Search Results (3,976)

Traffic-related air pollution (TRAP) is known to contribute to oxidative stress in the central nervous system (CNS) and has been linked to increased risk of Alzheimer’s disease (AD). Alterations in the renin–angiotensin system (RAS), specifically increased angiotensin II (Ang II) signaling via the angiotensin II type 1 (AT₁) receptor, are implicated in increased oxidative stress in the CNS via activation of NADPH oxidase (NOX). As exposure to TRAP may further elevate AD risk, we investigated whether exposure to inhaled mixed gasoline and diesel vehicle emissions (MVE) promotes RAS-dependent expression of factors that contribute to AD pathophysiology in an apolipoprotein E-deficient (ApoE^−/−) mouse model. Male ApoE^−/− mice (6–8 weeks old) on a high-fat diet were treated with either an ACE inhibitor (captopril, 4 mg/kg/day) or water and exposed to filtered air (FA) or MVE (200 µg PM/m³) for 30 days. MVE exposure elevated plasma Ang II, inflammation, and oxidative stress in the hippocampus, associated with increased levels of Aph-1 homolog B (APH1B), a gamma-secretase subunit, and beta-secretase 1 (BACE1), involved in Aβ production. Each of these endpoints was normalized with ACEi treatment. These findings indicate that TRAP exposure in ApoE^−/− mice drives a RAS- and NOX-dependent oxidative and inflammatory response and shifts Aβ processing towards an amyloidogenic profile before overt Aβ deposition, suggesting a potential therapeutic approach for air pollution-induced AD risk. Full article

(1) Background: Urban traffic micro-environments show strong spatial and temporal variability. Short and intensive campaigns remain a practical approach for understanding exposure patterns in complex environments, but they need clear and interpretable summaries that are not limited to simple site or time segmentation. (2) Methods: We carried out a multi-site campaign across five traffic-affected micro-environments, where measurements covered several pollutants, gases, and meteorological variables. A machine learning framework was introduced to learn interpretable operational regimes as recurring multivariate states using clustering with stability checks, and then we evaluated their added explanatory value and cross-site transfer using a strict site hold-out design to avoid information leakage. (3) Results: Five regimes were identified, representing combinations of emission intensity and ventilation strength. Incorporating regime information increased the explanatory power of simple NO₂ models and allowed the imputation of missing H₂S day using regime-aware random forest with an $R^2$ near 0.97. Regime labels remained identifiable using reduced sensor sets, while cross-site forecasting transferred well for NO₂ but was limited for PM, indicating stronger local effects for particles. (4) Conclusions: Operational-regime learning can transform short multivariate campaigns into practical and interpretable summaries of urban air pollution, while supporting data recovery and cautious model transfer. Full article

Public health impacts of non-optimal temperatures and air pollution have received insufficient attention in Southeast Europe, one of the most air-polluted regions in Europe, simultaneously pressured by climate change. This study employed a multimodal approach to characterize the microclimate and air quality and conduct a health impact assessment in the three biggest cities in Bulgaria. Simulation of atmospheric thermo-hydrodynamics and assessment of urban microclimate relied on the Weather Research and Forecasting model. Concentrations of fine particulate matter (PM_2.5) and nitrogen dioxide (NO₂) were calculated with a land-use regression model. Ischemic heart disease (IHD) hospital admissions were linked to daily measurements at background air quality stations. The results showed declining trends in PM_2.5 but persistent levels of NO₂, especially in Sofia and Plovdiv. Distributed lag nonlinear models revealed that, in Sofia and Plovdiv, PM_2.5 was associated with IHD hospitalizations, with a fifth of cases in Sofia attributable to PM_2.5. For NO₂, an increased risk was observed only in Sofia. In Sofia, the risk of IHD was increased at cold temperatures, while both high and low temperatures were associated with IHD in Plovdiv and Varna. Short-term effects were observed in response to heat, while the effects of cold weather took up to several weeks to become apparent. These findings highlight the complexity of exposure–health interactions and emphasize the need for integrated policies addressing traffic emissions, urban design, and disease burden. Full article

