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1.
Environ Sci Pollut Res Int ; 29(15): 22515-22530, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1750808

ABSTRACT

Escalating emissions of several air pollutants over South Asia could play a detrimental role in the regional and global atmosphere. Therefore, it is necessary to investigate these emissions within the boundary layer and at higher heights utilizing satellite data that are more inclusionary, where limited in situ observations are available. Here, we utilize the Infrared Atmospheric Sounding Interferometer (IASI), Ozone Monitoring Instruments (OMI), TROPOspheric Monitoring Instrument (TROPOMI), and Global Ozone Monitoring Experiment (GOME-2) hyperspectral satellite data to assess the changes in emission sources during Indian lockdown with a primary focus on the tropospheric profiles of ozone and carbon monoxide (CO). A significant reduction (> 20%) in the tropospheric ozone was seen over northern and northeast regions compared to 2018, while a dramatic increase (> 20%) compared to 2019 was seen. The subtropical dynamics mainly contributed to the increased ozone over the northern region. An analysis of the ozone production regime showed mostly NO2 limited regime over the major part of India and VOC limited regime over thermal power plants regions. Unlike in the boundary layer, where CO showed reduction (15-20%), CO profiles showed a consistent increase (as high as 31%) in the free troposphere over the majority of cities and thermal power plants. The CO total column also showed an increase (~ 20%) over central and western India and a slight decrease (5%) over northern India. Similar to CO, an increase (~ 15%) of NO2 column over the western region was observed particularly compared to 2019. However, unlike ozone and CO, reduction of tropospheric NO2 columns was seen over the major part of India, with the highest reduction over northern regions (20-52%). Furthermore, homogeneous yearly differences (> 30%) between OMI and TROPOMI NO2 observations were also seen distinctly over the remote areas. Contrary to surface-based studies, the present study shows an increase in CO, ozone (decrease), and NO2 at several locations and in the free troposphere during the lockdown.


Subject(s)
Air Pollutants , COVID-19 , Ozone , Air Pollutants/analysis , Communicable Disease Control , Environmental Monitoring , Humans , India , Nitrogen Dioxide/analysis , Ozone/analysis , Remote Sensing Technology , SARS-CoV-2
2.
Environ Sci Pollut Res Int ; 29(15): 21682-21691, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1750807

ABSTRACT

As an air pollutant closely related to urban traffic and heavy industrial capacity, the variation of NO2 (nitrogen dioxide) concentration can directly reflect the strength of socioeconomic activities. Using the weekly average results of daily product synthesis of tropospheric NO2 column concentrations from OMI (Ozone Monitoring Instrument) satellite inversion, a weekly-scale variation series of standardized socioeconomic activity index during the Spring Festival period of 2019-2021 is constructed. The results show that the OMI-NO2 satellite data are in good consistency with ground-based monitoring data; the Spring Festival holiday also suppresses socioeconomic activity in normal years, but the coronavirus disease 2019 (COVID-19) epidemic leads to an extended period of 2-3 weeks of weakened socioeconomic activity in China after the holiday, while the minimum value of socioeconomic activity intensity decreases by 0.12. Although socioeconomic activity is significantly suppressed in the short term, the intensity of socioeconomic activity rises steadily with the gradual resumption of work and production everywhere from the third week after the Chinese Spring Festival and has reached 60.91% of the highest level before the holiday in the seventh week after the holiday. OMI-NO2 satellite data can be used for a rapid assessment of the intensity of air pollution emissions and the level of socioeconomic activity in different regions.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollution/analysis , China , Environmental Monitoring/methods , Humans , Nitrogen Dioxide/analysis , Socioeconomic Factors
3.
Nature ; 601(7893): 380-387, 2022 01.
Article in English | MEDLINE | ID: covidwho-1631307

ABSTRACT

Nitrogen dioxide (NO2) is an important contributor to air pollution and can adversely affect human health1-9. A decrease in NO2 concentrations has been reported as a result of lockdown measures to reduce the spread of COVID-1910-20. Questions remain, however, regarding the relationship of satellite-derived atmospheric column NO2 data with health-relevant ambient ground-level concentrations, and the representativeness of limited ground-based monitoring data for global assessment. Here we derive spatially resolved, global ground-level NO2 concentrations from NO2 column densities observed by the TROPOMI satellite instrument at sufficiently fine resolution (approximately one kilometre) to allow assessment of individual cities during COVID-19 lockdowns in 2020 compared to 2019. We apply these estimates to quantify NO2 changes in more than 200 cities, including 65 cities without available ground monitoring, largely in lower-income regions. Mean country-level population-weighted NO2 concentrations are 29% ± 3% lower in countries with strict lockdown conditions than in those without. Relative to long-term trends, NO2 decreases during COVID-19 lockdowns exceed recent Ozone Monitoring Instrument (OMI)-derived year-to-year decreases from emission controls, comparable to 15 ± 4 years of reductions globally. Our case studies indicate that the sensitivity of NO2 to lockdowns varies by country and emissions sector, demonstrating the critical need for spatially resolved observational information provided by these satellite-derived surface concentration estimates.


