Journal of Environmental Health Science and Engineering最新文献

Air pollution remains a significant global health challenge and is increasingly recognized as a critical exposomic risk factor for adverse birth outcomes. Although numerous epidemiological studies have linked prenatal air pollution exposure to low birth weight, preterm birth, and stillbirth, important uncertainties remain regarding the underlying biological mechanisms, critical exposure windows, and the interplay between different pollutants and susceptibility factors. This narrative review synthesizes epidemiological findings and mechanistic evidence identified through literature searches in PubMed, Scopus, and Web of Science to provide a comprehensive overview of how maternal exposure to air pollutants affects fetal development and pregnancy outcomes. The reviewed epidemiological evidence largely supports an association between maternal air pollution exposure and adverse birth outcomes. For example, a 10 µg/m³ increase in fine particulate matter (PM_2.5) exposure during the second trimester has been associated with an 11.8 g reduction in birth weight and a 23.1% increase in the risk of preterm birth. Oxidative stress, inflammation, endocrine disruption, vascular dysfunction, and epigenetic modifications are considered key biological pathways through which air pollution may impair placental function, alter fetal growth trajectories, and increase the likelihood of pregnancy complications. The placenta serves as a critical interface between maternal and fetal health and is particularly vulnerable to environmental insults, with air pollution exposure linked to changes in placental morphology, perfusion, and metabolic function. However, challenges persist in disentangling the effects of individual pollutants, establishing causality, identifying critical windows of susceptibility, and determining the extent to which sociodemographic, lifestyle, and genetic factors modify these associations. Current research gaps underscore the need for studies integrating high-resolution exposure assessment, multi-pollutant modeling, and mechanistic investigations to better clarify the impact of air pollution on pregnancy outcomes.

Graphical Abstract

Air pollution and adverse birth outcomes

This research evaluates the potential radiological health risks caused by natural radionuclides in both imported and locally manufactured baby food brands consumed in the Iraqi Kurdistan region, utilizing statistical analysis and Monte Carlo-based methods. Activity concentrations of ²³⁸U, ²³²Th, and ⁴⁰K were measured in various baby food samples using a NaI(Tl) based gamma spectrometry with a CASSAY software for spectral analysis. The results shows that ²³⁸U, ²³²Th, and ⁴⁰K have mean activity concentrations of 13.2 ± 4.23, 10.6 ± 3.38, and 217.0 ± 6.94 Bq kg^− 1, respectively. The estimated annual effective dose from the three radionuclides for infants in age groups < 1 y and 1–2 y surpassed the internationally suggested limit of 1 mSv y^− 1, indicating a potential radiological health concern. The mean values of ELCR evaluated by deterministic calculations were 1.05 × 10^− 2 and 4.83 × 10^− 3 for infants aged < 1 y and 1–2 y, respectively. Monte Carlo simulations provided probabilistic risk estimates, which revealed that the ELCR surpassed the acceptable threshold of 1 × 10⁻⁴, suggesting a non-negligible carcinogenic risk associated with long-term consumption of the baby food brands. The results of this study emphasize the importance of stringent quality control measures, enhanced regulatory oversight and public awareness to mitigate potential health effects. Routine monitoring and additional research on dietary exposure routes are advised to guarantee the safety of infant food products in the region. The study calls for more research into dietary exposure pathways and regular monitoring to ensure the safety of infant food products in the region.

