Mean Concentrations Of Particulate Matter Research Articles

Exploratory Data Analytics of Air Pollutant Data for Air Quality Management Application

Purpose: With escalating concerns over the detrimental impacts of air pollution on public health and the environment, this study embarks on a comprehensive exploration of air quality dynamics, focusing on Ogun state metropolis of Nigeria. The primary objective is to contribute to the burgeoning field of air quality management by harnessing the power of data analytics, exploratory data analysis, and advanced python programming libraries. The study seeks to address critical questions regarding the current state of air quality, major sources of pollution, government interventions, and individual contributions to better air quality. Methodology: The research employs Exploratory Data Analysis to unveil intrinsic patterns and trends within historical air quality datasets extracted from IoT devices located across Ogun state. This initial phase aims to discern key statistical parameters, including mean concentrations, variations, and correlations among various pollutants. Subsequently, the study employs Topic Modeling to extract latent themes and sentiments from qualitative data, specifically focusing on public opinions gathered through digital surveys. Resulting topics provide insights into public perceptions regarding air quality, pollution sources, and the efficacy of governmental interventions. Findings: Experimental result is revealing of the diversity of the dataset. The EDA returned a mean Particulate Matter concentration of approximately 12.65 µg/m³, while the mean Nitric Oxide concentration is approximately 13.56 µg/m³. Notable correlations include a strong positive correlation between PM2.5 and PM10 (0.69), indicating a substantial association between fine and coarse particulate matter. Additionally, there is a noteworthy positive correlation between NO and Nox (0.97), suggesting a high degree of correlation between nitric oxide and nitrogen oxide levels. However, negative correlations are observed, such as the substantial negative correlation between RH (relative humidity) and PM2.5 (-0.46), implying an inverse relationship between humidity and fine particulate matter levels. The study develops an innovative air quality management application. Unique Contribution to Theory, Practice and Policy: The application aims to empower both the public and policymakers with actionable insights, fostering informed decision-making and collaborative efforts towards improving air quality. It is highly recommended that industry experts should continue to imbibe ethical standards in data acquisition and deployment practices.

Ambient air pollution associated with incident asthma, subsequent cardiovascular disease and death: A trajectory analysis of a national cohort

No previous study has examined the impact of air pollution on the cardiovascular disease (CVD) trajectory, especially among asthmatic subjects. Based on the UK Biobank cohort, we retrieved 292,227 adults free of asthma and CVD aged 37–73 years at recruitment (2006–2010). Annual mean concentrations of particulate matter (PM10 and PM2.5) and nitrogen oxides (NO2 and NOx) were assessed at each individual’s addresses. We used multi-state models to estimate the associations of air pollution with the trajectory from healthy to incident asthma, subsequent CVD, and death. During a median follow-up of 11.7 years, a total of 6338 (2.2%) participants developed asthma, among which, 638 (10.1%) subsequently proceeded to CVD. We observed significant impacts of various air pollutants on the CVD dynamic transitions, with a more substantial effect of particulate matter pollutants than gaseous air pollutants. For example, the hazard ratios (95% confidence intervals) for per interquartile range increase in PM2.5 and PM10 were 1.28 (1.13, 1.44) and 1.27 (1.13, 1.43) for transitions from incident asthma to subsequent CVD. In conclusion, long-term air pollution exposure could affect the CVD trajectory. Distinguishing the effect of air pollutants on CVD transition stages has great significance for CVD health management and clinical prevention, especially among asthma patients.

Association of joint exposure to various ambient air pollutants during adolescence with blood pressure in young adulthood.

