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• We develop a quantitative spatial equilibrium model with emissions regulation. • Counterfactual analyses of regional structural changes due to emissions regulation. • Emissions regulations impact regional GDP via regional-sectoral linkages. • Cross-regional impacts of emissions regulations have typical geographical characteristics. • Sectoral linkages widen variation in emissions regulations' impact on regional GDP. We develop and quantitatively evaluate a spatial general equilibrium model that incorporates carbon emission regulations. We study the impact of emission regulation on the economies of regions within a country under climate change mitigation goals, and how the impact of emission regulation in one region influences other regions through regional‒sectoral linkages. The model is calibrated using Chinese regional and sectoral data, and several counterfactual exercises are performed. The results indicate that undifferentiated increases in emission regulation across regions have resulted in inter-regional differences in real GDP changes; however, "equity-oriented" regionally differentiated emissions regulations reduce this imbalance. Regarding interactions between regions, negative impacts on the economy are characterized by geographical proximity, whereas positive impacts are not geographically constrained. Sectoral linkages exacerbate the negative economic impacts of emission regulations and widen regional disparities. Additionally, we demonstrate the extended application of our model through two case studies. [ABSTRACT FROM AUTHOR]

China is facing challenges to tackle the threat of climate change while reducing social inequality. Poverty eradication requires improvement in the living conditions of low-income households, which leads in turn to higher carbon footprints and may undermine the efforts of climate change mitigation. Previous studies have assessed the climate impacts of poverty eradication, but few have quantified how the additional carbon emissions of poverty eradication are shared at the subnational level in China and the impact on China's climate targets. We investigated the recent trend of carbon footprint inequality in China's provinces and estimated the climate burden of different poverty reduction schemes, measured by increased carbon emissions. The results indicate that poverty eradication will not impede the achievement of national climate targets, with an average annual household carbon footprint increase of 0.1%–1.2%. However, the carbon emissions growth in less developed provinces can be 4.0%, five times that in wealthy regions. Less developed regions suffer a greater climate burden because of poverty eradication, which may offset carbon reduction efforts. Therefore, interregional collaboration is needed to coordinate inequality reduction with investments in low-carbon trajectories in all provinces. [ABSTRACT FROM AUTHOR]

Accurate estimate of the size of land carbon sink is essential for guiding climate mitigation actions to fulfill China's net-zero ambitions before 2060. The atmospheric inversion is an effective approach to provide spatially explicit estimate of surface CO 2 fluxes that are optimally consistent with atmospheric CO 2 measurements. But atmospheric inversion of China's land carbon sink has enormous uncertainties, with one major source arising from the poor coverage of CO 2 observation stations. Here we use a regional atmospheric inversion framework to design an observation network that could minimize uncertainties in inverted estimate of China's land carbon sink. Compared with the large spread of inverted sink (∼1 Pg C a−1) from state-of-the-art inversions using existing CO 2 observations, the uncertainty is constrained within 0.3 Pg C a−1 when a total of 30 stations were deployed, and is further reduced to approximately 0.2 Pg C a−1 when 60 stations were deployed. The proposed stations are mostly distributed over areas with high biosphere productivity during the growing season, such as Southeast China, Northeast China, North China, and the Tibetan Plateau. Moreover, the proposed stations can cover areas where existing satellites have limited coverage due to cloud shadowing in the monsoon season or over complex topography. Such ground-based observation network will be a critical component in the future integrated observing system for monitoring China's land carbon fluxes. [ABSTRACT FROM AUTHOR]

Air pollution control policies in China have been experiencing profound changes, highlighting a strategic transformation from total pollutant emission control to air quality improvement, along with the shifting targets starting from acid rain and NO x emissions to PM 2.5 pollution, and then the emerging O 3 challenges. The marvelous achievements have been made with the dramatic decrease of SO 2 emission and fundamental improvement of PM 2.5 concentration. Despite these achievements, China has proposed Beautiful China target through 2035 and the goal of 2030 carbon peak and 2060 carbon neutrality, which impose stricter requirements on air quality and synergistic mitigation with Greenhouse Gas (GHG) emissions. Against this background, an integrated multi-objective and multi-benefit roadmap is required to provide decision support for China's long-term air quality improvement strategy. This paper systematically reviews the technical system for developing the air quality improvement roadmap, which was integrated from the research output of China's National Key R&D Program for Research on Atmospheric Pollution Factors and Control Technologies (hereafter Special NKP), covering mid- and long-term air quality target setting techniques, quantitative analysis techniques for emission reduction targets corresponding to air quality targets, and pathway optimization techniques for realizing reduction targets. The experience and lessons derived from the reviews have implications for the reformation of China's air quality improvement roadmap in facing challenges of synergistic mitigation of PM 2.5 and O 3 , and the coupling with climate change mitigation. [Display omitted] [ABSTRACT FROM AUTHOR]

Green finance is an effective policy instrument in mitigating climate change, but to date little is known about its impact on carbon dioxide (CO 2) emissions. This study extends the literature on the relationship between green finance and CO 2 emissions while taking trade openness and economic development into consideration to comprehensively explore the conservation/feedback hypothesis using the Autoregressive-Distributed Lag–Error Correction Model (ARDL–ECM) on data collected from 2000 to 2019. By constructing a green finance index comprising green credit, green securities, green insurance, and green investment, results include the following. (1) Support was found for the conservation hypothesis running from green finance, trade openness, and economic development to emissions per capita; the conservation hypothesis also was supported for the unidirectional relationship running from trade openness and economic development to green finance. (2) Green finance is found to be significantly and negatively related to emissions per capita in both the short and long term. (3) Trade openness shows a positive effect on emissions per capita. Robustness tests are provided. This study deepens policy implications of green finance in the post-pandemic era and highlights the moderating role of renewable energy in the green finance impact on carbon mitigation. • This study constructs a green finance index for China. • The autoregressive distributed lag–error correction model is employed. • Green finance contributes to carbon mitigation in both the short and long run. • CO 2 emissions are Granger result of green finance, trade openness and economic growth. • Trade openness and economic growth are Granger causes of each other. [ABSTRACT FROM AUTHOR]

[Display omitted] China is playing an increasing role in global climate change mitigation, and local authorities need more city-specific information on the emissions trends and patterns when designing low-carbon policies. This study provides the most comprehensive CO 2 emission inventories of 287 Chinese cities from 2001 to 2019. The emission inventories are compiled for 47 economic sectors and include energy-related emissions for 17 types of fossil fuels and process-related emissions from cement production. We further investigate the state of the emission peak in each city and reveal hidden driving forces. The results show that 38 cities have proactively peaked their emissions for at least five years and another 21 cities also have emission decline, but passively. The 38 proactively peaked cities achieved emission decline mainly by efficiency improvements and structural changes in energy use, while the 21 passively emission declined cities reduced emissions at the cost of economic recession or population loss. We propose that those passively emission declined cities need to face up to the reasons that caused the emission to decline, and fully exploit the opportunities provided by industrial innovation and green investment brought by low-carbon targets to achieve economic recovery and carbon mitigation goals. Proactively peaked cities need to seek strategies to maintain the downward trend in emissions and avoid an emission rebound and thus provide successful models for cities with still growing emissions to achieve an emission peak. [ABSTRACT FROM AUTHOR]

Natural climate solutions (NCS) offer immediate and cost-effective ways to tackle the climate crisis by transforming atmospheric carbon to soil carbon or avoiding greenhouse gas emissions. However, the climate mitigation potential and economic costs of NCS for cropping systems in China remain inconclusive. The major objectives of this study are (i) to estimate the NGHG reduction potential across Chinese main cropping systems caused by NCS, (ii) to quantify the economic costs of adopting optimal management with different abatement potentials. The Denitrification-Decomposition (DNDC) model was used to estimate the NGHG, including SOC sequestration, N 2 O emissions, and CH 4 emissions. After calibration, we ran the DNDC model with derived data at municipality-level. We estimated the NGHG under current management, adopting optimal management individually, and integrated optimal management to project the maximum NGHG reduction potential caused by NCS. We used the marginal abatement cost method to estimate the economic cost. The four natural climate solutions, N fertilization management (NFM), straw returning management (SRM), tillage management (TM), and rice irrigation management (RIM) can reduce national NGHG in main cropping systems by approximately 118.8 Tg CO 2 -eq, 116.3 Tg CO 2 -eq, 35.2 Tg CO 2 -eq, and 74.4 Tg CO 2 -eq, respectively. The integrated optimal management may potentially reduce NGHG by 256.9 Tg CO 2 -eq, equivalent to 90.2% of current NGHG, and 80% of which can be realized at the price of CN¥ 285 (Mg CO 2 -eq)−1. We further identify the priority NCS for different crops and regions and conclude that nitrogen fertilization management should be the priority NCS at the national level. Our findings highlight the great potential of NGHG reduction by adopting NCS precisely and the importance of optimizing agricultural management as a whole, and they will help policy makers to develop smart-agriculture in China. [Display omitted] • Estimating net greenhouse gas emissions (NGHG) reduction potentials of agriculture. • IPCC recommended tier 3 method was applied for seven cropping systems in China. • The integrated optimal management may potentially reduce NGHG by 256.9 Tg CO 2 -eq. • 80% of NGHG mitigation can be realized at the price of CN¥ 285 (Mg CO 2 -eq)−1. • The priority NCS was identified for different crops and regions. [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]

