Eco-Environment & Health最新文献

This study examined the potential health risks posed by the operation of 96 waste-to-energy (WtE) plants in 30 cities in the Bohai Rim of China. Utilizing a sophisticated simulation approach, the Weather Research and Forecasting (WRF) model coupled with the California Puff (CALPUFF) model, we obtained the spatial distribution of pollutants emitted by WtE plants in the atmosphere. Hazard indices (HI) and cancer risks (CR) were calculated for each plant using the United States Environmental Protection Agency's recommended methodologies. The results indicated that both HIs and CRs were generally low, with values below the accepted threshold of 1.0 and 1.0 × 10⁻⁶, respectively. Specifically, the average HI and CR values for the entire study area were 2.95 × 10⁻³ and 3.43 × 10⁻⁷, respectively. However, some variability in these values was observed depending on the location and type of WtE plant. A thorough analysis of various parameters, such as waste composition, moisture content, and operating conditions, was conducted to identify the factors that influence the health risks associated with incineration. The findings suggest that proper waste sorting and categorization, increased cost of construction, and elevated height of chimneys are effective strategies for reducing the health risks associated with incineration. Overall, this study provides valuable insights into the potential health risks associated with WtE plants in the Bohai Rim region of China. The findings can serve as useful guidelines for law enforcement wings and industry professionals seeking to minimize the risks associated with municipal solid waste (MSW) management and promote sustainable development.

The short-term associations of ambient temperature exposure with lung function in middle-aged and elderly Chinese remain obscure. The study included 19,128 participants from the Dongfeng-Tongji cohort's first (2013) and second (2018) follow-ups. The lung function for each subject was determined between April and December 2013 and re-assessed in 2018, with three parameters (forced vital capacity [FVC], forced expiratory volume in 1 s [FEV₁], and peak expiratory flow [PEF]) selected. The China Meteorological Data Sharing Service Center provided temperature data during the study period. In the two follow-ups, a total of 25,511 records (average age: first, 64.57; second, 65.80) were evaluated, including 10,604 males (41.57%). The inversely J-shaped associations between moving average temperatures (lag01–lag07) and FVC, FEV₁, and PEF were observed, and the optimum temperatures at lag04 were 16.5 °C, 18.7 °C, and 16.2 °C, respectively. At lag04, every 1 °C increase in temperature was associated with 14.07 mL, 9.78 mL, and 62.72 mL/s increase in FVC, FEV₁, and PEF in the low-temperature zone (<the optimum temperatures), whereas 5.72 mL, 2.01 mL, and 11.64 mL/s decrease in the high-temperature zone (≥the optimum temperatures), respectively (all P < 0.05). We observed significant effect modifications of gender, age, body mass index, body surface area, smoking status, drinking status, and physical activity on the associations (all P_modification < 0.05). Non-optimal temperatures may cause lung function decline. Several individual characters and lifestyles have effect modification on the temperature effects.

While plastic water bottles are known to potentially release various volatile organic compounds (VOCs) when exposed to light, existing knowledge in this field remains limited. In this study, we systematically examined the composition, yield, and toxicity of VOCs released from six plastic containers obtained from different continents under UV-A and solar irradiation. After light exposure, all containers released VOCs, including alkanes, alkenes, alcohols, aldehydes, carboxylic acids, aromatics, etc. The 1#, 3#, 4#, 5#, and 6# containers exhibited 35, 32, 19, 24 and 37 species of VOCs, respectively. Specifically, the 2# container released 28 and 32 series of VOCs after 1-day (short-term) and 7-day (long-term) UV-A irradiation, respectively, compared to 30 and 32 species under solar irradiation. Over half of the VOCs identified were oxidized compounds alongside various short-chain hydrocarbons. Significant differences in VOC compositions among the containers were observed, potentially originating from light-induced aging and degradation of the polyethylene terephthalate structure in the containers. Toxicological predictions unveiled distinctive toxic characteristics of VOCs from each container. For example, among the various VOCs produced by the 2# container, straight-chain alkanes like n-hexadecane (544-76-3) were identified as the most toxic compounds. After long-term irradiation, the yield of these toxic VOCs from the 2# container ranged from 0.11 ng/g to 0.79 ng/g. Considering the small mass of a single bottle, the volatilization of VOCs from an individual container would be insignificant. Even after prolonged exposure to light, the potential health risks associated with inhaling VOCs when opening and drinking bottled water appear manageable.