Graphical abstract

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This study characterized physicochemical properties, elemental contamination, and health risks of size-fractionated settled dust in child-relevant microenvironments in Tehran, Iran. Paired indoor and outdoor samples were collected from 50 residential houses and 50 kindergartens (February–July 2023). The < 150 μm fraction was analyzed for potentially toxic elements (PTEs) by microwave plasma-atomic emission spectroscopy. Mineralogy, morphology, and water-soluble ions were determined by XRD, FE-SEM/EDX, and ion chromatography, respectively. Particle size distributions were dominated by coarse material (D50: 29.6–53.3 μm), consistent with a quartz–calcite–clay assemblage. Mean concentrations followed the order Al > Fe > Zn > Mn; Zn (622–1,129 µg/g) and Pb (72–139 µg/g) were the most enriched anthropogenic elements. Contamination factor analysis identified very high contamination by Zn and Pb, while the pollution load index remained below unity (0.24–0.34). Outdoor concentrations explained 82.4% of indoor variability (r² = 0.824; β ≈ 1.09), confirming dominant outdoor influence. Ingestion contributed over 99% of total average daily dose. Non-carcinogenic hazard indices remained below unity but were highest in indoor kindergartens (total HI ≈ 0.73; Pb HI ≈ 0.53). The total carcinogenic risk approached or exceeded 10⁻⁴ in indoor houses, with Ni and estimated Cr(VI) as the principal contributors. Results highlight kindergartens as priority environments for pediatric exposure management and support targeted mitigation strategies, including traffic and construction control near child-occupied locations and enhanced dust-reduction practices.

Synthetic dyes, such as methyl violet (MV), are hazardous pollutants that pose risks to both aquatic ecosystems and public health. Thus, developing effective adsorbents for their removal is of environmental importance. In this study, a composite hydrogel of k-carrageenan-cl-Poly(Crotonic acid-co-N-isopropyl acrylamide)/dichloride-bis(6-aminopencillanic acid)titanium(III)Chloride), HML composite was created using a free radical copolymerization method with potassium persulfate (KPS) as the initiator and N, N-methylene bis-acrylamide (MBA) as a cross-linking agent. This hydrogel was designed to remove MV dye from aqueous solutions. The research focused on optimizing the synthesis conditions to prepare a hydrogel with the highest swelling ratio (SR%). The results indicated that using 0.08 g of ML complex resulted in the HML composite achieving the most significant swelling ratio of 4200% in distilled water. It was observed that the dye adsorption capacity of the HML composite was significantly influenced by the level of the CA monomer in the hydrogel, which improved its ability to swell. The HML composites were characterized using XRD, FTIR, FESEM/EDX, TEM, TGA, and BET. The Box-Behnken Design (BBD) based on response surface methodology (RSM) was employed to optimize the adsorption performance of the HML composite, considering factors such as A: pH (3–10), B: adsorbent dosage (0.03–0.12 g) and C: concentration (100–800 mg/L). The swelling ratio (SR%) and gel content (Gc%) of the HML composites were compared with those of the hydrogel without the complex in water. It was observed that as the complex increased, the Gc% also increased, while the SR% decreased. Additionally, the Point of Zero Charge (PZC) was determined to be 5.8. The thermal stability of the samples was investigated, revealing that the HML composites exhibit better thermal stability than the hydrogel alone. Furthermore, we studied the ability of the samples to adsorb the cationic MV dye from aqueous solutions. The study was conducted at dye concentrations of 100–800 mg/L for a duration of 5–120 min and at a pH range of 3–10. The optimal conditions for dye absorption were found to be at pH 7, a concentration of 600 mg/L, and a duration of 60 min. Additionally, the maximum adsorption efficiency was 730.88 mg/g, and the HML composites exhibited 94.33% dye removal at a concentration of 600 mg/L. The Freundlich isotherm and the first-order kinetic models well described the adsorption results. The thermodynamic parameters indicated that this adsorption system was endothermic in nature. The hydrogel was effectively regenerated using HCl for six cycles. Therefore, this study confirms the effectiveness of using HML composite as a promising adsorbent for removing toxic dyes.

The increasing generation of healthcare waste (HCW), together with inadequate management practices, poses risks to public health and environmental safety. This situation highlights the need for robust quantitative approaches to support waste estimation and planning. In this study, machine learning–based regression models, including Support Vector Machine (SVM), Ensemble of Trees (ET), and Gaussian Process Regression (GPR), were applied to estimate HCW generation across Indian states. Principal Component Analysis (PCA) was used to reduce data dimensionality and to construct a hybrid model based on the best-performing individual approach. Model performance was assessed using the root mean square error (RMSE) and the coefficient of determination (R²). Pearson correlation analysis was conducted during the preliminary stage to evaluate relationships among input variables, and statistical significance was verified using a two-tailed test. Sensitivity analysis was performed through nonlinear input selection, resulting in eight model configurations for the model creation. Among the individual models, GPR produced the lowest prediction error, with an RMSE of 0.0048 (GPR-2), outperforming the SVM and ET models. The PCA–GPR hybrid model further improved prediction accuracy, achieving a minimum RMSE of 0.0019. SHapley Additive exPlanations (SHAP) analysis was employed to enhance the effect of the model interpretability, revealing that healthcare capacity indicators and urban-demographic factors are the dominant drivers of HCW generation. The results demonstrate that regression-based and hybrid modelling approaches are effective for estimating HCW generation. The study also indicates that prediction performance can be enhanced by incorporating additional socioeconomic and demographic variables, although data availability and data quality remain key limitations, particularly in regions with incomplete historical records.

