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1.
Braz J Med Biol Res ; 55: e12273, 2022.
Article in English | MEDLINE | ID: covidwho-2197474

ABSTRACT

The association between exposure to air pollutants and respiratory diseases is well known. This study aimed to identify the association between this exposure and hospitalizations for COVID-19 in São José dos Campos, SP, a medium-sized city, between April 2020 and April 2021. Hospitalization data, concerning code B34.2, was supplied by DATASUS, and data concerning pollutants and climate variables were supplied by CETESB. Cases were quantified by sex, age, length of hospital stay in days, and type of discharge, whether hospital discharge or death. The negative binomial regression model was chosen. Estimates were produced for the relative risk (RR) of significant exposure to pollutants (P≤0.05) with a 10 µg/m3 increase of pollutant, as well as for excess hospitalizations. There were 1873 hospitalizations, with a daily average of 4.7 (±3.8), ranging from zero to 21: 716 deaths (38.2%) were recorded, 1065 admissions were men, and women were less susceptible (OR=0.82). The average age of women was higher than that of men; in cases of death, men were older than women; discharged patients were younger. All the above variables were significant. The risk of ozone exposure was higher and more significant in Lag 2, and the risk of nitrogen dioxide exposure was high in Lag 3, which was the period of the highest increase in hospitalizations, at 11.3%. The findings of this study, the first conducted in Brazil, corroborate the results of studies conducted in other centers.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Male , Humans , Female , Brazil/epidemiology , Air Pollution/adverse effects , Air Pollutants/adverse effects , Air Pollutants/analysis , Hospitalization , Particulate Matter
2.
J Environ Sci (China) ; 114: 170-178, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-2180480

ABSTRACT

To investigate the characteristics of particulate matter with an aerodynamic diameter less than 2.5 µm (PM2.5) and its chemical compositions in the Beijing-Tianjin-Hebei (BTH) region of China during the novel coronavirus disease (COVID-19) lockdown, the ground-based data of PM2.5, trace gases, water-soluble inorganic ions, and organic and elemental carbon were analyzed in three typical cities (Beijing, Tianjin, and Baoding) in the BTH region of China from 5-15 February 2020. The PM2.5 source apportionment was established by combining the weather research and forecasting model and comprehensive air quality model with extensions (WRF-CAMx). The results showed that the maximum daily PM2.5 concentration reached the heavy pollution level (>150 µg/m3) in the above three cities. The sum concentration of SO42-, NO3- and NH4+ played a dominant position in PM2.5 chemical compositions of Beijing, Tianjin, and Baoding; secondary transformation of gaseous pollutants contributed significantly to PM2.5 generation, and the secondary transformation was enhanced as the increased PM2.5 concentrations. The results of WRF-CAMx showed obviously inter-transport of PM2.5 in the BTH region; the contribution of transportation source decreased significantly than previous reports in Beijing, Tianjin, and Baoding during the COVID-19 lockdown; but the contribution of industrial and residential emission sources increased significantly with the increase of PM2.5 concentration, and industry emission sources contributed the most to PM2.5 concentrations. Therefore, control policies should be devoted to reducing industrial emissions and regional joint control strategies to mitigate haze pollution.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollution/analysis , Beijing , COVID-19/epidemiology , China/epidemiology , Communicable Disease Control , Environmental Monitoring , Humans , Particulate Matter/analysis
3.
Sci Rep ; 12(1): 16737, 2022 Oct 06.
Article in English | MEDLINE | ID: covidwho-2151072

ABSTRACT

A total of 188,859 meteorological-PM[Formula: see text] data validated before (2019) and during the COVID-19 pandemic (2020) were used. In order to predict PM[Formula: see text] in two districts of South Lima in Peru, hourly, daily, monthly and seasonal variations of the data were analyzed. Principal Component Analysis (PCA) and linear/nonlinear modeling were applied. The results showed the highest annual average PM[Formula: see text] for San Juan de Miraflores (SJM) (PM[Formula: see text]-SJM: 78.7 [Formula: see text]g/m[Formula: see text]) and the lowest in Santiago de Surco (SS) (PM[Formula: see text]-SS: 40.2 [Formula: see text]g/m[Formula: see text]). The PCA showed the influence of relative humidity (RH)-atmospheric pressure (AP)-temperature (T)/dew point (DP)-wind speed (WS)-wind direction (WD) combinations. Cool months with higher humidity and atmospheric instability decreased PM[Formula: see text] values in SJM and warm months increased it, favored by thermal inversion (TI). Dust resuspension, vehicular transport and stationary sources contributed more PM[Formula: see text] at peak times in the morning and evening. The Multiple linear regression (MLR) showed the best correlation (r = 0.6166), followed by the three-dimensional model LogAP-LogWD-LogPM[Formula: see text] (r = 0.5753); the RMSE-MLR (12.92) exceeded that found in the 3D models (RMSE [Formula: see text]) and the NSE-MLR criterion (0.3804) was acceptable. PM[Formula: see text] prediction was modeled using the algorithmic approach in any scenario to optimize urban management decisions in times of pandemic.


