Environmental Research Communications最新文献

{"title":"A Hotspot and Mechanism of Enhanced Bottom Intrusion on the Southern New England Shelf","authors":"Ke Chen","doi":"10.1088/2515-7620/ad61c7","DOIUrl":"https://doi.org/10.1088/2515-7620/ad61c7","url":null,"abstract":"\u0000 Understanding the occurrence of the intrusion of open ocean water onto the continental shelf has scientific significance and societal relevance as the intrusion can significantly disrupt the marine ecosystem and fisheries. High-resolution numerical modeling is used to investigate the spatiotemporal occurrence and mechanisms of highly anomalous bottom intrusions on the southern New England shelf. Based on multi-year numerical simulations, this study reveals a hotspot of cross-isobath bottom intensified intrusions at a topographic trough. Examination of multiple events portrays a robust mechanism of locally enhanced bottom intrusions. Persistent upwelling-favorable winds set up an enhanced pressure gradient field at the topographic trough and drive the intrusion a large-distance onshore. Numerical experiments with and without the topographic trough show that the localized pressure gradient results from a combination of the shelf orientation and local bathymetry, the latter being less decisive. Although highly anomalous waters on the shelf relate to wind forcing, correlations between the wind stress anomaly and bottom salinity anomaly at the location of the enhanced intrusion is modest, implying the need to incorporate other environmental factors to develop more deterministic prediction models for subsurface conditions on the shelf. The results have important implications for marine environment and fisheries management.","PeriodicalId":48496,"journal":{"name":"Environmental Research Communications","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141662562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Asian summer monsoon responses under RCP4.5 and RCP8.5 scenarios in CESM large ensemble simulations","authors":"Devanil Choudhury, Debashis Nath, Wen Chen","doi":"10.1088/2515-7620/ad5b3b","DOIUrl":"https://doi.org/10.1088/2515-7620/ad5b3b","url":null,"abstract":"The response of the Asian Summer Monsoon (ASM) circulation to the Representative Concentration Pathway 4.5 and 8.5 (RCP4.5 and RCP8.5) forcing scenarios is examined using the CESM1 state-of-the-art global circulation model from 2021 to 2050. The projections show that monsoon precipitation will increase over East Asia, the North Pacific Ocean, the Indian Peninsula, and the Bay of Bengal under the RCP4.5 scenario. Conversely, the South Indian Ocean, West Asia, the Middle East, and the Central Pacific Ocean exhibit a decreasing trend in precipitation. Under the RCP8.5 scenario, precipitation is projected to increase over a wider swath of the Indian Ocean and the Middle East Asia. In the RCP4.5 scenario, the low-level wind circulation is likely to strengthen over the entire northern Indian Ocean, extending to the South China Sea, thereby increasing moisture transport from the Indian Ocean to peninsular India and the South China Sea. Conversely, in the RCP8.5 scenario, easterly winds strengthen over the South Indian Ocean, leading to an increase in moisture transport from the equatorial West Pacific Ocean to the Indian Ocean. A weak (strong) cyclonic circulation in response to the east-centered (west-centered) low sea level pressure trend over the North Pacific in RCP4.5 (RCP8.5) scenario is projected to help maintaining a strong (weak) ASM circulation from the India to east Asia. Internal climate variability is also calculated, revealing that the North Pacific Ocean near the Bering Sea is likely to play a dominating role and contribute significantly to the future ASM dynamics. In both scenarios, internal variability is found to substantially contribute to changes in monsoon circulation over the Indian Ocean.","PeriodicalId":48496,"journal":{"name":"Environmental Research Communications","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141570764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Sediment ballast accelerates sinking of Alaska North Slope crude oil measured ex situ with surface water from Cook Inlet","authors":"J. Ross, Nancy Kinner, S. Saupe, Kai Ziervogel","doi":"10.1088/2515-7620/ad6125","DOIUrl":"https://doi.org/10.1088/2515-7620/ad6125","url":null,"abstract":"\u0000 Oil spilled into the ocean interacts with suspended matter forming aggregates that transport oil into subsurface layers and towards the bottom. We conducted a series of laboratory experiments to explore aggregation of oil with natural phytoplankton assemblages from Cook Inlet, Alaska at three times during a spring bloom. Oil and phytoplankton formed marine oil snow (MOS) that remained positively buoyant with a small fraction of MOS sinking to the bottom