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]

• The 57.00% of the Yangtze River Economic Belt area exhibited a significant increase in annual NPP. • The response of NPP on climate factors was nonlinear, with greater sensitivity to temperature. • The impact of topographic factors on NPP changes had a threshold effect. Net primary productivity (NPP) of terrestrial ecosystems serves as a crucial carbon sink, playing a significant role in mitigating climate change. This study, focusing on the Yangtze River Economic Belt (YREB), a key area for both economic development and ecological conservation in China, evaluates the temporal and spatial changes in regional NPP and its responses to climatic factors against the backdrop of global change. Utilizing long-term NPP and meteorological grid data from 1981 to 2017, we analyzed the annual change patterns of NPP and its linear and nonlinear responses to climatic factors using copula functions. Our findings indicate that 57.00 % of the YREB has experienced a significant increase in NPP, with the most substantial decreases observed in Shanghai and its surrounding areas (P < 0.05). Temperature emerged as the primary climatic driver, positively correlating with NPP changes in over half of the study area (P < 0.05). Moreover, the nonlinear response of NPP to temperature and precipitation underscores the complex interactions between these factors, revealing a sensitivity to temperature variations that surpasses that to precipitation. The study also highlights the influence of solar radiation and topographic factors, with a significant positive correlation between NPP and solar radiation observed in 15.85 % of the area (P < 0.05). The practical significance of these findings lies in their implications for regional ecological management and climate resilience strategies. The positive correlation between temperature and NPP underscores the potential for targeted temperature management to optimize carbon sequestration across the YREB. Furthermore, the identified nonlinear responses and the role of solar radiation and topography in influencing NPP offer valuable insights for the formulation of adaptive strategies that enhance ecosystem productivity and contribute to achieving carbon neutrality goals. By elucidating the dynamics of NPP in response to a range of environmental factors, this study provides a foundation for informed decision-making in ecological conservation and climate change mitigation efforts within the YREB and similar regions globally. [ABSTRACT FROM AUTHOR]

• Implementation costs are a more relevant constraint to afforestation than opportunity costs. • Financial incentives for afforestation are constrained by market access and market prices. • Carbon-neutral and food multi-oriented land policies need further exploration. • Collaboration among global carbon markets can enhance CO 2 removal efficiency. Afforestation is a promising nature-based climate solution for mitigating climate change, but it is subject to a complex web of biophysical, cost-benefit, market, and policy processes. Although its biophysical feasibility has been established, the cost, market, and policy constraints that affect climate change mitigation through afforestation are still unclear. Here, we estimate such cost, market, and policy constraints on the basis of biophysical feasibility. Our findings reveal that implementation costs are a more relevant constraint than opportunity costs on mitigating climate change through afforestation. The China Certified Emission Reduction market currently provides only a 0.308 % incentive for climate change mitigation through afforestation, due to market access constraints. The current market prices of China Certified Emission Reduction, China Carbon Emissions Trading Exchange, and Nature Based Carbon Offset in Voluntary Carbon Market constrain 88.15 %, 87.95 %, and 85.75 % of CO 2 removal actions through afforestation, compared to the carbon price scenario (US$62.97 tCO 2 -1) of the EU Emissions Trading System. Moreover, land policy under the scenarios of prohibiting conversion of cultivated land to forest and forest restoration in degraded areas exhibit 8.87–29.59 % and 65.16–74.10 % constraints, respectively, on mitigating climate change through afforestation compared to land-use freedom conversion scenarios from 2020 to 2060. Thus, enhancing the incentive price of CO 2 removal, addressing the market access barrier, strengthening cooperation between global carbon markets, and exploring carbon–neutral and food multi-oriented land policies can be valuable sources of mitigation efforts over the next 40 years. [ABSTRACT FROM AUTHOR]

Planning power system (PS) towards renewable energy is crucial for reducing carbon dioxide (CO 2) emission as well as mitigating climate change. However, the inherent uncertainty and hierarchical structure of PS pose intractable challenges to the planning process. This study develops a multi-GCM-based interval bi-level programming (MIBP) method that can balance two-level decision-making conflict between CO 2 -emisison reduction and system cost minimization. MIBP can also deal with uncertainties expressed as interval values in objective functions and constraints. Then, a MIBP-PS model is formulated to plan PS for China (2021–2050), where the upper-level objective is to minimize CO 2 emission and the lower-level objective is to minimize the system cost. The major findings are: (i) the CO 2 emission for PS would reach peak value before 2030 and then reduce by [10.2, 20.4]% in 2050, which is mainly owing to the curtailment of fossil fuel; (ii) compared with the conventional model, CO 2 emission from MIBP-PS model could decrease by [3.1, 4.8]%, which shows the superiority of the developed model; (iii) the fossil-fuel power would be gradually replaced by renewable energy, and the proportion of coal-fired power would decrease by 38.8% by 2050, especially small coal-fired facilities (i.e., below 0.3 GW) should be gradually phased down. [Display omitted] [ABSTRACT FROM AUTHOR]

The ever-increasing challenges related to water security and climate mitigation underscore the pressing need for forward-thinking systems planning tools to drive urban sustainability transitions. In this study, we propose a novel city-level multi-objective planning framework that explores the nexus between carbon trading and water management, with the aim of facilitating water-efficient urban industrial restructuring. The framework integrates cap-and-trade mechanisms into a two-layered optimization model, creating an integrated approach to optimizing carbon emissions and generating economic opportunities for improving water efficiency. To illustrate the potential application of this framework, we conducted a case study focusing on Dongguan City, a water-stressed industrial metropolis in southern China. The results illustrate potential synergies between water planning strategies and carbon trading schemes, which could be harnessed to enable targeted reductions in water usage and carbon emissions. Furthermore, our findings identify the textile, apparel, and paper products manufacturing industries as primary candidates for strategic production scale reduction, emphasizing the importance of sustained support for the development of the computer and electronic manufacturing sector as a catalyst for urban sustainability transitions. By pioneering this new nexus-based perspective, our study offers valuable insights into long-term strategic planning for a low-carbon and resource-efficient urban economy. • Synergizing carbon trading and water management within a novel integrated planning framework. • Implementing resource-efficiency-driven optimization for water- and carbon-intensive manufacturing sectors. • Gaining insights into the specific roles of key manufacturing sectors in water management and carbon trading. • Introducing carbon trading systems may help in promoting water-efficient industrial restructuring. [Display omitted] [ABSTRACT FROM AUTHOR]

[Display omitted] • It analyzes the feasibility of achieving net zero emission in the Chinese power sector by 2050 and the required policy measures. • It is essential to foster the concurrent development of renewable energy, energy storage, and demand response technologies. • The carbon pricing mechanism with exponential growth is more suitable. • Referring to the European offshore wind power investment model is beneficial for the development of offshore wind power in China. The low-carbon transition in China's power sector plays a crucial role in the mitigation of climate change worldwide, and increasing renewable energy penetration rate is widely recognized as the key approach to decarbonize this sector. This paper proposes a renewable energy penetration model to examine the feasibility for net zero emission by 2050 in China's power sector taking into account of economic and social development. It also evaluates the impacts of carbon pricing and financial incentives on renewable energy penetration and carbon emissions. The results indicate that along with economic development, China's electricity demand will continue to grow, but at a gradually slowing rate. It is possible for the power sector to achieve net zero emission by 2050 while meeting this growing electricity demand, with a renewable energy penetration rate of 75%. To ensure the achievement of the goal, we recommend setting the carbon price with the current market price as the baseline and increasing it annually by a relative increment index of 10%. Furthermore, given the high initial cost and late start of offshore wind power, we suggest incorporating associated grid connection cost into the transmission and distribution price to ensure the comprehensive and healthy development of renewable energy. [ABSTRACT FROM AUTHOR]

The mitigation of climate change requires that agricultural development would proceed in accordance with green and sustainable practices. This implies that economic performance should be improved while minimizing the impact on the environment. One way to assess the underlying costs of sustainable agricultural development, and to model the relationship between the environment and the economy in general, is to use the carbon shadow price (CSP). In this paper, we utilize a by-production model within a non-parametric framework to estimate the agricultural CSP from 1997 to 2020 in 31 provinces of China. The patterns of the agricultural CSP are unveiled through kernel density analysis and convergence tests. Additionally, this paper constructs a comprehensive agricultural informatization indicator using the entropy method. We then empirically investigate its influence on agricultural CSP. The results reveal that China's agricultural CSP has demonstrated consistent growth over the past two decades which suggests serious improvement in environmental performance. Furthermore, the CSP show cross-province variation, albeit with conditional β convergence. Our empirical findings indicate that agricultural information technology contributes to an increase in CSP, thereby indicating its positive role on the green growth of agriculture in China. [ABSTRACT FROM AUTHOR]

