Search

Only with the three largest emitters (the EU, China and the US) building a coalition was it possible to conclude the Paris Agreement in 2015. With the announced withdrawal of the US, the interdependence between the EU and China has increased significantly. Both actors have reiterated their will to implement the Paris Agreement and to cooperate on climate change. In times of political constraints between the EU and China, this seems puzzling. The paper takes a role‐theoretic perspective to assess the following question: How can the changing roles of the EU and China, ascribed to them by external and internal expectations, explain their increased climate cooperation? It draws on a qualitative text analysis of policy documents and expert interviews. The paper concludes with a discussion of the findings against the backdrop of growing tensions between the EU and China. [ABSTRACT FROM AUTHOR]

Streamflow in semiarid areas, especially in North China, was rapidly decreasing, which made it important to analyze the characteristics and influencing factors of streamflow. Using the hydro-meteorological data series of 1961–2017 in the upper Yongding River Basin (UYRB) (including the Yang River Basin (YRB) and Sanggan River Basin (SRB)), spatio-temporal variation characteristics of air temperature, precipitation, and potential evapotranspiration (E0) were analyzed. The results showed that precipitation has no significant trend; the temperature showed a significant increase of 0.1–0.5 °C per decade; E0 showed a significant decrease of approximately −2 mm/10yr (in 18 stations); the estimated rates of streamflow change were −7 and −8 mm/10yr for SRB and YRB. As for spatial distribution, the YRB presented a higher E0 value than the SRB; the mountain areas had more precipitation than the plain areas. The change points of streamflow occurred in 1982 and 2003. Both the Budyko and the DMC methods were used to evaluate the impacts of climate change and human activities on the mean annual streamflow. In variation stage I (1983~2003), impacts of human activities account for 90.6% and 62.7% of the mean annual streamflow changes in YRB and SRB, respectively. In variation stage II (2004~2017), the percentages were 99.5% and 93.5%, respectively. It is also noted that the first change point in streamflow was indeed at the beginning of China's land reform, when the farmers could manage their reallocated lands and, therefore, there was an increase in agricultural water consumption. The second change point coincided with "Capital Water Resources Planning", including water conservation projects and irrigation district construction programs. In general, human activities were mainly responsible for the significant decline in the annual streamflow of UYRB. This paper will provide valuable results for water resources planning and give guidance on the construction of water conservation function areas and ecological environment support areas in the capital. [ABSTRACT FROM AUTHOR]

With the acceleration of the global response to climate change, increasing attention has been paid to the risks associated with climate change mitigation, such as regulation uncertainties and market interactions. As the country with the greatest CO2 emissions globally, China has launched a national carbon market to speed up its climate mitigation. While the national carbon market provides a platform for regional coalitions to reduce emissions, its incomplete sectoral coverage might allow for the strategic behavior of industries in different regions and ultimately affect the efficiency of the carbon market. This paper explores how the sectoral expansion of the national carbon market affects regional emission reductions in China when emissions trading sectors engage in strategic behavior in the output market. From the sectoral perspective, our numerical results show that the strategic effect in the electricity and steel sectors is more significant than in other sectors. From a regional perspective, the western regions of China, which are mostly permit sale regions, have less strategic power than the eastern regions in the output and carbon markets. Finally, this paper suggests that measures, such as the dynamic adjustment of emission allowance allocation, should be considered by policy makers to prevent the widening of regional economic disparities when extending the sectoral coverage of the carbon market in China. [ABSTRACT FROM AUTHOR]

Though the United States and China emphasize the significance of multilateral frameworks, they have not departed from power politics. As the confrontation between U.S.-led and Chinese-style multilateralism intensifies, the practice of multilateral cooperation based on openness and responsibility is losing ground. In this context, this paper compares U.S.-led multilateralism and Chinese-style multilateralism to examine U.S.-China rivalry in multilateral mechanisms. It then zooms in on the rivalry in the context of the Indo-Pacific region. U.S. President Biden's key strategy in his China policy is represented by the catchphrase "cooperate, compete, confront," dubbed the "3C framework," reflecting the complexities of U.S.-China relations. While the two states tend to show a mix of competition and cooperation relative to global multilateral mechanisms, they exhibit a mix of competition and conflict in the Indo-Pacific. The paper analyzes recent United States and Chinese approaches towards topical multilateral issues: on climate change issues for the former and on cybersecurity and advanced technology for the latter. [ABSTRACT FROM AUTHOR]

In the context of global warming, snow cover changes have an extremely important impact on the hydrological cycle and the redistribution of water resources in arid and semi-arid regions. In this paper, based on the daily cloud-free snow area remote sensing product data in the source region of Yangtze River (SRYR) from 2000 to 2019, the snow phenology variables such as the snow cover day (SCD), snow onset date (SOD), snow end date (SED), and snow duration day (SDD) were extracted separately for each hydrological year, and the vertical distribution of snow cover area (SCA) in the SRYR was analyzed by combining with the digital elevation model (DEM). In addition, we also combined climate factors and land cover types to further explore the spatiotemporal variation characteristics of snow phenology in response to different influencing factors, in order to reveal the spatiotemporal variation patterns of snow cover in the SRYR. The results showed that: (1) The SCA in the SRYR has a more obvious vertical distribution, with the maximum SCA reaching 61.58% at high elevation, while at low elevation, the SCA is mostly below 20%. The distribution of SCD in the study area showed a significant exponential correlation with DEM (R2 = 0.87). (2) The area of SOD in the SRYR showed an advanced trend of about 63.37%, while the area of SED showed a delayed trend of about 69.59%, and the area which showed significant trends is 4.29% and 4.36%, respectively. Therefore, the trends of both SOD and SED showed insignificant changes. (3) Temperature change is the main factor affecting the change of snow cover in the SRYR. Among them, 90.9% of the regions showed a significant positive correlation between temperature and SCD, while precipitation showed a significant negative correlation with SCD in about 75.3% of the total area of SRYR. Under the stable snow area (SCD > 60), the land cover type is glacial or permanent snow about 1.5 × 103 km2, which covers almost the entire glacial or permanent snow of the SRYR. [ABSTRACT FROM AUTHOR]

