Integrated Environmental Assessment and Management最新文献

Understanding the removal of a chemical in a wastewater treatment plant (WWTP) is important when performing chemical risk assessments. Chemicals undergoing assessment often have limited experimental measurements of physicochemical properties, biodegradation rates, and WWTP removal efficiencies. Models available to risk assessors to predict WWTP removal efficiencies are best used with high quality input data and knowledge of plant conditions, information often unavailable when performing chemical risk assessments. In this work we outline the development of the Canadian A.I. Removal Rate Estimator (CAIRRE), an A.I. model suite designed to estimate removal efficiencies from secondary WWTPs. CAIRRE was trained on median experimental removal efficiencies for 161 chemicals across 59 secondary WWTPs in Canada, the United States of America (California), and various other locations curated from literature. The CAIRRE regression model has a validation Pearson R2 of 0.81 based on leave-one-out-validation (LOOV) results. When used to predict effluent concentrations for a test set containing 53 chemicals not seen during model training, CAIRRE was able to reproduce experimental observations with a Pearson R2 of 0.91. The CAIRRE model outperformed existing mechanistic and fugacity WWTP models which rely on physical-chemistry and biodegradation data provided by the user. This work demonstrates that the A.I. modeling approach taken in the development of CAIRRE is a promising strategy for predicting removal efficiencies of chemicals from secondary WWTPs.

The environmental persistence of a substance plays a key role in determining its exposure to humans and other organisms, making this an important component in the risk assessment and management of chemicals. Regulatory persistence assessments generally involve a comparison of degradation half-lives against threshold criteria for different environmental compartments, typically water, sediment, and soil. Half-lives are commonly determined using Organisation for Economic Cooperation and Development (OECD) guideline biodegradation simulation tests. Other information may be considered relevant to persistence assessments, such as results from biodegradation screening tests, quantitative structure-activity relationships, field studies, monitoring data, and non-standard laboratory experiments. All available relevant information should be considered together in a weight-of-evidence approach, but clear guidance is currently lacking both for evaluating the quality of individual studies and for combining these in a single weight-of-evidence determination. Here we propose a systematic methodology to collate, evaluate, and integrate relevant information to reach robust, transparent and consistent conclusions for persistence assessments. First, the quality (reliability and relevance) of individual studies within each information category, or 'line of evidence', is evaluated using a novel scoring methodology. Then, information from different studies is combined to determine outcomes for each line of evidence. Finally, a stepwise weight-of-evidence approach is applied to integrate outcomes from different lines of evidence to reach an overall conclusion for the persistence assessment. Consistency of information is evaluated at various stages in line with weight-of-evidence best practice. The methodology has been developed in accordance with principles of the European Union Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) regulatory framework, test guidelines and guidance, whilst being flexible to accommodate different regulatory practices. The methodology has been implemented in a freely available Excel-based software tool, the Persistence Assessment Tool (PAT), and is demonstrated using a case study substance hexabromocyclododecane.

The EU's Green Deal initiatives, including the Farm to Fork Strategy and the Chemical Strategy for Sustainability (CSS), emphasize the need for developing plant protection products (PPPs) that meet both safety and sustainability goals. In the EU, PPPs are regulated under Regulation (EC) No. 1107/2009 which sets approval criteria to ensure human health and environmental safety. This legislation is complemented by Sustainable Use of Pesticides (SUD) (Directive 2009/128) which aims to achieve sustainable pesticide use by minimising risks to human health and the environment, while promoting use of Integrated Pest Management (IPM) and non-chemical alternatives. Both legislations address the conditions of placing on the market and the use of PPPs, neither directly address broader aspects of sustainability compliance, such as the lifecycle impacts, resource efficiency during design and manufacture and socioeconomic dimensions of sustainability. The EU Commission's Joint Research Centre (JRC) Safe and Sustainable by Design (SSbD) framework offers a holistic approach to chemical product innovation, minimising risks and maximising sustainability throughout a chemical's lifecycle. This framework, combined with existing safety regulations, can advance sustainability of plant protection products in-line with the European Green Deal and the CSS. Agrochemical manufacturers have embedded SSbD-aligned practices in their innovation pipelines, but approaches used tend to be company-specific and lack standardised metrics. Incorporating well defined sustainability criteria and incentives for manufacturers would accelerate the development of PPPs that contribute to long-term agricultural sustainability, safeguard human health and the environment, and ensure food security in line with sustainable development goals.

Pharmaceutical residues in aquatic environments pose a growing concern, mainly driven by the increasing use of medications. This study investigated the occurrence of four pharmaceutical compounds, namely azithromycin (AZI), prednisolone (m-PRD), prednisone (PRD), and dexamethasone (DEX) in surface waters across eight different sites in the Free State Province, South Africa, during summer and winter 2024. Samples were collected from upstream, downstream, and the wastewater point of discharge at each site. Using a validated liquid chromatography-mass spectrometric (LC-MS) method, all target analytes were detected, with DEX (41.79 µg/L) and AZI (19.32 µg/L) recording the highest mean concentrations in summer and winter, respectively. Moreover, AZI showed the highest detection frequency across all sites and seasons. Spatial variation was evident, with concentrations of analytes differing among upstream, downstream, and points of discharge, revealing the influence of wastewater input and other site-specific factors. The consistent presence of these pharmaceutical residues in surface waters pinpoints a potential risk to aquatic ecosystems and raises concerns about human health implications resulting from the long-term environmental presence of these compounds. The findings underscore significant seasonal fluctuations in pharmaceutical residue levels, highlighting potential risks to aquatic ecosystems and public health. These results call for targeted monitoring efforts and evidence-based regulatory frameworks to mitigate contamination and guide sustainable water resource management in South Africa.

