Ambient Levels Of PM2 Research Articles

Causes of the unremitting high ambient levels of PM10 in a suburban background site in NE Spain

Atmospheric PM10 and benzo(a)pyrene (BaP) concentrations in Manlleu (NE Spain) have remained high from 2008 to 2023, frequently exceeding EU limit/target values, and reaching BaP levels up to six times higher than urban averages in Spain. Furthermore, PM speciation campaigns were carried out in 2013, 2014–2015, 2016–2017 and 2021–2022. Chemical mass closure for autumn-winter showed a consistent PM10 composition for the different PM speciation campaigns, comprising 46–53% organic matter (OM), 18–26% secondary inorganic aerosol (SIA), 13–23% mineral matter (MM), and 5–9% elemental carbon (EC). Trend analysis revealed very light decrease and constant concentrations for PM10 and BaP, respectively over the study period, emphasizing the need for compliance with current and forthcoming EU air quality directives, the last aiming to halve PM10 limit values. Source apportionment of samples of the sporadic campaigns identified biomass burning (BB, 17.5 μg m−3, 48%) and MM and industry (16.3 μg m−3, 44%) as the main autumn-winter PM10 contributors, with high SIA concentrations attributed to several factors, including high ammonia (NH3) emissions. Local topography and meteorological conditions contribute to aggravate PM10 pollution. While metal concentrations have decreased since 2013, suggesting reduced industrial emissions, persistently high OM and EC concentrations indicate ongoing issues with BB emissions from domestic, commercial, and agricultural sources. Online analysis of black carbon (BC) and non-refractory PM1 components during winter 2016–2017 confirmed domestic and commercial BB as the primary sources of the BB contributions. These findings highlight the need of the implementation of more effective measures in reducing BB and agricultural/farming NH3 emissions. This study highlights the relevance of these issues for similar towns, the probable unremitting problem over the last decade, and the necessity of enhanced monitoring in small cities and policy actions to meet air quality standards under the new EU directive.

Human health impacts attributable to inhalation exposure of particulate matter (PM10 and PM2.5) during the Holi festival

Objective The present study focuses on residential areas of Delhi to identify the elevated levels of ambient PM10 and PM2.5 due to biomass burning followed by the coloring activity in the Holi festival celebrated at the end of the winter season. This study also focuses on the health risk assessment and mortality among different age groups due to the change in particulate matter levels during the Holi festival in Delhi, India. Materials and Methods Secondary data of particulate matters have been procured from the Central Pollution Control Board (CPCB), Delhi Pollution Control Committee (DPCC), and Indian Institute of Tropical Meteorology (IITM), Pune for the period of the pre-, during, and post-Holi period for the year 2018-2020 at four selected residential locations in Delhi, India. The health impacts of particle inhalation were quantified using the AirQ + models. Results The results indicated the levels of PM10 and PM2.5 rise about 3-4 times higher during the Holi festival than on normal days, resulting in health risks and causing an excess number of mortality and Asthma cases in Delhi. Such cases were also found to be higher in 2018, followed by 2019 and 2020 at all the selected locations in Delhi. Conclusions The study linked the increasing particulate levels in the Holi festival with the increased health risk through short-term exposure of the population. The excess number of cases (ENCs) of mortality, all causes of mortality among adults (age > 30 years) associated with short-term exposure to particulate were also identified.

Direct Exposure to Outdoor Air Pollution Worsens the Functional Status of Stroke Patients Treated with Mechanical Thrombectomy