This paper examines the life-cycle wind resistant performance of a constructed long-span suspension bridge in the coastal region of China, aiming to quantify the multisource time-variant effects and uncertainties and offering a reference for designs of long-span bridges in the future. Randomness from modal frequencies, damping ratios, and identification uncertainty of flutter derivatives (FDs) was considered; then, their effects on probability of flutter failure and probability of exceeding the predefined buffeting response root-mean square (RMS) are discussed. Firstly, results of full-track tropical cyclone (TC) simulation under various climate warming scenarios are reviewed; then, the time-variant probability density function (PDF) of annual extreme wind speed is discussed. Secondly, 6-year modal frequencies and damping ratios of a long-span suspension bridge with a center-slotted section were extracted by fast Bayesian FFT method with structural health monitoring (SHM) data, which were utilized to explore the deterioration rules of structural properties. Thirdly, FDs were modeled from a probabilistic perspective based on complex Wishart distribution, which were identified in the turbulent flow and the frequency domain by Bayesian inference. The posterior distributions of FDs, namely identification uncertainty, were quantified by Markov chain Monte Carlo (MCMC) sampling. This paper finds that for flutter resistant performance, the time-variant effects (i.e., modal frequencies and PDFs of extreme wind speed) will make the flutter failure probability seven times larger than the initial value; for the probability of exceeding the predefined buffeting response RMS, however, the time-variant effects will make a negligible difference. [ABSTRACT FROM AUTHOR]

The problem of global climate change is a common problem faced by all countries, and developing countries will face heavier pressure to reduce carbon emissions while promoting economic development. China is currently in a period of economic transformation, and the contradiction of industrial structure upgrading is becoming more and more prominent. The unreasonable industrial structure has caused a large consumption of resources, hindering the optimal allocation of resources and affecting carbon emissions. Technological innovation is an important force to cope with environmental changes, promote economic growth, and improve comprehensive competitiveness. Can technological innovation achieve carbon emission reduction under industrial structure upgrading? In this paper, industrial structure upgrading, technological innovation, and carbon emissions are studied together, and the impact of industrial structure upgrading, technological innovation on carbon emissions is theoretically analyzed, as well as how industrial structure upgrading acts on carbon emissions through technological innovation. An empirical test is conducted using 30 provincial panel data in China from 2005 to 2017, and it is found that industrial structure upgrading can reduce carbon emissions. An econometric analysis based on the mediating effect model finds that industrial structure upgrading has both a direct carbon emission reduction effect and a mediating effect of reducing carbon emissions through technological innovation, and the mediating effect of technological innovation in reducing carbon emissions remains significant in the regression analysis of sub-regions. Based on the research of this paper, it is suggested that the advanced development of industrial structure should be promoted, the rationalization of industrial structure should be promoted, the innovation development strategy should be firmly implemented, and the level of technological innovation should be promoted. [ABSTRACT FROM AUTHOR]

To achieve carbon peak targets, realize carbon neutrality vision, and tackle global climate change, China must improve the carbon emission performance at the city level. Based on the carbon emission performance of 191 prefecture-level cities in China from 1997 to 2017, this paper analyses the evolution characteristics of urban carbon emission performance from three aspects: the overall spatial and temporal evolution, the differences according to both region and city size, and the differences among clusters categorized by carbon emission performance at the city level. This paper also reveals the impact of the social and economic transition on China's carbon emission performance. The results show that: (1) The overall level of carbon emission performance of Chinese cities is low, and there is a downward trend during the study period. The differences in carbon emission performance among cities are convergent, but there is a wide gap between high and low values. (2) The carbon emission performance of cities in eastern coastal areas is higher than that in non-coastal areas cities. Large urban agglomerations and economically developed regions, such as provincial capitals, are the agglomeration areas of high urban carbon emission performance values. (3) The carbon emission performance level of cities with similar sizes will converge. At the same time, such changes will enhance the differences among carbon emission performances at the city level within the same region. (4) Cities that belong to high urban carbon emission performance clusters are mainly distributed in the eastern region. Such cities are classified into large cities, supercities, and megacities. Compared with low urban carbon emission performance clusters, cities in high urban carbon emission performance clusters show a higher proportion in the medium-high level and high level of carbon emission performance. Moreover, cities in high urban carbon emission performance clusters are more likely to improve theirurban carbon emission performance. (5) The economic agglomeration effect, industrial structure adjustment and carbon intensity reduction have a significant impact on improving urban carbon emission performance. Population agglomeration has an incremental effect, and the anticipated benefits of environmental regulation have yet to be fully realized. The impacts of different clusters and different regions are variable. Finally, this paper advances policy enlightenment according to its research findings. [ABSTRACT FROM AUTHOR]