Subject(s)
Air Pollutants , COVID-19 , Air Pollutants/analysis , COVID-19/epidemiology , Dust , Environmental Monitoring/methods , Humans , Pandemics , Peru/epidemiology
4.
Environ Sci Pollut Res Int ; 28(30): 40474-40495, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-2148922

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease represents the causative agent with a potentially fatal risk which is having great global human health concern. Earlier studies suggested that air pollutants and meteorological factors were considered as the risk factors for acute respiratory infection, which carries harmful pathogens and affects the immunity. The study intended to explore the correlation between air pollutants, meteorological factors, and the daily reported infected cases caused by novel coronavirus in India. The daily positive infected cases, concentrations of air pollutants, and meteorological factors in 288 districts were collected from January 30, 2020, to April 23, 2020, in India. Spearman's correlation and generalized additive model (GAM) were applied to investigate the correlations of four air pollutants (PM2.5, PM10, NO2, and SO2) and eight meteorological factors (Temp, DTR, RH, AH, AP, RF, WS, and WD) with COVID-19-infected cases. The study indicated that a 10 µg/m3 increase during (Lag0-14) in PM2.5, PM10, and NO2 resulted in 2.21% (95%CI: 1.13 to 3.29), 2.67% (95% CI: 0.33 to 5.01), and 4.56 (95% CI: 2.22 to 6.90) increase in daily counts of Coronavirus Disease 2019 (COVID 19)-infected cases respectively. However, only 1 unit increase in meteorological factor levels in case of daily mean temperature and DTR during (Lag0-14) associated with 3.78% (95%CI: 1.81 to 5.75) and 1.82% (95% CI: -1.74 to 5.38) rise of COVID-19-infected cases respectively. In addition, SO2 and relative humidity were negatively associated with COVID-19-infected cases at Lag0-14 with decrease of 7.23% (95% CI: -10.99 to -3.47) and 1.11% (95% CI: -3.45 to 1.23) for SO2 and for relative humidity respectively. The study recommended that there are significant correlations between air pollutants and meteorological factors with COVID-19-infected cases, which substantially explain the effect of national lockdown and suggested positive implications for control and prevention of the spread of SARS-CoV-2 disease.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollution/analysis , China , Communicable Disease Control , Humans , India/epidemiology , Meteorological Concepts , Particulate Matter/analysis , Risk Factors , SARS-CoV-2
6.
Sci Rep ; 12(1): 20046, 2022 Nov 21.
Article in English | MEDLINE | ID: covidwho-2133569

ABSTRACT

This paper presents the evaluation of air quality in different districts of Haryana. Geo-spatial techniques were used to estimate gaseous and particulate pollutant's spatial and temporal variation during complete nationwide lockdown period and same month of previous year 2019 (March to May). Data of six fixed pollutants were collected from Central Pollution Control Board (CPCB). In this context, the data of air pollutants (PM10, PM2.5, O3, NOx, SO2, and CO) were analyzed for 2019 and 2020. The Spatio-temporal distribution of the Air Quality Index (AQI) clearly depicts difference in lockdown and unlock period. The result was showed that the air quality was very poor to satisfactory in 2019 and an improvement was observed from satisfactory to good in 2020 due to COVID-19 lockdown. On the basis of result, it will be concluded that automobile and industry are the major contributor in increase the pollutant concentration.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Humans , COVID-19/epidemiology , COVID-19/prevention & control , Environmental Monitoring/methods , Communicable Disease Control , Air Pollution/analysis , Air Pollutants/analysis
7.
J Glob Health ; 12: 05043, 2022 Nov 21.
Article in English | MEDLINE | ID: covidwho-2144961

