Particulate Matter Concentrations Research Articles

Improvement of the anthropogenic emission rate estimate in Ulaanbaatar, Mongolia, for 2020–21 winter

Ulaanbaatar (UB), the fast-growing capital of Mongolia, is known for its world's worst level of particulate matter (PM) concentrations in winter. However, current anthropogenic emission inventories over the UB are based on data from more than fifteen years ago, and satellite observations are scarce because UB is in high latitudes. During the winter of 2020–21, the first period of the Fine Particle Research Initiative in East Asia considering the National Differences (FRIEND), several times higher concentrations of PM in UB compared to other urban sites in East Asia were observed but not reproduced with a chemical transport model mainly due to the underestimated anthropogenic emissions. Therefore, we devised a method for sequentially adjusting emissions based on the reactivity of PM precursors using ground observations. We scaled emission rates for the inert species (CO, elemental carbon (EC), and organic carbon (OC)) to reproduce their observed ambient concentrations, followed by SO2 to reproduce the concentration of SO42−, which was examined to have the least uncertainty based on the abundance of observed NH3, and finally NO and NH3 for NO3−, and NH4+. This improved estimation is compared to regional inventories for Asia and suggests more than an order of magnitude increase in anthropogenic emissions in UB. Using the improved emission inventory, we were able to successfully reproduce independent observation data on PM2.5 concentrations in UB in December 2021 from the U.S. Embassy. During the campaign period, we found more than 50% of the SO42−, NO3−, and NH4+ increased in UB due to the improvement could travel to Beijing, China (BJ), and about 20% of the SO42− could travel to Noto, Japan (NT), more than 3000 km away. Also, the anthropogenic emissions in UB can effectively increase OC, NO3−, and NH4+ concentrations in BJ when Gobi dust storms occur.

The regulation effect of urban green space on air particulate matter concentration under different matrices in Xi'an city

The regulation effect of urban green space on air particulate matter concentration under different matrices in Xi'an city

Large transboundary health impact of Arctic wildfire smoke

Rapid warming at high latitudes, particularly in Siberia, has led to large wildfires in recent years that cause widespread smoke plumes. These fires lead to substantial deterioration in summer air quality in the region, with a factor 4 increase in summer fine particulate matter (PM2.5) concentrations in parts of Siberia during 1998–2020. Exposure to PM2.5 is associated with increased risk of mortality due to cardiovascular and respiratory disease, and the atmospheric lifetime of PM2.5 means that it can be efficiently transported between regions and nations. We used the Community Earth System Model to quantify the fraction of PM2.5 attributed to high latitude wildfires that occur in the Arctic Council member states and estimated the attributable health impact locally and in neighbouring countries. During 2001–2020 we attribute ~21,000 excess deaths to Arctic Council wildfires on average each year, of which ~8000 occur in countries outside the Arctic Council. Our analysis shows that the health impact of Arctic wildfires decreased during 2001–2020, despite the increase of wildfire-sourced PM2.5, which we suggest is due to a northwards shift in the average latitude of Siberian wildfires, reducing their impact on more densely populated regions.

The Relationship between Indoor and Outdoor Fine Particulate Matter in a High-Rise Building in Chicago Monitored by PurpleAir Sensors

In urban areas like Chicago, daily life extends above ground level due to the prevalence of high-rise buildings where residents and commuters live and work. This study examines the variation in fine particulate matter (PM2.5) concentrations across building stories. PM2.5 levels were measured using PurpleAir sensors, installed between 8 April and 7 May 2023, on floors one, four, six, and nine of an office building in Chicago. Additionally, data were collected from a public outdoor PurpleAir sensor on the fourteenth floor of a condominium located 800 m away. The results show that outdoor PM2.5 concentrations peak at 14 m height, and then decline by 0.11 μg/m3 per meter elevation, especially noticeable from midnight to 8 a.m. under stable atmospheric conditions. Indoor PM2.5 concentrations increase steadily by 0.02 μg/m3 per meter elevation, particularly during peak work hours, likely caused by greater infiltration rates at higher floors. Both outdoor and indoor concentrations peak around noon. We find that indoor and outdoor PM2.5 are positively correlated, with indoor levels consistently remaining lower than outside levels. These findings align with previous research suggesting decreasing outdoor air pollution concentrations with increasing height. The study informs decision-making by community members and policymakers regarding air pollution exposure in urban settings.

