Search Results (1,703)

Background: Outdoor and household PM_2.5 are established risk factors for chronic disease and early mortality. In China, high levels of outdoor PM_2.5 and solid fuel use for cooking and heating, especially in winter, pose large health risks to the country’s aging population. Hand grip strength is a validated biomarker of functional aging and strong predictor of disability and mortality in older adults. We investigated the effects of wintertime household and outdoor PM_2.5 on maximum grip strength in a rural cohort in Beijing. Methods: We analyzed data from 877 adults (mean age: 62 y) residing in 50 rural villages over three winter seasons (2018–2019, 2019–2020, and 2021–2022). Outdoor PM_2.5 was continuously measured in all villages, and household (indoor) PM_2.5 was monitored for at least two months in a randomly selected ~30% subsample of homes. Missing data were handled using multiple imputation. We applied multivariable mixed effects regression models to estimate within- and between-individual effects of PM_2.5 on grip strength, adjusting for demographic, behavioral, and health-related covariates. Results: Wintertime household and outdoor PM_2.5 concentrations ranged from 3 to 431 μg/m³ (mean = 80 μg/m³) and 8 to 100 μg/m³ (mean = 49 μg/m³), respectively. The effect of a 10 μg/m³ within-individual increase in household and outdoor PM_2.5 on maximum grip strength was 0.06 kg (95%CI: −0.01, 0.12 kg) and 1.51 kg (95%CI: 1.35, 1.68 kg), respectively. The household PM_2.5 effect attenuated after adjusting for outdoor PM_2.5, while outdoor PM_2.5 effects remained robust across sensitivity analyses. We found little evidence of between-individual effects. Conclusions: We did not find strong evidence of an adverse effect of household PM_2.5 on grip strength. The unexpected positive effects of outdoor PM_2.5 on grip strength may reflect transient physiological changes following short-term exposure. However, these findings should not be interpreted as evidence of protective effects of air pollution on aging. Rather, they highlight the complexity of air pollution’s health impacts and the value of longitudinal data in capturing time-sensitive effects. Further research is needed to better understand these patterns and their implications in high-exposure settings. Full article

Climate change and air pollution are associated with a range of health outcomes, including cardiovascular and respiratory disease. Evaluation of the synergic effects of air pollution and increasing natural temperature on mortality is important for understanding their potential joint health effects. In this study, the modification effects of air temperature on the short-term association of ambient fine particulate matter (PM_2.5) and ozone (O₃) with non-accidental death (NAD) and cardiovascular disease (CVD) mortality were evaluated by using the generalized additive model (GAM) combined with the distributed lag nonlinear model (DLNM) in urban areas of Taiyuan, a representative of energy and heavy industrial cities in Northern China. The data on the daily cause-specific death numbers, air pollutants concentrations, and meteorological factors were collected from January 2013 to December 2019, and the temperature was divided into low (<25th percentile), medium (25–75th percentile), and high (>75th percentile) categories. Significant associations of PM_2.5 and O₃ with NAD and CVD mortality were observed in single-effect analysis. A statistically significant increase in the effect estimates of PM_2.5 and O₃ on NAD and CVD mortality was also observed on high-temperature days. But the associations of those were not statistically significant on medium- and low-temperature days. At the same temperature level, the effects of PM_2.5 and O₃ on the CVD mortality were larger than those on NAD (1.74% vs. 1.21%; 1.67% vs. 0.57%), and the elderly and males appeared to be more vulnerable to both higher temperatures and air pollution. The results suggest that the acute effect of PM_2.5 and O₃ on NAD and CVD mortality in urban Taiyuan was enhanced by increasing temperatures, particularly for the elderly and males. It highlights the importance of reducing PM_2.5 and O₃ exposure in urban areas to reduce the public health burden under the situation of global warming. Full article