The association of various air pollutants exposure during adolescence with blood pressure (BP) in young adulthood is uncertain. We intended to evaluate the long-term association of individual and joint air pollutants exposure during adolescence with BP in young adulthood. This cross-sectional study of incoming students was conducted in five geographically disperse universities in China during September and October 2018. Mean concentrations of particulate matter with diameters ≤2.5μm (PM2.5 ), ≤10μm (PM10 ), nitrogen dioxides (NO2 ), carbon monoxide (CO), sulfur dioxide (SO2 ), and ozone (O3 ) at participants' residential addresses during 2013-2018 were collected from the Chinese Air Quality Reanalysis dataset. Generalized linear mixed models (GLM) and quantile g-computation (QgC) models were utilized to estimate the association between individual and joint air pollutants exposure and systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse pressure (PP). A total of 16,242 participants were included in the analysis. The GLM analyses showed that PM2.5 , PM10 , NO2 , CO, and SO2 were significantly positively associated with SBP and PP, while O3 was positively associated with DBP. The QgC analyses indicated that long-term exposure to a mixture of the six air pollutants had a significant positive joint association with SBP and PP. In conclusion, air pollutant co-exposure during adolescence may influence BP in young adulthood. The findings of this study emphasized the impacts of multiple air pollutants interactions on potential health and the need of minimizing pollution exposures in the environment.

Impact of different ventilation conditions on tobacco smoke-associated particulate matter emissions in a car cabin using the TAPaC platform

Despite antagonizing attempts from the tobacco industry, passive inhalation of tobacco smoke is known to be cancerogenic and toxic to human health for decades. Nonetheless, millions of non-smoking adults and children are still victims of second-hand smoke. Accumulation of particulate matter (PM) in confined spaces such as the car are particularly harmful due to high concentrations. We here aimed to analyze the specific effects of ventilation conditions in the setting of a car. By the use of the measuring platform TAPaC (tobacco-associated particulate matter emissions inside a car cabin), 3R4F reference cigarettes, Marlboro red, and Marlboro gold were smoked in a car interior with a volume of 3.709 m3. Seven different ventilation conditions (C1–C7) were analyzed. Under C1, all windows were closed. Under C2–C7, the car ventilation was turned on power level 2/4 with the air directed towards the windshield. Only the passenger side window was opened, where an outer placed fan could create an airstream speed of 15.9–17.4 km/h at one meter distance to simulate a driving car. C2: Window 10 cm opened. C3: Window 10 cm opened with the fan turned on. C4: Window half-opened. C5: Window half-opened with the fan turned on. C6: Window fully opened. C7: Window fully opened with the fan turned on. Cigarettes were remotely smoked by an automatic environmental tobacco smoke emitter and a cigarette smoking device. Depending on the ventilation condition the cigarettes emitted different mean PM concentrations after 10 min under condition C1 (PM10: 1272–1697 µg/m3, PM2.5: 1253–1659 µg/m3, PM1: 964–1263 µg/m3) under C2, C4, and C6 (PM10: 68.7–196.2 µg/m3, PM2.5: 68.2–194.7 µg/m3, PM1: 66.1–183.8 µg/m3) C3, C5, and C7 (PM10: 73.7–139 µg/m3, PM2.5: 72–137.9 µg/m3, PM1:68.9–131.9 µg/m3). Vehicle ventilation is insufficient to protect passengers from toxic second-hand smoke completely. Brand-specific variations of tobacco ingredients and mixtures markedly influence PM emissions under ventilation conditions. The most efficient ventilation mode to reduce PM exposure was achieved by opening the passenger´s window 10 cm and turning the onboard ventilation on power level 2/4. In-vehicle smoking should be banned to preserve innocent risk groups (e.g., children) from harm.

Early-Life Exposure to Ambient Air Pollution from Multiple Sources and Asthma Incidence in Children: A Nationwide Birth Cohort Study from Denmark.

