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Building a more resilient response system to climate change for sustainable development and reducing uncertainty in China's food markets, requires access to historical research gaps and mapping future research progress for decision making. However, the lack of quantitative and objective analyses to ensure the stability and development of agroecosystems increases the complexity of agro-climatic mechanisms, which leads to uncertainty and undesirable consequences. In this paper, we review the characteristics of climate change in China (1951–2020), reveal the mechanisms of agroecosystem structure in response to climate, and identify challenges and opportunities for future efforts in the context of research progress. The aim is to improve the scientific validity and relevance of future research by clarifying agro-climatic response mechanisms. The results show that surface temperature, precipitation, and frequency of extreme weather events have increased to varying degrees in major agricultural regions of China in 1951–2020. And they have strong geographic variation, which has resulted in droughts in the north and floods in the south. Moreover, climate change has complicated the mechanisms of soil moisture, Net Primary Productivity (NPP), soil carbon pool, and crop pest structure in agroecosystems. This lends to a reduction in soil water holding capacity, NPP, soil carbon content, and the number of natural enemies of diseases and insects, which in turn affects crop yields. However, human interventions can mitigate the deterioration of these factors. We have also realized that the methodology and theory of historical research poses a great challenge to future agroecosystem. Historical and projected climate trends identified current gaps in interdisciplinary integration and multidisciplinary research required to manage diverse spatio-temporal climate change impacts on agroecosystems. Future efforts should highlight integrated management and decision making, multidisciplinary big data coupling, and numerical simulations to ensure sustainable agricultural development, ecological security, and food security in China. [ABSTRACT FROM AUTHOR]

Global climate changes have led to frequent and recurrent heat stress, which has seriously affected the world maize production. The experiment presented in this paper was carried out during the maize‐growing season in 2021 and 2022 at the Huang–Huai–Hai Region Maize Science and Technology Innovation Center (36°09′N, 117°09′E) in Tai'an, Shandong province, China. The test site is located in the semi‐humid warm temperate continental monsoon climate zone, soil is brown loam. We selected different heat‐sensitive maize varieties: heat‐tolerant variety Zhengdan 958 (ZD958) and heat‐sensitive variety Xianyu335 (XY335) to study the stress effects of high temperature on the development of tassel in the key stage of its differentiation (the 12‐leaf stage, V12). We found that exposure to heat stress during the V12 stage significantly reduced the tassel size and the anther dehiscence area, making it difficult to disperse pollen, thus effectively reducing pollen production. In addition, heat stress had significant negative effects on pollen development, resulting in deformed pollen and lower pollen viability and germination rate. Our results also showed that heat stress significantly increased the activities of key reactive oxygen species‐scavenging enzymes including superoxide dismutase, peroxidase and catalase, and that the malondialdehyde and H2O2 content in tassels exposed to heat stress were significantly higher than those control group, where it should be noted that for the XY335, these effects were more pronounced than for the ZD958. The endogenous hormone content of tassels exhibited a variety of responses. After heat stress, the zeatin and salicylic acid content in tassels of both maize varieties were significantly lower than those in the respective control groups, while the abscisic acid and gibberellin acid content were significantly higher. With respect to the jasmonic acid and 3‐indoleacetic acid content, the two maize varieties exhibited opposite responses: in tassels from ZD958 plants subjected to heat stress were higher than those in the respective control group, while in tassels from XY335 plants, they were lower. The observed changes in protective enzyme activities and endogenous hormone contents induced by heat stress significantly affected the development of maize tassels and significantly reduced the amount, activity and germination rate of pollen. [ABSTRACT FROM AUTHOR]

Urban areas mediate climate transformations and generate new forms of climate urbanism. Looking at climate action in the twelve fastest-growing cities in China with under one million people, this paper proposes a perspective on urban climate politics 'from elsewhere' that foregrounds the potential role of smaller urban areas in mediating climate transformations. The analysis reveals three climate action strategies that reflect practical, institutional, and personal spheres of climate transformations. Planning action in the personal sphere provides opportunities for urban transformations. A perspective 'from elsewhere' calls for greater attention to planning for diverse change strategies for climate transformation. [ABSTRACT FROM AUTHOR]

Global climate change caused by greenhouse gas emissions has a direct impact on the sustainable development of human society and has gained widespread concern globally. Biological carbon sequestration measures, mainly forests, are conducive to improving the ecological carbon sink capacity and play an important role in mitigating global climate change. Therefore, assessing the efficiency of forest carbon storage (FCS) is key. In view of the lack of evaluation methods for forest carbon storage efficiency (FCSE) on a large spatial scale and long time series, a method based on Data Envelopment Analysis (DEA) was proposed in this paper. The FCS was calculated using the forest storage expansion method, and the FCSE was calculated using the DEA-Malmquist index to solve the dynamic balance between regional forestry economic input and carbon storage output efficiency. The FCSE in Chinese provinces was analyzed. The results showed that from 1999 to 2018, China's FCS increased annually, from 7558.34 million tons to 9476.73 million tons, and the spatial distribution pattern of total FCS was always different among regions. The average TFP value of FCSE was 1.089, which proves that the FCSE in China has been on the rise in the past 20 years, but the efficiency growth differed between provinces and was affected by different factors such as technical efficiency and technological progress. [ABSTRACT FROM AUTHOR]

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Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Long‐range transport and vertical distribution of aerosols are important factors for assessing the uncertainty in aerosol radiative forcing. This paper reveals the vertical distribution and trends of aerosol optical properties in China using 15 years of Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP) data. The Hybrid Single‐Particle Lagrangian integrated trajectory model was used to analyze the transport and trends of aerosols in the layer with the highest occurrence frequencies of dust, polluted dust, polluted continental and elevated smoke aerosols. The results indicated that (a) there were significant regional and seasonal differences in the vertical distribution of aerosols. The aerosol optical depth (AOD) trend in a given region depends on the changes in the aerosol type with the highest frequency and the layer corresponding to the largest AOD in the vertical profile. The frequency of polluted dust aerosols was the highest in Beijing‐Tianjin‐Hebei (BTH) and Central China. The considerable decrease in the 0–2 km AOD led to a significant trend of the column AOD. (b) The changes of AOD and main aerosol types in a region are also affected by the changes of aerosol sources and long‐range transport pathways. In the BTH, dust aerosols originated from the Mongolian Plateau, accounting for 57.88% of the total trajectories. The Pearl River Delta was dominated by elevated smoke aerosols, with trajectories mainly originating from the Myanmar and Vietnam, accounting for 27.38% and 29.59%, respectively. The trend of 15‐year backward trajectories of dust aerosols on the Tibetan Plateau indicated that the trajectory from India is increasing. Plain Language Summary: Aerosols are one of the main factors affecting global climate change, influencing global radiation through direct and indirect effects. Long‐range transport aerosols and their vertical distribution are important factors for assessing the uncertainty in aerosol radiative forcing. At present, there is limited research on the vertical distribution and transport pathways of different types of aerosols in multiple regions over China. Considering that aerosols in different regions of China exhibit large vertical distribution and transport differences, we revealed the vertical distribution and trends of aerosol optical properties in China using 15 years of Cloud‐Aerosol Lidar with Orthogonal Polarization data. The Hybrid Single‐Particle Lagrangian Integrated Trajectory model was used to analyze the transport and trends of different aerosols. We found significant regional and seasonal differences in the vertical distributions of aerosols. The changes in the aerosol optical depth and main aerosol types in a given region were also significantly affected by the changes in aerosol transport sources and transport pathways. This study provides comprehensive insight into the vertical distribution and transport characteristics of different types of atmospheric aerosols in the Chinese region over the last 15 years, which is very important to further evaluation of the impact of different aerosol types on the radiative effects and the environment. Key Points: The vertical distribution of aerosol optical properties exhibits notable seasonal and regional differences using 15 years of Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP) dataThe trend of total aerosol optical depth (AOD) mainly depends on the joint changes of the highest frequency aerosol and the maximum AOD layer in a vertical profileThe changes of AOD and main aerosol types in a region are also affected by the changes of aerosol transport sources and transport pathways [ABSTRACT FROM AUTHOR]

