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Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press 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.)

To address the current issues of insufficient precision in scenario division and limited applicability of models in energy storage planning， the paper proposes a method for refined energy storage planning based on multi-layer clustering of load scenarios. Firstly， an analysis method is introduced that considers the spatiotemporal coupling characteristics of load using association analysis and clustering， along with a multi-layer clustering method considering load spatiotemporal characteristics. Secondly， for typical load scenarios， a refined energy storage planning model is constructed that comprehensively considers carbon emissions， lifecycle costs， penalties for curtailed wind and solar power， and the coordination of energy storage and distributed energy sources. Finally， a case study is conducted on an actual distribution network， resulting in optimal coordinated configurations of energy storage and distributed energy sources for different load scenarios. This validates the feasibility and effectiveness of the proposed model and method.

ABSTRACTIncreased tourism forms subdivide the tourism market. Therefore, distinguishing spatiotemporal behaviors of different types of tourists is of great significance for tourism marketing and planning. In this study, we constructed a Spatial–Temporal-Preference model based on spatial clustering, seasonal-trend decomposition and statistical analysis, using multi-source data. It provides a novel frame for comparing tourist behavioral characteristics from a new perspective. Meanwhile, providing a method to rapidly identify the Tourism Infrastructure Supply and Demand Pattern (TISDP) fusing nighttime light and social media data. Then the framework was applied to analyze the differences between sightseeing tourists (STs) and cycling tourists (CTs) in Yunnan Province, China. The results showed clear spatial differences in location popularity and flow data with STs favoring northwestern Yunnan, and CTs favoring eastern Yunnan. Tourist behavior varied also seasonally and tourists preferred visiting minority areas or areas with better infrastructure. The tourism industry in the study area developed rapidly after 2013, although still with an unbalanced infrastructure supply and demand. The CTs loss areas were greater in northeastern and northwestern Yunnan and south of Kunming. The proposed methods help to identify differences in tourism activities and has important implications to tourism infrastructure planning and sustainable development.

Copyright of Zhejiang Electric Power is the property of Zhejiang Electric Power 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.)

Bustling port activities give rise to serious air pollution in port cities of China's Yangtze River Delta (YRD). Understanding the characteristics and driving forces of air pollutants over port cities of the YRD is conducive to the prevention and control of air pollution. This study analyzed the spatiotemporal characteristics and influencing factors of three air pollutants—PM2.5, NO2, and SO2—over coastal port cities (CPCs) and inland port cities (IPCs) in YRD from 2015 to 2020. The concentrations of air pollutants vary across geographic locations (low in the south/east and high in the north/west) and seasons (low in summer and high in winter). IPCs show higher pollutant concentrations than CPCs. The PM2.5, NO2, and SO2 concentrations over port cities in the YRD declined by 41.48%, 18.68%, and 64.8% from 2015 to 2020; CPCs have reduced more PM2.5 and NO2 than IPCs, while IPCs have reduced more SO2 than CPCs. There is a high synergy among the three air pollutants, with a stronger synergy found in CPCs. The impacts of wind speed and boundary layer height on air pollution are greater in CPCs than in IPCs. Concentrations of different air pollutants are strongly associated with emissions from different sectors. NO2 is the only one among the three air pollutants that cargo throughput shows a significant impact on, with the impact greater in CPCs than in IPCs. Findings from this study deepen the understanding of air pollution in port cities of YRD and may support air quality control in this area. [ABSTRACT FROM AUTHOR]

【Objective】Taking the lower reaches of Danshui River, a major regulated river in Guangdong Province, as the research object, the temporal and spatial dynamic changes of pollutants in its main tributaries were investigated.【Method】Through the method of remote sensing image interpretation combined with field investigation, monitoring points were arranged for different land use function areas in tributary basins of the lower reaches of the Danshui River in Guangdong Province, and monthly field monitoring of water quality in cross sections was carried out. Single factor evaluation method, comprehensive pollution index method and anomaly coefficient method were used to evaluate and analyze the spatio-temporal variation characteristics of water quality.【Result】In the main tributaries of the lower reaches of the Danshui River, except for Maxi River, the monitoring indexes of the catchment sections of other tributaries were significantly higher than those of the source water quality, and TN was the main pollution factor. During the study period, the NH4+-N compliance rate increased from 69.70% to 79.17%, and the COD compliance rate increased from 68.94% to 70.08%.In terms of annual variation, the fluctuation of the comprehensive pollution index of the Maxi River was the most stable, and the fluctuation of the Dali River was more severe, which was obviously higher in January, April, November and December compared with other months. The contribution rate of NH4+-N in the Dali River accounted for 15%-37%, and the TN was an important water pollutant in the Dali River. The TN pollution index in dry period was significantly higher than that in wet period, however, the TP pollution index was slightly lower than that in wet period. In general, the comprehensive pollution index of each tributary in the dry period was higher than that in the wet period. Spatially, the water quality of the west bank tributaries of the Danshui River was better than that of the east bank. Industrial zone, urban living area and rural residential area had a great impact on the TN, NH4+-N and TP flowing through the river section, respectively.【Conclusion】In the lower reaches of the Danshui River, the water quality of the Maxi River on the west bank is generally better, while that of the Dakeng River, the Shatian River and the Dali River on the east bank is relatively poor. The pollution indexes of various tributaries have no obvious change rules during the year, and the pollution indexes of the river reaches near industrial, urban and rural residential areas are higher than those of other river reaches.

Copyright of Hydrogeology Journal 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.)

Wind energy is a clean and pollution-free renewable energy source, particularly in coastal areas with abundant wind resources. To effectively plan for and invest in wind power development, accurate estimates of wind power (based on variable wind speeds) are needed. It is necessary to obtain a reliable quantification and spatiotemporal characteristics of wind speeds to inform wind energy development. In this study, the long-term wind speed data from 1973 to 2020 at 11 meteorological observation stations along the coast of the Guangdong–Hong Kong–Macau Greater Bay Area (GBA) were analyzed using the Wind Rose, Mann–Kendall (MK) test, and Empirical Orthogonal Functions (EOF). The outcomes of this study further the understanding of the spatiotemporal distribution and variability of wind speeds at monthly, interannual, and long-term time scales along the GBA. First, the distributions of prevailing wind directions influenced by the East Asian monsoon and temperature changes are mainly between the east southeast and north directions. Second, the monthly mean wind speed (MWS) has increased slightly and steadily over the last 10 years. Third, the MWS of a particular month over a long period (CMWS) was stronger in spring and winter and followed a 6-month variation cycle. Fourth, the yearly MWS differed significantly at different locations within the GBA, with a period of approximately 20 years. In addition, there was an upward trend in the yearly MWS at each station. Lastly, for extreme climates, the yearly maximum values (YMVs) of wind speeds were spatially different and not very stable year-round, and the YMVs changed downward slightly over a long period. Overall, these findings and results show that the GBA coastal area is a suitable location for wind energy development and wind farm building.

