Ambient Particulate Matter Concentrations Research Articles

Evaluation of Ambient Air Quality Levels at Various Locations within Lead City University, Ibadan

Universities are big metropolitan institutions with sizable populations of students, employees, and visitors. However, university settings can contribute to air pollution, with diverse activities such as lab work, cooking in dorms, and vehicle traffic, among others, causing interior and ambient air pollution. It is impossible to overestimate how much air pollution affects the health and happiness of students. Based on this, evaluation of ambient air quality (i.e., temperature, relative humidity (RH), CO2, and particulate matter (PM2.5)) at various locations within Lead City University, Ibadan, is essential. Ambient concentrations of carbon monoxide (CO), carbon dioxide (CO2), relative humidity (RH), temperature (TEMP), and particulate matter (PM) were recorded from 15 locations across Lead City University over a two-week period. Morning temperatures in all the locations measured ranged from 23.7°C to 29.2°C, while afternoon temperatures fluctuated more significantly, with the lowest recorded at 27.2°C and the highest at a notably warmer 35.8°C in all the locations measured. The morning RH levels ranged from 63.8% to 74.7%, while afternoon RH values ranged from 58.2% to 63.4%. The findings also show that afternoon CO2 levels range from 468.5 ppm to 971.6 ppm, with Location 13 having an unusually high average. Morning CO levels ranged from 4.1 µg/m³ to 49 µg/m³, with location 13 showing an outlier at 184.2 µg/m³. CO2 and CO levels are mostly within acceptable ranges. Conclusively, variability in these parameters has implications for human health; therefore, adequate ventilation and pollution control measures are thereby recommended for the university management in order to improve indoor air quality.

Examining UV Radiation Patterns in Relation to Particulate Matter and Atmospheric Conditions in Arid, Unclouded Skies

This study investigates the influences of air temperature (T), relative humidity (RH), wind speed (WS), clearance index (KT), particulate matter (PM) concentrations (PM10 and PM2.5), and aerosol optical depth (AOD) on ultraviolet (UV) radiation during clear skies in Riyadh, central Saudi Arabia. The observational dataset utilized in this study comprises global solar radiation (G), UVA radiation, AOD measurements, and PM concentrations. The data were collected from 2014 to 2015 at the King Abdulaziz City for Science and Technology (KACST) campus in Riyadh. Regression analyses were conducted to investigate the relationships between UV radiation and the considered variables. The methodology is based on the least square method and associated statistical tests. The findings of this study provide valuable insights into the impacts of meteorological variables and aerosols on UV radiation, contributing to the understanding of environmental and industrial applications in the Arabian Peninsula. The analyses showed that the strengths and magnitudes differed from one variable to another. No significant correlations between UVA radiation (315–400 nm) and hourly and daily values of PM2.5 were found. Moreover, no significant correlations were seen between daily values of the UVA radiation and RH and between the UVB (280–315 nm) and PM10. The rest of the correlations (between UV radiation and the PM10 and meteorological variables) were found to be significant. While WS, the ratio of the PM concentrations (PM2.5/PM10), KT, and T exhibited positive correlations with UV radiation, the rest of the variables had anti-correlations with UV radiation. The influences of T, WS, and RH on ambient PM concentrations during the considered period were taken into account, and it was found that the PM concentrations correlate, with different magnitudes and strengths, positively with T and negatively with RH and WS.

Association between exposure to ambient air pollution, meteorological factors and atopic dermatitis consultations in Singapore—a stratified nationwide time-series analysis