Background The effect of air pollutants on the functional status of stroke patients in short-term follow-up is unknown. The aim of this study was to evaluate the effect of air pollution occurring in the stroke period and during hospitalization on the functional status of patients undergoing mechanical thrombectomy (MT). Methods Our study included stroke patients for which the individual-level exposure to ambient levels of O3, CO, SO2, NO2, PM2.5, and PM10 during the acute stroke period was assessed. The correlations between the air pollutants’ concentration and the patients’ functional state were analyzed. A total of 499 stroke patients (mean age: 70) were qualified. Results The CO concentration at day of stroke onset was found to be significant regarding the functional state of patients on the 10th day (OR 0.014 95% CI 0–0.908, p = 0.048). The parameters which increased the risk of death in the first 10 days were as follows: NIHSS (OR 1.27; 95% CI 1.15–1.42; p < 0.001), intracranial bleeding (OR 4.08; 95% CI 1.75–9.76; p = 0.001), and SO2 concentration on day 2 (OR 1.21; 95% CI 1.02–1.47; p = 0.03). The parameters which increased the mortality rate within 90 days include age (OR 1.07; 95% CI 1.02–1.13; p = 0.005) and NIHSS (OR 1.37; 95% CI 1.19–1.63; p < 0.001). Conclusions Exposure to air pollution with CO and SO2 during the acute stroke phase has adverse effects on the patients’ functional status. A combination of parameters, such as neurological state, hemorrhagic transformation, and SO2 exposure, is unfavorable in terms of the risk of death during a hospitalization due to stroke. The risk of a worsened functional status of patients in the first month of stroke rises along with the increase in particulate matter concentrations within the first days of stroke.

Air pollution impacts of amine scrubbing for CO2 capture

The current political discussion in the United States around carbon capture and storage includes statements that suggest a need for a technical review to clarify the expected air pollution impacts of amine scrubbing. The Center for International Law and 50 other organizations published an open letter claiming that “CCS is not consistent with the principles of environmental justice… CCS makes dirty energy even more dangerous for frontline communities. Facilities equipped with carbon capture technology have to burn more fossil fuel to get the same energy output, resulting in increased emissions of toxic and hazardous pollutants, like fine particulates (PM2.5).”This paper reviews air pollutants produced by the use of amine scrubbing on coal- and gas-fired power plants in the U.S. and the process features and mitigation strategies that will minimize their impact on air quality. Even with atmospheric reactions, emissions of amine, nitrosamine, and other air toxics are likely to have insignificant environmental and health impacts. Stacks will disperse emissions with a dilution factor greater than 8000. Water wash with or without acid will reduce emissions of amine and nitrosamine that is produced from atmospheric reactions. Nitrosamine emissions will be managed with selective catalytic reduction (SCR) to reduce the NO/NO2 and/or selection of primary or non-volatile amines. With coal-fired power plants, amine aerosols, Hg, SO3, and fine particulate emissions will probably be managed by a fabric filter with alkali addition. Carbon capture by amine scrubbing will reduce significantly the effect of the power plant emissions on ambient levels of PM2.5. With coal-fired power plants, the application of amine scrubbing will significantly reduce SO2 emissions. NOx emissions will usually be minimized by selective catalytic reduction (SCR) in both gas- and coal-fired plants. Ammonia emissions will be minimized by managing amine oxidation, and if necessary, by adding an acid wash or other controls.

Exposure to air pollution concentrations of various intensities in early life and allergic sensitisation later in childhood

BackgroundEvidence on the relationship between air pollution and allergic sensitisation in childhood is inconsistent, and this relationship has not been investigated in the context of smoke events that are predicted to increase with climate change. Thus, we aimed to evaluate associations between exposure in two early life periods to severe levels of particulate matter with an aerodynamic diameter < 2.5 μm (PM2.5) from a mine fire, background PM2.5, and allergic sensitisation later in childhood.MethodsWe measured specific immunoglobulin E (IgE) levels for seven common aeroallergens as well as total IgE levels in a cohort of children who had been exposed to the Hazelwood coal mine fire, either in utero or during their first two years of life, in a regional area of Australia where ambient levels of PM2.5 are generally low. We estimated personal exposure to fire-specific emissions of PM2.5 based on a high-resolution meteorological and pollutant dispersion model and detailed reported movements of pregnant mothers and young children during the fire. We also estimated the usual background exposure to PM2.5 at the residential address at birth using a national satellite-based land-use regression model. Associations between both sources of PM2.5 and sensitisation to dust, cat, fungi, and grass seven years after the fire were estimated with logistic regression, while associations with total IgE levels were estimated with linear regression.ResultsNo association was found between the levels of exposure at either developmental stage to fire-related PM2.5 and allergic sensitisation seven years after the event. However, levels of background exposure were positively associated with sensitisation to dust (OR = 1.90, 95%CI = 1.12,3.21 per 1 μg/m3).ConclusionsChronic but low exposure to PM2.5 in early life could be more strongly associated with allergic sensitisation in childhood than time-limited high exposure levels, such as the ones experienced during landscape fires.

