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China has responded to the sustainability challenges via a range of policies with evolving objectives in the Yangtze River Economic Belt (YEB) since the 1990s. However, the multi-scale analysis of YEB's comprehensive sustainability and the human-environment nexus amid policy impact remains unexplored. A comprehensive review and forecast of historical and future sustainability pathways under policy impacts are imperative. Here, we systematically examined sustainability under ten National Policies (NPs) and Regional Development Policies (RDPs), forecasting Shared Socioeconomic Pathways (SSPs) in the 21st Century using the entropy weight method and machine learning models. We found that RDPs have contributed to 1.6 times increase in human development from 2000 to 2018 across dimensions of demography, economy, and society in YEB. However, it also revealed that the west-east disparity has widened from 0.14 to 0.19 during this period. Conservation efforts and national initiatives for ecological civilization have led to environmental improvement in the YEB, especially after the RDP3 in 2014, when the eastern provinces, like Shanghai, have already surpassed the peak inverted U-shape curve of the environmental-human nexus. Among the SSPs, SSP1 shows the most sustainable scenario with the lowest ecological footprint at 6.2 hm2 per capita and the highest value of regional sustainability and environmental subsystem. To achieve SSP1, an iterative, inclusive, and context-specific Science-Policy-Practice dialogue is essential. This enables feedback loops and collaboration among policymakers, scientists, and practitioners to foster regional sustainability by studying the implications of historical and future pathways. [Display omitted] • YEB's development transitioned from economic to high-quality. • Regional Policies' effect: Wellbeing surges, overshooting ecological footprints. • The systematic east-west sustainability gradient widened in the past 2 decades. • Eastern provinces of YEB experienced early sustainability turning points. • Optimal SSP1: Lower ecological footprint & climate mitigation, higher development. [ABSTRACT FROM AUTHOR]

[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]

Carbon emission reduction in China matters to global climate change mitigation. China has been experiencing extensive land changes, which profoundly influence terrestrial ecosystem carbon storage (TECS) and carbon emissions. Scholars have predicted influences of land changes on TECS in China with scenarios obtained from global integrated assessment models (IAMs), which lack national details. Moreover, universally existing variations in land-use intensity have not been considered when estimating influences on TECS. This study simulated changes of land-use intensity of China from 2000 to 2050 using CLUMondo under China-specified policies for sustainable development modeled by a national IAM named Threshold21-China. We proposed a more precise TECS estimation method by distinguishing land-vegetation and land-soil types. Results demonstrated that under scenario with preceding policies, the total TECS can increase by 865.5 Tg C from 2000 to 2050. Through implementing preceding policies, TECS loss by conversions from cultivated land to artificial surfaces can decline by 82 Tg C, and new TECS accumulated by increased and densified forests can increase by 73 Tg C. Mountainous and rapidly urbanizing regions are sensitively influenced and need more restrict land change management policies. This study demonstrates the significance of sustainable development policies for TECS conservation and indicates specific critical regions. • Introducing national IAM into land change simulation. • Considering land-use intensities in land change simulation. • Proposing an improved TECS estimation method. • Estimating influences of land changes on China's TECS. • TECS accumulation could be improved under sustainable policies. [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]

• 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]

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]