• The Carbon sink capacity of a typical ecotypic county was precisely estimated. • STARFM was employed to estimate interannual NEP at county scale. • The NEP dataset at a 30 m grid scale from 2000 to 2020 was generated. • Spatio-temporal dynamics of NEP in ecotype county were grasped. Net ecosystem productivity (NEP) serves as a pivotal metric for quantitatively elucidating the carbon sink function of terrestrial ecosystems. As a prototype county for the development of an ecological civilization in China, the quantitative estimation of the ecotypic county's ecosystem carbon sink capacity holds immense significance in comprehending the carbon cycle and facilitating the sustainable advancement of regional ecosystems. This study undertook the estimation of NEP in Wuning County from 2000 to 2020, employing a fusion of multi-source remote sensing data, the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), the improved Carnegie-Ames-Stanford Approach model, and the soil respiration model. Furthermore, we delved into the differences in NEP across various types of land cover. In addition, we employed the Theil-Sen Median trend analysis and Mann-Kendall test to discern the spatio-temporal trends of NEP. The findings indicated the following: (1) The downscaled NDVI generated by STARFM exhibited a remarkable consistency with Landsat NDVI overall (R 2 > 0.95, P < 0.01, 0 < RMSE < 0.1). (2) The gross NEP from 2000 to 2020 in the study area ranged from 542.78 to 720 Gg C, with a multi-year average NEP of 183.84 g C m−2 yr−1. The simulated NEP demonstrated higher accuracy when compared to the measured data (R 2 = 0.79, P < 0.01). (3) The NEP exhibited a spatial pattern characterized by lower values in the central area and higher values in the north and south. Approximately 89.60 % of the total area demonstrated an increase in NEP, with woodland acting as the primary contributor, while 4.50 % of the total area displayed a decreasing trend, predominantly due to the expansion of built-up land. (4) Notable variations in NEP existed among different types of land cover. In terms of vegetation types, the annual average NEP ranked as follows: woodland > grassland > cropland. The application of STARFM has provided valuable insights into the methodology for precise delineation of spatio-temporal dynamics of NEP at the county scale. The outcomes of this study have furnished support for implementing climate change mitigation strategies in ecologically-oriented counties and the bottom-up promotion of China's carbon peaking and carbon neutrality goals. [ABSTRACT FROM AUTHOR]

• Forests show higher temperature than croplands by 0.15 ± 0.06 ℃. • Forests show higher temperature than grasslands by 0.32 ± 0.04 ℃. • Non-growing season warming effects dominate annual positive temperature response. • The biophysical effects of forest transitions vary among forest types. • Radiative processes dominate the annual net warming effect on surface temperature. Forest cover change directly affects the surface energy balance by altering the radiative and non-radiative properties of the surface. These competing processes may yield considerable biophysical impacts on local and regional climate that depend on background climate and specific forest type. Here we compared the differences in land surface temperature (LST) between temperate forests and adjacent croplands/grasslands to quantify the potential biophysical effects of transitions from croplands/grasslands to forests in Northeast China, based on multiple satellite observation products from 2001 to 2016. Forests were found to show a slight lower daytime LST and strong higher nighttime LST than adjacent croplands or grasslands. As a result, the daily LST of forests was 0.15 ± 0.06 ℃ and 0.32 ± 0.04 ℃ higher than that of croplands and grasslands, respectively. On the seasonal scale, the warming effect of cropland/grassland-to-forest transition during non-growing season outweighed the cooling effect during growing season, and dominated the annual positive LST response. Moreover, the cooling effect of cropland-to-forest transition during growing season was stronger in the early growth stage than late growth stage (−1.65 ± 0.9 ℃ in May to June, −0.39 ± 0.5 ℃ in July to September). The net cooling effect of warm temperate broadleaved forests was found to shift toward net warming effect of cold temperate coniferous forests with increasing latitude. The daytime cooling effect of forests was mainly driven by increased non-radiative evapotranspiration. Overall, the radiative process related to the solar energy dominated the net warming effect of forest transitions over Northeast China. Estimating the climate feedback potential of forests could be useful to provide theoretical references for the adaptation and mitigation strategies for climate change. [ABSTRACT FROM AUTHOR]

No-tillage (NT) can enhance the accumulation of soil organic carbon (SOC), thereby aiding in climate change mitigation and improving soil fertility. However, the relations of soil microbial abundance, composition, and necromass to SOC increase under NT are still unclear, limiting the knowledge of SOC stabilization. We performed a 5-year paddy field experiment in southern China including NT, reduced tillage (RT) and conventional tillage (CT). Soil microbial necromass C (MC, including fungal and bacterial necromass C, FC, and BC) were analyzed, as well as soil bacterial and fungal community composition. At a depth of 0–10 cm, NT increased FC (by 48.6 %–50.2 %, P < 0.05), BC (28.6 %–41.7 %), and MC (38.5 %–45.1 %, P < 0.05) but did not significantly alter the FC/BC and MC/SOC ratios. The increase rate of MC (NT vs. CT and RT) was 12.8–16.2 % higher than that of total SOC. Compared with 0–10 cm and 10–20 cm, the MC/SOC ratio was 12.5 %–14.1 % lower at 20–30 cm. Linear regression indicated significant positive correlations of SOC with MC, BC, and FC, whereas no significant correlation was found between bacterial (or fungal) α-diversity (expressed by Shannon index) and BC (or FC). The Random Forest Model showed that several important fungal and bacterial Amplicon Sequence Variants (ASVs) explained 14 %–73 % of the FC and BC variations. Therefore, the composition of the microbial community may play a pivotal role in driving the accumulation of MC. Short-term NT in rice paddies resulted in increased levels of both MC and SOC. Notably, the rate of increase in MC exceeded that of SOC, suggesting the potential for SOC stabilization. • 5-Year no-tillage increased microbial-derived C in paddy soil. • Microbial composition explained 14–73 % of microbial-derived C variation. • The SOC is positively related with fungal and bacterial necromass C. • 5-Year no-tillage did not change microbial-derived C/SOC ratio. [ABSTRACT FROM AUTHOR]

[Display omitted] • We calculated the intensity of urban air pollution islands of 2273 china's cities. • Urban air pollution island intensities reduced significantly after 2013. • The influence of economic development on it shows an environmental Kuznets curve. • Urban sprawl, polycentric development, and urban green reduce urban air pollution. • Climate mitigation-oriented pollution control policies are essential in the future. Air pollution levels tend to be higher in urban areas than in surrounding rural areas, and this air pollution has a negative effect on human health. However, the spatiotemporal patterns of urban–rural air pollution differences and the determinants of these differences remain unclear. Here, we calculate the Urban Air Pollution Island (UAPI) intensity for PM 2.5 and PM 10 on a monthly, seasonal, and annual scale for 2273 cities in China from 2000 to 2020. Subsequently, we analyze the influence of urban characteristics using a combined approach of a two-way fixed effects model and a spatial Durbin model. Results show a strong downward trend in the UAPI intensity since 2013, with reductions ranging from 42 % to 61 % until 2020, for both pollutants and in summer as well as winter. Consistently, the proportion of the cities experiencing the UAPI phenomenon decreased from 94.5 % to 77.3 % for both PM 2.5 and PM 10. We find a significant influence of urban morphology on UAPI. Specifically, urban sprawl, polycentric development, and an increase in urban green spaces are associated with a reduction in UAPI, while dense urban areas intensify it. Our study also reveals a robust inverted U-shaped relationship between stages of economic development and UAPI. Moreover, economic development and air pollution itself show spillover effects that oppose their direct impacts. These results suggest that urban and regional planning and more ambitious climate change mitigation policies could be more effective strategies for mitigating air pollution in cities than end-of-pipe control. [ABSTRACT FROM AUTHOR]

• The β of terrestrial ecosystems in China varied among ecosystem types. • The β of terrestrial ecosystems in China increased linearly with latitude. • Climate-shaped vegetation factors dominated the spatial variation in β. • Lower hydrothermal conditions limit the importance of vegetation factors to β. The Bowen ratio (β), which is the ratio of sensible heat (H) to latent heat (LE), reflects the energy balance and partitioning processes among soil, vegetation, and the atmosphere. Although the spatial patterns of β have been clearly delineated, the importance of vegetation in the spatial variation of β is frequently underestimated. Revealing the spatial patterns of β would improve the understanding of the variation in energy partitioning in terrestrial ecosystems and its reciprocal relationship with environmental change. Here, we calculated β by integrating H and LE flux values from 80 flux observation sites based on the eddy-covariance method in ChinaFLUX to analyze the spatial pattern and mechanism of β in China. Terrestrial ecosystems in China had an average β of 0.64 ± 0.47. β varied significantly among ecosystem types. Deserts had the highest β (2.08 ± 0.17), while wetlands had the lowest β (0.37 ± 0.11). The β values of terrestrial ecosystems exhibited a significant latitudinal pattern, increasing linearly with latitude. This pattern also existed in forest and cropland ecosystems. The spatial pattern of β was dominated by climate-shaped vegetation factors, including leaf area index (LAI) and fractional vegetation cover (FVC). Nevertheless, as water and thermal conditions decline, the contribution of vegetation factors gradually wanes. These findings demonstrated the spatial variations and driving mechanisms of terrestrial ecosystem β and provided insights into the mitigation of future climate change by vegetation. [ABSTRACT FROM AUTHOR]

