Integrated Environmental Assessment and Management最新文献

The deployment of energy storage systems (ESS) plays a pivotal role in accelerating the global transition to renewable energy sources. Comprehending the life cycle environmental and economic impacts, as well as the necessary conditions and scenarios required for ESS deployment, is critical in guiding decision-making and supporting sustainable operations. In this study, we first analyzed the life cycle environmental impacts of pumped hydro energy storage (PHES), lithium-ion batteries (LIB), and compressed air energy storage. We then focused on elucidating the potential for carbon neutrality in existing PHES systems compared to LIBs in China by integrating various reduction measures to achieve net-zero emissions scenarios. Ultimately, we combined environmental and economic impacts to demonstrate the eco-efficiency of both ESS, supporting their sustainable deployment. Regarding environmental impacts, LIB is currently the most environmentally favorable ESS, followed by PHES. Various decarbonization measures revealed that transitioning to renewable energy sources is the most effective strategy for carbon reduction, with projected reductions ranging between 75% and 112% in both PHES and LIB systems. When implementing all carbon reduction strategies simultaneously, LIB is expected to achieve carbon neutrality by 2030, whereas PHES is projected to reach this milestone by 2040. With anticipated energy mix optimizations, carbon emissions are expected to further decrease to 22.2 kg CO2/MWh for PHES and 48.7 kg CO2/MWh for LIB by 2050. Economic analysis indicates that the life cycle cost per MWh for PHES is $66.5, approximately half that of LIB. Meanwhile, the payback period of PHES is 21 years, while that of LIB is 28 years to reach the break-even point. This disparity clearly underscores the superior economic benefits of PHES. The eco-efficiency of PHES is anticipated to surpass that of LIBs by 2028, rendering PHES a more favorable option in appropriate regions.

Plastics are integral to modern life and are ubiquitous across various environmental matrices. However, their widespread distribution has resulted in persistent contamination, now recognized as a critical environmental issue. Over time, this problem has intensified alongside the exponential increase in plastic production, leading to millions of tons being released into the environment via direct and indirect pathways. This accumulation poses significant risks to marine biota and ecosystem health. Despite ongoing mitigation efforts, projections indicate that plastic pollution will continue to rise in the coming years. The Colombian Caribbean, a region of high biodiversity and diverse industrial activities, has been notably affected by plastic contamination. This literature review aims to evaluate the reported concentrations of micro- and macroplastics in various environmental matrices within the Colombian Caribbean by systematically analyzing studies published over the past two decades. A total of 25 studies investigating plastic pollution in water, sediments, and marine organisms were examined. Additionally, this review evaluates the methodologies employed across these studies, revealing discrepancies in sampling protocols, laboratory analyses, and units of reporting. The lack of standardization in these aspects limits the comparability of results, underscoring the urgent need for harmonized methodologies. To enhance the reliability and comparability of future research on plastic pollution, this review proposes key measures for standardizing sampling techniques, analytical procedures, and data reporting. Furthermore, the promotion of interdisciplinary collaborations, policy development, and educational programs is recommended to address the growing plastic pollution problem in the Colombian Caribbean and mitigate its long-term environmental impacts.

Emerging contaminants (ECs) comprise classes of natural and anthropogenic chemicals that are increasingly detected in the environment especially waterways. The risk of ECs in the environment is recognized as an issue of concern in New Zealand. Environmental managers commissioned two virtual workshops to design a national survey of ECs in New Zealand where the largely primary production-based economy depends on uncontaminated natural resources and the ecosystem services they provide. Two 2- hour virtual workshops were commissioned to discuss the design of a national survey of ECs in New Zealand's waterways. The aim of these workshops was to hold initial discussions supporting the design and establishment of a national ECs survey of New Zealand rivers taking consideration of key technical aspects. The Ministry for the Environment and local authorities (regional councils) acknowledged the uncertainty associated with assessing the impacts of ECs on the New Zealand environment and developing protective actions and policy to minimize risk. Environmental managers, regulators, research scientists from Australasia, and Māori participants agreed that many knowledge gaps remain to fully characterize and assess the hazards of ECs both in New Zealand and globally. The importance of involving Māori is paramount when addressing EC issues and to develop sustainable solutions incorporating Indigenous knowledge and values. A key conclusion was that the large number of potential contaminants requires an approach for ranking ECs. As such, further research is needed to better characterize the type, quantities, sources, and fate of ECs in the environment as a first step towards identifying high-risk priority ECs. This would underpin an effective monitoring frameworks and inform policy that will ensure the sustainable management of ECs. It was recognized that collaboration across academic, industry, and government organizations is needed to coordinate and conduct effective ECs research by enabling prioritization and optimization of the resources and capability.

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.