Ambient air pollution exposure has been associated with childhood asthma, but previous studies have primarily focused on prevalence of asthma and asthma-related outcomes and urban traffic-related exposures. We examined nationwide associations between pre- and postnatal exposure to ambient air pollution components and asthma incidence in children age 0-19 y. Asthma incidence was identified from hospital admission, emergency room, and outpatient contacts among all live-born singletons born in Denmark between 1998 and 2016. We linked registry data with monthly mean concentrations of particulate matter (PM) with aerodynamic diameter () and PM with aerodynamic diameter (), nitrogen dioxide (), nitrogen oxides, elemental carbon, and organic carbon (OC), sulfur dioxide, ozone, sulfate, nitrate, ammonium, secondary organic aerosols, and sea salt. Associations were estimated with Cox proportional hazard models using fixed prenatal exposure means and time-varying postnatal exposures. Of the 1,060,154 children included, 6.1% had asthma during the mean follow-up period of 8.8 y. The risk of asthma increased with increasing prenatal exposure to all pollutants except for and sea salt. We also observed increased risk after restriction to asthma after age 4 y, after additional adjustment for area-specific socioeconomic status, and for postnatal exposure to most pollutants. The hazard ratio (HR) associated with an interquartile range increase of 2.4 and in prenatal exposure was 1.06 [95% confidence interval (CI): 1.04, 1.08] for and 1.04 (95% CI: 1.02, 1.05) for , respectively. This association with was stable after adjustment for , whereas it attenuated for to 1.01 (95% CI: 0.99, 1.03) after adjustment for . For a increase in prenatal OC exposure, for which biomass is an important source, the HR was 1.08 (95% CI: 1.06, 1.10), irrespective of adjustment for . These findings suggest that early-life exposure to ambient air pollution from multiple sources contributes to asthma development. https://doi.org/10.1289/EHP11539.

Long-Term Exposure to Ambient Air Pollution and Mortality among Four Million COVID-19 Cases in Italy: The EpiCovAir Study.

The role of chronic exposure to ambient air pollutants in increasing COVID-19 fatality is still unclear. The study aimed to investigate the association between long-term exposure to air pollutants and mortality among 4 million COVID-19 cases in Italy. We obtained individual records of all COVID-19 cases identified in Italy from February 2020 to June 2021. We assigned 2016-2019 mean concentrations of particulate matter (PM) with aerodynamic diameter (), PM with aerodynamic diameter (), and nitrogen dioxide () to each municipality () as estimates of chronic exposures. We applied a principal component analysis (PCA) and a generalized propensity score (GPS) approach to an extensive list of area-level covariates to account for major determinants of the spatial distribution of COVID-19 case-fatality rates. Then, we applied generalized negative binomial models matched on GPS, age, sex, province, and month. As additional analyses, we fit separate models by pandemic periods, age, and sex; we quantified the numbers of COVID-19 deaths attributable to exceedances in annual air pollutant concentrations above predefined thresholds; and we explored associations between air pollution and alternative outcomes of COVID-19 severity, namely hospitalizations or accesses to intensive care units. We analyzed 3,995,202 COVID-19 cases, which generated 124,346 deaths. Overall, case-fatality rates increased by 0.7% [95% confidence interval (CI): 0.5%, 0.9%], 0.3% (95% CI: 0.2%, 0.5%), and 0.6% (95% CI: 0.5%, 0.8%) per increment in , , and , respectively. Associations were higher among elderly subjects and during the first (February 2020-June 2020) and the third (December 2020-June 2021) pandemic waves. We estimated COVID-19 deaths were attributable to pollutant levels above the World Health Organization 2021 air quality guidelines. We found suggestive evidence of an association between long-term exposure to ambient air pollutants with mortality among 4 million COVID-19 cases in Italy. https://doi.org/10.1289/EHP11882.

A smart and flexible approach for aggregation of adjacent polygons to meet a minimum target area or attribute value

Many geospatial analyses require flexible aggregation of adjacent units to meet a minimum target area or attribute value. This is usually accomplished using several non-automated and complex GIS tasks. We developed an integrated user-friendly approach and algorithm implemented in the ‘GHS-SmartDissolve’ tool, which addresses minimum mapping unit or attribute value requirements, layers resolution mismatch, spatial uncertainty or modifiable areal unit problem in GIScience. This method automatically dissolves adjacent features updating fields’ values to reach a minimum target area or attribute value, using a flexible settings framework to meet user requirements. Also provided as a toolbox for ArcGIS (Esri), the approach is demonstrated by (i) estimating the mean particulate matter concentrations for all municipalities in Italy in 2011 by combining a coarse grid of global PM2.5 concentrations with fine administrative units; (ii) estimating boundaries of Metropolitan areas in Portugal as aggregation of municipalities, by matching their total population.

