identify the key factors that will influence individual's overall carbon emissions caused by students' daily behavior, it can be used to find effective ways to reduce individual carbon emissions. This paper applied EFE and machine learning to comprehensively evaluate campus sustainability and students' carbon emissions. Huazhong University of Science and Technology (HUST), a "University in the Forest", was used as a study case in China. Even if HUST is endowned with a forest coverage of 72%, here we showed that its Ecological Footprint Index was −12.52, indicating strong unsustainability. This is mainly due to the high energy and food consumption, caused by the large population living in the campus and the lacking of energy saving measures. The per capita ecological footprint was relatively high, compared with other universities in the world, which meant more efforts needed to be done on ecological sustainability. Low carbon emission is a key feature for a sustainable campus. Based on the questionnaire survey delivered to 486 students who live in the campus, their daily active data were collected in terms of students' personal clothing, food, housing, consumption and transportation. And their associated carbon emissions were calculated based on emission intensities of Chinese population. Based on 486 detailed datasets, machine learning was then used to identify the key daily behavior to influence students' total carbon emission. Results showed that making behavior changes in air conditioning, food and electric bicycle were the most effective ways to reduce carbon emissions. Finally, while effective suggestions were proposed based on qualitative and quantitative evaluations, it is concluded that it is imperative for universities in China to formulate effective low-carbon policies, to achieve sustainable development and to confront global climate change. • A review of main initiatives of sustainable campus construction worldwide. • An evaluation combining campus ecological footprint and individual carbon footprint. • The ecological footprint of "China Forest University" reflects unsustainable. • Machine learning identifies internal driving force of campus carbon emissions. • Targeted guidelines on campus low-carbon construction are provided. [ABSTRACT FROM AUTHOR]

The carbon dioxide emission from the industrial sector and the power plant contribute significantly to global climate change for several decades. The carbon capture and storage technology is the primary solution to reach the reduction target of carbon dioxide emissions. The carbon capture and storage activities involve CO 2 capturing, transporting, and storing in geological storage, requires number planning. The process integration approach by pinch analysis method can be used for the carbon capture and storage planning problem and to develop the carbon capture and storage network design. However, the applicability of the method needs to be evaluated when some constraints in carbon capture and storage network design are applied. This paper proposes an improved pinch analysis based method for carbon capture and storage target and network design. The method begins with targeting the maximum carbon exchange in the carbon capture and storage system, which is followed by designing the carbon capture and storage network. Next, the capital-carbon trade-off is introduced as a new strategy for assessing carbon capture and storage network design to show the economic feasibility of the design. Four case studies demonstrate the applicability of the proposed method to the carbon capture and storage systems in the central and western part of Indonesia. The application of this new strategy in the western part of Indonesia as a single region system revealed that the flat minimum of the total annual cost is obtained at a five year time difference with the amount of up to US$ 149.3 million. Image 1 • A CCS cascade analysis in central and western part of Indonesia was introduced. • A systematic approach in multi-region and multi- period was proposed. • Cascade analysis with minimum time difference was shown to be a good method. • Grid diagram showing the pairing between source and sink was a power tool. • Capital-carbon trade-off as a new strategy was proposed to assess CCS system design. [ABSTRACT FROM AUTHOR]

Global climate change caused by human activities has posed a huge threat to the environmental governance and sustainability of human-being. Fortunately, the carbon emission trading scheme, a powerful tool for reducing carbon emissions, has been established in many countries to slow catastrophic climate change thus promoting human well-being. The nexuses between energy and European carbon markets have been extensively studied due to the grim reality of global climate change. However, no literature to date has examined the multi-scale associations between China's energy and regional CET markets. This paper aims to fill this gap by utilizing a proposed wavelet-based multi-scale investigation framework to explore the information spillovers and dynamic dependence over different time horizons. The original energy and carbon return series are decomposed by the MODWT method. The TVP-VAR-based connectedness and the DECO-FIGARCH model are then built at each selected wavelet component. The wavelet coherence method is also applied to depict the time-frequency dependence. The empirical results demonstrate that the information spillovers at multivariate time-scales are heterogeneous. Generally, GDEA and the crude oil markets act as the information spillover net-transmitters at the raw data level and all wavelet scales. The dynamic spillovers present significant time-varying features and a similar evaluation trajectory. Besides, we offer strong evidence of a low dynamic equicorrelation between China's energy and regional CET markets, suggesting the portfolio diversification benefits. Furthermore, the information spillover and dependence are proved to be more significant at longer time horizons. Finally, the energy-carbon portfolios offer diversification opportunities, and the risk reduction effectiveness varies with wavelet scales. Moreover, the optimal-weighted portfolio exhibits the best risk management performance. Image 1 • Wavelet-based multi-scale spillover and dependence analysis framework is proposed. • MODWT is applied to decompose the original data into various wavelet components. • TVP-VAR-based connectedness is utilized to quantify the information spillovers. • Wavelet-based-DECO-FIGARCH model is employed to examine the dynamic dependence. • Wavelet coherence method is used to depict the time-frequency dependence structure. [ABSTRACT FROM AUTHOR]

Concentrations of building mass and insufficient greenery in cities are identified to contribute significantly to extended heat stress in the built environment, commonly known as the urban heat island (UHI) effect. This paper presents a scenario-based modelling built on climate change projections and potential alterations of urban greenery in 2030 and 2090 in Adelaide, South Australia. The model is based on regional climate change scenarios, potential urban surface cover alternatives and resulted urban microclimate variations in Adelaide. Projected energy demand variations and corresponding carbon emission are calculated in each scenario. Results indicate that an ideal urban landscape transformation scenario with 30% tree canopy can effectively decrease the surface temperature by 1 °C in winter and 3 °C in summer by 2090. It is estimated that having greener and more heat resilient public spaces could save a total carbon emission of 140,000 tone CO2e in Adelaide annually compared to a business-as-usual scenario. Urban greenery may be used as a mean of increased urban life resilience to climate change by reducing surface temperature, increasing urban resilience and decreasing the energy demand during summer. [ABSTRACT FROM AUTHOR]