Environmental Science and Ecotechnology最新文献

{"title":"Optimizing soil conservation through comprehensive benefit assessment in river basins","authors":"Siqi Sun ,&nbsp;Yihe Lü ,&nbsp;Xiaoming Feng ,&nbsp;Fernando T. Maestre ,&nbsp;Bojie Fu","doi":"10.1016/j.ese.2024.100496","DOIUrl":"10.1016/j.ese.2024.100496","url":null,"abstract":"<div><div>Land degradation from water erosion poses a significant threat to water security and ecosystem stability, driving global efforts in soil conservation. Quantitative assessment of soil conservation benefits—both on-site and off-site—is crucial for guiding effective conservation strategies. However, existing methodologies often fall short in quantifying the value of these combined benefits. Here, we present a comprehensive framework for quantifying soil conservation service flows in monetary terms, evaluating the effectiveness of both on-site and off-site measures. Applying this framework to the Yellow River Basin (YRB), we employ cost-avoidance algorithms related to soil fertility maintenance, dredging cost reduction, and mitigation of nonpoint source pollution. Our results reveal that while many areas contribute to both on-site and off-site benefits, over half of the YRB relies predominantly on off-site services. By strategically enhancing key regions—which constitute 30% of the basin—we demonstrate that the overall soil conservation service supply can increase by 64.2% over the multi-year average from 2001 to 2020 compared to a consideration of on-site only. These findings underscore the essential role of off-site services in fully understanding soil conservation needs, particularly in large river basins, and the identified priority areas can offer valuable insights for optimizing soil conservation efforts.</div></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"23 ","pages":"Article 100496"},"PeriodicalIF":14.0,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11513632/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142523260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Piezocatalysis for water treatment: Mechanisms, recent advances, and future prospects","authors":"Tian Jiang ,&nbsp;Yuehan Wang ,&nbsp;Chang Cai ,&nbsp;Chunyang Nie ,&nbsp;Honggen Peng ,&nbsp;Zhimin Ao","doi":"10.1016/j.ese.2024.100495","DOIUrl":"10.1016/j.ese.2024.100495","url":null,"abstract":"<div><div>Piezocatalysis, which converts mechanical energy into chemical energy via the piezoelectric properties of materials, has emerged as a promising, eco-friendly technology for advanced oxidation processes in water treatment. It can be synergistically combined with other advanced oxidation techniques, such as photocatalysis and Fenton reactions, to enhance contaminant removal efficiency. In this Review article, we outline the fundamental principles of piezocatalysis, the mechanical energy sources employed, and recent advancements in piezocatalysis-coupled techniques for water decontamination. We systematically examine three potential mechanisms of piezocatalysis, assess the benefits and drawbacks of various mechanical energy inputs, and highlight the synergistic effects observed in combined systems. Furthermore, the review provides a roadmap for future research, emphasizing key areas such as piezocatalysis mechanisms, catalyst design, reactor architecture, and practical applications for water treatment. By offering a comprehensive analysis of current progress and challenges, this review is expected to stimulate further research into the theoretical and practical aspects of piezocatalysis-coupled technologies.</div></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"23 ","pages":"Article 100495"},"PeriodicalIF":14.0,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142432279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In situ evolution of electrocatalysts for enhanced electrochemical nitrate reduction under realistic conditions","authors":"Yingkai Chen ,&nbsp;Jiayu Luo ,&nbsp;Li Ling ,&nbsp;Zhengshuo Zhan ,&nbsp;Jiutan Liu ,&nbsp;Zongjun Gao ,&nbsp;Jason Chun-Ho Lam ,&nbsp;Chunhua Feng ,&nbsp;Yang Lei","doi":"10.1016/j.ese.2024.100492","DOIUrl":"10.1016/j.ese.2024.100492","url":null,"abstract":"<div><div>Electrochemical nitrate reduction to ammonia (ENRA) is gaining attention for its potential in water remediation and sustainable ammonia production, offering a greener alternative to the energy-intensive Haber-Bosch process. Current research on ENRA is dedicated to enhancing ammonia selectively and productivity with sophisticated catalysts. However, the performance of ENRA and the change of catalytic activity in more complicated solutions (i.e., nitrate-polluted groundwater) are poorly