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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]

Approximately 172 million rural households in China in 2022, will still rely on traditional biofuels instead of electricity. This study explores the feasibility of achieving rural electrification in China utilization various Energy origins and assesses its potential impact on climate change mitigation. To do so, we employ the Regional Energy Model (REM) to formulate hypotheses for rural power distribution. Covering the era from 2020 until 2050. We evaluate consequences in terms of greenhouse gas discharges, principal energy consumption, associated expenses by comparing these possibilities with a Business- as -Usual (BU) scenario. Our findings reveal that diesel-based arrangements tend to produce 'the maximum Carbon Dioxide (CO2) emissions, trailed by network-based solutions. Electrification focused on renewable energy-driven applications has the potential to reduce total CO2 emissions by up to 97 % and primary energy consumption by 43 % in 2050 compared to the BU scenario. We also find that electrification through decentralized diesel systems tends to be the priciest choice. Rural electrification utilizing renewable energy emerges as a cost-effective choice when the majority of end-use applications rely on renewable energy sources. However, it becomes less economical than network expansions when electric end-user appliances are predominant. In summary, this study investigates the viability of renewable energy for rural power distribution and its role in climate change abatement in rural China, offering policy suggestions. • Analyzes six energy-based scenarios for China's rural electrification until 2050. • Evaluates GHG emissions, energy use, and costs impacts with regional energy model. • Provides policy insights and uncertainties for China's sustainability goals. • An oil price and distance-based analysis also is done with extra 6 scenarios. [ABSTRACT FROM AUTHOR]

To motivate public participation in climate change mitigation, both "carrot" policies that create positive incentives for mitigated carbon and "stick" policies that create negative incentives for emitted carbon have been widely applied. Given the joint deployment of these measures, a key question is whether they are compatible with each other. Focusing on the Low-Carbon Reward Scheme (LCRS) and carbon taxes, two prominent proposals on China's climate policy agenda, this study evaluates how one incentive policy affects public support for the other. The results of a large survey experiment with Hangzhou residents indicate a two-way crowding-out effect, wherein introducing the LCRS diminished support for the tax, albeit primarily among LCRS proponents, and introducing the tax reduced support for the LCRS. Aligning with the proposed account, crowding out was driven by a decrease in policy effectiveness and fairness perceptions. These findings reveal a contradictory relationship between carrot and stick policies at the citizen level and illuminate the underlying mechanism. • Both carrot and stick policies are applied to motivate climate mitigation behaviors. • We identify a two-way crowding-out effect between these policies in public opinion. • Introducing a stick (carbon tax) reduces support for a carrot (low-carbon reward). • Introducing a carrot reduces support for a stick among people favoring the carrot. • Crowding out is driven by weakened policy effectiveness and fairness perceptions. [ABSTRACT FROM AUTHOR]

Cities face twin challenges of changing climate and urban heat island (UHI) effect, with the environmental implications of urbanization still unclear. This study employs the Weather Research and Forecasting (WRF) model to examine the impacts of urbanization in the Greater Bay Area (GBA) during warm and cold seasons in past (2000) and near-future (2030) scenarios [i.e., under shared socioeconomic pathways (SSP): SSP1-26, SSP2-45, and SSP5-85]. Datasets from the World Urban Database and Access Portal Tools (WUDAPT) were incorporated into the WRF model to improve the representation of urbanization effects on weather patterns. Our findings indicate that urban expansion significantly increases urban temperatures and decreases wind speed across selected climate change scenarios. The spatially averaged urban temperatures in the fine resolution domain for 2030 could rise by 0.9 °C (warm season) and 2.4 °C (cold season), respectively, and urban wind speed decreases by ∼ 3 m/s under the SSP5-85 scenario. In cold season, the UHI effect could last over 20 h, while urban area may experience cooler nighttime temperatures than rural areas in warm season. Moreover, the future scenario predicts higher daytime O 3 levels due to the warming effects of climate change and urbanization, but lower nighttime levels in warm season, attributed to intensified south-easterly sea breeze and background winds, when compared to the past scenario. This study highlights the importance of incorporating urbanization and climate change in future urban atmospheric environment studies, and underscores that urban climate change adaptation and mitigation should consider extra impacts on built-environment caused by urbanization. • Climate change and urbanization impacts on meteorological and O 3 fields were explored in GBA. • Urbanization and climate change are expected to raised temperatures by 0.9 °C in warm season over the study area. • Urbanization and climate change are expected to raised temperatures by 2.4 °C in cold season over the study area. • Urbanization is expected to reduce wind speed by 3 m/s and intensify sea breeze penetration over the study area. [ABSTRACT FROM AUTHOR]