Health risk assessment of aerosol particles (PM2.5 and PM10) during winter crop at the agricultural site of Delhi, India.

For the last few decades, air pollution in developing country like India is increasing, and it is a matter of huge concern due to its associated human health impacts. In this region, the burgeoning population, escalating urbanization and industrialization, has been cited as the major reason for such a high air pollution. The present study was carried out for health risk assessment of aerosol particles (PM10 and PM2.5) and its associated heavy metals of an agriculture farm site at Indian Agricultural Research Institute (IARI) considered to be green urban area in Delhi, India. The concentrations of both PM10 and PM2.5 varied significantly from 136 to 177µg/m3 and 56 to 162µg/m3, respectively at the site. In the present case, the highest PM10 and PM2.5 levels were reported in January, followed by December. The levels of ambient PM10 and PM2.5 are influenced by wind prevailing meteorology. These levels of PM10 and PM2.5 are more than the permissible limits of WHO guidelines of 15 and 5µg/m3, respectively, thereby leading to high aerosol loadings specifically in winters. The PM concentration of the atmosphere was found to be negatively correlated with temperature during the sampling period. The concentrations of surface ozone O3 and NOx in the present study were observed to be high in February and March, respectively. The increasing air pollution in the city of Delhi poses a great risk to the human health, as the particulate matter loaded with heavy metals can enter humans via different pathways, viz., ingestion, inhalation, and absorption through skin. The mean hazard index for metals (Zn, Pb, Cd, As, Cr, and Ni) was observed within the acceptable limit (HI < 1), thereby indicating negligible non-carcinogenic effects to residing population. The carcinogenic risk assessment was conducted for Cd, Pb, and As only, as the concentrations for other metals were found to be quite low. The carcinogenic risk values were also within the limits of USEPA standards, indicating no carcinogenic risks to the health of children and adults residing near the site. This information about the PM pollution at the agricultural site and health risk assessment will serve as a baseline data in assessment of human health impacts due to air pollution at the local scale and can be used for development of mitigation strategies for tackling air pollution.

Background and baseline levels of PM2.5 and PM10 pollution in major cities of peninsular India

The pandemic-induced lockdown resulted in negligible anthropogenic emissions of particulate pollutants and provided an opportunity to estimate the baseline levels (to which people are chronically exposed) and the background levels (when internal emissions are negligible but external intrusions are ongoing). We report the baseline and background PM2.5 and PM10 levels in five major cities of peninsular India and compare them with the corresponding levels estimated for other parts of India. The baseline levels of PM2.5 and PM10 in these cities are estimated to be in the range of 5–15 μg/m3 and 15–43 μg/m3, respectively, whereas their background levels are 18–37 μg/m3 and 46–70 μg/m3, respectively. Although the ambient PM10 levels in Hyderabad and Vishakhapatnam are significantly lesser than in Delhi, the baseline levels in these cities are higher than in Delhi. In general, the baseline levels in Indian cities are higher than the WHO air quality guidelines. Human susceptibility to air pollution may vary based on age distribution, nutritional intake, access to health care, meteorological conditions, and any natural immunity. Therefore, this study will be useful to epidemiologists and policymakers to develop effective risk management policies and refine the national air quality standards.

The Role of International Maritime Traffic on PM10 Pollutant in the Strait of Istanbul (Bosphorus)

Today, over 90 percent of world trade is carried out via maritime transportation by 90,000 vessels. Like all modes of transportation that use fossil fuels, ship emissions that significantly contribute to global climate change and acidification. In this aspect, the shipping industry is responsible for a significant proportion of the global climate change problem. According to data of International Maritime Organization (IMO), more than 3% of global carbon dioxide emissions can be attributed to ocean-going ships. Furthermore, in European coastal areas, shipping emissions contribute with 1–7% of ambient air PM10 levels, 1–14% of PM2.5, and at least 11% of PM1 (Viana et al., 2014). Strait of Istanbul is the unique waterway between Black Sea countries and the rest of the world. As a result of the its intensive international maritime traffic, it is a serious emission factor for the city. Studies have shown that only ship emissions cause 4500 deaths per year in the Marmara region. In this study, it is discussed whether international maritime traffic is an effective factor on PM10 emissions by comparing number of passing ship from Strait of Istanbul and pm10 values between 2014 and 2018.