Preterm birth (PTB) is a major global public health concern with substantial impacts on neonatal morbidity and mortality. There is a growing body of evidence linking maternal exposure to fine particulate matter (PM_2.5) with PTB, and national birth cohort data from the Middle East remains sparse. We analyzed 3,839,531 singleton live births in Iran from 2013 to 2018. Monthly PM_2.5 concentrations during pregnancy were estimated using validated spatiotemporal models. Associations between prenatal PM_2.5 exposure and multiple PTB subtypes, moderate to late (MPTB), very (VPTB), and extremely preterm birth (EPTB), were assessed using multivariable logistic regression. A 10 μg/m³ increase in PM_2.5 was associated with increased odds of PTB (odds ratio [OR] = 1.048, 95% confidence interval [CI]: 1.044–1.051), MPTB (OR = 1.046, 95% CI: 1.042–1.049), VPTB (OR = 1.059, 95% CI: 1.048–1.070), and EPTB (OR = 1.064, 95% CI: 1.047–1.081), respectively. Age- and trimester-stratified analyses showed greater exposure-related risks among mothers aged 25–34 and during mid-pregnancy. We observed consistent evidence for a J-shaped exposure–risk pattern in overall and subgroup populations, suggesting a PM_2.5 threshold near 40 μg/m³. From 2013 to 2018, 6716 (95% CI: 5336–8678) PTB cases, representing 2.7% (95% CI: 2.2–3.5%) of total PTB, were attributable to PM_2.5 exposure exceeding the WHO first-stage interim target (IT1, 35 μg/m³). Our results suggested improved ambient PM_2.5 quality may substantially reduce PTB burden in Iran. Full article

In this study, the objective is to assess the impacts of NH₃ emissions from mink farming on human health and nature, which are sensitive to atmospheric nitrogen deposition. The impact-pathway approach is applied to follow the emissions from source to impact on human health in Europe (including Denmark) and from source to critical nitrogen load exceedances for NH₃-sensitive nature in Denmark. The Danish Eulerian Hemispheric Model (DEHM) is used for modelling the air pollution concentrations in Europe and nitrogen depositions on land and water surfaces in Denmark arising from NH₃ emissions from mink farming in Denmark. The Economic Valuation of Air (EVA) pollution model system is applied for deriving the health effects and corresponding socio-economic costs in Denmark and Europe arising from the emissions from mink farming. On a local scale in Denmark, the deposition resulting from the NH₃ emissions from mink farming is modelled using the results from the OML-DEP model at a high resolution to derive the critical nitrogen load exceedances for Danish nature areas sensitive to NH₃. From the analysis of the impacts through human exposure to the air pollutants PM_2.5, NO₂, and O₃, it is concluded that in total, ~60 premature deaths annually in Europe, including Denmark, can be attributed to the emissions of NH₃ to the atmosphere from the mink farming sector in Denmark. This corresponds to annual socio-economic costs on the order of EUR 142 million. From the analysis of critical load exceedances, it is concluded that an exceedance of the critical load of nitrogen deposition of ~14,600 hectares (ha) of NH₃-sensitive nature areas in Denmark can be attributed to NH₃ emissions from mink farming. The cost for restoring nature areas of this size, damaged by eutrophication from excess nitrogen deposition, is estimated to be ~EUR 110 million. In 2020, the mink sector in Denmark was shut down in connection with the COVID-19 pandemic. All mink were culled by order of the Danish Government, and now in 2025, the process of determining the level of financial compensation to the farmers is still ongoing. The socio-economic costs following the impacts on human health in Europe and nitrogen-sensitive nature in Denmark of NH₃ emissions from the now non-existing mink sector can therefore be viewed as socio-economic benefits. In this study, these benefits are compared with the expected level of compensation from the Danish Government to the mink farmers, and the conclusion is that the compensation to the mink farmers breaks even with the benefits from reduced NH₃ emissions over a timescale of ~20 years. Full article