Improvement in the Adaptation and Resilience of the Green Areas of Yerevan City to Climate–Ecological Challenges

The services provided by green infrastructures may lead to a decrease in climate-related ecological, social, and health risks, especially in the urban environment. Consequently, the best guarantee to make this environment as safe as possible is to increase the extent of green areas, taking into consideration the functional importance, and climatic–ecological peculiarities of the area. These are also issues for the Republic of Armenia’s (RA) capital Yerevan. There the current conditions of the green areas of Yerevan city do not meet the expected requirements of the climatic–ecological development of urban areas. The green area per capita is 8 m2, which is unevenly distributed within 12 different administrative districts of Yerevan city. The aim of this research was to study the natural climatic and ecological conditions of Yerevan city and the status of the green areas of the city. The eco-biological indicators of the trees and shrubs growing in Yerevan green areas have been assessed, and the more resilient plant species have been singled out. All 12 administrative districts of Yerevan have been mapped and the green area per capita for each administrative district has been calculated. The received data have been combined with health indicators and suggestions have been made to add green areas in Yerevan according to the functional significance and sustainability of shrubby species and to their decorative and phyto-filtration properties. The city has unfavorable climatic conditions. It is located in the northern section of the subtropical climatic zone and has a distinct dry continental climate. Temperatures above +40 °C are typical, while winter is rather cold and sometimes temperatures may drop below −20 °C (in January 2008, it dropped to −27.6 °C). The amount of atmospheric precipitation has reduced by 9%. The city is counted as one of the driest urban areas of the South Caucasus. The other unfavorable ecological conditions are heavy traffic, the city’s open landfill, the concentration of industrial enterprises, large-scale construction works, etc. The atmospheric concentrations of particulate matter (PM), gases and heavy metals have been detected to exceed the permitted limits. In terms of health care, the death cases due to various diseases (acute respiratory, vascular, and cancer) have increased, which requires complex activities to reduce environmental pollution and to improve the microclimate.

Analyzing Air Pollution in Urban Delhi: A Quantitative Assessment of Particulate Matter (PM) Concentrations

Air pollution poses significant challenges to urban environments, with particulate matter (PM) concentrations being a major concern due to their adverse effects on public health and the environment. This research paper aims to quantitatively assess PM concentrations in urban Delhi, focusing on spatial, temporal, and seasonal variations across diverse urban microenvironments. The research design involved mobile air quality monitoring using real-time PM sensors mounted on a vehicle, coupled with Geographic Information System (GIS) analysis to map pollution hotspots and assess correlations with urban features. The key findings of the study reveal significant spatial variability in PM concentrations, with industrial zones and busy intersections emerging as hotspots for pollution. Seasonal variations in PM levels, with elevated concentrations during winter months and lower levels during the monsoon season, underscore the influence of meteorological factors on air quality dynamics. The study also identifies correlations between PM concentrations and respiratory disease cases, highlighting the adverse health effects of air pollution. The implications of these findings extend to air quality management strategies and public health interventions, emphasizing the need for targeted measures to mitigate pollution levels and protect public health in urban environments.

Air pollution and diabetes mellitus: Association and validation in a desert area in China.

Despite the growing evidence pointing to the detrimental effects of air pollution on diabetes mellitus (DM), the relationship remains poorly explored, especially in desert-adjacent areas characterized by high aridity and pollution. We conducted a cross-sectional study with health examination data from over 2.9 million adults in two regions situated in the southern part of the Taklamakan Desert, China. We assessed three-year average concentrations (2018-2020) of particulate matter (PM1, PM2.5, and PM10), carbon monoxide (CO), nitrogen dioxide (NO2), and sulfur dioxide (SO2) through a space-time extra-trees model. After adjusting for various covariates, we employed generalized linear mixed models to evaluate the association between exposure to air pollutants and DM. The odds ratios for DM associated with a 10 µg/m3 increase in PM1, PM2.5, PM10, CO, and NO2 were 1.898 (95% CI: 1.741, 2.070), 1.07 (95% CI: 1.053, 1.086), 1.013 (95% CI: 1.008, 1.018), 1.009 (95% CI: 1.007, 1.011), and 1.337 (95% CI: 1.234, 1.449), respectively. Notably, men, individuals aged ≥50 years, those with lower educational attainment, nonsmokers, and those not engaging in physical exercise displayed more susceptible to the adverse effects of air pollution. Multiple sensitivity analyses confirmed the stability of these findings. Our study provides robust evidence of a correlation between prolonged exposure to air pollution and the prevalence of DM among individuals living in the desert-adjacent areas. This research contributes to the expanding knowledge on the relationship between air pollution exposure and DM prevalence in desert-adjacent areas.

