Ambient Particulate Matter Concentrations Research Articles

Ambient air pollution and obesity in school-aged children and adolescents: A multicenter study in China

BackgroundEnvironmental factors such as air pollution may contribute to the development of childhood obesity. However, current epidemiological evidence is limited and inconsistent. ObjectiveWe investigated the associations between long-term air pollution exposure and obesity in a large population of Chinese children and adolescents. MethodsA total of 44,718 children and adolescents (50.5% boys) aged 7 to 18 years were recruited from seven provinces/municipalities in China. Body mass index (BMI), waist circumference, waist-to-height ratio (WHtR) and the prevalence of general and central obesity were measured. Satellite-based spatial-temporal models were used to estimate ambient concentrations of particulate matter with aerodynamic diameter < 1.0 μm (PM1), <2.5 μm (PM2.5), <10.0 μm (PM10) and nitrogen dioxide (NO2). We used mixed-effects linear and logistic regression models to examine the associations between air pollution exposure and body weight measures. ResultsExposure to PM1, PM2.5, PM10 and NO2 was associated with increased BMI Z-score, waist circumference and WHtR, and higher prevalence of both general and central obesity. Generally, stronger associations were observed for particles, especially PM1 and PM2.5, than for NO2. Also, the associations of particles were generally more stable in two-pollutant models. Overall, the associations were more pronounced in boys than in girls except for general obesity. ConclusionsLong-term exposure to air pollution was associated with increased body weight and higher prevalence of obesity in children and adolescents, suggesting potential obesogenic effects of air pollution.

Comprehensive evaluation of potential coal mine dust emissions in an open-pit coal mine in Northwest China

Coal mining in China is continually increasing, and the associated emitted coal mine dust is of growing environmental and occupational concern. In this study, deposited coal mine dust (DD) was analysed in three different regions of an active, highly-volatile bituminous open-pit coal mine in the Xingjian Province, Northwest of China: coal working fronts, tailings handling sites, and road traffic sites. Samples were analysed for particle size, and geochemical and mineralogical patterns, and then compared with the respirable DD fractions (RDDs, <4 μm) separated from DD samples. Online measurements of ambient air concentrations of particulate matter (PM10 and PM2.5), black carbon (BC) and ultrafine particles (UFP) were performed in the same mine zones where DD was sampled.Furthermore, the RDD samples were subjected to analysis of specific biological response or toxicological indicators (oxidative potential, OP). The results demonstrated: i) large differences in particle size and composition among DD from tailings handling, road traffic and coal working front sites, ii) a strong influence of the DD moisture contents and ash yields on particle size, and, accordingly, on the potential dust emissions, iii) an enrichment of multiple elements (such as Nb, Th, Cr, Sr, Li, As, Pb, Cu, Zr and Ni) in the RDD from coal working fronts compared with their contents in the worked parent coal seams, mostly attributed to mining machinery, tyre and brake wear emissions and to deposition of dust emitted from gangue working zones, iv) low OP values of the RDD emitted from the studied mine, which works a high-quality coal, with OP being influenced by Mn, sulphate and anatase (TiO2) contents, and v) the impact of specific mining operations and mine areas on the levels of air pollutants, such as high PM from tailings handling in the upper parts of the mine or the high UFP levels in the bottom of the mine (due to vehicle and machinery emissions and lower dispersive conditions). The data presented here demonstrate the necessity of extracting the more deeply respirable size fraction of coal mine dusts in future studies on the health effects of these materials because this finer fraction is mineralogically and geochemically different from the parent rocks.

Evaluation of Variability in the Ambient PM2.5 Concentrations from FEM and FRM-like Measurements for Exposure Estimates

This study aims to evaluate the variability in ambient fine particulate matter (PM2.5) concentrations obtained from the federal equivalent method (FEM) and federal reference method (FRM)-like measurements at the national air quality monitoring stations (AQMSs) for exposure estimates and to examine the effect of environmental factors and sampling site characteristics affecting the spatial and temporal variations in PM2.5 concentrations. A mixed-effects model was used to evaluate the temporal and spatial variability in daily and annual PM2.5 concentrations during 2014-2017 at 16 AQMSs in the Big Taipei City, Taiwan. The mean FEM PM2.5 concentrations were ~30% higher than the FRM-like PM2.5 concentrations. The FRM-like PM2.5 concentrations obtained by applying the calibration procedures presented a negligible between-site variability. The daily FEM PM2.5 concentrations were dominated by the within-site variability (~90%), whereas the annual concentrations were reasonably attributable to the between-site variability (47.8%). Ambient PM2.5 was mainly affected by the gaseous pollutants (such as NO2, O3, and SO2), accounting for 45.8% and 26.8% of the within-site and between-site variability in concentrations, respectively. The FEM measurements rather than the FRM-like measurements at the AQMSs could provide a higher between-site variability for exposure estimates of PM2.5 in the epidemiological studies.