ABSTRACT

Background: Lockdowns have been fundamental to decreasing disease transmission during the COVID-19 pandemic even after vaccines were available. We aimed to evaluate and compare changes in air quality during the first year of the pandemic in different cities around the world, investigate how these changes correlate with changes in mobility, and analyse how lockdowns affected air pollutants' annual means. Methods: We compared the concentrations of NO2, PM2.5, and PM10 in 42 cities around the world in the first months of the pandemic in 2020 to data from 2016-2019 and correlated them with changes in mobility using Human Development Indexes (HDIs). Cities with the highest decreases in air pollutants during this period were evaluated for the whole year 2020. We calculated the annual means for these cities and compared them to the new World Health Organization (WHO) Air Quality Guidelines. A Student's t-test (95% confidence interval) was used to evaluate significant changes. Results: Highest decreases in NO2, PM2.5, and PM10 were between -50 and -70%. Cities evaluated for the whole year 2020 generally showed a recovery in air pollution levels after the initial months of the pandemic, except for London. These changes positively correlated with year-long mobility indexes for NO2 and PM2.5 for some cities. The highest reductions in air pollutants' annual means were from -20 to -35%. In general, decreases were higher for NO2, compared to PM2.5 and PM10. All analysed cities showed annual means incompliant with the new WHO Air Quality Guidelines for NO2 of 10 µg/m3, with values 1.7 and 4.3 times higher. For PM2.5, all cities showed values 1.3 to 7.6 times higher than the WHO Guidelines of 5 µg/m3, except for New Delhi, with a value 18 times higher. For PM10, only New York complied with the new guidelines of 15 µg/m3 and all the other cities were 1.1 to 4.2 times higher, except for New Delhi, which was 11 times higher. Conclusions: These data show that even during a pandemic that highly affected mobility and economic activities and decreased air pollution around the world, complying with the new WHO Guidelines will demand a global strategical effort in the way we generate energy, move in and around the cities, and manufacture products.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Humans , Nitrogen Dioxide/analysis , COVID-19/epidemiology , COVID-19/prevention & control , Pandemics/prevention & control , Environmental Monitoring , Communicable Disease Control , Air Pollution/prevention & control , Air Pollutants/analysis , World Health Organization , Particulate Matter/analysis
8.
Environ Health Perspect ; 130(11): 117006, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-2117113

ABSTRACT

BACKGROUND: Studies have suggested links between ambient air pollution and coronavirus 2019 (COVID-19) mortality, yet confirmation by well-designed epidemiological studies with individual data is needed. OBJECTIVES: We aimed to examine whether short-term exposure to air pollution is associated with risk of mortality from COVID-19 for those infected with COVID-19. METHODS: The Cook County Medical Examiner's Office reports individual-level data for deaths from COVID-19 that occur in its jurisdiction, which includes all confirmed COVID-19 deaths in Cook County, Illinois. Case-crossover analysis was conducted to estimate the associations of estimated short-term exposures to particulate matter (PM) with aerodynamic diameter ≤2.5µm (PM2.5) and ozone (O3) on the day of death and up to 21 d before death at location of death with COVID-19. A total of 7,462 deaths from COVID-19 that occurred up to 28 February 2021 were included in the final analysis. We adjusted for potential confounders by time-stratified case-crossover design and by covariate adjustments (i.e., time-invariant factors, meteorological factors, viral transmission, seasonality, and time trend). RESULTS: Of the 7,462 case and 25,457 self-control days, almost all were days with exposure levels below the PM2.5 24-h National Ambient Air Quality Standard (NAAQS) (35 µg/m3); 98.9% had O3 levels below the maximum 8-h NAAQS (35.7 µg/m3 or 70 parts per billion). An interquartile range (IQR) increase (5.2 µg/m3) in cumulative 3-wk PM2.5 exposure was associated with a 69.6% [95% confidence interval (CI): 34.6, 113.8] increase in risk of COVID-19 mortality. An IQR increase (8.2 µg/m3) in 3-d O3 exposure was associated with a 29.0% (95% CI: 9.9, 51.5) increase in risk of COVID-19 mortality. The associations differed by demographics or race/ethnicity. There was indication of modification of the associations by some comorbid conditions. DISCUSSION: Short-term exposure to air pollution below the NAAQS may increase the mortality burden from COVID-19. https://doi.org/10.1289/EHP10836.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Humans , Cross-Over Studies , Air Pollutants/analysis , Coroners and Medical Examiners , Environmental Exposure/analysis , Air Pollution/analysis , Particulate Matter/analysis , Registries
9.
Int J Environ Res Public Health ; 19(21)2022 Nov 05.
Article in English | MEDLINE | ID: covidwho-2099549