Associations Between Early-Life Adversity, Ambient Air Pollution, and Telomere Length in Children.

Examine the independent associations and interaction between early-life adversity and residential ambient air pollution exposure on relative buccal telomere length (rBTL). Experiences of abuse, neglect, household challenges, and related life events were identified in a cross-sectional sample of children ages 1-11 years (n = 197) using the 17-item Pediatric ACEs and Related Life Event Screener (PEARLS) tool. The PEARLS tool was analyzed both as a total score and across established domains (Maltreatment, Household Challenges, and Social Context). Ground-level fine particulate matter (PM2.5) concentrations were matched to residential locations for the one and twelve months prior to biospecimen collection. We used multivariable linear regression models to examine for independent associations between continuous PM2.5 exposure and PEARLS score/domains with rBTL. Additionally, effect modification by PEARLS scores and domains on associations between PM2.5 exposure and rBTL was examined. Study participants were 47% girls, with mean age = 5.9 years [standard deviation: 3.4] median reported PEARLS score of 2 [interquartile range (IQR): 4], median 12-month prior PM2.5 concentrations of 11.8 μg/m3 [IQR: 2.7], median 1-month prior PM2.5 concentrations of 10.9 μg/m3 [IQR: 5.8], and rBTL of 0.1 [IQR: 0.03]. Mean 12-month prior PM2.5 exposure was inversely associated with rBTL (ß = -0.02, 95% CI: -0.04, -0.01). While reported PEARLS scores and domains were not independently associated with rBTL, we observed a greater decrement in rBTL with increment of average annual PM2.5 as reported Social Context domain items increased (p-interaction<0.05). Our results suggest that adverse Social Context factors may accelerate the association between chronic PM2.5 exposure on telomere shortening during childhood.

Spatiotemporal Patterns of Air Pollutants over the Epidemic Course: A National Study in China

Air pollution has been standing as one of the most pressing global challenges. The changing patterns of air pollutants at different spatial and temporal scales have been substantially studied all over the world, which, however, were intricately disturbed by COVID-19 and subsequent containment measures. Understanding fine-scale changing patterns of air pollutants at different stages over the epidemic’s course is necessary for better identifying region-specific drivers of air pollution and preparing for environmental decision making during future epidemics. Taking China as an example, this study developed a multi-output LightGBM approach to estimate monthly concentrations of the six major air pollutants (i.e., PM2.5, PM10, NO2, SO2, O3, and CO) in China and revealed distinct spatiotemporal patterns for each pollutant over the epidemic’s course. The 5-year period of 2019–2023 was selected to observe changes in the concentrations of air pollutants from the pre-COVID-19 era to the lifting of all containment measures. The performance of our model, assessed by cross-validation R2, demonstrated high accuracy with values of 0.92 for PM2.5, 0.95 for PM10, 0.95 for O3, 0.90 for NO2, 0.79 for SO2, and 0.82 for CO. Notably, there was an improvement in the concentrations of particulate matter, particularly for PM2.5, although PM10 exhibited a rebound in northern regions. The concentrations of SO2 and CO consistently declined across the country over the epidemic’s course (p &lt; 0.001 and p &lt; 0.05, respectively), while O3 concentrations in southern regions experienced a notable increase. Concentrations of air pollutants in the Beijing–Tianjin–Hebei region were effectively controlled and mitigated. The findings of this study provide critical insights into changing trends of air quality during public health emergencies, help guide the development of targeted interventions, and inform policy making aimed at reducing disease burdens associated with air pollution.