Environmental loss can be caused by the excessive nitrogen input in crop production, leading to non-point source pollution in the lake basin. Among them, the planting structure can be one of the most important factors to affect the nitrogen input, due to the various levels of nitrogen management between different systems of crop production. Therefore, it is very necessary to explore the relationship between planting structure and environmental loss at present. In this study, the grain crops (wheat and maize) and economic crops (vegetables and fruit trees) were taken as research objects in Baoding and Dingzhou from the core areas of the Baiyangdian Basin in the North China Plain. An optimization was made to clarify the effect of planting structure on the regional environment, where the grain economy ratio was taken as the characterization factor of planting structure, while the nitrogen surplus was the characterization factor of environmental loss. Specifically, the grain economic ratio was the planting area ratio of grain crop to economic crop. Nitrogen surplus was the difference between nitrogen input and output in the planting system. The results showed that: 1) There were outstanding spatiotemporal changes in the planting structure in the Baiyangdian Basin. In the spatial view, the largest grain economic ratio was found nearby the Baiyangdian Lake area, whereas, the smallest grain economic ratio was upstream of the Baiyangdian Lake. The grain economy ratio decreased significantly with the increase in distance from the spatial divisions to the lake. In terms of time, the grain economic ratio and each spatial partition showed a slight upward trend during the study period (in 2013, 2015, 2017 and 2019) among the four spatial divisions. There was the largest increase in the grain economy ratio in the middle reaches of Baiyangdian Lake; 2) The spatial and temporal differentiation characteristics of planting nitrogen surplus in Baiyangdian Basin were obvious. In terms of time, the planting nitrogen surplus in Baiyangdian Basin showed a downward trend ((26.29-18.49)×104 t) during the study period. Spatially, the nitrogen surplus in the midstream and downstream of the basin is larger than those in the upstream and nearby Baiyangdian Lake. 3) There was no change in the total planting area of grain crops and economic crops in the four spatial zones, but the nitrogen surplus decreased significantly. Among them, the most decrease in the nitrogen surplus was found in the midstream of Baiyangdian. The trend was attributed to the small basic value of the grain economic ratio and the large increase in the grain economic ratio. Furthermore, the nitrogen surplus decreased with the increase in the grain economy ratio, while the planting area remained unchanged basically in the same area. In addition, the ever-increasing trend was observed in the grain economy ratio with the decrease of the basal value, leading to the decrease of nitrogen surplus; 4) There was a strong relationship between the grain economic ratio and nitrogen surplus intensity. The smaller the grain economic ratio was, the greater the nitrogen surplus intensity was. The nitrogen surplus intensity also decreased with the increase in the grain economic ratio. Consequently, the regional nitrogen surplus intensity can be expected to be significantly adjusted via the grain economic ratio. The nitrogen surplus intensity in the midstream of Baiyangdian Lake could be reduced to the level of II (140-180 kg/hm² ) from the level of IV (220-260 kg/hm² ), when the grain economy ratio is adjusted from 4.21 to 12.13-17.79. Therefore, the nitrogen surplus intensity can be regulated to adjust the planting structure, in order to control the nitrogen surplus for the less environmental risk of nitrogen input in planting industry. This finding can provide a scientific basis for the control of nitrogen pollution in the planting industry. [ABSTRACT FROM AUTHOR]

【Objective】Taking the lower reaches of Danshui River, a major regulated river in Guangdong Province, as the research object, the temporal and spatial dynamic changes of pollutants in its main tributaries were investigated. 【Method】Through the method of remote sensing image interpretation combined with field investigation, monitoring points were arranged for different land use function areas in tributary basins of the lower reaches of the Danshui River in Guangdong Province, and monthly field monitoring of water quality in cross sections was carried out. Single factor evaluation method, comprehensive pollution index method and anomaly coefficient method were used to evaluate and analyze the spatio-temporal variation characteristics of water quality.【Result】In the main tributaries of the lower reaches of the Danshui River, except for Maxi River, the monitoring indexes of the catchment sections of other tributaries were significantly higher than those of the source water quality, and TN was the main pollution factor. During the study period, the NH4 + -N compliance rate increased from 69.70% to 79.17%, and the COD compliance rate increased from 68.94% to 70.08%.In terms of annual variation, the fluctuation of the comprehensive pollution index of the Maxi River was the most stable, and the fluctuation of the Dali River was more severe, which was obviously higher in January, April, November and December compared with other months. The contribution rate of NH4 + -N in the Dali River accounted for 15%-37%, and the TN was an important water pollutant in the Dali River. The TN pollution index in dry period was significantly higher than that in wet period, however, the TP pollution index was slightly lower than that in wet period. In general, the comprehensive pollution index of each tributary in the dry period was higher than that in the wet period. Spatially, the water quality of the west bank tributaries of the Danshui River was better than that of the east bank. Industrial zone, urban living area and rural residential area had a great impact on the TN, NH4 + -N and TP flowing through the river section, respectively.【Conclusion】In the lower reaches of the Danshui River, the water quality of the Maxi River on the west bank is generally better, while that of the Dakeng River, the Shatian River and the Dali River on the east bank is relatively poor. The pollution indexes of various tributaries have no obvious change rules during the year, and the pollution indexes of the river reaches near industrial, urban and rural residential areas are higher than those of other river reaches. [ABSTRACT FROM AUTHOR]

Mobile crowdsensing (MCS) requires users to move to a specific area to complete the sensing task within a specified period. In order to match the tasks and users when users' historical visit data is relatively sparse, and to allocate the tasks effectively, we propose a spatiotemporal characteristic aware task allocation strategy using sparse user data. Firstly, tasks are classified into scheduled tasks and unscheduled tasks. Next, for the sparsity problem in the allocation of scheduled tasks, a matrix decomposition method is designed to evaluate the potential spatiotemporal preference of the users based on their direct spatiotemporal preference; for the sparsity problem in the allocation of unscheduled tasks, we use a similar user enhanced semi-Markov model to predict the task completion probability. Then, the scheduled tasks are allocated based on the users' spatiotemporal preference, and the unscheduled tasks are allocated based on the spatiotemporal preference and the task completion probability of the users. Finally, we conduct simulations to verify the proposed strategy based on a real world dataset (geolife dataset). Experimental result shows that the proposed strategy can effectively allocate the tasks under the condition of sparse users' historical visit data and improve the acceptance rate of tasks. [ABSTRACT FROM AUTHOR]