ABSTRACT

The supply of fresh air for underground rail transit systems is not as simple as opening windows, which is a conventional ventilation (CV) measure adopted in aboveground vehicles. This study aims to improve contaminant dilution and air purification in subway car ventilation systems and the safety of rail transit post-coronavirus disease pandemic era. We designed an air conditioning (AC) terminal system combined with stratum ventilation (SV) to enable energy consumption reduction for subway cars. We experimentally tested the effectiveness of a turbulence model to investigate ventilation in subway cars. Further, we compared the velocity fields of CV and SV in subway cars to understand the differences in their airflow organizations and contaminant removal efficiencies, along with the energy savings of four ventilation scenarios, based on the calculations carried out using computational fluid dynamics. At a ventilation flow rate of 7200 m3/h, the CO2 concentration and temperature in the breathing areas of seated passengers were better in the SV than in the CV at a rate of 8500 m3/h. Additionally, the energy-saving rate of SV with AC cooling was 14.05%. The study provides new ideas for reducing the energy consumption of rail transit and broadens indoor application scenarios of SV technology.


Subject(s)
Air Pollutants , Air Pollution, Indoor , Railroads , Automobiles , Air Pollution, Indoor/prevention & control , Air Pollution, Indoor/analysis , Air Pollutants/analysis , Environmental Monitoring , Ventilation
10.
Int J Environ Res Public Health ; 19(21)2022 Nov 04.
Article in English | MEDLINE | ID: covidwho-2099537

ABSTRACT

During the COVID-19 pandemic, the digital economy has developed rapidly. The airborne nature of COVID-19 viruses has attracted worldwide attention. Therefore, it is of great significance to analyze the impact of the digital economy on particulate matter 2.5 (PM2.5) emissions. The research sample of this paper include 283 prefecture-level cities in China from 2011 to 2019 in China. Spatial Durbin model was adopted to explore the spatial spillover effect of digital economy on PM2.5 emissions. In addition, considering the impact of smart city pilot (SCP) policy, a spatial difference-in-differences (SDID) model was used to analyze policy effects. The estimation results indicated that (1) the development of the digital economy significantly reduces PM2.5 emissions. (2) The spatial spillover effect of the digital economy significantly reduces PM2.5 emissions in neighboring cities. (3) Smart city construction increases PM2.5 emissions in neighboring cities. (4) The reduction effect of the digital economy on PM2.5 is more pronounced in the sample of eastern cities and urban agglomerations.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Humans , Particulate Matter/analysis , Cities , Air Pollution/analysis , Air Pollutants/analysis , Pandemics , COVID-19/epidemiology , China
11.
Int J Environ Res Public Health ; 19(21)2022 Oct 31.
Article in English | MEDLINE | ID: covidwho-2099494

ABSTRACT

The World Health Organization (WHO) have set sustainability development goals to reduce diseases, deaths, and the environmental impact of cities due to air pollution. In Istanbul, although average pollutant concentrations have been on a downward trend in recent years, extreme values and their annual exceedance numbers are high based on the air quality standards of WHO and the EU. Due to COVID-19 lockdowns, statistically significant reductions in emissions were observed for short periods. However, how long the effect of the lockdowns will last is unknown. For this reason, this study aims to investigate the impact of long-term lockdowns on Istanbul's air quality. The restriction period is approximated to the same periods of the previous years to eliminate seasonal effects. A series of paired t-tests (p-value < 0.05) were applied to hourly data from 12 March 2016, until 1 July 2021, when quarantines were completed at 36 air quality monitoring stations in Istanbul. The findings reveal that the average air quality of Istanbul was approximately 17% improved during the long-term lockdowns. Therefore, the restriction-related changes in emission distributions continued in the long-term period of 476 days. However, it is unknown how long this effect will continue, which will be the subject of future studies. Moreover, it was observed that the emission probability density functions changed considerably during the lockdowns compared to the years before. Accordingly, notable decreases were detected in air quality limit exceedances in terms of both excessive pollutant concentrations and frequency of occurrence, respectively, for PM10 (-13% and -13%), PM2.5 (-16% and -30%), and NO2 (-3% and -8%), but not for O3 (+200% and +540%) and SO2 (-10% and +2.5%).