Background/Objectives: As older adults spend increasing amounts of time indoors, concerns are rising about the neurological effects of indoor air pollution. This study examined associations between indoor air pollutants and structural brain changes in community-dwelling older adults in Seoul and Incheon, South Korea. A purposive sample of 23 individuals aged ≥65 years was recruited. Internet of Things (IoT)-based devices were installed in participants’ homes to continuously monitor indoor concentrations of PM₁₀, PM_2.5, and CO₂ for over two months. All participants underwent 3T brain magnetic resonance imaging (MRI), and brain structure metrics were analyzed using multiple linear regression models with and without adjustment for estimated total intracranial volume (eTIV). Hierarchical clustering was also performed based on exposure and neuroanatomical characteristics. Brain MRI indicators included cortical surface area, cortical thickness in six regions, and volumes of seven subcortical structures including the hippocampus and amygdala. Higher CO₂ concentrations were significantly associated with lower hippocampal volumes in both hemispheres (left: −2.83, −0.88, −1.02 mm³; right: −3.29, −0.86, −0.99 mm³; p ≤ 0.05). Elevated PM_2.5 levels were associated with reduced bilateral amygdala volume (−283.24 mm³ left; −292.37 mm³ right) and right hippocampal volume (−544.55 mm³; p ≤ 0.05). Cluster analysis showed that, before eTIV adjustment, Group C exhibited the lowest subcortical volumes. After adjustment, Group A showed the smallest cortical surface area, and Group D had the lowest subcortical volumes. These findings suggest that indoor air pollutants, including PM₁₀, PM_2.5, and CO₂, may be associated with structural brain alterations in older adults, supporting the need for age-specific indoor air quality standards and residential monitoring systems. Full article

Carbonaceous aerosols exert significant impacts on human health and climate systems. This study investigates the seasonal variations of carbonaceous components in fine particulate matter (PM_2.5) in Qinhuangdao, a coastal city in northern China, throughout 2023. The mass concentrations of organic carbon (OC) and elemental carbon (EC) averaged 9.44 ± 4.57 μg m⁻³ and 0.84 ± 0.33 μg m⁻³, contributing 26.49 ± 8.74% and 2.81 ± 1.56% to total PM_2.5, respectively. OC exhibited a distinct seasonal trend: winter (12.02 μg m⁻³) > spring (11.96 μg m⁻³) > autumn (8.15 μg m⁻³) > summer (5.71 μg m⁻³), whereas EC followed winter (1.31 μg m⁻³) > autumn (0.73 μg m⁻³) > spring (0.70 μg m⁻³) > summer (0.63 μg m⁻³). Both OC and EC levels were elevated at night compared to daytime. Secondary organic carbon (SOC), estimated via the EC-tractor method, constituted 37.94 ± 14.26% of total OC. A positive correlation between SOC/OC ratios and PM_2.5 concentrations suggests that SOC formation critically influences haze events. In autumn and winter, SOC formation was higher at night, likely driven by aqueous-phase reactions, whereas in summer SOC formation was more pronounced during the day, likely due to enhanced photochemical reactions. Source apportionment analysis revealed that gasoline and diesel vehicles were major contributors to carbonaceous aerosols, accounting for 27.35–29.06% and 14.97–31.83%, respectively. Coal combustion contributed less (10.51–21.55%), potentially due to strict regulations prohibiting raw coal use for domestic heating in surrounding regions. Additionally, fugitive dust was found to have a high contribution to carbonaceous aerosols during spring and summer. Full article

Using data on the children of the respondents who participated in Wave IV (2008) and Wave V (2016–2018) of the National Longitudinal Study of Adolescent to Adult Health, we estimate the effect of long-term exposure to ozone (O₃) and particulate matter 2.5 (PM_2.5) on diagnoses of allergies and asthma in adolescence and young adulthood. Estimates from individual-level fixed-effect models with time-varying controls show that exposure to PM_2.5 and O₃ is associated with higher likelihood of asthma and allergies in females at younger ages (10–12 years old) and allergies in males at older ages (13 years old and above). These findings are novel and contribute to the growing body of literature exploring gender and age differences in susceptibility to asthma and allergies. Full article