Simple Summary: This paper analyzed the different relationships between earlywood and latewood as well as total tree-ring growth and the climate factors and reconstructed 106 years of May–June mean temperature (TMJ) in the Tongbai Mountains based on the earlywood width chronology of Pinus taiwanensis Hayata. It also analyzed the linkages to the Indian and Pacific Oceans. This paper found that earlywood width chronology has better response to the climate factors than latewood width and total tree-ring width. This study also found that the main limiting factors that restrained radial growth of Pinus taiwanensis Hayata in the Tongbai Mountains were May–June mean temperature and mean maximum temperature. The reconstructed TMJ series have a better reliability and are significantly negatively correlated with sea surface temperature (SST) over the tropical Western Pacific Ocean and Indian Ocean and are significantly positively correlated with SST over the subtropical Pacific Ocean. Finally, the periodic fluctuations of TMJ in the Tongbai Mountains might be related to the quasi-biennial interannual oscillation of SST over the Indo-Pacific equatorial region (QBO). The results of this study are significant for further understanding and exploring forest growth and climate change in the climatic transition zone. The Tongbai Mountains are an ecologically sensitive region to climate change, where there lies a climatic transitional zone from a subtropical to a warm–temperate monsoon climate. The northern boundary of Pinus taiwanensis Hayata is here; thus, climate information is well recorded in its tree rings. Based on developed earlywood width (EWW), latewood width (LWW) and total ring width (RW) chronologies (time period: 1887–2014 year) of Pinus taiwanensis Hayata in the Tongbai Mountains in central China, this paper analyzed characteristics of these chronologies and correlations between these chronologies and climate factors. The correlation results showed that earlywood width chronology contains more climate information than latewood width chronology and total ring width chronology, and mean temperature and mean maximum temperature in May–June were the main limiting factors for radial growth of Pinus taiwanensis Hayata. The highest significant value in all correlation analyses is −0.669 (p < 0.05) between earlywood width chronology and May–June mean temperature (TMJ) in the pre-mutation period (1958–2005) based on mutating in 2006. Thus, this paper reconstructed May–June mean temperature using earlywood width chronology from 1901 to 2005 (reliable period of earlywood width chronology is 1901–2014). The reconstructed May–June mean temperature experienced eight warmer periods and eight colder periods and also showed 2–3a cycle change over the past 105 years. The spatial correlation showed that the reconstructed series was representative of the May–June mean temperature variation in central and eastern China and significant positive/negative correlation with the sea surface temperature (SST) of the subtropical Pacific Ocean and the tropical Western Pacific Ocean and Indian Ocean from the previous October to the current June. This also indicated that May–June mean temperature periodic fluctuations might be related to the quasi-biennial oscillation (QBO) in the tropical Western Pacific Ocean and Indian Ocean. The results of this study have extended and supplemented the meteorological records of the Tongbai Mountains and have a guiding significance for forest tending and management in this area. [ABSTRACT FROM AUTHOR]

Rivers have been under sampled to establish them as sinks or sources of the atmospheric carbon oxide (CO2). Such poor coverage is well known for tropical and sub-tropical, particularly monsoon driven rivers. An unprecedented high-temporal-resolution (daily) sampling during July 2008-August 2009 were conducted from the Longchuanjiang River of the upper Yangtze basin, a subtropical monsoon river in China to reveal the daily-to-seasonal dynamics of the partial pressure of CO2 (pCO2) and CO2 degassing flux from the river. The pCO2 levels were supersaturated in CO2 with respect to atmospheric equilibrium (380 µatm) during the entire survey period with obvious daily and seasonal variations, ranging from 450 to 63000 µatm with an average of 3900 µatm. pCO2 values in the surface water in the wet season were relatively low, except flooding period in November, due to a dilution effect by heavy rainfall. However, both daily and monthly minimal and maximal pCO2 also occurred in this period. In contrast, the pCO2 levels in the dry season were much higher, mainly resulted from lower pH by anthropogenic activities. Net CO2 flux and pCO2 were strongly correlated with pH, but weakly with water temperature, dissolved inorganic carbon and water discharge, and uncorrelated with particulate nutrients and biogenic elements. The estimated water-to-air CO2 degassing flux in the Longchuanjiang River was about 110 mol m-2 yr-1, with the upper limit of 460 mol m-2 yr-1. Our study also indicated that among the total organic carbon remobilized through soil erosion, around 17% (11 400tC yr-1) of was emitted to the atmosphere, 52% (35 000tC yr-1) deposited in the river-reservoirs system and 31 % (21 000tC yr-1) exported further downstream. High spatial and temporal resolution of estimates of CO2 emission from the world large rivers is required due to that catchment characteristics and anthropogenic activities are extremely heterogeneous in space and time. [ABSTRACT FROM AUTHOR]

The Chinese government has established carbon emissions trading schemes (CETS) to cope with climate change and reduce carbon emissions. This paper uses the multi-period difference in difference (DID) model to explore the impact of CETS on cities' GDP and GDP growth rates in China based on data from 285 prefecture-level cities from 2008–2019. We find that CETS increase the level of GDP by 3.4% and the GDP growth rate by 0.004. The mechanism of increasing GDP includes promoting investment and innovation, and the mechanism of increasing the GDP growth rate includes only promoting the investment growth rate. Thus, CETS satisfy both the weak and strong versions of the Porter Hypothesis from the GDP and growth rate perspectives. In the heterogeneity analysis, we find that the impacts of CETS on cities' GDP and GDP growth rates decrease with the increase of the corresponding dependent variable. In the spatial spillover analysis, we find that the establishment of CETS has a positive spillover effect on the GDP of cities around 50 km and 150 km, and a negative spillover effect on the GDP of cities around 200 km, but there is no spatial spillover effect on the GDP growth rate. [ABSTRACT FROM AUTHOR]

Climate change is directly linked to a broad array of changes because of disorganized activities within the economic system and human intervention. Climate change affects the well-being status of both non-living and living things. Relevant policies to mitigate and adapt to climate change conditions concentrate on solutions that intend to use renewable energy instead of fossil fuels or other conventional energy sources. This study aims to process a review focused on how renewables advance environmental quality and create relevant benefits within severe economic activities. This study elaborates on the case of China for two main reasons. First, China has a pivotal role in the economic system worldwide. Second, China is making serious attempts to transition into a low-carbon economy. An integrative review was processed to receive selected publications. The advantage of this process is that it considers empirical and non-empirical studies, policy papers, and conceptual frameworks. Inclusion and exclusion criteria were applied to retrieve the final number of publications. Review results from 39 well-acknowledged Journals provided 180 selected publications categorized into seven study groups: data analyses, model optimization studies, market issues, renewable energy technology publications, nuclear energy publications, ocean energy publications, and policy-related studies. Policy implications concern China's efforts to accelerate the integration of renewables in the energy mix. Hence, the country should increase energy efficiency in consumption and process investment plans based on robust research and development efforts. [ABSTRACT FROM AUTHOR]