understood. Here we first explored the influence of Ca²⁺ and bicarbonate on ENRA using commercial cathodes. We found that the catalytic activity of used Ni or Cu foam cathodes significantly outperforms their pristine ones due to the <em>in situ</em> evolution of new catalytic species on used cathodes during ENRA. In contrast, the nitrate conversion performance with nonactive Ti or Sn cathode is less affected by Ca²⁺ or bicarbonate because of their original poor activity. In addition, the coexistence of Ca²⁺ and bicarbonate inhibits nitrate conversion by forming scales (CaCO₃) on the <em>in situ</em>-formed active sites. Likewise, ENRA is prone to fast performance deterioration in treating actual groundwater over continuous flow operation due to the presence of hardness ions and possible organic substances that quickly block the active sites toward nitrate reduction. Our work suggests that more work is required to ensure the long-term stability of ENRA in treating natural nitrate-polluted water bodies and to leverage the environmental relevance of ENRA in more realistic conditions.</div></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"23 ","pages":"Article 100492"},"PeriodicalIF":14.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142327997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stable phytoplankton community compositions in Lake Mead (Nevada-Arizona, USA) during two decades of severe drought","authors":"Charlotte van der Nagel ,&nbsp;Deena Hannoun ,&nbsp;Todd Tietjen","doi":"10.1016/j.ese.2024.100491","DOIUrl":"10.1016/j.ese.2024.100491","url":null,"abstract":"<div><div>Lake Mead, a large reservoir on the Colorado River and a critical drinking water source for the southwestern United States, typically exhibits high water quality, characterized by low nutrient and chlorophyll-<em>a</em> concentrations. This stability persists despite the inflow of highly treated wastewater since the 1960s and significant water level declines since 2000, driven by the ongoing Megadrought and basin-wide consumptive use. Such environmental changes may alter phytoplankton communities, potentially leading to increased cyanobacteria abundance, which could negatively impact water quality and the aquatic ecosystem through harmful algal blooms and toxin production. Here we analyzed 17 years of phytoplankton community structure and chlorophyll-<em>a</em> concentrations in Lake Mead, alongside quantitative water quality data, including nutrients, temperature, and water clarity, to assess the effects of environmental changes on phytoplankton communities. Contrary to the hypothesis that cyanobacteria abundance would have increased throughout the reservoir, our results indicate that phytoplankton community structures have remained largely stable, except for shallow areas where increases in temperature or phosphorus levels were observed. Additionally, we evaluated machine learning models for predicting changes in phytoplankton community structures. While the models confidently predicted changes in total phytoplankton biovolume and chlorophyll-<em>a</em> concentrations within the input parameter boundaries, predictions of peak biovolume showed considerable uncertainty, emphasizing the importance of incorporating uncertainty analysis in forecasting and communicating results. This study underscores the current buffering capacity of large, oligotrophic reservoirs like Lake Mead to maintain stable phytoplankton communities despite environmental changes. However, it also highlights the potential for significant community shifts if this buffering capacity is exceeded.</div></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"23 ","pages":"Article 100491"},"PeriodicalIF":14.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142417655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ex-ante life cycle evaluation of spent lithium-ion battery recovery: Modeling of complex environmental and economic impacts","authors":"Jiefeng Xiao ,&nbsp;Jiaqi Lu ,&nbsp;Bo Niu ,&nbsp;Xiaohua Liu ,&nbsp;Junming Hong ,&nbsp;Zhenming Xu","doi":"10.1016/j.ese.2024.100490","DOIUrl":"10.1016/j.ese.2024.100490","url":null,"abstract":"<div><p>The recycling of lithium-ion batteries (LIBs) is essential for promoting the closed-loop sustainable development of the LIB industry. However, progress in LIB recycling technologies is slow. There are significant gaps between academic research and industrial application, which hinder the industrialization of new technologies and the improvement of existing ones. Here we show a universal model for spent LIB-lithium recycling (<em>SliRec</em>) to evaluate the applicability and upgrading potential across various recycling