of our experimental bottles. Seawater treatments amended with suspended sediments formed oil-mineral aggregates (OMAs) with an oil capacity similar to MOS (~20% of aggregate area was covered with oil). OMAs accelerated oil sedimentation in our bottles relative to MOS sedimentation underlining the significance of suspended matter as ballast for sinking oil. Our results reveal potential transport mechanisms of oil in Cook Inlet which apply to other coastal systems with high productivity and sediment loads.","PeriodicalId":48496,"journal":{"name":"Environmental Research Communications","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141664702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Impact of global warming on labor productivity in the Chengdu-Chongqing economic circle, China","authors":"Jiajin Wang, Jie Guo, Chunxue Wang, Yanmei Pang","doi":"10.1088/2515-7620/ad5ccd","DOIUrl":"https://doi.org/10.1088/2515-7620/ad5ccd","url":null,"abstract":"In recent years, the Chengdu-Chongqing Economic Circle (CCEC) has experienced frequent heat events, significantly impacting labor productivity. The CCEC is an important economic growth pole in western China. Therefore, an in-depth study of the impact of heat stress on labor productivity holds great significance for climate change adaptation and enhancing economic efficiency. Based on the relationship between the wet-bulb globe temperature (WBGT) and labor productivity of different industries, the labor productivity loss caused by heat in the CCEC was estimated using the observation data of the meteorological station and the projection results of the BCC-CSM2-MR model from the Coupled Model Intercomparison Project Phase 6 (CMIP6). The results showed that the impact of heat on the labor productivity of different industries in the CCEC mainly occurs from June to August, with the largest impact on agriculture, followed by industry, and the smallest impact on service sectors. Losses from heat stress to labor productivity in agriculture, industry, and services showed a significant increasing trend from 1980 to 2020 but a decreasing trend in comprehensive labor productivity loss. From 2020–2100, labor productivity losses in different industries due to heat stress show an increasing and then decreasing trend in the low emissions scenario, productivity losses in the medium emissions scenario are characterized by an increasing and then sustained change, and labor productivity losses in the high emissions scenario show a sustained increasing trend from 2020. By the end of the 21st century, the increase in labor productivity losses across different industries under the high emission scenario is approximately 15%–23%, and the large value center shifts slightly to the west. In most areas, the losses of agricultural, industrial, service, and comprehensive labor productivity exceed 45%, 32%, 20%, and 24%, respectively.","PeriodicalId":48496,"journal":{"name":"Environmental Research Communications","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141570762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"AO-SVM: A Machine Learning Model for Predicting Water Quality in the Cauvery River","authors":"Vellingiri J, Kalaivanan K, K. S, Femilda Josephin Joseph Shobana Bai","doi":"10.1088/2515-7620/ad6061","DOIUrl":"https://doi.org/10.1088/2515-7620/ad6061","url":null,"abstract":"\u0000 Water pollution is a significant cause of death globally, resulting in 1.8 million deaths annually due to waterborne diseases. Assessing water quality is a complex process that involves identifying contaminants in water sources and determining whether it is safe for human consumption. In this study, we utilized the Cauvery River dataset to develop a model for evaluating water quality. The aim of our research was to proficiently perform feature selection and classification tasks. We introduced a novel technique called the Aquila Optimization Support Vector Machine (AO-SVM), an advanced and effective machine learning system for predicting water quality. Here SVM is used for the classification, and the Aquila algorithm is used for optimizing SVM. The results show that the proposed method achieved a maximum accuracy rate of 96.3%, an execution time of 0.75s, a precision of 93.9 %, a recall rate of 95.1 %, and an F1-Score value of 94.7%. The suggested AO-SVM model outperformed all other existing classification models regarding classification accuracy and other parameters.","PeriodicalId":48496,"journal":{"name":"Environmental Research Communications","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141669007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Qualifying uncertainty of precipitation projections over China: mitigating uncertainty with emergent constraints","authors":"Jinge Zhang, Chunxiang Li, Tianbao