The composition of air pollutants in industrial complexes differs from that of general urban areas, often containing more hazardous substances that pose significant health risks to both workers and residents nearby. In this study, PM_2.5 and its 29 chemical components (eight ions, two carbon species, and 19 trace elements) were measured and analyzed at five monitoring sites adjacent to the Yeosu and Gwangyang industrial complexes from August 2020 to December 2024. Chemical characterization and source identification were conducted. The average PM_2.5 concentration was 18.63 ± 9.71 μg/m³, with notably higher levels observed during winter and spring. A low correlation (R = 0.56) between elemental carbon (EC) and organic carbon (OC) suggests a dominance of secondary aerosols. The charge balance analysis of [NH₄⁺] with [SO₄²⁻], [NO₃⁻], and [Cl⁻] showed slopes below the 1:1 line, indicating that NH₄⁺ is capable of neutralizing these anions. Positive matrix factorization (PMF) identified eight contributing sources—biomass burning (10.4%), sea salt (11.8%), suspended particles (7.1%), industrial sources (4.6%), Asian dust (5.2%), steel industry (21.8%), secondary nitrate (16.4%), and secondary sulfate (22.7%). These findings provide valuable insights for the development of targeted mitigation strategies and the establishment of effective emission control policies in industrial regions. Full article

The main objective of this research was to evaluate the seasonal variability of PM₁₀-bound polycyclic aromatic hydrocarbons (PAHs), their sources, and analyse their health impacts We confirmduring the COVID-19 pandemic period. The chemical composition of PM₁₀ in terms of PAH content was carried out using the gas chromatography-mass spectrometry (GC-MS) technique. PM₁₀ samples were collected in Krakow from 2020 to 2021. A total of 92 samples of particulate matter (PM₁₀ fraction) were analysed. The analyses contained 16 basic PAHs identified by the United States Environmental Protection Agency (U.S. EPA) as the most harmful. The information obtained on the concentrations of PAHs was used to determine the profiles of pollution sources, exposure profiles, and the values of toxic equivalency factors recommended by the EPA: mutagenic equivalent to B[a]P (ang. mutagenic equivalent, MEQ), toxic equivalent to B[a]P (ang. toxic equivalent, TEQ), and carcinogenic equivalent to 2,3,7,8-tetrachlorodibenzo-p-dioxin (ang. carcinogenic equivalent, CEQ). In Kraków, heavy PAHs accounted for over 90% of the total PAHs detected in the PM₁₀ samples. In addition, air trajectory frequency analysis was performed to obtain information on the possibility of transporting pollutants from selected areas in the vicinity of the studied site. Interpreting the trajectory results provided information on the nature of air pollution sources. Analysis of Kraków’s air mass trajectory showed that the highest daily concentration of PM₁₀ in the air flow was from the southwest and east for days. Full article

PM_2.5 pollution has become one of the major environmental issues in Shandong Province in recent years. High concentrations of PM_2.5 not only reduce atmospheric visibility but also induce respiratory and cardiovascular diseases, and significantly increase health risks. Source apportionment of PM_2.5 is important for policy makers to determine control strategies. This study analyzed regional and sectoral PM_2.5 sources across 17 Shandong cities during the 2017–2018 winter heating season, which is selected because it is representative of severe air pollution with an average PM_2.5 of 65.75 μg/m³ and hourly peak exceeding 250 μg/m³. This air pollution episode aligned with key control policies, where seven major cities implemented steel capacity reduction and coal-to-gas/electric heating, as a baseline for evaluating emission reduction effectiveness. The particulate matter source apportionment technology in the Comprehensive Air Quality Model with extensions (CAMx) was applied to simulate the source contributions to PM_2.5 in 17 cities from different regions and sectors including industry, residence, transportation, and coal-burning power plants. The meteorological fields required for the CAMx model were generated using the Weather Research and Forecasting (WRF) model. The results showed that all cities besides Dezhou city in Shandong Province contributed PM_2.5 locally, varying from 39% to 53%. The emissions from Hebei province have a large impact on the PM_2.5 concentrations in Shandong Province. The non-local industrial and residential sources in Shandong Province accounted for the prominent proportion of local PM_2.5 in all cities. The contribution of non-local industrial sources to PM_2.5 in Heze City was up to 56.99%. As for Zibo City, the largest contribution of PM_2.5 was from non-local residential sources, around 56%. Additionally, the local industrial and residential sources in Jinan and Rizhao cities had relatively more contributions to the local PM_2.5 concentrations compared to the other cities in Shandong Province. Finally, the emission reduction effects were evaluated by applying different reduction ratios of local industrial and transportation sources, with decreases in PM_2.5 concentrations ranging from 0.2 to 26 µg/m³ in each city. Full article