Subject(s)
Atmosphere/chemistry , COVID-19/epidemiology , COVID-19/prevention & control , Communicable Disease Control/statistics & numerical data , Environmental Indicators , Nitrogen Dioxide/analysis , Altitude , Humans , Ozone/analysis , Quarantine/statistics & numerical data , Satellite Imagery , Time Factors
4.
Chemosphere ; 293: 133631, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1639538

ABSTRACT

The COVID-19 pandemic and the corresponding lockdown measures have been confirmed to reduce the air pollution in major megacities worldwide. Especially at some monitoring hotspots, NO2 has been verified to show a significant decrease. However, the diffusion pattern of these hotspots in responding to COVID-19 is not clearly understood at present stage. Hence, we selected Beijing, a typical megacity with the strictest lockdown measures during COVID-19 period, as the studied city and attempted to discover the NO2 diffusion process through complex network method. The improved metrics derived from the topological structure of the network were adopted to describe the performance of diffusion. Primarily, we found evidences that COVID-19 had significant effects on the spatial diffusion distribution due to combined effect of changed human activities and meteorological conditions. Besides, to further quantify the impacts of disturbance caused by different lockdown measures, we discussed the evolutionary diffusion patterns from lockdown period to recovery period. The results displayed that the difference between normal operation and pandemic operation firstly increased at the cutoff of lockdown measures but then declined after the implement of recovery measures. The source areas had greater vulnerability and lower resilience than receptors areas. Furthermore, based on the conclusion that the diffusion pattern changed during different periods, we explored the key stations on the path of diffusion process to further gain information. These findings could provide references for comprehending spatiotemporal pattern on city scale, which might be help for high-resolution air pollution mapping and prediction.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollution/analysis , Beijing , Cities , Communicable Disease Control , Environmental Monitoring , Humans , Nitrogen Dioxide/analysis , Pandemics , Particulate Matter/analysis , SARS-CoV-2
5.
Environ Sci Pollut Res Int ; 29(18): 27496-27509, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1606104

ABSTRACT

The coronavirus disease 2019 (COVID-19) pandemic is still rapidly spreading globally. To probe high-risk cities and the impacts of air pollution on public health, this study explores the relationship between the long-term average concentration of air pollution and the city-level case fatality rate (CFR) of COVID-19 globally. Then, geographically weighted regression (GWR) is applied to examine the spatial variability of the relationships. Six air pollution factors, including nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), PM2.5 (particles with diameter ≤2.5 µm), PM10 (particles with diameter ≤10 µm), and air quality index (AQI), are positively associated with the city-level COVID-19 CFR. Our results indicate that a 1-unit increase in NO2 (part per billion, PPB), SO2 (PPB), O3 (PPB), PM2.5 (microgram per cubic meter, µg/m3), PM10 (µg/m3), AQI (score), is related to a 1.450%, 1.005%, 0.992%, 0.860%, 0.568%, and 0.776% increase in the city-level COVID-19 CFR, respectively. Additionally, the effects of NO2, O3, PM2.5, AQI, and probability of living with poor AQI on COVID-19 spatially vary in view of the estimation of the GWR. In other words, the adverse impacts of air pollution on health are different among the cities. In summary, long-term exposure to air pollution is negatively related to the COVID-19 health outcome, and the relationship is spatially non-stationary. Our research sheds light on the impacts of slashing air pollution on public health in the COVID-19 pandemic to help governments formulate air pollution policies in light of the local situations.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollution/analysis , COVID-19/epidemiology , Cities/epidemiology , Humans , Nitrogen Dioxide/analysis , Pandemics , Particulate Matter/analysis
6.
Sci Rep ; 11(1): 23517, 2021 12 07.
Article in English | MEDLINE | ID: covidwho-1561736