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Humans , Air Pollutants/analysis , Particulate Matter/analysis , COVID-19/epidemiology , COVID-19/prevention & control , Communicable Disease Control , Air Pollution/analysis , Environmental Monitoring , Nitrogen Dioxide/analysis
12.
Am J Epidemiol ; 191(11): 1897-1905, 2022 Oct 20.
Article in English | MEDLINE | ID: covidwho-2097303

ABSTRACT

We aimed to determine whether long-term ambient concentrations of fine particulate matter (particulate matter with an aerodynamic diameter less than or equal to 2.5 µm (PM2.5)) were associated with increased risk of testing positive for coronavirus disease 2019 (COVID-19) among pregnant individuals who were universally screened at delivery and whether socioeconomic status (SES) modified this relationship. We used obstetrical data collected from New-York Presbyterian Hospital/Columbia University Irving Medical Center in New York, New York, between March and December 2020, including data on Medicaid use (a proxy for low SES) and COVID-19 test results. We linked estimated 2018-2019 PM2.5 concentrations (300-m resolution) with census-tract-level population density, household size, income, and mobility (as measured by mobile-device use) on the basis of residential address. Analyses included 3,318 individuals; 5% tested positive for COVID-19 at delivery, 8% tested positive during pregnancy, and 48% used Medicaid. Average long-term PM2.5 concentrations were 7.4 (standard deviation, 0.8) µg/m3. In adjusted multilevel logistic regression models, we saw no association between PM2.5 and ever testing positive for COVID-19; however, odds were elevated among those using Medicaid (per 1-µg/m3 increase, odds ratio = 1.6, 95% confidence interval: 1.0, 2.5). Further, while only 22% of those testing positive showed symptoms, 69% of symptomatic individuals used Medicaid. SES, including unmeasured occupational exposures or increased susceptibility to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) due to concurrent social and environmental exposures, may explain the increased odds of testing positive for COVID-19 being confined to vulnerable pregnant individuals using Medicaid.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Pregnancy , Female , Humans , Particulate Matter/analysis , SARS-CoV-2 , Air Pollution/adverse effects , Air Pollutants/analysis , New York City/epidemiology , Prevalence , Environmental Exposure/adverse effects , Social Class
13.
Sci Rep ; 12(1): 18144, 2022 Oct 28.
Article in English | MEDLINE | ID: covidwho-2096792

ABSTRACT

NO2 and nitric oxide (NO) are the most reactive gases in the atmosphere. The interaction of NOx molecules with oxygen, water and other chemicals leads to the formation of acid rain. The presence of NO2 in the air affects human health and forms a photochemical smog. In this study, we utilize wavelet analysis, namely, the Morlet wavelet, which is a type of continuous wavelet transform, to conduct a spectral analysis of the periodicity of nitrogen dioxide (NO2). The study is conducted using data from 14 weather stations located in diverse geographic areas of the United Arab Emirates (UAE) over a period of two years (2019 and 2020). We explain and relate the significance of human activities to the concentration level of NO2, particularly considering the effect of the COVID-19 lockdown to the periodicity of NO2. The results show that NO2 concentrations in desert areas such as Liwa and Al Quaa were unaffected by the lockdown period (April-July 2020) resulting from the COVID-19 pandemic. The other stations in the urban areas of Abu Dhabi city, Al Dhafra and Al Ain, showed a reduction in NO2 during the lockdown. NO2 is more highly concentrated during winter seasons than during other seasons. The periodicity of NO2 lasted from a few days up to 16 days in most regions. However, some stations located in the Al Dhafra region, such as Al Ruwais and the Gayathi School stations, exhibited a longer period of more than 32 days with a 0.05 significance test. In the Abu Dhabi region, NO2 lasted between 64 and 128 days at the Al Mafraq station. The correlation between the NO2 concentration across several ground stations was studied using wavelet coherence.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Humans , Nitrogen Dioxide/analysis , Nitric Oxide/analysis , Wavelet Analysis , United Arab Emirates , Pandemics , COVID-19/epidemiology , Communicable Disease Control , Air Pollutants/analysis , Environmental Monitoring/methods , Air Pollution/analysis
14.
Infect Control Hosp Epidemiol ; 41(9): 1011-1015, 2020 Sep.
Article in English | MEDLINE | ID: covidwho-2096316

