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[Display omitted] • Contribution variations of various policies to PM 2.5 deaths are quantified by period and region. • Carbon and pollution controls can enable 79% to reside in low PM 2.5 areas by 2060. • Population aging could double PM 2.5 deaths by 2060 if other factors remain constant. • A joint effort for carbon and pollution could prevent 2.15 million PM 2.5 deaths by 2060. • Pollution controls can greatly reduce PM 2.5 before 2030, but climate policy becomes crucial after. To confront the challenges posed by air pollution and climate change, China has undertaken significant initiatives to develop strategies that address both issues concurrently. However, the health benefits of these initiatives have not been clearly articulated. In this study, the dynamic changes in health impacts under air pollution and carbon reduction actions in China are evaluated by employing the latest concentration–response models and projected PM 2.5 concentrations under future scenarios. From 2020 to 2060, the enforcement of clean air and climate mitigation policies is expected to increase the percentage of the population living with PM 2.5 concentrations meeting the 10 μg/m3 standard by 79 %. Without the implementation of relevant mitigation measures, PM 2.5 -associated deaths are projected to double due to an aging population. In comparison to the 2060 reference scenario, the joint implementation of clean air and carbon neutrality measures is expected to reduce nationwide PM 2.5 -associated mortality by 62 %, equivalent to 2.15 (95 % CI: 1.80–2.48) million deaths. Stringent pollution controls are crucial for reducing PM 2.5 -associated deaths before 2030, after which carbon neutrality actions become increasingly significant from 2030 to 2060. The challenges of mitigating future PM 2.5 -associated deaths vary greatly across regions, showing a critical response to pollution control and carbon reduction. The research proves the effectiveness of China's future air pollution control and carbon reduction policies in mitigating PM 2.5 -associated deaths. [ABSTRACT FROM AUTHOR]

Extreme weather and climate events tend to increase and strengthen as global warming intensifies, which severely affect human life and sustainable economic development. Therefore, based on the Detection and Attribution Model Intercomparison Project (DAMIP) and the Land Use Model Intercomparison Project (LUMIP) provided by the Coupled Model Intercomparison Project phase 6 (CMIP6), the optimal fingerprinting method is applied to quantify the greenhouse gases (GHG), aerosols (AA), natural forcing (NAT), and land use/cover change (LUCC) contributions to the intensity, frequency, and duration of extreme temperatures in China during 1960—2020. The results show that GHG is the main driver of extreme temperature changes in China, except for ice days (ID0) and cold spells (CSDI). GHG causes an increase in warm spells (WSDI) by about 10 days and an extension of the growing season length (GSL) by 6 to 8 days. The Tibetan Plateau is the region with the strongest extreme temperature changes influenced by GHG. AA forcing has a cooling effect that partially offsets the warming effect of GHG, especially in southeastern China. It should be pointed out that AA forcing is also the main driver for the changes in diurnal temperature range (DTR) in southeastern China, which exceeds the GHG contribution. Additionally, LUCC has greater impact in nighttime extreme temperature indices changes than the regional AA, and becomes the second dominant factor beside GHG. LUCC leads to an attributable cooling contribution of 0.34 °C for the maximum of daily minimum temperatures (TNx). Spatially, the LUCC effects on extreme temperature changes are stronger in western China than in eastern China. The more robust estimation of the GHG, AA, NAT, and LUCC contributions over distinct regions provides an advanced understanding of anthropogenic impacts on regional extreme temperatures, which is expected to be an important reference for regional climate change adaptation and mitigation. [Display omitted] • Tibetan Plateau is the region with the strongest extreme temperature changes influenced by greenhouse gases (GHG). • GHG displays a nonuniformity effect on the changes in the extreme temperature frequency. • Land use/cover change (LUCC) has a stronger role in nighttime extreme temperature indices changes than the regional AA. • The LUCC effects on extreme temperature changes are stronger in western China than in eastern China • The LUCC effects on extreme temperature show asymmetrical characteristics. [ABSTRACT FROM AUTHOR]