Economic development has brought about global greenhouse gas emissions and, thus, global climate change, a common challenge worldwide and urgently needs to be addressed. Accurate carbon price forecasting plays a pivotal role in providing a reasonable basis for carbon pricing and ensuring the healthy development of carbon markets. Therefore, this paper proposes a two-stage interval-valued carbon price combination forecasting model based on bivariate empirical mode decomposition (BEMD) and error correction. In Stage I, the raw carbon price and multiple influencing factors are decomposed into several interval sub-modes by BEMD. Then, we select artificial intelligence-based multiple neural network methods such as IMLP, LSTM, GRU, and CNN to conduct combination forecasting for interval sub-modes. In Stage II, the error generated in Stage I is calculated, and LSTM is used to predict the error; then, the error forecasting result is added to the first stage result to obtain the error-corrected forecasting result. Taking the carbon trading prices of Hubei, Guangdong, and the national carbon market, China, as the research object, the empirical analysis proves that the combination forecasting of interval sub-modes of Stage I outperforms the single forecasting method. In addition, the error correction technique in Stage II can further improve the forecasting accuracy and stability, which is an effective model for interval-valued carbon price forecasting. This study can help policymakers formulate regulatory policies to reduce carbon emissions and help investors avoid risks. [ABSTRACT FROM AUTHOR]

Rainfall fluctuations are the major threats caused by climate change. This paper analyses the impact of seasonal rainfall fluctuations on rural poverty using panel data for 992 counties, which are located in humid zone in the south of China from 2000 to 2018. The findings are as follows: (1) Rainfall fluctuations significantly affect rural poverty, specifically, increased rainfall significantly alleviates rural poverty in the dry season, but aggravates rural poverty in the rainy season. (2) The effect of rainfall fluctuations on rural poverty is significantly heterogeneous in different regions. (3) Rainfall fluctuations put low‐income areas at greater risk of returning to poverty. (4) The mechanism through which rainfall fluctuations affect rural poverty is agricultural production, and market regulation can mitigate the shock of rainfall fluctuations. Our research provides policy implications for developing countries to address the risks of poverty from climate change. [ABSTRACT FROM AUTHOR]

Recent years have witnessed climate change characterized by increasingly frequent extreme precipitation events, and the assumption of stationarity in traditional frequency analyses is gradually being questioned. In terms of the current research status in China, there is a lack of thorough investigations on the linkage between extreme precipitation and climate change. This paper aims to determine the dominant climate indices as well as the corresponding significant time scales and periods affecting extreme precipitation over China for dynamic assessments of the upcoming rainstorm risk. Correlations between 15 climate indices and precipitation extremes, as well as the correlations among climate indices, are fully explored to identify potential predictors for non-stationary modeling. Then, 21 non-stationary generalized extreme value (GEV) models are constructed, and the optimal covariates as well as their lag times with extreme precipitation at 769 stations are ascertained in a Bayesian framework. Finally, a complete predictive process is developed, and the national rainstorm risk under non-stationary conditions is assessed. The results indicate that precipitation extremes remain stationary only at 74 stations (less than 10%). WPI is dominant in modeling the variability in precipitation extremes for nearly 22% of the total stations, ranking first among all the climate indices. The predominant time scale affecting extreme precipitation at the majority of stations is 3 months. Ignoring the non-stationarity of extreme precipitation inevitably leads to misperceptions of rainstorm risks, and the spatial distribution of the maximum case of the design rainstorms under non-stationary conditions differs remarkably from that under stationary conditions. Our findings have important implications for the in-depth understanding of the real drivers of extreme precipitation non-stationary and enable advanced predictions of rainstorm risks for mitigating subsequent disasters. [ABSTRACT FROM AUTHOR]

This paper studies climate change impacts on total factor productivity (TFP) in China using economic and climatic data for provincial capital cities and municipalities from 1998 to 2017. We employ a novel nonparametric quantile method to decompose historical temperature data into multiple temperature quantiles, which are then used in our regression analysis to avoid estimation bias caused by seasonal heterogeneity of temperatures across China. Specifically, we create three temperature quantiles for each city to represent their extremely high temperatures in summer, extremely low temperatures in winter, and mild temperatures in spring and fall. In general, we find that a warming climate has a significant negative impact on TFP in the long-run, while in the short term, only increases in extreme temperatures exert significant negative effects on TFP growth. However, the temperature effects on TFP vary substantially across coastal capital cities, inland capital cities, and municipalities due to their differences in geography, development levels, and political positions. Finally, our results are robust when spatial spillover, temporal lagging, and labor intensity effects are taken into account. [ABSTRACT FROM AUTHOR]

The aims of this paper is to illustrate the importance of grain production in China's food security strategy based on the three Northeastern provinces (NEP) in the new period, which quantitative assessment of climate change under the background of the loss caused by meteorological disasters of regional food production is clarify. In this paper, using grain planting area, yield and agricultural disaster statistics from 1981 to 2020, comparison analysis grain production and disaster characteristics between NEP and the whole country respectively. The disaster-yield assessment model was used to estimate the disaster-yield loss and final yield of the NEP by inputting disaster data in recent 10 years, and the sensitivity and stability of the disaster-yield assessment model were re-tested. The results showed that :(1) from 1981 to 2020, the grain planting area and total output in NEP increased significantly, and the proportion of the total output of NEP increased steadily, and the proportion of the total output of the three northeast provinces reached 1/5 of the total output of the whole country by 2020. (2) The disaster situation in NEP showed a significant trend of first increasing and then decreasing. The incrasing of average grain yield during the past 40 years was 65.96kg⋅ha-1 and 252.5kg⋅ha-1 per year for NEP and the whole country, while the incrasing of average grain yield during the past 10 years was 52.6kg⋅ha-1 per year for NEP significantly. (3) From 2011 to 2020, the average affected area and affected area in China were 23704.5x10³ha and 11204.7x10³ha, respectively, and 3899.1x10³disasters of the whole country and the three northeastern provinces were significantly lower than those of the previous three years, making it the decade with the least severe disasters in 40 years. (4) The simulation accuracy of the disaster-yield assessment model was high. The linear regression coefficients (R²) of simulated grain yield and measured grain yield in Heilongjiang, Jilin and Liaoning provinces were 0.98, 0.90 and 0.88, respectively. The slopes were 1.05, 1.02 and 0.98 (P < 0.01), respectively. The loss rate of grain yield due to agro-disaster was 10.4%, 17.9% and 18.0% respectively in the three province, while which was more than 8.0%, 17.0% and 16.0% for 20a.years. (5) The model slightly overestimated the grain yield of Jilin and Liaoning in recent 10 years due to the overall light disaster situation. Based on the data from 1981 to 2010, the regional grain disaster loss assessment model was proved to be able to evaluate the loss of grain yield caused by meteorological disasters well, and had the performance of predicting grain yield, and has the feasibility of operational application. The impact of meteorological disasters on the grain output in northeast China is higher than the average level of disasters in the whole country. Considering that the grain output in Northeast China accounts for a high proportion of the national grain output, preventing the risk of agro-meteorological disasters in Northeast China in the new period is of great importance to guarantee the national food security. [ABSTRACT FROM AUTHOR]