ABSTRACT

Lockdown measures implemented in response to the COVID-19 pandemic produced sudden behavioral changes. We implement counterfactual time series analysis based on seasonal autoregressive integrated moving average models (SARIMA), to examine the extent of air pollution reduction attained following state-level emergency declarations. We also investigate whether these reductions occurred everywhere in the US, and the local factors (geography, population density, and sources of emission) that drove them. Following state-level emergency declarations, we found evidence of a statistically significant decrease in nitrogen dioxide (NO2) levels in 34 of the 36 states and in fine particulate matter (PM2.5) levels in 16 of the 48 states that were investigated. The lockdown produced a decrease of up to 3.4 µg/m3 in PM2.5 (observed in California) with range (- 2.3, 3.4) and up to 11.6 ppb in NO2 (observed in Nevada) with range (- 0.6, 11.6). The state of emergency was declared at different dates for different states, therefore the period "before" the state of emergency in our analysis ranged from 8 to 10 weeks and the corresponding "after" period ranged from 8 to 6 weeks. These changes in PM2.5 and NO2 represent a substantial fraction of the annual mean National Ambient Air Quality Standards (NAAQS) of 12 µg/m3 and 53 ppb, respectively. As expected, we also found evidence that states with a higher percentage of mobile source emissions (obtained from 2014) experienced a greater decline in NO2 levels after the lockdown. Although the socioeconomic restrictions are not sustainable, our results provide a benchmark to estimate the extent of achievable air pollution reductions. Identification of factors contributing to pollutant reduction can help guide state-level policies to sustainably reduce air pollution.


Subject(s)
Air Pollution/analysis , COVID-19/epidemiology , COVID-19/virology , Databases, Factual , Humans , Nitrogen Dioxide/analysis , Particulate Matter/analysis , SARS-CoV-2/isolation & purification , United States/epidemiology
7.
Environ Sci Pollut Res Int ; 29(17): 24911-24924, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1536342

ABSTRACT

The COVID-19 pandemic has a close relationship with local environmental conditions. This study explores the effects of climate characteristics and air pollution on COVID-19 in Isfahan province, Iran. A number of COVID-19 positive cases, main air pollutants, air quality index (AQI), and climatic variables were received from March 1, 2020, to January 19, 2021. Moreover, CO, NO2, and O3 tropospheric levels were collected using Sentinel-5P satellite data. The spatial distribution of variables was estimated by the ordinary Kriging and inverse weighted distance (IDW) models. A generalized linear model (GLM) was used to analyze the relationship between environmental variables and COVID-19. The seasonal trend of nitrogen dioxide (NO2), wind speed, solar energy, and rainfall like COVID-19 was upward in spring and summer. The high and low temperatures increased from April to August. All variables had a spatial autocorrelation and clustered pattern except AQI. Furthermore, COVID-19 showed a significant association with month, climate, solar energy, and NO2. Suitable policy implications are recommended to be performed for improving people's healthcare and control of the COVID-19 pandemic. This study could survey the local spread of COVID-19, with consideration of the effect of environmental variables, and provides helpful information to health ministry decisions for mitigating harmful effects of environmental change. By means of the proposed approach, probably the COVID-19 spread can be recognized by knowing the regional climate in major cities. The present study also finds that COVID-19 may have an effect on climatic condition and air pollutants.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollution/analysis , COVID-19/epidemiology , Cities/epidemiology , Environmental Monitoring , Humans , Iran/epidemiology , Nitrogen Dioxide/analysis , Pandemics , Particulate Matter/analysis , Spatio-Temporal Analysis
8.
Sci Total Environ ; 804: 149986, 2022 Jan 15.
Article in English | MEDLINE | ID: covidwho-1525947

ABSTRACT

BACKGROUND: Long-term exposure to ambient air pollution was linked to depression incidence, although the results were limited and inconsistent. OBJECTIVES: To investigate the effects of long-term air pollution exposure on depression risk prospectively in China. METHODS: The present study used data from Yinzhou Cohort on adults without depression at baseline, and followed up until April 2020. Two-year moving average concentrations of particulate matter with a diameter ≤ 2.5 µm (PM2.5), ≤10 µm (PM10) and nitrogen dioxide (NO2) were measured using land-use regression (LUR) models for each participant. Depression cases were ascertained using the Health Information System (HIS) of the local health administration by linking the unique identifiers. We conducted Cox regression models with time-varying exposures to estimate the hazard ratios (HRs) and 95% confidence intervals (95% CIs) of depression with each pollutant, after adjusting for a sequence of individual covariates as demographic characteristics, lifestyles, and comorbidity. Besides, physical activity, baseline potential depressive symptoms, cancer status, COVID-19 pandemic, different outcome definitions and air pollution exposure windows were considered in sensitivity analyses. RESULTS: Among the 30,712 adults with a mean age of 62.22 ± 11.25, 1024 incident depression cases were identified over totaling 98,619 person-years of observation. Interquartile range increments of the air pollutants were associated with increased risks of depression, and the corresponding HRs were 1.59 (95%CI: 1.46, 1.72) for PM2.5, 1.49 (95%CI: 1.35, 1.64) for PM10 and 1.58 (95%CI: 1.42, 1.77) for NO2. Subgroup analyses suggested that participants without taking any protective measures towards air pollution were more susceptible. The results remained robust in all sensitivity analyses. CONCLUSIONS: Long-term exposure to ambient air pollution was identified as a risk factor for depression onset. Strategies to reduce air pollution are necessary to decrease the disease burden of depression.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Adult , Air Pollutants/adverse effects , Air Pollutants/analysis , Air Pollution/adverse effects , Air Pollution/analysis , China/epidemiology , Cohort Studies , Depression/epidemiology , Environmental Exposure/analysis , Humans , Incidence , Nitrogen Dioxide/analysis , Pandemics , Particulate Matter/adverse effects , Particulate Matter/analysis , SARS-CoV-2
9.
Environ Health Perspect ; 129(11): 117003, 2021 11.
Article in English | MEDLINE | ID: covidwho-1523382