Growing concerns over global warming and environmental degradation emphasize the need for sustainable waste management and renewable energy solutions. This study conducts a comprehensive multi-criteria decision-making (MCDM) assessment of manure from six livestock and poultry types-Dairy Cow, Buffalo, Beef Cattle, Sheep, Goat, and Chicken-in Turkey, focusing on their carbon footprint and environmental impacts. Fourteen criteria, including greenhouse gas emissions, biogas potential, volatile solids, and nutrient composition, were used for evaluation. To determine the most sustainable manure source, three MCDM methods-Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR)-were applied. AHP provided the criteria weights through pairwise comparisons, while TOPSIS and VIKOR ranked alternatives based on proximity to the ideal solution. All methods consistently identified Beef Cattle manure as the optimal option. This integrated MCDM framework offers insights for policymakers to improve manure management strategies balancing environmental impact reduction and renewable energy production.

The main focus of this study is to evaluate possible alternatives for organic waste disposal and compare different waste management options to determine the most appropriate disposal method for biowaste in sustainable waste management. With increasing urbanization and population growth, managing biowaste has become critical for environmentally friendly solutions. Traditional landfill methods contribute to global warming through greenhouse gas emissions, whereas methods such as composting, biogas production, bokashi, vermicomposting, and biochar production, which offer bio-based product generation and renewable energy potential, present sustainable alternatives. In this research, the analytic hierarchy process (AHP), a multicriteria decision-making method, was used to evaluate these methods based on criteria such as investment costs, operating costs, carbon footprint, energy recovery, and contributions to agricultural health. The AHP results indicate that biogas is the most suitable method for biowaste management. Despite high initial investment and operating costs, biogas is highlighted for its significant carbon footprint reduction and high energy efficiency. Biochar and compost rank second and third, respectively, followed by bokashi and vermicompost among the evaluated options. These findings show that biogas plants around the world have significant potential as a renewable energy source and can help reduce dependence on external energy sources. This study evaluates biowaste disposal methods with the AHP.

Human health surface water quality criteria (SWQC) for perfluorooctane sulfonic acid (PFOS) vary by up to five orders of magnitude between jurisdictions. The current study undertakes a probabilistic analysis to calculate a range of PFOS SWQC and rank input parameters based on their influence on criteria derivation. Probability distributions were used for exposure parameters (e.g., fish consumption rate, body weight, bioaccumulation factors), as well as the noncancer toxicity factor, which itself ranges over three orders of magnitude. Three distributions of the PFOS reference dose were evaluated: one based on animal data, one based on human data, and one based on both animal and human data. Using the three reference dose distributions, the 10th percentile SWQC range from 0.1 ng/L to 3 ng/L. Using the distribution based on human toxicity data only, approximately two thirds of the distribution of SWQC falls below typical analytical detection limits (around 1 ng/L). The sensitivity analysis identified fish consumption rate and PFOS toxicity factor as the most influential parameters, followed by bioaccumulation factors and relative source contribution. The application of probabilistic risk assessment as used in this study provides a useful tool for calculating a range of possible SWQC and understanding the relative importance of input parameters. The method of sensitivity analysis can be adapted to any chemical and target population.

Under Section 304(a) of the Clean Water Act, the U.S. Environmental Protection Agency (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.

Antibiotics have reduced disease burdens in humans and animals, but the development of resistant microbes in agricultural products poses a risk. The long-term impacts of antibiotics in agri-foods remain poorly understood, making it difficult to assess their risks to human and animal health. Current research suggests that most antibiotic contamination in the agri-food chain poses negligible risks, based on assessments of measured environmental concentrations (MECs), predicted environmental concentration (PEC)/predicted no-effect concentration (PNEC) ratios (MEC/PNEC < 0.1), toxic units (TU = MECs/half-maximal effect concentration [EC50] < 0.01), and summed risk quotients (STUs < 0.3), but hotspots and unknowns need attention. To verify existing findings, we reviewed literature from Web of Science, Scopus, and ScienceDirect (n = 281,865), excluded duplicates (n = 272,085) and irrelevant studies (n = 9,516) based on predefined criteria (relevance, impact factor, citations), retaining 264 articles for analysis through a One Health approach. Although antimicrobial resistance (AMR) critically disrupts gut microbiota and increases global health/economic burdens, long-term studies frequently overlook key foodborne pathogens: Salmonella spp., Escherichia coli, Staphylococcus aureus, Listeria monocytogenes, Campylobacter, and Vibrio parahaemolyticus. This review provides new perspectives on the integration of AMR within a One Health concept by (1) summarizing current knowledge on the spread of antibiotic-resistant bacteria (ARB) and antibiotic-resistant genes (ARGs) in agri-food systems and their health and environmental human impacts and (2) identifying critical research gaps, particularly in understanding postingestion effects. A major finding of this review is that while there is documented transmission of antibiotic residues, ARBs, and ARGs to humans via the food chain, their actual impacts on gut-acquired infections remain largely unknown. Given the accelerating pace of AMR, delaying targeted research within the One Health framework is no longer an option. Immediate coordinated action across agriculture, policy, and science is critical to close these knowledge gaps, disrupt resistance pathways, and safeguard the health of humans, animals, and ecosystems before AMR escalates beyond control.