Highlights • 2050 primary energy use can be the same as in 2010 with a 7-fold increase in GDP. • Coal use can peak around 2020, then oil in 2033, and natural gas in 2045. • Non-fossil energy is 28% in 2030, higher than China's Paris Agreement goal of 20%. • Industry CO 2 emissions can peak ∼2020, buildings ∼2029, and transportation ∼2035. • CO 2 emissions can peak in 2025, earlier than China's Paris Agreement goal of 2030. Abstract As part of its Paris Agreement commitment, China pledged to peak carbon dioxide (CO 2) emissions around 2030, striving to peak earlier, and to increase the non-fossil share of primary energy to 20% by 2030. Yet by the end of 2017, China emitted 28% of the world's energy-related CO 2 emissions, 76% of which were from coal use. How China can reinvent its energy economy cost-effectively while still achieving its commitments was the focus of a three-year joint research project completed in September 2016. Overall, this analysis found that if China follows a pathway in which it aggressively adopts all cost-effective energy efficiency and CO 2 emission reduction technologies while also aggressively moving away from fossil fuels to renewable and other non-fossil resources, it is possible to not only meet its Paris Agreement Nationally Determined Contribution (NDC) commitments, but also to reduce its 2050 CO 2 emissions to a level that is 42% below the country's 2010 CO 2 emissions. While numerous barriers exist that will need to be addressed through effective policies and programs in order to realize these potential energy use and emissions reductions, there are also significant local environmental (e.g., air quality), national and global environmental (e.g., mitigation of climate change), human health, and other unquantified benefits that will be realized if this pathway is pursued in China. [ABSTRACT FROM AUTHOR]

Abstract Reducing power sector emissions in China is a critical step toward mitigating climate change and lowering health damages from air pollution. We conduct a discrete choice survey (N = 1060) among urban residents from 10 Chinese cities, assessing how individuals compare electricity source, cost, and reduction of emissions related to climate change or air pollution. Using observed air quality data, we also evaluate how pollution levels affect respondents' support for different types of emissions reductions. We find that reductions targeting both climate change and human health benefits have stronger support than those which address only one of the two. Furthermore, respondents in cities with the highest annual concentrations of particulate matter are willing to pay 30% more to clean up the air when compared to individuals living in less polluted cities. The analysis suggests that the public values co-optimizing mitigation policy across climate and health objectives, and that making available information on long-term air quality may encourage sustained support for cleaner energy. [ABSTRACT FROM AUTHOR]

Highlights • We mapped city-level CO 2 emissions simulated by DMSP/OLS nighttime light imagery. • City-level CO 2 emissions were featured as spatial agglomerations. • The GWR revealed significant spatial heterogeneity in the impacts of different factors. • Private car ownership, PCGDP, energy consumption positively affected CO 2 emissions both globally and locally. • The reminder factors studied in the GWR were found to bi-directionally affect CO 2 emissions. Abstract Cities produce over 70% of the global CO 2 emissions that result from energy use, and thus play a key role in climate mitigation and adaptation. While the factors influencing CO 2 emissions have been subject to extensive study, via research that has explored the path of developing a low-carbon economy, little work has been undertaken at the city level as a result of a deficiency in data availability. Addressing this gap, this study firstly estimated CO 2 emissions of cities in China using Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) nighttime light imagery. We then analyzed spatial variations in the estimated CO 2 emissions at the city level, using a spatial analytical model, finding significant spatial autocorrelation in CO 2 emissions. Subsequently, we compared the effects of different socioeconomic factors on CO 2 emissions, using both global and local regression models. The results from the global regression model revealed that private car ownership, economic growth, and energy consumption were the major factors promoting CO 2 emissions in China's cities, while population density had an effect in reducing CO 2 emissions. The use of a Geographically Weighted Regression (GWR) model provided more detailed results, revealing significant spatial heterogeneity in the impacts of different factors. Economic growth, private car ownership, and energy consumption all posed positive effects on CO 2 emissions while the remainder of the factors studied were found to pose a bidirectional impact on CO 2 emissions in different areas of China. Economic growth and private car ownership were to found to exert the strongest positive effects in the cities of western and central China, and energy consumption was shown to significantly and positively influence CO 2 emissions in the southernmost part of China. Urban expansion and road density were identified as key promoting factors in CO 2 emissions in the northeast of China; and the industrial structure demonstrated significantly positive effects in relation to CO 2 levels in cities located in the Beijing-Tianjin-Hebei region. The role of foreign direct investment (FDI) was not found to be significant in most cities expect Guangdong, where a significant positive relationship appeared. [ABSTRACT FROM AUTHOR]

