Integrated Environmental Assessment and Management最新文献

Artificial intelligence (AI) transforms extreme-weather forecasting by delivering faster and more accurate predictions at a fraction of the computational cost of traditional models. However, these advances are often accompanied by opaque decision processes, raising challenges for trust, equity, and long-term resilience in early warning systems. This article examines transparency in AI-based forecasting across three dimensions-predictive integrity, societal fairness, and long-term resilience-and argues that accuracy alone is insufficient in high-stakes contexts. Drawing on recent regulatory developments and global meteorological practice, we outline practical measures such as harmonized forecast labeling, impact-ready model cards, and extreme-event regulatory sandboxes. Embedding these measures within international frameworks is essential to ensure that the speed and efficiency of AI-driven forecasts translate into effective, trusted, and equitable early warning systems.

Commonly used, over-the-counter nonsteroidal anti-inflammatory drugs (OTC NSAIDs) and antipyretic pharmaceuticals represent emerging contaminants of concern, with high global consumption attributing to their frequent detection across diverse water systems. Concerns surround their harmful impacts on aquatic biota, especially because waterbodies represent the predominant receiving matrices for drug-imbued effluents and waste disposal. To support the growing evidence of toxicity effects from emerging contaminants like OTC drugs on nontarget organisms, ecotoxicological assessments have been conducted using bioassay experiments and biological models, like crustaceans. To shed light on the scope of toxicity data on common OTC drugs available for this sensitive group while identifying research gaps and poorly studied areas that need future ecotoxicological attention, the goal focused on reviewing existing literature on toxicity studies that involved crustaceans and commonly used NSAID and antipyretic OTC medications represented by ibuprofen, diclofenac, aspirin/acetylsalicylic acid, and paracetamol/acetaminophen. Published studies were accrued from literature databases using a systematic search strategy and a four-stage protocol. A total of 814 records resulted, with 68 meeting relevance following their eligibility screening against defined criteria. Extracted data were organized according to general bibliographical identifiers, experimental design aspects, and key findings. Assimilated information revealed that most studies focused on acute toxicity testing for the chosen pharmaceuticals using largely microcrustaceans as test models (Branchiopoda, Copepoda, Isopoda, Amphipoda, Ostracoda, and Mysida), especially conventionally known groups (daphnids). Ibuprofen was the most investigated across all taxa (32.9%), but effect concentrations for caridean shrimps (Neocaridina denticulata and Atyaephyra desmarestii) and the amphipod Hyalella azteca reflected notable sensitivity toward diclofenac. Fewer studies assessed mixtures, metabolites, and long-term/sublethal effects in relation to the focus drugs. Future research efforts can supplement these information deficiencies with the aid of efficient nontraditional (ecotoxicological) methodologies within ethical frameworks to support environmental policy and risk management for NSAID and antipyretic pharmaceuticals.

Water contamination from heavy metals and synthetic dyes presents a persistent environmental challenge, necessitating the development of efficient and sustainable remediation strategies. This review critically evaluates chitosan-based adsorbents, focusing on chitosan-activated carbon composites, and explores recent breakthroughs in structural and functional modifications that enhance their adsorption capacity. Innovations such as nanoparticle integration, metal-organic frameworks (MOFs), bio-based reinforcements, and surface functionalization have significantly improved selectivity, adsorption kinetics, and regeneration potential, enabling greater adaptability for wastewater treatment. Additionally, this review highlights the emergence of hybrid water treatment technologies, including adsorption-assisted photocatalysis, electrochemical regeneration, and nanostructured filtration systems, which offer promising solutions for overcoming challenges related to adsorbent stability, scalability, and process efficiency in complex wastewater matrices. The study comprehensively evaluates these advancements, offering insights into material innovations, process optimization strategies, and their alignment with circular economy principles for sustainable water treatment applications. Future research should prioritize enhancing long-term adsorbent stability, improving regeneration efficiency, and integrating predictive modeling techniques to bridge the gap between laboratory advancements and large-scale implementation.