Although numerous land cover datasets can act as references for understanding land cover change in China, the inconsistencies between the datasets can also provide understanding. Previous studies on the consistency between land cover datasets have mostly focused on land cover type consistencies and have ignored data consistencies in land cover change. Therefore, we aim to analyse the consistencies in land cover changes through likelihood assessment methods. We compared the spatiotemporal changes in forest, grassland, cropland, and bare land in the Climate Change Initiative land cover dataset (CCI-LC), Moderate-resolution Resolution Imaging Spectroradiometer land cover dataset (MCD12Q1), China's National Land Use and Cover Change (CNLUCC), Globeland30 and Global Land Cover Fine Surface Covering 30 (GLC-FCS30) datasets in 2010. The results showed that the percentages and changes in each land cover type in MCD12Q1 were different from those in the other datasets. For example, the proportion of grassland in MCD12Q1 was the highest, reaching 48.04%. The places with high consistency were the places where the land cover types were concentrated, and the bare land had the highest consistency. However, the consistency of China's land cover change was quite low, and the percentage of low consistency was more than 87% from 2000-2018. Comparison of the data with the global artificial impervious area (GAIA) and Hansen-Global Forest Change (Hansen-GFC) datasets showed that the percentage of high construction gain consistency (38.83%) was higher than the forest change consistency, and the percentage forest loss high consistency (8.85%) was lower than the forest gain high consistency (12.76%). The results not only provide a basis for the use of land cover datasets but also give a clearer understanding of the pattern of land cover changes. [ABSTRACT FROM AUTHOR]

Promoting the coupling coordinated development between ecological protection and high-quality development is an important path to achieve sustainable regional development around the world. Taking Guizhou, China as a typical case, this study builds a comprehensive evaluation index system for ecological protection and high-quality development, and then uses the coupling coordination degree model to assess the spatiotemporal characteristics of ecological protection and high-quality development. According to the findings, Guizhou's ecological protection index and high-quality development index both exhibit an upward trend and a center-edge spatial pattern, but they also exhibit a "spatial misalignment relationship". The coupling coordination between ecological protection and high-quality development in Guizhou has shown a continuous growth trend from near-disorder to a primary coordination, with a spatial pattern of "central > western > eastern". This study enriches the knowledge body of sustainable development, helps Guizhou make decisions that are best for ecological protection and high-quality development, and is useful as a reference for other regions and countries. [ABSTRACT FROM AUTHOR]

Abstract Precipitable Water Vapor (PWV), as an important indicator of atmospheric water vapor, can be derived from Global Navigation Satellite System (GNSS) observations with the advantages of high precision and all-weather capacity. GNSS-derived PWV with a high spatiotemporal resolution has become an important source of observations in meteorology, particularly for severe weather conditions, for water vapor is not well sampled in the current meteorological observing systems. In this study, an empirical atmospheric weighted mean temperature (T m) model for Guilin is established using the radiosonde data from 2012 to 2017. Then, the observations at 11 GNSS stations in Guilin are used to investigate the spatiotemporal features of GNSS-derived PWV under the heavy rainfalls from June to July 2017. The results show that the new T m model in Guilin has better performance with the mean bias and Root Mean Square (RMS) of − 0.51 and 2.12 K, respectively, compared with other widely used models. Moreover, the GNSS PWV estimates are validated with the data at Guilin radiosonde station. Good agreements are found between GNSS-derived PWV and radiosonde-derived PWV with the mean bias and RMS of − 0.9 and 3.53 mm, respectively. Finally, an investigation on the spatiotemporal characteristics of GNSS PWV during heavy rainfalls in Guilin is performed. It is shown that variations of PWV retrieved from GNSS have a direct relationship with the in situ rainfall measurements, and the PWV increases sharply before the arrival of a heavy rainfall and decreases to a stable state after the cease of the rainfall. It also reveals the moisture variation in several regions of Guilin during a heavy rainfall, which is significant for the monitoring of rainfalls and weather forecast.

The accurate prediction and analysis of electromagnetic excitation source is the pre-condition for the investigation of electromagnetic vibration and noise. In this work, an analytical model for electromagnetic (EM) force calculation of interior permanent magnet synchronous motors (IPMSMs) is proposed by coupling the 2-D model in polar coordinates and the Maxwell stress tensor method (MSTM). In the modeling, the boundary conditions for solving the air-gap magnetic field are firstly simplified based on the equivalent conversion of permanent magnets (PMs). Then, the magnetic field is acquired by solving the governing equation based on the simplified boundary conditions. Finally, the EM force is obtained according to the MSTM. The effectiveness is fully verified by finite element (FE) analysis that the analytical model can be applied not only for the calculation of radial EM force of IPMSMs with/without load but also for the calculation of tangential EM force. Besides, the tangential EM force is further analyzed by 2-D Fourier decomposition, and the relationship between tangential EM force and torque fluctuation is also clarified. The results show that the radial EM force harmonics and the tangential EM force harmonics have the same spatiotemporal characteristics no matter under no-load or load. Moreover, the high-frequency components of tangential EM force harmonics with low spatial orders, which have the highest contribution to vibration and noise, are comparable to those of radial EM force harmonics. Meanwhile, the torque fluctuation of IPMSMs with/without load only comes from the zero-order tangential EM force harmonics in space. [ABSTRACT FROM AUTHOR]

Strata in red bed areas have typical characteristics of soft-hard interbedding and high sensitivity to water. Under the comprehensive action of internal stratigraphic structure and external hydrological factors, red bed landslides have highly complex spatiotemporal characteristics, presenting significant challenges to the prevention and control of landslide disasters in red bed areas, especially for slope and tunnel engineering projects. In this study, we applied an interdisciplinary approach combining small baseline subset interferometric synthetic aperture radar (SBAS-InSAR), deep displacement monitoring, and engineering geological surveying to identify the deformation mechanisms and spatiotemporal characteristics of the Abi landslide, an individual landslide that occurred in the red bed area of Western Yunnan, China. Surface deformation time series indicated that a basic deformation range developed by March 2020. Based on InSAR results and engineering geological analysis, the landslide surface could be divided into three zones: an upper sliding zone (US), a lower uplifted zone (LU), and a toe zone (Toe). LU was affected by the structure of the sliding bed with variable inclination. Using deep displacement curves combined with the geological profile, a set of sliding surfaces were identified between different lithology. The groundwater level standardization index (GLSI) and deformation normalization index (DNI) showed different quadratic relationships between US and LU. Verification using the Pearson correlation analysis shows that the correlation coefficients between model calculated results and measured data are 0.7933 and 0.7577, respectively, indicating that the DNI-GLSI models are applicable. A fast and short-lived deformation sub stage (ID-Fast) in the initial deformation stage was observed, and ID-Fast was driven by concentrated rainfall. [ABSTRACT FROM AUTHOR]

Non-point source (NPS) pollution has caused serious threats to water quality on a global scale. However, the investigation using a single measure with multi-scenarios for the long-term simulation in karst agricultural watershed is still lacking. In this study, the Annualized Agricultural Non-Point Source Pollution (AnnAGNPS) model was developed to verify the applicability in a karst agricultural watershed. Then, the model was used to determine the best management measures (BMPs) and the reduction rate characteristics under long-term effects (about 10 years) in the watershed. The AnnAGNPS model perform well in simulating in NPS pollution with R2 (0.95 for runoff, 0.93 for TN, and 0.93 for TP, respectively) and NSE (0.95 for runoff, 0.53 for TN, and 0.57 for TP, respectively). The output of total nitrogen (TN) and total phosphorus (TP) primarily occurred in the rainy season (up to 80%). The loss of mass of TN and TP were mainly observed in orchards and woodlands in the upstream of each sub-basin. The results from AnnAGNPS model demonstrated that different BMPs had significant impacts on the reduction of NPS pollution. Furthermore, a same BMPs measure showed it was closely related to land use in the watershed. In the Qifeng River watershed, stubble tillage (ST) showed to be useful with relatively good reduction rates (16.64% for sediment, 17.85% for TN, and 17.80% for TP, respectively). The simulation results indicated that AnnAGNPS was a valuable tool after validation for the planning and management of the watershed in karst areas.