Petroleum coke, a non-environmentally friendly energy source, is gradually replacing other power fuels in China’s industrial enterprises because of its price advantage. Petroleum coke has high emission factors and thus emits more greenhouse gases (GHGs) and air pollutants than even raw coal. This study first examines the rapid growth of petroleum coke consumption in China since 2010 by industry sector and region and then estimates the petroleum coke-related emissions. We conclude that the total consumption of petroleum coke increased by 18.9% from 2010 to 2016 and that the industry final consumption for burning in boilers increased dramatically (by 158.2%). Petroleum coke-related CO 2 emissions reached 28 million tonnes in 2016, whereas CH 4 and N 2 O emissions totaled 870 and 143 tonnes, respectively. The increased use of petroleum coke will increase the urgency for the development of climate change mitigation and emissions reduction measures in China. We propose several possible policy suggestions for petroleum coke management and emissions control, such as strongly restricting the production and import of high-sulphur petroleum coke, as well as burning petroleum coke to provide power; more power plants and industrial kiln stoves/boilers should be equipped with efficient decontamination systems; the development of advanced industrial processes and the clean utilization of petroleum coke should be encouraged. [ABSTRACT FROM AUTHOR]

• We assessed the climate change impact on wheat production in China. • We employed the FGLS, DOLS, and D–K estimation techniques. • Temperature negatively affected wheat production in the long–run. • Precipitation contributed positively to wheat production in the long-run. • Agro–chemical input (fertilizer use) enhanced wheat production in the long–run. Northern and Southern regions are the two major wheat production belts of China. Agro–climatic resources have changed significantly in recent years, threatening staple food production in these regions. As a result, it is critical to investigate the long–term effect of climate change and agri–inputs on wheat production in China's top six wheat producing provinces (Hebei, Shandong, Henan, Jiangsu, Anhui, and Hubei) from 1995 to 2020. The estimated long-run results from the FGLS, DOLS, and D–K estimators revealed that climatic factors, specifically temperature, had a negative impact on wheat production, while precipitation had a positive impact. The findings also revealed that agrochemical inputs, such as fertilizer, increases wheat production, whereas pesticide use decreases wheat production significantly. The results from the Dumitrescu–Hurlin panel causality test showed a bidirectional causality between rainfall, fertilizer use, and cultivated area with wheat production, while a unidirectional causality association is running from labor force to wheat production. The current study provides several critical policy recommendations for China's sustainable food production through green agricultural practices and robust climate mitigation strategies. [Display omitted] [ABSTRACT FROM AUTHOR]

The thermal power industry, the cement industry and the iron & steel industry are among the top energy consumers and air-polluters in China, which have significant impacts on climate change. The annual productions of these three industry sectors are all ranked as the top one in the world. In order to assist the short-term policy making for the development of critical LCTs in China, an evaluation of the performance of low carbon technologies (LCTs) for the top three energy-intensive industries in China is conducted in this paper through multi-criteria decision making (MCDM) method. There are 31 LCTs identified for these three industries based on the criteria including environmental performance, technological performance, and economic performance. Based on the experts’ evaluation, top 10 LCTs are selected as the critical LCTs which should be given priority in the short-term technology diffusion in China. Suggestions are provided for policy-makers on the carbon mitigation and cleaner production in the main energy-intensive industries in China. [ABSTRACT FROM AUTHOR]

During the past two decades there has been a shift in the geography of Global Supply Chains (GSCs) from developed countries to China, and more recently from China to successor developing countries in South Asia, Africa and Latin America. The shift in GSC geography influences global greenhouse gas (GHG) emissions because of an energy efficiency and low-carbon technology gap between developed and developing economies. Our simulations indicate that changing GSC geography toward China positively contributed, on average (2001–2008), 919 Mt CO 2 equivalents to global GHG emissions annually. In addition, there are potentially even larger indirect effects, including import-related and transportation-related emissions that are attributable to GSC shift-related improvements in developing world consumption and infrastructure. We then investigate the emission impact of a further GSCs shift toward South Asia, Africa and Latin America. Although the direct impact of such a shift is likely negative due to a lower dependency on coal as well as lower carbon intensities in South Asia, Africa and Latin America relative to China, it is likely that the direct effects are more than offset by the indirect shift-related effects associated with improvements in consumption and infrastructure. Our results have policy implications for future climate change mitigation. [ABSTRACT FROM AUTHOR]