Pre-pregnancy ozone and ultrafine particulate matter exposure during second year of life associated with decreased cognitive and adaptive functioning at aged 2–5 years

BackgroundThis study sought to investigate the association of prenatal and early life exposure to a mixture of air pollutants on cognitive and adaptive outcomes separately in children with or without autism spectrum disorder (ASD). MethodsUtilizing data from the CHARGE case-control study (birth years: 2000–2016), we predicted daily air concentrations of NO2, O3, and particulate matter <0.1 μm (PM0.1), between 0.1 and 2.5 μm (PM0.1-2.5), and between 2.5 and 10 μm (PM2.5-10) using chemical transport models with ground-based monitor adjustments. Exposures were evaluated for pre-pregnancy, each trimester, and the first two years of life. Individual and combined effects of pollutants were assessed with Vineland Adaptive Behavior Scales (VABS) and Mullen Scales of Early Learning (MSEL), separately for children with ASD (n = 660) and children without ASD (typically developing (TD) and developmentally delayed (DD) combined; n = 753) using hierarchical Bayesian Kernel Machine Regression (BKMR) models with three groups: PM size fractions (PM0.1, PM0.1-2.5, PM2.5-10), NO2, and O3. ResultsPre-pregnancy Ozone was strongly negatively associated with all scores in the non-ASD group (group posterior inclusion probability (gPIP) = 0.83–1.00). The PM group during year 2 was also strongly negatively associated with all scores in the non-ASD group (gPIP = 0.59–0.93), with PM0.1 driving the group association (conditional PIP (cPIP) = 0.73–0.96). Weaker and less consistent associations were observed between PM0.1-2.5 during pre-pregnancy and ozone during year 1 and VABS scores in the ASD group. ConclusionsThese findings prompt further investigation into ozone and ultrafine PM as potential environmental risk factors for neurodevelopment.

A comprehensive review of urban vegetation as a Nature-based Solution for sustainable management of particulate matter in ambient air.

Air pollution is one of the most pressing environmental threats worldwide, resulting in several health issues such as cardiovascular and respiratory disorders, as well as premature mortality. The harmful effects of air pollution are particularly concerning in urban areas, where mismanaged anthropogenic activities, such as growth in the global population, increase in the number of vehicles, and industrial activities, have led to an increase in the concentration of pollutants in the ambient air. Among air pollutants, particulate matter is responsible for most adverse impacts. Several techniques have been implemented to reduce particulate matter concentrations in the ambient air. However, despite all the threats and awareness, efforts to improve air quality remain inadequate. In recent years, urban vegetation has emerged as an efficient Nature-based Solution for managing environmental air pollution due to its ability to filter air, thereby reducing the atmospheric concentrations of particulate matter. This review characterizes the various mitigation mechanisms for particulate matter by urban vegetation (deposition, dispersion, and modification) and identifies key areas for further improvements within each mechanism. Through a systematic assessment of existing literature, this review also highlights the existing gaps in the present literature that need to be addressed to maximize the utility of urban vegetation in reducing particulate matter levels. In conclusion, the review emphasizes the urgent need for proper air pollution management through urban vegetation by integrating different fields, multiple stakeholders, and policymakers to support better implementation.

Characteristics and health implications of fine particulate matter near urban road site in Islamabad, Pakistan

The escalating issue of air pollution has become a significant concern in urban regions, including Islamabad, Pakistan, due to the rise in air pollutant emissions driven by economic and industrial expansion. To gain a deeper understanding of air pollution, a study was conducted during winter 2022–2023, assessing physical, chemical, and biological factors in Islamabad. The findings revealed that the average concentration of fine particulate matter (PM2.5) was notably greater than the World Health Organization (WHO) guidelines, reaching 133.39 μg/m³. Additionally, the average concentration of bacteria (308.64 CFU/m³) was notably greater than that of fungi (203.55 CFU/m³) throughout the study. Analytical analyses, including SEM-EDS and FTIR, showed that the PM2.5 in Islamabad is composed of various particles such as soot aggregates, coal fly ash, minerals, bio-particles, and some unidentified particles. EF analysis distinguished PM2.5 sources, enhancing understanding of pollutants origin, whereas Spearman's correlation analysis elucidated constituent interactions, further explaining air quality impact. The results from the Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-OES) indicated a gradual increase in the total elemental composition of PM2.5 from autumn to winter, maintaining high levels throughout the winter season. Furthermore, a significant variation was found in the mass concentration of PM2.5 when comparing samples collected in the morning and evening. The study also identified the presence of semi-volatile organic compounds (SVOCs) in PM2.5 samples, including polycyclic aromatic hydrocarbons (PAHs) and phenolic compounds, with notable variations in their concentrations. Utilizing health risk assessment models developed by the US EPA, we estimated the potential health risks associated with PM2.5 exposure, highlighting the urgency of addressing air quality issues. These findings provide valuable insights into the sources and composition of PM2.5 in Islamabad, contributing to a comprehensive understanding of air quality and its potential environmental and health implications.