S-01-2: ASSOCIATION OF EXPOSURE TO AIR POLLUTANTS DURING ADOLESCENCE WITH BLOOD PRESSURE IN YOUNG ADULTHOOD

Objective: The effect of long-term exposure to air pollutants during adolescence on blood pressure in young adulthood is uncertain. We aimed to assess the association of air pollutants exposure during adolescence with blood pressure in young adulthood based on a nationwide sample of Chinese college students. Design and method: This cross-sectional study of incoming students was conducted in five geographically disperse universities in China during September and October 2018. Mean concentrations of particulate matter (PM) with diameters < = 2.5 um (PM2.5), < = 10 um (PM10), and nitrogen dioxides (NO2) at participants’ residential addresses during 2013–2018 were collected from the Chinese Air Quality Reanalysis dataset. A generalized linear mixed model was used to estimate the connection between air pollutants exposure and systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse pressure (PP). Results: A total of 16,042 participants (18.2 ± 0.7 years of age, 54.0% male) were included in the final analysis. After adjusting for potential confounding factors including age, sex, body mass index, drinking, smoking, physical activity, humidity, temperature, and so on, a 10 ug/m3 increase in PM10 and NO2 was significantly associated with 0.86 [95% confidence interval (CI): 0.51, 1.21] in SBP, 0.83[95% CI: 0.52, 1.13] in PP, respectively. Similarly, 1.69 [95% CI: 0.92, 2.46] in SBP and 1.76 [95% CI: 1.09, 2.43] in PP were found for each 10 ug/m3 increase in PM10. However, there was no correlation between PM2.5 and SBP, DBP, and PP (P > 0.05). Conclusions: Our study suggests that exposure to air pollutants during adolescence may contribute to a significant correlation with elevated blood pressure in young adulthood. The findings of this study emphasize the impacts of air pollutants exposure on potential health and the need of minimizing pollution exposures in the environment.

Long-term residential exposure to source-specific particulate matter and incidence of diabetes mellitus — A cohort study in northern Sweden

Diabetes mellitus (DM) incidence have been assessed in connection with air pollution exposure in several studies; however, few have investigated associations with source-specific local emissions. This study aims to estimate the risk of DM incidence associated with source-specific air pollution in a Swedish cohort with relatively low exposure. Individuals in the Västerbotten intervention programme cohort were followed until either a DM diagnosis or initiation of treatment with glucose-lowering medication occurred. Dispersion models with high spatial resolution were used to estimate annual mean concentrations of particulate matter (PM) with aerodynamic diameter ≤10 μm (PM10) and ≤2.5 μm (PM2.5) at individual addresses. Hazard ratios were estimated using Cox regression models in relation to moving averages 1–5 years preceding the outcome. During the study period, 1479 incident cases of DM were observed during 261,703 person-years of follow-up. Increased incidence of DM was observed in association with PM10 (4% [95% CI: -54–137%] per 10 μg/m3), PM10-traffic (2% [95% CI: -6–11%] per 1 μg/m3) and PM2.5-exhaust (11% [95% CI: -39–103%] per 1 μg/m3). A negative association was found for both PM2.5 (-18% [95% CI: -99–66%] per 5 μg/m3), but only in the 2nd exposure tertile (-10% [95% CI: -25–9%] compared to the first tertile), and PM2.5-woodburning (-30% [95% CI: -49–4%] per 1 μg/m3). In two-pollutant models including PM2.5-woodburning, there was an 11% [95% CI: -11–38%], 6% [95% CI: -16–34%], 13% [95% CI: -7–36%] and 17% [95% CI: 4–41%] higher risk in the 3rd tertile of PM10, PM2.5, PM10-traffic and PM2.5-exhaust, respectively, compared to the 1st. Although the results lacked in precision they are generally in line with the current evidence detailing particulate matter air pollution from traffic as an environmental risk factor for DM.