Increased temperature and carbon dioxide concentration caused by climate change will aggravate the creep shrinkage and structural durability of concrete bridges. Overloading also has a great impact on the time-dependent reliability of existing bridges. This research paper analyses the time-dependent reliability of bridges based on climate change and overload. By improving the concrete carbonation model and referring to the B4 model of concrete creep, the effects of ambient temperature and humidity on concrete under different emission-reduction scenarios were considered. At the same time, given the serious problems of vehicle overload in China, combining different overload scenarios with climate change led to the establishment of a time-dependent reliability model for precast-concrete bridges. The results showed that as the overload rate increased, the time-dependent reliability degradation rate of a case study bridge accelerated. Under the scenario considering both high greenhouse gas emissions and the maximum overload rate, the service life of the case study bridge decreased to 50% of its design life. [ABSTRACT FROM AUTHOR]

Climate change is a global problem facing mankind, and achieving peak CO2 emissions and carbon neutrality is an important task for China to respond to global climate change. The quantitative evaluation of the trends of urban energy consumption and carbon emissions is a premise for achieving this goal. Therefore, from the perspective of urban expansion, this paper analyzes the complex relationship between the mutual interactions and feedback between urban population, land expansion, economic growth, energy structure and carbon emissions. STELLA simulation software is used to establish a system dynamics model of urban-level carbon emissions effects, and Changsha city is used for the case study. The simulated outputs of energy consumption and carbon emissions cover the period from 1949 to 2016. From 1949 to 2016, Changsha's total energy consumption and carbon emissions per capita have continuously grown. The total carbon emissions increased from 0.66 Mt-CO2 to 60.95 Mt-CO2, while the per capita carbon emissions increased from 1.73 t-CO2/10,000 people to 18.3 Mt-CO2/10,000 people. The analysis of the structure of carbon emissions shows that the industrial sector accounted for the largest proportion of emissions, but it had gradually dropped from between 60% and 70% to about 40%. The carbon emissions of residential and commercial services accounted for less than 25%, and the proportion of transportation carbon emissions fluctuated greatly in 2013 and 2016. From the perspective of carbon emissions effects, carbon emissions per unit of GDP had a clear downward trend, from 186.11 t-CO2/CNY104 to 1.33 t-CO2/CNY104, and carbon emissions per unit of land showed two inflection points: one in 1961 and the other in 1996. The general trend showed an increase first, followed by a decrease, then a stabilization. There is a certain linear correlation between the compactness of urban shape and the overall trend of carbon emissions intensity, while the urban shape index has no linear correlation with the growth rate of carbon emissions. The carbon emissions assessment model constructed in this paper can be used by other municipalities, and the assessment results can provide guidance for future energy planning and decision making. [ABSTRACT FROM AUTHOR]

Two of the biggest issues in international politics today are climate change and the ongoing power transition between the United States and China. However, very few works examine the way these issues interact with each other. This paper attempts to resolve this by integrating climate change into power transition theory (PTT), which attempts to capture the behavior of states in the midst of transition to or from global power. This paper first analyzes the literatures on the (tenuous) links between environmental degradation and interstate conflict as well as PTT. Opportunities for integration are then examined, especially focusing on climate change's impact on the central variables of power and state satisfaction. These theoretical links are then applied to the looming US-Sino transition and highlight how climate change opens up new arenas of great power competition, exacerbates tensions and impacts relative power in unpredictable ways. [ABSTRACT FROM AUTHOR]

The excessive carbon emissions not only intensify the global climate change, but also seriously restrict the sustainable development of social economy. However, improving industrial carbon emissions efficiency is the most directly effective way to reduce emissions. Therefore, accurate measurement and analysis of carbon emissions efficiency and evolution characteristics of China's industrial system is the basis for China to improve carbon emissions efficiency. Based on this, we adopted energy consumption method and input-output method to calculate and analyze the industrial carbon emissions efficiency and evolution characteristics of China from 2002 to 2015. The results show that (1) If carbon emissions from cement production are ignored and only energy-related carbon emissions are considered, the calculation results of carbon emissions efficiency of heavy industry will be overestimated about 30%. (2) Compared with 2002, China's industrial carbon emissions efficiency increased by about twice in 2015. Specifically, the optimization of carbon emissions efficiency in agriculture, construction, light industry and service industry is very obvious, which has increased by 5.65, 5.00, 4.69 and 4.68 times respectively; The optimization of carbon emissions efficiency in power sector, heavy industry, transportation and chemical industry was obvious, which increased by 2.55, 2.01, 1.86 and 1.47 times respectively; The carbon emissions efficiency of the fossil energy sector has decreased by 0.36 times. (3) The carbon emissions efficiency of various industries has significant differences. Among them, agriculture, service industry, light industry and construction industry are generally industries with higher carbon emissions efficiency, while power sector, fossil energy sector, transportation industry, chemical industry and heavy industry are generally industries with lower carbon emissions efficiency, especially power and fossil energy sectors. Based on these, this paper provides policy implications and scientific evidence for accurately improving carbon emissions efficiency from the perspective of carbon emissions efficiency. [ABSTRACT FROM AUTHOR]

Green transformation of energy use in China's transport sector will promote sustainable development in the country. This paper extends the Bounded-adjusted Measure and Luenberger indicators to detect the performance of China's inland transport sector across 2006–2015. In the framework, the climate change and traffic accident risks are taken as undesirable outputs. In addition, source-specific and variable-specific decomposition are proposed for investigating the sources of inefficiency and productivity, and quantifying the contributions of climate change and traffic accident risks. This paper opens up the "black box" of technological progress, identifying the different channels (i.e., quantity and time-dimensions) through which affect economic growth. Therefore, policymakers can find out the most effective pathway to boost productivity growth and mitigate climate change and traffic accident risks in the transport sector, which are ignored in the conventional framework. Empirical results indicate great variances exist among 30 provinces in inefficiency scores, productivity change, and technological progress. Hence, classified regulations help to tackle this issue. We clustered 30 provinces into 4 groups according to their technological progress along quantity and time-dimensions. Variable-wise, CO2 emission-reduction and civil vehicle gains promote the TFP gains most. Also, we verify that economic development and environmental regulations can coordinate to promote the sustainable development of the transport sector. [ABSTRACT FROM AUTHOR]

As the world's largest CO2 emitter, China's emission reduction is the key to mitigating global climate change. Global investment capital, as a significant influencing factor of emissions, greatly contributes to China's economic growth and stimulates frequent interprovincial trade since the reform and opening. However, the spatial correlation of foreign investment and CO2 emissions across Chinese provinces is rarely considered. This paper explores the role of foreign direct investment (FDI) in emission reduction in China during 2004–2015 using the spatial Durbin economic models with two‐way fixed effects. Then, the partial differential equations decomposition of the local and spatial spillover effects is conducted for capturing the marginal effects of influencing factors. Results show that FDI contributes to emission reduction for the whole country, whereas interprovincial transmission and intra‐provincial transmission show significant heterogeneity. Specifically, FDI increases emissions in host areas, while FDI provides positive environmental externalities to adjacent areas through spatial spillovers. Our findings provide a new perspective to explain the coexistence of the "Pollution Haven" and "Pollution Halo" theories in a country. Also, the exploration of spatial spillover effects of FDI on emissions can provide a reference for other countries with rising trade and investment flows to promote collaborative emission reduction. Key Points: Local effects of foreign direct investment on emissions are positive, while spatial spillover effects are negativeThe coexistence of the "Pollution Haven" and "Pollution Halo" theories in a country is examinedResults help promote collaborative emission reduction across regions with trade [ABSTRACT FROM AUTHOR]