Promoting the adoption and maintenance of low-carbon consumption behaviors (LCBs) is a global climate action. Most prior studies have considered only the adoption of LCBs and not explored how behavioral characteristics and emotions influence individual behaviors. To address these limitations, this study builds a dual-level integrated model to detect the maintenance rate of various LCBs and identify what factors affect behavioral maintenance. Using data collected from 2052 residents in China, generalized linear mixed models are employed to examine the effects of behavioral and individual-level factors and of social interaction on the maintenance of LCBs. Robustness is checked using the instrumental variable method, least-squares dummy variable method, and Probit approach. The estimated maintenance rate for different LCBs ranges between 29.02 % and 83.49 %, while the estimated cessation rate ranges between 2.31 % and 6.58 %. Maintenance of LCBs is positively affected by context stability but negatively influenced by effort expectancy. Anticipated guilt is identified as the strongest driver (positive) of maintenance of LCBs for all tested variables, followed by symbol expectancy. However, neither behavior routinization nor anticipated pride is found to be significantly associated with behavioral maintenance. The effects of anticipated guilt, effort expectancy, and symbol expectancy on behavioral maintenance are moderated by social interaction. Regarding demographics, family size is positively associated with behavioral maintenance, while females are more likely than males to maintain LCBs. These findings address the under-studied effects of behavioral characteristics and emotions on behavioral maintenance, and provide new insights for redefining target interventions to engage the public in maintaining LCBs. [Display omitted] • Maintenance of low-carbon consumption behaviors (LCBs) is studied. • A dual-level integrated model incorporating social interaction is built. • Maintenance rate of LCBs is estimated between 29.02 % and 83.49 %. • Anticipated guilt is the strongest driver (positive) of maintenance of LCBs. • Symbol expectancy and context stability contribute to maintaining of LCBs. [ABSTRACT FROM AUTHOR]

• The leaf area index (LAI) increased significantly in all climate zones of China. • Climate becomes wetter in A and SA areas, and soil becomes drier in SH and H areas. • Compared to LAI, the effect of climate on soil moisture (SM) was relatively strong. • The effect of LAI on SM was reversed with the change of vegetation greenness. • There are thresholds that switch the direction of vegetation influence on SM. Wetting and drying climate sequences and anthropogenic vegetation changes can have profound effects on the hydrological cycle and sustainability of terrestrial ecosystems. China contains many different climates, from humid to extremely arid and it contributes to the global mitigation strategies of climate change. China is also an important contributor to global greening and carbon sequestration. In view of this, we estimated the spatial and temporal variation of leaf area index (LAI), dryness/wetness index (DWI), and soil moisture (SM) in arid (A), semi-arid (SA), semi-humid (SH), and humid (H) climate zones during 1981–2018 in China and analyzed the patterns of DWI and LAI effects on SM under different vegetation greenness. The results showed a significantly increasing trend of LAI in all climatic zones, and the contribution was from highest to lowest: SH (8.17 × 10-3 m2 m−2 year−1), SA (7 × 10-3 m2 m−2 year−1), H (4.71 × 10-3 m2 m−2 year−1), and A (3.98 × 10-3 m2 m−2 year−1). The SA and A zones are becoming wetter, while the soil of SH and H zones are drying. The dry/wet climate variation plays a decisive role in soil moisture, while the role of vegetation is limited. Additionally, the LAI 3 (mean LAI from 2016 to 2018) thresholds were 0.25–0.41 and 0.84–0.86 for A and SA as a whole, respectively, as well as 0.47–0.54 and 0.93–1.18 for grassland, respectively. When vegetation exceeded this threshold, the effect of vegetation on soil moisture showed a shift from increasing to decreasing change. Overall, the results of the study provide improved understanding of the atmosphere-soil-vegetation interactions under climate change, as well as effects of vegetation restoration and water conservation efforts. [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]

Tillage practices have major impacts on soil properties, grain yield, soil carbon sequestration, and greenhouse gas emissions. Conservation tillage is an agriculture practice aiming to minimize soil disturbance and protect soil structure. It is reported that more and more croplands are being converted from conventional tillage to conservation tillage in China. However, the information is lacking as to where and when conservation tillage practice is implemented at a regional and national scale. The objectives of this study are 1) to develop a new framework for classifying tillage practices with a random forest model and Google Earth Engine platform to overcome the limitations in mapping tillage practices across China; and 2) to map the spatiotemporal patterns of tillage practices across Chinese croplands from 2016 to 2020. We generated a 1 km grid dataset for tillage practices across Chinese croplands during 2016–2020 based on Sentinel-2 imagery. First, we generated two ground reference sample pools about tillage practices based on literature review and high-resolution maps. Then, we produced Sentinel-2 features during the tillage period by composting 18 bands related to the ratios of returned crop residues. Next, we trained an optimal random forest (RF) classifier by conducting a cross-validation. Finally, we applied the optimal RF classifier to composited features to produce tillage maps from 2016 to 2020. The validation with ground reference samples shows that the classification results have an overall accuracy of 0.80. Comparisons at a provincial scale show the estimated proportion of conservation tillage is significantly correlated with statistic data with R2 being 0.88. Results show that conservation tillage practice is adopted in about 36% of Chinese croplands, mainly distributed in northeast China, northwest China, and the North China Plain. The proportion of conservation tillage ranged from 29% to 40% during 2016–2020 although with a large spatial heterogeneity. This study develops a sound framework to map tillage practices and provides more details about the spatiotemporal patterns of tillage practices, supporting regional planning of agricultural management and climate change mitigation. [ABSTRACT FROM AUTHOR]

Large-scale Photovoltaics (PV) play a pivotal role in climate change mitigation due to their cost-effective scaling potential of energy transition. Consequently, selecting locations for large-scale PV power plants has gained worldwide prominence in recent decades. Although massive studies have examined various siting criteria, land consolidation and cost-benefit feasibility issues are not often included due to the lack of a comprehensive and discretionary decision-making system. In this study, we introduced a three-stage framework combining DBSCAN clustering and cost-benefit analysis to identify the most efficient and cost-effective land parcels. The results indicate that while a total area of 425,191 km2 is considered developable for PV installation in China, only 23% of that area (128,588 km2) are consolidated land parcels which are suitable for developing large-scale PV power plants. Moreover, the potential of these consolidated land parcels (8,289,662 gWh/year) can supply about 90% of China's electricity demand. However, when considering the infrastructure investment per kWh, high-potential land parcels doubled the moderate-potential ones. These results emphasize the importance of large-scale PV plant siting as it impacts the efficiency of PV integration and the optimal land use. Hence, this methodology equips decision-makers with a practical and efficient tool for economically developing large-scale solar PV. [ABSTRACT FROM AUTHOR]

• Vegetation greening slows land surface warming in Chinese drylands. • Biogeophysical feedback of vegetation greening to climate is seasonally asymmetric. • Land use change amplifies the greening-induced cooling effects. Vegetation change can provide strong feedback to climate system, but there is a severe shortage of understanding regarding how biogeophysical (BGP) processes related to vegetation changes and their impact on local temperature in arid and semi-arid regions of China (ASAC), a unique region where large-scale ecological engineering projects have been implemented. To address this knowledge gap, this study is aims to investigate the BGP effects of vegetation changes (including growth change and type conversion) and elucidate the BGP mechanisms that link vegetation and surface temperature (T s) through integrating the Intrinsic Biophysical Mechanism (IBM) method and pairwise comparison analysis. The findings reveal that vegetation change slows down climate warming rate of T s in ASAC, with a cooling magnitude of -0.0096 K/year (Non-radiative forcing: -0.0114 K/year; Radiative forcing: 0.0018 K/year) from 2000 to 2018, embodied as cooling in summer-autumn and warming in winter-spring. Vegetation-induced BGP effects in ASAC are dominated by non-radiative mechanisms. During the study period, compared to the stable land use/land cover (LULC), cropland expansion and grassland restoration usually led to cooling exceeding -0.05 K and -0.01 K, respectively. However, afforestation and urbanization generally cause warming about 0.02 K and 0.04 K, respectively. From a BGP point of view, avoiding large-scale afforestation in extremely arid regions is an effective strategy. This study highlights the importance of land use/ land cover change (LULCC) in regulating regional climates, and emphasizes the necessity of fully considering the multiple effects of LULCC in the formulation or evaluation of climate change mitigation policies. [ABSTRACT FROM AUTHOR]