Nitrogen (N) fertilisation is critical for sugarcane crop production. Consequently, overuse of N fertiliser in sugarcane is widespread and it is most prevalent in China. Yet, a comprehensive analysis of sugarcane N balance accounting for different reactive N (Nr) loss pathways, crop N use and soil N retention using 15N labelled fertilisers under commercial high-input cropping conditions is lacking. A two-year field experiment with 5 N levels (0–560 kg N ha−1; N0, N210, N300, N390, N560) was conducted to quantify the effect of N rate on sugarcane yield, Nr loss through different loss pathways, crop N use and soil N retention, and to identify an optimal N rate that sustain high yield whilst reducing Nr loss in Southern China. The results showed that optimal N rate (N300) had similar yield compared with farmer practice (N560) for the plant crop and the ratoon crop. Nitrogen leaching and ammonia loss were increased significantly with increase in N rate, with farmer practice recording the highest Nr loss. Compared with farmer practice, under optimal N application, N leaching was reduced from 211 kg ha−1 to 107 kg ha−1 and from 244 kg ha−1 to 165 kg ha−1 for the plant and ratoon crops, respectively. The ammonia volatilization from the plant crop and the ratoon crop in the optimal N treatment was 24.8 kg ha−1 and 27.0 kg ha−1, respectively, which are considerably less compared with the emission from the farmer practice. There was no significant difference in nitrous oxide emission between optimal N rate and farmer practice. 15N labelling studies showed that crop N recovery, soil N residue and fertiliser N lost at the optimal N rate were 20.9%, 24.9% and 54.2%, respectively, as opposed to 12.5%, 14.8% and 72.7%. respectively, under farmer practice. To the best of our knowledge, this study forms the first comprehensive evaluation of sugarcane N balance accounting Nr loss, N use and native N soil stock covering a wide range of N supply simultaneously in the plant and ratoon crops under commercial crop production condition. This study thus provides very valuable new knowledge not only for crop N supply optimisation in high-input sugarcane production systems as in China but also for sugarcane greenhouse gas accounting studies particularly from climate change mitigation and bioenergy production context. [Display omitted] • First detailed sugarcane crop N balance (Nr loss, N use, soil N stock) estimated. • Current average sugarcane crop N input in China (560 kg N ha−1) very excessive. • Large reduction in N input and Nr loss without yield loss in multi-year field trials. • Leaching, the single largest N loss pathway in sugarcane crop. • Large crop N recovery, fertiliser N loss reduction with optimal N use (300 kg N ha−1). [ABSTRACT FROM AUTHOR]

Ethylene is one of the most important products in the emissions-intensive petrochemical industry. Decarbonizing the ethylene industry is thus important for achieving global carbon neutrality. This study is the first to explore future long-term zero-emissions production pathways for the ethylene industry in China, the world's biggest ethylene producer. An optimization model was built in the context of China's carbon neutrality target of 2060. Four scenarios were developed where the policy ambitions for climate mitigation and for plastic management including waste were varied. Based on this, authors assessed the cumulative total emissions, technology options, future geographical location of ethylene production, and policy challenges associated with each scenario. This is also the first time that scope 3 emissions from waste incineration are included, motivated by the short lifetime of most ethylene products. Results show the cumulative CO 2 emissions for the scenarios differ considerably, ranging from 4.3 to 7.8 Gt, even if carbon neutrality by 2060 is achieved in all scenarios. The results suggest that ambitious plastic focused policies can result in lower costs and less cumulative emissions compared to ambitious climate focused policies. The results demonstrate the importance of adopting CCS for waste incineration. This reduces cumulative CO 2 emissions by up to 2 Gt. However, reduced overall demand and increased recycling rates should be priority options due to CCS challenges. Results suggest Chinese ethylene industry should adopt a mixed portfolio of production technologies, where the share of emission-intensive coal-based methanol-to-olefins is limited. These findings on decarbonization pathways can contribute to achieving the Paris agreement. [Display omitted] • Ambitious plastic policies lead to 1.3 Gt less cumulative CO 2 than climate policies. • Cumulative CO 2 until 2060 can be reduced by 3.5 Gt compared to reference scenario. • Adopting CCS in incineration can reduce cumulative CO 2 emissions by 2 Gt. • Ethylene industry should adopt a mixed production portfolio due to uncertainties. • Coal-based MTO with CCS does not appear to be a cost-competitive option. [ABSTRACT FROM AUTHOR]