Separating existing historical precipitation data into solid and liquid precipitation remains a challenge in the study of climate change, extreme precipitation, and hydrological modelling. Based on historical daily air temperature and precipitation data, as well as visual observations of precipitation phase (weather phenomena records) in China mainland, this study proposed a snow‐day direct definition method (SDDM) to determine the threshold air temperature (TAT) of rainfall and snowfall, and analysed the spatial pattern and its influential factors. The main findings include: (1) the TAT based on the SDDM varied from −1.2 to 6.3°C, with a mean value of 2.8°C for the entire study region; (2) TAT was generally higher and more variable in the low‐latitude areas, and the Qinghai‐Tibet Plateau was characterized by an abnormally high average TAT of 5.2°C, almost twice as large as that of the eastern monsoon region; (3) TAT exhibited a significant positive correlation with altitude and negative correlation with precipitation and relative humidity. The results presented in this paper have potential application for studies of large‐scale snowfall climatology and climate change, weather forecasting techniques, and hydrological model parameterization in areas with complex and diverse geographical and climatic conditions. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of Chinese firms' environmental, social, and governance (ESG) performance on their financial constraint and financing activities. We find a negative association between firms' ESG performance and their financial constraint driven by the Chinese government's commitment to tackling climate change. Compared with state‐owned enterprises (SOEs), non‐SOEs have alleviated their financial constraint through both equity and debt issuance, thanks to the stock price appreciation and green credit. High‐pollution firms benefit from both equity and debt issuance, while low‐pollution firms mainly finance through equity issuance. Our findings demonstrate the leading role of the Chinese government in its domestic capital markets. [ABSTRACT FROM AUTHOR]

The purpose of this article is to investigate the new driving forces behind China's green energy and further assess the impact of green energy on climate change. The existing literature has used linear methods to investigate green energy, ignoring the non-linear relationships between economic variables. The nonparametric models can accurately simulate nonlinear relationships between economic variables. This paper constructs a nonparametric additive model and uses it to explore green energy. The empirical results show that the impact of green finance on green energy is more prominent in the later stage (a U-shaped impact). Fiscal decentralization also exerts a positive U-shaped impact, meaning that expanding local fiscal autonomy has contributed to green energy growth in the later stage. Similarly, the impact of oil prices and foreign direct investment demonstrates a positive U-shaped pattern. However, the nonlinear impact of environmental pressure displays an inverted U-shaped pattern. Furthermore, this article explores the impact of green energy on climate change and its impact mechanisms. The results exhibit green energy generates a positive U-shaped impact on climate change, meaning that the role of green energy in mitigating climate change gradually becomes prominent over time. Mechanism analysis exhibits that industrial structure and energy structure both produce a nonlinear influence on climate change. [ABSTRACT FROM AUTHOR]

With the escalating challenges of climate change and the imperative for carbon neutrality, evaluating the carbon footprint of regional power systems becomes crucial. To address this issue, a low-carbon evaluation framework for regional power systems is developed. First, this study identifies the fundamental requirements that the index system for the low-carbon power system should follow and specifies the general direction for the index system's creation. Second, an evaluation model for carbon reduction ability is proposed by considering generation side, grid side and load side of the power system. Then, a comparative evaluation model for the carbon reduction capability of multi-regional power systems is proposed to spatiotemporally compare the carbon reduction capability of different power systems. Next, a quantification method for the weights of low-carbon evaluation indicators is established based on the power system simulation of multi-scenario scheduling and index sensitivity analysis method. Finally, a low-carbon comprehensive score for regional power systems is created by combining the evaluation results of the system's carbon reduction capacity with index weights. The practical research results in a region of Zhejiang province in China demonstrate that the proposed model can provide a reasonable and feasible evaluation plan for the low-carbon construction of regional power systems. [ABSTRACT FROM AUTHOR]

An analysis is presented of the precipitation bias and change signal in an ensemble of regional climate model (RCM) (RegCM4) projections driven by multiple general circulation models (GCMs) over China. RegCM4 is driven by five different GCMs for the 120‐year period 1979–2099 at 25 km grid spacing, under the representative concentration pathway RCP8.5. We find that the GCMs and RegCM4 reproduce the general spatial pattern of precipitation over China in all four seasons, with RegCM4 providing greater spatial detail, especially over areas with complex terrain. The spatial patterns of precipitation bias show common features between the GCMs and RegCM4, characterized by an underestimation in the wetter regions, and an overestimation in the drier ones. Systematic increases of precipitation are projected in northern China, most pronounced in the Northwest basins, by both the GCMs and RegCM4 in all seasons except summer, when more mixed results are found. In addition, weak correlations of the projected change patterns are found in summer between the GCMs and nested RegCM4, indicating the greater role played by the representation of local convection processes during this monsoon season. The projections across the RegCM4 experiments show higher consistency and lower spread compared to the GCM ensemble, again indicating that the nested model physics significantly modulates the change signal deriving from the GCM boundary forcing. Plain Language Summary: China is a vulnerable country to climate change due to its dense population, unbalanced social and economic development, shortage of water resources, and fragile ecosystems. How future precipitation will change over the region is of great concern for the general public and decision makers. This paper presents a first analysis of precipitation simulations from a set of five RCM (RegCM4) 21st century climate change projections, driven by coarse resolution general circulation models (GCMs) over China. We find that the spatial patterns of precipitation bias show common features between the GCMs and RegCM4, characterized by a precipitation underestimation in the wetter regions, and an overestimation in the drier ones. Systematic increases of precipitation are projected in north China by both the GCMs and RegCM4 in all seasons except summer, when, weak correlations of the projected change patterns are found between the GCMs and nested RegCM4, indicating the greater role of the representation of local convection processes during this monsoon season. The projections across the RegCM4 experiments show higher consistency and lower spread compared to the GCM ensemble, again indicating that the nested model physics significantly modulates the change signal deriving from the GCM boundary forcing. Key Points: The spatial patterns of bias show common features between the GCMs and RegCM4RegCM4 provides greater spatial detail of present day precipitation simulation compared to the GCMs and finer structures of future changesThe change patterns across the RegCM4 projections show a high correlation, but not always between each pair of driving GCM and RegCM4 [ABSTRACT FROM AUTHOR]

Drought seriously endangers the development of agro‐pastoral ecotone in arid and semi‐arid regions. However, drought evolution characteristics of semi‐arid sandy grassland and its drivers are not well understood in the complex climate change context. Thus, in this paper, the revised standardized precipitation evaporation indices on one‐month (SPEI‐1) and growing‐season (SPEI‐6) scale, flash drought and dry spells (DS) were calculated as drought indicators, and the temporal variabilities and meteorological drivers of drought in Horqin Sandy Land during the growing period (April–September) from 2007 to 2021 were studied. The results showed that SPEI‐1 and SPEI‐6 exhibited negative trends and periodic change. This drought aggravation was manifested in increased grades and numbers of drought months. Flash droughts can occur every month during the growing season. And its occurrence was not only positively correlated with all drought events in frequency but also synchronized in time. The increased number of DS showed an asymmetrical shift towards 7‐day‐and‐longer DS. SPEI sensitivity to precipitation (P) was noticeably higher than to atmospheric evapotranspiration demand (AED) at both monthly and growing season scales. SPEI sensitivity to AED was modulated by P amounts, which was higher during low P period. Apart from the amounts of P and AED, their temporal variability also strongly determined how they affect the drought severity. P was also the main driver for flash drought and long DS, but AED with larger amount and higher variability is the reason for their aggravation. Our results demonstrate the complexity of drought intensification in semi‐arid sandy grasslands and highlight the important role of AED anomalies in it. [ABSTRACT FROM AUTHOR]