The efficient and effective new energy vehicles (NEVs) power batteries recycling (PBR) plays a critical role in reusing scared metal resources, decarbonizing the transport sector and climate warming mitigation. The policy consistency from up to down in a big country lays a solid foundation for sustainable recycling. However, quantitative comparison or evaluation of power batteries recycling policies (PBRPs) from various levels of government is insufficient in the existing literature. In this paper, text mining technology and the Policy Modelling Consistency Index (PMC-Index) model are used to evaluate the longitudinal and horizontal consistency level of China's 13 central PBRPs as well as 25 local PBRPs from 2016 to 2022. The findings demonstrated that: (1) Longitudinally, the local governments present a high consistency level with the central government in the objective and content of PBRPs via comparison analysis of high-frequency words, which embodies the local governments firmly advocating the national strategy for retired battery recycling. (2) Horizontally, the number of central PBRPs with excellent and good consistency is five and seven, respectively, while the number of local PBRPs with excellent and good consistency is six and seven, respectively. One central and twelve local PBRPs are of acceptable consistency, indicating significant disparity in local governments' policymaking ability. (3)The drawbacks of those acceptable policies attribute to the policy tendency of traceability management, policy timeliness, policy content in terms of incentives and business recycling model. Finally, management implications were summarized to optimize China's PBRPs system and PBR performance based on the empirical result, an overview of PBRPs and recycling practices in developed countries. [Display omitted] • We evaluate the China's central and local power batteries recycling policies. • The PMC-Index model is used to quantitative analysis of policy consistency. • The longitudinal and horizontal consistency of battery recycling policies is good. • We outline the power battery recycling policies and practice in the EU and the U.S. • Carbon footprint requirements should be added in China's battery recycling polices. [ABSTRACT FROM AUTHOR]

Micro-level concerns about climate change can not only affect individual low-carbon behaviors but also exert intense pressure on carbon emission reduction strategies and policy design. However, whether public concern about climate change can affect per capita carbon emission is still unclear. Based on panel data from 30 provinces in China and 188,943 climate change-related blogs from 2012 to 2019, this research investigates the impact of public concern on per capita carbon emissions. Results show that, in general, public concern about climate change has a significant negative impact on per capita carbon emissions in China, indicating that climate crisis awareness has a supervisory effect on greenhouse gas emissions. Nevertheless, the effects of different public concerns on per capita carbon emissions are different, with the topics of "low-carbon appeal" and "concern for future" have significant positive impacts on per capita carbon emissions, while the topics of "carbon governance performance" and "climate change mitigation strategies" have significant negative impacts on per capita carbon emissions. The findings yield new opportunities to delve into the relationship between the externality of people's will and governmental behaviors and provide in-depth insights for decision-makers to develop tailor-made solutions towards carbon reduction and sustainable development. [Display omitted] [ABSTRACT FROM AUTHOR]

As a key component in mitigating global warming and achieving sustainable development strategies, wind power has received widespread attention and support from governments around the world. Numerous countries are engineering ambitious programs to map and project the mitigation potential of wind energy expansion to combat future global warming. Here, using the global installed wind capacity data, we identity that a total of 837 GW of wind energy installed capacity (WEIC) in 31 countries generated about 2186 TWh of electricity, that is 1311 Mt of CO 2 mitigation, in 2021. Considering power mix transformation, wind power could account for more than 30% of total global electricity generation by the mid-21st century, when many countries expect to realize carbon neutrality, and could reduce CO 2 emission up to 14871 Mt by 2050 and 32864 Mt by 2100. Meanwhile, the global phenomenon of the future southward shift of wind energy resources makes the wind energy development in low-latitude countries, such as Brazil, Vietnam, and Central African, more confident. Combined with the Shared Socio-economic Pathways (SSPs), we find that the mitigation benefits of wind energy expansion are significant and will directly reduce global warming by up to 0.64 °C by the end of the century (NZE deployment scenario, SSP3-7.0). For China and the United States, the share of renewable energy will reach 78% and 84% by 2050 (APS scenario) and the cumulative climate mitigation by wind power will be 0.12 °C and 0.11 °C during 2020–2100, respectively. The findings strongly support the development and practice of global climate mitigation energy solutions. • This study quantifies wind energy's impact on CO 2 and temperatures reduction. • Global wind energy can currently mitigate 1311 Mt CO 2 , up to 32864 Mt by 2100. • Wind energy expansion could mitigate global warming by up to 0.64 °C in 2100. • China and the U.S. lead global CO 2 reductions in wind power. [ABSTRACT FROM AUTHOR]

Climate change is related to human well-being and the health of the planet. Education is a critical component of global action to mitigate climate change, and young people are future citizens in the fight against climate change. This article discusses the factors that affect adolescents' willingness to continue participating in climate change governance actions. First, based on an expansion of the Theory of Planned Behavior (TPB), the article conducts partial least square-structural equation modeling (PLS-SEM) analysis on the data collected before adolescents participate in climate change education courses and clarifies the factors that significantly impact adolescents' behavioral willingness to participate in climate change governance actions. The results showed that emotions (EMO, β = 0.323) had the most significant effect on the willingness to engage in social good (SG) behaviors, followed by attitudes toward environmental protection (ATEP, β = 0.198) and pro-natural emotion (PNE, β = 0.123). Secondly, the researchers devised an exploratory climate change education curriculum and validated its efficacy through empirical research. The single group comparison of before and after lessons results shows that the exploratory climate change education curriculum can improve the scores of the nine measured factors. Higher effect sizes for attitudes toward environmental protection, confidence in protecting the environment, and pro-natural emotion. This study provides a reference theoretical framework and curriculum model for developing climate change education courses. Effective climate change education courses are crucial in improving youth climate literacy and guiding them to respond scientifically to climate change. [Display omitted] • Expand TPB and evaluate the factors that affect adolescents' willingness to participate in climate change behaviors. • The regional dimension difference analysis is carried out on Chinese adolescents' perception of climate change. • It has provided an effective educational model for advancing climate change education in developing countries. [ABSTRACT FROM AUTHOR]

• A high-resolution integrated assessment framework for estimating future watershed ecosystem services was proposed under the latest SSP-RCP scenarios; • The spatial–temporal dynamics on water-related ESs of the PRB were projected under the SSP-RCP scenarios; • The main driving factors affecting the spatial–temporal heterogeneity of water-related ESs of the PRB were identified under the SSP-RCP scenarios. The projection of future ecosystem service (ES) dynamics under SSP-RCP scenarios would be beneficial for the development of effective climate mitigation strategies for policymakers. However, current projection frameworks generally neglect the downscaling of high-resolution climate and land use data, leading to uncertainties in the simulation of ESs under the SSP-RCP scenarios. To address this issue, this study proposes an integrated analysis framework to downscale climate and land use data. We first identified areas of high risk in terms of inadequate water-related ESs in the Pearl River Basin (PRB) of China. Subsequently, we analyzed key socio-environmental factors driving the dynamics of water-related ESs under future SSP-RCP scenarios. The results indicate that 1) water-related ESs in the PRB are expected to show an overall increasing trend, 2) the sub-watersheds located in the downstream is at a higher risk of experiencing insufficient supply capacity for water-related ESs, and 3) under the coupling effects of climate change, land use change, and socio-economic development, drastic changes in future land use are expected to have a stronger impact on watershed ESs than the climate (i.e., global warming). Our work provides valuable insights for policymakers and managers regarding future water and land resource planning. The proposed framework can be integrated with other hydrological or land surface models to project the spatial–temporal evolution characteristics of future watershed ESs with finer temporal resolution. [ABSTRACT FROM AUTHOR]

[Display omitted] • Modeled changes in GPP in China over the last 40 years. • Discovered an increase in GPP with a near 3-years periodic oscillation. • A recent 20 years accelerated increasing rate than that of previous 20 years. • Minimum temperature was found as the dominant factor for accelerated growth. Vegetation response to climate change can be characterized as long-term trends, but with periodic oscillations. Revealing vegetation response trends, with oscillations, is essential for formulating climate change mitigation and adaptation planning, as well as adopting ecological protection and restoration measures. Here, the long-term trend and periodic oscillations in vegetation changes were explored through a measure of gross primary production (GPP), an indicator of vegetation photosynthesis, using data of both high spatial resolution (1 km2) and a long-term of nearly 4 decades, from 1980 to 2018. The GPP data were estimated for China's terrestrial ecosystem and validated against the eddy covariance-based observations of 70 site-year in China and compared to other GPP data products. The results showed the estimated GPP can explain 76% of spatial–temporal variance with the same data accuracy as other products, but with the advantage of both high spatial resolution and long time periods that other products do not have. From the estimated GPP data, Chinese terrestrial vegetation growth was found to have a periodic oscillation of close to 2.79 years and a long-term increasing trend of 59.8 Mt C per year over 92% of all vegetated land in China from 1980 to 2018. Moreover, it was found that vegetation growth accelerated significantly in the two recent decades over the previous two decades. The growth rate was 83.5 Mt C a−1 from 2000 to 2018, which was 2.31 times faster than the rate from 1980 to 2000. The underlying mechanism of the vegetation responses was analyzed by ridge regression, a method to decrease the effects of multicollinearity. Long-term variability and trends in vegetation could be attributed to a warming minimum air temperature when examined with precipitation, maximum air temperature, and solar shortwave radiation. Though more influences, such as those from freezing and thawing and human activities, should be explored in the future, this study offers insight that warming, with increasing daily minimum temperatures, is likely to be a vital contributor to ecosystem changes, and will be essential knowledge for mitigation of effects and adaptation to future climate. [ABSTRACT FROM AUTHOR]

