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China's paper industry development is rapid, but the recycling rate of China's waste paper has been low all the time. Meanwhile, material flow analysis can help determine the flow of waste paper, and life cycle assessment (LCA) is the methodological framework for quantifying greenhouse gas emissions. Therefore, present study integrates these two methods into the model construction of China's waste paper recycling decision system. Present study constructs a benchmark model of China's waste paper recycling decision system in 2017, focusing on the impact of nonstandard waste paper recycling on the economic and environmental benefits of China's domestic waste paper recycling system. This model construction is followed by sensitivity analysis of the relevant parameters affecting the efficiency of the waste paper recycling system. Finally, present study forecasts the system's economic benefits and greenhouse gas (GHG) emissions in the context of integrating and regulating nonstandard recycling vendors. The results show that the economic benefit of China's waste paper recycling in 2017 is approximately 458.3 yuan/t and that the GHG emissions are 901.1 kgCO 2 eq. The standard recovery rate and nonstandard recovery acceptance rate will both have a significant impact on the system's economic benefits and improve the GHG emissions structure. In the context of integrating nonstandard recycling enterprises and individual recycling vendors, the economic benefits will rise to 3312.5 yuan/t in 2030, while GHG emissions will rise to 942.9 kgCO 2 eq. Present study can play a certain guiding role for policy makers in formulating waste paper recycling industry specifications and formulating relevant policies., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Purpose: Based on the protection motivation theory (PMT), which is an extension of the health belief model that takes the "reward" brought by behavior in the long-term process as a consideration factor and considering the influence of environmental and social factors on behavior patterns, this cross-sectional study evaluated medication adherence among children with epilepsy using structural equation modeling., Methods: Children with epilepsy from pediatric neurology clinics were consecutively sampled at West China Second Hospital of Sichuan University from July 2021 to January 2024. According to PMT, we designed the 23-item questionnaire, which included seven factors, namely severity, susceptibility, external return, internal returns, self-efficacy, reaction efficiency, and reaction cost. Medication adherence was assessed using the Morisky Medication Adherence Scale. The reliability and validity of the scale were tested by confirmatory factor analysis, and path analysis was used to conduct hypothesis testing and calculate standardized path coefficients., Results: We enrolled 1357 children with epilepsy (mean age, 8.36 ± 4.04 years). Younger age, being an only child, caregivers' unemployment, and comorbidities were associated with high medication adherence scores. The designed scale of PMT displayed good reliability and validity. Through path analysis of the structural equation model, self-efficacy, susceptibility, and severity exerted significant positive effects on adherence, and external return, internal returns, and reaction cost had significant negative effects on adherence., Conclusions: Medication adherence in children with epilepsy is relatively poor. PMT can explain and predict the medication adherence behavior and behavior intention of patients with epilepsy. It is recommended to increase the health education, personalize medication guidance, and provide telephone interventions to caregivers of children with epilepsy to enhance medication adherence and further improve therapeutic efficacy., 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 © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Soybean is one of the most valuable legume crops in the world. Soybean stay-green syndrome (SGS), which causes delayed leaf senescence (stay-green), flat pods, and abnormal seeds of soybean, has become one of the most serious diseases of soybean in the Huang-Huai-Hai Valley of China. However, the causal agent of SGS was controversial. Until recently, a newly evolved geminivirus with the unassigned genus in the family Geminiviridae, soybean stay-green associated geminivirus (SoSGV) was identified by several individual labs as one of the main causative agents of SGS. The epidemiological assessment reveals that SGS is prevalent in the field and is undergoing geographical expansion and genetic differentiation. The common brown leafhopper (Orosius orientalis) is considered the transmission vector of SoSGV. In this review, we discuss the biology and epidemiology of SoSGV and summarize its occurrence, distribution, and transmission in China, which would benefit further studies and support preventing and controlling this virus., 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 © 2024 Elsevier Inc. All rights reserved.)

Objective: To analysis the differential composition in vaginal microbial communities following HPV infection in Uygur and Han women, and to Explore the correlation between these difference and the degree of Human Papillomavirus (HPV) infection in Uygur women compared to Han women., Methods: A total of 151 Uygur and Han women, with and without HPV, were studied at Xinjiang Uygur Autonomous Region People's Hospital (June 2021-June 2022). These participants were divided into six groups: Uygur control (CV), Uygur transient infection (TPV), Uygur persistent infection (PPV), Han control (CH), Han transient infection (TPH), Han persistent infection (PPH). Vaginal microbiota diversity and dominant bacteria with or without HPV infection were compared using 16S rDNA sequencing., Results: After HPV infection, vaginal pH increased significantly in Uygur and Han women. Vaginal environment cleanliness decreased notably only in Han women (P < 0.05). In Han women, Lactobacillus and Gardnerella dominated both with or without HPV infection. Prevotella, Streptococcus, and Atopobium decreased, while Sneathia increased significantly in persistent HPV cases. Among Uygur women, Gardnerella, Streptococcus, Prevotella, and Shuttleworthia increased significantly in the TPV group, with lower Lactobacillus compared to CV and PPV groups. Bacterial diversity indices (Chao1, Shannon, Simpson) were significantly lower in TPH compared to CH (P < 0.05), with no significant difference in PPH compared to CH (P > 0.05). Chao1 index was significantly lower in TPH than TPV (P < 0.05), with no difference between PPH and PPV (P > 0.05). CV group's Chao1 index was significantly lower than CH (P < 0.01). PCoA and NMDS analyses showed distinct vaginal microbiota between TPH and TPV groups. LEfSe identified 20 differentially expressed taxa in CH-TPH-PPH comparison and 17 in CV-TPV-PPV., Conclusion: Our study reveals ethnic-specific differences in vaginal microbial responses to HPV infection, with notable alterations in diversity and composition. The differential patterns observed between Uygur and Han women underscore the importance of considering host ethnicity in HPV-related microbial dysbiosis, emphasizing the need for tailored interventions targeting microbial signatures to enhance HPV prevention and management strategies., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Min Guo reports financial support was provided by Special Programme for Natural Science Foundation of Xinjiang Uygur Autonomous Region, China. If there are other authors, they 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 © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The genus Sylvirana includes 12 species widely distributed in South China and Southeast Asia. The phylogenetic relationships and species diversity for Sylvirana and allied genera remain unresolved and controversial due to insufficient data and incomplete taxon sampling. Using a combined dataset of mitochondrial genes (16S and COI) and 101 nuclear genes obtained through the amplicon sequence capture approach, we generated the most comprehensive phylogenetic analysis for the genus Sylvirana to date, inferring diversity, phylogenetic relationships, and historical biogeography with unprecedented levels of taxon and geographic sampling. Our results conservatively reveal six undescribed species, mostly distributed in peninsular Indochina. Phylogenetic analyses strongly support the non-monophyly of Sylvirana with respect to Pterorana. Additionally, phylogenetic results place Sylvirana guentheri and Pelophylax lateralis into genus Humerana, supporting the inclusion of Hylarana latouchii, Papurana milleti, and Hylarana attigua within Pterorana + Sylvirana. The long-disputed species of Hylarana bannanica (previously Sylvirana) cluster with genus Papurana. Because the results of multiple non-monophyletic genera create taxonomic confusion, we suggest relegating all genera to subgenus rank of Hylarana. Sylvirana is a junior synonym of the Pterorana. Biogeographically, we trace the origin of Pterorana to Southeast Asia during the early Miocene, with subsequent dispersal thereafter. Our study shows that climatic changes may have profoundly influenced the diversification of Pterorana during the Miocene., 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 © 2024. Published by Elsevier Inc.)

Faced with increasingly severe climate and energy crises, promoting renewable energy development has become an inevitable choice for realizing carbon reduction strategy and energy structure transformation. This paper selects the panel data of 30 provinces in China from 2001 to 2021 and constructs a dynamic spatial Durbin model to study the effect of renewable energy development on carbon emission intensity. The study shows a significant positive spatial correlation between renewable energy development and carbon emission intensity in Chinese provinces. Renewable energy development can significantly reduce carbon emission intensity, and affect the carbon emission intensity of neighboring regions through spatial spillover effects in both the short and long term. In the central-western and southern regions, energy-rich regions, regions with high levels of environmental pollution, high levels of fiscal decentralization, and high levels of green finance, the inhibitory effect of renewable energy development on carbon emission intensity is more significant, suggests that its impact effects are characterized by heterogeneity. Enhancing energy use efficiency, promoting industrial structure optimization, and strengthening green technology innovation capability can significantly improve the inhibition effect of renewable energy development on carbon emission intensity., 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 © 2024 Elsevier Ltd. All rights reserved.)