technologies. Instead of modeling the entire recycling process, we focus on partial processes to enable a comparative analysis of environmental and economic impacts. We find a strong correlation between lithium concentration (LC) and the advancement of recycling technologies, where higher LC is associated with a reduced carbon footprint and increased economic benefits. The implementation of high-level recycling technology can result in an 85.91% reduction in carbon footprint and a 5.97-fold increase in economic returns. Additionally, we explore the effects of technological interventions through scenario analysis, demonstrating that while low-level recycling technology faces more substantial challenges in upgrading, it holds greater potential for reducing carbon emissions (−2.38 kg CO₂-eq mol⁻¹) and enhancing economic benefits (CNY 11.04 mol⁻¹). Our findings emphasize the significance of process modeling in evaluating the quality of spent LIB recycling technologies, and can provide comparative information for the application of emerging technologies or the upgrade of existing ones.</p></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"23 ","pages":"Article 100490"},"PeriodicalIF":14.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666498424001042/pdfft?md5=1971080c42e7dcd6ad524635469c9a0c&pid=1-s2.0-S2666498424001042-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142274252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-throughput single-cell sequencing of activated sludge microbiome","authors":"Yulin Zhang ,&nbsp;Bingjie Xue ,&nbsp;Yanping Mao ,&nbsp;Xi Chen ,&nbsp;Weifu Yan ,&nbsp;Yanren Wang ,&nbsp;Yulin Wang ,&nbsp;Lei Liu ,&nbsp;Jiale Yu ,&nbsp;Xiaojin Zhang ,&nbsp;Shan Chao ,&nbsp;Edward Topp ,&nbsp;Wenshan Zheng ,&nbsp;Tong Zhang","doi":"10.1016/j.ese.2024.100493","DOIUrl":"10.1016/j.ese.2024.100493","url":null,"abstract":"<div><div>Wastewater treatment plants (WWTPs) represent one of biotechnology's largest and most critical applications, playing a pivotal role in environmental protection and public health. In WWTPs, activated sludge (AS) plays a major role in removing contaminants and pathogens from wastewater. While metagenomics has advanced our understanding of microbial communities, it still faces challenges in revealing the genomic heterogeneity of cells, uncovering the microbial dark matter, and establishing precise links between genetic elements and their host cells as a bulk method. These issues could be largely resolved by single-cell sequencing, which can offer unprecedented resolution to show the unique genetic information. Here we show the high-throughput single-cell sequencing to the AS microbiome. The single-amplified genomes (SAGs) of 15,110 individual cells were clustered into 2,454 SAG bins. We find that 27.5% of the genomes in the AS microbial community represent potential novel species, highlighting the presence of microbial dark matter. Furthermore, we identified 1,137 antibiotic resistance genes (ARGs), 10,450 plasmid fragments, and 1,343 phage contigs, with shared plasmid and phage groups broadly distributed among hosts, indicating a high frequency of horizontal gene transfer (HGT) within the AS microbiome. Complementary analysis using 1,529 metagenome-assembled genomes from the AS samples allowed for the taxonomic classification of 98 SAG bins, which were previously unclassified. Our study establishes the feasibility of single-cell sequencing in characterizing the AS microbiome, providing novel insights into its ecological dynamics, and deepening our understanding of HGT processes, particularly those involving ARGs. Additionally, this valuable tool could monitor the distribution, spread, and pathogenic hosts of ARGs both within AS environments and between AS and other environments, which will ultimately contribute to developing a health risk evaluation system for diverse environments within a One Health framework.</div></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"23 ","pages":"Article 100493"},"PeriodicalIF":14.