Under the background of "carbon peak" and "carbon neutrality", China's cities are at the heart of climate change mitigation. To fulfill the commitments, the potential drivers of China's low-carbon economy at the city level should be explored. Thus, this study estimated the quality of low-carbon economy from the perspectives of carbon emissions and sequestration. Subsequently, spatial econometric approach was adopted to analyze the direct and spatial spillover effects of drivers on low-carbon economy. Moreover, to explore more potential variables, this study combined machine learning algorithms with different weight matrices to assess the importance scores of neighbouring cities' potential variables. The results show that (1) GDP per capita, emissions reduction technological progress, terrestrial vegetation's net primary productivity and the ratio of forest land cover improved cities' low-carbon economy; (2) land urbanization reduced nearby cities' low-carbon economy (especially those with high human footprint index at the inter-city border), which was caused by its negative spatial spillover effects on forest net primary production; (3) based on importance analysis, this study found that the characteristics of different sectors (e.g., the ratio of labor to fixed capital stocks, employment and fixed asset investment expenditure) also significantly influenced nearby cities' low-carbon economy. • China's city-level quality of low-carbon economy (reo) was estimated based on carbon intensity and sequestration. • The importance of 72 variables' spatial spillover effects were ranked based on machine learning algorithms. • Terrestrial vegetation's net primary productivity and the ratio of forest land cover greatly improved the reo. • The spatial spillover effect of land urbanization was negative in nearby cities. [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]

Coastal salt marshes suffering from anthropogenic coastal development and sea level rise have attracted much attention because of their capacity for carbon sequestration and global climate change mitigation. Accurate mapping of coastal salt marshes is always the first step for their protection, management, and restoration. The inherent complexities of vegetation, dynamics of tides, and anthropogenic disturbances pose challenges for remote sensing-based approaches. Existing studies have utilized phenology information and various black-box algorithms to reduce misclassifications. However, the approaches with dual-temporal images containing phenology information have suffered from inefficiency; the misclassifications have been objectively post-processed rather than considered in the method design, and the tacit knowledge of the trained black-box models has not been revealed. To address the above issues, we proposed a new approach with solid improvements in dual-temporal image construction, misclassification processing, and tacit knowledge analysis, including an efficient method to synthesize dual-temporal images based on the common divisor of the green-up season or senescence season resulting from latitudinal gradients in narrow coastal areas of China, a detailed classification scheme by interpretation of iteratively collected samples, and a key decision rule approximating the trained model. We applied the approach to Sentinel-1/2 images and DEM data, thus deriving a 10-m resolution coastal salt marsh map of China with an overall accuracy of 92.5%. A qualitative comparison showed that the map produced in this study was fitted well with actual salt marsh distributions, resulting in improved accuracy when compared to recently generated maps. The most important contribution is that the overall nature of the trained model observed from the training samples was approximated by a four-feature decision rule following the principle of explainable artificial intelligence, i.e., B8 senescence /B4 senescence < 2.06 & B4 green /B8 green < 0.78 & B12 green /B11 green < 0.72 & elevation < 2.13 , and thus established a new potential classification mechanism for dual-temporal black-box algorithms, i.e., the water signal was covered up by flourishing vegetation, but the situation changed when vegetation withered. This study not only generates an accurate coastal salt marsh map at a national scale but also provides a classification mechanism for dual-temporal image-based coastal salt marsh identification and mapping. • Developed an efficient method for constructing senescence and green images. • Established a mechanism for dual-temporal image-based coastal salt marsh mapping. • Provided a coastal salt marsh map with solid improvements on the most recent one. • Explored a case of explainable artificial intelligence (XAI) in the coastal. [ABSTRACT FROM AUTHOR]

The contribution of municipal solid waste incineration (MSWI) to anthropogenic mercury and CO 2 emissions have become increasingly important over the past decade. This study developed an inventory of anthropogenic mercury emissions and CO 2 emissions during the period of 2014–2020, of MSWI process in China using a bottom-up inventory at the plant level. Overall, national MSWI anthropogenic mercury emissions increased from 2014 to 2020 by province. It was estimated that total 8321.09 kg of anthropogenic mercury emissions from 548 MSWI plants were scattered in 31 provinces of mainland China in 2020. The average intensity of mercury emission in China was 0.06 g·t−1 in 2020, which was much lower than the pre-2010 level. Furthermore, the increased CO 2 emission generated by MSWI from 2014 to 2020 is 1.97 times. Anthropogenic mercury emissions and CO 2 emissions were concentrated mainly in developed coastal provinces and cities. The general uncertainty of national mercury emissions and CO 2 emissions was estimated to be −123% to 323% and −130% to 335%, respectively. Furthermore, future emissions were predicted from 2030 to 2060 based on different scenarios of the independent and collaborative effects of control proposals, the results indicate that the enhancement of advanced air pollution control technologies and effective management of MSWI represent pivotal factors in realizing future reductions in CO 2 and mercury emissions. The findings will supplement those for mercury and CO 2 emissions, and be useful for relevant policy-making and to improve urban air quality, as well as human health. [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]

[Display omitted] • SOC storage and stability increased with vegetation restoration and succession. • Macroaggregates play an important role in SOC storage and stability. • Coniferous forests are more conducive to soil carbon fixation. Soil organic carbon (SOC) plays the most significant role in climate change mitigation and ecosystem productivity. However, dynamic changes in the storage and stability of SOC during vegetation restoration and succession, especially the physical protection role of soil aggregates, are not well understood. This study, therefore, explored the variations in SOC storage and stability along with vegetation restoration by combining the physical protection of soil aggregates with the chemical structural stability of organic carbon (OC). OC fractions and carbon functional groups of bulk soil and soil aggregates were investigated using soil samples collected from abandoned farmland, grassland, miscellaneous shrubland, pioneer arbor forest, and coniferous forest plots representing typical vegetation restoration consequence on the Loess Plateau of China. Vegetation restoration enhanced clumps of clay particles with visible pores and cementing substances. The contents of OC fractions (total, inert, and active carbons) in bulk soil and aggregates significantly increased during vegetation restoration process. Total and active OC in macroaggregates (>0.25 mm) were significantly higher than those in other aggregate fractions, while inert OC had no significant difference among different aggregate fractions. The elevated absorption intensity, i.e., absolute content of OC functional groups, especially stable OC functional groups, enhanced SOC chemical stability during vegetation restoration. From the abandoned farmland to miscellaneous shrubland, the relative content of active OC functional groups significantly increased and was primarily distributed in macroaggregates (84.94–86.32%), while silt–clay aggregates (<0.053 mm) had higher relative content of stable functional groups (21.84–26.53%). A significant increase was observed in the relative content of the stable functional group from miscellaneous shrubland to pioneer arbor forest, primarily in silt–clay aggregates (∼27.15%). In the coniferous forest, stable functional groups mainly distributed in macroaggregates also showed the most pronounced increase (∼36.15%). We concluded that vegetation restoration improves the soil structure and storage and stability of SOC due to the increased accumulation of OC in macroaggregates and enhanced chemical stability of OC in silt–clay aggregates from the abandoned farmland to the pioneer arbor forest. However, SOC stability in the coniferous forest is significantly influenced by macroaggregates in the soil. [ABSTRACT FROM AUTHOR]

Understanding future climate change is crucial for securing and managing water supplies necessary for agricultural activities in China, particularly in rainfed agriculture regions. This paper evaluates the projected climate change for nine major agricultural zones in China, using ensembles of regional climate models (RCMs) simulated under the Coordinated Regional Downscaling Experiment-East Asia second phase (CORDEX-EA-II) framework. The simulations were conducted for two climate scenarios (RCP2.6 and RCP8.5) at a 25 km grid spacing, with three RCMs (RegCM4, REMO, and WRF) driven by multiple CMIP5 global climate models (GCMs). The study compares the RCM simulations to the driving CMIP5 and the recent CMIP6 ensembles, focusing on surface temperature, precipitation, and surface relative humidity for the present day (1981–2010), mid-future (2036–2065), and far future (2070–2099) periods. The model evaluations indicate that the GCM and RCM simulations are consistent with observations, with RCMs showing better performance than the driving GCMs. The results show that both GCMs and RCMs project increased temperature and precipitation in most agricultural zones of China in the future, with the CMIP6 ensembles projecting the largest temperature increase and the CORDEX-EA-II ensemble showing the finest spatial details. Relative humidity is projected to decrease over major rice-producing areas of South China in the CORDEX-EA-II, CMIP5, and CMIP6 ensembles. This study provides valuable information to support climate change adaptation and mitigation efforts in China, particularly in the agricultural sectors. • CORDEX-EA-II simulations demonstrate better model performance over China. • Temperature and precipitation are projected to increase in the future. • Relative humidity is projected to decrease over South China. [ABSTRACT FROM AUTHOR]