Association of ambient air pollution exposure and its variability with subjective sleep quality in China: A multilevel modeling analysis

Growing epidemiological evidence has shown that exposure to ambient air pollution contributes to poor sleep quality. However, whether variability in air pollution exposure affects sleep quality remains unclear. Based on a large sample in China, this study linked individual air pollutant exposure levels and temporal variability with subjective sleep quality. Town-level data on daily air pollution concentration for 30 days prior to the survey date were collected, and the monthly mean value, standard deviations, number of heavily polluted days, and trajectory for six common pollutants were calculated to measure air pollution exposure and its variations. Sleep quality was subjectively assessed using the Pittsburgh Sleep Quality Index (PSQI), and a PSQI score above 5 indicated overall poor sleep quality. Multilevel and negative control models were used. Both air pollution exposure and variability contributed to poor sleep quality. A one-point increase in the one-month mean concentration of particulate matter with aerodynamic diameters of ≤2.5 μm (PM2.5) and ≤10 μm (PM10) led to 0.4% (95% confidence interval (CI): 1.002–1.006) and 0.3% (95% CI: 1.001–1.004) increases in the likelihoods of overall poor sleep quality (PSQI score >5), respectively; the odds ratios of a heavy pollution day with PM2.5 and PM10 were 2.2% (95% CI: 1.012–1.032) and 2.2% (95% CI: 1.012–1.032), respectively. Although the mean concentrations of nitrogen dioxide, sulfur dioxide, and carbon monoxide met the national standard, they contributed to the likelihood of overall poor sleep quality (PSQI score >5). A trajectory of air pollution exposure with maximum variability was associated with a higher likelihood of overall poor sleep quality (PSQI score >5). Subjective measures of sleep latency, duration, and efficiency (derived from PSQI) were affected in most cases. Thus, sleep health improvements should account for air pollution exposure and its variations in China under relatively high air pollution levels.

Long-term exposure to particulate air pollution and presence and progression of carotid artery plaques - A northern Sweden VIPVIZA cohort study

AimsTo estimate the association between long-term exposure to particulate air pollution and sub-clinical atherosclerosis based on the existence of plaque and the carotid intima-media thickness (cIMT). MethodsVisualization of asymptomatic atherosclerotic disease for optimum cardiovascular prevention (VIPVIZA) is a randomised controlled trial integrated within the Västerbotten Intervention Programme, an ongoing population-based cardiovascular disease (CVD) prevention programme in northern Sweden. Individuals aged 40, 50, or 60 years with one or more conventional CVD risk factors in Umeå municipality were eligible to participate. The 1425 participants underwent an ultrasound assessment of cIMT and plaque formation during the period 2013–2016 and at 3-year follow-up. Source-specific annual mean concentrations of particulate matter with aerodynamic diameter ≤10 μm (PM10) and ≤2.5 μm (PM2.5), and black carbon (BC) at the individual's residential address were modelled for the calendar years 1990, 2001 and 2011. Poisson regression was used to estimate prevalence ratios for presence of carotid artery plaques, and linear regression for cIMT. ResultsThe plaque prevalence was 43% at baseline and 47% at follow-up. An interquartile range (IQR) increase in PM10 (range in year 2011: 7.1–13.5 μg/m3) was associated with a prevalence ratio at baseline ultrasound of 1.11 (95% CI 0.99–1.25), 1.08 (95% CI 0.99–1.17), and 1.00 (95% CI 0.93–1.08) for lag 23, 12 and 2 years, and at follow-up 1.04 (95% CI 0.95–1.14), 1.08 (95% CI 1.00–1.16), and 1.01 (95% CI 0.95–1.08). Similar prevalence ratios per IQR were found for PM2.5 and BC, but with somewhat lower precision for the later. Particle concentrations were however not associated with the progression of plaque. No cross-sectional or longitudinal associations of change were found for cIMT. ConclusionsThis study of individuals with low/moderate risk for CVD give some additional support for an effect of long-term air pollution in early subclinical atherosclerosis.

Association between long-term exposure to particulate matter and childhood cancer: A retrospective cohort study