Air pollution has been one of the major threats to public health. The study aimed to determine latent patterns of geographical distribution of health-related air pollutants across the USA and to evaluate real-world cumulative effects of these patterns on public health metrics. It was an ecological study using county-level data on the concentrations of 12 air pollutants over 20 years. Latent class analysis was used to identify the common clusters of life expectancy-associated air pollutants based on their concentration characteristics in the final counties studied (n = 699). Multivariate linear regression analyses were then applied to assess the relationship between the LCA-derived clusters and health measurements with confounding adjustment. We found that PM_2.5 mass, PM₁₀ speciation, and NONO_xNO_y (the reactive nitrogen species) were associated with life expectancy and thus were included in LCA. Among five identified clusters, the one with a more severe pollutant profile was associated with a decreasing life expectancy, an increasing mortality risk among middle-aged and elderly populations (≥45 years), and an increasing mortality rate caused by chronic respiratory conditions, cardiovascular diseases, and neoplasms. Our study brings new perspectives on real-world geographical patterns of air pollution to explain health disparities across the USA. Full article

To date, dust storms and haze episodes have rarely been compared with pollution characteristics of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) and particulate matter, as well as human health risks due to a lack of efficient data. In this study, we selected dust storms and haze episodes in East China during 2023, monitored the concentrations of PCDD/Fs in ambient air, further revealed the main characteristic variations in PCDD/Fs toxic equivalent (TEQ) concentration and congener distribution in ambient air, and assessed the human health risk posed by dust storms and haze episodes. The results show that the TEQ concentration of PCDD/Fs in ambient air was 147.6 fg-TEQ/m³ in haze episodes compared with 48.7 fg-TEQ/m³ for dust storms and 25.8 fg-TEQ/m³ for a good weather day. This indicates that the concentration for PCDD/Fs and PM_2.5 in haze episodes was 3.03 times and 0.733 times, respectively, compared with dust storms. Moreover, the variations for particulate matter of air pollution during 2022–2023, as well as the relationship between PCDD/Fs and PM_2.5 in East China was also systematically revealed. The results reveal that the concentration of PM_2.5 shows a positive correlation with PCDD/Fs. Furthermore, the human health risk of dust storms was also compared with haze episodes. Accordingly, this study could fill the knowledge gap of dust storms and haze episodes on the transmission of PCDD/Fs in the ambient air of East China and provide a scientific reference for monitoring and early warning of PCDD/Fs. Full article

Air pollution represents one of the foremost environmental and public health challenges of the twenty-first century, with differentiated impacts according to the socio-economic and urban conditions of affected populations. It therefore remains necessary to integrate social and spatial factors into air quality assessment, going beyond purely physicochemical approaches. This study aims to develop a socio-environmental index to assess air quality (SAQI) based on particulate matter (PM) concentrations in two urban areas of Bogota (Colombia). The methodology is structured in three phases: (i) a global review of reported socio-environmental indices over the past decade, (ii) construction of the index via integration of environmental and socio-economic variables collected in the locality of Kennedy, and (iii) comparative validation of the index in the locality of Barrios Unidos to assess robustness and transferability. The structure of the proposed SAQI assigns 45% weight to the socio-economic dimension and 55% to environmental exposure (PM_2.5 and PM₁₀ concentrations). During the development phase in Kennedy, annual PM_2.5 concentrations were systematically found to exceed World Health Organization guidelines by factors ranging between 4.0 and 5.7 (24.5 ± 2.89 µg/m³). The comparative application in Barrios Unidos (SAQI = 12, “good”) and Kennedy (SAQI = 21.8, “acceptable”) revealed an 81.5% socio-environmental gap driven by PM concentrations up to 49.8% higher and greater social vulnerability in Kennedy. The methodological divergence compared to the local technical index—IBOCA (45.2 in Kennedy)—underscores the added value of the SAQI developed to capture effective socio-environmental risk. The SAQI developed in this work is a potential decision-making tool that guides public policies toward fairer and more equitable air quality management in urban areas of developing countries. Full article