[Display omitted] • SOC stocks of VCEs were estimated and projected at a 10 m spatial resolution. • Climate and soil salinity are critical for estimating SOC stocks in the VCEs. • Warming would decrease SOC stocks of VCEs by enhancing SOC decomposition. • Increasing precipitation would increase SOC stocks by reducing soil salinity. • SOC stocks of VCEs in the Bohai Rim could reduce ∼ 12 % − 19 % between 2041 and 2100. Vegetated coastal ecosystems (VCEs) have much higher organic carbon sequestration rates and storage capacities than most other earth surface ecosystems, and thus play a vital role in blue carbon sequestration for climate change mitigation. However, soil organic carbon (SOC) stock assessment in VCEs at a large regional-scale remain problematic, and the controlling mechanisms for SOC remain poorly understood. Here, we estimated current and future SOC stocks of VCEs in the Bohai Rim Region, China at a spatial resolution of 10 m, using a data-driven method based on multi-source data; and investigated the key environmental and anthropogenic controls. The total SOC stocks and SOC density of VCEs in the Bohai Rim Region were estimated to be approximately 62.7 Tg carbon and about 68.8 Mg ha−1, respectively (in the upper 1 m of soil). We found that climate and soil salinity are the most critical environmental controls of SOC stocks within VCEs in the region. Increasing temperature and soil salinity would increase SOC decomposition and decrease plant productivity, resulting in a decrease in SOC stocks. Conversely, increasing precipitation would increase SOC stocks by reducing soil salinity. We projected that the potential losses of SOC stocks due to the combined effects of climate changes, sea-level rise, and anthropogenic disturbances would be ∼ 12.2 % between 2041 and 2060 under two Shared Socioeconomic Pathway (SSP) scenarios (SSP245 and SSP585), extending to 19.3 % between 2081 and 2100. The decreases in SOC stocks would occur mainly in the higher latitude and colder regions. The study demonstrated the potential significant reduction in SOC stocks in coastal ecosystems and provided an important framework for better understanding the blue carbon ecosystems. [ABSTRACT FROM AUTHOR]

Heatwaves have significant adverse effects on human health. The frequency, duration, and intensity of heatwaves are projected to increase dramatically, in the context of global warming. However, there are few comprehensive assessments of the health impact of heatwaves considering different definitions, and their characteristics under climate change scenarios. We aimed to compare future excess mortality related to heatwaves among different definitions under climate change, population, and adaptation scenarios in China and further explore the mortality burden associated with heatwave characteristics. Daily data during 2010–2019 were collected in Guangzhou, China. We adopted nine common heatwave definitions and applied quasi-Poisson models to estimate the effects of heatwaves and their characteristics' impact on mortality. We then projected the excess mortality associated with heatwaves and their characteristics concerning climate change, population, and adaptation scenarios. The relative risks of the nine common heatwave definitions ranged from 1.05 (95% CI: 1.01, 1.10) to 1.24 (95% CI: 1.13, 1.35). Heatwave-related excess mortality will consistently increase in the future decades considering multiple heatwave definitions, with more rapidly increasing rates under the Shared Socioeconomic Path5-8.5 and non-adaptability scenarios. Regarding heatwave characteristics, the intensity is the main factor involved in the threat of heatwaves. The increasing trend of characteristic-related mortality burden is similar to that of heatwaves, and the mortality burden caused by the duration of the heatwaves was the largest among all characteristics. This study provides a comprehensive picture of the impact of heatwaves and their characteristics on public health under various climate change scenarios, population changes, and adaptive assumptions. The results may provide important public health implications for policymakers in planning climate change adaptation and mitigation policies, and implementing specific plans. [ABSTRACT FROM AUTHOR]

[Display omitted] • Global land-use impacts of China's bioenergy import schemes were explored. • Major sustainability concerns arise when relying on any single market for biomass import. • Economically optimized biomass import can partly mitigate sustainability tradeoffs. Most ambitious climate change mitigation pathways indicate multifold bioenergy expansion to support the energy transition, which may trigger increased biomass imports from major bioenergy-consuming regions. However, the potential global land-use change and sustainability trade-offs alongside the bioenergy trade remain poorly understood. Here, we apply the Global Biosphere Management Model (GLOBIOM) to investigate and compare the effects of different increasing bioenergy import strategies in line with the 1.5℃-compatible bioenergy demand in China, which is projected to represent 30% of global bioenergy consumption by the middle of the century. The results show that sourcing additional bioenergy from different world regions could pose heterogeneous impacts on the local and global land systems, with implications on food security, greenhouse gas emissions, and water and fertilizer demand. In the worst cases under strict trade settings, relying on biomass import may induce up to 25% of unmanaged forests converted to managed ones in the supplying regions, while in an open trade environment, increasing bioenergy imports would drastically change the trade flows of staple agricultural or forestry products, which would further bring secondary land-use changes in other world regions. Nevertheless, an economically optimized biomass import portfolio for China has the potential to reduce global overall sustainability trade-offs with food security and emission abatement. However, these benefits vary with indicator and time and are conditional on stricter land-use regulations. Our findings thus shed new light on the design of bioenergy trade strategies and the associated land-use regulations in individual countries in the era of deep decarbonization. [ABSTRACT FROM AUTHOR]

While feeding 20% of global population, China's agriculture is a large greenhouse gas (GHG) emitter, posing a major challenge to the country's carbon neutrality target. However, the pathways of agriculture towards carbon neutrality remain unclear. To address this knowledge gap, we conduct a comprehensive life-cycle assessment and show that valorization of sustainable biomass wastes (crop residues, forest residues, livestock manure, food waste, and sewage sludge) into biochar can contribute importantly towards agricultural carbon neutrality in China. The maximum potential of biochar production from these waste resources in 2018 is 145 Mt yr−1 with a corresponding GHG mitigation potential of 455.7 (405.5–572.4) Mt CO 2 -eq yr−1. This can fully offset the total CH 4 and N 2 O emissions from China's croplands (∼400 Mt CO 2 -eq yr−1), which are difficult to be entirely eliminated due to rice paddy irrigation and intensive use of fertilizers. Distribution of biomass waste varies across regions, and at the national level , crop residues (48.8%) and livestock manure (25.4%) and food waste (15.6%) are the main sources of biochar feedstocks and should be prioritized in biochar development. Forest residues have a marginal contribution due to competing uses from other sectors, and sewage sludge derived biochar is a net source of GHG emissions due to the large energy consumption required for sludge drying. The total GHG mitigation potential of biochar is greatly affected by pyrolysis temperature and the highest mitigation effect is observed under 300–500 °C. These results underscore the benefit of sustainable biochar production to agricultural carbon neutrality, and to maximize the climate benefit requires differential policies and pyrolysis technologies tailored to regional availability of biomass resources. • The GHG mitigation potential of sustainable biochar in China was analyzed. • The maximum mitigation potential can offset all CH 4 and N 2 O emission from croplands. • Biochar GHG mitigation potential is affected significantly by pyrolysis temperature. • Sustainable biochar can contribute toward agricultural carbon neutrality. [ABSTRACT FROM AUTHOR]

Macroalgae aquaculture faces grand challenges from extreme temperature events in the context of global warming. For mapping aquaculture areas and assessing potential risks, it is urgent to evaluate the thermal sensitivity of commercially and ecologically important macroalgae. In the present study, thermal tolerance of commercial macroalgae species in China and sea surface temperature (SST) under current conditions and three Shared Socioeconomic Pathways (SSP1–2.6, SSP3–7.0, SSP5–8.5) scenarios in 2050 were collected for calculating thermal safety margin (TSM), an index of thermal sensitivity, for each species in the aquaculture area. Our results indicated that a few species were particularly sensitive to current conditions, and the kelp Saccharina japonica and Ulva pertusa were the most sensitive species to heat and cold stress, respectively. As indicated by the regional thermal sensitivity (RTS) (i.e., the mean of TSMs for all species in each grid cell), the commercial macroalgae located in southern China (20–25°N) were more sensitive to heat stress, while the commercial macroalgae located in the regions of 27–40°N was more sensitive to cold stress. Commercial macroalgae nearby the Yangtze River Estuary (~30°N) were sensitive to both heat and cold stress. Under the three SSP scenarios, macroalgae aquaculture would be more sensitive to heat stress, and the impacts from cold stress would relatively weaken in 2050. Our findings provide crucial information for the management of macroalgae aquaculture and for climate change mitigation and adaptation in China. • Species-specific and region-specific thermal sensitivity of macroalgae aquaculture in China were evaluated. • The impacts of heat stress will increase while cold stress will decrease in the future in the face of climate change. • Macroalgae farming potentially is running out of traditional geographies. • Effective adaptation and mitigation efforts are urgent for the sustainable development of macroalgae aquaculture. [ABSTRACT FROM AUTHOR]

Clean vehicle fleet will greatly benefit air quality and climate change mitigation. Here, we employ an integrated model to systematically investigated the contribution of combined clean vehicle policies to "emissions, exposure, and health benefits" from a regional perspective 2019–2035 in China. We find that driven by clean vehicle polices, the national vehicle CO 2 will likely to peak around 2028 with about 1327 million tons, and then reduce by 7.8% from 2028 to 2035. The developed region will peak CO 2 before 2030, while the developing region probably peak after 2030. In general, most air pollutants emissions from vehicles will decrease, subsequently leading to obvious PM 2.5 and O 3 exposure decrease. About 68 thousand PM 2.5 related and 33 thousand O 3 related deaths will be avoided 2019–2035 nationwide. Note that the health benefits are unequal, with higher PM 2.5 -O 3 related excess deaths be avoided per 100000 in developed region than developing region. Besides, results show that emission standard upgrade contributes largest to emission reduction and related health benefits, followed by electric vehicles, road-to-railways and waterways, and fuel consumption regulation in general. This work is able to provide valuable information for policy makers to collaboratively reduce CO 2 , air pollutants and premature deaths in China and other developing countries. [Display omitted] • Emissions in CO 2 and air pollutants were both investigated based on a dataset with 27 vehicle categories from 338 cities. • The contribution of vehicle clean policies to abated PM 2.5 -O 3 exposure and related deaths was quantified and decomposed. • This work proposed region-specific clean vehicle pathways from a national and regional perspective 2019-2035. [ABSTRACT FROM AUTHOR]