Zhao","doi":"10.1088/2515-7620/ad5ad9","DOIUrl":"https://doi.org/10.1088/2515-7620/ad5ad9","url":null,"abstract":"Predicting future mean precipitation poses significant challenges due to uncertainties among climate models, complicating water resource management. In this study, we introduce a novel methodology to mitigate uncertainty in future mean precipitation projections over China on a grid-by-grid basis. By constraining precipitation parameters of the Gamma distribution, we establish emergent constraints on parameters, revealing significant correlations between historical and future simulations. Our analysis spans the periods 2040–2069 and 2070–2099 under low-to-moderate and high emission scenarios. We observe reductions in uncertainty across most regions of China, with constrained mean precipitation indicating increases in monsoon regions and decreases in non-monsoon zones relative to raw projections. Notably, the observed 30%–40% increase in mean precipitation for the whole of China underscores the efficacy of our methodology. These observationally constrained results provide valuable insights into current precipitation projections, offering actionable information for water resource planning and climate adaptation strategies amidst future uncertainties.","PeriodicalId":48496,"journal":{"name":"Environmental Research Communications","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141570763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Interactions between gut microbiota and emerging contaminants exposure: new and profound implications for human health","authors":"Feng Zhao, Zhaoyi Liu, Yuehua Wu, Jiao Wang, Yinyin Xia, Shuqun Cheng, Xuejun Jiang, Jun Zhang, Zhen Zou, Chengzhi Chen, Jingfu Qiu","doi":"10.1088/2515-7620/ad5f7f","DOIUrl":"https://doi.org/10.1088/2515-7620/ad5f7f","url":null,"abstract":"\u0000 Emerging contaminants (ECs) pollution has attracted global attention, and a large number of ECs spread in the environment, threatening the ecological environment and human health. Gut microbiota is the most complex microbial community, and its high sensitivity to ECs exposure has been widely concerned and reported by researchers. In fact, many studies have demonstrated that the gut microbiota is closely related to host health and is a toxic target of various environmental pollutants including ECs. This review evaluates the interaction of ECs (including persistent organic pollutants, antibiotics, microplastics and environmental endocrine disruptors) with the gut microbiota, and considers the possible harm of ECs to human health, finding that the gut microbiota may be involved in the regulation of various organ damage, endocrine disorders, embryotoxicity, and cancer development and other toxic processes caused by ECs exposure through related mechanisms such as the gut-liver axis, direct effects (toxins and metabolites enter the blood after intestinal injury), and gut-brain axis. In short, we hope that more future studies will pay more attention to the relationship between ECs, gut microbiota and human health.","PeriodicalId":48496,"journal":{"name":"Environmental Research Communications","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141680103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Extraction of building footprint using MASK-RCNN for high resolution aerial imagery","authors":"Jenila Vincent M and Varalakshmi P","doi":"10.1088/2515-7620/ad5b3d","DOIUrl":"https://doi.org/10.1088/2515-7620/ad5b3d","url":null,"abstract":"Extracting individual buildings from satellite images is crucial for various urban applications, including population estimation, urban planning, and other related fields. However, Extracting building footprints from remote sensing data is a challenging task because of scale differences, complex structures and different types of building. Addressing these issues, an approach that can efficiently detect buildings in images by generating a segmentation mask for each instance is proposed in this paper. This approach incorporates the Regional Convolutional Neural Network (MASK-RCNN), which combines Faster R-CNN for object mask prediction and boundary box recognition and was evaluated against other models like YOLOv5, YOLOv7 and YOLOv8 in a comparative study to assess its effectiveness. The findings of this study reveals that our proposed method achieved the highest accuracy in building extraction. Furthermore, we performed experiments on well-established datasets like WHU and INRIA, and our method consistently outperformed other existing methods, producing reliable results.","PeriodicalId":48496,"journal":{"name":"Environmental Research Communications","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141551063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Developing a transdisciplinary tool for water risk management and decision-support in