Atopic dermatitis (AD) is a chronic inflammatory skin disease affecting approximately 20% of children globally. While studies have been conducted elsewhere, air pollution and weather variability is not well studied in the tropics. This time-series study examines the association between air pollution and meteorological factors with the incidence of outpatient visits for AD obtained from the National Skin Centre (NSC) in Singapore. The total number of 1,440,844 consultation visits from the NSC from 2009 to 2019 was analysed. Using the distributed lag non-linear model and assuming a negative binomial distribution, the short-term temporal association between outpatient visits for AD and air quality and meteorological variability on a weekly time-scale were examined, while adjusting for long-term trends, seasonality and autocorrelation. The analysis was also stratified by gender and age to assess potential effect modification. The risk of AD consultation visits was 14% lower (RR10th percentile: 0.86, 95% CI 0.78–0.96) at the 10th percentile (11.9 µg/m3) of PM2.5 and 10% higher (RR90th percentile: 1.10, 95% CI 1.01–1.19) at the 90th percentile (24.4 µg/m3) compared to the median value (16.1 µg/m3). Similar results were observed for PM10 with lower risk at the 10th percentile and higher risk at the 90th percentile (RR10th percentile: 0.86, 95% CI 0.78–0.95, RR90th percentile: 1.10, 95% CI 1.01–1.19). For rainfall for values above the median, the risk of consultation visits was higher up to 7.4 mm in the PM2.5 model (RR74th percentile: 1.07, 95% CI 1.00–1.14) and up to 9 mm in the PM10 model (RR80th percentile: 1.12, 95% CI 1.00–1.25). This study found a close association between outpatient visits for AD with ambient particulate matter concentrations and rainfall. Seasonal variations in particulate matter and rainfall may be used to alert healthcare providers on the anticipated rise in AD cases and to time preventive measures to reduce the associated health burden.

The Long Hazy Tail: Analysis of the Impacts and Trends of Severe Outdoor and Indoor Air Pollution in North China.

China, especially the densely populated North China region, experienced severe haze events in the past decade that concerned the public. Although the most extreme cases have been largely eliminated through recent mitigation measures, severe outdoor air pollution persists and its environmental impact needs to be understood. Severe indoor pollution draws less public attention due to the short visible distance indoors, but its public health impacts cannot be ignored. Herein, we assess the trends and impacts of severe outdoor and indoor air pollution in North China from 2014 to 2021. Our results demonstrate the uneven contribution of severe hazy days to ambient and exposure concentrations of particulate matter with an aerodynamic diameter <2.5 (PM2.5). Although severe indoor pollution contributes to indoor PM2.5 concentrations (23%) to a similar extent as severe haze contributes to ambient PM2.5 concentrations (21%), the former's contribution to premature deaths was significantly higher. Furthermore, residential emissions contributed more in the higher PM2.5 concentration range both indoors and outdoors. Notably, severe haze had greater health impacts on urban residents, while severe indoor pollution was more impactful in rural areas. Our findings suggest that, besides reducing severe haze, mitigating severe indoor pollution is an important aspect of combating air pollution, especially toward improving public health.

Chemical composition and source apportionment of PM2.5 in Seoul during 2018–2020

Air pollution, particularly high ambient particulate matter (PM) concentrations, poses a serious public health concern in South Korea. This study analyzed 139 daily PM2.5 samples collected from an urban site in Seoul between March 2018 and January 2020. This study aimed to quantify the chemical composition of PM2.5 and identify the source characteristics. The average PM2.5 mass concentration for the entire study period was 25.3 μg m−3. The chemical composition was dominated by ionic particles (13.2 μg m−3, 52%), carbonaceous particles (7.0 μg m−3, 28%), and trace elements (0.5 μg m−3, 2%). The Positive Matrix Factorization (PMF) model was employed to identify PM2.5 sources using quality-controlled sampling data after eliminating factors that could adversely affect the modeling. Seven sources were resolved through PMF, applying a trial-and-error method to determine the optimal number of sources. The PMF modeling results indicated that secondary sulfate (28%) was the largest contributor, followed by internal factors (23%), secondary nitrate (19%), soil (14%), biomass burning (9%), and aged sea salt (7%). As an additional case study, the analysis of backward trajectories for the winter of 2018, which had the highest PM2.5 concentrations, revealed that the air current carrying PM2.5 had passed from the northwest region of Seoul. Particulary, source identification for this winter case resulted in the highest secondary nitrate across all study periods. This more specific interpretation of the pollutant characteristics of PM2.5 in Seoul could aid in developing effective control strategies and policies for air pollution mitigation.

Environmental and social inequities in continental France: an analysis of exposure to heat, air pollution, and lack of vegetation.