Statistical Assessment and Temperature Study from the Interlaboratory Application of the WLTP–Brake Cycle

The relative contribution of brake emissions to traffic-induced ambient Particulate Matter (PM) concentrations has increased over the last decade. Nowadays, vehicles’ brakes are recognised as an important source of non-exhaust emissions. Up to now, no standardised method for measuring brake particle emissions exists. For that reason, the Particle Measurement Programme (PMP) group has been working on the development of a commonly accepted method for sampling and measuring brake particle emissions. The applied braking cycle is an integral part of the overall methodology. In this article, we present the results of an interlaboratory study exploring the capacity of existing dynamometer setups to accurately execute the novel Worldwide Harmonised Light-Duty Vehicles Test Procedure (WLTP)–brake cycle. The measurements took place at eight locations in Europe and the United States. Having several dynamometers available enabled the coordination and execution of the intended exercise, to determine the sources of variability and provide recommendations for the correct application of the WLTP–brake cycle on the dyno. A systematic testing schedule was applied, followed by a thorough statistical analysis of the essential parameters according to the ISO 5725 standards series. The application of different control programmes influenced the correct replication of the cycle. Speed control turned out to be more accurate and precise than deceleration control. A crucial output of this interlaboratory study was the quantification of standard deviations for repeatability (between repeats), sample effect (between tests), laboratory effect (between facilities), and total reproducibility. Three critical aspects of the statistical analysis were: (i) The use of methods for heterogeneous materials; (ii) robust algorithms to reduce the artificial increase in variability from values with significant deviation from the normal distribution; and (iii) the reliance on the graphical representation of results for ease of understanding. Even if the study of brake emissions remained out of the scope of the current exercise, useful conclusions are drawn from the analysis of the temperature profile of the WLTP–brake cycle. Urban braking events are generally correlated to lower disc temperature. Other parameters affecting the brake temperature profile include the correct application of soak times, the temperature measurement method, the proper conditioning of incoming cooling air and the adjustment of the cooling airspeed.

Evaluation of optical particulate matter sensors under realistic conditions of strong and mild urban pollution

Abstract. In this paper we evaluate characteristics of three optical particulate matter sensors/sizers (OPS): high-end spectrometer 11-D (Grimm, Germany), low-cost sensor OPC-N2 (Alphasense, United Kingdom) and in-house developed MAQS (Mobile Air Quality System), which is based on another low-cost sensor – PMS5003 (Plantower, China), under realistic conditions of strong and mild urban pollution. Results were compared against a reference gravimetric system, based on a Gemini (Dadolab, Italy), 2.3 m3 h−1 air sampler, with two channels (simultaneously measuring PM2.5 and PM10 concentrations). The measurements were performed in Sarajevo, the capital of Bosnia-Herzegovina, from December 2019 until May 2020. This interval is divided into period 1 – strong pollution – and period 2 – mild pollution. The city of Sarajevo is one of the most polluted cities in Europe in terms of particulate matter: the average concentration of PM2.5 during the period 1 was 83 µg m−3, with daily average values exceeding 500 µg m−3. During period 2, the average concentration of PM2.5 was 20 µg m−3. These conditions represent a good opportunity to test optical devices against the reference instrument in a wide range of ambient particulate matter (PM) concentrations. The effect of an in-house developed diffusion dryer for 11-D is discussed as well. In order to analyse the mass distribution of particles, a scanning mobility particle sizer (SMPS), which together with the 11-D spectrometer gives the full spectrum from nanoparticles of diameter 10 nm to coarse particles of diameter 35 µm, was used. All tested devices showed excellent correlation with the reference instrument in period 1, with R2 values between 0.90 and 0.99 for daily average PM concentrations. However, in period 2, where the range of concentrations was much narrower, R2 values decreased significantly, to values from 0.28 to 0.92. We have also included results of a 13.5-month long-term comparison of our MAQS sensor with a nearby beta attenuation monitor (BAM) 1020 (Met One Instruments, USA) operated by the United States Environmental Protection Agency (US EPA), which showed similar correlation and no observable change in performance over time.