BackgroundAlthough particulate matter is a known carcinogen, its association with childhood cancer is inconclusive. The present study aimed to examine the association between long-term exposure to particulate matter and childhood cancer. MethodsA retrospective cohort was constructed from the claims database of the Korea National Health Insurance Service, including children born in seven metropolitan cities in Korea between 2002 and 2012. Monthly mean concentrations of particulate matter with aerodynamic diameter <10 μm (PM10) and other air pollutants (NO2, SO2, CO, and O3) were calculated using data from the AirKorea. Monthly mean concentrations of particulate matter with aerodynamic diameter <2.5 μm (PM2.5) were estimated based on a data fusion approach. Cumulative exposure was assessed by averaging the monthly concentrations accounting for the residential mobility of the children. The occurrence of cancer was identified by the appearance of diagnosis codes in the claims database. Hazard ratios (HR) and 95% confidence intervals (95% CI) were calculated using Cox proportional regression, adjusting for potential confounders and O3 concentrations. ResultsDuring the study period, 1,725 patients were newly diagnosed with cancer among 1,261,855 children. HR of all cancers per 10 μg/m3 increment in annual mean concentrations of PM2.5 and PM10 were 3.02 (95% CI: 1.63, 5.59) and 1.04 (0.74, 1.45), respectively. ConclusionPM2.5 exposure was positively associated with childhood cancer in a large retrospective cohort with exposure assessment accounting for residential mobility.

Particular matter influences the incidence of acute otitis media in children

Particulate matter (PM) is the main component of air pollution. Children are vulnerable to PM and acute otitis media (AOM), which is one of the most common diseases in children. However, studies on the relationship between AOM in children and PM are rare and their results are inconsistent. The aim of this study is to investigate the effect of PM on AOM in children on the basis of the Korea National Health Insurance service (NHIS) claims data. NHIS claim data from 2008 to 2015 was used to identify outpatient visits, antibiotic use to treat AOM, and demographic data. This data was combined with the data on PM2.5 (≤ 2.5 μm) and PM10 (≤ 10 μm according to its aerodynamic diameter) level extracted from air pollution data from Korean National Institute of Environmental Research for 16 administrative regions. The children with AOM were divided into three age groups (< 2, 2–4, 5–10 years). Generalized linear Poisson regression model was used to estimate the association between AOM and PM using daily counts of AOM and daily mean PM concentrations. It was adjusted to temperature, wind, humidity, season, year, age, and region. With an increase in PM2.5 of 10 μg/m3, the relative risk of OM increased by 4.5% in children under 2 years of age. The effect of PM2.5 was strongest influence on the day of exposure. The exposure to PM10 was related to the incidence of AOM on the day of exposure and the following seven days in all three age groups. The PM concentrations did not strongly affect either AOM duration or the use of antibiotics to cure AOM. The RR in the each lag day after exposure to PM10 was diverse according to the age groups. Regardless of PM size and children’s age, the PM levels are positively related to the incidence of AOM. Both PM2.5 and PM10 have the most adverse effects on children under 2 years of age and on the day of exposure.

Vertical distribution characteristics of particulate matter beside an elevated expressway by unmanned aerial vehicle measurements

Increasing knowledge in the law of particulate matter (PM) distributions beside elevated expressways could assist in addressing the deterioration of urban air quality. However, the vertical distribution patterns of PM concentration have not been clearly recognized due to limited measurement methods. Hence, unmanned aerial vehicle (UAV) measurements are carried out at three typical sites near an elevated expressway to investigate the effects of the noise barrier, vegetation, and building on PM vertical distribution patterns. Results show that the order of mean PM concentration in three trial sites from low to high is: 86.3 μg/m3 at VN (with vegetation and noise barrier), 90.2 μg/m3 at CT (control, without vegetation, noise barrier, and building), and 93.2 μg/m3 at VNB (with vegetation, noise barrier, and building) site. Additionally, the PM1 concentrations present a unimodal distribution, peaking at 5–7 m and 7–9 m at CT and VN sites, respectively. PM10 concentrations decrease continuously with height at CT site and show a bimodal distribution at VN site, with the maximum and the upper peak occurring at 0–3 m and 5–7 m, respectively. High-density vegetation is more conducive to remove PM downwind than low-density vegetation in the open road, while the opposite is true in the street canyon. Moreover, statistically significant positive correlations are obtained between roadside concentration and traffic volume, as well as between roadside concentration and background concentration, with Spearman correlation coefficients of 0.61 and 0.93, respectively. This study could provide insights in mitigating traffic-related PM pollution into urban areas.