Pedodiversity conservation is critical for the sustainable use of soil resources and the regulation of ecological security. To explore the relationship between pedodiversity and soil erosion over a prolonged history. In this paper, the response of the regional measurement factor for erosion (RMFE) to pedodiversity at different hierarchical levels was investigated using the optimal window method and structural equation modeling on the basis of water erosion-prone zones. The results suggest that variations in the factors used for soil classification at different hierarchical levels was the main cause of spatial heterogeneity in pedodiversity. Significant impacts of the RMFE on pedodiversity occurred mainly in the Middle reaches of Yangtze River low mountains, hills, plains and basins sub-region (IIC), the Southern China low mountains, hills and plains sub-region (IID) and the Southwestern Yunnan middle and high mountains sub-region (VE) at the Group, Subgroup and Genus levels. Notably, at the Subgroup and Genus levels, the impacts of soil erosion begin to be significant in the Wanda Mt and Sanjiang Plain low mountains and hills sub-region (IA), the Zhejiang and Fujian middle and low mountains, hills and valleys sub-region (IIA), and Taiwan plains and mountains of sub-region (IIE). The regional distribution revealed that pedodiversity in the southeast was more sensitive and positively correlated with the RMFE, with parent material, temperature and anthropogenic activities being the main influences. However, the negatively correlated effects of RMFE on pedodiversity were concentrated in the northeast, where the roles of parent material and vegetation were more critical. The findings of this study are of great practical value and scientific importance for the protection of soil ecological functions and the improvement of regional ecosystem quality and stability., 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 © 2024 Elsevier Ltd. All rights reserved.)

Eutrophication is an ecological process showing the state shift of a lake. This shift could be triggered when the external nitrogen (N) loads exceed N thresholds. Meanwhile, external water inputs and the resulting changes in lake water depth could affect N thresholds. Thus, the shift towards eutrophication may occur more quickly when the N thresholds decrease. Lake Baiyangdian is located in the North China Plain and plays an essential role in ecosystem service provision. However, this lake may have seen a decrease in the N threshold decrease due to frequent water replenishment since 2015. In this study, we compared the external N loads to Lake Baiyangdian with the N thresholds from 2012 to 2017. For this, we considered the effects of water replenishment by linking the MARINA-Lakes and the PCLake + models. Then, we assessed how N thresholds could be met by external N loads from sub-basins of Lake Baiyangdian under 2017 and different N management cases, including improved crop yield and efficiency (S1), improved sewage treatment (S2), improved manure management (S3), and combined options (S4). Results indicate that a 45% reduction in river export of N to Lake Baiyangdian was found from 2012 to 2017. Agricultural sources (fertilizer and manure) accounted for 59% of river exports of N in 2017. River N exports to the lake are projected to be reduced by 13-67% under the four cases. In 2017, the N-load response curve exhibited hysteresis with a 56-87% decrease in N thresholds compared to 2012. Measures in S4 can help to reduce external N exports to Lake Baiyangdian below the N thresholds. Our study emphasizes the importance of combined N management strategies to mitigate the eutrophication risk of the lake. These results offer valuable insights for N management in lake basins experiencing increasing water depth resulting from water replenishment., 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 © 2024 Elsevier Ltd. All rights reserved.)

Investigating demand-side emission reduction through individual behavior and public infrastructure remains a focal point, yet existing studies lack a temporal perspective on their relationship. This study introduces the concept of carbon time intensity (CTI), which refines carbon emission analysis from total quantity to temporal structure, aiming to deepen the understanding of demand-side mitigation through an integrated spatiotemporal framework. This study, drawing on data from the 2021 China Time Use Survey and Household Finance Survey, investigates the mechanisms by which urban basic public service (BPS) affect residents' travel carbon time intensity (TCTI). The analysis reveals that enhancing BPS quality significantly reduces TCTI, primarily through two pathways: altering residents' choices toward low-carbon travel and reinforcing green living concepts with marginal effects of 0.223 and 0.278 respectively. Moreover, the impact of BPS on TCTI exhibits clear heterogeneity across income levels, urban-rural divisions, and geographic regions, with high-income urban populations in developed areas demonstrating substantial yet untapped potential for carbon reduction. Additionally, the gradient boosting tree model identifies a notable plateau in BPS improvements' effect on TCTI, alongside persistent long-term mitigation effects, both following pronounced non-linear patterns. This study preliminarily explores the feasibility of demand-side emission reduction by examining the temporal structure of individual travel-related emissions and delineates key patterns in TCTI influenced by BPS. It provides a theoretical framework for advancing demand-side mitigation through a spatiotemporal approach, offering novel insights and methodologies for more personalized emission reduction strategies within this context., 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 © 2024 Elsevier Ltd. All rights reserved.)

In recent years, data has increasingly become the "new oil" for 21st-century economic development. However, there is still a gap in how the development of big data promotes the improvement of urban carbon unlocking efficiency (UCUE). Utilizing advanced double machine learning (DML) methods, and treating the big data comprehensive pilot zone (BDCPZ) as a quasi-natural experiment, we employ panel data from 282 Chinese cities spanning 2011 to 2022 to study the impact of big data policies on UCUE and its mechanisms. The study finds that: (1) Big data policies significantly enhance carbon unlocking efficiency, and their importance in carbon unlocking is confirmed even when alternative machine learning models are used.(2) Regarding the mechanisms, big data policies improve carbon unlocking efficiency through three pathways: government modernization, enterprise intelligent development, and economic transformation.(3) Heterogeneity analysis reveals that the carbon unlocking benefits of big data policies are more pronounced in large cities, old industrial base cities, digital economy dividend cities and key environmental protection cities. We also provide insights for strengthening the construction of big data, alleviating carbon emission pressures, and achieving the goals of "dual carbon"., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Neng Shen reports financial support was provided by National Planning Office of Philosophy and Social Sciences. If there are other authors, they 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 © 2024 Elsevier Ltd. All rights reserved.)

Since its implementation in 2018, China's environmental tax has become a crucial mechanism in the nation's strategy for reducing environmental pollution. However, its synergistic effect between pollution and carbon reduction has not been adequately focused on and evaluated. This study employs the difference-in-differences (DID) model to analyze the impact of the environmental tax policy on the emissions of pollutant and CO 2 as well as the synergistic effect between them. The baseline results reveal that the implementation of environmental taxes significantly reduces the emissions of SO 2 and CO 2 and enhances the level of synergistic effects. This finding passed a series of robustness tests. Additional analysis reveals that the environmental tax promotes reductions in SO 2 and CO 2 emissions through adjustments in industrial and energy consumption structures. Furthermore, mechanism analysis from an econometric perspective provides theoretical support for the synergistic effect of pollution reduction and carbon mitigation. In the process of achieving CO 2 reduction, SO 2 plays a crucial mediating role. The heterogeneity effect suggests that in non-coastal areas and regions with larger governmental scales, the environmental tax exhibits significant emission reduction effects. It is advisable to strengthen the legal safeguard of environmental tax, dynamically adjust tax rates, and timely expand the tax scope to improve the environmental tax system and enhance its policy effects. This study provides empirical evidence and policy insights to optimize the environmental tax, offering valuable references for environmental tax reforms in developing countries., 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 © 2024 Elsevier Ltd. All rights reserved.)

China is the largest carbon dioxide (CO 2 ) emitter and has formulated CO 2 emission peak and carbon-neutral plans. Studies on CO 2 emission volume and CO 2 emission intensity (CEI) indicate a growing interest in related fields. The purpose of this research is to improve the performance and reliability of the model for forecasting CO 2 emissions and judging whether to achieve China's CO 2 reduction targets under business-as-usual scenarios. We originally applied a novel hybrid model combining the projection pursuit regression (PPR) model and parasitism-predation optimization algorithm (PPA) (PPA-PPR) to forecast the CO2 emissions from 2022 to 2035, with the time series' CO2 emissions data from 1965 to 2017 and compare with various machine learnings. From the studied results, we can conclude that the hybrid PPA-PPR has better stability and accuracy than BPNN, RF, SVM, GM, TDGM, and LSTM models. The mean absolute percentage error (MAPE) of the verification set data is only 1.19%, and the MAPE of forecasting set data from 2018 to 2021 is 1.44, which obviously outperforms the BPNN, RF, SVM, GM, TDGM, and LSTM models. The second finding is that if China continues to develop in its present trend, it can't implement the CO 2 emission peak and reduction CEI target by over 65% by 2030. The limitation of this research is that we don't decompose the time series data into intrinsic modes to study the possibility of improving the model performances., 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 © 2024 Elsevier Ltd. All rights reserved.)