Distribution and influencing factors of Mycobacterium in rail transit based on metagenomic analysis

With the increasing prevalence of metro systems in urban transportation, there is a growing concern about the microbial pollution risks associated with these systems. To address this issue, this study employs metagenomic sequencing technology to investigate the distribution of Mycobacterium in aerosol samples collected from metro environments. Through the analysis of various environmental factors, insights into the factors influencing Mycobacterium contamination in metro systems are provided, aiming to offer evidence to support prevention and control measures against such pollution. In this study, a total of 90 species of Mycobacterium were detected in aerosol samples with a positivity rate of 30.77% including Mycobacterium tuberculosis that accounts for over 90% of the total abundance, as well as common opportunistic pathogens such as Mycobacterium gordonae, Mycobacterium avium, Mycobacterium intracellular, and Mycobacterium lentiflavum. Through correlation analysis, it was found that the distribution of Mycobacterium is related to season, temperature, CO2, PM1, PM2.5, and PM10 concentrations. In conclusion, it is recommended to adopt measures to control temperature and airborne concentrations of CO2 and particulate matter (PM1, PM2.5, and PM10) in order to minimize the risk of Mycobacterium contamination in metro systems. By implementing these recommendations, the prevention and control of Mycobacterium pollution can be effectively enhanced in the context of urban metros.

Particle emissions from heated tobacco products.

This study determines the particle emissions from five heated tobacco products (HTPs). An aethalometer is used for the determination of black carbon (BC) and an aerosol monitor for total particulate matter (PM) concentration and also PM fractions (1, 2.5, 4, and 10 μm) in the mainstream emissions of 5 HTPs: IQOS, LIL, PULZE, ILUMA, and GLO. Fifteen different flavors were used, five sticks per flavor, which were smoked using a peristaltic pump under both ISO and Canadian smoking regimes. The method repeatability was determined using 15 sticks of one flavor for each brand for each smoking regime. All HTPs emit particles, and more than 99.7% of the particles emitted are smaller than 1 μm. Both BC and PM emissions show quite low repeatability. Particle emissions increase in relation to the heating temperature and the intensity smoking regime, and are depending on the flavor used. BC corresponds to a small percentage of total PM. Although HTPs are promoted as products of reduced risk compared to conventional cigarettes, high particle concentrations are detected in their emissions, depending on the smoking regime, the flavor used, and the operation parameters. PM emissions vary significantly between different brands under the ISO smoking regime, probably due to the heating temperature. In contrast, PM emissions under the Canadian smoking regime do not vary significantly between different brands. This could probably be attributed to the fact that increased puff frequency does not allow the device to cool down between puffs, resulting in an increase in PM emissions for all the brands, but not dependent on the maximum heating temperature of the device. BC emissions only consist of a very small fraction of PM and do not vary significantly between different brands under both smoking regimes.

Analysis of Gas Flow and PM Movement Characteristics Inside Diesel Particulate Filter Channel

Based on experimental data from engine after-treatment tests, the diesel particulate filter (DPF) microscopic channel model was constructed using UG, and the accumulation of particulate matter (PM) in the deep bed filter layer and carbon deposit layer was analyzed through computational fluid dynamics (CFD). A comprehensive study was conducted on the exhaust gas flow characteristics and PM movement within the DPF channel, and focus on the effects of PM distribution type on capture and regeneration characteristics. The results show that with the increase in particle size in the exhaust, the distribution of PM concentration along the axial position of the channel shows a trend of gradually shifting from 0.2 to 0.25m (rear section) to 0.125 to 0.2m (front section). In particular, PM with 1 μm particle size has a large motion inertia, which is easy to move out of the airflow and deposit in the middle part of the channel. For PM in the front and middle sections of the channel, the airflow obstruction is relatively small, but the heat transfer loss is large, which is not beneficial for PM regeneration in the rear section. Therefore, with the distribution of LID, PD-1, and PD-2, the regeneration efficiency is relatively low, at 50.84%, 55.01%, and 54.59%, respectively.