Background/Objectives: Alport syndrome (AS) predominantly presents with X-linked inheritance worldwide. However, the epidemiological landscape remains poorly characterized, particularly among ethnic minority groups like the Roma minority in Slovakia. Our study aimed to investigate the inheritance patterns of AS in this region and determine whether a distinct pattern predominates. Methods: Selective genetic screening for pathogenic variants previously occurring in Slovakia was performed. Samples from patients with persistent (familial) hematuria ± hearing loss who had not yet undergone biopsy or genetic testing were analyzed by high-resolution melting analysis. The prevalence of AS per million (pm) population was calculated by adding information on patients with previously confirmed AS. Results: Twenty-five new cases of ARAS, one digenic form, and two cases of XLAS were identified by screening. In total, we collected information on 46 patients with genetically or bioptically confirmed AS in the region of eastern Slovakia, corresponding to a prevalence of 29 pm population. The c.1598G>A (p.Gly533Asp) pathogenic variant of the collagen type IV alpha 4 chain, which follows an autosomal recessive inheritance pattern, was the most prevalent variant that was exclusively confirmed in Roma patients (n = 35), suggesting a founder effect. Within the Roma community, the prevalence of ARAS (the most prevalent inheritance pattern) corresponds to 133 pm of the Roma population, based on midpoint population estimates. Conclusions: Our findings demonstrate a unique genetic profile of AS in the Roma population, characterized by a high prevalence of ARAS, with implications for genetic counseling and screening strategies. Full article

The aim of this study was to investigate the method of estimating actual crop evapotranspiration (ET_cact) in a greenhouse using other measured meteorological parameters when solar radiation (R_s) data are missing. The study estimated ET_cact of greenhouse green peppers by combining solar radiation estimation models with the Penman–Monteith (PM) model and evaluated model performance. The results showed that the prediction accuracy of the temperature-based solar radiation model was higher than the model based on sunshine hours in the Hexi Corridor region. The effect of the insulation cover on the incident solar radiation in the greenhouse is modeled by introducing a ramp function. In terms of crop coefficients (K_cb), the initial K_cb value of green peppers in the 2023 growing season was generally consistent with the updated FAO-56 standard values, whereas the initial K_cb values (0.17) were higher than the standard values in the 2023–2024 growing season. During the two growing seasons, the mid-stage K_cb values were 1.01 in the 2023 growing season and 0.82 in the 2023–2024 growing season. The study also found that PM–RT4, PM–RT5, and PM–RT6 models were all able to accurately predict the ET_cact of greenhouse green peppers during the 2023 growing season. The PM–RT4 model performed well in both growing seasons, with R² = 0.8101 in the 2023 growing season and R² = 0.7561 in the 2023–2024 growing season. Our research supports the PM–RT4 model as appropriate to estimate green pepper actual evapotranspiration in Gobi solar greenhouses (GSGs) and may be further used to improve irrigation scheduling for green peppers grown in GSGs. Full article

Ambient air pollutants (APs) are associated with increased chronic kidney disease (CKD) risk in general populations, but their renal impact on HIV/AIDS patients remains understudied. This dynamic cohort included 7981 HIV/AIDS patients without baseline kidney disease from Wuhan and Zhenjiang, followed every 6 months with fasting blood tests to assess the triglyceride-glucose (TyG) index and estimated glomerular filtration rate (eGFR). Monthly average exposures to six APs were estimated from geocoded residential addresses. Modified Poisson regression models were used to assess associations between cumulative AP exposure and CKD incidence, with mediation analysis conducted to explore the potential role of the TyG index. Weighted quantile sum regression was applied to evaluate the joint effects of six APs. During the follow-up period, 168 new cases of CKD were identified. Each interquartile range increase in PM_2.5, PM₁₀, and SO₂ corresponded to a 16.5%, 18.9%, and 9.7% higher CKD risk, respectively, with the TyG index mediating 10.21%, 9.16%, and 5.14% of these associations. PM_2.5 demonstrated the highest attribution weight (44.4%) for CKD risk elevation in mixed-exposure models. Chronic ambient AP exposure, particularly PM_2.5, synergistically elevates CKD risk in HIV/AIDS patients with glucolipid dysregulation potentially being involved, necessitating targeted air quality policies to mitigate AP impacts on this vulnerable population. Full article