The quantity and complexity of environmental data show exponential growth in recent years. High-quality big data analysis is critical for performing a sophisticated characterization of the complex network of environmental pollution. Machine learning (ML) has been employed as a powerful tool for decoupling the complexities of environmental big data based on its remarkable fitting ability. Yet, due to the knowledge gap across different subjects, ML concepts and algorithms have not been well-popularized among researchers in environmental sustainability. In this context, we introduce a new research paradigm—“ChatGPT + ML + Environment”, providing an unprecedented chance for environmental researchers to reduce the difficulty of using ML models. For instance, each step involved in applying ML models to environmental sustainability, including data preparation, model selection and construction, model training and evaluation, and hyper-parameter optimization, can be easily performed with guidance from ChatGPT. We also discuss the challenges and limitations of using this research paradigm in the field of environmental sustainability. Furthermore, we highlight the importance of “secondary training” for future application of “ChatGPT + ML + Environment”.

Despite the existence of many interventions to mitigate or adapt to the health effects of climate change, their effectiveness remains unclear. Here, we introduce the Comprehensive Evaluation Framework for Intervention on Health Effects of Ambient Temperature to evaluate study designs and effects of intervention studies. The framework comprises three types of interventions: proactive, indirect, and direct, and four categories of indicators: classification, methods, scope, and effects. We trialed the framework by an evaluation of existing intervention studies. The evaluation revealed that each intervention has its own applicable characteristics in terms of effectiveness, feasibility, and generalizability scores. We expanded the framework's potential by offering a list of intervention recommendations in different scenarios. Future applications are then explored to establish models of the relationship between study designs and intervention effects, facilitating effective interventions to address the health effects of ambient temperature under climate change.

Nuclear isotopes, distinct atoms characterized by varying neutron counts, have profoundly influenced a myriad of sectors, spanning from medical diagnostics and therapeutic interventions to energy production and defense strategies. Their multifaceted applications have been celebrated for catalyzing revolutionary breakthroughs, yet these advancements simultaneously introduce intricate challenges that warrant thorough investigation. These challenges encompass safety protocols, potential environmental detriments, and the complex geopolitical landscape surrounding nuclear proliferation and disarmament. This comprehensive review embarks on a deep exploration of nuclear isotopes, elucidating their nuanced classifications, wide-ranging applications, intricate governing policies, and the multifaceted impacts of their unintended emissions or leaks. Furthermore, the study meticulously examines the cutting-edge remediation techniques currently employed to counteract nuclear contamination while projecting future innovations in this domain. By weaving together historical context, current applications, and forward-looking perspectives, this review offers a panoramic view of the nuclear isotope landscape. In conclusion, the significance of nuclear isotopes cannot be understated. As we stand at the crossroads of technological advancement and ethical responsibility, this review underscores the paramount importance of harnessing nuclear isotopes' potential in a manner that prioritizes safety, sustainability, and the greater good of humanity.

Soil, the largest terrestrial carbon reservoir, is central to climate change and relevant feedback to environmental health. Minerals are the essential components that contribute to over 60% of soil carbon storage. However, how the interactions between minerals and organic carbon shape the carbon transformation and stability remains poorly understood. Herein, we critically review the primary interactions between organic carbon and soil minerals and the relevant mechanisms, including sorption, redox reaction, co-precipitation, dissolution, polymerization, and catalytic reaction. These interactions, highly complex with the combination of multiple processes, greatly affect the stability of organic carbon through the following processes: (1) formation or deconstruction of the mineral–organic carbon association; (2) oxidative transformation of the organic carbon with minerals; (3) catalytic polymerization of organic carbon with minerals; and (4) varying association stability of organic carbon according to the mineral transformation. Several pieces of evidence related to the carbon turnover and stability during the interaction with soil minerals in the real eco-environment are then demonstrated. We also highlight the current research gaps and outline research priorities, which may map future directions for a deeper mechanisms-based understanding of the soil carbon storage capacity considering its interactions with minerals.