ABSTRACT

BACKGROUND: Emerging evidence links ambient air pollution with coronavirus 2019 (COVID-19) disease, an association that is methodologically challenging to investigate. OBJECTIVES: We examined the association between long-term exposure to air pollution with SARS-CoV-2 infection measured through antibody response, level of antibody response among those infected, and COVID-19 disease. METHODS: We contacted 9,605 adult participants from a population-based cohort study in Catalonia between June and November 2020; most participants were between 40 and 65 years of age. We drew blood samples from 4,103 participants and measured immunoglobulin M (IgM), IgA, and IgG antibodies against five viral target antigens to establish infection to the virus and levels of antibody response among those infected. We defined COVID-19 disease using self-reported hospital admission, prior positive diagnostic test, or more than three self-reported COVID-19 symptoms after contact with a COVID-19 case. We estimated prepandemic (2018-2019) exposure to fine particulate matter [PM with an aerodynamic diameter of ≤2.5µm (PM2.5)], nitrogen dioxide (NO2), black carbon (BC), and ozone (O3) at the residential address using hybrid land-use regression models. We calculated log-binomial risk ratios (RRs), adjusting for individual- and area-level covariates. RESULTS: Among those tested for SARS-CoV-2 antibodies, 743 (18.1%) were seropositive. Air pollution levels were not statistically significantly associated with SARS-CoV-2 infection: Adjusted RRs per interquartile range were 1.07 (95% CI: 0.97, 1.18) for NO2, 1.04 (95% CI: 0.94, 1.14) for PM2.5, 1.00 (95% CI: 0.92, 1.09) for BC, and 0.97 (95% CI: 0.89, 1.06) for O3. Among infected participants, exposure to NO2 and PM2.5 were positively associated with IgG levels for all viral target antigens. Among all participants, 481 (5.0%) had COVID-19 disease. Air pollution levels were associated with COVID-19 disease: adjusted RRs=1.14 (95% CI: 1.00, 1.29) for NO2 and 1.17 (95% CI: 1.03, 1.32) for PM2.5. Exposure to O3 was associated with a slightly decreased risk (RR=0.92; 95% CI: 0.83, 1.03). Associations of air pollution with COVID-19 disease were more pronounced for severe COVID-19, with RRs=1.26 (95% CI: 0.89, 1.79) for NO2 and 1.51 (95% CI: 1.06, 2.16) for PM2.5. DISCUSSION: Exposure to air pollution was associated with a higher risk of COVID-19 disease and level of antibody response among infected but not with SARS-CoV-2 infection. https://doi.org/10.1289/EHP9726.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Adult , Aged , Air Pollutants/adverse effects , Air Pollutants/analysis , Air Pollution/analysis , Antibody Formation , Cohort Studies , Environmental Exposure/analysis , Humans , Middle Aged , Nitrogen Dioxide/analysis , Particulate Matter/adverse effects , Particulate Matter/analysis , SARS-CoV-2 , Spain/epidemiology
10.
Environ Sci Pollut Res Int ; 29(15): 22515-22530, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1520436

ABSTRACT

Escalating emissions of several air pollutants over South Asia could play a detrimental role in the regional and global atmosphere. Therefore, it is necessary to investigate these emissions within the boundary layer and at higher heights utilizing satellite data that are more inclusionary, where limited in situ observations are available. Here, we utilize the Infrared Atmospheric Sounding Interferometer (IASI), Ozone Monitoring Instruments (OMI), TROPOspheric Monitoring Instrument (TROPOMI), and Global Ozone Monitoring Experiment (GOME-2) hyperspectral satellite data to assess the changes in emission sources during Indian lockdown with a primary focus on the tropospheric profiles of ozone and carbon monoxide (CO). A significant reduction (> 20%) in the tropospheric ozone was seen over northern and northeast regions compared to 2018, while a dramatic increase (> 20%) compared to 2019 was seen. The subtropical dynamics mainly contributed to the increased ozone over the northern region. An analysis of the ozone production regime showed mostly NO2 limited regime over the major part of India and VOC limited regime over thermal power plants regions. Unlike in the boundary layer, where CO showed reduction (15-20%), CO profiles showed a consistent increase (as high as 31%) in the free troposphere over the majority of cities and thermal power plants. The CO total column also showed an increase (~ 20%) over central and western India and a slight decrease (5%) over northern India. Similar to CO, an increase (~ 15%) of NO2 column over the western region was observed particularly compared to 2019. However, unlike ozone and CO, reduction of tropospheric NO2 columns was seen over the major part of India, with the highest reduction over northern regions (20-52%). Furthermore, homogeneous yearly differences (> 30%) between OMI and TROPOMI NO2 observations were also seen distinctly over the remote areas. Contrary to surface-based studies, the present study shows an increase in CO, ozone (decrease), and NO2 at several locations and in the free troposphere during the lockdown.