In arid and semi-arid climates, where water scarcity is a persistent challenge, accurately estimating reference evapotranspiration (ET) becomes essential for sustainable water management and agricultural planning. The objectives of this study are to compare hourly ET among P–M ASCE, P–M FAO, and P–M KSA mathematical models. In addition to the accuracy assessment of daily ET derived from hourly timestep calculations for the P–M ASCE, P–M FAO, and P–M KSA. To achieve these goals, a total of 525,600-min data points from the Riyadh region, KSA, were used to compute the reference ET at multiple temporal resolutions: hourly, daily, hourly averaged over 24 h, and daily as the sum of 24 h values, across all selected Penman–Monteith (P–M) models. For hourly investigation, the comparison between reference ET computed as average hourly values and as daily/24 h values revealed statistically and practically significant differences. The Wilcoxon test confirmed a statistically significant difference (p < 0.0001) with R² of 94.75% for ASCE, 94.87% for KSA at h_plt = 50 cm, 92.41% for FAO, and 92.44% for KSA at h_plt = 12 cm. For daily investigation, comparing the sum of 24 h ET computations to daily ET measurements revealed an underestimation of daily ET values. The Wilcoxon test confirmed a statistically significant difference (p < 0.0001), with R² exceeding 90% for all studied reference ET models. This comprehensive approach enabled a rigorous evaluation of reference ET dynamics under hyper-arid climatic conditions, which are characteristic of central Saudi Arabia. The findings contribute to the growing body of literature emphasizing the importance of high-frequency meteorological data for improving ET estimation accuracy in arid and semi-arid regions. Full article

Soil fugitive dust (SFD) emissions pose a significant threat to both human health and the environment, highlighting the need for accurate and reliable estimation and assessment in the desert regions of northwest China. This study used climate, soil, and vegetation data from Bayingolin Prefecture (2001–2022) and applied the WEQ model to analyze temporal and spatial variations in total suspended particulate (TSP), PM₁₀, and PM_2.5 emissions and their driving factors. The region exhibited high emission factors for TSP, PM₁₀, and PM_2.5, averaging 55.46 t km⁻² a⁻¹, 27.73 t km⁻² a⁻¹, and 4.14 t km⁻² a⁻¹, respectively, with pronounced spatial heterogeneity and the highest values observed in Yuli, Qiemo, and Ruoqiang. The annual average emissions of TSP, PM₁₀, and PM_2.5 were 3.23 × 10⁷ t, 1.61 × 10⁷ t, and 2.41 × 10⁶ t, respectively. Bare land was the dominant source, contributing 72.55% of TSP emissions. Both total emissions and emission factors showed an overall upward trend, reaching their lowest point around 2012, followed by significant increases in most counties during 2012–2022. Annual precipitation, wind speed, and temperature were identified as the primary climatic drivers of soil dust emissions across all counties, and their influences exhibited pronounced spatial heterogeneity in Bazhou. In Ruoqiang, Bohu, Korla, and Qiemo, dust emissions are mainly limited by precipitation, although dry conditions and sparse vegetation can amplify the role of wind. In Heshuo, Hejing, and Yanqi, stable vegetation helps to lessen wind’s impact. In Yuli, wind speed and temperature are the main drivers, whereas in Luntai, precipitation and temperature are both important constraints. These findings highlight the need to consider emission intensity, land use, or surface condition changes, and the potential benefits of increasing vegetation cover in severely desertified areas when formulating regional dust mitigation strategies. Full article