Machine Learning Methods to Forecast the Concentration of PM10 in Lublin, Poland

Air pollution has a major impact on human health, especially in cities, and elevated concentrations of PMx are responsible for a large number of premature deaths each year. Therefore, the amount of PM10 in the air is monitored and forecasts are made to predict the air quality. In Poland, mainly deterministic models are used to predict air pollution. Accordingly, research efforts are being made to develop other models to forecast the ambient PM10 levels. The aim of the study was to compare the machine learning models for predicting PM10 levels in the air in the city of Lublin. The following machine learning models were used: Linear regression (LR), K-Nearest Neighbors Regression (KNNR), Support Vector Machine (SVM), Regression Trees (RT), Gaussian Process Regression Models (GPR), Artificial Neural Network (ANN) and Long Short-Term Memory network (LSTM). The collected data for three consecutive years (January 2017 to December 2019) were used to develop the models. In total, 19 parameters, covering meteorological variables and concentrations of several chemical species, were explored as potential predictors of PM10. The data used to build the models did not take into account the seasons. The algorithms achieved the following R2 values: 0.8 for LR, 0.79 for KNNR, 0.82 for SVM, 0.77 for RT, 0.89, 0.90 for ANN and 0.81 for LSTM. Research has shown that the selection of a machine learning model has a large impact on the quality of the results. In this research, the ANN model performed slightly better than other models. Then, an ANN was used to train a network with five output neurons to predict the approximate level of PM10 at different time points (PM level at a given time, after 1 h, after 6 h, after 12 h and after 24 h). The results showed that the developed and tuned ANN model is appropriate (R = 0.89). The model created in this way can be used to determine the risk of exceeding the PM10 alert level and to inform about the air quality in the region.

Indoor and Ambient Air Pollution in Chennai, India during COVID-19 Lockdown: An Affordable Sensors Study

The Tamil Nadu Air Pollution and Health Effects study (TAPHE-2) aims to evaluate the relationship between air pollution and birth outcome in a rural-urban cohort of 300 pregnant women. Due to COVID-19 related lockdowns, some TAPHE-2 activities were delayed; however, continuous indoor and outdoor air quality data were collected in and around Chennai, India. We report here the impact of graded COVID-19 lockdown on indoor particulate matter (PM2.5 and PM10) levels based on calibrated data from affordable real-time PM sensors called atmos™ and ambient PM levels from publicly available regulatory monitors. The study period was between 11 March and 30 June 2020 (i.e., 100 days of continuous monitoring), which coincided with four phases of a nationwide graded lockdown. Field calibration coefficients for the atmos PM were derived by collocating them with reference-grade PM monitors. The normalized root mean square error (NRMSE) of the atmos hourly PM2.5 (PM10) improved from 41% to 15% (33% to 18%) after applying the field calibration coefficients. Lockdowns resulted in significant reductions in indoor and ambient PM levels, with the highest reduction observed during lockdown phase 2 (L2) and phase 3 (L3). Reductions as high as 70%, 91%, and 62% were observed in ambient PM2.5, indoor PM2.5, and indoor PM10 relative to pre-lockdown levels (PL), respectively. The indoor PM2.5/PM10 ratio decreased during the lockdown, suggesting a decline in the fine mode dominance in PM10. The indoor-to-outdoor (I/O) ratios in PM2.5 marginally increased during L1, L2, and L3 phases compared to that of PL levels, suggesting an uneven reduction in indoor and ambient PM2.5 levels during the lockdown.