Exposure contrasts associated with a liquefied petroleum gas (LPG) intervention at potential field sites for the multi-country household air pollution intervention network (HAPIN) trial in India: results from pilot phase activities in rural Tamil Nadu

BackgroundThe Household Air Pollution Intervention Network (HAPIN) trial aims to assess health benefits of a liquefied petroleum gas (LPG) cookfuel and stove intervention among women and children across four low- and middle-income countries (LMICs). We measured exposure contrasts for women, achievable under alternative conditions of biomass or LPG cookfuel use, at potential HAPIN field sites in India, to aid in site selection for the main trial.MethodsWe recruited participants from potential field sites within Villupuram and Nagapattinam districts in Tamil Nadu, India, that were identified during a feasibility assessment. We performed.(i) cross-sectional measurements on women (N = 79) using either biomass or LPG as their primary cookfuel and (ii) before-and-after measurements on pregnant women (N = 41), once at baseline while using biomass fuel and twice – at 1 and 2 months – after installation of an LPG stove and free fuel intervention. We involved participants to co-design clothing and instrument stands for personal and area sampling. We measured 24 or 48-h personal exposures and kitchen and ambient concentrations of fine particulate matter (PM2.5) using gravimetric samplers.ResultsIn the cross-sectional analysis, median (interquartile range, IQR) kitchen PM2.5 concentrations in biomass and LPG using homes were 134 μg/m3 [IQR:71–258] and 27 μg/m3 [IQR:20–47], while corresponding personal exposures were 75 μg/m3 [IQR:55–104] and 36 μg/m3 [IQR:26–46], respectively. In before-and-after analysis, median 48-h personal exposures for pregnant women were 72 μg/m3 [IQR:49–127] at baseline and 25 μg/m3 [IQR:18–35] after the LPG intervention, with a sustained reduction of 93% in mean kitchen PM2.5 concentrations and 78% in mean personal PM2.5 exposures over the 2 month intervention period. Median ambient concentrations were 23 μg/m3 [IQR:19–27). Participant feedback was critical in designing clothing and instrument stands that ensured high compliance.ConclusionsAn LPG stove and fuel intervention in the candidate HAPIN trial field sites in India was deemed suitable for achieving health-relevant exposure reductions. Ambient concentrations indicated limited contributions from other sources. Study results provide critical inputs for the HAPIN trial site selection in India, while also contributing new information on HAP exposures in relation to LPG interventions and among pregnant women in LMICs.Trial registrationClinicalTrials.Gov. NCT02944682; Prospectively registered on October 17, 2016.

Associations of household solid fuel for heating and cooking with hypertension in Chinese adults.

The association between indoor air pollution resulting from household solid fuel use for heating and cooking with hypertension or blood pressure (BP) remains less clear. This study aims to rectify these knowledge gaps in a large Chinese population. During 2005-2009, 44 007 individuals aged 35-70 years with complete information on household solid fuel use for cooking and heating were recruited from 279 urban and rural communities of 12 centers. Solid fuel referred to charcoal, coal, wood, agriculture crop, animal dung or shrub. Annual concentration of ambient atmospheric particulate matter that have a diameter of less than 2.5 μm for all communities was collected. Generalized linear mixed models using community as the random effect were performed to estimate the association with hypertension prevalence or BP after considering ambient atmospheric particulate matter that have a diameter of less than 2.5 μm and a comprehensive set of potential confounding factors at the individual and household level. A total of 47.6 and 61.2% of participants used household solid fuel for heating and cooking, respectively. Solid fuel use for heating was not associated with an increase in hypertension prevalence (adjusted odds ratio = 1.08, 95% confident interval: 0.98, 1.20) or elevated SBP (0.62 mmHg, 95% confident interval: -0.24, 1.48). No association was found between solid fuel for cooking and hypertension or BP, and no additional risk was observed among participants who had both exposures to solid fuel for heating and cooking compared with those used for heating only. The current large Chinese study revealed a statistically insignificant increase in the association between solid fuel use for heating and hypertension prevalence or BP. As this cross-sectional study has its inherent limitation on causality, findings from this study would have to be confirmed by prospective cohort studies.