Coordinating the reduction of pollution and carbon emissions (CRPCE) is essential for China's climate governance and environmental protection. However, research on policy synergy related to CRPCE remains limited. To systematically explore the characteristics of policy synergy on CRPCE in China over the long term, this study collects policy documents on pollution reduction and carbon abatement from 2008 to 2023. Utilizing the lenses of policy objectives, policy pathways, and policy tools, text mining and network analysis are employed to develop a tri-level co-word network comprising 'policy elements - policy topics - policy keywords' in phases. Based on the structural characteristics of the network, the evolution trend of policy synergy on CRPCE is examined in detail. The findings indicate that: (1) Although the annual average number of published policies has steadily increased, the synergy among these policies has not risen correspondingly; instead, there was an increase in synergy from 2013 to 2017, followed by a gradual decline after 2018. (2) The fluctuation in synergy among policy elements aligns with the overall trend in policy synergy, while the synergy among topics within different policy elements exhibits varied trends. (3) If significant indirect synergy exists between two topics within the policy pathway and policy objective, the direct synergy between them is expected to strengthen in the future. This study introduces a novel approach to enhance current methodologies for researching policy synergy, providing valuable insights for the formulation of effective CRPCE policies in China and other developing nations., 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 © 2024 Elsevier Ltd. All rights reserved.)

This study offers a novel approach for examining the variations of effective park service radius (PSR) in parks with different sizes (small, medium, and large parks) and temporal conditions (weekday morning-noon (M-N), weekday afternoon-evening (A-E), weekend M-N, and weekend A-E). Using Shenzhen as an example and employing shared-bike order data, a detection tool was developed to identify the effective PSRs of 228 sample parks under different spatiotemporal conditions. Analysis of variance (ANOVA) was used to investigate the variations in PSRs in parks of different sizes and periods and multiple linear regression models were built to investigate the influential mechanisms of PSRs for different sized parks. We found that: 1) the differences in the PSRs between medium and large parks were not statistically significant (p < 0.05), proving that the PSR did not increase stably with an increase in park size, and the gaps in PSRs between parks of different sizes were smaller than those of the values predefined in most planning codes; 2) the PSRs of different sized parks in all temporal conditions displayed statistically significant differences while only the PSRs of small parks demonstrated significant differences across different periods; 3) restaurants, water features, and attractions showed significant and positive effects on the PSR while sports fields and parking lots showed significant and negative effects on the PSR, and the influence of these factors differed significantly as park size varied. These findings can inform future decision-making and park planning in Shenzhen and other bike-friendly cities., 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 © 2024 Elsevier Ltd. All rights reserved.)

In the context of global digitalization, it is of great significance to promote the development of digital economy to reduce carbon emissions and improve green total factor productivity (GTFP). Based on the data of 30 provinces in China from 2011 to 2021, this study constructs a variety of methods, such as Super-SBM model, fixed effect model and intermediary effect model, to empirically test the impact and mechanism of digital economy (DIE) on GTFP. Based on the research findings, the growth of DIE contributes to the improvement of GTFP. Moreover, the impact of DIE on GTFP in eastern China is greater than that in central and western China. There are significant differences between the development level of DIE and GTFP in eastern, central and western regions. Further research shows that digital economy affects the improvement of GTFP through three intermediary variables: economic scale, industrial structure and technological innovation. This study provides empirical evidence to support the effective enhancement of GTFP in developing countries as the digital economy evolves. It provides effective recommendations for developing countries and emerging economies to develop a green economy. However, this study has limitations in data sample, research scope and mechanism analysis depth. Therefore, the conclusions drawn in this study can only provide empirical evidence for identifying the relationship between the DIE and GTFP to a certain extent. Future research should be expanded in these aspects., 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 © 2024 Elsevier Ltd. All rights reserved.)

Although green finance policy is essential for sustainable development, its impact on green development is often underestimated. Using city-level data in China from 2009 to 2022, this study identifies the causal effect of green finance policy on green total factor productivity (GTFP) through an improved synthetic control method. The findings are as follows: First, green finance positively influences GTFP growth, and this effect increases over time. Second, the baseline results remain robust when tested using alternative estimation methods and information criteria. Third, the mechanism analysis shows that green finance policy enhances GTFP through the optimization of energy structure and technological innovation. This study provides new evidence that green finance promotes green development and contributes to addressing global climate change., 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 © 2024 Elsevier Ltd. All rights reserved.)

Water quality monitoring data from various points within the same basin often show non-uniformity. A key scientific question is how to extract relevant knowledge from data-rich sites (source domains) and leverage the possible inter-site consistency of water quality to compensate for the limitations of data-poor sites (target domains). Transfer learning (TL) methods can improve the applicability of water quality predictions for data-poor sites but their comparison and combination have not been fully explored. This study employs feature-based (Transfer Component Analysis, TCA) and model-based (pretraining and fine-tuning) transfer learning, to assist in constructing Long Short-Term Memory (LSTM) models for forecasting the dissolved oxygen (DO) levels in the West Channel of Guangzhou, southern coastal China. The LSTM models at Yagang and Shimen stations were constructed as the basic and baseline models for source and target domains, respectively. By comparing and selecting different transfer learning strategies, the best single-type TL strategy emerged as a multi-sequence LSTM model without TCA but with the fully connected layer frozen after pretraining. It achieved increases in validation Nash efficiency coefficient (NSE) of 5.2%, 10.8%, and 46.2% for predicting DO over the next 3 days, respectively, compared to the baseline LSTM model at Shimen station. The best combined TL strategy involved using TCA and freezing the second fully connected layer in a multi-sequence LSTM model. It improved upon the baseline LSTM model with a validation NSE increase of 5.3%, 21.4%, and 48.7% over the next three days, respectively. This study demonstrates that combining feature- and model-based transfer learning methods can yield better DO prediction performance in data-poor rivers than using a single-type transfer learning method., 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 © 2024 Elsevier Ltd. All rights reserved.)

Exploring farmland production efficiency and demand is helpful to realize the efficient, economical and intensive use of farmland. This study improved the farmland production efficiency evaluation system by incorporating both natural and anthropogenic indices, calculated the farmland use embodied in domestic trade, identified the realistic farmland demand under the assumption of no domestic trade and explored the potentiality of farmland demand reduction by considering the efficiency difference. The results showed that the farmland production efficiencies were high in the eastern coastal, mid-western and northern regions, while the efficiencies of some major grain-producing areas (MGPAs) were low. Embodied in domestic trade, compared with other areas, MGPAs undertook higher direct and indirect farmland use with lower production efficiencies. However, the realistic farmland demand of high-efficiency regions was lower than their initial farmland use area. By coupling production efficiency, the land-use pattern that high-efficiency regions provide farmland externally could create 7.49 × 10 4  km 2 of farmland demand reduction potentiality for the whole country under the current domestic trade system. Some suggestions have been made to reduce the current farmland demand, such as improving the overall production efficiency by strengthening the management of natural elements input, narrowing the efficiency gap between regions by promoting agricultural technology progress, optimizing planting and industrial structure, and adjusting the policy of major grain-producing areas by rationally planning agricultural development and accelerating land transfer., 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 © 2024 Elsevier Ltd. All rights reserved.)

The improvement of coastal saline land would alleviate the problem of insufficient arable land and provide new solutions for guaranteeing food security and ecological environment modification. In this study, five typical soil samples were collected from Tongzhou Bay, China. The changes in bacterial, animal and plant community composition before and after improvement were comprehensively investigated by a combination of high-throughput sequencing and macro-barcode sequencing analysis of eDNA. The study aimed (1) to characterize the species composition and diversity of the bacterial communities in saline soils, (2) to elucidate the mechanisms of salt tolerance of the bacterial communities, and (3) to investigate the impacts of the microbial salt tolerance mechanisms on the regional bacteria and fauna. The results showed that over 15 years of improvement, the composition of the bacteria in the saline-alkaline plots evolved significantly, changing from Desulfovibrio (10.60%) and Campylobacter (11.20%), to Acidobacter (12.91%). After the improvement, salt stress on the bacterial phyla gradually decreased. The functional differentiation of the bacterial phyla became more pronounced. As ion concentrations decreased, the main mechanism of salt tolerance of the bacterial bacteria changed from mainly mechanism of inorganic ion accumulation (55.56%), supplemented by flexible halophilic enzymes (31.77%), to mainly mechanism of compatible solute (44.80%). The mechanism of microbial salt tolerance directly affected micro-diversity and indirectly influenced the diversity of environmental species (R = 0.54). The results of this study provide a scientific basis for coastal saline land as a microbiodiversity marker and for the exploration of microbial improvement of saline land., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Mao ye reports financial support was provided by the National Natural Science Foundation of China. Keyu yao reports writing assistance was provided by NATIVE English Editing. If there are other authors, they 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 © 2024 Elsevier Ltd. All rights reserved.)

