Environmental Science and Ecotechnology最新文献

{"title":"Temperature-dependent microbial dynamics in touchless sensor faucets during short-term stagnation","authors":"Anran Ren ,&nbsp;Zihan Dai ,&nbsp;Xiaoming Li ,&nbsp;Walter van der Meer ,&nbsp;Joan B. Rose ,&nbsp;Gang Liu","doi":"10.1016/j.ese.2025.100624","DOIUrl":"10.1016/j.ese.2025.100624","url":null,"abstract":"<div><div>Microbial contamination in building plumbing systems poses significant risks to public health at the point of use. Stagnation and warm temperatures are well-known drivers of microbial regrowth, but the effects of common short-term stagnation in touchless sensor faucets—widely used for hygiene and comfort—remain poorly understood. Here we show that microbial water quality in touchless sensor faucets changes during short-term stagnation (0.25–10 h) at varying temperatures (10, 30, and 40 °C). We identify two pivotal time points—2 and 4 h—where microbial diversity decreases and <em>Legionella pneumophila</em> concentrations increase significantly, driven by accelerated chlorine decay and biofilm contributions. Heating to 30 °C maximizes microbial biomass (measured as ATP) but minimizes <em>L. pneumophila</em> proliferation, whereas 40 °C reduces biomass while promoting <em>L. pneumophila</em> growth. These findings reveal a temperature-dependent microbial water quality guarantee period of 2–4 h, beyond which flushing is necessary to mitigate health risks. Optimizing faucet temperatures between 30 and 40 °C could balance microbial safety, user comfort, and energy efficiency, offering practical guidance for managing water quality in modern plumbing systems.</div></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"28 ","pages":"Article 100624"},"PeriodicalIF":14.3,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145223411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tropical intertidal microbiome response to the 2024 Marine Honour oil spill","authors":"Christaline George ,&nbsp;Hashani M. Dharan ,&nbsp;Lynn Drescher ,&nbsp;Jenelle Lee ,&nbsp;Yan Qi ,&nbsp;Yijin Wang ,&nbsp;Ying Chang ,&nbsp;Serena Lay Ming Teo ,&nbsp;Benjamin J. Wainwright ,&nbsp;Charmaine Yung ,&nbsp;Federico M. Lauro ,&nbsp;Terry C. Hazen ,&nbsp;Stephen B. Pointing","doi":"10.1016/j.ese.2025.100623","DOIUrl":"10.1016/j.ese.2025.100623","url":null,"abstract":"<div><div>Marine fuel oil (MFO) spills in tropical coastal environments are under-characterized despite increasing risk from maritime activities. Microbial and geochemical responses to the June 2024 Marine Honour MFO spill on Singapore's intertidal sediments were analyzed in real time over 185 days. Using metagenomics and hydrocarbon profiling, microbial community shifts and hydrocarbon degradation were quantified across visibly oiled (high-impact) and clean (low-impact) sites. Microbiomes at all sites adapted rapidly to the spill through increased diversity and abundance of genes encoding alkane and aromatic compound degradation, detoxification, and biosurfactant production. The dominant hydrocarbon-degrading bacteria differed markedly from those reported in other crude oil spills and in regions with different climates. Oil deposition intensity strongly influenced microbial succession and hydrocarbon-degrading gene profiles, and this reflected early toxicity constraints in heavily oiled areas. The persistence of hydrocarbon degradation genes beyond hydrocarbon detection in sediments suggested long-term functional priming may occur. The study provides novel genome-resolved insight into the microbial response to MFO pollution, advances understanding of marine environmental biodegradation, and provides urgently needed baseline data for oil spill response strategies in Southeast Asia and beyond.</div></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"28 ","pages":"Article 100623"},"PeriodicalIF":14.3,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145128305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-time sludge moisture monitoring via jet imaging and deep learning","authors":"Tiefu Xu ,&nbsp;Bo Zhang ,&nbsp;Yue Sun ,&nbsp;Man Wang ,&nbsp;Yuejia Chen ,&nbsp;Penghe Zhu ,&nbsp;Binqiao Ren ,&nbsp;Yanhong Jie ,&nbsp;Guotao Wang","doi":"10.1016/j.ese.2025.100614","DOIUrl":"10.1016/j.ese.2025.100614","url":null,"abstract":"<div><div>Waste activated sludge from wastewater treatment plants poses a major environmental challenge, with its high moisture content complicating disposal and resource recovery processes across global industries. Efficient sludge management requires precise moisture monitoring to optimize treatment methods, reduce costs, and enhance outcomes such as anaerobic digestion and composting. Traditional approaches for moisture measurement are time-intensive and batch-based, while emerging techniques, such as infrared or nuclear magnetic resonance methods, suffer from inaccuracies, high costs, or limitations in real-time applications. Here we show that sludge jet characteristics, reflecting its non-Newtonian fluid properties, can be captured via high-speed imaging and analyzed with