Assuming responsibility for emission reduction is an important part of participating in the global governance of climate change. Countries with a carbon neutrality target now cover about 75% of global greenhouse gas emissions. Carrying out fairness evaluations of their carbon neutrality targets provide a strong basis for the global carbon inventory. In this paper, the target years of carbon neutrality for major countries and regions under the global target of 2 °C and 1.5 °C are studied using the burden sharing model. On this basis, this paper simulates the possible pathways of carbon neutrality and evaluates the ambition of emission reduction targets in terms of annual emission reduction, per capita emission, and cumulative per capita emission. The results show that, from the perspective of equity, most of the developing countries cannot meet the global goal of 1.5 °C. The United States and the European Union nations could achieve carbon neutrality by 2050 by continuing their annual emission reductions under their existing NDC targets. However, to achieve carbon neutrality by 2060, China's annual emission reduction rate from 2030 to 2050 will be 6.7%, and the annual amount of emission reduction accounts for 51% of the global amount under the 1.5 °C target. Meanwhile, China would become the main force behind global cumulative emissions in the following decades. Thus, the emission reduction pathways China chooses will have an important impact on global climate mitigation progress. Based on the above research conclusions, this paper proposes that developed countries and developing countries should explore bilateral or multilateral cooperation in technology and finance in the field of climate change. Under the great pressure to achieve carbon neutrality, China needs to carry out research on the overall emission reduction pathways as soon as possible and clarify the paths at the scale of sectors, industries, provinces, and time stages. [ABSTRACT FROM AUTHOR]

In the context of climate change, innovative financing solutions and the rapid development of financial technology (fintech) offer great potential for the growth of renewable energy. Based on panel data from 30 provinces in China, this paper explores the impact of fintech on renewable energy growth by employing the instrumental variable-generalized method of moments (IV-GMM). We also pay attention to the nexus between fintech and renewable energy growth at different quantiles. This paper also explores the moderating role of the digital economy and the mediating role of green technological innovation. The main results indicate that (1) fintech positively affects renewable energy growth in China; (2) the positive effect between fintech and renewable energy is stronger in provinces with lower levels of renewable energy growth; (3) the digital economy, on the one hand, can significantly accelerate renewable energy growth; on the other hand, under the help of the digital economy, fintech can play a more effective role in increasing renewable energy growth; and (4) fintech indirectly promotes renewable energy growth by increasing the level of green technology innovation. The findings provide meaningful references for governments and policymakers and encourage the accelerated adoption of fintech in the sustainable energy sectors. • The role of financial technologies "fintech" on renewable energy growth is explored. • Fintech successfully stimulates the development of renewable energy. • The impact of fintech on renewable energy growth is asymmetric. • Digital economy facilitates the positive role of fintech in increasing renewable energy growth. • Green technology innovation is the path through which fintech affects renewable energy growth. [ABSTRACT FROM AUTHOR]

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper presents an in-depth analysis of the Marginal Abatement Cost Curve (MACC) for CO2 of China's industrial sector. Leveraging comprehensive firm-level panel data spanning the period 2011–2015, we employ a parameterized directional output distance function to estimate the shadow price of CO2. By doing so, we derive the marginal abatement cost for individual firms across different years, which provides crucial insights into two fundamental aspects: first, the variation in shadow prices as indicators of the economic efficiency of existing climate policies; and second, the carbon price levels necessary to achieve CO2 mitigation targets in the future. Furthermore, we conduct scenario simulations to assess the potential industrial output loss resulting from forthcoming carbon policies, such as the European Union's Carbon Border Adjustment Mechanism (CBAM). Our findings underscore the necessity for a considerably higher tax rate to stimulate pollution reduction in order to meet the desired emission targets. [ABSTRACT FROM AUTHOR]

Damage from climate change is widespread throughout the world. This change has brought about calamities, the most prevalent of which is the emergence of numerous droughts which are increasingly threatening human lives. In this paper, we studied the spatial and temporal variations of drought under the effect of climate change in the Huaibei Plain, which is a very important agricultural zone in China. Drought has attracted increasing attention in research due to its heavy impact on agriculture, the environment, livelihood, and food security. The SPEI (Standardized Precipitation Evapotranspiration Index) has been used in this study to express and identify drought events in the Huaibei Plain due to climate change. A general circulation model (GCM), HadGEM2-AO, which was the most appropriate for the study area's precipitation simulation, and three Representative Concentration Pathways (RCP), RCP 2.6, RCP 4.5, and RCP 8.5, were used to analyze and compare the drought effect for the baseline (1985–2017) and the future climate scenarios (2025–2090). At 3 and 6 months, the SPEI successfully detects agricultural drought in temporal and spatial variation. However, according to the analysis, more severe agricultural drought events are foreseen in the future than in the baseline because of climate change. SPEI performed better than SPI in detecting drought in the baseline and simulated data due to increased evapotranspiration. Between the SPEI-3 and SPEI-6, the Pearson coefficient correlation reveals a positive association. The Mann-Kendall test was used to cover the two studied periods in order to establish the drought trend. Both decreasing and increasing trends, in different timescales, were detected by Sen's Slope in the baseline and future periods with all RCPs. [ABSTRACT FROM AUTHOR]

China has made remarkable achievements in reducing carbon emissions in recent years. However, there is still much reduction room before achieving carbon neutrality. In Beijing, the capital of China, it is a strategic choice to respond to global climate change by promoting green and low-carbon development. This paper calculates the carbon dioxide emissions of key industries in Beijing and analyzes the temporal evolution trend of carbon emissions. Carbon dioxide emissions in Beijing before 2030 are predicted based on the grey prediction GM (1,1) and BP neural network model. The effects of factors of carbon dioxide emissions are discussed using the threshold regression model under different economic conditions. The results show that energy consumption intensity, GDP per capita, and the ownership of civil cars have a positive impact on carbon dioxide emissions, while the number of permanent residents and urban green space areas have a negative impact on carbon dioxide emissions. These findings of carbon emission prediction and influencing factors contribute to carbon reduction path design. Related policy implications on carbon emission reduction are put forward from the aspects of promoting industrial upgrading, accelerating the construction of advanced economic structures, optimizing transportation structures, and strengthening green building development. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Irrigation & Drainage is the property of Journal of Irrigation & Drainage Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In China, irrigation plays a fundamental role in food production, which is hampered by water security, rising population and climate change. To ensure food security and formulate agricultural and irrigation policies, decision-makers need detailed grid-level information on the location of irrigated areas. Unfortunately, this information is not easily available as national irrigation maps are frequently outdated and often have a coarse spatial resolution. In this paper, we present new irrigation maps for China at a spatial resolution of 30 arc seconds (~1 × 1 km) that cover the period between 2005 and 2015. The maps were created using a synergy approach, which combines and integrates regional and global irrigation maps, cropland maps and subnational statistics. The maps were calibrated to subnational irrigation statistics and validated using an external dataset with geocoded information on the location of irrigated areas. The maps show, at the detailed spatial level, how much irrigation expanded over the period of 2005–2015. The proposed synergy approach is flexible and can easily be applied to create irrigation maps for other regions. [ABSTRACT FROM AUTHOR]