Soundscape appropriateness (SA) provides supplemental information on the matching degree between auditory information and the surrounding scene in soundscape perception. This indicator has been integrated into the standard ISO process for collecting soundscape data, forming a component of the sound quality assessment questionnaire. However, its role in soundscape quality assessment has not been fully understood. Herein, we present the findings from soundscape data collected from Beiling Park in Shenyang, China. A method was developed that integrates mediation effect models with multiscale geographically weighted regression models to explore the mediating role of SA in the impact of sound source types on soundscape quality, as well as the spatial heterogeneity of this mediation effect. The results confirm that SA does mediates the influence of sound source types on acoustics comfort (AC). Specifically, natural sounds (indirect effect/total effect = .19/.19), traffic sounds (indirect effect/total effect = -.46/-.65), and commercial sounds (indirect effect/total effect = -.25/-.12) impact the perception of AC by either enhancing or reducing SA. Moreover, the relationships among variables depicted in this model demonstrate spatial heterogeneity, demonstrating that in urban open spaces with complex constructures, local spatial models may be needed for soundscape assessment. The research reaffirms the significance of SA in urban open spaces. In terms of practical implications for urban and landscape planners, when sound sources cannot be controlled or altered, coordinating between the sound and the surrounding environment through landscape optimisation could also improve the quality of the soundscape through enhancing SA and help achieve the goal of creating healthy urban open spaces., 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 © 2024 Elsevier Ltd. All rights reserved.)

The traditional extensive development of the manufacturing industry has caused significant environmental damage. Consequently, the manufacturing sector urgently needs a green transformation to achieve sustainable development. The primary goal of current research is to examine the extent to which green technological innovation (GTI) impacts enterprises' environmental, social, and governance (ESG) performance. Moreover, it determines if this impact varies across enterprises of different natures, resource allocation capabilities, and geographical regions. Furthermore, we will explore how GTI affects the ESG performance of companies through internal and external mechanisms. We empirically examine these issues through panel models using a sample of 3203 Chinese manufacturing firms with 28,334 observations from 2006 to 2022. The findings reveal that (i) GTI significantly enhances firms' ESG performance; (ii) market-based environmental regulation positively influences the relationship between GTI and ESG performance; (iii) GTI contributes to improving a firm's ESG performance by reducing carbon emission intensity; and (iv) the impact of GTI on firms' ESG performance is notably pronounced among non-state-owned enterprises, those with high green total factor productivity, and firms in the central region. Collectively, these findings present a clear pathway for firms to enhance their ESG performance, provide a theoretical foundation for government policy decisions, and contribute to sustainable 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 © 2024 Elsevier Ltd. All rights reserved.)

This study examines how stock market returns in emerging BRICS economies respond to growing physical and transition climate risks. To capture the physical climate risk, we use the frequency of natural disasters, the number of people affected by natural disasters, temperature anomaly, and precipitation anomaly. For transition risk, we included two climate-policy uncertainty measures. First, we conduct a panel-level analysis using a cross-sectionally augmented autoregressive distributed lag model. Second, for country-level analysis, we applied the augmented autoregressive distributed lag model to the monthly dataset from January-2000 to March-2023. The empirical results show that an increase in transition climate risk causes a significant and negative shock to stock returns, both in the short- and long-term in the panel and across each BRICS country. Second, we find that physical climate risk indicators have a significant and negative impact on stock returns in China, India, and South Africa, but not in Brazil or Russia. We conclude that the impact of physical climate risk on stock returns is country-specific, and that the impact of transition climate risk is widespread. These findings provide important insights for investors, regulators, hedgers, portfolio managers, and policymakers regarding policy formulation and future investment strategies., 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 © 2024 Elsevier Ltd. All rights reserved.)

Studies on the potential disruptions that future land use changes may have on trade-offs and synergies among ecosystem services (ESs) in the ecologically fragile region of hilly red soil region (HRSR) are still lacking. We employed multi-source observational data to project the land use patterns expected for the year 2035 in Jiangxi Province - a typical HRSR in China - across three specific scenarios: nature development (ND), economic development (ED), and ecological protection (EP). Through the integration of the InVEST model, correlation analysis, and geographically weighted regression methods, we evaluated habitat quality, soil conservation, water yield, and soil conservation, as well as the associated trade-offs/synergies among ESs. The results showed that the built-up land will continue to increase and occupy a large amount of cropland and woodland, resulting in a 0.79-1.96% reduction for the above four ESs under ND scenario. Under the ED scenario, the cropland and built-up land will increase by 2.95% and 12.00%, respectively, and most of them will convert from woodland, which will reduce ESs by 1.07-1.99%. Under the EP scenario, the expansion rate of built-up land will slow down and woodland will increase by 1.55%, leading to a 0.02-1.58% increase in ESs relative to the ED and ND scenarios. In addition, there were clear trade-offs observed in the ES pairs related to the water yield, while other ES pairs showed synergies. The proportions of counties that will experience changes in trade-off intensity, synergy intensity and the direction of trade-offs/synergies are expected to be 1-31%, 1-47% and 1-37%, respectively, from 2010 to 2035 under different scenarios. The study can provide valuable insights for ecological managers in HRSR in developing land use management strategies that optimize the mutual benefits of various ESs according to local 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 © 2024 Elsevier Ltd. All rights reserved.)

Soil infiltration is essential in the hydrological cycle, fulfilling plant water requirements, particularly in semi-arid regions such as the Loess Plateau. However, comprehensive characterization of soil infiltration responses to different vegetation restoration types remains unclear. Therefore, this study aims to examine the effects of revegetation on soil infiltration by conducting field experiments with nine representative plant species across five vegetation restoration types. Specifically, we focused on how revegetation affects soil and root properties to determine key factors impacting soil infiltration. The results showed that artificial forestland and natural grassland exhibited the most substantial effects on soil properties. Natural grassland exhibited the highest soil aggregate stability and organic matter content. Root length density and root surface area increased after vegetation restoration, most notably in artificial forestland. Root characteristics were positively correlated with aggregate stability, soil organic matter, and porosity. An increase in root surface area significantly enhanced the steady infiltration rate and saturated hydraulic conductivity (P < 0.01). Except for economic forestland, all types of vegetation restoration improved soil infiltration properties, especially notable in Artemisia sacrorum and Platycladus orientalis. The soil infiltration properties in forestland surpassed those in natural grassland, artificial grassland, and shrubland. Random Forest Regression (RFR) suggested that soil particle size, porosity, and aggerate stability were key predictors of soil infiltration properties. Partial least squares structural equation modeling (PLS-SEM) indicated that soil infiltration rates were altered by root-mediated changes in soil porosity. Additionally, soil organic matter exerts an indirect positive effect on infiltration rates by influencing soil aggregate stability. These findings are crucial for evaluating hydrological processes and devising more effective ecological restoration and soil and water conservation strategies in the Loess Plateau., 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 © 2024 Elsevier Ltd. All rights reserved.)

The changes in the carbon emissions in China's provincial construction industries are of high complexity. It is essential to understand the changes in the construction carbon emissions (CCEs) in China on the provincial scale. This study evaluates the factors and structural paths of the changes in provincial CCEs in China between 2012 and 2017 using the structural path decomposition analysis. The results show that the emission intensity effect and production structure effect contributed greatly to the reduction of CCEs across various regions, while the final demand effect had contrary impacts. The local nonmetallic mineral products industry (c13), metal smelting and pressing industry (c14), and electricity industry (c24) generally contributed significantly to the emission intensity effect, production structure effect, and final demand effect across most regions. The consumption of local c13, c14, and c24 by the construction industry (c27), namely "local c13→c27", "local c14→c27", and "local c24→c27" were generally the important structural paths of the CCEs changes across various regions. Nonlocal industries such as Hebei c14 and nonlocal structural paths such as "Hebei c14→c27" contributed substantially to the CCEs changes in many regions such as Beijing. The emission intensity effect, first-order production structure effect, and final demand effect typically dominated the effects of the critical structural paths of the CCEs changes across various regions. This study can help policymakers better understand the changes in China's provincial CCEs to formulate region-specific emission reduction measures and provide a comprehensive reference for related research., 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 © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Against the backdrop of water resource depletion in the Qinghai-Tibet Plateau, water conservation services (WCS) have emerged as critical ecosystem services warranting attention. Adjusting the ecological network (EN) structure and optimizing topological relationships among landscape elements are instrumental in facilitating ecological processes, constituting an effective approach for enhancing WCS. We employed the Integrated Valuation of Ecosystem Services and Tradeoffs model to simulate the WCS value in the Nianchu River Basin and used the Minimum Cumulative Resistance model in combination with the Linkage Mapper to construct an EN. Through topological analysis based on complex network theory, we examined the EN topology and identified ecological pinch points and barriers by applying circuit theory. According to the correlation between EN topology and WCS, and taking into account local vegetation restoration potential, we ultimately optimized the EN to enhance the WCS value. The results revealed a positive correlation between the WCS value and betweenness centrality (r = 0.86, p < 0.01) of forest patches, as well as with the clustering coefficient of grassland patches (r = 0.44, p < 0.05). Following the optimization of key areas with restoration potential, we enhanced the EN structure by adding six new patches, eliminating four redundant corridors, and establishing 11 new corridors. The optimized EN demonstrated enhanced stability in robustness tests, indicated by a reduced slope of edge recovery against malicious attacks (from -0.0224 to -0.0199) and an increase in the WCS value of 630,311.6 m³. This study highlights the importance of landscape spatial structure in enhancing ecosystem services, providing valuable insights for sustainable water resource management in the ecologically sensitive regions of the Qinghai-Tibet Plateau., 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 © 2024 Elsevier Ltd. All rights reserved.)