The arid endorheic basin of northwest China is characterized by rich land resources, water shortage, and a fragile ecological environment. The establishment of a credible coupling model of groundwater and surface water based on multi-source observation data is an effective means to study the change in basin water cycles and the sustainable utilization of water resources in the past and future. Based on the latest understanding of hydrogeological conditions, hydrology and water resource utilization data in the middle reaches of the Heihe River Basin (HRB), this paper constructs an up-to-date coupling model of surface water and groundwater to study the water balance change of the basin. The water resources data series under historical replay and CMIP5 climate model prediction are constructed to predict future changes in water resources. The study shows that, under the joint influence of natural conditions and human activities, the average annual recharge of groundwater in the study area from 1990 to 2020 is 17.98 × 108 m3/a, the average annual discharge is 18.62 × 108 m3/a, and the difference between recharge and discharge is −0.64 × 108 m3/a. The total groundwater storage is −19.99 × 108 m3, of which the groundwater storage from 1990 to 2001 was −17.52 × 108 m3 and from 2002 to 2020 was −2.47 × 108 m3. Abundant water from 2002 to 2020 in the basin significantly improved the loss of groundwater storage. Under the prediction of historical reappearance and the CMIP5 CNRM-CM5 model RCP4.5 and RCP8.5 pathways, the groundwater level of the Heihe River–Liyuanhe River inclined plain falls first because the HRB has just experienced a wet season and then rises according to future climate change. The groundwater level of the inclined plain east of the Heihe River and Yanchi basin decreases continuously because of the change in water cycle caused by human activities. The erosion accumulation plain is located in the groundwater discharge zone, and the water level is basically stable. Under the conditions of water resource development and utilization, the runoff of Zhengyixia hydrological station cannot meet the requirements of the "97 Water Dividing Plan" of the State Council in most years in the future, and the ecological and production water in the lower reaches of HRB cannot be effectively guaranteed. With the implementation of water-saving irrigation under the RCP4.5 and RCP8.5 scenarios, the runoff of Zhengyixia can meet the "97 Water Diversion Plan". It is suggested to further improve the level of agricultural water savings in the middle reaches of the HRB and control the reasonable scale of cultivated land in order to reduce water consumption in the middle reaches of the HRB and implement sustainable utilization of water resources in the HRB. [ABSTRACT FROM AUTHOR]

China has established three rounds of low-carbon pilot city initiatives. However, a gap exists between policy making and successful implementation, and the effects on greenhouse gas (GHG) emission reduction were found to be different among pilots. This paper considers the question of how low-carbon policies in cities can be implemented effectively and how policy combinations are adopted for GHG emissions reduction. It uses a mixed research approach, including Qualitative Comparative Analysis (QCA) and field investigation in Pilot Y (situated in the southwest China). The results show that, first, financial support and monitoring systems are necessary conditions, while political leadership is a sufficient condition. This means that the absence of financial support or monitoring systems could lead to increased GHG emissions, while the presence of political leadership always promotes the reduction of GHG emissions but may not be sufficient on its own to achieve them. Second, the target responsibility system (TRS) – a system used by higher government levels to assess the policy implementation of lower government levels – and human resource mechanisms cannot effectively lead to the promotion of GHG emissions reduction. Finally, in the absence of TRS and human resource mechanisms, environmental information disclosure (EID) was found to effectively promote low-carbon urban development by encouraging public participation. This paper reveals the complexity of the implementation of low-carbon policies in cities, identifies the link between city-level and national action, and enriches the theoretical explanation of governance and low-carbon policy implementation gaps in China. Key policy insights China's low-carbon pilot city project is critical for reducing GHG emissions, however, the effects of the low-carbon pilot city programmes varied greatly. Financial support and monitoring systems are necessary conditions, while political leadership is a sufficient condition to achieve cities' GHG emissions reduction goals. Local low-carbon development is limited and not put into practice at the city level in China, in part because of the absence of financial support and limited political attention. This study highlights the key conditions of organizational behaviour at the meso-level, and enriches the theoretical explanation of environmental policy implementation gaps in China. [ABSTRACT FROM AUTHOR]

The Qinghai–Tibet Plateau is a unique global natural geographical unit with a high altitude and fragile ecology, where land cover change has been affecting its regional ecological security and sustainable development. The plateau covers nine countries with different variations in climate change and human activities, which cause significant spatial variations in its land cover change. This paper uses land cover data to reveal the spatiotemporal characteristics and multi-country differences in land cover change on the Qinghai–Tibet Plateau from 1992 to 2020 by applying spatiotemporal characteristic analysis and mapping methods. The results show that grassland (65.70%), bare land (15.56%), and woodland (10.25%) are the main types of land cover on the plateau, accounting for 91.51% of the total area. The interconversion of bare land and grassland was dominant in 1992–2020, with an area share of 67.83%. The turning point year of grassland change occurred in 2015. The grassland area increased by 6312 km2 in 1992–2015, while it decreased by 14,646 km2 in the plateau in 2015–2020. The areas of woodland, cropland, and water increased by 2.77%, 5.85%, and 7.57%, respectively, and the area of built-up land increased from 299.17 km2 to 1206.29 km2. Overall, a warming and wetting trend of the climate in the Qinghai–Tibet Plateau has driven the expansion of natural vegetation and water in the central plateau within China, with its natural vegetation area increasing by 0.11%. However, the development of regional warming and drying caused local grassland degradation, where Kyrgyzstan and India within the Qinghai–Tibet Plateau experienced the most prominent vegetation degradation. Human activities are relatively frequent in the Qinghai–Tibet Plateau within China and India, causing higher growth rates of built-up land and cropland than in other countries. The establishment of reserves and effective forest management policies have led to significant increases in woodland areas in China and Nepal within the plateau, while weak forest management and limited investment in forest conservation have led to high rates of deforestation in India and Myanmar. Accelerated temperature rises and regional differences in precipitation are the main drivers of large-scale land cover change on the plateau and differences in human activities and land use policies are responsible for the dramatic and diverse localized land cover change. [ABSTRACT FROM AUTHOR]