Air pollution shares the attributes of multi-factorial influence and spatiotemporal complexity, leading to air pollution control assistance models easily falling into a state of failure. To address this issue, we design a framework containing improved data fusion method, novel grey incidence models and air pollution spatiotemporal analysis to analyze the complex characteristics of air pollution under the fusion of multiple factors. Firstly, we improve the existing data fusion method for multi-factor fusion. Subsequently, we construct two grey spatiotemporal incidence models to examine the spatiotemporal characteristics of multi-factorial air pollution in network relationships and changing trends. Furthermore, we propose two new properties that can manifest the performance of grey incidence analysis, and we provide detailed proof of the properties of the new models. Finally, in the Jing-Jin-Ji region, the novel models are used to study the network relationships and trend changes of air pollution. The findings are as follows: (1) Two highly polluted belts in the region require attention. (2) Although the air pollution network under multi-factorial fusion obeys the first law of geography, the network density and node density exhibit significant variations. (3) From 2013 to 2021, all pollutants except O 3 show improvement. (4) Recommendations for responses are presented based on the above-mentioned results. (5) The parameter analyses, model comparisons, Monte Carlo experiments and model feature summaries illustrate that the proposed models are practical, interpretable and considerably outperform various prevailing competitors with remarkable universality. • A framework is designed for analyzing multi-factorial air pollution. • The new data fusion method and two novel GIMs enhance the analytical capabilities. • Two major pollution zones are found in the Jing-Jin-Ji region. • Economic and transportation factors influence the network characteristics. • Different cities may serve as key locations depending on the integration of factors. [ABSTRACT FROM AUTHOR]

Although numerous land cover datasets can act as references for understanding land cover change in China, the inconsistencies between the datasets can also provide understanding. Previous studies on the consistency between land cover datasets have mostly focused on land cover type consistencies and have ignored data consistencies in land cover change. Therefore, we aim to analyse the consistencies in land cover changes through likelihood assessment methods. We compared the spatiotemporal changes in forest, grassland, cropland, and bare land in the Climate Change Initiative land cover dataset (CCI-LC), Moderate-resolution Resolution Imaging Spectroradiometer land cover dataset (MCD12Q1), China’s National Land Use and Cover Change (CNLUCC), Globeland30 and Global Land Cover Fine Surface Covering 30 (GLC-FCS30) datasets in 2010. The results showed that the percentages and changes in each land cover type in MCD12Q1 were different from those in the other datasets. For example, the proportion of grassland in MCD12Q1 was the highest, reaching 48.04%. The places with high consistency were the places where the land cover types were concentrated, and the bare land had the highest consistency. However, the consistency of China’s land cover change was quite low, and the percentage of low consistency was more than 87% from 2000-2018. Comparison of the data with the global artificial impervious area (GAIA) and Hansen-Global Forest Change (Hansen-GFC) datasets showed that the percentage of high construction gain consistency (38.83%) was higher than the forest change consistency, and the percentage forest loss high consistency (8.85%) was lower than the forest gain high consistency (12.76%). The results not only provide a basis for the use of land cover datasets but also give a clearer understanding of the pattern of land cover changes.

Spatiotemporal characteristics of the trade-off among ecosystem services and its mechanism have been extensively studied. However, studies on the difference in spatiotemporal variation of ecosystem services trade-offs in various climate zones under climate change are limited. This study aims to explore the spatiotemporal characteristics and driving factors of trade-offs between crop production and soil conservation in different climate zones by employing a case study in various climate zones of the Shaanxi Province. We adopted statistical and GIS-based spatial analyses to explore the spatiotemporal characteristics of the trade-off and used gradient boosting decision tree to quantify the relative contribution of driving factors. Results showed that trade-off between crop production and soil conservation in a middle temperate zone (0.09) is significantly lower than in a warm temperate zone (0.18) and a subtropical zone (0.21). The trade-off clearly exhibits an upward trend from 1995 to 2018 in all climate zones. However, the increasing trend gradually weakened from the middle and warm temperate zones to the subtropical zone. Moreover, changes in the trade-off are spatially heterogeneous in all climate zones. Anthropogenic activities have larger relative contribution (62.27%–71.67%) to the trade-off than environmental factors in all climate zones. Climate zone type has an insignificant effect on the relative contributions of anthropogenic activities, whereas the relative contributions of most environmental factors are significantly different in various climate zones. Fertilization (relative contribution, 26.58%–37.66%), GDP per land area (relative contribution, 8.50%–20.49%), and population density (relative contribution, 9.77%–16.11%) are the most important anthropogenic driving factors in all climate zones. The environmental factors with greatest relative contribution in the middle temperate, warm temperate, and subtropical zones are accumulated temperature (13.40%), precipitation (26.64%), and accumulated temperature (9.63%), respectively. Thus, differences of spatiotemporal characteristics and driving factors of ecosystem services trade-off must be considered in the formulation of targeted polices for agroecosystem management in different climate zones.

Ecological restoration projects have great impacts on ecosystem service values (ESVs) in China. However, it is still unclear how the temporal and spatial characteristics of ESVs in karst areas in southwestern China changed before and after the implementation of some ecological restoration projects. Land use data from five phases between 1980 and 2018 were used in combination with socioeconomic data of karst areas in southwestern China. The equivalent factor method and spatial, autocorrelation analysis method were used to study the temporal and spatial distributions of ESVs. The results show that (1) the conversion of land use types mainly consisted of the conversion of cultivated lands to woodlands, grasslands, and water areas, and from grasslands to woodlands, construction lands, and wetlands; (2) from 1980 to 2018, the overall trend of ESVs in the study area first decreased and then increased; the ESVs increased by 19.62 billion yuan, with a growth rate of 0.35%, and changes in water areas were the main reason for the ESVs increase, while changes in the areas of woodlands and wetlands were the second reason for the ESVs increase; (3) in terms of its spatial distribution, the ESVs was higher in the southwest direction, while in other areas, from west to east, the ESVs generally showed a spatial distribution pattern of "high-low-high-low"; and (4) the ESVs in the study area had significant, positive autocorrelations in its spatial distribution from 1980 to 2018. The spatial aggregation of ESVs among cities mainly included aggregations of spatially similar values. The results of this study provide reference data for ecological infrastructure construction and ecological-economic development in karst areas in southwestern China. [ABSTRACT FROM AUTHOR]