A Comparative Study of the Concentration of Ambient Particulate Matter of Size 2.5 microns in Georgetown

Air quality is a growing public concern in both developed and developing countries. Over the years, there has been an increase in the number of vehicles on major roadways. Vehicles release particulate matter (PM) into the atmosphere, which adversely affects air quality and, consequently, the health of the population. This study was conducted to measure ambient PM concentrations of size 2.5 microns (PM2.5) along two streets in Georgetown, Guyana; namely Regent Street and Woolford Avenue.

Predicting intraurban PM2.5 concentrations using enhanced machine learning approaches and incorporating human activity patterns

Urban areas contribute substantially to human exposure to ambient air pollution. Numerous statistical prediction models have been used to estimate ambient concentrations of fine particulate matter (PM2.5) and other pollutants in urban environments, with some incorporating machine learning (ML) algorithms to improve predictive power. However, many ML approaches for predicting ambient pollutant concentrations to date have used principal component analysis (PCA) with traditional regression algorithms to explore linear correlations between variables and to reduce the dimensionality of the data. Moreover, while most urban air quality prediction models have traditionally incorporated explanatory variables such as meteorological, land use, transportation/mobility, and/or co-pollutant factors, recent research has shown that local emissions from building infrastructure may also be useful factors to consider in estimating urban pollutant concentrations. Here we propose an enhanced ML approach for predicting urban ambient PM2.5 concentrations that hybridizes cascade and PCA methods to reduce the dimensionality of the data-space and explore nonlinear effects between variables. We test the approach using different durations of time series air quality datasets of hourly PM2.5 concentrations from three air quality monitoring sites in different urban neighborhoods in Chicago, IL to explore the influence of dynamic human-related factors, including mobility (i.e., traffic) and building occupancy patterns, on model performance. We test 9 state-of-the-art ML algorithms to find the most effective algorithm for modeling intraurban PM2.5 variations and we explore the relative importance of all sets of factors on intraurban air quality model performance. Results demonstrate that Gaussian-kernel support vector regression (SVR) was the most effective ML algorithm tested, improving accuracy by 118% compared to a traditional multiple linear regression (MLR) approach. Incorporating the enhanced approach with SVR algorithm increased model performance up to 18.4% for yearlong and 98.7% for month-long hourly datasets, respectively. Incorporating assumptions for human occupancy patterns in dominant building typologies resulted in improvements in model performance by between 4% and 37%. Combined, these innovations can be used to improve the performance and accuracy of urban air quality prediction models compared to conventional approaches.

Prenatal exposure to ambient air pollution and traffic and indicators of adiposity in early childhood: The Healthy Start Study

Background: Prenatal exposure to ambient air pollution and traffic have been associated with lower birth weight, but relationships with weight and body composition in childhood are unclear. The aim of this study was to examine associations of prenatal exposure to ambient air pollution and traffic with indicators of adiposity in early childhood. Methods: We included 738 participants of the Colorado-based Healthy Start Study whose height, weight, waist circumference and/or fat mass (via air displacement plethysmography, n=652) were measured at age 4-6 years. We estimated residential exposure to ambient concentrations of particulate matter with a diameter of &lt;2.5µm (PM2.5) and ozone (O3) averaged by trimester and throughout pregnancy via inverse distance-weighted interpolation of stationary monitoring data. We assessed the distance to the nearest major roadway and traffic density in multiple buffers surrounding the participants’ homes. Associations of prenatal exposure to air pollution and traffic with overweight (yes/no), waist circumference and fat mass index (fat mass/height2) were assessed by logistic and linear regression, adjusting for potential confounders. Results: Third trimester average 8-hour maximum O3 was associated with a higher odds of being overweight (adjusted odds ratio 1.71 [95%CI 1.12, 2.62] per IQR increase) and higher fat mass index (adjusted difference 0.27kg/m2 [95%CI 0.09, 0.44kg/m2] per IQR increase) at age 4-6 years. We found associations of third trimester PM2.5 with a lower fat mass index (adjusted difference -0.19kg/m2 [95%CI -0.32, -0.07kg/m2] per IQR increase), while first trimester O3 was associated with a lower odds of being overweight and lower fat mass index. Residential proximity to a highway was associated with a higher odds of being overweight and a non-significant higher waist circumference and fat mass index. Conclusion: Higher ambient concentrations of O3 during the third trimester of pregnancy and residential proximity to a highway during pregnancy may contribute to overweight in early childhood.