The Chinese government's use of fiscal policy, which includes fiscal income and spending, is crucial in its fight against environmental pollution and climate change. Innovation‐driven has arisen as a new alternative to reconcile economic success with environmental conservation in light of tighter resource restrictions and the suggestion of the Chinese High‐quality Development policy. The paper uses an econometric model to examine the connection between institutional resource consumption efficiency and carbon neutrality, using a data set consisting of Chinese inter‐provincial panel data from 2007 to 2020 as a research sample; fiscal decentralization is also discussed as a potential moderating factor. Collaborative innovation positively boosts ecological efficiency and produces geographical spillovers, and the findings suggest so long as the economic distance is considered. When it comes to increasing ecological efficiency, collaborative innovation plays a more important role than financial decentralization alone. Among these is the improvement of carbon neutrality, which is best achieved via the joint promotion of ecological efficiency and industrial organizations. By reducing the intensity of the positive effect of innovative cooperation on ecological efficiency, the moderating effect suggests that fiscal decentralization is a critical factor in this relationship. Promoting China's ecological efficiency necessitates a fair distribution of local budgetary spending. China should also actively encourage the degree of synergy between institutional resource consumption efficiency and associated institutions to improve eco‐efficiency. [ABSTRACT FROM AUTHOR]

The Chinese government continues to contribute to tackling the global climate challenge and plans to continue lowering carbon emissions in the transportation infrastructure field. The comprehensive assessment of the impact of carbon emissions is mainly focused on high-speed railways (HSRs). This paper proposes a life-cycle cost considering carbon emissions (LCCCCE) model for HSR projects, which consists of a general life-cycle cost (GLCC) model and a quantified carbon emissions cost (CEC) model. The Beijing-Shanghai HSR is employed as a case study, in which the LCCCCE and sensitivity of carbon emission factors are analyzed using the proposed methodology. The results show that the LCCCCE of the Beijing-Shanghai HSR is 64.56 billion USD, and that its CEC is 1.04 billion USD, which contributes 1.61% to the LCCCCE. Thus, the LCCCCE analysis of HSRs or transportation infrastructure projects is an effective methodology to quantify the impacts of carbon emissions in China and around the world. [ABSTRACT FROM AUTHOR]

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]

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.)

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]

In this paper, climate change in the Jinping area is investigated. The climate change trend in the Jinping area is studied by plotting the porosity value of the carbonate rocks as a curve. By comparing the curve established using the climate change data from published articles, it is found that the B value curve obtained using the saddle line is the closest to the curve established using the climate change data from published articles. This shows that the carbonate porosity in the Jinping area obtained using an image analysis technique can be used for climate change research., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Kuang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