Pre-conception and Prenatal Exposure to Ambient PM2.5 with Newborn Telomere Length in Cord Blood

BACKGROUND AND AIM: Telomere length (TL) at birth determines TL in a later life and has been linked to midlife risk of cardiovascular disease, but its own determinants remain unclear. We aim to examine the association and to identify the sensitive window of pre-conception and prenatal exposures to fine particulate matter (PM2.5) with cord blood TL in a heavily air-polluted area in China. METHODS: In 2017, 107 pregnant women admitted for delivery at Anzhen Hospital in Beijing, China, were interviewed for demographics, addresses, and lifestyle factors. Weekly levels of ambient PM2.5 exposure from the three months before pregnancy to the end of pregnancy were estimated from a validated spatiotemporal model. PM2.5 exposure levels based on home and work addresses were combined by work routines. Cord blood leukocyte TL was measured using quantitative polymerase chain reaction. We used distributed lag models (DLMs) to analyze the association and to identify the sensitive window of ambient PM2.5 exposure with cord blood TL with adjusting for potential confounders. DLM analyses were also conducted in stratified subsamples by newborn sex. RESULTS:PM2.5 levels (median: 85 μg/m3) in the three months before LMP was positively (r=0.16) correlated with cord blood TL, while PM2.5 levels (median 78 μg/m3) in the whole pregnancy was inversely (r=-0.15) correlated with cord blood TL, although none of the correlation was significant (P0.05). From DLM, we found PM2.5 exposure was significantly associated with cord blood TL in three sensitive windows: 6-12 weeks before pregnancy (positive association), 6-18 weeks during pregnancy (inverse association), and 39-40 weeks during pregnancy (inverse association). These associations were more evident in female than male newborns. CONCLUSIONS:Preconception and prenatal exposure to ambient PM2.5 exposure may shorten cord blood TL, especially for female fetuses. Future studies with larger sample size are needed to replicate our findings. KEYWORDS: Particulate matter, Birth outcomes, Environmental epidemiology, Modeling

Risks of hospital outpatient visits for overall and cause-specific respiratory disease associated with particulate matter pollution in Lanzhou, China

Until now, few epidemiological studies have focused on the association between ambient particulate matter (PM) pollution and hospital outpatient visits for overall and cause-specific respiratory disease, especially in Lanzhou. This study aimed to evaluate the short-term effects of PM2.5, PMC, and PM10 on hospital outpatient visits for overall and subtypes of respiratory disease in Lanzhou, China, during 2007–2017, using a generalized additive model (GAM). We further assessed the impact of ambient size-fractioned PM on daily total and cause-specific respiratory morbidity, following a series of air quality improvement action in the area with overall and period-specific analyses. Positive associations were identified between PM2.5, PMC, and PM10 and daily morbidity rates from overall respiratory diseases, upper respiratory tract infection, lower respiratory tract infection, pneumonia, and COPD at different lag pattern. Each 10 μg/m3 increase in PM2.5 at lag07, PMC at lag03, and PM10 at lag06 corresponded to an increase of 1.353% (95% CI: 1.249%, 1.457%), 0.052% (95%CI: 0.015%, 0.089%), and 0.201% (95% CI: 0.165%, 0.236%) in daily hospital outpatient visits for total respiratory, respectively. We did not find significant effects of PM2.5, PMC, and PM10 on asthma. For specific subtypes of respiratory diseases, the effects of PM were strongest on pneumonia morbidity, with an increase of 3.712% (95% CI: 3.308%, 4.117%), 0.874% (95% CI: 0.698%, 1.051%), and 0.967% (95% CI: 0.836%, 1.099%) per 10 μg/m3 increment in PM2.5, PMC, and PM10, respectively. The exposure-response association was non-linear across the full range of exposures. With drastic reductions in annual PM levels, the three size-specific PM associate and respiratory morbidity risk showed decreasing trend over time. This study suggests that PM could exert adverse influences on the outcomes of all-cause and cause-specific respiratory outpatient visits in Lanzhou, China. PM2.5 would have significant effects on pneumonia and RTI. Strategies should be considered to further reduce levels of ambient PM2.5.