In this paper, recent research on terrestrial ecosystem predictability using the conditional nonlinear optimal parameter perturbation (CNOP-P) method is summarized. The main findings include the impacts of uncertainties in climate change on uncertainties in simulated terrestrial ecosystems, the identification of key physical parameters that lead to large uncertainties in terrestrial ecosystem modeling and prediction, and the evaluation of the simulation ability and prediction skill of terrestrial ecosystems by reducing key physical parameter errors. The study areas included the Inner Mongolia region, north–south transect of eastern China, and Qinghai–Tibet Plateau region. The periods of the studies were from 1961 to 1970 for the impacts of uncertainties in climate change on uncertainties in simulated terrestrial ecosystems, and from 1951 to 2000 for the identification of the most sensitive combinations of physical parameters. Climatic Research Unit (CRU) data were employed. The numerical results indicate the important role of nonlinear changes in climate variability due to the occurrences of extreme events characterized by CNOP-P in the abrupt grassland ecosystem equilibrium state and formation of carbon sinks in China. Second, the most sensitive combinations of physical parameters to the uncertainties in simulations and predictions of terrestrial ecosystems identified by the CNOP-P method were more sensitive than those obtained by traditional methods (e.g., one-at-a-time (OAT) and stochastic methods). Furthermore, the improvement extent of the simulation ability and prediction skill of terrestrial ecosystems by reducing the errors of the sensitive physical parameter combinations identified by the CNOP-P method was higher than that by the traditional methods. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was threefold: (1) to measure farmers' health poverty, (2) to examine the effect of health vulnerability on health poverty and (3) to identify countermeasures that may alleviate health poverty in rural China. Design/methodology/approach: This study built a health poverty measurement model based on the multi-dimensional poverty framework to evaluate farmers' health vulnerability. Further, this paper used an econometric model to assess the impact of health vulnerability on health poverty. The sample for this study comprised 1,115 rice farmers from Hubei province, China. Findings: The medical affordability poverty ratio was 17.95%, where farmers in the low-income group faced severe medical affordability poverty (27.46%). Results from the multi-dimensional analysis showed that, the health poverty ratios were 17.95 and 30.50%, respectively. Our results indicated that climate change vulnerabilities, living habits, medical facilities and medical accessibility were positively related to health poverty, whereas the regular physical examinations reduced mental health poverty. Research limitations/implications: Based on this study's findings, we proposed that: (1) to address illness-induced poverty among members of the agricultural community, national and provincial strategies and programs grounded on a multi-dimensional health poverty framework ought to be formulated and implemented, (2) mechanisms of health knowledge exchange may facilitate the improvement of farmers' health status, (3) robust and comprehensive metrics should be employed to understand and improve farmers' ability to absorb and mitigate the negative health impacts and (4) the improvement in both quality and quantity for medical facilities and medical affordability in the rural areas should be key priorities in governmental-wide initiatives. Originality/value: Existing studies for alleviating poverty caused by disease mainly focus on medical service support to those economic vulnerabilities after a disease happens. However, few studies have focused on the root causes of poverty caused by disease, particularly from the preventive perspective of health vulnerability. To fill this gap, this study, therefore, proposes the health poverty index and analyzes the impact of health vulnerability on health poverty. [ABSTRACT FROM AUTHOR]

Carbon peaking and carbon neutrality have become key agendas for countries to participate in global climate change governance. Research on China's carbon peaking has a guidance significance for the actions to achieve a nationwide carbon peaking by 2030. This paper builds a STIRPAT model which, in combination with a scenario -setting method, predicts the carbon peaking time of eight comprehensive economic zones in China, and analyzes the possible path of achieving carbon peaking at national level. The result shows a disparity in carbon peaking time among the zones--there are zones that can achieve carbon peaking under baseline scenario; zones that can achieve carbon peaking under conditional scenarios; and zones that cannot achieve carbon peaking under any scenario. In the first group, the zones can achieve carbon emission through both active path (southwest and eastern coastal comprehensive economic zones) and passive path (northeast comprehensive economic zones) according to characteristics of regional socio-economic development. The second group includes two economic anchors (northern coastal and southern coastal comprehensive economic zones) and an energy-exporting center (the middle reaches of Yellow River comprehensive economic zone). Zones in the third group generally witness a late development (the middle reaches of Yangtze River and northwest comprehensive zones). Based on characteristics of regional economy, population, industry, and energy of each zone, this paper proposes an initiative that the achievement of a nationwide carbon peaking should take regional development equity into consideration, and presumes that making each zone adopts differentiated peaking strategies may have a stronger effectiveness in controlling carbon emission growth than making all zones adopt strategies constraining on single factors on industry or energy. [ABSTRACT FROM AUTHOR]

China is the largest carbon emitter in the world. Understanding carbon emissions of China, especially at the provincial level, will help identify the critical factors behind carbon emissions and effectively implement carbon emission reduction measures. There are significant achievements in the study of carbon emissions of China's provinces. However, there is a gap for improvement in the study from periods and groups' perspectives using a decomposition-clustering method. This paper adopts the Logarithmic Mean Divisia Index (LMDI) to decompose each province's carbon emissions, introduces the elbow and K-means methods to cluster provinces based on the driving factors of decomposition, and analyzes the driving factors of carbon emissions from the view of groups and periods. By analyzing the carbon emissions data of 28 provinces in China from 1998 to 2018, a breakthrough has been found that economic activities and energy intensity were the main driving factors of carbon emissions. Some possible countermeasures, such as optimizing the industrial structure and the energy structure, significantly increasing clean energy consumption, would receive effective carbon emission reduction feedback. The results provide better decision-making support for emission reduction policies in China and contribute to global climate change issues. [ABSTRACT FROM AUTHOR]

China's declaration to the international community to peak CO2 emissions before 2030 and achieve carbon neutrality before 2060 is of great significance in advancing the objectives of the Paris Agreement, and has a positive and far-reaching impact on China's high-quality development. This paper expounds on responsibilities and ambitions in tackling climate change, analyzes the high-quality development opportunities brought about by CO2 emissions peak and carbon neutrality, and discusses the net zero carbon emissions transformation in the new era of ecological civilization. This paper is of the view that development towards net zero carbon emissions provides a new impetus for building a Beautiful China, and promoting ecological civilization and green development. The essence of carbon neutrality should be correctly understood so that the world will work together to improve climate resilience. China should also deepen the understanding of the principles and methodologies of climate change economics. [ABSTRACT FROM AUTHOR]

Drought poses a serious threat to agricultural production and food security in the context of global climate change. Few studies have explored the response mechanism and lag time of agricultural drought to meteorological drought from the perspective of cultivated land types. This paper analyzes the spatiotemporal evolution patterns and hysteresis relationship of meteorological and agricultural droughts in the middle and lower reaches of the Yangtze River in China. Here, the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index products and surface temperature products were selected to calculate the Temperature Vegetation Dryness Index (TVDI) from 2010 to 2015. Furthermore, we obtained the Standardized Precipitation Evapotranspiration Index (SPEI) and the Palmer Drought Severity Index (PDSI) for the same period. Based on these indices, we analyzed the correlation and the hysteresis relationship between agricultural and meteorological drought in rainfed and irrigated arable land. The results showed that, (1) compared with SPEI, the high spatial resolution PDSI data were deemed more suitable for the subsequent accurate and scientific analysis of the relationship between meteorological and agricultural droughts. (2) When meteorological drought occurs, irrigated arable land is the first to experience agricultural drought, and then alleviates when the drought is most severe in rainfed arable land, indicating that irrigated arable land is more sensitive to drought events when exposed to the same degree of drought risk. However, rainfed arable land is actually more susceptible to agricultural drought due to the intervention of irrigation measures. (3) According to the cross-wavelet transform analysis, agricultural droughts significantly lag behind meteorological droughts by about 33 days during the development process of drought events. (4) The spatial distribution of the correlation coefficient between the PDSI and TVDI shows that the area with negative correlations of rainfed croplands and the area with positive correlations of irrigated croplands account for 77.55% and 68.04% of cropland areas, respectively. This study clarifies and distinguishes the details of the meteorological-to-agricultural drought relationship in rainfed and irrigated arable land, noting that an accurate lag time can provide useful guidance for drought monitoring management and irrigation project planning in the middle and lower reaches of the Yangtze River. [ABSTRACT FROM AUTHOR]