Short-term exposure to ambient particulate matter and hospital outpatient visits for respiratory diseases among children: A five-city time-series study in China

Background: Evidence concerning the association between ambient particulate matter (PM) and outpatient visits for respiratory diseases is quite limited, especially in children at a multicity level. Methods: A time-series study was performed in five Chinese cities from 2013 to 2018 among children aged 0-14 years. The city-specific effects of PM were estimated for time lags of zero up to seven days using the overdispersed generalized additive models after adjusting for time trends, meteorological variables, day of the week and holidays. Meta-analyses using random effects models were applied to pool the effect estimates in the five cities. The exposure-response relationship curves were also evaluated. Results: Exposure to PM was dose-responsive related to an increased respiratory outpatient visits among children. The cumulative lag effects of PM showed higher estimates than that of single-day exposure, and the lag07 (moving averages for the present day and the previous 7 days) concentrations of fine particles (PM2.5) and inhalable particles (PM10) produced the largest estimates. Each 10 μg/m3 increment in PM2.5 and PM10 at the lag07 was associated with a 1.39% (95% CI: 0.36%, 2.43%) and 1.11% (95% CI: 0.38%, 1.84%) increase in outpatient visits for all respiratory diseases among children, respectively, and the associations remained statistically significant at levels below the current Chinese Ambient Air Quality Standards (CAAQS). The effect estimates for acute lower respiratory infections (ALRIs) tended to be higher. Children 7-14 years old and 4-6 years old are the most susceptible groups for acute upper respiratory infections (AURIs) and ALRIs, respectively, but no sex differences were observed. Moreover, the effects of PM were stronger in the transition season of Beijing and Xining, whereas stronger in the cold season of the other 3 cities. Conclusions: Ambient PM concentrations, even at levels below the CAAQS, was dose-responsive associated with increased respiratory outpatient visits among children.

Effect of infectious disease outbreak on air quality: Impact of COVID-19 on changes in particulate matter concentrations in Taiwan

Backgrounds: Abundant research has shed light on how climate change instigates and propels the spread of infectious diseases. Recently published literature reported that global epidemic of COVID-19 has reduced air pollutant emissions in several metropolises due to lockdown measures. This study aims to compare the ambient particulate matter concentrations in Taiwan in the past year during the same time frame. Methods: We examined air quality in 17 counties from Taiwan; concentrations of PM1.0, PM2.5, and PM10 detected by low-cost air quality sensors (LCS) from January to March of 2019 and 2020, were analyzed to demonstrate the spatiotemporal pattern air pollution prior to and during the COVID-19 outbreak. We examined monitoring data from 674 LCS and calculated monthly and seasonal mean levels, as well as Wilcoxon signed-rank test to assess whether changes in concentrations were statistically significant. Particulate matter concentrations detected by another type of LCS, hereafter denoted as microsensors, were also analyzed. Results: Ambient concentrations of PM1.0, PM2.5, and PM10 in January of 2019 did not differ significantly from those detected in 2020. However, decreases in PM2.5 levels in February of 2020 reached statistical significance when we compared to levels detected in February of the previous year (30.35 10.38 and 28.13 8.22 μg/m3, p =0.027). Differences in monthly mean PM2.5 concentrations detected by microsensors were also statistically significant (22.57 7.05 and 21.61 7.13 μg/m3, p =0.035). As the pandemic progressed and social distancing encouraged, decreases in levels of PM1.0, PM2.5, and PM10 in March of 2020 were statistically significant (p=0.004, p=0.0002, p&lt;0.001). Similar decreases were detected by microsensors across Taiwan, with levels of PM2.5 decreased from 24.40 to 21.39 μg/m3, p&lt;0.001). Conclusion: Initial analysis showed even though Taiwan did not enforce full nationwide lockdown amidst COVID-19 pandemic, reductions in anthropogenic activities have lowered air pollution levels.