The so-called post-China countries (PC-16́s), distinguished by low wages and high economic growth, will replace China as the “world’s factory”. The aim of this paper is to assess the effect of these changes on global CO 2 emissions pathways. To achieve this, a counterfactual is proposed wherein China’s trade with the rest of the world is replaced by the PC-16’s trade in a global multiregional input–output context. The emissions savings realized by trade replacement are significant in those scenarios where the current pattern of trade is maintained (−13% on emissions traded and −3.5% on global emissions) and in scenarios where enterprises relocate their production directly or indirectly to the most environmentally efficient countries (ranging from −15.2% to −18.2% on emissions embodied in trade). Nevertheless, the potential savings drop considerably (ranging from −1.5% to −7.1%) if companies and host countries take advantage of cheaper, but more polluting means of production and do not internalize the externalities. Through changes in international trade, there is a possibility of reducing emissions, which have to be included in international, multilateral and bilateral agreements to mitigate climate change if we do not want to lose the opportunities these changes present. [ABSTRACT FROM AUTHOR]

Community shared solar (CSS) program has great potentials in contributing to the complete decarbonization of the power sectors worldwide. Few research have focused on its potential diffusion from the user perspective. This paper fills the gap by conducting a survey-based unlabeled choice experiment in the Guangdong Province, China to investigate the determinants of potential users' willingness to participate in CSS programs. We analyzed the survey data using a random parameter logit model. Our results show that users are more likely to participate in CSS programs with lower upfront payment, trialability, shorter payback period, a public utility as provider and larger impact on climate change mitigation. However, they are likely to accept longer payback period in CSS programs with higher participation rate because of the potential benefit from interpersonal communication. Users' previous knowledge of CSS programs and income will also increase their willingness to participate in CSS programs with higher upfront payment. Our results provide important implications for designing policies and business models to promote the distributive renewable energy in China. • Community shared solar is widely accepted among surveyed individuals in our choice experiment. • The business model, and the ownership structure of community shared solar affect its potential adoption. • The interpersonal communication and public promotion of community shared solar program can increase its popularity. [ABSTRACT FROM AUTHOR]

Agricultural land carbon opportunity cost (COC) characterizes potentials for carbon sequestration through ecosystem restoration, which is a critical component for formulating nature-based solutions to mitigate climate change. Yet existing relevant estimates still stayed at global scale, lacking estimates at national and provincial scale. Here, we integrated multi-source downscaled data to estimate the magnitude of land COC for 20 categories of crops and livestock in 30 provinces of China. Results show that beef got the highest land COC with about 29% of the national total, and COC per unit production of beef was much higher than that of other products. The high beef-induced COC was primarily caused by vast amount of grass feed consumed by beef cattle, resulting in native forest land being cleared into grazing land. Moreover, both land COC and crops yield per unit area of cropland enhanced with latitude decrease, but the increase rate of the former was much higher than that of the latter. Therefore, improving utilization efficiency of existing grazing land and raising yields per unit area of existing croplands in low-latitude provinces, rather than clearing new native forest land into grazing land and cropland, would have great functions on declining national total land COC for agricultural products. The research could also contribute to discussions of local tradeoffs between land carbon storage and agricultural production and then inform climate mitigation strategies. • Land carbon opportunity cost (COC) by province-product in China was estimated. • Sichuan, Hunan, and Guangxi had the largest capacity to restore carbon. • Beef production contributed the most (29%) of national total COC. • Land COC per unit yield enhanced substantially with decreasing latitude. • Tradeoffs between carbon stock and agricultural production needs to be discussed. [ABSTRACT FROM AUTHOR]