Understanding the coupling relationship between ecosystem services and poverty livelihoods is a prerequisite for poverty eradication and ecological protection in China. In this paper, we intended to quantify the coupling relationship between ecosystem services and poverty livelihoods in 717 poverty-stricken counties in China. First, we identified distinct levels of ecosystem services and poverty respectively in the poverty-stricken areas based on the ecosystem services subsystem index and poverty livelihoods subsystem index. Then, we calculated the coupling degree and coupling coordination degree between the ecosystem services and the poverty livelihoods in China's poverty-stricken counties from 2000 to 2015. Finally, we analyzed the temporal and spatial evolution of the coupling between ecosystem services and poverty livelihoods. The results indicate that the ecosystem services showed a trend of first decreasing and then increasing, while the poverty level showed an increased trend. In addition, the coupling relationship between ecosystem services and poverty livelihoods in poverty-stricken counties was also improved from 2000 to 2015. However, the coupling degree value or coupling coordination degree values in some counties or contiguous impoverished areas showed a decreased trend, the coupling relationship between ecosystem services and poverty livelihoods in those counties or areas was higher conflict. Future more, the coupling relationship in China's poverty-stricken counties was mainly intermediate conflict and low conflict, which need to improve in the future. Thus, it is suggested that effective measures are required to lift ecosystem services out of the poverty trap and into sustainable livelihoods. [ABSTRACT FROM AUTHOR]

Understanding monitor accurately and predicting drought conditions are necessary to prevent economic losses and natural disasters. Now, there is still a lack of comprehensive assessment of drought prediction in Xinjiang. In order to better predict the future drought trend, firstly we analyzed the trends of SPEI and the magnitude and frequency of drought in selected surface meteorological stations from 1960 to 2017. Secondly, we compared drought trends and spatial distribution characteristics of SPEI and PDSI. Based on historical data from 1960 to 2017, the paper predicted the trends of SPEI and PDSI in the next five years. The results show that the winter SPEI has risen significantly, and there was a SPEI value mutation in 1994. The Spring, Summer and Autumn SPEI show an insignificant downward trend. It is relatively stable on other time scales , and there is no significant sudden change. It is inferred thatthe increasing trend of wetting that may occur under different time scales at NRX in 2021, winter and annual scales will continue to be humidified, and spring, summer, and autumn will continue to be arid. Droughts in NRX occur at least once every three years, which is a high frequency event. The prediction results of the artificial neutral network (ANN) method based on multilayer feed forward network show that probability of humidification at NRX is more likely in the future, and the prediction results of wavelet and Hurst index are basically consistent with that of ANN method.

Promoting the coupling coordinated development between ecological protection and high-quality development is an important path to achieve sustainable regional development around the world. Taking Guizhou, China as a typical case, this study builds a comprehensive evaluation index system for ecological protection and high-quality development, and then uses the coupling coordination degree model to assess the spatiotemporal characteristics of ecological protection and high-quality development. According to the findings, Guizhou’s ecological protection index and high-quality development index both exhibit an upward trend and a center-edge spatial pattern, but they also exhibit a “spatial misalignment relationship”. The coupling coordination between ecological protection and high-quality development in Guizhou has shown a continuous growth trend from near-disorder to a primary coordination, with a spatial pattern of “central > western > eastern”. This study enriches the knowledge body of sustainable development, helps Guizhou make decisions that are best for ecological protection and high-quality development, and is useful as a reference for other regions and countries.

In this study, the temporal and spatial patterns of rainfall in the Longchuan River basin from 1977 to 2017 were analyzed, to assess the feature of precipitation. Based on the daily precipitation time series, the Lorenz curve, precipitation concentration index (PCI), precipitation concentration degree (PCD), and the precipitation concentration period (PCP) were used to evaluate the precipitation distribution characteristics. The PCI, PCD and PCP in five categories, defined by the fixed thresholds, were proposed to investigate the concentrations, and the average values indicated the higher concentrations in the higher intensities. The indices showed strong irregularity of daily and monthly precipitation distributions in this basin. The decrease in the PCD revealed an increase in the proportion of precipitation in the dry season. The rainy days of slight precipitation in the upper and lower basins with significant downward trends (−13.13 d/10 a, −7.78 d/10 a) led to longer dry spells and an increase in the risk of drought, even severe in the lower area. In the upper basin, the increase in rainfall erosivity was supported by the upward trend in the PCIw of heavy precipitation and the simple daily intensity index (SDII) of extreme precipitation. Moreover, the PCP of light precipitation, moderate precipitation, and heavy precipitation concentrated earlier at the end of July. The results of this study can provide beneficial reference information to water resource planning, reservoir operation, and agricultural production in the basin.

Understanding the spatiotemporal (ST) characterization of precipitation is one key component in evaluating the climatic environment, which provides executable and effective suggestions for the implementers of climatic strategy. In this paper, the ST ordinary kriging method was used to obtain the ST distribution of annual precipitation (AP) based on the data collected from the 961 meteorological monitoring stations of the Huanghuaihai basin in China during 1956–2016. Then, stochastic site indicators were applied to quantitatively assess the ST uncertainties, and the results indicated the probability that higher precipitation (beyond 1000 mm) occurred simultaneously at any two regions was extremely low. In terms of the AP intensity analysis, the annual rainfall in 50% of the regions exceeded 500 mm, and the largest fragmentation of AP was calculated from this threshold. Furthermore, the ST characterization and the trend of AP were analyzed in different climatic environments, indicating that (1) the AP increased from west to east, exhibiting a significant gradient distribution; (2) overall, the temperature of the study area increased by approximately 0.027 °C per year, while the AP decreased by 0.2 mm per year; (3) the temperature in three subregions [high-altitude region (HAR), mid-altitude region (MAR), low-altitude region (LAR)] exhibited an increasing trend, and the significant increasing trend of temperature occurred primarily in the LAR; (4) the precipitation in the MAR and LAR exhibited a nonsignificant decreasing trend, while the precipitation in the HAR showed a significant increasing trend. [ABSTRACT FROM AUTHOR]

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Under the backdrop of achieving carbon neutrality and accelerating urbanization, China’s forests face unprecedented pressures. This study explored the spatiotemporal characteristics of forest loss in the urban agglomeration in the middle reaches of the Yangtze River (UAMRYR). The dynamic mechanism of forest loss caused by fire, logging, construction, and pollution was also analyzed using spatial database development, polygon superposition analysis, grid system construction, and coordinate system calculation. The results show that the forest loss in the UAMRYR experienced three stages: continuous acceleration (1990–2010), peak (2010–2015), and slight decline (2015–2020). Rapid urban expansion is the primary cause of forest loss, and the three metropolitan areas had the fastest urban expansion and the most severe forest loss. Due to the success of afforestation efforts, the forest loss caused by fire, logging, and pollution was restored by 80%, while most of the forest losses caused by construction are permanent. Given the current forest loss trends, large expanses of forests in the UAMRYR are at risk of being destroyed and causing serious damage to the region’s ecological environment. Forest losses can be significantly reduced by guiding the rational expansion of cities, supporting afforestation for urban construction projects, strengthening forest fire risk investigation, and implementing ecological reconstruction of polluted areas.