Subject(s)
Air Pollutants , COVID-19 , Ozone , Air Pollutants/analysis , Communicable Disease Control , Environmental Monitoring , Humans , India , Nitrogen Dioxide/analysis , Ozone/analysis , Remote Sensing Technology , SARS-CoV-2
11.
Environ Sci Pollut Res Int ; 29(15): 21682-21691, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1509304

ABSTRACT

As an air pollutant closely related to urban traffic and heavy industrial capacity, the variation of NO2 (nitrogen dioxide) concentration can directly reflect the strength of socioeconomic activities. Using the weekly average results of daily product synthesis of tropospheric NO2 column concentrations from OMI (Ozone Monitoring Instrument) satellite inversion, a weekly-scale variation series of standardized socioeconomic activity index during the Spring Festival period of 2019-2021 is constructed. The results show that the OMI-NO2 satellite data are in good consistency with ground-based monitoring data; the Spring Festival holiday also suppresses socioeconomic activity in normal years, but the coronavirus disease 2019 (COVID-19) epidemic leads to an extended period of 2-3 weeks of weakened socioeconomic activity in China after the holiday, while the minimum value of socioeconomic activity intensity decreases by 0.12. Although socioeconomic activity is significantly suppressed in the short term, the intensity of socioeconomic activity rises steadily with the gradual resumption of work and production everywhere from the third week after the Chinese Spring Festival and has reached 60.91% of the highest level before the holiday in the seventh week after the holiday. OMI-NO2 satellite data can be used for a rapid assessment of the intensity of air pollution emissions and the level of socioeconomic activity in different regions.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollution/analysis , China , Environmental Monitoring/methods , Humans , Nitrogen Dioxide/analysis , Socioeconomic Factors
12.
Environ Sci Pollut Res Int ; 29(13): 18923-18931, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1491325

ABSTRACT

Nitrogen dioxide (NO2) is one of the main air pollutants, formed due to both natural and anthropogenic processes, which has a significant negative impact on human health. The COVID-19 pandemic has prompted countries to take various measures, including social distancing or stay-at-home orders. This study analyzes the impact of COVID-19 lockdown measures on nitrogen dioxide (NO2) changes in Central Asian countries. Data from TROPOspheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor satellite, as well as meteorological data, make it possible to assess changes in NO2 concentration in countries and major cities in the region. In particular, the obtained satellite data show a decreased tropospheric column of NO2. Its decrease during the lockdown (March 19-April 14) ranged from - 5.1% (Tajikistan) to - 11.6% (Turkmenistan). Based on the obtained results, it can be concluded that limitations in anthropogenic activities have led to improvements in air quality. The possible influence of meteorology is not assessed in this study, and the implied uncertainties cannot be quantified. In this way, the level of air pollution is expected to decrease as long as partial or complete lockdown continues.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollution/analysis , Cities , Communicable Disease Control , Environmental Monitoring , Humans , Nitrogen Dioxide/analysis , Pandemics , Particulate Matter/analysis , SARS-CoV-2
13.
Environ Sci Pollut Res Int ; 29(13): 18905-18922, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1491324

ABSTRACT

In this study, changes in air quality by NO2, O3, and PM10 in Barcelona metropolitan area and other parts of Catalonia during the COVID-19 lockdown with respect to pre-lockdown and to previous years (2018 and 2019) were evaluated. Selected air monitoring stations included 3 urban (Gràcia, Vall d'Hebron, and Granollers), 1 control site (Fabra Observatory), 1 semi-urban (Manlleu), and 3 rural (Begur, Bellver de Cerdanya, and Juneda). NO2 lockdown levels showed a diminution, which in relative terms was maximum in two rural stations (Bellver de Cerdanya, - 63% and Begur, - 61%), presumably due to lower emissions from the ceasing hotel and ski resort activities during eastern holidays. In absolute terms and from an epidemiologic perspective, decrease in NO2, also reinforced by the high amount of rainfall registered in April 2020, was more relevant in the urban stations around Barcelona. O3 levels increased in the transited urban stations (Gràcia, + 42%, and Granollers, + 64%) due to the lower titration effect by NOx. PM10 lockdown levels decreased, mostly in Gràcia, Vall d'Hebron, and Granollers (- 35, - 39%, and - 39%, respectively) due to traffic depletion (- 90% in Barcelona's transport). Correlation among mobility index in Barcelona (- 100% in retail and recreation) and contamination was positive for NO2 and PM10 and negative for O3 (P < 0.001). Satellite images evidenced two hotspots of NO2 in Spain (Madrid and Barcelona) in April 2018 and 2019 that disappeared in 2020. Overall, the benefits of lockdown on air quality in Catalonia were evidenced with NO2, O3 and PM10 levels below WHOAQG values in most of stations opposed to the excess registered in previous years.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollution/analysis , Communicable Disease Control , Environmental Monitoring , Humans , Nitrogen Dioxide/analysis , Particulate Matter/analysis , SARS-CoV-2 , Spain
14.
Sci Rep ; 11(1): 21336, 2021 10 29.
Article in English | MEDLINE | ID: covidwho-1493226