• Tree species diversity decreased standing biomass C stock via the dominant tree biomass C stock. • Tree species diversity enhanced the C and N stocks in stand litter mainly via affecting the proportion of conifer. • Tree species diversity enhanced the soil organic C and N stocks via increasing their stable factions. • Tree species diversity can elevate the stabilities of soil organic C and N stocks in the secondary forests. Carbon (C) and nitrogen (N) stocks are important for food security and mitigation of climate change, also could be likely affected by tree diversity. However, a detailed evaluation of the relationships between tree species diversity and stand biomass C (AGC), and the C and N stocks of stand litter and soil is still scant, especially in secondary forests. Thus, we assessed the associations between tree species diversity (i.e., Shannon-Wiener index) and the AGC stock, the C and N stocks in stand litter and soil [soil organic carbon (SOC), N, microbial biomass fractions (MBC and MBN), heavy fractions (HFOC and HFON) and mineral associated factions (MAOC and MAON)] at the plot level (25 m × 25 m) in mature secondary forests in subtropical China. We also used the structural equation model (SEM) to explore the underlying mechnism by which tree diversity drives the AGC stock and the C and N stocks in stand litter and soil. We found that the tree species diversity decreased AGC stock via the dominant tree biomass C stock. However, the tree species diversity enhanced the C and N stocks in stand litter mainly via affecting conifer proportion, and the SOC and N stocks at the depth of 0–40 cm via increasing their stable factions (i.e., heavy fractions and mineral associated factions). We also observed the tree species diversity had positive effects on the stocks of MBC, HFOC and HFON in soil epipedon, and had non-significant effects on the stocks of MBN, MAOC and MAON. Our results revealed that tree species diversity can elevate the soil C and N stocks and their stability in the subtropical secondary forests of China. [ABSTRACT FROM AUTHOR]

Middle-class expansion has played a crucial role in driving the changes in embodied carbon emissions. However, its driving mechanisms still need to be clarified. In this paper, we compiled novel multiregional input-output tables to capture the rise of the middle class in China in terms of its expansion and consumption pattern changes. Structural path analysis was employed to investigate the critical paths of embodied carbon emissions from middle classes of different regions in China during 2012–2015. Structural path decomposition was further used to explore the driving factors along the paths, including changes in population size, consumption patterns, industrial structure, and carbon intensity. Our results show that, from 2012 to 2015, the role of the middle class in driving carbon emissions through the most critical paths was either enhanced or reduced depending on different factorial changes. Generally, the paths with enhanced roles of the middle class stemmed from the urban and rural middle classes in Central China, Southwestern Coastal, and Northern Coastal regions, and the changes in consumption patterns and population of the urban middle class were the main driving factors. The top 30 paths of carbon emissions growth driven by the urban and rural middle classes approximately increase 19.5 Mt and 8 Mt of carbon emissions, respectively. In contrast, most of the paths with the weakened role of the middle class were intraregional paths in the Southern Coastal and Eastern Coastal regions, and carbon intensity was the dominant factor governing the changes. Our analysis systematically revealed, for the first time, the heterogeneous impacts and driving factors of middle-class expansion in different regions of China on carbon emissions. Therefore, it provides new insights for climate mitigation in the context of China's plan to cultivate a majority middle-class society. • New multiregional input-output tables are compiled for the rise of the middle class in China. • Middle-class expansion has heterogeneous effects on regional carbon emissions. • Urban and rural middle class lead to an incease of 19.5 and 8 Mt CO2 for top 30 paths, respectively. • Four driving factors play different roles in supply chains affecting carbon emissions. • Consumption patterns and urban middle-class size changes were the main driving factors. [ABSTRACT FROM AUTHOR]

[Display omitted] • A framework for quantifying the effects of wetlands on hydrological droughts is proposed. • Wetland effects on drought characteristics and propagation of meteorological to hydrological droughts were determined using a hydrological modeling platform. • Wetlands can mitigate the development process, accelerate the recovery, shorten the duration and alleviate the severity of hydrological droughts. • Wetlands can extend the propagation time and weaken the transition from meteorological to hydrological drought. Wetlands have been singled out as a potential nature-based solution for improving the resilience and reducing the risks of hydrometeorological extremes. However, whether and to what extent wetlands can affect hydrological droughts is not well understood. To fill this gap, we proposed a general framework to discern the effect of wetlands on: (i) the characteristics (duration, severity, development and recovery processes) of hydrological droughts, and (ii) the propagation of meteorological droughts to hydrological droughts. First, hydrological modeling was conducted with a spatially-explicit model integrated with wetland modules. Then, the run theory and pooling method were selected to recognize hydrological drought events and identify their characteristics. Further, the Pearson correlation coefficient, temporal shift method and cross wavelet transform were used to explore the propagation processes. Finally, the characteristics and propagation processes were compared to quantify wetland mitigation services on hydrological droughts. To validate the proposed framework, two river basins from China and Canada (the Gan River Bain and the Nelson River Bain), with distinct land cover, were chosen to perform hydrological modeling and quantify wetland effects. The results indicate that wetlands mainly contribute to alleviating hydrological droughts by decelerating the development process, accelerating the recovery, shortening the duration, and reducing the severity of the hydrological drought events. However, the effects are variable as they may have weak impacts and even worsen drought conditions. Wetlands can extend drought propagation time and weaken the transition of meteorological to hydrological droughts. The likelihood of hydrological drought formation due to meteorological decreased by 19% and 18% respectively, for the Gan River Bain and Nelson River Bain, thanks to the mitigation services of wetlands. These findings highlight the drought-mitigation roles of wetlands and the proposed modelling framework has the potential to be useful in beneficial in assisting basin management on drought risks in the context of climate change mitigation. [ABSTRACT FROM AUTHOR]

In an effort to contribute to climate change mitigation, China has committed to achieving its peak carbon by 2030 and carbon neutrality by 2060. However, reaching these goals will require a massive reduction in carbon emissions. The humans have to consume food to meet their survival needs. Furthermore, the society's demand for food is consistent with the development level of agricultural structures. At present, reducing environmental costs associated with food to adjust the agricultural structure has not received sufficient scientific attention. Because of this, the present study combines food consumption, climate change, and agricultural structure to design future scenarios based on the widely used SSP storyline. Moreover, in order for China to reach its carbon peak in 2030, this study applies a life-cycle approach to uncover the potential carbon reduction of Chinese residents under different dietary structures. From a demand perspective, this study puts forward recommendations for dietary restructuring and guides the direction of future agricultural restructuring in China. It also shows that a diet structure that replaces red meat with plant foods such as vegetables and fruits will have a more significant carbon reduction potential. The traditional agricultural structure consumes a large amount of food and produces a significant amount of greenhouse gases. Reducing meat and high-fat foods consumption may help reduce GHG emissions produced by food consumption. In addition, reducing the proportion of food used for feeding in the agricultural structure will also help achieve peak carbon targets. The shift in diet structure will advance China's agricultural structure and promote green agriculture development. • Food consumption and related carbon emissions within the 2030 scenario will continue to increase, with the highest share of rice consumption. • The carbon emissions of food consumption in the environmentally sustainable scenario will decrease. • Readjusting toward a more balanced diet could significantly contribute to the carbon peak goal. • A shift in dietary structure will promote agricultural restructuring. [ABSTRACT FROM AUTHOR]

Urban parks are considered as an effective, sustainable, and affordable heat mitigation strategy. At present, there is a lack of understanding of the carbon saving potential of urban parks in the context of urban warming. Here we provide a simple approach to estimate the potential carbon savings due to heat mitigation based on analysis of 1510 parks in 26 major urban areas of the years 2017–2021 within the Yangtze River Economic Belt (YREB), China's largest sustainability experiment. On average, an urban park with 26.9 ± 1.5 ha in the YREB could avoid 23.7 ± 1.6 t CO 2 (1.08 ± 0.03 t CO 2 /ha) in emissions due to heat mitigation per summer day. Considered altogether, the 1510 urban parks can offset 5.37% of the daily fossil fuel emissions in the YREB. To boost carbon saving efficiency, lush vegetation should be first considered and the coupled green and blue infrastructures are always advocated. The total parks carbon saving of cities gradually improved along the Yangtze River from west to east, among which Shanghai city (in the east of the YREB) is with the largest amount (4341 t CO 2). The strategies using exquisite landscape design for improving carbon saving may differ across different climate zones. These findings can inform decision-making for urban sustainable development and climate change mitigation, which may benefit China's movement toward carbon neutrality. [ABSTRACT FROM AUTHOR]