Size-resolved water-soluble organic carbon and its significant contribution to aerosol liquid water

Size-segregated aerosols collected in Beijing from 2021 to 2022 were used to investigate the contribution of organic aerosols to the aerosol liquid water content (ALWC), the influencing factors of ALWC, and the concentrations and size distribution characteristics of water-soluble organic carbon (WSOC) after clean air actions. The results showed that the concentration of WSOC in particulate matter (PM)1.8 was 3.52 ± 2.43 μg/m3 during the sampling period. Obvious changes were observed in the size distribution of WSOC after clean air actions, which may be attributed to the enhancement of atmospheric oxidation capacity and the decrease in PM concentration. The contribution of organic aerosols to the ALWC in fine PM was 18.1 % during the sampling period, which was more significant at lower particles concentration and smaller particle size ranges. The ambient relative humidity (RH) and the ratio of NO3−/SO42− had an apparent influence on ALWC. The continuous increase in the nitrate proportion significantly reduced the deliquescence point of the aerosols, making them prone to hygroscopic growth at lower RH. Analysis of the relation among nitrogen oxidation ratio (sulfur oxidation ratio), ALWC and PM1.8 mass concentrations suggests that organic matter has a significant effect on the formation of secondary inorganic aerosols in the initial phase of pollution formation and plays a crucial role in aerosol pollution formation in Beijing. These results are conducive to understanding the formation mechanism of aerosols and provide scientific data and theoretical support for the formulation of more effective emission-reduction measures.

Response of warm season secondary pollutants to emissions and meteorology in the North China Plain region during 2018–2022

Air quality in China has continued to improve since 2013, although severe pollution events still occur over the North China Plain (NCP). It is noticeable that contributions from secondary pollutants have increased, but understanding of their formation and variations with changing emissions and meteorological conditions remains limited. In this study, the warm season of May to September from 2018 to 2022 was selected to explore the response of secondary pollutants to meteorology and emissions using the Community Multi-scale Air Quality model (CMAQ). Fine particulate matter (PM2.5) concentrations over the NCP decreased significantly by 31%–37% from 2018 to 2022, while ozone (O3) and nitrogen dioxide (NO2) generally showed decreasing trends by 1% and 0.5% per year, respectively. Secondary inorganic aerosol (including sulfate, nitrate, and ammonium) and secondary organic aerosol (SOA) also decreased significantly, by 9% and 6% per year, respectively. The results showed that emissions contributed 96% to the decreases in PM2.5 concentrations, while O3 fluctuated due to meteorological changes. Although the decreases in sulfate and ammonium were mainly associated with emission reductions, that of nitrate was more sensitive to meteorological changes. Meteorological and emission changes were similarly important for the overall decrease in SOA, with anthropogenic SOA being more sensitive to emissions control, while biogenic SOA was more easily attributed to meteorological changes. This research emphasizes the importance of controlling anthropogenic emissions in relieving summer secondary pollution in the NCP region.

An evaluation of fungal contamination and its relationship with PM levels in public transportation systems

Transmission of fungi in the air and its impact on health are regarded as important public health issues. Bioaerosols play an important role in causing or exacerbating infectious diseases, acute toxic effects, allergies, and cardiopulmonary symptoms. As many people use the public transportation system daily, it is necessary to determine the type and manner of dispersal and abundance of airborne fungi in public transport places. Three public transportation systems including a bus station, a train station, and an airport in Ahvaz city (Iran) were examined. At each of these stations, the air samples were taken from inside and outside the hall stations, and in-vehicle. A bio-stage Anderson sampler was used by suctioning air and passing it over a petri dish containing culture medium Sabouraud Dextrose Agar (SDA). Relative humidity (RH, %), temperature (T, ◦C), and mass concentration of particulate matter (PM1, PM2.5, and PM10, μg/m3) at the sampling points were measured. The highest concentration of airborne fungi was observed in the airport. The concentration of fungi in the ambient air was higher than that in the indoor air of halls and in-vehicle. In all sampling points, the ambient predominant airborne fungi were Cladosporium and Alternaria, while the indoor predominant airborne fungi were Cladosporium, Aspergillus, and Penicillium. The indoor to outdoor ratio showed that the fungi were of an external origin. Due to the influence of the ambient air on indoor air, it is recommended to use proper ventilation and enhance the hygiene level of vehicles in public transportation systems to reduce exposure to environmentally pathogenic bioaerosols.