Ultrahigh resolution fine particulate matter (PM_2.5) mass concentration remote sensing products are crucial for atmospheric environmental monitoring, pollution source verification, health exposure risk assessment, and other fine-scale applications in urban environments. This study developed an ultrahigh resolution retrieval algorithm to estimate 30 m resolution PM_2.5 mass concentrations over urban areas from Landsat-8 and Sentinel-2A/B satellite measurements. The algorithm utilized aerosol optical depth (AOD) products retrieved from the Landsat-8 OLI and Sentinel-2 MSI measurements from 2017 to 2020, combined with multi-source auxiliary data to establish a PM_2.5-AOD relationship model across China. The results showed an overall high coefficient of determination (R²) of 0.82 and 0.76 for the model training accuracy based on samples and stations, respectively. The model prediction accuracy in Beijing and Wuhan reached R² values of 0.86 and 0.85. Applications in both cities demonstrated that ultrahigh resolution PM_2.5 has significant advantages in resolving fine-scale spatial patterns of urban air pollution and pinpointing pollution hotspots. Furthermore, an analysis of point source pollution at a typical heavy pollution emission enterprise confirmed that ultrahigh spatial resolution PM_2.5 can accurately identify the diffusion trend of point source pollution, providing fundamental data support for refined monitoring of urban air pollution and air pollution prevention and control. Full article

This study investigates the health impacts of air pollution in the Greater Athens Area (GAA), Greece, by estimating the Relative Risk (RR) of hospital admissions (HA) for cardiovascular (CVD) and respiratory diseases (RD) from 2018 to 2020. The analysis focuses on daily exceedances of key air pollutants—PM₁₀, O₃, and NO₂—based on the “Fair” threshold and above, as defined by the European Union Air Quality Index (EU AQI). Data from ten monitoring stations operated by the Ministry of Environment and Energy were spatially matched with six hospitals across the GAA. A Distributed Lag Non-linear Model (DLNM) was employed to capture both the delayed and non-linear exposure–response (ER) relationships between pollutant exceedances and daily HA. Additionally, the synergistic effects of pollutant interactions were assessed to provide a more comprehensive understanding of cumulative health risks. The combined exposure term showed a peak RR of 1.49 (95% CI: 0.79–2.78), indicating a notable amplification of risk when multiple pollutants exceed thresholds simultaneously. The study utilizes R for data processing and statistical modeling. Findings aim to inform public health strategies by identifying critical exposure thresholds and time-lagged effects, ultimately supporting targeted interventions in urban environments experiencing air quality challenges. Full article

Clean and safe air quality is essential for public health, yet particulate matter (PM) significantly degrades air quality and poses serious health risks. The Gulf Cooperation Council (GCC) countries are particularly vulnerable to frequent and intense dust storms due to their vast desert landscapes. This study presents the first health risk assessment of carcinogenic and non-carcinogenic risks associated with exposure to PM2.5 and PM10 bound heavy metals and polycyclic aromatic hydrocarbons (PAHs) based on air quality data collected during the years of 2016–2018 near Dubai International Airport and Abu Dhabi International Airport. The results reveal no significant carcinogenic risks for lead (Pb), cobalt (Co), nickel (Ni), and chromium (Cr). Additionally, AI-based regression analysis was applied to time-series dust monitoring data to enhance predictive capabilities in environmental monitoring systems. The estimated incremental lifetime cancer risk (ILCR) from PAH exposure exceeded the acceptable threshold (10⁻⁶) in several samples at both locations. The relationship between visibility and key environmental variables—PM1, PM2.5, PM10, total suspended particles (TSPs), wind speed, air pressure, and air temperature—was modeled using three machine learning algorithms: linear regression, support vector machine (SVM) with a radial basis function (RBF) kernel, and artificial neural networks (ANNs). Among these, SVM with an RBF kernel showed the highest accuracy in predicting visibility, effectively integrating meteorological data and particulate matter variables. These findings highlight the potential of machine learning models for environmental monitoring and the need for continued assessments of air quality and its health implications in the region. Full article