Ontario, Canada","authors":"Guneet Sandhu, Olaf Weber, Michael O Wood, Horatiu A Rus and Jason Thistlethwaite","doi":"10.1088/2515-7620/ad5b3f","DOIUrl":"https://doi.org/10.1088/2515-7620/ad5b3f","url":null,"abstract":"Extant literature reveals limited examination of risk management strategies and tools to support decision-making for sustainable water management in the private sector in Ontario, Canada. Moreover, a gap persists in understanding how water risks are prioritized and managed in the private sector. Addressing these gaps, this transdisciplinary study applied a novel normative-analytical risk governance theoretical framework to water security risks, which combines analytical risk estimation with normative priorities and insights of practitioners, to examine contextually-attuned water risk management strategies and develop a decision-support tool. Using mixed methods, the study first employed a survey to elicit practitioner priorities for seven water risk indicators and investigated water risk management approaches. Then, interviews were conducted to obtain in-depth understanding about the priorities, strategies, opportunities, and role of trust in water risk management. The study found that a combination of regulatory, voluntary, and multi-stakeholder participatory approaches is needed, contingent on the severity of water risks, sector, location, and context. Moreover, the criteria of flexibility, efficiency, strategic incentives, and economic and regulatory signals, are essential. Finally, using secondary data analysis, the study integrated interdisciplinary risk data with practitioner priorities to develop a first-of-a-kind decision-support tool for water risk management in Ontario, ‘WATR-DST’. WATR-DST is an automated tool that applies the study’s findings and assists multi-sector water-related decisions, practices, and investments by providing contextually-attuned risk information in a user-friendly format. Based on the user inputs (location, sector, and source type), it displays the severity of seven water risks, qualitative themes under public and media attention, and recommends water risk management strategies. Thus, the study contributes to knowledge in sustainability management, risk analysis, and environmental management by demonstrating the novel application of the normative-analytical framework for water risk management in the private sector. WATR-DST is a key contribution envisioned to improve multi-sector water-related decisions in Ontario.","PeriodicalId":48496,"journal":{"name":"Environmental Research Communications","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141551064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Evaluating Non-Consumptive Household Water Uses in a growing Urban centre in Nigeria.","authors":"Timothy O Ogunbode, Ayobami A. Oyelami, Victor O Oyebamiji, Oluwatobi O. Faboro, Aruna O. Adelkiya","doi":"10.1088/2515-7620/ad5e3d","DOIUrl":"https://doi.org/10.1088/2515-7620/ad5e3d","url":null,"abstract":"\u0000 Efficient use of water could be partly achieved with sound management strategies of the non-consumptive uses (N-CUs) of water in homes being put in place. This research evaluated the non-consumptive water use component in Iwo, Osun State, Nigeria. Data required for the investigation was generated from the administration of 325 questionnaires across the five Quarters into which the town is divided, out of which 269 were completed and retrieved. Both descriptive and inferential analysis of the data were carried out. Descriptive analysis showed that households engage absolutely in different non-consumptive uses such as bathing, clothe washing, drainage cleaning and dish washing while households’ engagement in other N-CUs were in varying proportions. The results of Factor Analysis (FA) revealed that five out of the 13 variables identified and analyzed with a minimum eigen value of 1.000 were strong explanatory variables of 73.674% when engaging in issues relating to N-CUs at household level. These are water use for the following (i) drainage cleaning (16.153%); (ii) Dish washing (15.922%); (iii) Toilet cleaning (14.547%); (iv) Auto-wash (14.238%); and Bathing (12.814%). Regression analysis (RA) of the data revealed that three variables namely clothe washing, Incidental washing and auto-washing were significant (p<0.001) in generating predictive model of N-CUs of water in homes. The combined results of FA and RA implied that the set of variables in both analysis need to be considered in any issue involving the management and control of N-CUs of water in homes for a result-oriented water use efficiency at household level.","PeriodicalId":48496,"journal":{"name":"Environmental Research Communications","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141685030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}