Roles of meteorological factors in inter-regional variations of fine and coarse PM concentrations over the Republic of Korea

This study examined meteorological effects on airborne concentrations of particulate matter (PM) of <2.5 μm (PM2.5) and 2.5–10 μm (PM2.5–10) diameter in 16 regions of Korea, including seven metropolitan cities and nine provinces. Regional distributions of mean PM concentrations indicate that PM2.5 concentrations were higher in provinces than in metropolitan cities, while PM2.5–10 concentrations were higher in the western than eastern regions, in the season with the highest concentrations during 2015–2019. Concentrations of PM of diameter <10 μm (PM10), the sum of fine and coarse PMs, decreased over all regions during 2001–2019, particularly in Seoul, the capital of Korea. Mechanisms by which meteorological factors such as air temperature, wind, humidity, and air pressure control PM concentrations in Korea vary with region, season, and PM size. Regardless of emissions, >25% of PM2.5 variability can be explained by Random Forest regression with only atmospheric variables, compared to little accountability for PM2.5–10. The two most important variables that affect PM2.5 variability are surface air temperature and wind. Transboundary transport controlled by atmospheric factors causes fine PM from northeast and east China to affect PM2.5 variations a day after emissions in the northern-central and southern regions of Korea, respectively; and coarse PM from east China affects PM2.5–10 variations in Korea on the same day. The present results suggest that local governments of regions with high PM concentrations should strengthen regulation policies with a long-term perspective, considering future changes in atmospheric conditions that may cause increases in PM levels.

Long-term exposure to particulate air pollution and black carbon in relation to natural and cause-specific mortality: a multicohort study in Sweden

ObjectivesTo estimate concentration–response relationships for particulate matter (PM) and black carbon (BC) in relation to mortality in cohorts from three Swedish cities with comparatively low pollutant levels.SettingCohorts from Gothenburg, Stockholm...

Association between long-term exposure to particulate matter and childhood cancer: Retrospective cohort study

BACKGROUND AND AIM: Particulate matter is known carcinogen, but its association with childhood cancer is inconsistent. The aim of the present study was to examine the association between air pollution and childhood cancer. METHODS: A retrospective cohort was constructed from claims database of the Korea National Health Insurance Service. Children who had been born in 7 metropolitan cities in Korea (Seoul, Incheon, Daejeon, Gwangju, Daegu, Busan, and Ulsan) from 2002 to 2012 were recruited and half of them were randomly selected. Children who were diagnosed with cancer within 5 years of birth were excluded. Monthly mean concentrations of particulate matter with aerodynamic diameter 10 μm (PM10) and other air pollutants (NO2, SO2, CO and O3) was calculated from AirKorea. Monthly mean concentrations of particulate matter with aerodynamic diameter 2.5 μm (PM2.5) was estimated with a concentration prediction model. The cumulative exposure was calculated by averaging monthly concentrations according to the subject's residential information. We constructed Cox proportional hazard model adjusting for potential confounders and O3 concentration. RESULTS:A total of 1,261,855 children (boys 641,704, girls 610,151) were included in the analysis. During the study period, 1,725 were newly diagnosed with cancer. Exposures to higher mean ambient PM2.5 and PM10 concentration increased the risk of childhood cancer. The hazard ratio of all cancers was 3.02 (95% confidence interval [CI]: 1.63, 5.59) and 1.04 (95% CI: 0.71, 1.45) for an increment of 10 μg/m3 of annual mean concentrations of PM2.5 and PM10, respectively. CONCLUSIONS:We observed significant positive association between particulate matter exposure and childhood cancer in a retrospective cohort of 1.2 million children. KEYWORDS: Particulate matter, Cancer, Children, Retrospective cohort

Long-Term Residential Exposure to Particulate Matter and Its Components, Nitrogen Dioxide and Ozone—A Northern Sweden Cohort Study on Mortality