Carbon neutrality strategies have a significant role in climate mitigation efforts. As global concerns regarding climate change continue to increase, achieving carbon neutrality has emerged as a paramount objective for reducing greenhouse gas emissions and limiting the adverse impacts of anthropogenic activities on the environment. This research investigates a wide range of scholarly works to conduct an in-depth analysis and synthesis of the relevant information about carbon neutrality strategies. The review introduces carbon neutrality principles and terminologies, highlighting their importance in climate mitigation. It then proceeds to explore the wide range of strategies employed across different sectors and industries, investigating their effectiveness, scalability, and potential challenges. A multidimensional analysis contrasts the United States Nationally Determined Contributions pathway 2023, China's Nationally Determined contributions 2023, and the EU Directive 2023/2413, assessing their economic, environmental, political, and social impacts. The study evaluates strategies' effectiveness, scalability, and innovation for transitioning to a sustainable, low-carbon future. It fills a gap by analyzing global approaches across the US, China, and the EU, which account for about 50% of the world's total GHG emissions. It evaluates the novel application of diverse strategies, from renewable energy transitions to innovative policy measures, highlighting their potential to mitigate climate change effectively. By providing a multidimensional analysis of these strategies' impacts, the research not only enhances understanding of effective carbon neutrality tactics but also underscores the importance of international cooperation in realizing a sustainable, low-carbon future. • Identifies and analyzes carbon neutrality strategies, emphasizing the need for diverse US, Chinese, and EU approaches. • Evaluate renewable energy, carbon capture, and policy tools for carbon reduction effectiveness, scalability, and innovation. • Highlights the study's novelty in synthesizing current knowledge on carbon neutrality, addressing a significant research gap. • Concludes with strategic ideas for international collaboration and policy development for low-carbon futures. [ABSTRACT FROM AUTHOR]

The number of patent ap plications for climate change mitigation technologies (CCMT) in China has shown a rapid development trend over the past decade. This study applies social network analysis (SNA) method and directed time-exponential random graph model(TERGM), while considering endogenous network structure variables, node variables and external network covariates, to analyze the Climate Change Mitigation Technology Innovation Cooperation Network (CCMTICN) formed in Chinese provinces, and analyzes the influencing factors and evolution of the CCMTICN from 2011 to 2021 using CCMT patent data from the Himmpat database. The results show that CCMTICN shows obvious core-edge structural characteristics; endogenous network structural variables have a non-negligible influence on the formation of the network, and other factors such as the information exchange network, industrialization level, knowledge level, and the degree of governmental intervention can promote the formation of CCMTICN; whereas, foreign direct investment, urbanization level, and carbon dioxide(CO 2) emissions can inhibit the formation of CCMTICN. When considering the 11-year time effect of CCMTICN, it is found that the CCMT cooperative relationship between provinces remains relatively stable. • Edge weights set by cooperative patents between provinces. • Examined CCMTICN factors over three periods using TERGM. • Added Baidu index to network variables; assessed CO2 impact. • Time effects in TERGM analyzed for network stability. [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]