The remediation of Comprehensive Environmental Response, Compensation, and Liability Act or Superfund sites is limited to cleanup to levels no lower than background concentrations. However, both anthropogenically induced and naturally occurring metal concentrations in soil and sediments often complicate this cleanup process. To support informed decisions on heavy metal cleanup and the development of soil heavy metal-related policies in North Carolina, a statewide dataset of background heavy metal data from Superfund site investigations was compiled. The dataset represents background concentrations at 326 Superfund sites found in North Carolina, United States, from 1985 to 2015. This 30-year dataset comprises site location data and analytical measurement results for 18 heavy metals in 624 soil and 228 sediment samples, obtained using standard methods. The data are presented in an interactive dashboard, offering summary statistics and graphical representations that can be customized to support specific decision-making needs. The data and Dashboard serve two main goals: (1) to inform and support cleanup decisions and policy development regarding soil heavy metals, and (2) to increase public awareness of the levels of naturally occurring and anthropogenic background heavy metals in soil and sediments across the state. The publicly accessible and interactive dashboard offers a deeper understanding of background environmental conditions in relation to evolving anthropogenic contamination within a broader context.

A spatially referenced environmental exposure model for down-the-drain substance emissions was developed for Europe, including the 27 European Union Member States, Norway, Switzerland, and the United Kingdom. The model builds upon the global modeling framework that leverages the well-established iSTREEM model for the United States and further expands global coverage of the framework. The data are parameterized using European Union data on wastewater treatment plants, locations, infrastructure, and global spatial datasets on population and river flow rates and routing. The model provides substance concentration distributions based on the spatial variability of these parameters across Europe while taking into account river connectivity, chemical routing between rivers, and in-stream decay. Chemical-specific model inputs include wastewater treatment removals, in-stream decay rates, and emissions. The model is demonstrated for four case study chemicals that are used in consumer products with down-the-drain disposal routes: linear alkylbenzene sulfonate and alkyl sulfate are common surfactants used in laundry detergents, and oxybenzone and octinoxate are ultraviolet (UV)-filters used in personal care products. Monitoring data were collected to represent spatial variability across Europe as a comparison to modeled values. Modeled concentrations were found to be predictive while still being conservative, with 90th percentile modeled concentrations agreeing with monitored concentrations within a factor of two to eight across the case study substances. We further demonstrate how the model can be applied in prospective safety assessments by comparing modeled concentrations to previously established predicted no-effect concentrations, and also demonstrate how the model is consistent with tiered risk assessment approaches when compared to the monitoring data assessments.

Life Cycle Assessment (LCA) and Social Life Cycle Assessment (S-LCA) are currently essential tools for evaluating the sustainability of products and industrial systems. Although LCA is systematically applied today and is considered a stable methodology, supported by material-specific guidelines and rich databases, S-LCA remains immature in certain aspects. In the presented case study, LCA was applied to compare 11 methanol synthesis processes, all based on reverse Water-Gas Shift, but characterized by different sources of CO2 and H2 supply, to identify the most promising. Accordingly, the model was then integrated with that of propylene production (methanol to propylene-MtP), identified as a molecule of interest for the current and future market. Then, the authors propose an innovative approach to enhance the application of S-LCA in the industrial chemistry sector. The climate change impact of the different methanol production scenarios varies significantly: the most impactful is the methanol synthesis via coal gasification (2.76 kg CO2 eq), and the most promising are via CO2 generated by wood chips waste or dedicated biomass by employing hydrogen produce with wind electrolysis, which show the negative impacts of -0.40 kg CO2 eq thanks to cogeneration and the use of hydrogen from renewable sources. On the social level, the database shows a preference for productions occurring in Europe, across all the categories analyzed. The proposal of a sector-specific guideline represents a step forward that could facilitate the future application of the methodology. Moreover, the integration of LCA and S-LCA proves effective in delivering a richer and more comprehensive understanding of the issues addressed, offering valuable insights for stakeholders. The LCA should be applied to assess the environmental sustainability of alternative production routes in chemical processes, while the complexity of S-LCA can be mitigated by initiating preliminary assessments.