Multiple dietary patterns and the association between long-term air pollution exposure with type 2 diabetes risk: Findings from UK Biobank cohort study

BackgroundEvidence of modifying effect of various dietary patterns (DPs) on risk of type 2 diabetes (T2D) induced by long-term exposure to air pollution (AP) is still rather lacking, which therefore we aimed to explore in this study. MethodsWe included 78,230 UK Biobank participants aged 40–70 years with at least 2 typical 24-hour dietary assessments and without baseline diabetes. The annual average concentration of particulate matter with diameter micrometers ≤2.5 (PM2.5) and ≤10 (PM10), nitrogen dioxide (NO2), and nitrogen oxides (NOX) estimated by land use regression model was the alternative proxy of long-term AP exposure. Three well-known prior DPs such as Mediterranean diet (MED), dietary approaches to stop hypertension diet (DASH), and empirical dietary inflammatory pattern (EDIP), as well as three posterior DPs derived by the rank reduced regression model were used to capture participants’ dietary habits. Cox regression models were used to estimate AP-T2D and DP-T2D associations. Modifying effect of DPs on AP-T2D association was assessed using stratified analysis and heterogeneity test. ResultsDuring a median follow-up 12.19 years, 1,693 participants developed T2D. PM2.5, PM10, NO2, and NOX significantly increased the T2D risk (P <0.05), with hazard ratio (HR) and 95% confidence interval (95% CI) for per interquartile range increase being 1.09 (1.02,1.15), 1.04 (1.00, 1.09), 1.11 (1.04, 1.18), and 1.08 (1.03, 1.14), respectively. Comparing high with low adherence, healthy DPs were associated with a 14–41% lower T2D risk. Participants with high adherence to MED, DASH, and anti-EDIP, alongside the posterior anti-oxidative dietary pattern (AODP) had attenuated and statistically non-significant NO2-T2D and NOX-T2D associations (Pmodify <0.05). ConclusionsMultiple forms of healthy DPs help reduce the T2D risk associated with long-term exposure to NO2 and NOX. Our findings indicate that adherence to healthy DPs is a feasible T2D prevention strategy for people long-term suffering from NO2 and NOX pollution.

Estimation of historical daily PM2.5 concentrations for three Chinese megacities: Insight into the socioeconomic factors affecting PM2.5

Studying historical changes in the 2.5 μm particulate matter concentration (PM2.5) can clarify the relationship between air pollution and socioeconomic development. Daily PM2.5 levels and meteorological data (2012–2022) for three large cities (Beijing, Shanghai, and Xi'an) at different development stages in different regions of China were used to construct a random forest (RF) model for estimating historical PM2.5 data for the period 1973–2011, a time period in which few measurements were made. The eigenvalue for visibility was the largest in the RF model; visibility explained 0.76–0.87 of the variance in PM2.5 for the three cities. The daily estimated PM2.5 was validated, with an R2 of 0.654–0.780 and average absolute error of 11.52–31.73 μg m−3 in the model. PM2.5 concentrations predicted by the RF model for 2004–2011 were highly correlated with gravimetric measurements (R = 0.585, p < 0.01). We extensively validated the results of RF using manual weighing PM2.5 data, online monitoring concentration of PM10, and aerosol optical depth (AOD), demonstrating the accuracy of the model. Over the study period, the PM2.5 level first increased and then decreased in the three cities; however, the year at which the trend changed differed. We further explored the effects of urbanization and economic growth on PM2.5 levels by investigating the correlations between socioeconomic indicators and PM2.5. The magnitude of the permanent population of Beijing and gross regional production growth in Shanghai were both significantly positively correlated with the PM2.5 level. Increasing the size of urban green areas can reduce PM2.5; this effect was strongest for the southern city of Shanghai, may due to their different climates and green tree species. Energy consumption and emissions from primary industries were strongly positively correlated with the urban PM2.5 level. An in-depth understanding of the factors affecting PM2.5 concentrations could help policymakers improve air quality management strategies, especially for densely populated megacities.