Risk Assessment for People Exposed to PM2.5 and Constituents at Different Vertical Heights in an Urban Area of Taiwan

Environmental epidemiological studies have consistently reported associations between ambient particulate matter (PM) concentrations and everyday mortality/morbidity. Many urban dwellers in Asia live in high-rise apartment buildings; thus, the pollutant concentrations of their immediate outdoor environments are affected by the vertical distribution of pollutants in the atmosphere. The vertical distributions of pollutants provide unique information about their sources and dynamic transport in urban areas, as well as their relationship to people’s exposure at ground level, while the vertical distributions of pollutants have rarely been considered in exposure assessment. In the current study, PM concentrations (with aerodynamic diameters less than 1.0 μm (PM1), 2.5 μm (PM2.5), and 10 μm (PM10)), nanoparticles, black carbon (BC), and particle-bound polycyclic aromatic hydrocarbons (p-PAHs) were measured at different residential heights—6 m, 16 m, and 27 m—at Feng Chia University near a popular night market in Western Taiwan. PM2.5 data were further adopted for health risk estimations. In winter, the magnitude of PM1, PM2.5, and PM10 concentrations were 16 m &gt; 6 m &gt; 27 m; nanoparticle concentrations were 6 m &gt; 27 m &gt; 16 m; and BC and p-PAHs concentrations were 27 m &gt; 16 m &gt; 6 m. In summer, PM1, PM2.5, and PM10 concentrations ranged from 6 m &gt; 16 m &gt; 27 m; nanoparticle concentrations were 6 m &gt; 16 m; and BC and p-PAHs concentrations were from 27 m &gt; 16 m. PM and constituents concentrations during winter were significantly higher in the nighttime than those in daytime, and levels of PM1, PM2.5, and PM10 increased rapidly on 6 m and 16 m heights (but did not increase at 27 m) after 5 pm, whereas these trends became less significant in summer. Health risk analysis for PM2.5 concentrations showed a decrease in lung cancer mortality rate and an extended lifespan for residents living at 27 m. Overall, the current study investigated the vertical profile of particulate matters and analyzed health impacts of PM2.5 at different residential heights in urban area of Taiwan. As the distributions of PM and the constituents varied at different residential heights, exposure and risk assessment of particle concentrations with multiple sizes and various components at broader vertical heights should be further investigated.

Spatio-temporal characteristics of air pollutants over Xinjiang, northwestern China.

To understand the characteristics of particulate matter (PM) and other air pollutants in Xinjiang, a region with one of the largest sand-shifting deserts in the world and significant natural dust emissions, the concentrations of six air pollutants monitored in 16 cities were analyzed for the period January 2013-June 2019. The annual mean PM2.5, PM10, SO2, NO2, CO, and O3 concentrations ranged from 51.44 to 59.54μgm-3, 128.43-155.28μgm-3, 10.99-17.99μgm-3, 26.27-31.71μgm-3, 1.04-1.32mgm-3, and 55.27-65.26μgm-3, respectively. The highest PM concentrations were recorded in cities surrounding the Taklimakan Desert during the spring season and caused by higher amounts of wind-blown dust from the desert. Coarse PM (PM10-2.5) was predominant, particularly during the spring and summer seasons. The highest PM2.5/PM10 ratio was recorded in most cities during the winter months, indicating the influence of anthropogenic emissions in winters. The annual mean PM2.5 (PM10) concentrations in the study area exceeded the annual mean guidelines recommended by the World Health Organization (WHO) by a factor of ca. ∼5-6 (∼7-8). Very high ambient PM concentrations were recorded during March 19-22, 2019, that gradually influenced the air quality across four different cities, with daily mean PM2.5 (PM10) concentrations ∼8-54 (∼26-115) times higher than the WHO guidelines for daily mean concentrations, and the daily mean coarse PM concentration reaching 4.4mgm-3. Such high PM2.5 and PM10 concentrations pose a significant risk to public health. These findings call for the formulation of various policies and action plans, including controlling the land degradation and desertification and reducing the concentrations of PM and other air pollutants in the region.