• Carbon efficiency and abatement costs of the PLEEZ are estimated. • The regional heterogeneity among the three major types of functional zones in the PLEEZ are analyzed. • Major agriculture production zone has a higher carbon efficiency and lowest abatement costs in the PLEEZ. • The global non-radial directional distance function and its dual model are used. In this paper we investigate the carbon efficiency and abatement cost for different main functional regions in China, to test whether major agriculture production zone has higher carbon efficiency and abatement cost than other functional regions. For this purpose, we use a global non-radial distance function to examine the efficiency and abatement cost of carbon emissions and take China's Poyang Lake Ecological Economics Zone (PLEEZ), one of China's national strategy for sustainable development, as an empirical study. By using the non-radial efficiency model, the carbon emissions efficiency indicator can be constructed. By employing the dual model of the non-radial directional distance function, the shadow prices of carbon emissions, which is interpreted as marginal abatement cost can be derived. County level data from 2009 to 2013 of the PLEEZ is used as the empirical investigation. Empirical results show that the CO 2 emissions of the PLEEZ are not performing efficiently and the CO 2 emissions efficiency remains at a very low level with an average value of 0.279. Meanwhile, the shadow prices of CO 2 emissions are calculated, with a mean value of 11.867 yuan per ton, which is relatively low compared with other previous studies of different regions or industry and indicate that carbon emissions are not strictly regulated. Moreover, significant heterogeneities in the carbon efficiency and abatement cost are found among three major functional zones in the PLEEZ remain. Major agriculture production zone shows better carbon efficiency than key ecological function zone, but lower than key economic development zone. It is also found carbon abatement cost of major agriculture production zone is lower than key economic development zone indicating the less pressure under climate change mitigation. [ABSTRACT FROM AUTHOR]

The industrial sector is characterized by high energy consumption and high carbon emissions. It is of great significance to clarify the determinants of industrial CO 2 emissions for emissions abatement policy making. For this purpose, a comprehensive decomposition framework that can quantify the impacts of both oriented technologies and economic factors on CO 2 emissions is developed. By applying the proposed decomposition framework, this paper investigates the determinants of China's industrial CO 2 emissions. The main findings show that, during the study period, (1) investment scale expansion was the leading factor promoting emissions growth; (2) against our expectations, efforts for energy structure adjustment failed to curb emissions but had marginal promoting effects on emissions growth; (3) energy-oriented and output-oriented technologies were indispensable contributors to emissions mitigation, followed by decreases in investment efficiency, potential energy intensity, and the CO 2 emission coefficient; and (4) energy use efficiency and production efficiency changes usually exerted moderate influences on industrial CO 2 emissions, and their influencing directions were sensitive in different sub-industries and Five-Year Plan periods. In most situations, the inhibiting effects could not counteract the promoting effects. Based on these empirical findings, policy recommendations to further reduce industrial CO 2 emissions are provided. • Empirical analysis was conducted at sub-industries and different FYPs levels. • Investment scale was the leading factor promoting industrial CO 2 emissions. • The technology progress contributed most to emission mitigation. • Driving effects distinctly differed among sub-industries and FYP periods. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to study the decoupling status and mitigation potential of CO2 emissions from China's transport sector over the period 1991–2015. Firstly, this paper utilizes the Log-Mean Divisia Index (LMDI) technique to identify influencing factors, which govern CO2 emissions from China's transport sector. Over the study period, the CO2 coefficient effect (Δ C c f t ) was the main factor for decreasing CO2 emissions. However, the economic growth effect (Δ C g t ) was the main factor for increasing CO2 emissions. Then, the decoupling indicator is also constructed based on the above influencing factors, which can be utilized to reflect the dependence degree of economic development on CO2 emissions from China's transport sector. During 1991–2015, the CO2 emissions from China's transport sector presented expansive coupling (EC) with economic development. Weak decoupling (WD) only appeared in the sub-period 1991–1995. The CO 2 emissions only presented 3 decoupling grades in all sub-period and the period 1991–2015: Ⅱ, Ⅲ, and Ⅳ. Furthermore, the above influencing factors are also used to establish a theoretical mitigation model, which is used to reflect the mitigation potential of CO2 emissions from China's transport sector. Finally, the occurrence of CO2 mitigation only appeared in 3 sub-periods: 1991–1995, 2005–2010, and 2010–2015. • The LMDI technique is used to identify influencing factors. • The decoupling indicator is constructed based on the influencing factors. • The influencing factors are used to establish a theoretical mitigation model. [ABSTRACT FROM AUTHOR]