The influence of air pollution by PM2.5, PM10 and associated heavy metals on the parameters of out-of-hospital cardiac arrest

Out-of-hospital cardiac arrest (OHCA), defined as abrupt cessation of mechanical activity of the heart, is one of the most common causes of death in high-income countries. Cardiac arrest is most often a result of severe cardiovascular disease. New evidence shows that air pollutants such as heavy metals and atmospheric particulate matter have an impact on the pathophysiology of many cardiovascular diseases as well on incidences of OHCA. This retrospective analysis includes all OHCA cases that occurred in central Poland covering the area of 11.711 km2 with the population density of 108 people per square kilometer. Among 2878 EMS-treated OHCA cases between 2013 and 2016, cardiopulmonary resuscitation (CPR) was attempted in 2076 (72%) patients. Concentrations of air pollutants were compared with temperature, humidity and clinical factors affecting the CPR. The study shows seasonal variation of PM 2.5 (p < 0.001), PM 10 (p < 0.001), As (p < 0.001) and Cd (p < 0.001) over the years. Air pollution has a significant effect on the parameters of pre-hospital evaluation in OHCA patients, especially with respect to the content of PM2.5/PM10 and heavy metals. Nickel exposure affects the incidence of initial shockable rhythm (IRR 0.92; p = 0.01) and effectiveness of CPR (IRR 0.94; p = 0.003). Arsenic has an impact on overall mortality (IRR 1.07; p = 0.01) and death upon the arrival of EMS team (IRR 1.15; p < 0.001). Overall mortality was also related to ambient levels of PM10 (IRR 1.004; p < 0.047).

Racial Difference in the Association of Long-Term Exposure to Fine Particulate Matter (PM2.5) and Cardiovascular Disease Mortality among Renal Transplant Recipients.

Ambient air pollutants are known risk factors for cardiovascular disease (CVD) morbidity and mortality with significant racial disparities. However, few studies have explored racial differences among highly susceptible subpopulations, such as renal transplant recipients (RTRs). Despite improvements in quality of life after transplantation, CVD remains the major cause of mortality, especially among Black recipients. This study aimed to evaluate potential racial differences in the association between long-term levels of PM2.5 and the risk of all-cause, total CVD, and coronary heart disease (CHD) mortality among RTRs. This retrospective study consists of 93,857 non-smoking adults who received a renal transplant between 2001 and 2015. Time-dependent Cox regression was used to assess the association between annual concentrations of PM2.5 and mortality risk. In the multivariable-adjusted models, a 10 μg/m3 increase in ambient PM2.5 levels found increased risk of all-cause (HR = 3.45, 95% CI: 3.08–3.78), CVD (HR = 2.38, 95% CI: 1.94–2.92), and CHD mortality (HR = 3.10, 95% CI: 1.96–4.90). Black recipients had higher risks of all-cause (HR = 4.09, 95% CI: 3.43–4.88) and CHD mortality (HR = 6.73, 95% CI: 2.96–15.32). High levels of ambient PM2.5 were associated with all-cause, CVD, and CHD mortality. The association tended to be higher among Black recipients than non-Blacks.

Urinary levels of PAH metabolites in pregnant women and their correlation with sociodemographic factors and PM2.5 exposure in an urban and a suburban area

Exposure to PAHs during pregnancy is associated with adverse birth outcomes. The objectives of this study were to determine the urinary levels of PAH metabolites in pregnant women and to evaluate their association with sociodemographic and lifestyle variables and exposure to atmospheric PM2.5. Subjects of 80 non-smoking pregnant women from three regions in an urban area (Isfahan city) and one region of suburb area (Mobarakeh town) were recruited to the study. The urine samples of women were collected during their first (spring) and third (autumn) trimester of pregnancy. Urinary PAHs’ metabolites including 1-naphthol (1-NAP), 2-naphthol (2-NAP), 9-phenanthrol (9-PHN), and 1-hydroxypyrene (1-OHP) were analysed by a GC/MS after their extraction and derivatization. Ambient PM2.5 data for the study period were collected from air pollution monitoring stations. The mean urinary concentrations of 1-NAP, 2-NAP, 9-PHN and 1-HOP in spring were 3.3, 2.2, 0.9 and 8.8 μg g−1 creatinine, and those in autumn accounted for 5.2, 3.0, 11.2 and 11.3 μg g−1 creatinine, respectively. Coincidently, the mean atmospheric PM2.5 concentrations of 23.2 μg m−3 in spring and 37.3 μg m−3 in autumn were attained. The concentration of the metabolites in the urban area was higher than that in the suburban area in both seasons which was following the ambient levels of PM2.5. A significant positive correlation between the metabolites and ambient PM2.5 was observed (p value < 0.05). Although the socio-demographic factors affected the level of exposure, the difference was not statistically significant (p value < 0.05). Residents of the urban area were exposed to a higher level of PAHs due to air pollution especially in the cold season.