Chronic obstructive pulmonary disease (COPD) is strongly associated with the inhalation of harmful particulate matter in ambient air. This study examined 786,290 COPD-related hospital admissions among patients aged 45–64 in Istanbul from 2013 to 2015, using a Generalized Linear Model (GLM) with meteorological variables included as covariates and air pollutant effects evaluated across lag days 0–9. Daily mean concentrations of PM₁₀, PM_2.5, and NO₂ were used as air pollution indicators, while average temperature and relative humidity were considered as meteorological variables. Relative risk (RR) and excess relative risk (ERR) estimates were calculated for a 10 μg/m³ increase in pollutant concentrations across the lag period. Significant associations were found between air pollution and COPD-related hospital admissions in overall analyses as well as seasonal assessments, especially for temperature-related effects. A 10 μg/m³ increase in PM_2.5 was associated with an ERR of 1.26% in females and 1.07% in males at lag 1, while NO₂ exposure showed ERRs of 1.31% in males and 1.30% in females. The effects of PM₁₀ were comparatively smaller, peaking at about 1.13% ERR at lag 5. Stronger associations were observed in both summer and winter seasons. PM_2.5 demonstrated the highest overall impact, particularly among females, with an excess risk of 1.7%. Pollutant effects were more pronounced at ambient temperatures around 0 °C and 25 °C. Full article

Cropland fires are an important source of air pollution emissions and have a significant impact on regional air quality and human health. Although straw-burning ban policies have been implemented to mitigate emissions, the dynamics of PM_2.5 emissions from cropland fires under such stringent regulations are still not fully understood. This study utilizes PM_2.5 emission data from the Global Fire Assimilation System (GFAS), land-cover data from CLCD, and PM_2.5 concentration data from ChinaHighAirPollutants (CHAP) to examine the dynamic evolution of PM_2.5 emissions from cropland fires under straw-burning ban policies across China and to assess their environmental impacts. The results show that the 2013 Air Pollution Prevention and Control Action Plan initiated the development of provincial straw-burning ban policies. These policies resulted in a drastic reduction in PM_2.5 emissions from cropland fires in North China (NC), with a 65% decrease in 2022 compared to the 2012 peak. In contrast, a notable lagged effect was observed in Northeast China (NEC), where the increasing trend of PM_2.5 emissions was not reversed until 2017. By 2022, emissions in this region had declined by 53% and 45% compared to the 2015 peak and 2017 sub-peak, respectively. Moreover, significant regional differences were found in the environmental impacts of PM_2.5 emissions from cropland fires, with strong effects during summer in NC and during spring and autumn in NEC. This study provides empirical support for understanding the environmental impacts of cropland fires in key regions of China and offers critical insights to inform and refine related pollution control policies. Full article

This study evaluates the effectiveness of air pollution control measures in Xi’an, China, by investigating long-term changes in the concentrations, optical properties, and sources of black carbon (BC) and brown carbon (BrC). Wintertime observations of PM_2.5 carbonaceous aerosols were conducted over multiple years using a continuous Aethalometer. The data were analyzed using advanced aethalometer models, potential source contribution function (PSCF) analysis, and generalized additive models (GAMs) to deconstruct emission sources and formation pathways. Our results revealed a significant decrease in the mass concentration and light absorption coefficient of BC (b_abs-BC) between the earlier and later study periods, indicating successful emission reductions. In contrast, the light absorption from BrC (b_abs-BrC) remained relatively stable, suggesting persistent and distinct emission sources. Source apportionment analysis demonstrated a temporal shift in dominant regional influences, from biomass burning in the initial years to coal combustion in later years. In addition, GAMs showed that the primary driver for liquid fuel-derived BC transitioned from gasoline to diesel vehicle emissions. For solid fuels, residential coal combustion consistently contributed over 50% of BC, highlighting that improvements in coal combustion technology were effective in reducing BC emissions. Furthermore, a substantial fraction of BrC was increased, with nocturnal peaks associated with high relative humidity, emphasizing the aqueous-phase formation influences. Collectively, these findings demonstrated that although certain control strategies successfully mitigated BC, the persistent challenge of BrC pollution necessitates targeted measures addressing secondary formation and primary fossil fuel sources. Full article