Aquatic macroinvertebrates inhabiting freshwater wetlands make important contributions to biodiversity. However, environmental characteristics of wetlands is often varied in a specific region, especially in mountainous areas. We investigated 24 depression wetlands and 20 slope wetlands in the Great Xing'an Mountains in Northeast China and aimed to reveal the hydrogeomorphic settings in driving the wetland aquatic macroinvertebrate diversity and offer insights to environmental management. We found that depression wetlands supported higher taxonomic richness and more habitat specialists. Fifteen orders or infraclasses responded positively to depression wetlands, whereas eight orders responded positively to slope wetlands. The composition of aquatic macroinvertebrate assemblages differed significantly between the depression and slope wetlands. Additionally, the variation in species composition in the depression and slope wetlands are largely explained by habitat variables. For community assembly of aquatic macroinvertebrates, both wetland types were largely driven by stochastic processes, with a higher proportion observed in the slope wetlands. Whereas a significant distance-decay relationship and stronger dispersal limitation were detected in the depression wetlands. These findings enhance our understanding of diversity patterns and mechanisms driving aquatic macroinvertebrate community assembly in mountain wetlands. Our research also highlighted the critical need to attach importance to hydrogeomorphic settings and habitat variables in driving aquatic macroinvertebrate diversity for more effective wetland management and conservation., Competing Interests: Declaration of competing interest The authors declare that they have no known financial or personal relationships that may have influenced the work reported in this paper, and no competing interests., (Copyright © 2024. Published by Elsevier Ltd.)

Soybean and maize rotation has been recommended as a promising strategy to maximize crop yield. However, the impacts of soybean-maize rotation, and particularly the frequency of soybean inclusion, on soil quality and carbon (C) stock need to explored. We conducted an 8-year field experiment of randomized design in Northeast China with four cropping systems as continuous soybean (S), continuous maize (M), soybean-maize rotation (SM), and soybean-maize-maize rotation (SMM). The results showed that the soil quality index, soil ecosystem multifunctionality (EMF), and C stock under crop rotation (SM and SMM) were 5.4-23.5%, 13.1-22.6%, and 9.3-29.4% higher than those under continuous cropping (M and S), respectively. Additionally, the increased frequency of soybean in the rotation increased soil EMF by 14.8% due to higher soil enzyme activities and available N. Notably, the soybean-maize rotation alleviated microbial nitrogen (N) limitation compared to continuous cropping, due to stimulated C, N, and P acquisition by enzyme activities. Furthermore, the soil quality index correlated positively with C stock in the topsoil. The accumulation rates of soil organic C and total N were higher by 0.39 and 0.14 g kg -1 year -1 in SMM than in SM, respectively. Therefore, scientifically based soybean frequency is an effective approach to enhance soil organic C in soybean and maize rotation. In conclusion, soybean-maize rotation improves soil quality compared to monoculture, and a reduced frequency of soybean within the rotation (SMM) is beneficial for C and N storage., Competing Interests: Declaration of competing interest We declare that there are no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Developing effective disaster response networks (DRNs) is crucial for mitigating the impacts of rainstorm waterlogging in old communities. Aiming at providing implementable strategies for enhancing DRN resilience, this paper developed an enhanced dynamic network analysis (DNA)-based framework for DRNs utilizing the DNA and CRITIC-VIKOR method. This framework conceptualizes community disaster response as a three-stage 'agent-information-resource-task' (A-I-R-T) dynamic network, facilitating a comprehensive understanding of interactions among stakeholders, disaster information, emergency resources, and response tasks. Subsequently, a hybrid evaluation model combining CRITIC and VIKOR methods was established to quantify DRN resilience by assessing deviations from ideal response scenarios. Validated through a case study of the Y community in Xuzhou city of China, the findings reveal significant variations in stakeholder communication effectiveness across different stages of disaster response, with resilience peaking during the function recovery stage at 0.292. This study not only contributes to the body of knowledge in disaster management and resilience theory but also provides actionable strategies for enhancing DRN resilience, thereby contributing to more resilient urban environments., Competing Interests: Declaration of competing interest The authors declare that they have no conflict of interest., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Wetlands are vital components of the global ecosystem, significantly influencing the retention and dissemination of microplastics (MPs) and antibiotic resistance genes (ARGs). However, the effects of different types of MPs on the environmental dynamics of ARGs within these ecosystems remain poorly understood. This study focused on the distribution and composition of ARGs associated with two primary types of MPs-polyethylene and polypropylene-within the Poyang Lake wetland, the largest freshwater lake in China, utilizing metagenomic analysis. The findings demonstrated that the bacterial communities and ARG profiles in the plastisphere were markedly distinct from those in the surrounding water. Specifically, thirteen opportunistic pathogens and forty subtypes of ARGs, primarily related to multidrug, bacitracin, and β-lactam resistance, were identified in the plastisphere. Notably, polyethylene exhibited four times more specific ARG subtypes than polypropylene. Procrustes analysis combined with network analysis indicated a lack of strong correlation between ARG abundance and bacterial populations, suggesting potential horizontal transfer of ARGs within the microbiota of the plastisphere. Additionally, three novel and functional β-lactamase genes were identified within this environment. This investigation highlights the role of MPs as reservoirs for ARGs, facilitating their exchange and posing risks to both ecological integrity and human health, thereby underscoring the need for increased attention in future research efforts., 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 © 2024 Elsevier Ltd. All rights reserved.)

Investigating trends in water use efficiency (WUE) and its causality is critical for understanding ecosystem behaviors. Although WUE has shown nonlinear changes in the last several decades across most global ecosystems, the majority of available studies have focused on its linear trend. This study attempted to accurately attribute the linear and nonlinear variations in WUE using normalized driving factors in the Partial Derivative (PD) equation to develop a Normalized Partial Derivative model (NPD-model). Two linear trends obtained from the Linear Regression (LR) and Non-Parametric (NP) and a nonlinear trend obtained from the Ensemble Empirical Mode Decomposition (EEMD) are employed in the NPD-model for attributing WUE change in China. The individual and relative responses of driving factors to WUE change during 2000-2018 are quantified using the China version of the PML-V2 evapotranspiration and gross primary productivity products. The results show that the nonlinear EEMD-based NPD-model with an R 2 of 0.83, performs best compared to the LR- and NP-based NPD-models, which have R 2 values of 0.64 and 0.7, respectively. WUE increased monotonically in most areas of all vegetation types, with high variability observed in grassland and shrubland. The EEMD-based attribution analysis indicates that leaf area index is the leading factor in regulating WUE in China, followed by CO 2 and climate. The relative contributions revealed that increased WUE in most of China is dominated by the combination of vegetation and environmental factors, covering more than 80% of the study area. These contribution results, however, are largely different from those obtained using the LR- and NP-based NPD-models, as 52% of the study area exhibits cyclic variation in WUE. Therefore, the nonlinear EEMD-based NPD-model provides excellent spatiotemporal attribution of WUE through its driving factors, which is crucial for understanding the ecosystem response to changing environments, potentially assisting in ecosystem and water resource management., 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 © 2024 Elsevier Ltd. All rights reserved.)