Cumulative environmental exposures and social deprivation increase health vulnerability and limit the capacity of populations to adapt to climate change. Our study aimed at providing a fine-scale characterization of exposure to heat, air pollution, and lack of vegetation in continental France between 2000 and 2018, describing spatiotemporal trends and environmental hotspots (i.e., areas that cumulate the highest levels of overexposure), and exploring any associations with social deprivation. The European (EDI) and French (FDep) social deprivation indices, the normalized difference vegetation index, daily ambient temperatures, particulate matter (PM2.5 and PM10), nitrogen dioxide, and ozone (O3) concentrations were estimated for 48,185 French census districts. Reference values were chosen to characterize (over-)exposure. Hotspots were defined as the areas cumulating the highest overexposure to temperature, air pollution, and lack of vegetation. Associations between heat overexposure or hotspots and social deprivation were assessed using logistic regressions. Overexposure to heat was higher in 2015-2018 compared with 2000-2014. Exposure to all air pollutants except for O3 decreased during the study period. In 2018, more than 79% of the urban census districts exceeded the 2021 WHO air quality guidelines. The evolution of vegetation density between 2000 and 2018 was heterogeneous across continental France. In urban areas, the most deprived census districts were at a higher risk of being hotspots (odds ratio (OR): 10.86, 95% CI: 9.87-11.98 using EDI and OR: 1.07, 95% CI: 1.04-1.11 using FDep). We studied cumulative environmental exposures and social deprivation in French census districts. The 2015-2018 period showed the highest overexposure to heat between 2000 and 2018. In 2018, the air quality did not meet the 2021 WHO guidelines in most census districts and 8.6 million people lived in environmental hotspots. Highly socially deprived urban areas had a higher risk of being in a hotspot. This study proposes for the first time, a methodology to identify hotspots of exposure to heat, air pollution, and lack of vegetation and their associations with social deprivation at a national level.

Light-Duty Vehicle Brake Emission Factors

Particulate Matter (PM) air pollution has been linked to major adverse health effects. Road transport still contributes significantly to ambient PM concentrations, but mainly due to the non-exhaust emissions from vehicles. For the first time worldwide, limits for non-exhaust emissions have been proposed by the European Union for the upcoming Euro 7 step. For these reasons, interest in brake emissions has increased in the past few years. Realistic emission factors are necessary to accurately calculate the contribution of brake emissions to air pollution but also to estimate the emissions reduction potential of new or existing technologies and improved brake formulations. This paper reviews emission factors from light-duty vehicles reported in the literature, with a focus on those that followed the recently introduced Global Technical Regulation (GTR 24) methodology on brakes in light-duty vehicles. Reduction efficiencies of non-asbestos organic (NAO) pads, brake dust filters, ceramic discs, coated discs, and regenerative braking are also discussed. Finally, the emission factors are compared with roadside measurements of brake emissions and emission inventories worldwide. The findings of this study can be used as an input in emission inventories to estimate the contribution of brakes to air pollution.

High ambient air pollution erodes the benefits of using clean cooking fuel in preventing low birth weight in India

A large fraction of the population in rural India continues to use biomass fuel for cooking and heating. In-utero exposure to the resulting household air pollution (HAP), is known to increase the risk of low birth weight (LBW). Mitigating HAP, by shifting to clean cooking fuel (CCF), is expected to minimize the risk associated with LBW. However, India also has high levels of ambient air pollution (AAP). Whether exposure to AAP modifies the effect of reducing HAP by switching to CCF on LBW is not known. The present study addressed this knowledge gap by analyzing the National Family Health Survey (2019–21) data of the most recent full-term, singleton, live births from rural households born after 2017 (n = 56 000). In-utero exposure to AAP was calculated from satellite-derived ambient fine particulate matter (PM2.5) concentration at the level of the primary sampling unit for the pregnancy duration of the mothers. The moderation by ambient PM2.5 level on the odds of LBW among CCF users was examined by logistic regression analysis with interaction. The adjusted odds ratio (aOR) of LBW was 7% lower among users of CCF. At the lowest Decile (20–37 μg m−3) of ambient PM2.5 exposure, the aOR of LBW among CCF users was 0.83 (95% CI:0.81–0.85). At every 10th percentile increase in ambient PM2.5 exposure (in the range 21–144 μg m−3), aOR increased gradually, reaching the value of 1 at PM2.5 level of 93 μg m−3. Our results, therefore, suggest that the benefit of using CCF during pregnancy may be downgraded by moderate to high ambient PM2.5 exposure.