An ambitious new Post-2020 Global Biodiversity Framework "Kunming-Montreal Global Biodiversity Framework" has been developed. However, the combined effects of climate change and human modification can undermine the potential benefits of the global post-2020 conservation efforts. The co-benefits of stabilizing the climate, conserving biodiversity, and maintaining intact wilderness areas may help to persuade the general public of the need to quickly expand existing protected areas (PAs). To maximize the co-benefits after 2020, the careful optimization of existing (PAs) network and scientific identification of conservation targets are both essential. Here, we mapped hotspots of biodiversity, climate vulnerability, and wilderness in Southwest China (SWC). By analyzing the representativeness and gaps of the existing PAs network in SWC, we devised post-2020 conservation targets and highlighted their implications for decision-makers. Our results showed that the incongruence between hotspots of different species exists, indicating that habitats suitable for one taxon may not fully harbor other taxa. According to our assessment, the five jurisdictions of SWC have warmed on average by 0.4°C-1.1 °C over the past 60 years alone. In particular, biodiversity hotspots in SWC are undergoing stark climatic changes. We uncovered prominent conservation gaps in SWC's network of PAs, especially in terms of climate vulnerability and biodiversity. Due to their insufficient number and unreasonable spatial distribution, the PAs network in SWC may be not capable of meeting its biodiversity, climate vulnerability, and wilderness conservation objectives. To rectify this, we proposed a 3-step mission: milestone 2025, milestone 2030, and goal 2050, which aims to protect 23%, 28%, and 60% of the terrestrial area in SWC, respectively. Taken together, our study derived conservation priority areas with relatively clear spatial boundaries and importance levels, thus providing detailed, timely information for decision-makers to expand the PAs network and implement conservation measures varying in strictness in post-2020 conservation practice., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Quantify the relative effects of climate change and human activities on vegetation cover can help us understand the vegetation cover change and its drivers. Residual analysis, defined as the difference between potential normalized difference vegetation index (NDVI pot ) and observed normalized difference vegetation index (NDVI act ), was used to solve this problem. The estimation of NDVI pot is one of the important issues faced by ecologists. Due to the strictly protection of environment and ecosystems, the ecosystems in nature reserves are rarely disturbed by human activities. Therefore, establishing NDVI pot estimation model based on nature reserves can improve the estimation accuracy of NDVI pot . However, the estimation of NDVI pot based on nature reserves has not yet been reported. In this paper, the NDVI pot estimation model was established based on nature reserves, and residual analysis was used to quantify the impact of human activities on NDVI act . The results show that the NDVI act in Nanjing metropolitan area (NJMA) showed a significant upward trend from 2000 to 2019, and 74.20% of NJMA showed greening trends, while 24.47% showed browning trends. The temperature and precipitation were positively correlated with normalized difference vegetation index (NDVI), and the impact of the temperature on NDVI was greater than that of precipitation. The promotion of human activities on NDVI had become more and more significant. There was 51.88% of NJMA where the human activities had a positive promotion effect on NDVI, while there was 46.29% of the regional where the human activities had a negative inhibitory effect on NDVI. The population density (POP) and gross domestic product (GDP) were mainly positively correlated with NDVI, and the impact of the POP on NDVI was greater than that of GDP. The conversion of cropland to forests and the increase of the sown area of crops also caused the NDVI to increase, while the disorderly expansion of urban land caused the NDVI to decrease., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Climate change is closely related to the distribution of plant resources. Cerasus serrulata is an important plant resource in China. The study on the influence of environmental factors on the distribution of suitable areas of C. serrulata is conducive to the protection and development of C. serrulata. In this paper, the distribution information of 238 Chinese Cerasus serrulata plants was processed by DIVA-GIS. The MaxEnt model was used to simulate the current and future distribution, and the ecological distribution and richness of Cerasus were analyzed. The results showed that the Cerasus serrulata was widely distributed in Hebei, Heilongjiang, Shandong, Jiangsu, Zhejiang, Anhui, Jiangxi, Hunan, and Guizhou provinces, mainly in the low and middle elevation areas of 10 to 1200 m. Based on this model, the precipitation of the warmest quarter, the precipitation of the driest month, and the mean temperature of the coldest were the most significant bioclimatic variables affecting the distribution of C. serrulata. In the future, climate change may lead to a slight increase of 2.31% in the area of suitable habitat for Cerasus serrulata, while the optimal habitat will decrease from 20.81 to 14.55%. Therefore, conservation measures should be taken to protect these precious resources., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Forests influence climate through both the biochemical and biophysical processes, and the impacts of the latter on local climate may be much larger than the former. However, the biophysical effects of afforestation in arid regions have received little attention compared with afforestation in the tropic, temperate and boreal zones. In this study, we combined in situ eddy covariance flux measurements from a neighboring pairs of forested and background desert sites with the decomposed temperature metric (DTM) method to characterize the impacts of arid forests on surface temperature (T s ). A clear-sky, one-dimensional planetary boundary layer (PBL) model was used to estimate the impacts of afforestation on state of regional climate. We showed that despite absorbing more net radiation (35.4 W m -2 ) the riparian forests tended to cool T s (-1.28 °C) on annual basis, but with a significant seasonality. Specifically, afforestation may lead to a net cooling effect from March to September and a slightly warming effect in other months. The DTM method revealed that evapotranspiration played a dominant role in cooling surface temperature, while surface albedo (α) and incoming longwave radiation (L↓) acted together to increase forest surface temperature. From June to September, a shallower, cooler and wetter boundary layer was developed over the forest due to high plant transpiration. In other months, the PBL was slightly deeper and warmer over the forest than that over the desert. Therefore, the riparian forests were important in moderating warming trends in arid regions., Competing Interests: Declaration of competing interest We declared that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work. All authors have agreed the submits of this paper to your Journal. We declared that we will not submit this paper to another Journal until we hear from you., (Copyright © 2022. Published by Elsevier B.V.)

The Budyko-based elasticity method has been widely employed to clarify the driving factors behind runoff changes. However, different formulations of the Budyko framework could produce biases in the elasticity analysis and the assessment errors induced from different formulations of the Budyko framework in the elasticity method remain unclear. Here, we attempt to address this issue by validating the performance of elasticity methods derived from two analytical Budyko equations (Fu's equation and Choudhury's equation), as well as one empirical Budyko equation (Wang-Tang's equation) of the Budyko framework across 22 basins in China. Validations show that the runoff change simulated by the elasticity method derived from the empirical equation has lower errors compared with the two analytical Budyko equations. Results reveal that in the semi-humid environment, the alteration of basin characteristics takes the main responsibility for the runoff change. However, a clear divergence was found in simulated runoff changes among different Budyko-based elasticity methods in humid basins. For parts of the humid basin, the precipitation is the main driver of runoff change from the analytical Budyko-based elasticity methods, while the alteration of basin characteristics is the main derive of the runoff changes according to based on the empirical Budyko-based elasticity method. This difference could be attributed to the variations in the simulated contributions from the alteration of basin characteristics on runoff changes. Generally, our results highlight the importance of validating different Budyko equations when applying the elasticity method to investigate the driver of the runoff changes in humid regions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Carbon dioxide (CO 2 ) emissions are considered a significant factor that results in climate change. To better support the formulation of effective policies to reduce CO 2 emissions, specific types of important emission patterns need to be considered. Motivated by the flock pattern that exists in the domain of moving object trajectories, this paper extends this concept to a geographical flock pattern and aims to discover such patterns that might exist in CO 2 emission data. To achieve this, a spatiotemporal graph (STG)-based approach is proposed. Three main parts are involved in the proposed approach: generating attribute trajectories from CO 2 emission data, generating STGs from attribute trajectories, and discovering specific types of geographical flock patterns. Generally, eight different types of geographical flock patterns are derived based on two criteria, i.e., the high-low attribute values criterion and the extreme number-duration values criterion. A case study is conducted based on the CO 2 emission data in China on two levels: the province level and the geographical region level. The results demonstrate the effectiveness of the proposed approach in discovering geographical flock patterns of CO 2 emissions and provide potential suggestions and insights to assist policy making and the coordinated control of carbon emissions.