Purpose: This research investigates the effects of biochar application on rice quality through a comprehensive meta-analysis, aiming to elucidate the ambiguous impacts of biochar on rice quality indicators and providing a comprehensive quantitative evaluation to inform sustainable agricultural practices and the practical application of biochar in rice cultivation., Design/methodology/approach: Utilizing a systematic meta-analysis, this study extracts 934 pairs of observations from 28 different studies. It integrates data to assess the overarching impact of biochar on rice quality, with a specific focus on ten essential quality indicators: brown rice rate, milled rice rate, head rice rate, chalky rice rate, degree of chalkiness, length-width ratio, amylose content, protein content, gel consistency, and eating quality score. This approach enables a detailed evaluation of how biochar application influences these critical aspects of rice quality., Findings: The meta-analysis reveals that biochar application notably enhances the processing, appearance, and eating quality score of rice, evidenced by improvements in the brown rice rate by 0.5%, milled rice rate by 1.7%, head rice rate by 6.2%, length-width ratio by 1.4%, and eating quality score by 2.6%. It also substantially reduces the chalky rice rate by 11.1% and the degree of chalkiness by 12.9%. However, the impacts on nutritional indicators, such as amylose content, gel consistency, and protein content, were found to be statistically insignificant. The most favorable effects were observed in heavy loam soil, alkaline soil(pH ≥ 7.5), soil organic content (SOM)＜10 g kg -1 , biochar with a pH range of 7-8, high-temperature biochar (≥ 400 °C), and biochar derived from husk and shell., Practical Implications: This study highlights biochar's potential to improve rice quality, particularly in terms of processing and appearance, without negatively affecting its nutritional profiles. These findings support the utilization of biochar in rice production to improve quality and provide valuable insights for the development of sustainable agricultural practices and effective biochar application guidelines., Originality/value: This study represents a pioneering effort in agricultural science by systematically quantifying the impact of biochar on key rice quality indicators. It sheds light on the positive effects of biochar in enhancing various aspects of rice quality, underscoring its vital role in promoting sustainable agricultural practices. Through this meta-analysis, the study establishes a foundation for effective biochar usage guidelines in rice cultivation, offering substantial insights and paving new avenues for research into biochar's application in agriculture., 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 © 2024 Elsevier Ltd. All rights reserved.)

Recent studies have demonstrated that monocropping of flue-cured tobacco can lead to various issues, including nutrient deficiencies, accumulation of allelopathic substances, and disturbance in soil microbial flora. While diversification in cropping systems has proven effective in alleviating monocropping barriers, however, further exploration is needed to understand the potential microbial mechanisms involved in this process. In our study, we set five cropping systems (RR: rice monocropping; TR: tobacco-rice rotation over 20 years; TRA: tobacco-rice-astragalus rotation; TRW: tobacco-rice-wheat rotation; TRO: tobacco-rice-oilseed rape rotation) to explore the impact on crop yield and quality, soil chemical properties, and microbial diversity. The results showed that the yield and gross margin were significantly decreased. Following diversification in cropping systems, particularly after implementing the TRA treatment, the yield and gross margin increased by 27.35% and 38.67%, respectively, compared to the TR treatment. Additionally, the presence of tobacco in the soil resulted in acidification, reduced soil fertility, and suppression of soil microorganism diversity and metabolite abundance. With diversification in cropping systems, there was an increase in soil pH, carbon and nitrogen cycle enzyme activities, and the relative abundance of beneficial microorganisms (acidobacteria, nitrospirillum, and ascomycota) and soil metabolites. Diversification in cropping systems has the potential to increase crop biomass, soil fertility, and soil microbial environment. Our results suggest a scientific foundation for implementing effective nutrient management practices and rational crop rotation systems., 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 © 2024 Elsevier Ltd. All rights reserved.)

Climate heterogeneity is commonly associated with exceptionally high species richness, thus bolstering ecological resilience and maximizing long-term biodiversity benefits. However, few studies have been conducted to examine the implications of climatically heterogeneous areas (CHAs) for effective biodiversity conservation. In this study, we collected occurrence records of birds and vascular plants in a biodiversity hotspot in Yunnan, China, and delineated corresponding CHAs. The conservation effectiveness of CHAs for species diversity was demonstrated through a comparison of climate- and species-based prioritization schemes, incorporating surrogacy analysis and species representation. Despite significant spatial discrepancies with species-based conservation prioritization, we found that a prioritization scheme based on CHAs would effectively conserve more than 86.3% of Yunnan's birds and vascular plant species, regardless of spatial scale. The coverage of protected areas for priority conservation areas of two prioritization schemes is relatively low (<14.4%). Therefore, our study also underscores the significant conservation gaps for birds and vascular plants in Yunnan revealed by both prioritization schemes, with the latter emphasizing the crucial roles of mountainous regions, gorges, and particularly dry valleys along the Jinsha River and Yuanjiang River. These conservation gaps provide complementary and previously hidden potential conservation areas for the preservation of species diversity in Yunnan. Overall, our study demonstrates that incorporating CHAs into conservation prioritization represents a smart and effective approach for safeguarding species diversity, serving as a paradigm for integrating abiotic factors into conservation planning and providing valuable strategies to conserve species diversity in biodiversity hotspots., 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 © 2024 Elsevier Ltd. All rights reserved.)

Faced with the environmental pollution challenges brought by urbanization, smart city construction (SCC) offers a practical and viable pathway for environmental protection. This study treats China's SCC policy as a quasi-natural experiment, utilizing balanced panel data from 285 cities across the country spanning from 2003 to 2019. Through the multi-period Difference-in-Differences (DID) model, the influence of smart city initiatives on urban pollution emissions is systematically examined. Results demonstrate that SCC effectively control urban pollution emissions, leading to a 1.46% decrease in pollution levels in pilot cities. These findings are robust to various tests, including parallel trends analysis, placebo tests, Propensity Score Matching (PSM)-DID, alternative pollution calculation methods, pollution intensity adjustments, control for other policy interferences, and sample adjustments, alongside endogeneity tests using instrumental variables. SCC achieves pollution control through mechanisms that enhance urban technological innovation, facilitate industrial restructuring, and talent agglomeration and financial agglomeration. Heterogeneity analysis reveals a more pronounced impact in the eastern area, large cities, higher administrative levels, cities with superior digital infrastructure, and those with higher human capital levels and pollution severity. This research explores a practical approach towards achieving sustainable pollution control by optimizing technology, industrial structure, and human resources., 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 © 2024 Elsevier Ltd. All rights reserved.)

The contribution of biodiversity to supporting ecosystem multifunctionality (EMF) is well established in natural ecosystems. However, the effects of multidimensional understory diversity, such as taxonomic diversity (TD), functional diversity (FD), and phylogenetic diversity (PD), on EMF remain largely unknown in plantations. Here, we investigated the TD, FD, PD, and EMF in plantations (Pinus tabuliformis, Robinia pseudoacacia, Platycladus orientalis) and natural forests (Quercus wutaishanica) on the Loess Plateau and examined the effects of stand structure, topography, and understory multidimensional understory diversity on EMF. The results showed that on the Loess Plateau, plantations had lower TD and PD than natural forests. However, the differences in FD between plantations and natural forests were nonsignificant. Natural forests were associated with higher EMF than plantations, except R. pseudoacacia, which performed better in N cycling function and water conservation. In general, EMF was positively correlated to TD, PD, and community-weighted means (CWM, represents the first principal component axis composed of eight leaf traits: leaf area, leaf dry matter content, leaf thickness, specific leaf area, leaf water content, leaf nitrogen content, leaf phosphorus content, and leaf carbon content). In contrast, EMF was negatively correlated to FD. In particular, CWM, FD, and PD mainly affected the N and P cycling, water conservation, and productivity of plantations. The structural equation models indicated that forest stand structure had a direct influence on EMF, while both forest stand structure and topography had an indirect influence on EMF through their effects on multidimensional understory plant diversity., 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 © 2024. Published by Elsevier Ltd.)

The adoption of organic fertilizers is crucial for improving sustainable agricultural development in China. Digital agricultural extensions offer personalized guidance to farmers, delivering these services more cost-effectively and rapidly. This paper, conducted in Shaanxi Province with a total of 495 kiwifruit farmers, employs an endogenous switching regression model to empirically examine the influence of digital agricultural extensions on the purchasing behaviors associated with organic fertilizers. The findings reveal three key insights. First, digital agricultural extensions significantly boost the likelihood of farmers purchasing organic fertilizers. Second, public welfare digital extensions have a more pronounced effect on these purchasing behaviors compared to those driven by profit motives. Finally, digital agriculture extensions facilitate organic fertilizer adoption by enhancing ecological literacy and broadening information channels. Based on these findings, the government is recommended to robustly support digital agricultural extensions, develop a supply system prioritizing public welfare with profit-driven approaches as supplementary, to encourage the adoption of organic fertilizers., 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 © 2024 Elsevier Ltd. All rights reserved.)

The mutual empowerment and coordinated advancement of digitization and greening are intrinsic requirements for social development. This paper collects data from 30 provinces in China from 2013 to 2023 to measure the level of digitization and greening. Then, we use the coupling coordination degree model to clarify the coupling coordination relationship between the two, and utilize the Gini coefficient to explore the degree of difference and the trend of change. Finally, the driving factors affecting coupling coordination are analyzed by using geographic detector. The results indicate that the levels of digitization and greening in China have steadily improved, showing a spatial feature of "high in the east and low in the central and western regions". Digitization and greening have experienced marginal coordination, low coordination, and finally entered the stage of moderate coordination. The overall difference is mainly caused by inter-regional differences. The digitization, greening, economic level, and technology innovation are the major driving factors for coupling coordination of digitization and greening. Therefore, the government should steadfastly guide digitization and greening, and introduce targeted policies for the synergistic development of digitization and greening in accordance with local 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 © 2024 Elsevier Ltd. All rights reserved.)