deep learning to accurately predict moisture content within 20 s. By developing a laboratory-scale system of instantaneous capturing of activated sludge jet expansion images (iCASJEI), we acquired over 11,000 jet images across 79–94 % moisture ranges and trained convolutional neural networks, with VGG-16 outperforming AlexNet and LeNet under optimized conditions (0.2 MPa pressure, 4 mm aperture), achieving 93.5 % validation accuracy at 2 % precision and 87.6 % at 1 % precision. These findings show that incorporating iCASJEI to extract non-Newtonian fluid characteristics from sludge jets with deep learning algorithms can substantially reduce testing time for sludge moisture content. This approach could also be applicable to other sectors where non-Newtonian fluid characteristics enable real-time moisture detection in viscous liquids.</div></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"27 ","pages":"Article 100614"},"PeriodicalIF":14.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145019003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Two decades of ecological wisdom and scientific progress in China","authors":"Jinnan Wang","doi":"10.1016/j.ese.2025.100613","DOIUrl":"10.1016/j.ese.2025.100613","url":null,"abstract":"","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"27 ","pages":"Article 100613"},"PeriodicalIF":14.3,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144879778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adjoint analysis of PM2.5 and O3 episodes in priority control zones in China","authors":"Ruixin Zhang ,&nbsp;Zhihong Chen ,&nbsp;Xueyan Wu ,&nbsp;Qiming Liu ,&nbsp;Zelin Mai ,&nbsp;Zhiyu Zheng ,&nbsp;Yilin Chen ,&nbsp;Shu Tao ,&nbsp;Yongtao Hu ,&nbsp;Shunliu Zhao ,&nbsp;Amir Hakami ,&nbsp;Armistead G. Russell ,&nbsp;Huizhong Shen","doi":"10.1016/j.ese.2025.100612","DOIUrl":"10.1016/j.ese.2025.100612","url":null,"abstract":"<div><div>Understanding and mitigating PM_2.5 and ozone (O₃) pollution remains challenging due to the nonlinear atmospheric chemistry and spatially heterogeneous nature of pollutant emissions. Traditional forward modeling approaches suffer from high computational cost and limited diagnostic resolution to precisely attribute emissions sources at fine spatial, temporal, and chemical scales. Adjoint modeling has emerged as an efficient alternative, enabling high-resolution, multi-pollutant source attribution in a single integrated framework; however, its application to simultaneous PM_2.5–O₃ pollution episodes is limited, particularly in densely populated regions experiencing complex co-pollutant interactions. Here we apply a newly developed multiphase adjoint of the Community Multiscale Air Quality (CMAQ) model to quantify the emission sensitivities of PM_2.5 and O₃ concentrations during pollution episodes in major urban agglomerations. Our results indicate that local emissions predominantly drive PM_2.5 concentrations, contributing up to 79 μg m⁻³. In contrast, O₃ episodes are largely initiated by regional transport (3.8–7.3 ppbv), surpassing local emission contributions during episode onset. The sensitivity analyses reveal distinct spatial emission signatures and pollutant-specific influences from critical precursors, including volatile organic compounds (VOCs; up to 15.9 ppbv O₃, 11.4 μg m⁻³ PM_2.5), nitrogen oxides (NO_<em>x</em>; 16.6 ppbv O₃, 13.8 μg m⁻³ PM_2.5), and ammonia (NH₃; up to 8.7 μg m⁻³ PM_2.5). This study demonstrates the diagnostic strength and predictive capabilities of adjoint modeling in unraveling complex source–receptor relationships. By offering detailed, pollutant-specific emission sensitivity information, our approach provides a robust foundation for precision-driven emission control strategies and improved cross-regional policy coordination, substantially advancing air quality management frameworks.</div></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"27 ","pages":"Article 100612"},"PeriodicalIF":14.3,"publicationDate":"2025-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144829185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Steep sustainability challenges in transboundary basins worldwide","authors":"Yiqi Zhou ,&nbsp;Yanfeng Di ,&nbsp;Xianjin Huang ,&nbsp;Shilin Fu ,&nbsp;Xinxian Qi ,&nbsp;Chao He ,&nbsp;Georgia Destouni","doi":"10.1016/j.ese.2025.100611","DOIUrl":"10.1016/j.ese.2025.100611","url":null,"abstract":"<div><div>Transboundary hydrological basins span international borders and are essential to global water systems, human development, and environmental sustainability. Nearly 40 % of the world's population lives within these basins, which supply critical resources such as freshwater, food, energy, and biodiversity. Yet their sustainability remains poorly understood, as existing assessments often overlook the unique social, environmental, and political complexities of transboundary basins. This study addresses that gap by developing and applying a systematic framework to assess Sustainable Development Goals (SDGs) progress across 310 transboundary basins worldwide. Here we show that