Leaf phenology is one of the most reliable indicators of global warming in temperate regions because it is highly sensitive to temperatures. Temperature sensitivity (S T ) is defined as the values of changed days of leaf flushing date (LUD) per degree increase in temperatures. Climate warming substantially advanced LUD in the temperate region, but its effect on S T of LUD is still not clear. We used spring phenological records of 12 woody plants in eastern China in the years of 1983-2014 to explore temporal and spatial changes of LUD and S T . Furthermore, we compared the difference of S T and preseason temperatures in two periods (1983-1997 and 2000-2014), and explored the main factors regulating S T . The results showed that the average LUD significantly advanced (-2.7 days per decade). The mean LUD over the period 1983-2014 was in day of the year (DOY) 87 ± 7 across sites and species for the early leaf flushing species (EFS), and mean DOY 102 ± 5 for the late leaf flushing species (LFS). LUD was earlier in low latitude than that in high latitude. S T of Armeniaca vulgaris was the most sensitive to temperature across all sites (-3.66 d °C -1 ), while Firmiana simplex was the most insensitive (-2.37 d °C -1 ). LUD of EFS was more sensitive to temperature warming than that of LFS. At the same site, LUD of EFS would advance more obviously than that of LFS under global warming. For all species, S T decreased significantly with shorter preseason length and warmer temperatures at the preseason end. Our results had demonstrated a strong relationship between S T and the preseason length (mean temperature at the preseason end)., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Quantifying the contributions of climate change (CC) and human activities (HA) to vegetation change is crucial for making a sustainable vegetation restoration scheme. However, the effects of extreme climate and time-lag and -accumulation effects on vegetation are often ignored, thus underestimating the impact of CC on vegetation change. In this study, the spatiotemporal variation of fractional vegetation cover (FVC) from 2000 to 2019 in northern China (NC) as well as the time-lag and -accumulation effects of 15 monthly climatic indices, including extreme indices, on the FVC, were analyzed. Subsequently, a modified residual analysis considering the influence of extreme climate and time-lag and -accumulation effects was proposed and used to attribute the change in the FVC contributed by CC and HA. Given the multicollinearity of climatic variables, partial least squares regression was used to construct the multiple linear regression between climatic indices and the FVC. The results show that: (1) the annual FVC significantly increased at a rate of 0.0268/10a from 2000 to 2019 in all vegetated areas of NC. Spatially, the annual FVC increased in most vegetated areas (∼81.6 %) of NC, and the increase was significant in ∼54.6 % of the areas; (2) except for the temperature duration (DTR), climatic indices had no significant time-lag effects but significant time-accumulation effects on the FVC change. The DTR had both significant time-lag and -accumulation effects on the FVC change. Except for potential evapotranspiration and DTR, the main temporal effects of climatic indices on the FVC were a 0-month lag and 1-2-month accumulation; and (3) the contributions of CC and HA to FVC change were 0.0081/10a and 0.0187/10a in NC, respectively, accounting for 30.2 % and 69.8 %, respectively. HA dominated the increase in the FVC in most provinces of NC, except for the Qinghai and Neimenggu provinces., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier B.V.)

Average climatic events describe the occurrence of weather or climate at an average value, whereas extreme events are defined as events that exceed the upper or lower threshold value of statistical or observational average climatic events. This study investigated the impacts of both average climate change (ACC) (i.e., average precipitation, temperature, and potential evapotranspiration [PET]) and extreme climate change (ECC) (i.e., five precipitation and five temperature extremes) on dryland vegetation based on the Normalized Difference Vegetation Index (NDVI). The spatial divergences of ACC and ECC in affecting changes in NDVI over drylands were determined using the geographical detector model. In this study, the growth of vegetation in 40.29 % of global drylands was driven by average precipitation and this dominant effect also occurred in all the plant species, particularly shrubs. However, the sensitivity of grassland to average precipitation exceeded that of most of the woody vegetation. The average temperature and PET controlled 28.64 % and 31.07 % of the changes in NDVI, respectively. Precipitation extremes (except for consecutive dry days and consecutive wet days) and warm temperature extremes (WTE) had positive influences on dryland vegetation, and the effect of WTE on NDVI exceeded that of the remaining temperature extremes. Temperature extremes exerted more significant effects than precipitation extremes for changes in the grassland NDVI. In contrast, the variations in shrub NDVI were primarily dominated by precipitation extremes. We also found that the impacts of parts of average and extreme climatic factors on vegetation had changed over time. Furthermore, temperature extremes had far exceeded the average temperature in affecting vegetation growth at the spatial scale, and this action gradually intensified from 1982 to 2015. The influences of all precipitation extremes were weaker than those of the average precipitation. Those can offer scientific references for ecosystem protection in drylands., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Global climate change is rooted in the imbalance between carbon sources and sinks, and net-zero greenhouse gas emissions should focus not only on the source-side drivers but also on the sink-side influencing factors. Taking the county-level administrative districts in China as the sample, this study uses machine learning models to fit the relationship between socioeconomic development (SED) and net primary productivity (NPP) of terrestrial ecosystems. Moreover, it identifies key influencing factors and their effects based on the SHapley Additive exPlanations (SHAP) algorithm. The results show that the districts with low terrestrial NPP show the characteristics of agglomeration distribution. The eight key factors, in order, are as follows: agricultural development level, latitude, population size, longitude, animal husbandry development level, economic scale, time trend and industrialization level. In this study, via SHAP interaction plots, we found that the effects of population, economic growth, and industrialization on terrestrial NPP are regionally heterogeneous; via cluster analysis, we found the stage characteristics of the mode of SED affecting terrestrial NPP. Therefore, the conservation of terrestrial NPP needs to be combined with the stage changes of SED, as well as inter-regional differences, to develop a regionally coordinated and time-coherent ecological carbon sink conservation plan., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Vegetation change reflects sensitive responses of ecosystem environment to global climate change as well as land use. It is well known that land use type and its transformation affect vegetation change. However, how the changes in land use intensity (LUI) within different land use types impact vegetation and the interactions with other drivers remain poorly understood. We measured the LUI of Jiangsu Province, China, within the main land use types in 1995, 2000, 2005, 2010, 2015 and 2018 by combining remote sensing-based land use data with representative county scale economic and social indicators. Structural equation models (SEMs) were built to quantify the influences of long term LUI on vegetation change interacting with economic development, climate change and topographical conditions in transformed land, cropland, rural settlements and urbanized land, respectively. Seventy percent of significant vegetation change existed in non-transformed land use types. Although the area with a vegetation greening trend is larger than that with a vegetation browning trend, the vegetation browning areas is prominent in urbanized lands and some croplands in south basins. The constructed SEMs suggested the dominant negative effect of fast economic development regardless of land use types, while LUI played important and different direct and indirect effects on affecting vegetation change significantly interacting with economic development and climate change in different land use types. The LUI increasing led a vegetation greening in cropland, and stronger than climate warming with both positive direct and indirect effects for influencing climate change. The LUI change took negative effects on vegetation change in rural and urban areas, while a positive indirect effect of LUI increasing in urbanized land signaled the positive results of human managements. We then provided some land use-specific suggestions on basin scale for land management in Jiangsu. Our results highlight the necessity of long-term LUI quantification and promote the understanding of its effects on vegetation change interacted with other drivers within different land use types. This can be very helpful for sustainable land use and managements in regions with fast economic development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