As an essential market player, corporations play a crucial role in achieving green and sustainable economic development, while information technology is vital in influencing corporate environmental decision-making. Therefore, using a sample of A-share listed companies in China from 2009 to 2021, we developed a measurement for IT change through computer-aided text analysis to investigate the impacts of IT change on corporate environmental violations. The key findings are as follows: (1) a 1% increase in external or internal IT change can reduce corporate environmental violations by approximately 0.139 and 0.204. (2) IT change influences corporate environmental violations through monitoring and knowledge acquisition mechanisms. (3) IT change significantly affects environmental violations in firms that are large in size, lack government supervision, and adopt cost leadership strategies. (4) IT change complements green credit policies and positively affects firms in non-green credit-restricted industries. To sum up, this paper contributes to understanding the factors that influence corporate environmental decisions and offers insights into promoting the construction of IT change., 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 © 2024 Elsevier Ltd. All rights reserved.)

Microplastics (MPs) are widespread in farmland soil. However, the risks associated with their loss through soil erosion remain unknown. This study investigates the occurrence and behavior of MPs in farmland soil in a southeastern coastal area of China, focusing on their synchronized dynamic release during soil erosion scenarios. The results showed that the abundance of MPs in the tested farmland soil ranged from 2.40 × 10 4 to 1.04 × 10 5 items·kg -1 . MPs predominantly appear as fragments and particles, with sizes concentrated between 30 and 100 μm. During the process of soil erosion, characterized by rapid soil subsidence, the amount of MPs released into water bodies initially decreases, averaging a reduction of 1.08 × 10 4 items·kg -1 . This is followed by an average increase of 1.89 × 10 4 items·kg -1 . The competition between the adsorption, collision, and sedimentation of soil particles and the desorption and release of settled particles, determines this behavior. This pattern is strongly related to the physicochemical properties and mechanical composition of the soil. Deep learning predictions revealed that, without external influences, 49.42% of MPs in farmland soil could be synchronously released into water bodies during erosion. The analysis shows that MPs exhibit dynamic behavior in time and space, posing serious threats to aquatic ecosystems. Controlling soil erosion in farmland is crucial for the source management of MP migration., 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 © 2024 Elsevier Ltd. All rights reserved.)

While the identification of critical ecological areas (CEAs) has been limited by the availability of resources, funds, and land space, these areas are central for maintaining the contributions from nature and ecosystem biodiversity. Thus, in this study, CEAs were systematically identified and classified via long-term ecosystem assessment with a multifunctionality-stability-integrity framework in the Yellow River Basin (YRB). The intensity and pathways of the driving factors of CEA dynamics were also determined by the geographical detector model (GDM) and the partial least squares structural equation model (PLS-SEM). The results revealed a gradual decrease in the proportion of CEAs in the upper and lower reaches from 2005 to 2020, in contrast with a significant increase in the middle reaches. The CEAs were distributed mainly in the Sanjiangyuan and Ziwuling regions and the Qingling, Qilian, Lvliang and Taihang Mountains. The areas with low, medium, and high levels of CEAs accounted for 12.48%, 17.73% and 12.54%, respectively, of the YRB. Moreover, climate factors, especially precipitation, were the foremost drivers influencing the dynamic patterns of CEAs. However, notably, the CEAs in the YRB experienced continuous degradation from 2005 to 2020 due to intensified human activities. Our results confirmed the important role of climate factors in determining the distribution of CEAs while underscoring the necessity of mitigating human disturbances to maintain ecosystem functions. These investigations of the dynamics and drivers of CEAs based on long-term multi-dimensional ecosystem assessments could provide useful insights for developing ecological conservation and sustainable development strategies., 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 © 2024 Elsevier Ltd. All rights reserved.)

Water pollution control in transboundary watersheds can improve the water environment quality, alleviate water resource conflicts, and is an important guarantee for achieving healthy and stable development of watersheds. Ecological compensation is an important measure to solve the problem of water pollution in transboundary watersheds and has been widely applied in China. We constructed differential game models for water pollution control in transboundary watersheds under four scenarios: (1) no ecological compensation scenario, (2) upstream one-way ecological compensation scenario, (3) downstream one-way ecological compensation scenario, and (4) upstream and downstream two-way ecological compensation scenario. We studied the optimal water pollution control strategies and ecological compensation strategies under different scenarios, and compared the results obtained under different scenarios to explore which scenario has better water pollution control and ecological compensation, as well as the applicable conditions for different one-way ecological compensation. The results indicate that both upstream and downstream one-way ecological compensation can promote water pollution control, and the optimal one-way ecological compensation should be determined based on the cost and benefit parameters of upstream and downstream water pollution control. The upstream and downstream two-way ecological compensation can reduce the pollutant reduction furthest and improve the social welfare extremely, making it the best ecological compensation. Finally, it is necessary to actively promote the formation of two-way ecological compensation in the upstream and downstream of transboundary watersheds to achieve long-term sustainable development of the watershed., 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 © 2024 Elsevier Ltd. All rights reserved.)

Energy-intensive industries in China are generally water-intensive. In the context of clean energy and electricity substitution driven by the carbon peaking goal, few studies have examined changes in industrial water resources in this development. To address this knowledge gap, a new framework is proposed for quantitatively analyzing industrial water conservation pathways. This study focuses on the nine provinces in the Yellow River Basin (YRB). It employs a bottom-up approach to estimate the overall water consumption of the power and steel industries, which are two key components of both energy-intensive and water-intensive sectors. Subsequently, decomposition analysis was used to identify the key factors affecting inter-annual water consumption changes. Based on the above information, indicators are established to quantify the potential for water conservation, and scenario analysis is utilized to measure and evaluate the water conservation potential of the study area. The results show that the total water consumption for power generation in nine provinces is projected to reach 5.13 billion m 3 by 2030, with an average water consumption factor of 0.97 m 3 /MWh. Simultaneously, the total water consumption for steelmaking is expected to be 820 million m 3 , with an average water consumption factor of 2.89 m 3 /t. The increase in water consumption can be decoupled into scale, structure, and intensity effects, which have positive, negative, and negative impacts, respectively. By 2030, the nine provinces have the potential to conserve up to 4.57 billion m 3 of water through clean energy and electricity substitution, traditional technology improvement, and inter-regional transmission. These results will contribute to the future coordinated management of energy and water resources., 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 © 2024 Elsevier Ltd. All rights reserved.)

Regional disparities in energy efficiency persist despite the significant potential offered by the digital economy for China's low-carbon transition. From a technology applications perspective, this study analyzed the configurations and conditions of digital economy and recommendations that are crucial for promoting overall energy efficiency improvements. This study begins by calculated and analyzed the spatiotemporal characteristics of CEE across 30 provinces in China from 2011 to 2021 by using the SBM-Undesirable model. Based on the Technology-Organization-Environment (TOE) perspective, we combined fs QCA and NCA to identify multiple conjunctural causations, asymmetries, and hidden pathways that support the low-carbon transition. Finally, this study provides a new policy scheme for China's low-carbon transition. The results indicated that: (1) CEE has improved over time, with significant improvement in the east and west, while the central region lags; (2) no single element of the digital economy is sufficient to ensure high CEE; (3) The impact of the digital economy on CEE involves complex causal relationships and asymmetries, with four effective pathways identified: human capital-driven, finance-technology complementarity, technology-organization complementarity, and balanced element integration. This study provides policymakers with systematic empirical evidence and targeted policy recommendations to promote regional industrial digital transformation, bridge regional disparities in carbon emission efficiency, and achieve overall sustainable 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 © 2024 Elsevier Ltd. All rights reserved.)

Rapid urbanization and industrial growth have led to water quantity and quality problems. Most current water allocation models focus solely on physical water and neglect the optimization of the water quantity and quality considering the water footprint. Therefore, this study aimed to establish an optimal water resource allocation model for industrial sectors based on the water footprint to identify the most effective strategies for determining the water quantity and quality distribution in river basins. First, we constructed an improved water footprint accounting system using input‒output tables to quantify the total water footprint, grey water footprint, and virtual water trade. Second, we constructed a multiobjective optimal water resource allocation model by considering the water footprint as a decision variable and combining regional economic development and productivity differences. Finally, we compared the water allocation results obtained for the Yellow River Basin, a typical "water-quantity water-scarce region" in China, with those of the Yangtze River Basin, a "water-quality water-scarce region." The results indicate that the total water footprints of the Yellow and Yangtze River Basins were 211.37 and 317.83 billion m³, respectively, prior to optimization. After optimization, the footprints were 199.54 and 306.03 billion m³, respectively. Water resources have been reallocated through virtual water trade strategies to effectively alleviate both water quantity and quality problems. Virtual water trade strategies have emerged as policy tools capable of mitigating mismatches between industrial systems and regional water resource allocation and providing a solution to physical-virtual water system challenges within river basins., 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 © 2024 Elsevier Ltd. All rights reserved.)