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142417656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing sustainable development in arid river basins: A multi-objective approach to balancing water, energy, economy, carbon and ecology nexus","authors":"Yufei Zhang ,&nbsp;Yongping Li ,&nbsp;Guohe Huang ,&nbsp;Yuan Ma ,&nbsp;Yanxiao Zhou","doi":"10.1016/j.ese.2024.100481","DOIUrl":"10.1016/j.ese.2024.100481","url":null,"abstract":"<div><p>The ongoing water crisis poses significant threats to the socioeconomic sustainability and ecological security of arid and semi-arid river basins. Achieving Sustainable Development Goals (SDGs) within a complex socio-ecological nexus requires effective and balanced resource management. However, due to the intricate interactions between human societies and environmental systems, the tradeoffs and synergies of different SDGs remain unclear, posing a substantial challenge for collaborative management of natural resources. Here we introduce a gray fractional multi-objective optimization (GFMOP) model to balance multi-dimensional SDGs through a novel water–energy–economy–carbon–ecology nexus perspective. The model was applied to a typical arid river basin in Northwest China, where thirty-two scenarios were explored, considering factors such as shared socioeconomic pathways, carbon removal rates, water conveyance efficiencies, and ecological requirements. The results reveal a strong tradeoff between marginal benefit and carbon emission intensity, indicating that improving the economic efficiency of water use can simultaneously reduce emissions and protect the environment. Given the immense power generation potential, wind power development should be prioritized in the future, with its share in the energy structure projected to increase to 23.3% by 2060. Furthermore, promoting carbon capture technologies and expanding grassland coverage are recommended to achieve regional carbon neutrality, contributing 39.5% and 49.1% to carbon absorption during 2021–2060, respectively. Compared with traditional single-objective models, GFMOP demonstrates a superiority in uncovering interrelationships among multiple SDGs and identifying compromised alternatives within the compound socio-ecological nexus. The model also provides detailed strategies for resource allocation and pollutant control, offering valuable guidance to policymakers and stakeholders in pursuing sustainable and harmonious watershed management.</p></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"23 ","pages":"Article 100481"},"PeriodicalIF":14.0,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666498424000954/pdfft?md5=600f6cdd1662bc975045954cf3530b8d&pid=1-s2.0-S2666498424000954-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142243660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hydrology, vegetation, and soil properties as key drivers of soil organic carbon in coastal wetlands: A high-resolution study","authors":"Mao Guo ,&nbsp;Lin Yang ,&nbsp;Lei Zhang ,&nbsp;Feixue Shen ,&nbsp;Michael E. Meadows ,&nbsp;Chenghu Zhou","doi":"10.1016/j.ese.2024.100482","DOIUrl":"10.1016/j.ese.2024.100482","url":null,"abstract":"<div><p>Coastal wetlands are important blue carbon ecosystems that play a significant role in the global carbon cycle. However, there is insufficient understanding of the variations in soil organic carbon (SOC) stocks and the mechanisms driving these ecosystems. Here we analyze a comprehensive multi-source dataset of SOC in topsoil (0–20 cm) and subsoil (20–100 cm) across 31 coastal wetlands in China to identify the factors influencing their distribution. Structural equation models (SEMs) reveal that hydrology has the greatest overall effect on SOC in both soil layers, followed by vegetation, soil properties, and climate. Notably, the mechanisms driving SOC density differ between the two layers. In topsoil, vegetation type and productivity directly impact carbon density as primary sources of carbon input, while hydrology, primarily through seawater salinity, exerts the largest indirect influence. Conversely, in subsoil, hydrology has the strongest direct effect on SOC, with seawater salinity also influencing SOC indirectly through soil and vegetation mediation. Soil properties, particularly pH, negatively affect carbon accumulation, while climate influences SOC indirectly via its effects on vegetation and soil, with a diminishing impact at greater depths. Using Random Forest, we generate high-resolution maps (90 m × 90 m) of topsoil and subsoil carbon density (<em>R</em>² of 0.53 and 0.62, respectively), providing the most detailed spatial distribution of SOC in Chinese coastal wetlands to date. Based on these maps, we estimate that SOC storage to a depth of 1 m in Chinese coastal wetlands totals 74.58 ± 3.85 Tg C, with subsoil carbon storage being 2.5 times greater than that in topsoil. These findings provide important insights into mechanism on driving spatial pattern of blue carbon and effective ways to assess carbon status on a national scale, thus contributing to the advancement of global blue carbon monitoring and management.