Gauging Size Resolved Ambient Particulate Matter Concentration Solely Using Biometric Observations: A Machine Learning and Causal Approach

Human physiology responds to external environmental stimuli across different time scales. Long-term exposure to heat, air pollution, and volatile organic compounds has documented adverse effects on human health. Our previous work established that autonomic responses of the human body, collected from biometric sensors on a single subject, can successfully empirically model the concentration of particulate matter (PM) in the surrounding microenvironment. In this study, we demonstrate that this relationship holds across multiple observations involving multiple participants. Each subject rode a stationary bike outdoors while adorned with various biometric sensors, and the im- mediate environment around the subject was also captured through an array of environmental sensors. With additional data, Machine Learning (ML) models were able to predict PM concentrations (PM 2.5 at = 0.97) with only a handful of easily accessible biometric fea- tures, such as skin temperature, heart rate, and respiration rate. The causal perspective explored highlights the importance of physiological responses as indicators of exposure to particulate matter, providing a basis for the use of biometric data in environmental health surveillance and real-time pollution assessment.

The effects of the COVID-19 pandemic on PICU admissions for severe asthma exacerbations: Asingle-center experience.

The incidence of severe asthma exacerbations (SAE)requiring a pediatric intensive care unit (PICU)admission during the coronavirus disease 2019 (COVID-19) pandemic (and its association with public restrictions) is largely unknown. We examined the trend of SAE requiring PICU admission before, during, and after COVID-19restrictions in Amsterdam, the Netherlands, and its relationship with features such as environmental triggers and changes in COVID-19restriction measures. In this single-center, retrospective cohort study, all PICU admissions of children aged ≥2 years for severe asthma at the Amsterdam UMC between 2018 and 2022 were included. The concentrations of ambient fine particulate matter (PM2.5 ) and pollen were obtained from official monitoring stations. Between January 2018 and December 2022, 228 children were admitted to the PICU of the Amsterdam UMC for SAE. While we observed a decrease in admissions during periods of more stringent restriction, there was an increase in the PICU admission rate for SAE in some periods following the lifting of restrictions. In particular, following the COVID-19restrictions in 2021, we observed a peak incidence of admissions from August to November, which was higher than any other peak during the indicated years. No association with air pollution or pollen was observed. We hypothesize that an increase in clinically diagnosed viral infections after lockdown periods was the reason for the altered incidence of SAE at the PICU in late 2021, rather than air pollution and pollen concentrations.

Particulate Air Pollution and Blood Pressure: Signaling by the Arachidonate Metabolism.

Short-term exposure to ambient particulate matter (PM) can raise blood pressure, but the underlying mechanisms are unclear. We explored whether arachidonate metabolites serve as biological intermediates in PM-associated prohypertensive changes. This panel study recruited 110 adults aged 50 to 65 years living in Beijing, China. The participants' blood pressure, arterial stiffness, and cardiac and endothelial function were measured up to 7 times. The serum concentrations of arachidonate metabolites were quantified by targeted lipidomics. Ambient concentrations of fine PM (PM2.5), black carbon, and accumulation mode particles were continuously monitored at a station and their associations with the health indicators were evaluated. Interquartile range increases in 25 to 96-hour-lag exposure to PM2.5, black carbon, and accumulation mode particles were associated with significant increases in systolic blood pressure (brachial: 0.8-3.2 mm Hg; central: 0.7-2.8 mm Hg) and diastolic blood pressure (brachial, 0.5-1.5 mm Hg; central, 0.5-1.6 mm Hg). At least 1 pollutant was associated with increases in augmentation pressure and heart rate and decreases in reactive hyperemia index and ejection time. The serum concentrations of arachidonate were significantly increased by 3.3% to 14.6% in association with PM exposure, which mediated 9% of the PM-associated increases in blood pressure. The levels of eicosanoids from the cytochrome P450, cyclooxygenase, and lipoxygenase pathways changed with PM exposure, and those from the cytochrome pathway significantly mediated the association between PM exposure and blood pressure. Short-term exposure to particulate air pollution was associated with a prohypertensive change in adults, which was in part mediated by alteration of arachidonate metabolism.