ABSTRACT

OBJECTIVE: To determine whether ambient air pollutants and meteorological variables are associated with daily COVID-19 incidence. DESIGN: A retrospective cohort from January 25 to February 29, 2020. SETTING: Cities of Wuhan, Xiaogan, and Huanggang, China. PATIENTS: The COVID-19 cases detected each day. METHODS: We collected daily data of COVID-19 incidence, 8 ambient air pollutants (particulate matter of ≤2.5 µm [PM2.5], particulate matter ≤10 µm [PM10], sulfur dioxide [SO2], carbon monoxide [CO], nitrogen dioxide [NO2], and maximum 8-h moving average concentrations for ozone [O3-8h]) and 3 meteorological variables (temperature, relative humidity, and wind) in China's 3 worst COVID-19-stricken cities during the study period. The multivariate Poisson regression was performed to understand their correlation. RESULTS: Daily COVID-19 incidence was positively associated with PM2.5 and humidity in all cities. Specifically, the relative risk (RR) of PM2.5 for daily COVID-19 incidences were 1.036 (95% confidence interval [CI], 1.032-1.039) in Wuhan, 1.059 (95% CI, 1.046-1.072) in Xiaogan, and 1.144 (95% CI, 1.12-1.169) in Huanggang. The RR of humidity for daily COVID-19 incidence was consistently lower than that of PM2.5, and this difference ranged from 0.027 to 0.111. Moreover, PM10 and temperature also exhibited a notable correlation with daily COVID-19 incidence, but in a negative pattern The RR of PM10 for daily COVID-19 incidence ranged from 0.915 (95% CI, 0.896-0.934) to 0.961 (95% CI, 0.95-0.972, while that of temperature ranged from 0.738 (95% CI, 0.717-0.759) to 0.969 (95% CI, 0.966-0.973). CONCLUSIONS: Our data show that PM2.5 and humidity are substantially associated with an increased risk of COVID-19 and that PM10 and temperature are substantially associated with a decreased risk of COVID-19.


Subject(s)
Air Pollutants/toxicity , Air Pollution/adverse effects , Betacoronavirus , Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Weather , Air Pollutants/analysis , Air Pollution/analysis , Air Pollution/statistics & numerical data , COVID-19 , China/epidemiology , Coronavirus Infections/etiology , Humans , Incidence , Pandemics , Pneumonia, Viral/etiology , Poisson Distribution , Retrospective Studies , Risk Factors , SARS-CoV-2
15.
Int J Environ Res Public Health ; 19(21)2022 Oct 30.
Article in English | MEDLINE | ID: covidwho-2090189

ABSTRACT

Many studies have shown that air pollution may be closely associated with increased morbidity and mortality due to COVID-19. It has been observed that exposure to air pollution leads to reduced immune response, thereby facilitating viral penetration and replication. In our study, we combined information on confirmed COVID-19 daily new cases (DNCs) in one of the most polluted regions in the European Union (EU) with air-quality monitoring data, including meteorological parameters (temperature, relative humidity, atmospheric pressure, wind speed, and direction) and concentrations of particulate matter (PM10 and PM2.5), sulfur dioxide (SO2), nitrogen oxides (NO and NO2), ozone (O3), and carbon monoxide (CO). Additionally, the relationship between bacterial aerosol (BA) concentration and COVID-19 spread was analyzed. We confirmed a significant positive correlation (p < 0.05) between NO2 concentrations and numbers of confirmed DNCs and observed positive correlations (p < 0.05) between BA concentrations and DNCs, which may point to coronavirus air transmission by surface deposits on bioaerosol particles. In addition, wind direction information was used to show that the highest numbers of DNCs were associated with the dominant wind directions in the region (southern and southwestern parts).