This study aims to estimate the mortality risk associated with air pollution in a Swedish cohort with relatively low exposure. Air pollution models were used to estimate annual mean concentrations of particulate matter with aerodynamic diameter ≤ 2.5 µm (PM2.5), primary emitted carbonaceous particles (BC/pOC), sea salt, chemically formed particles grouped as secondary inorganic and organic aerosols (SIA and SOA) as well as ozone (O3) and nitrogen dioxide (NO2). The exposure, as a moving average was calculated based on home address for the time windows 1 year (lag 1), 1–5 years (lag 1–5) and 1–10 years (lag 1–10) preceding the death. During the study period, 1151 cases of natural mortality, 253 cases of cardiovascular disease (CVD) mortality and 113 cases of respiratory and lung cancer mortality were observed during 369,394 person-years of follow-up. Increased natural mortality was observed in association with NO2 (3% [95% CI −8–14%] per IQR) and PM2.5 (2% [95% CI −5–9%] for an IQR increase) and its components, except for SOA where a decreased risk was observed. Higher risk increases were observed for CVD mortality (e.g., 18% [95% CI 1–39%] per IQR for NO2). These findings at low exposure levels are relevant for future decisions concerning air quality policies.

Microbiological Aerosol, Particulate Matter Concentrations and Antibiotic Resistant Staphylococcus spp. in the Premises of Poland’s Oldest Agricultural School

Bioaerosol, particulate matter concentration and antibiotic resistance of airborne Staphylococcus was assessed in animal and public premises (classroom, sports hall, horse stable, cowshed, newborn calf shed and outdoor background control site) of Poland’s oldest agricultural school. The concentration and size distribution of bacteria, fungi, actinomycetes and staphylococci were assessed with a six stage Andersen impactor. Particulate matter (PM10, PM4, PM2.5 and PM1) was determined using the DustTrak aerosol monitor. The Staphylococcus species were determined with MALDI-TOF mass spectrometry and antimicrobial resistance was assessed using disk diffusion. Bioaerosol concentrations differed significantly between sampling points, with the highest levels of all microorganisms occurring in the newborn calf shed. The proportion of respirable fraction exceeded 60% in all sites, indicating potential harmfulness to exposed people. Mean concentrations of particulate matter were the smallest in school rooms and the highest in the newborn calf shed. Neither particulate matter nor microbial aerosol exceeded threshold values for workplaces. Among thirty-four isolated staphylococcal strains, S. equorum (35%), S. succinus (26%) and S. xylosus (15%) were the most prevalent. Resistance to macrolides (erythromycin) and lincosamides (clindamycin) was the most frequent. One strain was methicillin-resistant. Farm animals are significant sources of bioaerosol and therefore attention should be paid with respect to maintaining appropriate sanitary conditions and hygiene of premises and animals.

Effects of long-term air pollution exposure on ankle-brachial index and cardio-ankle vascular index: A longitudinal cohort study using data from the Electricity Generating Authority of Thailand study.

Ankle-brachial index (ABI) and cardio-ankle vascular index (CAVI) are surrogate measures of atherosclerosis based on the functional performance of vessels, and are highly related to cardiovascular events. However, only a few longitudinal studies have been conducted on their associations with long-term air pollution exposure. This study aimed to examine whether long-term air pollution exposure is associated with ABI and CAVI in workers of the Electricity Generating Authority of Thailand (EGAT) in the Bangkok Metropolitan Region (BMR). This longitudinal study included 1261 participants (age range, 57-76 years as of 2007) of the EGAT study (2007-2017). ABI and CAVI were measured in 2007, 2012, and 2017. Annual mean concentrations of particulate matter ≤10μm in diameter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and carbon monoxide (CO) were estimated by ordinary kriging using data from 22 background and 7 traffic monitoring stations in BMR between 2002 and 2017. Linear mixed-effects models were used to assess associations between air pollution (expressed as 1-year, 3-year, and 5-year average concentration) and ABI and CAVI (expressed as percent changes per interquartile range (IQR) increase in PM10, O3, NO2, SO2, and CO). We also applied the mixed-effect ordinal logistic models to calculate odds ratios (ORs) of having high or moderate CAVI per an IQR increase in air pollution. After controlling for potential confounders, 1-year average CO was negatively associated with ABI, but not significantly (-0.48%, 95% CI: -1.03, 0.07). Three-year average NO2 was positively associated with CAVI (6.67%, 95% CI: 0.21, 13.1). In contrast, 1-year average PM10 was inversely associated with CAVI although the association was not significant. Although not significantly, 1-year average NO2 and CO were positively associated with prevalence of high or moderate CAVI. Although not statistically significant, long-term NO2 and CO exposure was associated with ABI and CAVI in the participants of the EGAT study.