Air pollution and fecundability in a North American preconception cohort study

BackgroundAnimal and epidemiologic studies indicate that air pollution may adversely affect fertility. However, the level of evidence is limited and specific pollutants driving the association are inconsistent across studies. MethodsWe used data from a web-based preconception cohort study of pregnancy planners enrolled during 2013–2019 (Pregnancy Study Online; PRESTO). Eligible participants self-identified as female, were aged 21–45 years, resided in the United States (U.S.) or Canada, and were trying to conceive without fertility treatments. Participants completed a baseline questionnaire and bi-monthly follow-up questionnaires until conception or 12 months. We analyzed data from 8,747 participants (U.S.: 7,304; Canada: 1,443) who had been trying to conceive for < 12 cycles at enrollment. We estimated residential ambient concentrations of particulate matter < 2.5 µm (PM2.5), nitrogen dioxide (NO2), and ozone (O3) using validated spatiotemporal models specific to each country. We fit country-specific proportional probabilities regression models to estimate the association between annual average, menstrual cycle-specific, and preconception average pollutant concentrations with fecundability, the per-cycle probability of conception. We calculated fecundability ratios (FRs) and 95% confidence intervals (CIs) and adjusted for individual- and neighborhood-level confounders. ResultsIn the U.S., the FRs for a 5-µg/m3 increase in annual average, cycle-specific, and preconception average PM2.5 concentrations were 0.94 (95% CI: 0.83, 1.08), 1.00 (95% CI: 0.93, 1.07), and 1.00 (95% CI: 0.93, 1.09), respectively. In Canada, the corresponding FRs were 0.92 (95% CI: 0.74, 1.16), 0.97 (95% CI: 0.87, 1.09), and 0.94 (95% CI: 0.80, 1.09), respectively. Likewise, NO2 and O3 concentrations were not strongly associated with fecundability in either country. ConclusionsNeither annual average, menstrual cycle-specific, nor preconception average exposure to ambient PM2.5, NO2, and O3 were appreciably associated with reduced fecundability in this cohort of pregnancy planners.

Air pollution and suicide in rural and urban America: Evidence from wildfire smoke

Air pollution poses well-established risks to physical health, but little is known about its effects on mental health. We study the relationship between wildfire smoke exposure and suicide risk in the United States in 2007 to 2019 using data on all deaths by suicide and satellite-based measures of wildfire smoke and ambient fine particulate matter (PM2.5) concentrations. We identify the causal effects of wildfire smoke pollution on suicide by relating year-over-year fluctuations in county-level monthly smoke exposure to fluctuations in suicide rates and compare the effects across local areas and demographic groups that differ considerably in their baseline suicide risk. In rural counties, an additional day of smoke increases monthly mean PM2.5 by 0.41 μg/m3 and suicide deaths by 0.11 per million residents, such that a 1-μg/m3 (13%) increase in monthly wildfire-derived fine particulate matter leads to 0.27 additional suicide deaths per million residents (a 2.0% increase). These effects are concentrated among demographic groups with both high baseline suicide risk and high exposure to outdoor air: men, working-age adults, non-Hispanic Whites, and adults with no college education. By contrast, we find no evidence that smoke pollution increases suicide risk among any urban demographic group. This study provides large-scale evidence that air pollution elevates the risk of suicide, disproportionately so among rural populations.

Racial/ethnic disparities in PM2.5-attributable cardiovascular mortality burden in the United States.

Average ambient fine particulate matter (PM2.5) concentrations have decreased in the US in recent years, but the health benefits of this improvement among different racial/ethnic groups are unknown. We estimate the associations between long-term exposure to ambient PM2.5 and cause-specific cardiovascular disease (CVD) mortality rate and assess the PM2.5-attributable CVD deaths by race/ethnicity across 3,103 US counties during 2001-2016 (n = 595,776 county-months). A 1 µg m-3 increase in PM2.5 concentration was associated with increases of 7.16 (95% confidence interval (CI): 3.81, 10.51) CVD deaths per 1,000,000 Black people per month, significantly higher than the estimates for non-Hispanic white people (1.76 (95% CI: 1.37, 2.15); difference in coefficients: 5.40 (95% CI: 2.03, 8.77), P = 0.001). No significant difference in this association was observed between Hispanic (2.66 (95% CI: -0.03, 5.35)) and non-Hispanic white people (difference in coefficients: 0.90 (95% CI: -1.81, 3.61), P = 0.523). From 2001 to 2016, the absolute disparity in PM2.5-attributable CVD mortality burden was reduced by 44.04% between non-Hispanic Black and white people and by 2.61% between Hispanic and non-Hispanic white people. However, in 2016, the burden remained 3.47 times higher for non-Hispanic Black people and 0.45 times higher for Hispanic people than for non-Hispanic white people. We call for policies that aim to reduce both exposure and vulnerability to PM2.5 for racial/ethnic minorities.