The impact of climate change on nearshore coastal water quality and its interaction with pollution prevention efforts (e.g., the development of green and gray water infrastructure) still lack systematic investigation. This study performed a holistic analysis of the impact of climate change on the salinity and concentrations of total nitrogen (TN), total phosphorus (TP) and chlorophyll a (Chl.a) in Shenzhen Bay between Shenzhen and Hong Kong, the two most developed megacities in South China, based on three-dimensional hydrodynamic and water quality modeling. The major study findings were as follows. First, Chl.a was the most sensitive parameter, and its bay-wide average concentration in 2100 was predicted to be approximately 13% and 46% higher than those in 2015 under mild and rapid climate change scenarios, respectively. Second, sea level rise was found to be a major driver of all four water quality parameters, while temperature and radiation mainly influenced Chl.a and precipitation mainly influenced nutrients. Third, water quality responses to climate change were highly heterogeneous over the bay. Even under a mild climate change scenario, the highest location-specific changes (2100 vs. 2015) in salinity and TN, TP and Chl.a concentrations were projected to be approximately 21%, 19%, 25%, and 65%, respectively. Fourth, changes in seasonal variation due to climate change may lead to an enhanced ecological risk of algal blooms. Finally, the effect of reducing TN and TP concentrations by proposed water infrastructure development was found to be significantly weakened (nearly 40% and 20% for TN and TP, respectively, under a mild climate change scenario), while the negative effect (i.e., increase in the Chl.a concentration) was notably accelerated. Regional cooperation is critical for protecting the water quality of the bay, particularly under climate change. The insights obtained in this study are applicable to other coastal water zones around the world with similar socioeconomic backgrounds and climatic conditions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Ecological engineering is an important measure to promote ecosystem adaptation and restoration to deal with environmental change and human disturbance. To assess the effectiveness of ecological construction and analyze the influencing factors of ecosystem changes in the Qinghai-Tibet Plateau (QTP), this study detected the spatial changes and dynamic hotspots of vegetation ecosystems in the ecological construction regions of the QTP (QTPE) and regions without ecological construction (QTPWE) using hot spot analysis and comprehensive dynamic degree model. Then the random forest (RF) model and geographical weighted regression model were used to study the degree and spatial heterogeneity of impacts of climate and human activities on normalized difference vegetation index (NDVI). Results showed that the vegetation restoration of the QTPE was obvious during 2001-2018 as the area of the increasing NDVI accounted for 74.15%. In addition, the effects of climate and human activities on NDVI of vegetation ecosystem showed significant spatial heterogeneity. The RF model showed that population density was the most significant factor affecting ecosystem vegetation in the QTPE, and its relative importance was between 26.1-32.6%, followed by downward shortwave radiation (7.9-16.8%). However, climate factors still had the greatest impact in the QTPWE, with the relative importance of precipitation and temperature being 45% and 15%, respectively. These findings provide a scientific basis for the restoration and management of vegetation on the QTP, and are of great significance for the deployment of future ecological engineering projects., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

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 reconstruction of high-resolution chronologies for prehistoric cultures is a prerequisite for understanding the history of human evolution and its relationship with environmental change, and is valuable for exploring the trajectory of transcontinental cultural exchanges in prehistoric time. The Hexi Corridor of northwest China was one of the earliest centers for long-distance culture exchange in the prehistoric world. The timing and sequence of cultural changes in this area remains poorly understood resulting from the lack of radiometric age control. This paper presents a refined radiocarbon (14C) chronology to resolve the timing of human occupation and cultural evolution in the Hexi Corridor. Radiocarbon dating of crop remains, which have an annual life cycle, has the advantage of eliminating problems such as the carbon stored in 'old wood'. As a result, 14C dates from crop remains are used to test the validity of the 14C dates derived from charcoal, bone and plant remains. The resultant database of ages is modelled using the Bayesian approach. The updated chronology presented in this paper shows generally good agreement with the original dates used to constrain cultural evolution in the Hexi Corridor. However, the occupation of the corridor by the Shajing and Shanma Late Bronze Age-Early Iron Age cultures appears to have taken place ~300 years later than previously thought. On the basis of comparing this updated chronology of cultural evolution with palaeoclimatic and historical records, it is proposed that the collapse of the Shajing and Shanma cultures occurred as a result of geopolitical impact rather than climate change. [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]