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Ozone , Humans , Air Pollutants/analysis , Nitrogen Dioxide/analysis , COVID-19/epidemiology , Poland/epidemiology , Respiratory Aerosols and Droplets , Air Pollution/adverse effects , Air Pollution/analysis , Particulate Matter/analysis , Ozone/analysis , China
16.
J Environ Sci Health A Tox Hazard Subst Environ Eng ; 57(11): 970-976, 2022.
Article in English | MEDLINE | ID: covidwho-2087557

ABSTRACT

The main goal of this study is to compare concentrations of atmospheric Hg(p) for various particles sizes Total Suspended Particulates (TSP), PM18, PM10, PM2.5, PM1, PM<1 before (2018-2019) and during (2019-2020 and 2020-2021) COVID-19 occurred periods in central Taiwan. In addition, test the statistical differences concentrations of Hg(p) for various particles sizes before and during COVID-19 occurred periods in central Taiwan. Finally, calculate the Hg(p) health risk assessment before and during COVID-19 occurred period in central Taiwan.The result indicated that the mean Hg(p) concentrations in TSP and PM2.5 were higher during (2020-2021) the COVID-19 occurred period than that of the mean Hg(p) concentrations in TSP and PM2.5 before the COVID-19 occurred period. In addition, the Hg(p)concentrations PM18, PM10, PM2.5, PM1 and PM<1 were all increased during the COVID-19 occurred period. The Hg(p) concentrations in TSP were decreased during (2019-2020) the COVID-19 occurred period when compared with that of the before the COVID-19 occurred period. Moreover, significant mean Hg(p) concentrations differences were existed at PM18, PM10 and PM2.5 before and during (2020-2021) COVID-19 occurred periods. Finally, the HQ and HI values for Hg(p) were both increased during COVID-19 occurred periods when compared with before COVID-19 occurred period in this study.


Subject(s)
Air Pollutants , COVID-19 , Mercury , Humans , Air Pollutants/analysis , Particle Size , Environmental Monitoring , COVID-19/epidemiology , Taiwan/epidemiology , Mercury/analysis , Dust , Particulate Matter/analysis , Seasons
17.
Sci Total Environ ; 838(Pt 4): 156516, 2022 Sep 10.
Article in English | MEDLINE | ID: covidwho-2082807

ABSTRACT

The worldwide restrictions of social contacts that were implemented in spring 2020 to slow down infection rates of the SARS-CoV-2 virus resulted in significant modifications in mobility behaviour of urban residents. We used three-year eddy covariance measurements of size-resolved particle number fluxes from an urban site in Berlin to estimate the effects of reduced traffic intensity on particle fluxes. Similar observations of urban surface-atmosphere exchange of size-resolved particles that focus on COVID-19 lockdown-related effects are not available, yet. Although the site remained a net emission source for ultrafine particles (UFP, Dp < 100 nm), the median upward flux of ultrafine particles (FUFP) decreased from 8.78 × 107 m-2 s-1 in the reference period to 5.44 × 107 m-2 s-1 during the lockdown. This was equivalent to a relative reduction of -38 % for median FUFP, which was similar to -35 % decrease of road traffic intensity in the flux source area during that period. The size-resolved analysis demonstrated that, on average, net deposition of UFP occurred only during night when particle emission source strength by traffic was at its minimum, whereas accumulation mode particles (100 nm < Dp < 200 nm) showed net deposition also during daytime. The results indicate the benefits of traffic reductions as a mitigation strategy to reduce UFP emissions to the urban atmosphere.


Subject(s)
Air Pollutants , COVID-19 , Air Pollutants/analysis , Atmosphere , Communicable Disease Control , Environmental Monitoring/methods , Humans , Particle Size , Particulate Matter/analysis , SARS-CoV-2 , Vehicle Emissions/analysis
18.
Int J Environ Res Public Health ; 19(20)2022 Oct 19.
Article in English | MEDLINE | ID: covidwho-2081995

ABSTRACT

Air is a diverse mixture of gaseous and suspended solid particles. Several new substances are being added to the air daily, polluting it and causing human health effects. Particulate matter (PM) is the primary health concern among these air toxins. The World Health Organization (WHO) addressed the fact that particulate pollution affects human health more severely than other air pollutants. The spread of air pollution and viruses, two of our millennium's most serious concerns, have been linked closely. Coronavirus disease 2019 (COVID-19) can spread through the air, and PM could act as a host to spread the virus beyond those in close contact. Studies on COVID-19 cover diverse environmental segments and become complicated with time. As PM pollution is related to everyday life, an essential awareness regarding PM-impacted COVID-19 among the masses is required, which can help researchers understand the various features of ambient particulate pollution, particularly in the era of COVID-19. Given this, the present work provides an overview of the recent developments in COVID-19 research linked to ambient particulate studies. This review summarizes the effect of the lockdown on the characteristics of ambient particulate matter pollution, the transmission mechanism of COVID-19, and the combined health repercussions of PM pollution. In addition to a comprehensive evaluation of the implementation of the lockdown, its rationales-based on topographic and socioeconomic dynamics-are also discussed in detail. The current review is expected to encourage and motivate academics to concentrate on improving air quality management and COVID-19 control.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Humans , Particulate Matter/analysis , COVID-19/epidemiology , Communicable Disease Control , Air Pollution/analysis , Air Pollutants/analysis , Environmental Monitoring
19.
Environ Pollut ; 315: 120408, 2022 Dec 15.
Article in English | MEDLINE | ID: covidwho-2068946