This investigation endeavored to assess the human health and ecological risks intrinsically associated with the environmental discharge of frequently utilized antibiotics during 2022–2023. Commonly used antibiotics (17 entities in 2022 and 18 in 2023) were designated based on sales volume metrics (> 95% cumulative threshold). Environmental releases were estimated contingent upon consumption figures, pharmacokinetic parameters, and population size. The MERLIN-Expo framework modeled environmental disposition and anthropogenic exposure. Toxicity endpoints were predicted using quantitative structure-activity relationship (QSAR) models. Human health risk and ecological risk of the antibiotics were determined in terms of hazard quotient (HQ) and risk quotient (RQacute and RQchronic), respectively. Amoxicillin, metronidazole, and azithromycin constituted the agents consumed in the greatest quantities annually. Significant increments in cephalosporin (+ 28.6%) and tetracycline (+ 35.8%) consumption manifested in 2023, concurrent with diminished penicillin utilization (-4%). All HQ and RQ values of the antibiotics were determined to be subordinate to conventionally accepted concern thresholds (HQ < 1, RQacute < 0.5, and RQchronic < 1.0). Nitrofurantoin (HQ = 6.54 × 10^− 4, 2022) and clavulanic acid (HQ = 5.51 × 10^− 4, 2023) exhibited the highest human health risks. Although human health and ecological risk of prevalent antibiotics in Tehran were appraised as subordinate to standard concern levels, elevated consumption rates precipitate continuous environmental discharge. The fact that risk quotients for some compounds reached noteworthy levels, although still well below regulatory thresholds, accentuates the imperative for sustained environmental surveillance, targeted antibiotic stewardship, and augmentation of wastewater management efficacy to mitigate potential long-term sequelae and the potential for antimicrobial resistance selection.

Developing countries, undergoing rapid urbanization, have a keen interest in circular economy and its application in the construction sector in hopes of alleviating stresses on urban resources and waste management systems. This study presents a novel approach to identifying the demolition candidates from a city master plan, estimating natural building turnover from past demolitions, and quantifying the resultant materials with a potential to close the loop. Astana, the capital of Kazakhstan, was selected as a representative case due to its booming construction development along with scarce data on demolition activities. The methodology included (1) using ArcGIS and its fine-tuned Mask RCNN model to extract building footprints, (2) manual identification of demolition activities, (3) characterization of the building stock based on the city’s master plan to estimate the demolition waste composition, and using results obtained, (4) the prediction of annual demolition material volumes until 2035. The model for footprint extraction from past satellite imagery achieved 70.1% object-based recall (≥ 50% overlap with ground truth) while the average error for the footprint area estimation was 2.0%. Between 2016 and 2022, there were nearly 4,500 demolition works resulting in over 108 Mt of demolition materials including concrete (57.6%), steel (3.6%), brick (14.0%), wood (7.4%), and others (17.4%). Due to planned land-use changes occurring over a third of the city area by 2035, around 9,000 buildings with cumulative 500 Mt of materials are potential demolition candidates and, by extension, sources for urban mining. The proposed methodology allows to capitalize on the knowledge from city master plans and paves way to preparing a city-scale waste management strategy on how to incorporate demolition materials into new construction and close the material loop.

Purpose

Air pollution is the biggest environmental factor impacting the health of people worldwide contributing significantly to mortality. This study has been conducted to investigate the strategies of air pollution policies suggested by multilateral organisations to mitigate the adverse impact of air pollution on populations’ health.