Following the implementation of the Shanghai Clean Air Act, this study investigates the evolution of air pollution in central Shanghai (Putuo District) by analyzing continuous monitoring data (2016–2020) and chemical speciation of particulate matter (2017–2018). The results confirm a transition toward a “low exceedance rate and low background concentration” regime. However, short-term exceedance episodes persist, generally occurring in winter and spring, with significantly amplified diurnal variations on exceedance days. Distinct patterns emerged between PM fractions: PM₁₀ exceedances were characterized by a single morning peak linked to traffic-induced coarse particles, while PM_2.5 exceedances showed synchronized diurnal peaks with NO₂, suggesting a stronger contribution from vehicle exhaust. Source apportionment revealed that mineral components (21.61%) and organic matter (OM, 21.02%) dominated in PM₁₀, implicating construction and road dust. In contrast, PM_2.5 was primarily composed of OM (26.73%) and secondary inorganic ions (dominated by nitrate), highlighting the greater importance of secondary formation. The findings underscore that sustained PM_2.5 mitigation requires targeted control of gasoline vehicle emissions and gaseous precursors. Full article

Air pollution from lignite combustion represents a major environmental and public health concern, particularly for cardiovascular disease. This study investigated the relationship between ambient air pollution and hospital admissions for Acute Coronary Syndromes (ACS) and Atrial Fibrillation (AF) in Western Macedonia, Greece—a region historically dominated by lignite mining and power generation. Air quality data for PM₁₀, SO₂, and NO_x from 2011–2014 and 2021 were analyzed alongside hospital admission records from four regional hospitals (Kozani, Ptolemaida, Florina, Grevena). Spatial analyses revealed significantly higher pollutant concentrations and cardiovascular admissions in high-exposure areas near power plants compared with the control area. Temporal analyses demonstrated a pronounced decline in pollutant levels between 2014 and 2021, coinciding with lignite phase-out and accompanied by a marked reduction in ACS and AF hospitalizations, particularly in the high-exposure areas of Ptolemaida and Florina. Correlation analyses indicated modest but significant positive associations between monthly pollutant concentrations and cardiovascular admissions. These findings provide real-world evidence that reductions in air pollution following lignite decommissioning were associated with improved cardiovascular outcomes. The study underscores the medical importance of air quality improvement and highlights emission reduction as a critical strategy for cardiovascular disease prevention in transitioning energy regions. Full article

This study evaluates the performance of two real-time fluorescence-based bioaerosol sensors, the WIBS-NEO and IBAC-2, operating in urban Dublin, Ireland, and assesses the influence of different meteorological and pollution parameters on their outputs. This was done by comparing particle sensor data to meteorological variables and air quality metrics. Over the 41-day campaign, Urticaceae pollen and Cladosporium spores were the dominant bioaerosols recorded, comprising 78% and 66% of total pollen and fungal spore concentrations, respectively. Correlation analyses revealed several significant variables: fluorescent BC-type particles (>8 μm) detected by WIBS-NEO strongly correlated with pollen concentrations (r = 0.84 after excluding high-wind days). For fungal spores, PM₁₀ and grass minimum temperature were the most significant parameters related to variability. Anthropogenic pollutants, particularly NO_X and combustion-related aerosols, were found to correlate with fluorescence signals, especially for smaller particles (<2 μm), underscoring urban detection challenges. Wind trajectory analysis identified the likely source of Urticaceae pollen as northerly green spaces (e.g., Phoenix Park), while Cladosporium spores showed multidirectional transport. Multiple linear regression (MLR) analysis achieved strong correlation (${\mathrm{R}}^2$ = 0.82 for pollen, 0.78 for fungal spores), highlighting the value of incorporating multiple environmental variables to investigate the complex relationships between urban environmental conditions and bioaerosol sensor outputs. Both instruments exhibited operational limitations under the study conditions. The WIBS-NEO outperformed the IBAC-2 in biological discrimination due to its multi-channel single particle fluorescence capabilities. However, operational limitations emerged during higher wind speeds, comparable to moderate breezes (>16.6 km/h), which affected sampling comparability when compared with traditional methods. This study investigates how meteorological conditions and air quality influence bioaerosol detection in an urban environment. The use of MLR techniques to examine the complex relationships between environmental variables and fluorescent sensor outputs may help inform future bioaerosol modelling efforts. Full article