Using Low-Cost Sensing Technology to Assess Ambient and Indoor Fine Particulate Matter Concentrations in New York during the COVID-19 Lockdown

Air pollution is a leading cause of death in the United States and is associated with adverse health outcomes, including increased vulnerability to coronavirus disease 2019 (COVID-19). The AirBeam2 was used to measure particulate matter with a diameter of 2.5 μm or smaller (PM2.5) to investigate differences between indoor and ambient levels at seven private homes in New York during and after the COVID-19 lockdown. Measurements taken in 2020 fall, 2021 winter, and 2022 fall showed that at 90% of the sites, indoor PM2.5 levels exceeded outdoor levels both during and after the COVID-19 lockdown, p = 0.03, possibly exceeding safety levels. Higher indoor PM2.5 levels attributed to little or no ventilation in the basement and kitchens from cooking and smoke were greater in fall than in winter. Higher ambient PM2.5 levels were attributed to vehicular traffic at a street-facing sampling site. PM2.5 sources identified in this study may help in devising control strategies to improve indoor air quality (IAQ) and consequently alleviate respiratory health effects. These findings may be used as a basis for in-house modifications, including natural ventilation and the use of air purifiers to reduce exposures, mitigate future risks, and prevent potential harm to vulnerable residents.

Association between ambient air particulate matter and human health impacts in northern Thailand

Air pollution in Thailand is regarded as a serious health threat, especially in the northern region. High levels of particulate matter (PM2.5 and PM10) are strongly linked to severe health consequences and mortality. This study analyzed the relationship between exposure to ambient concentrations of PM2.5 and PM10 by using data from the Pollution Control Department of Thailand and the burden of disease due to an increase in the ambient particulate matter concentrations in northern Thailand. This study was conducted using the Life Cycle Assessment methodology considering the human health damage impact category in the ReCiPe 2016 method. The results revealed that the annual average years of life lived with disability from ambient PM2.5 in northern Thailand is about 41,372 years, while from PM10 it is about 59,064 years per 100,000 population. The number of deaths from lung cancer and cardiopulmonary diseases caused by PM2.5 were approximately 0.04% and 0.06% of the population of northern Thailand, respectively. Deaths due to lung cancer and cardiopulmonary diseases caused by PM10, on the other hand, were approximately 0.06% and 0.08%, respectively. The findings expressed the actual severity of the impact of air pollution on human health. It can provide valuable insights for organizations in setting strategies to address air pollution. Organizations can build well-informed strategies and turn them into legal plans by exploiting the study’s findings. This ensures that their efforts to tackle air pollution are successful, in accordance with regulations, and contribute to a healthier, more sustainable future guidelines on appropriate practices of air pollution act/policy linkage with climate change mitigation.

Per- and polyfluoroalkyl substances in ambient fine particulate matter in the Pearl River Delta, China: Levels, distribution and health implications