Single-day and cumulative effects of ambient particulate matter exposure on emergency department visits for respiratory disease in South Korea

Background: Along with the industrialization, the air pollutants have gained more attention and studies especially about respiratory diseases were conducted. Emergency visit reflects acute aggravation of disease rather than chronic exacerbation. Objectives: The objective of this study was to evaluate the relationship between the ambient particulate matter and the emergency visits with respiratory disease in South Korea. Methods: Patients diagnosed with respiratory disease in the emergency department in 2018 were enrolled. The data of meteorological factors and air pollutants between 4 December 2017 and 31 December 2018 were acquired. Poisson regression was used with daily emergency visits as the response variable and single-day particulate matter concentration as the explanatory variable. Results: A total of 4207 patients were enrolled. In Poisson regression analysis of all respiratory diseases, the effects of [Formula: see text] and [Formula: see text] were strongest at day before 8 and 26. Age older than 65 group and chronic respiratory disease group had earlier lag effect than the all-diseases group. Cumulative effect was peaked at 14 lag day. The split point of prediction was 87 µg/m3 before 3 days for [Formula: see text] and 37 µg/m3 before 8 days for [Formula: see text]. Conclusion: The results can be used to predict the increase of emergency visits and need for medical resources when the ambient particulate matter concentration rises.

Trends in ambient air pollution levels and PM2.5 chemical compositions in four Chinese cities from 1995 to 2017.

An in-depth analysis of the specific evolution of air pollution in a given city can provide a better understanding of the chronic effects of air pollution on human health. In this study, we reported trends in ambient concentrations of particulate matter (PM) and gaseous pollutants [sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3)] from 1995 to 2017 and PM2.5 composition for the period of 2000–2017 in Guangzhou, Wuhan, Chongqing, and Lanzhou. We provided socio-economic indicators to help explain the pollution trends. SO2 and PM (including PM10 and PM2.5) concentrations showed a downward trend in recent years with the most notable reduction in SO2 in Chongqing and PM2.5 in Guangzhou. There was an overall flat trend for NO2, while O3 showed an upward trend in recent years except in Lanzhou. The majority of PM2.5 mass was SO42− (6.0–30 µg/m3) and organic carbon (6.0–38 µg/m3), followed by NO3− (2.0–12 µg/m3), elemental carbon (2.1–12 µg/m3), NH4+ (1.0–10 µg/m3), K+ (0.2–2.0 µg/m3), and Cl− (0.2–1.9 µg/m3). Except for secondary inorganic aerosols in Wuhan, annual average concentrations of all PM2.5 constituents showed a declining trend after 2013, corresponding to the trend of PM2.5. The secondary sources in PM2.5 were found to be most prominent in Wuhan, while the most abundant EC and Cl− in Lanzhou was attributed to the use of coal. Despite temporal and spatial variabilities across the four cities, coal combustion, traffic emissions, and secondary pollution have been the major sources of PM2.5 pollution. These trends in ambient air pollution levels and PM2.5 composition may help understand changes in health outcomes measured at different times within the time period of 1995–2017 in the four cities.

The Grass Is Always Greener on My Side: A Field Experiment Examining the Home Halo Effect

Wood-burning pollution is a severe problem in southern Chile, where every winter, people are exposed to unhealthy ambient fine particulate matter (PM2.5) concentrations. Urban air quality is a major concern for health officials, but public awareness campaigns tend to focus on outdoor hazards. Our understanding of how residents are exposed and perceive air pollution risks in their homes remains incomplete. This study explores the ability of participants to perceive indoor air quality. We collected data on 81 households, combining perceptions of air quality with objective measurements of PM2.5. Residents’ evaluations of air quality were systematically compared to inspectors’ evaluations in order to examine the home halo effect. We found that residents tended to overestimate air quality in their homes. We discuss how our data supported the existence of a home halo effect, but also point out the possibility that individuals’ ability to perceive air quality in indoor spaces is limited by other factors.

Decrease in Ambient Fine Particulate Matter during COVID-19 Crisis and Corresponding Health Benefits in Seoul, Korea.