transboundary basins score significantly lower on average SDGs achievement (an SDG Index score of 42 on a scale of 0–100) compared to national averages (a score of 67), with considerable variation between regions. We identify four distinct types of transboundary basins in terms of SDGs achievement and associated challenges. We also show that progress on a specific set of goals can drive broader sustainability within each basin type. Notably, achieving clean water (SDG 6), sustainable economic growth (SDG 8), and healthy livelihoods (SDG 3) is linked to overall SDGs success in 38 % of transboundary basins worldwide. Our results highlight the importance of basin-level analysis for revealing sustainability patterns overlooked by national assessments. This framework can inform future basin research and support policy development in transboundary regions.</div></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"27 ","pages":"Article 100611"},"PeriodicalIF":14.3,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144826543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Viruses are a key regulator of the microbial carbon cycle in the deep-sea biosphere","authors":"Xinyi Zhang ,&nbsp;Tianliang He ,&nbsp;Jiyong Zhou ,&nbsp;Xiaobo Zhang","doi":"10.1016/j.ese.2025.100609","DOIUrl":"10.1016/j.ese.2025.100609","url":null,"abstract":"<div><div>The marine biosphere profoundly influences atmospheric chemistry and climate through its carbon cycle. Viruses, the most abundant and diverse entities in marine ecosystems, significantly shape global carbon dynamics by infecting microbes and altering their metabolism. Both DNA and RNA viruses drive these processes in surface oceans, yet their roles in the deep sea—a sunlight-independent ecosystem that stores vast carbon reserves—remain largely unexplored. Here we show that viruses regulate the microbial carbon cycle in the deep-sea biosphere, based on viromic analysis of 66 global sediment samples spanning 1900 to 24,000 years. We identified 324,772 DNA viruses and 61,066 RNA viruses, revealing high diversity and long-term persistence. These viruses co-participate in host carbon metabolism via synergistic genes that encode carbohydrate-active enzymes, with DNA viruses primarily aiding synthesis and RNA viruses supporting decomposition. Integrated virome and microbiome data indicate that viral genes form novel metabolic branches, compensating for host deficiencies and enhancing pathway efficiency in processes like fructose-mannose and pyruvate metabolism. Our findings position deep-sea viruses as key regulators of marine microbial carbon cycling, with implications for global biogeochemical models and climate resilience. This work offers the first holistic perspective on DNA and RNA viruses in deep-sea carbon dynamics, illuminating their ecological significance across geological timescales.</div></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"27 ","pages":"Article 100609"},"PeriodicalIF":14.3,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144826542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heavy metals trigger distinct molecular transformations in microplastic-versus natural-derived dissolved organic matter","authors":"Xianbao Zhong ,&nbsp;Kaiying Zhao ,&nbsp;Mengyuan Wu ,&nbsp;Yaohui Zhang ,&nbsp;Chiyue Ma ,&nbsp;Hexiang Liu ,&nbsp;Bokun Chang ,&nbsp;Xiaohui Lian ,&nbsp;Yujing Li ,&nbsp;Zixuan Huang ,&nbsp;Lang Zhu ,&nbsp;Ming Zhang ,&nbsp;Chi Zhang ,&nbsp;Yajun Yang ,&nbsp;Jialong Lv","doi":"10.1016/j.ese.2025.100610","DOIUrl":"10.1016/j.ese.2025.100610","url":null,"abstract":"<div><div>Dissolved organic matter (DOM) is a key determinant of heavy metal fate in aquatic environments, influencing their mobility, toxicity, and bioavailability. Derived from natural sources such as soil and vegetation decomposition, natural DOM (N-DOM) typically features humic-like substances with abundant oxygen-containing functional groups that stabilize heavy metals through complexation. However, microplastic-derived DOM (MP-DOM), increasingly prevalent due to plastic degradation, may interact differently with heavy metals, potentially exacerbating environmental risks amid rising plastic pollution. Yet, how heavy metals drive molecular transformations in MP-DOM versus N-DOM remains unclear, hindering accurate pollution assessments. Here, we compare interactions between N-DOM and MP-DOM with cadmium, chromium (Cr), copper, and lead from both fluorescence and molecular perspectives. Our results show that N-DOM, dominated by humic-like substances (46.0–57.3 %), lignin-like (55.0–64.9 %), and tannin-like (10.1–17.6 %) compounds, forms more stable heavy metal complexes via carboxyl, phenolic hydroxyl, and ether groups than MP-DOM. By contrast, MP-DOM—enriched in protein/phenolic-like substances (13.8–24.0 %), condensed aromatic (12.1–28.5 %), and protein/aliphatic-like (8.6–12.4 %) compounds—yields less stable complexes and is highly susceptible to Cr-induced oxidation. Mass-difference network analysis and density functional theory calculations further reveal that both DOM types undergo heavy-metal-triggered decarboxylation and dealkylation, but N-DOM retains complex structures, whereas MP-DOM degrades into smaller, hazardous molecules such as phenol and benzene. This study underscores the potential for heavy metals to exacerbate the ecological risks associated with the transformation of MP-DOM, providing crucial insights to inform global risk assessment and management strategies in contaminated waters where plastic and metal pollution co-occur.