Lockdowns and reduction of economic activities during the COVID-19 pandemic improved air quality in Alexandria, Egypt.

Parallel reductions in atmospheric aerosols (particulate matter (PM)) and nitrogen dioxide (NO2) accompanied the drastic measures that were adopted to limit the spread of COVID-19. The results of this preliminary study conducted in northern Egypt revealed that ambient PM10, PM2.5, and NO2 levels decreased by 22.8%, 29.3%, and 25.9%, respectively, after the lockdown started on March 13, 2020. These reductions in concentrations significantly (p ˂ 0.01) correlated with the decrease in transportation and industrial and other economic activities. Furthermore, PM and NO2 concentrations radically reduced during the full lockdown on Easter, Ramadan, and Eid Al-Fitr. The findings of this study will help the World Health Organization (WHO) and other health regulators to combat COVID-19 in the world. This study is part of an ongoing research related to the current pandemic.

Prenatal Ambient Air Pollutants and Maternal Depressive Symptoms at 12 months Postpartum

Background: Depression is the leading cause of mental health-related morbidity, particularly among women. Ambient air pollutants are modifiable exposures that have increasingly been associated with depression and pregnancy is a period that may increase maternal susceptibility to environmental exposures. We examined whether exposures to prenatal ambient air pollutants are associated with maternal depressive symptoms at 12 months postpartum. Methods: Women participating in the MADRES cohort—an ongoing cohort of predominantly low income, Hispanic women in Los Angeles—were followed from pregnancy through 12 months postpartum with a series of visits and phone calls. At the 12-month study visit, women were orally administered the Center for Epidemiologic Studies-Depression (CES-D) scale as part of a questionnaire on home exposures, social stressors, sociodemographics, and health history. Residential address histories were recorded from one year prior to conception through 12 months postpartum and average ambient pollutant estimates of NO2, PM10, PM2.5 and O3 were spatially interpolated at participants’ residential locations. Logistic regression models were fitted to evaluate associations between trimester-specific and 9-month average levels across pregnancy of ambient air pollutants and probable depression (score of ≥16 on the CES-D) at 12 months postpartum, adjusting for maternal age and recruitment site (N=101). Results: We found that second trimester ambient NO2 levels were associated with a two-fold increased odds of probable depression at 12 months (OR=2.03 per SD increase in NO2 exposure, 95% CI: 1.24, 3.33). Similar results were found for 9-month prenatal average NO2 (OR=1.88, 95% CI: 1.07, 3.32). Prenatal ambient PM10, PM2.5, and O3 levels were not significantly associated with depressive symptoms at 12 months postpartum. Conclusions: Prenatal ambient NO2 levels were associated with increased maternal depressive symptoms at 12 months postpartum. These results underscore the need to better understand the contribution of modifiable environmental risk factors during critical susceptible exposure periods.