Both domestic emissions and transported pollutants from neighboring countries affect the ambient fine particulate matter (PM2.5) concentration of Seoul, Korea. Diverse measures to control the coronavirus disease 2019 (COVID-19), such as social distancing and increased telecommuting in Korea and the stringent lockdown measures of China, may reduce domestic emissions and levels of transported pollutants, respectively. In addition, wearing a particulate-filtering respirator may have decreased the absolute PM2.5 exposure level for individuals. Therefore, this study estimated the acute health benefits of PM2.5 reduction and changes in public behavior during the COVID-19 crisis in Seoul, Korea. To calculate the mortality burden attributable to PM2.5, we obtained residents’ registration data, mortality data, and air pollution monitoring data for Seoul from publicly available databases. Relative risks were derived from previous time-series studies. We used the attributable fraction to estimate the number of excessive deaths attributable to acute PM2.5 exposure during January to April, yearly, from 2016 to 2020, and the number of mortalities avoided from PM2.5 reduction and respirator use observed in 2020. The average PM2.5 concentration from January to April in 2020 (25.6 μg/m3) was the lowest in the last 5 years. At least −4.1 μg/m3 (95% CI: −7.2, −0.9) change in ambient PM2.5 in Seoul was observed in 2020 compared to the previous 4 years. Overall, 37.6 (95% CI: 32.6, 42.5) non-accidental; 7.0 (95% CI: 5.7, 8.4) cardiovascular; and 4.7 (95% CI: 3.4, 6.1) respiratory mortalities were avoided due to PM2.5 reduction in 2020. By considering the effects of particulate respirator, decreases of 102.5 (95% CI: 89.0, 115.9) non-accidental; 19.1 (95% CI: 15.6, 22.9) cardiovascular; and 12.9 (95% CI: 9.2, 16.5) respiratory mortalities were estimated. We estimated that 37 lives were saved due to the PM2.5 reduction related to COVID-19 in Seoul, Korea. The health benefit may be greater due to the popular use of particulate-filtering respirators during the COVID-19 crisis. Future studies with daily mortality data are needed to verify our study estimates.

Predicting Photovoltaic Soiling From Air Quality Measurements

Ambient particulate matter in urban environments is dynamic and heterogeneous; therefore, understanding photovoltaic energy loss due to soiling is challenging. Silicon reference cells were deployed in an urban-industrial area in Colorado colocated with measurements of ambient particulate matter concentrations. Regressing measured soiling ratios against cumulative sums of ambient coarse particulate matter since the last precipitation event and ambient fine particulate matter since the first day of deployment produces a root-mean-square error of approximately 0.013. This model partially addresses the challenge of quantifying the relationships between ambient air quality and photovoltaic soiling.

Quantifying the impact of particle matter on mortality and hospitalizations in four Brazilian metropolitan areas

Air quality management involves investigating areas where pollutant concentrations are above guideline or standard values to minimize its effect on human health. Particulate matter (PM) is one of the most studied pollutants, and its relationship with health has been widely outlined. To guide the construction and improvement of air quality policies, the impact of PM on the four Brazilian southeast metropolitan areas was investigated. One-year long modeling of PM10 and PM2.5 was performed with the WRF-Chem model for 2015 to quantify daily and annual PM concentrations in 102 cities. Avoidable mortality due to diverse causes and morbidity due to respiratory and circular system diseases were estimated concerning WHO guidelines, which was adopted in Brazil as a final standard to be reached in the future; although there is no deadline set for its implementation yet. Results showed satisfactory representation of meteorology and ambient PM concentrations. An overestimation in PM concentrations for some monitoring stations was observed, mainly in São Paulo metropolitan area. Cities around capitals with high modelled annual PM2.5 concentrations do not monitor this pollutant. The total avoidable deaths estimated for the region, related to PM2.5, were 32,000 ± 5,300 due to all-cause mortality, between 16,000 ± 2,100 and 51,000 ± 3,000 due non-accidental causes, between 7,300 ± 1,300 and 16,700 ± 1,500 due to cardiovascular disease, between 4,750 ± 900 and 10,950 ± 870 due ischemic heart diseases and 1,220 ± 330 avoidable deaths due to lung cancer. Avoidable respiratory hospitalizations were greater for PM2.5 among ‘children’ age group than for PM10 (all age group) except in São Paulo metropolitan area. For circulatory system diseases, 9,840 ± 3,950 avoidable hospitalizations in the elderly related to a decrease in PM2.5 concentrations were estimated. This study endorses that more restrictive air quality standards, human exposure, and health effects are essential factors to consider in urban air quality management.