The continuous impact of COVID-19 on aquatic environments has attracted considerable attention, primarily focusing on short-term water quality effects during lockdown, while studies on changes following the lifting of restrictions are relatively limited. Following adjustments to China's pandemic public policy in December 2022, the effects on water quality and nutrient status in lakes and reservoirs remain unclear. In this study, we collected national environmental monitoring data comprising 15 indicators of water quality, meteorology, soil, and economic factors, from 86 lakes and reservoirs across China between March 2021 and December 2023. Total nitrogen (TN), total phosphorus (TP), the mass TN/TP ratio (TN/TP), and ammonia-nitrogen (NH 3 -N) were selected as representative nutrient indicators. The water quality index (WQI) and multivariate statistical techniques were employed to comprehensively assess national water quality and identify the drivers of nutrient variations in sub-regions. The results show that during the monitoring period from 2021 to 2023, Chinese national water quality consistently fell within the 'good (61-80)' or 'excellent (81-100)' categories, with the lowest water quality observed in the summer of each year. The summer of 2021 recorded the lowest WQI value among all seasons at 75.01. Following the elimination of the COVID-19 epidemic public lockdown policy, concentrations of TN, TP, and NH 3 -N declined. These findings indicate a general improvement in the water quality of lakes and reservoirs nationwide. Mantel test and multiple stepwise linear regression models revealed significant correlations between nutrients and human activity indicators in central, eastern, and northern China. In northern China, TP showed a significant positive correlation with GDP (0.2 < Mantel's r < 0.5, P < 0.05), with the beta value increasing from 0.27 to 0.38 after the elimination of the COVID-19 epidemic public lockdown policy. In these regions, the influence of rainfall, wind speed, NDVI, surface soil moisture, and water temperature on nutrients shifted from significant to insignificant effects after the elimination of the COVID-19 epidemic public lockdown policy, indicating that human activities have overshadowed natural factors. This study examines the water quality and nutrient status of lakes and reservoirs in China after the elimination of the COVID-19 epidemic public lockdown policy, highlighting the long-term impacts and spatial variations of the pandemic. These findings will inform environmental governance and promote sustainable water resource management in the post-pandemic era., 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 © 2024 Elsevier Ltd. All rights reserved.)

Cadmium (Cd) pollution poses a significant threat to wetland ecosystems. Phragmites australis, a species with intraspecific ploidy diversity, is commonly used in constructed wetlands for pollution remediation. However, little is known about how the ploidy variation of P. australis influences the phytoremediation processes via physiological and rhizosphere regulations. Here, we used P. australis from two major lineages in China (i.e., tetraploid lineage O and octoploid lineage P) and applied three Cd treatments (control, low Cd concentration, and high Cd concentration). We found that the lineage O had a bioconcentration factor of Cd approximately 40% higher than that of the lineage P. The translocation factor of the lineage P was about 300% higher than that of the lineage O. These suggest that the lower ploidy lineage exhibited a greater capacity to absorb Cd from the environment into the underground part compared to the higher ploidy lineage, and the higher ploidy lineage demonstrated a superior ability in transferring Cd from the underground to the aboveground part. The advanced transpiration system in the higher ploidy lineage can contribute to its enhanced ability to translocate Cd, as the translocation factor of Cd was significantly correlated with the base shoot diameter and the transpiration rate, both notably higher in the lineage P. The rhizobacterial community associated with the lineage P displayed a more intense response to Cd, characterized by an increase in both the diversity of the community and the number of varied bacterial functions following the addition of Cd. Our study offers profound insights into the ecological consequences of intraspecific polyploidization and the application of intraspecific ploidy variation in environmental management and wetland restoration., 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 © 2024 Elsevier Ltd. All rights reserved.)

Assessing groundwater quality is essential for achieving sustainable development goals worldwide. However, it is challenging to conduct hydrochemical analysis and water quality evaluation by traditional methods. To fill this gap, this study analyzed the hydrochemical processes, drinking and irrigation water quality, and associated health risks of 93 groundwater samples from the Sichuan Basin in SW China using advanced unsupervised machine learning, the Combined-Weights Water Quality index, and Monte-Carlo simulations. Groundwater samples were categorized into three types using the self-organizing map with the K-means method: Cluster-1 was Ca-HCO 3 type, Cluster-2 was dominated by Ca-HCO 3 , Na-HCO 3 , and mixed Na-Ca-HCO 3 types, Cluster-3 was Ca-Cl and Ca-Mg-Cl types. Ion ratio diagrams revealed that carbonate dissolution and silicate weathering primarily influenced the hydrochemical characteristics. Cluster-1 samples exhibited high NO 3 - contents from intensive agricultural activities. Cluster-2 samples with high Na + contents were characterized by positive cation exchange, while Cluster-3 samples with elevated Ca 2+ and Mg 2+ contents were influenced by reverse cation exchange. Combined-Weights Water Quality Index indicated that 62.37% of total samples were suitable for drinking, predominantly located in the central part of the study area. Irrigation Water Quality Index revealed that 33.34% of total samples were suitable for irrigation, mainly in the northeastern region. NO 3 - concentration and electrical conductivity (EC) value were the main indicators with the highest sensitivity for drinking and irrigation suitability, respectively. Probabilistic health risk assessments suggested that a significant portion of the groundwater samples posed a health risk greater than 1 to children (63%) and adults (52%) by Monte-Carlo simulation. The high-risk areas (hazard index >4), primarily in the eastern region, are closely associated with nitrate distribution. Sensitivity analysis demonstrated that NO 3 - concentration is the primary indicator accounting for health risks. Reducing the application of nitrogen-based fertilizers on cultivated land is the most effective approach to improve drinking quality and mitigate the associated health risks to the population. This study's findings aim to produce a novel groundwater quality evaluation for promoting the sustainable management and utilization of groundwater resources., 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 © 2024 Elsevier Ltd. All rights reserved.)

Human activities have altered the quantity and distribution of cropland, and climate change profoundly affects crop productivity. However, the spatiotemporal patterns and driving mechanisms of crop productivity remain unclear. Here, we analyze the spatiotemporal evolution of Chinese crop productivity using long-term satellite observation data. We employ the residual trend analysis method to separate the relative contributions of climate change and non-climate factors to crop productivity. Our results indicate the following: (1) from 2001 to 2020, China's crop productivity increased by approximately 0.11 kgCm -2 yr -1 , which compensated for the decline in crop yields caused by a reduction in cropland area. (2) Crop productivity exhibits significant spatial heterogeneity, with notable differences between the southern and northern regions of China. Both cropland and crop productivity show a northward shift, with the migration distance of the mean center of crop productivity exceeding that of cropland. (3) Agricultural production inputs are closely related to crop productivity, but climate change remains the primary factor influencing changes in Chinese crop productivity. Crop productivity in northern China is more sensitive to climate change, and the dominant factors vary among different agricultural districts. (4) Over the study period, long-term crop cultivation in northern China has benefited the net primary productivity of surface vegetation, though the sustainability of production faces challenges. This study is of great importance for maintaining food security and promoting sustainable agricultural development, offering guidance for cross-regional cropland compensation., 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 © 2024 Elsevier Ltd. All rights reserved.)

Definite setting of water quality target is a challenge when considering non-point source (NPS) pollution which demands reasonable allocation of reduction requirements. However, research on the dynamic water environmental capacity (WEC) allocation aimed at reflecting varying rainfall conditions has rarely been performed. In this study, the relationship between rainfall and WEC was explored by a stochastic algorithm, while then reduction target was allocated in a small catchment, the Three Gorges Reservoir Region (TGRR), China. Combined with the distributed model, three commonly adopted best management practices (BMPs) were located precisely. The results indicate that a specific rainfall threshold exists for water quality (84 mm/month for the study area) which reveals the comprehensive effect of rainfall flushing and dilution effect. At 90% confidence, the total phosphorus (TP) load was 1518 kg/yr, and the ideal WEC was 1194 kg/yr, with excess of 324 kg/yr. In addition, the highest amount of inflow phosphorus can be reduced by fertilizer reduction (FR) with 303.8 kg/yr. Besides, slope-to-terrace (ST) measures should be implemented mainly in the upper reaches, while FR should be preferentially considered in the lower reaches. For the small watershed dominated by agricultural NPS, this study can provide accurate water quality target settled by WEC calculation impacted by uneven rainfall and a feasible watershed management., 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 © 2024 Elsevier Ltd. All rights reserved.)