China, the world's largest CO 2 emitter, is making every effort to transition to a low-carbon economy and fulfill its part of a concerted global commitment to combating climate change. In tandem with decarbonizing energy and industries, feasible supplementary measures are urgently needed to help remove anthropogenic CO 2 from the atmosphere. A burgeoning literature has emphasized the CO 2 removal capability of land re-naturalization (such as afforestation and wetland restoration), thereby regarding cognate land-use conversions as Nature-based Solutions (NbS) and potential climate policy options. However, little empirical evidence exists concerning the effectiveness of different land re-naturalization pathways (such as converting wetlands to forests or agricultural lands to grasslands), and it also remains unclear how NbS alternatives (i.e., land-use conversions resulting in negative CO 2 emission) and non-NbS options (i.e., land-use conversions resulting in positive CO 2 emission) could affect the social cost of carbon (SCC), a conventional measurement for prescribing carbon mitigation approaches. This study aims to fill in this knowledge gap via embedding NbS into the dynamic integrated climate-economics (DICE) model to quantify their impacts on the SCC. Using the Pearl River Delta region (south China) as a case study for the temporal horizon during 2000–2020, we find that both positive and negative CO 2 fluxes have been brought by different natural/semi-natural land conversions, affecting the SCC correspondingly. A total of 7 out of 17 types of land-use conversions could be identified as feasible NbS interventions, including forest restoration, forest-to-wetland, grassland-to-forest, grassland-to-wetland, grassland-to-cropland, cropland-to-forest, and cropland-to-wetland conversions, which could reduce the SCC values (comparing 2020 base-year with 2000 base-year) by 0.0132, 0.0009, 0.0033, 0.0030, 0.0001, 0.0082, and 0.0001 (USD/tCO 2), respectively. While the SCC is mainly determined by energy and industrial structure, the overall effect of NbS is larger than the sum of land urbanization and non-NbS land-use conversions. Via embedding the real-world inter-dynamics of land-use conversions into the SCC quantification, this study presents a pioneer assessment of the impacts of NbS on the SCC in an integrated framework, sheds important insights into the effectiveness of NbS, and offers practical implications for policy-makers to devise comprehensive policies covering all feasible CO 2 abatement options. [ABSTRACT FROM AUTHOR]

Urban form is increasingly being recognised by scientists for the potential role it might play in the coordination of sustainable urban development and the reduction of CO 2 emissions. However, despite increasing interest in the morphology of cities in climate change science, few quantitative estimates have been made of the effects of urban form on CO 2 emissions. The goal of this study is to quantify this relation, using panel data for China’s 30 provincial capital cities from 1990 to 2010. In order to meet this aim, we first selected a series of urban form indicators, which we quantified by applying spatial metrics to remotely sensed data. We then estimated CO 2 emission levels using a unified standard method recommended by the IPCC Guidelines, and subsequently performed a panel data analysis. The results of the study demonstrated a positive correlation between the growth of urban areas and CO 2 emission levels. Further, it was also found that increased “urban continuity” led to reductions in CO 2 emissions and that, conversely, increased “urban shape complexity” exerted a positive influence in relation to CO 2 emissions. The findings of this study indicate that measures to make existing cities in China more compact may in fact help to reduce levels of CO 2 emissions, just as increasing fragmentation or increased irregularity with respect to urban form may contribute to increased CO 2 emissions. If serious about achieving meaningful reductions in CO 2 emissions, decision makers and planners should take urban form into consideration when developing low-carbon cities in China. [ABSTRACT FROM AUTHOR]

The increasing vehicle numbers in China have raised issues on effective mitigation of the vehicular NO x emissions recently. Notably, temporally growing and spatial agglomeration of high vehicular NO x emissions make an essential challenge to the mitigation strategy-makers. However, so far, there have been few studies to give insight into the socioeconomic drivers like the spatial imbalance of socioeconomic development, vehicle structure and road infrastructure to help governors. To fill the above gap, this study explores drivers of temporal change and spatial differences by building a temporal-spatial decomposition model and accounting for national and regional NO x emissions from vehicles in China from 2005 to 2015. Results show that, of all the driving forces in this study, only road vehicle carrying capacity (ΔN VI) acts as a primary driving force for both temporal growing and spatial agglomeration of vehicular NO x emissions in China. Regional vehicle emission intensity (ΔN NI) and road economic growth (ΔN EI) only mainly contributed to spatial agglomeration. While economic development (ΔN G) played a crucial role in the temporal growing of vehicular NO x emissions in China. These findings indicate that the future mitigation policy should fully cover the comprehensive socioeconomic factors, which would be useful for China and other developing countries when aiming to improve the performance of their current vehicle emissions policy system. Image 1 • China's NO x emissions from provincial vehicles were estimated during 2005–2015. • A new temporal-spatial decomposition model was built to identify emission drivers. • Road vehicle carrying capacity drives both temporal change and spatial difference. • Regional emission intensity and road economic growth affect spatial difference. • Economic development played a crucial role in the temporal change. [ABSTRACT FROM AUTHOR]