ABSTRACT

Air quality improvements pollution changes due to COVID-19 restrictions have been reported for many urban developments and large metropolitan areas, but the respective impacts at rural and remote zones are less frequently analysed. This study evaluated air pollution changes across all Portugal (68 stations) considering all urban, suburban and rural zones. PM10, PM2.5, NO2, SO2, ozone was analysed in pre-, during, and post-lockdown period (January-May 2020) and for a comparison also in 2019. NO2 was the most reduced pollutant in 2020, which coincided with decreased traffic. Significant drop (15-71%) of traffic related NO2 was observed specifically during lockdown period, being 55% for the largest and most populated region in country. PM was affected to a lesser degree (with substantial differences found for largely populated areas (Lisbon region ~ 30%; North region, up to 49%); during lockdown traffic-related PM dropped 10-70%. PM10 daily limit was exceeded 50% less in 2020, with 80% of exceedances before lockdown period. SO2 decreased by 35%, due to suspended industrial productions, whereas ozone concentrations slightly (though not significantly) increased (83 vs. 80 µg m-3).


Subject(s)
Air Pollution/analysis , COVID-19/prevention & control , Quarantine/methods , Rural Population , SARS-CoV-2 , Suburban Population , Urban Population , Air Pollutants/analysis , COVID-19/epidemiology , COVID-19/virology , Environmental Monitoring/methods , Humans , Nitrogen Dioxide/analysis , Ozone/analysis , Particulate Matter/analysis , Portugal/epidemiology , Sulfur Dioxide/analysis
15.
Environ Pollut ; 292(Pt B): 118396, 2022 Jan 01.
Article in English | MEDLINE | ID: covidwho-1482582

ABSTRACT

A growing number of studies report associations between air pollution and COVID-19 mortality. Most were ecological studies at the county or regional level which disregard important local variability and relied on data from only the first few months of the pandemic. Using COVID-19 deaths identified from death certificates in California, we evaluated whether long-term ambient air pollution was related to weekly COVID-19 mortality at the census tract-level during the first ∼12 months of the pandemic. Weekly COVID-19 mortality for each census tract was calculated based on geocoded death certificate data. Annual average concentrations of ambient particulate matter <2.5 µm (PM2.5) and <10 µm (PM10), nitrogen dioxide (NO2), and ozone (O3) over 2014-2019 were assessed for all census tracts using inverse distance-squared weighting based on data from the ambient air quality monitoring system. Negative binomial mixed models related weekly census tract COVID-19 mortality counts to a natural cubic spline for calendar week. We included adjustments for potential confounders (census tract demographic and socioeconomic factors), random effects for census tract and county, and an offset for census tract population. Data were analyzed as two study periods: Spring/Summer (March 16-October 18, 2020) and Winter (October 19, 2020-March 7, 2021). Mean (standard deviation) concentrations were 10.3 (2.1) µg/m3 for PM2.5, 25.5 (7.1) µg/m3 for PM10, 11.3 (4.0) ppb for NO2, and 42.8 (6.9) ppb for O3. For Spring/Summer, adjusted rate ratios per standard deviation increase were 1.13 (95% confidence interval: 1.09, 1.17) for PM2.5, 1.16 (1.11, 1.21) for PM10, 1.06 (1.02, 1.10) for NO2, and 1.09 (1.04, 1.14) for O3. Associations were replicated in Winter, although they were attenuated for PM2.5 and PM10. Study findings support a relation between long-term ambient air pollution exposure and COVID-19 mortality. Communities with historically high pollution levels might be at higher risk of COVID-19 mortality.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollution/analysis , California/epidemiology , Environmental Exposure , Humans , Mortality , Nitrogen Dioxide/analysis , Particulate Matter/analysis , SARS-CoV-2
16.
Sci Rep ; 11(1): 20339, 2021 10 13.
Article in English | MEDLINE | ID: covidwho-1467132