ABSTRACT

Large reductions in anthropogenic emissions during the Chinese New Year (CNY) holiday in Beijing have been well reported. However, the changes during the CNY of 2021 are different because most people stayed in Beijing to control the spread of coronavirus disease (COVID-19). Here a high-resolution aerosol mass spectrometer (HR-AMS) was deployed for characterization of the changes in size-resolved aerosol composition and sources during the CNY. We found that the reductions in traffic-related NOx and fossil fuel-related organic aerosol (OA), and cooking OA (1.3-12.7%) during the CNY of 2021 were much smaller than those in previous CNY holidays of 2013, 2015, and 2020. In contrast, the mass concentrations of secondary aerosol species except nitrate showed ubiquitous increases (17.6-30.4%) during the CNY of 2021 mainly due to a 4-day severe haze episode. OA composition also changed substantially during the CNY of 2021. In particular, we observed a large increase by nearly a factor of 2 in oxidized primary OA likely from biomass burning, and a decrease of 50.1% in aqueous-phase secondary OA. A further analysis of the severe haze episode during the CNY illustrated a rapid transition of secondary formation from photochemical to aqueous-phase processing followed by a scavenging process, leading to significant changes in aerosol composition, size distributions, and oxidation degree of OA. A parameterization relationship between oxygen-to-carbon (O/C) and f44 (fraction of m/z 44 in OA) from a collocated capture vaporizer aerosol chemical speciation monitor (CV-ACSM) was developed, which has a significant implication for characterization of OA evolution and the impacts on hygroscopicity due to the rapidly increased deployments of CV-ACSM worldwide.


Subject(s)
Air Pollutants , COVID-19 , Humans , Particulate Matter/analysis , Air Pollutants/analysis , Respiratory Aerosols and Droplets , Beijing , Environmental Monitoring
20.
Int J Environ Res Public Health ; 19(19)2022 Oct 08.
Article in English | MEDLINE | ID: covidwho-2066081

ABSTRACT

Under the clean air action plans and the lockdown to constrain the coronavirus disease 2019 (COVID-19), the air quality improved significantly. However, fine particulate matter (PM2.5) pollution still occurred on the North China Plain (NCP). This study analyzed the variations of PM2.5, nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3) during 2017-2021 on the northern (Beijing) and southern (Henan) edges of the NCP. Furthermore, the drivers for the PM2.5 pollution episodes pre- to post-COVID-19 in Beijing and Henan were explored by combining air pollutant and meteorological datasets and the weighted potential source contribution function. Results showed air quality generally improved during 2017-2021, except for a slight rebound (3.6%) in NO2 concentration in 2021 in Beijing. Notably, the O3 concentration began to decrease significantly in 2020. The COVID-19 lockdown resulted in a sharp drop in the concentrations of PM2.5, NO2, SO2, and CO in February of 2020, but PM2.5 and CO in Beijing exhibited a delayed decrease in March. For Beijing, the PM2.5 pollution was driven by the initial regional transport and later secondary formation under adverse meteorology. For Henan, the PM2.5 pollution was driven by the primary emissions under the persistent high humidity and stable atmospheric conditions, superimposing small-scale regional transport. Low wind speed, shallow boundary layer, and high humidity are major drivers of heavy PM2.5 pollution. These results provide an important reference for setting mitigation measures not only for the NCP but for the entire world.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Ozone , Air Pollutants/analysis , Air Pollution/analysis , COVID-19/epidemiology , Carbon Monoxide/analysis , China/epidemiology , Communicable Disease Control , Environmental Monitoring/methods , Humans , Nitrogen Dioxide/analysis , Ozone/analysis , Particulate Matter/analysis , Sulfur Dioxide/analysis
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