Using personal trajectory information to grasp the spatiotemporal laws of dangerous activities to curb the occurrence of criminal acts is a new opportunity and method for security prevention and control. This paper proposes a novel method to discover abnormal behaviors and judge abnormal behavior patterns using mobility trajectory data. Abnormal behavior trajectory refers to the behavior trajectory whose temporal and spatial characteristics are different from normal behavior, and it is an important clue to discover dangerous behavior. Abnormal patterns are the behavior patterns summarized based on the regular characteristics of criminals’ activities, including wandering, scouting, random walk, and trailing. This paper examines the abnormal behavior patterns based on mobility trajectories. A Long Short-Term Memory Network (LSTM)-based method is used to extract personal trajectory features, and the K-means clustering method is applied to extract abnormal trajectories from the trajectory dataset. Based on the characteristics of different abnormal behaviors, the spatio-temporal feature matching method is used to identify the abnormal patterns based on the filtered abnormal trajectories. Experimental results showed that the trajectory-based abnormal behavior discovery method can realize a rapid discovery of abnormal trajectories and effective judgment of abnormal behavior patterns.

Optical remote sensing data are used widely in many fields (such as agriculture, resource management and the environment), especially for the vast territory of China; however, the application of these data is usually limited by clouds. Although it is valuable to analyze the probability of acquiring cloud-free imagery (PACI), PACI using different sensors at the pixel level across China has not been reported. In this study, the PACI of China was calculated with daily Advanced Very High Resolution Radiometer (AVHRR) cloud mask data from 1990 to 2019. The results showed that (1) PACI varies dramatically in different regions and months in China. The value was larger in autumn and winter, and the largest figure reached 49.55% in October in Inner Mongolia (NM). In contrast, relatively small values occurred in summer, and the minimum value (5.26%) occurred in June in South China (SC). (2) As the climate changes, the PACI has increased significantly throughout the country and most regions, especially in North China (NC), with a growth rate of 1.9% per decade. The results can be used as a reference for selecting appropriate optical sensors and observation times in areas of interest.

Understanding the temperature difference between neighbouring days (TDN) is beneficial for reducing the harmful impacts of sudden temperature changes on human health and establishing adaptation policies considering global TDN characteristics. This study analyses the spatiotemporal characteristics of TDN in Mainland China on the basis of the daily observation data from 839 stations in 1961–2017. Results show that the TDN increases with the latitude from south to north. Meanwhile, TDN in winter is higher but lower in summer. These characteristics potentially arise from the variations in solar elevation angle, that is, a decreased TDN corresponds to an increased solar elevation angle in most parts of China. Areas with high solar elevation angle are usually characterized by low TDN, which implies that temperature is stable for neighbouring days in areas with high solar elevation angle. Moreover, the variation rate of the annual mean TDN is negative in most parts of China, especially in the north. These findings are expected to provide an overview of the spatiotemporal characteristics of TDN and support future studies on the impacts of TDN variations on regional environmental changes. [ABSTRACT FROM AUTHOR]

Urban land-use change simulations without considering the sustainable planning policies, especially in special economic park highly concerned by planners, might lack the reliability and availability. Thus, this study proposes a novel planning support systems integrating the Cellular Automata Markov chain model and Shared Socioeconomic Pathways (CA-Markov-SSPs) for predicting the changing of land use and land cover (LULC) at the local and system level by using a novel machine learning-driven, multi-source spatial data modelling framework. Using multi-source satellite data of coastal special economic zones from 2000 to 2020 as a sample, calibration validation based on the kappa indicates a highest average reliability above 0.96 from 2015 to 2020, and the cultivated land and built-up land classes of LULC is the most significant changes in 2030 by using the transition matrix of probabilities, the other classes except water bodies continue to increase. And the non-sustainable development scenario can be prevented by the multiple level collaboration of socio-economic factors. This research intended to help decision makers to confine irrational urban expansion and achieve the sustainable development. • The sustainable development path and planning policies are integrated in scenario land-use models. • Urban land-use change is explored under a context with different shared socioeconomic pathways. • Simulated scenario show that the non-sustainable development can prevented by the collaboration of socio-economic factors. • CA-Markov-SSPs framework for simulating the effects of sustainable development planning can be extended at different scale [ABSTRACT FROM AUTHOR]

Resilience has become an essential aspect of the high-quality development of the marine economy. This study considered multiple combinations of dimensions, including politics, economy, culture, society, ecology, and security, in developing marine economy resilience. Based on the adaptability theory, this study measures the resilience of China's marine economy by constructing an evaluation index system using the three resilience sub-dimensions of resistance, adaptability, and evolution from 2000 to 2020 in 11 Chinese coastal provinces. The evaluation index system also considers social factors such as institution, culture, and history. The new technical methods such as remote sensing interpretation and text analysis are used to obtain one-hand data. We use a fuzzy comprehensive evaluation (FCE) model to calculate the comprehensive evaluation index and determine the weight of each index using the entropy weight method, analytic hierarchy process, and the least square decision model. Furthermore, based on the Local Indicators of Spatial Association (LISA) time path and spatiotemporal transition probability matrix, we analyze the spatiotemporal characteristic evolution characteristics of marine economic resilience. The results reveal that (1) the resilience, resistance, adaptability, and evolution of the marine economy in 11 coastal provinces show an upward trend from 2000 to 2020. (2) The development speed of the resilience level differs in terms of resistance, adaptability, and evolution, but the overall level shows adaptability > evolution > resistance. (3) The analysis of the spatiotemporal interaction characteristics of resilience shows that the overall spatial characteristic of resilience is relatively stable. Therefore, some measurements are suggested to improve marine economic resilience. For example, government formulates marine plans, sea-related enterprises assume social responsibilities, and individuals actively participate in marine governance. The evaluation model of marine economic resilience applies to other complex systems with multiple factors. • Assess spatiotemporal characteristics of marine economic resilience. • A new compound asymmetric spatial vector weight matrix is constructed. • A new method explores the spatiotemporal evolution of marine economic resilience. • The evaluation model of resilience is applicable to other complex systems. [ABSTRACT FROM AUTHOR]