ABSTRACT

This study investigated the environmental spatial heterogeneity of novel coronavirus (COVID-19) and spatial and temporal changes among the top-20 metropolitan cities of the Asia-Pacific. Remote sensing-based assessment is performed to analyze before and during the lockdown amid COVID-19 lockdown in the cities. Air pollution and mobility data of each city (Bangkok, Beijing, Busan, Dhaka, Delhi, Ho Chi Minh, Hong Kong, Karachi, Mumbai, Seoul, Shanghai, Singapore, Tokyo, Wuhan, and few others) have been collected and analyzed for 2019 and 2020. Results indicated that almost every city was impacted positively regarding environmental emissions and visible reduction were found in Aerosol Optical Depth (AOD), sulfur dioxide (SO2), carbon monoxide (CO), and nitrogen dioxide (NO2) concentrations before and during lockdown periods of 2020 as compared to those of 2019. The highest NO2 emission reduction (~ 50%) was recorded in Wuhan city during the lockdown of 2020. AOD was highest in Beijing and lowest in Colombo (< 10%). Overall, 90% movement was reduced till mid-April, 2020. A 98% reduction in mobility was recorded in Delhi, Seoul, and Wuhan. This analysis suggests that smart mobility and partial shutdown policies could be developed to reduce environmental pollutions in the region. Wuhan city is one of the benchmarks and can be replicated for the rest of the Asian cities wherever applicable.


Subject(s)
Air Pollution/prevention & control , COVID-19/epidemiology , Environmental Monitoring/methods , Aerosols/analysis , Air Pollutants/analysis , Air Pollution/analysis , Asia, Southeastern/epidemiology , Carbon Monoxide/analysis , Cities/epidemiology , Far East/epidemiology , Humans , Nitrogen Dioxide/analysis , Particulate Matter/analysis , Physical Distancing , SARS-CoV-2/pathogenicity , Sulfur Dioxide/analysis
17.
PLoS One ; 16(9): e0258070, 2021.
Article in English | MEDLINE | ID: covidwho-1448578

ABSTRACT

BACKGROUND: Air pollution is the largest environmental health risk in the United Kingdom, and an issue of concern amongst outdoor workers. Road transport is a major source producing the largest amount of nitrogen dioxide (NO2) and ozone (O3) (as a secondary pollutant). Hundreds of vehicles enter and exit the Tidworth Camp's main gate daily, potentially producing these pollutants. However, the air pollution exposure experienced by personnel on guard duty is unknown. This study aimed to determine and compare background NO2 and O3 levels experienced by personnel on guard duty. METHODS: Cross-sectional data was collected using a static sampling technic on randomly selected days of the week. Data analysis was done using IBM-SPSS-26 and a p-value of <0.05 was considered statistically significant. RESULTS: The background concentration of NO2 and O3 pollutants were within recommended limits. There was no significant difference between mean morning and afternoon exposure levels for both pollutants. However, NO2 and O3 levels were significantly higher during weekdays compared to weekends (M = -0.022, SD = 0.007, t(6) = -8.672, p <0.0001 and M = -0.016, SD = 0.008, t(6) = -5.040, p = 0.002 respectively). Both pollutants showed no significant differences in exposure levels when only weekdays were compared. NO2 levels showed a weak positive correlation during weekdays (r = 0.04) and a strong positive correlation during weekends (r = 0.96). O3 levels had a positive correlation on both weekdays and weekends; however, levels on Monday showed a negative correlation (r = -0.55). Linear regression analysis showed that outside temperature was a significant predictor of O3 levels (p = 0.026). CONCLUSION: Personnel on guard duty experienced higher pollution levels during weekdays compared to weekends; however, air pollution levels for both pollutants were within recommended limits. Further studies are recommended over hotter months using a personal sampling technic to measure personal air pollution exposure levels in order to minimise any health and safety risks.


Subject(s)
Air Pollutants/analysis , Air Pollution/analysis , Nitrogen Dioxide/analysis , Occupational Exposure/analysis , Ozone/analysis , Cross-Sectional Studies , Environmental Exposure/analysis , Environmental Monitoring , Humans , Military Personnel , United Kingdom
18.
Environ Int ; 158: 106887, 2022 01.
Article in English | MEDLINE | ID: covidwho-1433201