For many years, China has invested effort into achieving resource conservation and environmentally friendly economic development. The measures implemented include promoting technological innovation, market-oriented reform and industrial structure adjustment. But there are open questions: What have the effects of these measures been? Have they helped China achieve win-win development in terms of its resources, environment, and economy? This paper aims to answer these questions by using a newly proposed global three-hierarchy meta-frontier Luenberger index that can quantify the effects of promoting technological innovation, industrial restructuring, etc., on economic growth, energy conservation and emissions reduction. The results show that (1) during 2001–2016, China's energy efficiency, economic efficiency, and emissions efficiency improved, indicating that China's efforts have brought about the win-win development of resources, the environment, and the economy; (2) the implemented measures have heterogeneous effects on economic growth, energy conservation, and emissions reduction. The implemented measures are generally beneficial to energy conservation and emissions reduction but potentially harmful to the economy; (3) the effects of these measures on economic growth, energy conservation and emissions reduction across China's regions and provinces are also quite different, indicating that local provincial governments should have a clear understanding of their own characteristics before implementing the relevant policies and measures. • A global three-hierarchy meta-frontier Luenberger index was proposed for the study. • It can quantify the effects of China's efforts on economy, energy, and emissions. • Results show that China's efforts have brought about a win-win development. • There are the heterogeneities of China's pathways to economic growth, energy conservations and emissions reductions. • The future strategies for China's win-win development should take the heterogeneities into account. [ABSTRACT FROM AUTHOR]

• We quantified wood substitution benefits in the furniture sector for China. • Displacement factor is used to assess substitution effects on emission reduction. • The avoided emissions for the products were weighted by consumption statistics. • Each tC in wood used for material substitution reduces 1.46 tC of emissions. Wood and wood-based products have positive effects on climate change mitigation. These products can substitute for energy-intensive products made of conventional materials. The main objective of this study was to quantify substitution benefits of wood furniture for China via national-scale mitigation analyses. We selected a basket of representative furniture and estimated the emission reduction for two functionally equivalent products, which differentiate in wood intensity. The emissions avoided in each type of product were weighted by its share of the furniture market to ensure that the basket can represent the current situation. Then, avoided emissions were estimated for wood commodities contained in the products basket. Results demonstrated that wood materials exerted low environmental impacts. From the less to the more wood intensity products with the equivalent function, the proportion of energy-intensive materials decreased 24% while the proportion of their greenhouse gas (GHG) emissions decreased 34%. The overall displacement factor for the wood material was 2.67 kg CO 2 eq/kg or 1.46 tC/tC. The findings highlight the importance of material selection in mitigating climate change in the furniture sector. It is urgent to use of the existing timber resources efficiently and pursue alternative schemes for emission reduction to achieve the goal of GHG mitigation. [ABSTRACT FROM AUTHOR]

Curbing the increasing carbon emissions from residential and commercial buildings would be of great importance for achieving China's NDC (Nationally Determined Contributions) target. However, studies on city-level emission pathways and mitigation strategies aiming at building sector are still far from sufficient, especially for regions in Central China. Considering the large potential for further building energy demand increase within this area, this study focuses on Hubei, one of the first batch low-carbon pilot provinces to investigate the possibility of earlier emission peak and reduction potentials by prefecture-level city. When downscaling provincial energy use and emissions estimated from local government plans and academic research, statistical data was applied to exploring the relationship between building energy consumption and socioeconomic variables, then spatial allocation factor could be generated after combining with projections of grid-level GDP and population. Results show that by replacing coal and natural gas (NG) that are currently the main heating & cooking energy sources with more electricity and renewable energy, emissions from the building sector would peak around 2025, which is especially true for three major big cities with higher emission growth rate due to population and urban expansions. Moreover, when considering additional improvement on building energy efficiency, provincial reductions burden would be more evenly distributed among cities. It is implied that by formulating tiered mitigation policies for cities at various economic development levels, including decarbonization of energy structure and improvement of energy efficiency, more cities would peak their emissions from the building sector before 2030. This analytical framework innovatively create a multi-city platform for the simulation of building sector mitigation pathway to facilitate cities' low-carbon development. Image 1 • A spatial downscaling framework was developed for building energy consumption and emission projections on city-level. • Building sector mitigation potential for a low-carbon region with limited supporting data was quantified with this method. • Emission pathway and reduction contribution of the building sectors of multiple cities were estimated. • Electrification and greater renewable energy use in buildings would make emissions peak earlier for more developed cities. • Further building energy efficiency improvement helps increase the mitigation contribution from the less developed cities. [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]