Methods

This study was a qualitative document analysis of health policies and strategies related to air pollution. For this purpose, READ’s 4-step approach (Ready material, Extract findings, Analyse data and Distil findings) was used. This approach entails systematic method for collating documents and extracting information from them. This was done with respect to air pollution and health policy studies at global, national and local levels. After extraction of related documents, the content analysis of the obtained documents was done.

Results

Cumulatively 12 documents were considered for analysis. In toto, 810 codes, 27 subcategories and 9 categories were extracted by content analysis. The categories included strategies for emission reduction, strategies for exposure reduction, strategies for education & communication, strategies for high-risk groups, strategies for research, strategies for capacity building, strategies for policymaking, implementation and enforcement, strategies for collaboration and coordination, and strategies for evaluation.

Conclusion

Mitigating health impacts of air pollution needs to go beyond emission reduction at the sources of pollution. They could encompass comprehensive and holistic measures addressed to population affected by pollution. Health sector strengthening, policy advocacy by health sector, health sector awareness, policy enforcement and implementation through cross sectoral and geographical collaboration and coordination also needs to be the focus for improving the health of the population.

According to global statistics, approximately 400 million tons of plastic are produced worldwide each year, yet only about 9% is recycled. Environmental degradation of plastics generates microplastics and nanoplastics, which have been shown to induce oxidative stress, genotoxicity, and endocrine disruption. Additionally, nanoplastics can adsorb environmental pollutants, act as transport vectors within biological systems, and alter pollutant toxicokinetics. In this study, we conducted a comparative analysis of paraquat adsorption and in vitro cytotoxicity of polyethylene terephthalate nanoplastics (n-PET) and polypropylene nanoplastics (n-PP). The results showed that n-PET exhibited significantly higher adsorption capacity for paraquat than n-PP, with maximum interaction observed at pH 11 and particle sizes below 100 nm. In vitro experiments using the human embryonic kidney (HEK-293) cell line demonstrated higher cytotoxicity for n-PET compared to n-PP. Co-exposure to n-PET and paraquat resulted in significantly greater cytotoxic effects than exposure to either agent alone. IC₅₀ values were determined at 24, 48, and 72 h. Furthermore, both nanoplastics disrupted cellular redox homeostasis, with n-PET inducing a more pronounced oxidative imbalance than n-PP. These findings indicate that n-PET may act as a stronger carrier of paraquat and pose a greater toxicological risk under co-exposure scenarios, highlighting the importance of nanoplastic–pollutant interactions in environmental risk assessment.

Background

Indoor air quality (IAQ) impacts well-being and the spread of airborne diseases, particularly in multi-occupancy environments like classrooms. Carbon dioxide (CO₂) and particulate matter (PM) levels have been used in continuous monitoring as indicators of indoor air quality.

Methods

We used cost-effective sensors to assess levels of CO2 and PM in two Italian university classrooms (Unit 1 and Unit 2), differing in size and ventilation, from March 2022 to May 2023. For CO2 and PM monitoring we used respectively ARANET4 sensors and Optical Particle Counters (OPC) assessing aerosol diameter size distribution between 350 nm and 40 μm in order to evaluate trends in IAQ and the influence of environmental factors including ventilation, occupancy, and season.

Results

The naturally ventilated classroom (Unit 1) exhibited higher CO2 and PM concentrations with greater variability, whereas the HVAC-supported one (Unit 2) maintained more consistent air quality but faced occasional spikes. Occupancy also affected CO2 and PM levels, with higher variability in Unit 1 characterized by lower size and generally full occupancy. Seasonal trends highlighted increased PM levels during colder months due to reduced ventilation in both units.

Conclusions

In this feasibility study, variations in building design, ventilation strategies, and occupancy dynamics were associated with corresponding patterns in IAQ, supporting the use of low-cost, user-friendly sensors as practical tools to characterize ventilation performance and to inform interventions aimed at safer learning spaces. Implementation of CO2 and PM measurements as proxy indicators of ventilation adequacy and of potential airborne infection risk, along with outreach programs and guidelines to educate teachers and students about relevance of IAQ assessment is recommended to promote occupant health and mitigate risk of airborne disease transmission.