ABSTRACT

The containment and closure policies adopted in attempts to contain the spread of the 2019 coronavirus disease (COVID-19) have impacted nearly every aspect of our lives including the environment we live in. These influences may be observed when evaluating changes in pollutants such as nitrogen dioxide (NO2), which is an important indicator for economic, industrial, and other anthropogenic activities. We utilized a data-driven approach to analyze the relationship between tropospheric NO2 and COVID-19 mitigation measures by clustering regions based on pollution levels rather than constraining the study units by predetermined administrative boundaries as pollution knows no borders. Specifically, three clusters were discovered signifying mild, moderate, and poor pollution levels. The most severely polluted cluster saw significant reductions in tropospheric NO2, coinciding with lockdown periods. Based on the clustering results, qualitative and quantitative analyses were conducted at global and regional levels to investigate the spatiotemporal changes. In addition, panel regression analysis was utilized to quantify the impact of policy measures on the NO2 reduction. This study found that a 23.58 score increase in the stringency index (ranging from 0 to 100) can significantly reduce the NO2 TVCD by 3.2% (p < 0.05) in the poor cluster in 2020, which corresponds to a 13.1% maximum reduction with the most stringent containment and closure policies implemented. In addition, the policy measures of workplace closures and close public transport can significantly decrease the tropospheric NO2 in the poor cluster by 6.7% (p < 0.1) and 4.5% (p < 0.1), respectively. An additional heterogeneity analysis found that areas with higher incomes, CO2 emissions, and fossil fuel consumption have larger NO2 TVCD reductions regarding workplace closures and public transport closures.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollution/analysis , Communicable Disease Control , Environmental Monitoring , Humans , Nitrogen Dioxide/analysis , Particulate Matter/analysis , Policy , SARS-CoV-2
19.
Sci Total Environ ; 735: 139542, 2020 Sep 15.
Article in English | MEDLINE | ID: covidwho-1428441

ABSTRACT

The effect of lockdown due to coronavirus disease (COVID-19) pandemic on air pollution in four Southern European cities (Nice, Rome, Valencia and Turin) and Wuhan (China) was quantified, with a focus on ozone (O3). Compared to the same period in 2017-2019, the daily O3 mean concentrations increased at urban stations by 24% in Nice, 14% in Rome, 27% in Turin, 2.4% in Valencia and 36% in Wuhan during the lockdown in 2020. This increase in O3 concentrations is mainly explained by an unprecedented reduction in NOx emissions leading to a lower O3 titration by NO. Strong reductions in NO2 mean concentrations were observed in all European cities, ~53% at urban stations, comparable to Wuhan (57%), and ~65% at traffic stations. NO declined even further, ~63% at urban stations and ~78% at traffic stations in Europe. Reductions in PM2.5 and PM10 at urban stations were overall much smaller both in magnitude and relative change in Europe (~8%) than in Wuhan (~42%). The PM reductions due to limiting transportation and fuel combustion in institutional and commercial buildings were partly offset by increases of PM emissions from the activities at home in some of the cities. The NOx concentrations during the lockdown were on average 49% lower than those at weekends of the previous years in all cities. The lockdown effect on O3 production was ~10% higher than the weekend effect in Southern Europe and 38% higher in Wuhan, while for PM the lockdown had the same effect as weekends in Southern Europe (~6% of difference). This study highlights the challenge of reducing the formation of secondary pollutants such as O3 even with strict measures to control primary pollutant emissions. These results are relevant for designing abatement policies of urban pollution.


Subject(s)
Air Pollution/analysis , Coronavirus Infections , Environmental Monitoring , Ozone/analysis , Pandemics , Pneumonia, Viral , Betacoronavirus , COVID-19 , China , Cities , Europe , Humans , Nitrogen Dioxide/analysis , Particulate Matter/analysis , SARS-CoV-2
20.
Sci Rep ; 11(1): 18614, 2021 09 20.
Article in English | MEDLINE | ID: covidwho-1428902

ABSTRACT

Air pollution is the result of comprehensive evolution of a dynamic and complex system composed of emission sources, topography, meteorology and other environmental factors. The establishment of spatiotemporal evolution model is of great significance for the study of air pollution mechanism, trend prediction, identification of pollution sources and pollution control. In this paper, the air pollution system is described based on cellular automata and restricted agents, and a Swarm Intelligence based Air Pollution SpatioTemporal Evolution (SI-APSTE) model is constructed. Then the spatiotemporal evolution analysis method of air pollution is studied. Taking Henan Province before and after COVID-19 pandemic as an example, the NO2 products of TROPOMI and OMI were analysed based on SI-APSTE model. The tropospheric NO2 Vertical Column Densities (VCDs) distribution characteristics of spatiotemporal variation of Henan province before COVID-19 pandemic were studied. Then the tropospheric NO2 VCDs of TROPOMI was used to study the pandemic period, month-on-month and year-on-year in 18 urban areas of Henan Province. The results show that SI-APSTE model can effectively analyse the spatiotemporal evolution of air pollution by using environmental big data and swarm intelligence, and also can establish a theoretical basis for pollution source identification and trend prediction.


Subject(s)
Air Pollution/analysis , Algorithms , COVID-19/epidemiology , Models, Theoretical , Nitrogen Dioxide/analysis , Pandemics , Air Pollutants/analysis , China/epidemiology , Diffusion , Environmental Monitoring , Geography , Humans , Multivariate Analysis , Seasons , Spatio-Temporal Analysis
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