In recent decades, the occurrence and severity of drought in China has had devastating impact on social and economic development. The increase in drought has been attributed to global warming. We used the high-accuracy self-calibrating Palmer Drought Severity Index (scPDSI) to investigate the variation in drought in China between 1961 and 2009 using the Mann-Kendall (MK), continuous wavelet transform (CWT) and the rotated empirical orthogonal function (REOF) methods. We also analyzed the relationship between the rotated principal component time series (RPCs) and 74 circulation indices. The results revealed that: 1) all of China experienced a significant wet trend at annual and seasonal scale; an abrupt change in the drought pattern occurred around 1970 with a 2–8-year significant period; 2) eight major sub-climate regions were identified: Northwest China, Northeast-Inner Mongolia Plateau, Greater Khingan Range area, Northern Tibetan Plateau, Southern Tibetan Plateau, Central China, Huang-Huai-Hai Plain and Southeast China. Of these regions, the Southern Tibetan Plateau experienced a significant wet trend, but the Northeast-Inner Mongolia Plateau and Northern Tibetan Plateau became significantly drier. Using either annual or seasonal scales, Northwest China became significantly wetter and Central China became more arid. In addition, the period of each sub-climate region shared a significant 2–8-year band; 3) the polar vortex exhibited dominant patterns that affected most areas of China. The Pacific Decadal Oscillation had a significant influence on drought evolution, especially for Northwest China and the Huang-Huai-Hai plain. Additionally, the El Niño-Southern Oscillation also affected drought evolution, and the Central China was impacted by the Indian Ocean Dipole. [ABSTRACT FROM AUTHOR]

Carbon peaking and carbon neutrality in the shipping industry are hot topics but now facing serious challenges. One of them is the current lack of scientific guidance on ship carbon reduction. Precise identification of carbon emission hotspot areas and ship types in ports is the key to controlling carbon emissions from ships. In this paper, a method of identifying and extracting ship carbon emission hotspots based on data field theory is proposed. Based on the theory of field in physics, the spatiotemporal aggregation pattern of ship carbon emissions in the port region is analyzed with regard to the characteristics of ship emission trajectory data. Taking Wuhan Port as an example, we successfully extracted the ship's carbon emission hotspot area based on the proposed method and analyzed the spatial and temporal dynamics of the ship's carbon emission hotspot in the area from several perspectives. The method proposed in this paper can be further applied to coastal ports, which is conducive to exploring the distribution of carbon emission hotspots and the spatial and temporal variation patterns of ships in China's ports. It provides scientific guidance for relevant departments to formulate and implement policies to reduce carbon emissions from ports, and promotes the early realization of the dual carbon goal of China's shipping industry. [ABSTRACT FROM AUTHOR]

As an important part of urban intelligent transportation system, predicting users' demand for taxi using offline GPS data has attracted interests in recent years. In general, the distribution of traffic flow in different areas of the urban is different. Furthermore, the characteristics of traffic flow in different location areas present different. Therefore, it is challenging to achieve accurate prediction of users' demand for taxi in different spatiotemporal scenes. This paper presents a combined multi-scale residual calibration network (MS-ResCnet) using residual calibration network and multi-scale fusion mechanism to predict users' demand for taxi. Specifically, mapping rasterization and time series division methods are used to convert vehicular GPS data into spatiotemporal images of traffic flow within continuous sub grid areas. Then, the proximity, periodicity, and tendency, as significant characteristics of spatiotemporal images of traffic flow in each sub grid area are extracted. Thus, we establish a multi-dimensional spatiotemporal characteristic perception scheme of traffic flow in each grid area. Moreover, the datum characteristics and calibration characteristics of spatiotemporal images are extracted through the dual channel ResCnet network. Through the deep stagger training network, the full fusion of multi-scale spatiotemporal characteristics is realized. The performance of MS-ResCnet model is evaluated and verified using public datasets. The simulation results show that the traffic flow prediction performance of MS-ResCnet model is better than that of traditional STAR model. The root mean square error (RMSE) of the proposed method outperform the STAR model around 2.57%. [ABSTRACT FROM AUTHOR]

Calculating the fossil energy consumption, revealing the temporal and spatial evolution characteristics of net CO 2 emissions, and analyzing the decoupling effect between social development and net CO 2 emissions in different regions of the Yangtze River Economic Belt (YREB) is crucial to support the different regions, allowing them to select their individual industrial development and carbon emission reduction path. The results showed that:① from 1999 to 2012, YREB became greener, the CO 2 emission of the YREB increased by 2244.23 million tons, and the carbon sink increased by 148.07 million tons during the research period. ② From 2013 to 2018, the area of medium-high carbon sequestration (NPP>800 g·m -2 , count for C) increased by 23.25%, compared with that from 1999-2012. ③ A highly decoupling effect between social development and net CO 2 emissions was found in the downstream of the YREB. The highest decoupling cities in the upstream, midstream, and downstream accounted for 12%, 34%, and 54% of the highest decoupling cities in the YREB, respectively.

Understanding the spatiotemporal characteristics of land use, ecosystem services, and their relationship provides a basis for the sustainable development of ecosystems. However, the effect of land use change on multiple ecosystem services has not been widely quantified, especially in transnational areas. This study analysed the spatiotemporal characteristics of land use change in the China–Mongolia–Russia Economic Corridor using the ESA-Global Land Cover product from 1992 to 2019. We used the InVEST model to evaluate the changes in carbon storage, habitat quality, water yield, and soil retention and quantified the contribution of land use to the changes in ecosystem services by calculating the ecosystem service contribution index (ESCI). The results showed that from 1992 to 2019, the urban/built-up environment and croplands increased by 22,010 km2 and 32,946 km2, respectively, which led to the continuous decline of forests. The implementation of ecological projects significantly decreased the barren environment. The value of four ecosystem services gradually decreased depending on the distance from the coastline and improved overall from 1992 to 2019. Land use conversion significantly affected ecosystem services. The expansion of croplands, urbanisation, and desertification had a significant negative impact on ecosystem services and the conversion to grasslands. Forests had a significant positive impact on ecosystem services. The findings will enrich our understanding of ecosystem services in transnational areas and help balance the relationship between ecological conservation and social-economic development in the China-Mongolia-Russia Economic Corridor. • Land-use change had significant spatiotemporal differences from 1992 to 2019. • Quantitative assessment to the contributions of land use conversion on changes in ecosystem services. • Ecosystem services improved in the China–Mongolia–Russia Economic Corridor. • Land-use conversion was significantly correlated with ecosystem services. [ABSTRACT FROM AUTHOR]