Associations between ambient air pollution and medical care visits for atopic dermatitis

BackgroundPrevious studies have reported numerous environmental factors for atopic dermatitis (AD), such as allergens and chemical stimulants. However, few studies have addressed the relationship between ambient air pollution and AD at a population level. ObjectiveTo evaluate the effect of air pollutants on medical care visits for AD and to identify susceptible populations. MethodsIn this time-series study conducted on 513,870 medical care visits for AD from 2012 to 2015 identified by reviewing national health insurance claim data in Incheon, Republic of Korea. Treating daily number of medical care visits for AD as a dependent variable, generalized additive models with Poisson distributions were constructed, which included air pollutant levels, ambient temperature, relative humidity, day of the week, national holiday, and season. Risks were expressed as relative risks (RR) with 95% confidence intervals (95% CIs) per interquartile range increase of each air pollutant. ResultsHigher levels of particulate matter of diameter ≤10 μm (PM10) (RR, 1.009; 95% CI, 1.007–1.012), ozone (1.028; 1.023–1.033), and sulfur dioxide (1.033; 1.030–1.037) were significantly associated with increased risk of medical care visits for AD on same days. In all age and sex groups, ozone was associated with a significantly higher risk of medical care visits, with the greatest risk among 13- to 18-year-old males (RR, 1.127; 95% CI, 1.095–1.159). ConclusionThis study suggests relationships of ambient PM10, ozone, and sulfur dioxide levels with medical care visits for AD.

Depression and anxiety with exposure to ozone and particulate matter: An epidemiological claims data analysis

Depression and anxiety have complex etiologies and are associated with a significant burden of disease. Although air pollution has been hypothesized as a possible risk factor of these disorders, the associations are still under-investigated. We aimed to analyze associations between long-term exposure to ambient ozone and particulate matter with diameter <10μm (PM10) and diagnoses of depression and anxiety in a general population. We utilized data from a large statutory health insurance company from Saxony, Germany. Information on outpatient clinical diagnoses of depression and anxiety was available for the years 2005-2014. We assigned ambient ozone and PM10 estimates to residential districts of 1.13 million individuals aged 16 and older. Depression and anxiety were defined as diagnoses counts. Associations with depression and anxiety were assessed using adjusted generalized estimating equations models. In the ten-year study period, the observed prevalences of depression and anxiety were 7.40% and 3.82%, respectively. In the two-pollutant model, 10 more days with a maximum 8-h average ozone concentration exceeding 120μg/m³ resulted in a relative risk (RR) of 1.010 with 95% confidence interval (CI) (1.005, 1.014) for depression and an RR of 1.007 (95% CI (1.000, 1.014)) for anxiety. The effect estimates of PM10 for depression and anxiety were 1.180 (95% CI (1.160, 1.201)) and 1.176 (95% CI (1.148, 1.205)) per 10μg/m³ increase in PM10 concentration, respectively. Age, sex, and access to healthcare of the individual were also associated with the diagnosis of the disorders. The associations were consistent across one- and two-pollutant models. Our findings indicate that increased levels of ambient ozone and PM10 may elevate the risk of a depression or anxiety diagnosis in the general population. However, given the lack of data on individual air pollutant exposure and socioeconomic status, our results should be interpreted with caution. Further well-designed epidemiological studies should replicate our findings.

Validation of Low-Cost Sensors in Measuring Real-Time PM10 Concentrations at Two Sites in Delhi National Capital Region.

In the present study, we assessed for the first time the performance of our custom-designed low-cost Particulate Matter (PM) monitoring devices (Atmos) in measuring PM10 concentrations. We examined the ambient PM10 levels during an intense measurement campaign at two sites in the Delhi National Capital Region (NCR), India. In this study, we validated the un-calibrated Atmos for measuring ambient PM10 concentrations at highly polluted monitoring sites. PM10 concentration from Atmos, containing laser scattering-based Plantower PM sensor, was comparable with that measured from research-grade scanning mobility particle sizers (SMPS) in combination with optical particle sizers (OPS) and aerodynamic particle sizers (APS). The un-calibrated sensors often provided accurate PM10 measurements, particularly in capturing real-time hourly concentrations variations. Quantile–Quantile plots (QQ-plots) for data collected during the selected deployment period showed positively skewed PM10 datasets. Strong Spearman’s rank-order correlations (rs = 0.64–0.83) between the studied instruments indicated the utility of low-cost Plantower PM sensors in measuring PM10 in the real-world context. Additionally, the heat map for weekly datasets demonstrated high R2 values, establishing the efficacy of PM sensor in PM10 measurement in highly polluted environmental conditions.