</div></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"27 ","pages":"Article 100610"},"PeriodicalIF":14.3,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144779336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heterogeneity, nonlinearity, and multifactor interactions of polycyclic aromatic hydrocarbons in steelworks soils","authors":"Yixuan Hou ,&nbsp;Xiaoyong Liao ,&nbsp;You Li ,&nbsp;Hongying Cao","doi":"10.1016/j.ese.2025.100607","DOIUrl":"10.1016/j.ese.2025.100607","url":null,"abstract":"<div><div>Industrial polycyclic aromatic hydrocarbons (PAHs) pollution threatens soil ecosystems worldwide, posing persistent risks due to their toxicity and intricate transport dynamics. In steelworks, a major PAH emitter, contaminant distribution arises from multifaceted interactions between production activities and geological features, complicating the elucidation of underlying mechanisms. Previous studies have largely overlooked the inherent heterogeneity in these influences, focusing instead on global relationships that may bias assessments of pollution drivers and PAH migration. Here we show heterogeneity, nonlinearity, and multifactor interactions in PAH contamination at a steelworks site using a multidimensional framework that integrates machine learning and spatial analysis. Applied to 3339 soil samples and nine influencing factors, the framework reveals distance to production facilities as the dominant driver, with a 60-m impact radius; production factors exert stronger effects on 2–3-ring PAHs than on 4–6-ring PAHs, particularly in deeper soil layers at depths of 9–20 m. Soil moisture and clay content synergistically control PAH mobility across strata, elevating the framework's explanatory power from 0.5 to 0.9 and enabling precise delineation of dynamics. This modular approach not only advances mechanistic insights into industrial PAH pollution but also provides scalable guidance for targeted prevention and remediation strategies across diverse contaminated sites.</div></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"27 ","pages":"Article 100607"},"PeriodicalIF":14.3,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144772537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fine-tuning large language models for interdisciplinary environmental challenges","authors":"Yuanxin Zhang ,&nbsp;Sijie Lin ,&nbsp;Yaxin Xiong ,&nbsp;Nan Li ,&nbsp;Lijin Zhong ,&nbsp;Longzhen Ding ,&nbsp;Qing Hu","doi":"10.1016/j.ese.2025.100608","DOIUrl":"10.1016/j.ese.2025.100608","url":null,"abstract":"<div><div>Large language models (LLMs) are revolutionizing specialized fields by enabling advanced reasoning and data synthesis. Environmental science, however, poses unique hurdles due to its interdisciplinary scope, specialized jargon, and heterogeneous data from climate dynamics to ecosystem management. Despite progress in subdomains like hydrology and climate modeling, no integrated framework exists to generate high-quality, domain-specific training data or evaluate LLM performance across the discipline. Here we introduce a unified pipeline to address this gap. It comprises EnvInstruct, a multi-agent system for prompt generation; ChatEnv, a balanced 100-million-token instruction dataset spanning five core themes (climate change, ecosystems, water resources, soil management, and renewable energy); and EnvBench, a 4998-item benchmark assessing analysis, reasoning, calculation, and description tasks. Applying this pipeline, we fine-tune an 8-billion-parameter model, EnvGPT, which achieves 92.06 ± 1.85 % accuracy on the independent EnviroExam benchmark—surpassing the parameter-matched LLaMA-3.1–8B baseline by ∼8 percentage points and rivaling the closed-source GPT-4o-mini and the 9-fold larger Qwen2.5–72B. On EnvBench, EnvGPT earns top LLM-assigned scores for relevance (4.87 ± 0.11), factuality (4.70 ± 0.15), completeness (4.38 ± 0.19), and style (4.85 ± 0.10), outperforming baselines in every category. This study reveals how targeted supervised fine-tuning on curated domain data can propel compact LLMs to state-of-the-art levels, bridging gaps in environmental applications. By openly releasing EnvGPT, ChatEnv, and EnvBench, our work establishes a reproducible foundation for accelerating LLM adoption in environmental research, policy, and practice, with potential extensions to multimodal and real-time tools.</div></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"27 ","pages":"Article 100608"},"PeriodicalIF":14.3,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144750607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}