Based on the sixth forest inventory data of Taihe County, Jiangxi Province, this paper analyzed the curve relations between the carbon densities and ages of major forest types by using Logistic equation, and estimated the total amounts and change trends of the biomass and carbon storage of forest vegetation from 1985 to 2003 by the method of biomass expansion factor. The carbon storage in 2020 and 2030 was estimated by setting 2003 as the baseline year and assuming that the area of forest vegetation remained stable and without consideration of forest rotation. In 2003, the total forest area of Taihe County was 15.74×104 hm2, the total biomass was 6.71 Tg, the vegetation carbon storagewas 4.14 Tg C, and the average carbon density was 26.31 t C·hm-2. In 1985, 1994, 2003, 2020, and 2030, the forest carbon storage was 1.06, 2.83, 4.14, 5.65, and 6.35 Tg C, respectively. The carbon density of the forest vegetation in Taihe County decreased from the eastern and western regions to the central. Artificial afforestation contributed significantly to the increase of forest stand area, and consequently, to the improvement of forest carbon sequestration capacity. [ABSTRACT FROM AUTHOR]

In this study, the temporal and spatial patterns of rainfall in the Longchuan River basin from 1977 to 2017 were analyzed, to assess the feature of precipitation. Based on the daily precipitation time series, the Lorenz curve, precipitation concentration index (PCI), precipitation concentration degree (PCD), and the precipitation concentration period (PCP) were used to evaluate the precipitation distribution characteristics. The PCI, PCD and PCP in five categories, defined by the fixed thresholds, were proposed to investigate the concentrations, and the average values indicated the higher concentrations in the higher intensities. The indices showed strong irregularity of daily and monthly precipitation distributions in this basin. The decrease in the PCD revealed an increase in the proportion of precipitation in the dry season. The rainy days of slight precipitation in the upper and lower basins with significant downward trends (−13.13 d/10 a, −7.78 d/10 a) led to longer dry spells and an increase in the risk of drought, even severe in the lower area. In the upper basin, the increase in rainfall erosivity was supported by the upward trend in the PCIw of heavy precipitation and the simple daily intensity index (SDII) of extreme precipitation. Moreover, the PCP of light precipitation, moderate precipitation, and heavy precipitation concentrated earlier at the end of July. The results of this study can provide beneficial reference information to water resource planning, reservoir operation, and agricultural production in the basin. [ABSTRACT FROM AUTHOR]

This study constructs a fully fuzzy data envelopment analysis (DEA) with large datasets to evaluate the urban circular economy. The proposed fully fuzzy DEA model considers uncertainties of circular economy indicators and introduces fuzzy trigonometric numbers. Additionally, the model provides a modified algorithm to overcome calculation difficulties due to voluminous data and large-scale decision-making units. The proposed model can quickly solve urban circular economy efficiency under uncertainty and with large datasets. An empirical study of 264 Chinese cities over 2009–2018 was conducted. Overall, the average annual fuzzy efficiency scores (theoretically vary from 0 ˜ to 1 ˜) of the urban circular economy in these cities are (0.7471, 0.7463, 0.7451), indicating that there is substantial room for improvement. The average efficiency scores and the subitem coordination levels of western cities are the highest compared to those of the other regions. Moreover, Northeast China exhibits the lowest efficiency score, which may be attributed to its decaying industry and unadvanced technical level. The overall urban economy performance presents two distinct trends: in 2009–2015, the urban circular economy exhibited negative growth, whereas it increased in 2015–2018. However, the growth rate declined, and negative growth remains a risk. Based on the results, several policy implications are provided for promoting urban circular economy. • Novel fully fuzzy DEA with large datasets is proposed for urban circular economy evaluation • Proposed model applied to 264 Chinese cities for the 2009–2018 period. • Average circular economy efficiency scores indicated great room for improvement. • Western China efficiency scores high, whereas those of Northeast China were low. • Although the circular economy grew from 2015 to 2018, negative growth remains a risk. [ABSTRACT FROM AUTHOR]

[Display omitted] • We explored the difference of ecosystem services trade-off in various climate zone. • The increasing trend of trade-off gradually weakened along the climate gradient. • Anthropogenic activities are the predominate driving factors of the trade-off. • The climate zone has a negligible effect on anthropogenic driving factors. • Environmental driving factors show different importance in various climate zones. Spatiotemporal characteristics of the trade-off among ecosystem services and its mechanism have been extensively studied. However, studies on the difference in spatiotemporal variation of ecosystem services trade-offs in various climate zones under climate change are limited. This study aims to explore the spatiotemporal characteristics and driving factors of trade-offs between crop production and soil conservation in different climate zones by employing a case study in various climate zones of the Shaanxi Province. We adopted statistical and GIS-based spatial analyses to explore the spatiotemporal characteristics of the trade-off and used gradient boosting decision tree to quantify the relative contribution of driving factors. Results showed that trade-off between crop production and soil conservation in a middle temperate zone (0.09) is significantly lower than in a warm temperate zone (0.18) and a subtropical zone (0.21). The trade-off clearly exhibits an upward trend from 1995 to 2018 in all climate zones. However, the increasing trend gradually weakened from the middle and warm temperate zones to the subtropical zone. Moreover, changes in the trade-off are spatially heterogeneous in all climate zones. Anthropogenic activities have larger relative contribution (62.27%–71.67%) to the trade-off than environmental factors in all climate zones. Climate zone type has an insignificant effect on the relative contributions of anthropogenic activities, whereas the relative contributions of most environmental factors are significantly different in various climate zones. Fertilization (relative contribution, 26.58%–37.66%), GDP per land area (relative contribution, 8.50%–20.49%), and population density (relative contribution, 9.77%–16.11%) are the most important anthropogenic driving factors in all climate zones. The environmental factors with greatest relative contribution in the middle temperate, warm temperate, and subtropical zones are accumulated temperature (13.40%), precipitation (26.64%), and accumulated temperature (9.63%), respectively. Thus, differences of spatiotemporal characteristics and driving factors of ecosystem services trade-off must be considered in the formulation of targeted polices for agroecosystem management in different climate zones. [ABSTRACT FROM AUTHOR]

Under the backdrop of achieving carbon neutrality and accelerating urbanization, China's forests face unprecedented pressures. This study explored the spatiotemporal characteristics of forest loss in the urban agglomeration in the middle reaches of the Yangtze River (UAMRYR). The dynamic mechanism of forest loss caused by fire, logging, construction, and pollution was also analyzed using spatial database development, polygon superposition analysis, grid system construction, and coordinate system calculation. The results show that the forest loss in the UAMRYR experienced three stages: continuous acceleration (1990–2010), peak (2010–2015), and slight decline (2015–2020). Rapid urban expansion is the primary cause of forest loss, and the three metropolitan areas had the fastest urban expansion and the most severe forest loss. Due to the success of afforestation efforts, the forest loss caused by fire, logging, and pollution was restored by 80%, while most of the forest losses caused by construction are permanent. Given the current forest loss trends, large expanses of forests in the UAMRYR are at risk of being destroyed and causing serious damage to the region's ecological environment. Forest losses can be significantly reduced by guiding the rational expansion of cities, supporting afforestation for urban construction projects, strengthening forest fire risk investigation, and implementing ecological reconstruction of polluted areas. [ABSTRACT FROM AUTHOR]