{"title":"An Open-source Shiny Tool for the Derivation of Human Health Water Quality Criteria using Probabilistic Risk Assessment.","authors":"Jayme Coyle, Bradley Barnhart, Giffe Johnson","doi":"10.1093/inteam/vjaf060","DOIUrl":null,"url":null,"abstract":"<p><p>Under Section 304(a) of the Clean Water Act, EPA is mandated to develop national recommended human health water quality criteria (HHWQC) which represent the concentration of specific chemicals, biologicals, and physical conditions in ambient water not expected to adversely affect human health. To date, EPA has set HHWQC using the deterministic approach for key exposure parameters for criteria development. However, these methods do not account for variability or uncertainty, and may substantially misestimate risk for the general population. Probabilistic approaches address these issues, but they have been hampered by several factors, including time and resource complexity, technical expertise requirements, lack of amenable open-source software, and lack of certainty regarding EPA approval. Here, we describe a new R Shiny tool, Surface Water Probabilistic Risk Online, developed for deriving HHWQC using either deterministic or probabilistic approaches to derive HHWQC for 105 chemicals for multiple risk management scenarios simultaneously. For the probabilistic approach, alternate distributions of body weight, fish consumption rate, and daily water intake can be parameterized using the tool's custom distribution module. The results of the tool can be aggregated and downloaded for record-keeping, reporting, and further analysis purposes. Given the flexibility and simplicity of the tool, development of probabilistic-based HHWQC may become more accessible for States' upcoming criteria reviews.</p>","PeriodicalId":13557,"journal":{"name":"Integrated Environmental Assessment and Management","volume":" ","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Integrated Environmental Assessment and Management","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1093/inteam/vjaf060","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Under Section 304(a) of the Clean Water Act, EPA is mandated to develop national recommended human health water quality criteria (HHWQC) which represent the concentration of specific chemicals, biologicals, and physical conditions in ambient water not expected to adversely affect human health. To date, EPA has set HHWQC using the deterministic approach for key exposure parameters for criteria development. However, these methods do not account for variability or uncertainty, and may substantially misestimate risk for the general population. Probabilistic approaches address these issues, but they have been hampered by several factors, including time and resource complexity, technical expertise requirements, lack of amenable open-source software, and lack of certainty regarding EPA approval. Here, we describe a new R Shiny tool, Surface Water Probabilistic Risk Online, developed for deriving HHWQC using either deterministic or probabilistic approaches to derive HHWQC for 105 chemicals for multiple risk management scenarios simultaneously. For the probabilistic approach, alternate distributions of body weight, fish consumption rate, and daily water intake can be parameterized using the tool's custom distribution module. The results of the tool can be aggregated and downloaded for record-keeping, reporting, and further analysis purposes. Given the flexibility and simplicity of the tool, development of probabilistic-based HHWQC may become more accessible for States' upcoming criteria reviews.
期刊介绍:
Integrated Environmental Assessment and Management (IEAM) publishes the science underpinning environmental decision making and problem solving. Papers submitted to IEAM must link science and technical innovations to vexing regional or global environmental issues in one or more of the following core areas:
Science-informed regulation, policy, and decision making
Health and ecological risk and impact assessment
Restoration and management of damaged ecosystems
Sustaining ecosystems
Managing large-scale environmental change
Papers published in these broad fields of study are connected by an array of interdisciplinary engineering, management, and scientific themes, which collectively reflect the interconnectedness of the scientific, social, and environmental challenges facing our modern global society:
Methods for environmental quality assessment; forecasting across a number of ecosystem uses and challenges (systems-based, cost-benefit, ecosystem services, etc.); measuring or predicting ecosystem change and adaptation
Approaches that connect policy and management tools; harmonize national and international environmental regulation; merge human well-being with ecological management; develop and sustain the function of ecosystems; conceptualize, model and apply concepts of spatial and regional sustainability
Assessment and management frameworks that incorporate conservation, life cycle, restoration, and sustainability; considerations for climate-induced adaptation, change and consequences, and vulnerability
Environmental management applications using risk-based approaches; considerations for protecting and fostering biodiversity, as well as enhancement or protection of ecosystem services and resiliency.