</p></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"23 ","pages":"Article 100482"},"PeriodicalIF":14.0,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666498424000966/pdfft?md5=776b163f662f0e025c275fc2b9592572&pid=1-s2.0-S2666498424000966-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142228822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mass transfer in heterogeneous biofilms: Key issues in biofilm reactors and AI-driven performance prediction","authors":"Huize Chen ,&nbsp;Ao Xia ,&nbsp;Huchao Yan ,&nbsp;Yun Huang ,&nbsp;Xianqing Zhu ,&nbsp;Xun Zhu ,&nbsp;Qiang Liao","doi":"10.1016/j.ese.2024.100480","DOIUrl":"10.1016/j.ese.2024.100480","url":null,"abstract":"<div><p>Biofilm reactors, known for utilizing biofilm formation for cell immobilization, offer enhanced biomass concentration and operational stability over traditional planktonic systems. However, the dense nature of biofilms poses challenges for substrate accessibility to cells and the efficient release of products, making mass transfer efficiency a critical issue in these systems. Recent advancements have unveiled the intricate, heterogeneous architecture of biofilms, contradicting the earlier view of them as uniform, porous structures with consistent mass transfer properties. In this review, we explore six biofilm reactor configurations and their potential combinations, emphasizing how the spatial arrangement of biofilms within reactors influences mass transfer efficiency and overall reactor performance. Furthermore, we discuss how to apply artificial intelligence in processing biofilm measurement data and predicting reactor performance. This review highlights the role of biofilm reactors in environmental and energy sectors, paving the way for future innovations in biofilm-based technologies and their broader applications.</p></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"22 ","pages":"Article 100480"},"PeriodicalIF":14.0,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666498424000942/pdfft?md5=ba26eb2e90c12c1c8a58245ebad2ca78&pid=1-s2.0-S2666498424000942-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142229725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trusted artificial intelligence for environmental assessments: An explainable high-precision model with multi-source big data","authors":"Haoli Xu ,&nbsp;Xing Yang ,&nbsp;Yihua Hu ,&nbsp;Daqing Wang ,&nbsp;Zhenyu Liang ,&nbsp;Hua Mu ,&nbsp;Yangyang Wang ,&nbsp;Liang Shi ,&nbsp;Haoqi Gao ,&nbsp;Daoqing Song ,&nbsp;Zijian Cheng ,&nbsp;Zhao Lu ,&nbsp;Xiaoning Zhao ,&nbsp;Jun Lu ,&nbsp;Bingwen Wang ,&nbsp;Zhiyang Hu","doi":"10.1016/j.ese.2024.100479","DOIUrl":"10.1016/j.ese.2024.100479","url":null,"abstract":"<div><p>Environmental assessments are critical for ensuring the sustainable development of human civilization. The integration of artificial intelligence (AI) in these assessments has shown great promise, yet the \"black box\" nature of AI models often undermines trust due to the lack of transparency in their decision-making processes, even when these models demonstrate high accuracy. To address this challenge, we evaluated the performance of a transformer model against other AI approaches, utilizing extensive multivariate and spatiotemporal environmental datasets encompassing both natural and anthropogenic indicators. We further explored the application of saliency maps as a novel explainability tool in multi-source AI-driven environmental assessments, enabling the identification of individual indicators' contributions to the model's predictions. We find that the transformer model outperforms others, achieving an accuracy of about 98% and an area under the receiver operating characteristic curve (AUC) of 0.891. Regionally, the environmental assessment values are predominantly classified as level II or III in the central and southwestern study areas, level IV in the northern region, and level V in the western region. Through explainability analysis, we identify that water hardness, total dissolved solids, and arsenic concentrations are the most influential indicators in the model. Our AI-driven environmental assessment model is accurate and explainable, offering actionable insights for targeted environmental management. Furthermore, this study advances the application of AI in environmental science by presenting a robust, explainable model that bridges the gap between machine learning and environmental governance, enhancing both understanding and trust in AI-assisted environmental assessments.</p></div>","PeriodicalId":34434,"journal":{"name":"Environmental Science and Ecotechnology","volume":"22 ","pages":"Article 100479"},"PeriodicalIF":14.0,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666498424000930/pdfft?md5=910b7c0d9e34a403e422cad4c29a7fe1&pid=1-s2.0-S2666498424000930-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142096512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}