Blue-green algae (CyanoHABs), photosynthetic bacteria that create a harmful aquatic environment, have been a trending issue on Taihu for over a decade. CyanoHABs adapt to varying climatic changes, which explains why the problem on Taihu still thrives. One major drive that keeps the algae is Sediment Oxygen Demand (SOD). In this paper, seasonal and spatial variations of SOD that contribute immensely to nutrient growth in Lake Taihu were done using the Environmental Fluid Dynamics Code (EFDC). The results were analyzed based on Nitrogenous SOD (NSOD) and Total SOD (TSOD). Summer results ranged from − 0.05754 to − 0.0826 (− 0.75658 to − 0.83902) (g/m2/day) and Winter values ranged from − 0.3022 to − 0.40171 (− 1.34486 to − 1.48856) (g/m2/day) indicate a gradual decrease in NSOD (TSOD) values respectively. Relatively higher values in summer are attributed to warmer surface water which sets up thermal stratification to increase the internal loading of nitrogen. Lower winter values are related to inverse stratification, where lower oxygen concentration decreases the SOD to trigger ammonium accumulation in the water column. NSOD (TSOD) values for Autumn results ranged from − 0.1039 to − 0.24786 (− 0.96251 to − 1.39454) (g/m2/day) and Spring values of − 0.43019 to − 0.35959 (− 1.48297 to − 0.54089) (g/m2/day). Transition seasons (i.e., Autumn and Spring) results are impacted by wind mixing that allows dissolved oxygen and nutrients in the whole water column. However, spring values depict a gradual increase in SOD value attributed to spring turnover and gradual stratification, which decrease nutrient concentration. In contrast, decreasing SOD values in autumn are related to mixing, but temperature decreases tend to increase nutrient concentrations. Carbonaceous sediment oxygen demand (CSOD), due to sulfide oxidation, presents high values from the difference between TSOD and NSOD. Based on the high values of CSOD, it is highly recommended that more research on eutrophic Taihu lakes would consider delving into CSOD. [ABSTRACT FROM AUTHOR]

While post-disaster rebuilding is an urgent task for affected areas, an approach without consideration for climate protection will probably lead to another disaster of carbon lock-in. Therefore, policymaking and implementation are critically important. This paper takes the Guangyuan prefecture as a case study, where the local government took the lead in low-carbon initiative and made a great contribution to low-carbon development. Based on long-term field investigations and semi-structured interviews, using the theory of multi-level governance, it discusses policy formation and implementation in the Guangyuan prefecture, and how the governance system promoted an environment-and-climate-friendly rebuilding. The results demonstrate the urgency of carbon decoupling in post-disaster-rebuilding and the significance of an effective governance system. This provides insight to the contemporary world that post-disaster rebuilding is not only a revitalization of the affected areas, but a comprehensive undertaking to avoid other possible disasters and ensure a sustainable future. [ABSTRACT FROM AUTHOR]

Understanding the actual heating patterns of air-to-air heat pumps (AAHP) in rural areas is crucial for energy planning and clean-heating policy optimization. To explore the influence of outdoor climate change on occupants' heating patterns when using AAHPs in rural areas, the heating season was classified into three periods: the early heating period (EH), the mid heating period (MH), and the late heating period (LH). The investigation was conducted in rural areas of northern China, and indoor environmental parameters were measured from December 2021 to March 2022. Occupants completed household questionnaires about their heating habits before heating and phone interviews at the end of heating. This paper proposes clustering analysis to identify the AAHP heating pattern in rural areas. The results revealed four typical heating patterns of AAHP utilization. Occupant heating behaviors were dominated by the outdoor temperature fluctuation. In particular, during the mid heating period, the heating operation time periods and the heating duration were longer than that of other heating periods. Moreover, the heating patterns in living rooms were different from that in bedrooms. Room occupancy had an impact on household heating demands. These results could provide guidance for energy planning and the development of clean heating policy in the rural area. [ABSTRACT FROM AUTHOR]

Global climate change has caused governments worldwide to take actions to improve their energy efficiency. This paper investigates how China's Top-1000 program, a command-and-control type of energy-saving mandate, has affected the operational choices of firms, and in turn, their profitability. We apply the propensity score matching method to find "identical twins" for the participants in the Top- 1000 program, then conduct a difference-in-differences analysis on the matched sample. Our findings suggest that the profitability of the enterprises targeted for energy savings decreased by one-third, mainly due to increased production costs. The targeted enterprises tended to increase their fixed assets per capita, which was associated with improvements in energy efficiency. Furthermore, compared to similar untargeted enterprises, there was a significant slowdown in the production growths of the targeted enterprises, raising concerns about carbon leakage due to increased production by less efficient producers. [ABSTRACT FROM AUTHOR]

Since the early 2000s, China has carried out extensive "grain-for-green" and grazing exclusion practices to combat desertification in the desertification-prone region (DPR). However, the environmental and socioeconomic impacts of these practices remain unclear. We quantify and compare the changes in fractional vegetation cover (FVC) with economic and population data in the DPR before and after the implementation of these environmental programmes. Here we show that climatic change and CO2 fertilization are relatively strong drivers of vegetation rehabilitation from 2001-2020 in the DPR, and the declines in the direct incomes of farmers and herders caused by ecological practices exceed the subsidies provided by governments. To minimize economic hardship, enhance food security, and improve the returns on policy investments in the DPR, China needs to adapt its environmental programmes to address the potential impacts of future climate change and create positive synergies to combat desertification and improve the economy in this region. This paper shows that desertification combating practices decline incomes of farmers and herders, and China needs to adapt its ecological programmes to address the impacts of climate change and create positive synergies to combat desertification. [ABSTRACT FROM AUTHOR]

Building a new power system with renewable energy as its main component is a key measure proposed by China to address the climate change problem. Strengthening demand-side management (DSM) is an important way to promote the development of a new power system. As an important economic incentive measure in DSM, the current TOU tariff is faced with the problem of a weak incentive effect due to the small tariff difference between the peak and valley periods. Against this background, a novel hybrid three-stage seasonal TOU tariff optimization model is proposed in this paper. First, the K-means++ algorithm is adopted to select the typical days of the four seasons through load curve clustering. Then, the price elasticity of the electricity demand model is constructed to calculate the self-elasticity and cross-elasticity in four seasons. Finally, the seasonal TOU tariff optimization model is constructed to determine the optimal TOU tariff. Through the proposed model, the tariff in the peak period has increased by 8.06–15.39%, and the tariff in the valley period has decreased by 18.48–27.95%. The result shows that the load in the peak period has decreased by 4.03–8.02% and the load in the valley period has increased by 6.41–9.75% through the proposed model. [ABSTRACT FROM AUTHOR]

Rapid urbanization and climate change are two grand challenges faced by many cities in pursuing sustainable urban development. While ecosystem-based adaptation practices are increasingly recognized and adopted across the world as an important urban development strategy, their effective implementation in diverse biophysical conditions and development contexts is of interest, requiring scientific research and learning. This paper presents the case of China in implementing an ecosystem-based approach – sponge city development – to address the water-related challenges of urbanization and climate change. It draws on the literature to synthesize understanding of the interaction between the urban landscape, urban development, and ecosystem services, and proposes mainstreaming an ecosystem service framework in spatial planning and performance evaluation to guide ecosystem-based adaption practices. Focusing on China's practice, the paper develops a five-step procedure for operationalizing and mainstreaming ecosystem services so as to improve policy implementation for sponge city development. This paper aims to provide a practical perspective to help enhance ecosystem-based adaptation in urban development to better address the challenges of urbanization and climate change. Cities are increasingly looking into ecosystem-based adaptation, as an integrated part of urban development, to increase resilience to climate change and to promote urban sustainability. China's experience with implementing a national initiative called sponge city development contributes to learning and an understanding of ecosystem-based adaptation practices to address urbanization and climate change challenges. Existing literature shows the need and potential for an ecosystem service framework to guide spatial planning and performance evaluation for ecosystem-based adaptation. China is in a unique position to mainstream an ecosystem service framework in sponge city development to improve current practice and to promote climate-resilient and ecosystem-integrated urban development. A five-step empirical procedure outlines a systematic approach for mainstreaming ecosystem services, contributing to the literature and policy practice to build urban resilience and sustainability in the face of urbanization and climate change. [ABSTRACT FROM AUTHOR]