We issue a call to action: in the context of safe design, all pesticides must be traceable via low-cost methods that are accessible for routine environmental monitoring by public institutions. Insights into the far-reaching impacts of pesticides depend on our ability to detect these chemicals in the environment. Once a pesticide is authorized for use, environmental monitoring serves as a critical warning system that complements risk assessments. Postregistration monitoring is recognized by different policy frameworks such as the Water Framework Directive and the European Green Deal. However, we highlight an urgent concern: despite formal requirements for detectability in registration, novel pesticides are becoming progressively undetectable in practice. We demonstrate how mandated reductions in pesticide use measured as volume can drive chemical innovations that unintentionally undermine environmental accountability and safety. For example, volume can be decreased while maintaining effectiveness by increasing the specificity or toxicity of the pesticide. This phenomenon is analogous to "analytical homeopathy," where active ingredients remain effective even at extremely low dosages, rendering them undetectable by standard analytical chemistry. This issues a significant challenge: higher toxicity can imply lower environmental quality standards near detection limits. This leads to the troubling problem of "known unknowns," risks posed by active ingredients whose emissions remain unquantified under current field monitoring conditions. In response to this emerging threat, we propose a foundational principle, that all synthetic pesticides should be detectable in the environment at the concentration of their active ingredients, enabling cost-effective and reliable monitoring. If neglected, then the credibility and function of monitoring as a warning system for unintended biodiversity harm is increasingly undermined, regardless of formal analytical capabilities.

The inclusion of analytics in soil invertebrate laboratory studies is gaining increasing attention in the European risk assessment of plant protection products (PPPs). Analytics in soil were recently requested for fast-dissipating compounds in the revised Central Zone Working Document. However, the Working Document, as well as the technical Organization for Economic Co-operation and Development (OECD) testing guidelines, lack clarity on (1) how to design the laboratory studies to reliably fulfill this requirement, (2) how to consider the analytically measured values to derive robust ecotoxicological endpoints, and (3) how to use endpoints that consider time-variable exposure in the test, in the risk assessment of PPPs. A hypothetical case study is presented to show the impact on the risk assessment when ecotoxicological endpoints that are expressed as time-weighted average (TWA) concentrations are compared with maximum predicted environmental concentrations (PEC) in soil to calculate a Tier 1 toxicity-exposure-ratio (TER). The persistent compound would pass the critical TER trigger of 5, whereas the fast-dissipating compound fails the risk assessment. However, a fast dissipation of a compound is, from an environmental perspective, a favorable substance property and especially inherent for biological products. This sets the wrong motivation for the development of new PPPs. The suitability of using TWA-PECs in the risk assessment instead of maximum PECs is discussed by comparing temporal exposure scenarios in the test system with scenarios that may occur under realistic field situations. This analysis shows that potential underestimation of the risks may occur only for specific situations where the PEC in soil temporally exceeds the regulatory acceptable concentration over time. In such cases, the use of TWA-PECs in soil may be applicable in the risk assessment, provided the assumption of reciprocity is fulfilled. A reciprocity check can be performed via tailored ecotoxicological testing and/or effect modeling to justify the use of TWA-PECs in the risk assessment.

The aim of this study is to conduct a biophysical and economic assessment of carbon stocks associated with changes in land use and cover (LULC) in the Itajaí-Açu Valley Basin (IVB). The IVB is immersed in the Atlantic rainforest, considered one of the most diverse, as well as one of the most threatened, forests on the planet. The Valley is also home to important urban and industrial centers located along the riverbanks. Since its colonization in the second half of the 19th century, the region has constantly suffered from natural disasters, such as floods and landslides. With the expected escalation in extreme weather events in the near future due to climate change, these natural disasters may increase in intensity and frequency. Maps of LULC and the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) program were used to quantify and value the carbon stock and sequestration for three periods. The results show that between 2000 and 2020, there was an increase in forestry (354.64%), mosaic (57.43%), and pasture (43.08%) areas in the IVB, while a decrease was observed for natural forest (-4.38%), nonforest natural formation (-69.56%), and agriculture (-68.69%). The carbon stock values were 259,328,452 Mg C in 2000; 265,079,768 Mg C in 2010; and 262,577,960 Mg C in 2020. The carbon sequestration in the period 2000-2010 represented an economic benefit of US$138 million. Conversely, between 2010 and 2020, there were net carbon emissions equivalent to US$60 million. Over the entire period analyzed, there was a gain of US$78 million in ecosystem services related to carbon stocks. Targeted policies, such as Payment for Ecosystem Services programs, market-based incentives for carbon credits, and public investments in forest conservation and restoration, can bring economic, social, and ecological benefits, ensuring the continued provision of ecosystem services in the region.