Per- and polyfluoroalkyl substances (PFAS) have attracted worldwide attention as one of persistent organic pollutants; however, there is limited knowledge about the exposure concentrations of PFAS-contained ambient particulate matter and the related health risks. This study investigated the abundance and distribution of 32 PFAS in fine particulate matter (PM2.5) collected from 93 primary or secondary schools across the Pearl River Delta region (PRD), China. These chemicals comprise four PFAS categories which includes perfluoroalkyl carboxylic acids (PFCAs), perfluoroalkyl sulfonic acids (PFSAs), perfluoroalkyl acid (PFAA) precursors and PFAS alternatives. In general, concentrations of target PFAS ranged from 11.52 to 419.72 pg/m3 (median: 57.29 pg/m3) across sites. By categories, concentrations of PFSAs (median: 26.05 pg/m3) were the dominant PFAS categories, followed by PFCAs (14.25 pg/m3), PFAS alternatives (2.75 pg/m3) and PFAA precursors (1.10 pg/m3). By individual PFAS, PFOS and PFOA were the dominant PFAS, which average concentration were 24.18 pg/m3 and 6.05 pg/m3, respectively. Seasonal variation showed that the concentrations of PFCAs and PFSAs were higher in winter than in summer, whereas opposite seasonal trends were observed in PFAA precursors and PFAS alternatives. Estimated daily intake (EDI) and hazard quotient (HQ) were used to assess human inhalation-based exposure risks to PFAS. Although the health risks of PFAS via inhalation were insignificant (HQ far less than one), sufficient attention should be levied to ascertain the human exposure risks through inhalation, given that exposure to PFAS through air inhalation is a long term and cumulative process.

Understanding the time-activity pattern to improve the measurement of personal exposure: An exploratory and experimental research

Although ambient fine particulate matter (PM2.5) concentrations and their components are commonly used as proxies for personal exposure monitoring, developing an accurate and cost-effective method to use these proxies for personal exposure measurement continues to pose a significant challenge. Herein, we propose a scenario-based exposure model to precisely estimate personal exposure level of heavy metal(loid)s (HMs) using scenario HMs concentrations and time-activity patterns. Personal exposure levels and ambient pollution levels for PM2.5 and HMs differed significantly with corresponding personal/ambient ratios of approximately 2, and exposure scenarios could narrow the assessment error gap by 26.1–45.4%. Using a scenario-based exposure model, we assessed the associated health risks of a large sample population and identified that the carcinogenic risk of As exceeded 1 × 10−6, while we observed non-carcinogenic risks from As, Cd, Ni, and Mn in personal exposure to PM2.5. We conclude that the scenario-based exposure model is a preferential alternative for monitoring personal exposure compared to ambient concentrations. This method ensures the feasibility of personal exposure monitoring and health risk assessments in large-scale studies.

Effects of Gas and Steam Humidity on Particulate Matter Measurements Obtained Using Light-Scattering Sensors.

With the increasing need for particulate matter (PM) monitoring, the demand for light-scattering sensors that allow for real-time measurements of PM is increasing. This light-scattering method involves irradiating light to the aerosols in the atmosphere to analyze the scattered light and measure mass concentrations. Humidity affects the measurement results. The humidity in an outdoor environment may exist as gas or steam, such as fog. While the impact of humidity on the light-scattering measurement remains unclear, an accurate estimation of ambient PM concentration is a practical challenge. Therefore, this study investigated the effects of humidity on light-scattering measurements by analyzing the variation in the PM concentration measured by the sensor when relative humidity was due to gaseous and steam vapor. The gaseous humidity did not cause errors in the PM measurements via the light-scattering method. In contrast, steam humidity, such as that caused by fog, resulted in errors in the PM measurement. The results help determine the factors to be considered before applying a light-scattering sensor in an outdoor environment. Based on these factors, directions for technological development can be presented regarding the correction of measurement errors induced by vapor in outdoor environments.

Ten Years Behavior of Carbonaceous Ultrafine Particulate Matter (PM0.1) in Phnom Penh, Cambodia

The long-term behavior of mass concentration of ambient ultrafine particulate matter was discussed on samples collected at a site located in Phnom Penh City, Cambodia, between 2011-2020. A cascade air sampler that can collect PM0.1 (<0.1 μm) has been used at a site located on a roof floor of a 5-story building on the campus of the Institute of Technology of Cambodia (ITC) located near the central part of Phnom Penh City. The main goal was to investigate PM0.1 and carbon compositions, including elemental carbon (EC) and organic carbon (OC). As a result, PM0.1 increased by about 2.3 times, and PM0.1 remarkably increased in the past ten years. EC and soot-EC, which are considered to be road traffic sources, also increase PM0.1 mass concentration. Soot-EC and the number of vehicles per year are correlated. Biomass burning indicators such as OC, char-EC, and hot spots number increase at the same time. Consequently, it is considered that the dry season (January to March) is greatly affected by open fires in Cambodia and neighboring countries.