Clues of climate change on the Alashan Plateau since the last glacial period (40 ka) are important for revealing the mechanism of desertification of middle-latitude deserts in the Northern Hemisphere (NH). Studies are still rare for the understanding of the specific relationship of climate changes between the Alashan Plateau and the global. Based on a systematic and comparative analysis of the existing research in China and the international academic community, this paper reviews the environmental evolution history of the Alashan Plateau since the last glacial period from the records of paleo-environment and geomorphological characteristics in different deserts of the plateau (e.g., Badanjilin, Tenggeli, and Wulanbuhe). From about 40 ka to the end of the last glacial maximum, the climate on the plateau was wetter than it is today, and to the end of the Pleistocene, the climate was generally dry and the aeolian activities were enhanced. However, the climate was arid during the whole last glacial period in the Wulanbuhe Desert, evidently different from the overall pattern of the plateau. The Tenggeli Desert was characterized by an arid climate in the early Holocene. The most controversial events for the Alashan Plateau are the drought events in the middle Holocene in the Badanjilin Desert. The role and impact of the westerlies and the East Asian Summer Monsoon (EASM) systems on the climate change of the desert and even the whole plateau is a vexed question that brings different views in different periods. There is still a lack of definite evidence representing the events of global environmental change that occurred on the plateau during the discussed period. The distinctive morphology of dune mountains and the distribution of sand dunes are mutually indicative of the direction and energy of wind systems on the plateau. It is suggested that appropriate wind energy is the significant key to the desertification in these middle-latitude deserts on the plateau. From a global-scale review of climate change, the desertification of the modern-scale sandy desert landscapes on the Alashan Plateau is generally related to the global glacial period and the cold and dry climate during the past 40 ka. [ABSTRACT FROM AUTHOR]

In frequency analysis of annual maximum flood series (AMFS), it is mechanism‐based and significant to incorporate the information of the underlying "ordinary" daily streamflow events for improving accuracy of flood risk estimation and appropriate management. In previous studies related to flood nonstationarity, the classical norming constants method (C‐NCM) has been used to derive statistical parameters of annual maximum flood distribution from daily streamflow distribution. However, C‐NCM does not flexibly consider the feasible range of the scale parameter of annual maximum flood distributions, which can result in the inability to provide sufficient and reliable models to fit AMFS. This paper aims to investigate the potential of two alternative norming constants methods in fitting annual maximum floods, namely the Hall's norming constants method (H‐NCM) and the Fisher and Tippetts' norming constants method (FT‐NCM) respectively. A comparative study of these three methods was carried out using hydrological streamflow series of 77 stations in the Yangtze and Yellow River basins, China. The results found that H‐NCM outperforms both C‐NCM and FT‐NCM for the stations with relatively low‐skewness coefficient of AMFS. Therefore, H‐NCM is recommended to prioritize for practical applications when considering daily streamflow rather than small samples of flood events. Furthermore, if the skewness coefficient exceeds Cs,Gumbel≈1.14, the overall modelling performance of these three methods is significantly deteriorated. This can provide some reference for the applicability of the norming constants method in flood frequency analysis. [ABSTRACT FROM AUTHOR]

The accurate assessment and prediction of forest ecosystem quality is an important basis for evaluating the effectiveness of regional ecological protection and restoration, establishing a positive feedback mechanism for forest quality improvement and restoration policies, and promoting the construction of an ecological civilization in China. Based on the existing studies at home and abroad, this paper mainly analyzes and summarizes the connotation of forest ecosystem quality, assessment index systems, assessment and prediction methods, and outlooks on the existing problems of imperfect forest ecological quality assessment index systems, preliminary assessment and prediction capabilities, and unknown dynamic responses of forest ecological quality to climate change, etc. Efforts should be made to develop a scientific and standardized assessment index system, produce high-quality forest ecological data products, develop localization of assessment model parameters, and explore forest quality–climate change response mechanisms to provide references for in-depth research to realize the transformation of forest ecosystem quality assessments from historical and status quo assessments to future predictions, and to support the construction of a national ecological civilization. [ABSTRACT FROM AUTHOR]

The alpine grassland ecosystem accounts for 53 % of the Qinghai–Tibet Plateau (QTP) area and is an important ecological protection barrier, but it is fragile and vulnerable to climate change. Therefore, continuous monitoring of grassland aboveground biomass (AGB) is necessary. Although many studies have mapped the spatial distribution of AGB for the QTP, the results vary widely due to the limited ground samples and mismatches with satellite pixel scales. This paper proposed a new algorithm using unmanned aerial vehicles (UAVs) as a bridge to estimate the grassland AGB on the QTP from 2000 to 2019. The innovations were as follows: (1) in terms of ground data acquisition, spatial-scale matching among the traditional ground samples, UAV photos, and MODIS pixels was considered. A total of 906 pairs between field-harvested AGB and UAV sub-photos and 2602 sets of MODIS pixel-scale UAV data (over 37 000 UAV photos) were collected during 2015–2019. Therefore, the ground validation samples were sufficient and scale-matched. (2) In terms of model construction, the traditional quadrat scale (0.25 m 2) was successfully upscaled to the MODIS pixel scale (62 500 m 2) based on the random forest and stepwise upscaling methods. Compared with previous studies, the scale matching of independent and dependent variables was achieved, effectively reducing the impact of spatial-scale mismatch. The results showed that the correlation between the AGB values estimated by UAV and MODIS vegetation indices was higher than that between field-measured AGB and MODIS vegetation indices at the MODIS pixel scale. The multi-year validation results showed that the constructed MODIS pixel-scale AGB estimation model had good robustness, with an average R2 of 0.83 and RMSE of 34.13 g m -2. Our dataset provides an important input parameter for a comprehensive understanding of the role of the QTP under global climate change. The dataset is available from the National Tibetan Plateau/Third Pole Environment Data Center (10.11888/Terre.tpdc.272587; H. Zhang et al., 2022). [ABSTRACT FROM AUTHOR]

Financial activity plays an important role in the analysis of environmental and ecological implications. Previous research shows that shadow banking activities, informal and less regulated financial activities, have become an important part of financial systems after the 2008 financial crisis. However, the impact of shadow banking activities on carbon dioxide emissions has been ignored in previous research. In this paper, we use the panel annual data of 30 Chinese provinces over the period 2013–2020 to study the effect of shadow banking activities on carbon dioxide emissions. The result shows that shadow banking activities have a positive impact on carbon dioxide emissions, and the result is still robust by using dynamic panel regression with general method of moments (GMM) method. Heterogeneity analysis shows that the impact of shadow banking activities on carbon emissions is more pronounced for the secondary industry, which proves that shadow banking activities support more for environmentally unfriendly businesses. Furthermore, by using difference-in-difference (DiD) method, we examine the causal effect of shadow banking regulation policy on carbon dioxide emission reduction and demonstrate that the shadow banking regulation can reduce carbon dioxide emissions. Our research contributes to environment protection and achieving the goal of low-carbon economy by exploring the role of shadow banking activities and financial regulation in carbon dioxide reduction. [ABSTRACT FROM AUTHOR]