scholarly journals Impact of COVID-19 Lockdowns on Air Quality and Health. Association between Concentrations of Tropospheric Ozone and Infection Cases and Deaths in Spain

2020 ◽  
Author(s):  
Eusebio R Álvarez-Vázquez ◽  
Pablo A Castro-Guijarro ◽  
Antonio José Fernandez-Espinosa
Keyword(s):  
Air Quality ◽  
Tropospheric Ozone ◽  
Air Pollutants ◽  
Hospital Admissions ◽  
Meteorological Factors ◽  
Vehicular Traffic ◽  
Respiratory Problems ◽  
Health Association ◽  
Industrial Gases ◽  
Pearson Correlations

Abstract BackgroundThis work describes the changes of the air quality and the health implications caused by the lockdown of the first-wave provoked by the SARS-CoV-2 pandemic. Air pollutants were studied in 83 locations in Southern Spain. The study covered urban and industrial gases, NO2, CO, SO2, H2S and O3, and also PM10 and PM2.5 particles.MethodsIt was evaluated the increase and decrease of concentrations during the state of alarm declared on 14th March. Pearson correlations for air pollutants, meteorological factors, vehicular traffic densities (VTDs) and data of infections and deaths caused by the COVID-19 disease were also assessed.ResultsIt was found a clear reduction in carbon monoxide (-25% to -83%), particulate matter (-21% to -42%) and mainly nitrogen dioxide (-55% to -81%) in trafficked areas during the lockdown, reducing cardiovascular and respiratory problems. CO, SO2 and H2S increased (+26 to 34%, +68 to +85% and +32 to +84%) at industrial locations. O3 increased along the lockdown period coinciding with reductions in NO2 and CO (r = -0.90 and -0.81). This ozone rising constitute the ozone lockdown effect (OLE), increasing the risk of pneumonia hospital admissions. Regarding traffic, Pearson coefficients between ozone and VTDs were higher during lockdown than pre-lockdown period, and in the most trafficked areas a reduction in PM10 and PM2.5 levels was observed, contributing this also to the OLE.ConclusionsEffects of ozone on COVID-19 disease was revealed by the graphic associations and correlations found between O3 levels and infection cases and deaths, which were remarkable, constituting in this case the ozone COVID effect (OCE): when concentrations of O3 increase, the incidence of the disease is higher; when O3 falls, infection cases are reduced.

scholarly journals Positive correlation between long term emission of several air pollutants and COVID-19 deaths in Sweden

2020 ◽  
Author(s):  
Lars Helander
Keyword(s):  
Air Quality ◽  
Population Density ◽  
Air Pollutants ◽  
Meteorological Factors ◽  
Threshold Value ◽  
Wind Speeds ◽  
Average Wind ◽  
Incidence And Mortality ◽  
Positive Correlations

AbstractSeveral recent studies have found troubling links between air pollution and both incidence and mortality of COVID-19, the pandemic disease caused by the virus SARS-CoV-2. Here, we investigate whether such a link can be found also in Sweden, a country with low population density and a relatively good air quality in general, with low background levels of important pollutants such as PM2.5 and NO2. The investigation is carried out by relating normalized emission levels of several air pollutants to normalized COVID-19 deaths at the municipality level, after applying a sieve function using an empirically determined threshold value to filter out noise. We find a fairly strong correlation for PM2.5, PM10 and SO2, and a moderate one for NOx. We find no correlation neither for CO, nor (as expected) for CO2. Our results are statistically significant and the calculations are simple and easily verifiable. Since the study considers only emission levels of air pollutants and not measurements of air quality, climatic and meteorological factors (such as average wind speeds) can trivially be ruled out as confounders. Finally, we also show that although there are small positive correlations between population density and COVID-19 deaths in the studied municipalities (which are for the most part rural and non densely populated) they are either weak or not statistically significant.

scholarly journals Mobility Restrictions and Air Quality under COVID-19 Pandemic in São Paulo, Brazil

2020 ◽  
Author(s):  
Edmilson D. Freitas ◽  
Sergio A. Ibarra-Espinosa ◽  
Mario E. Gavidia-Calderón ◽  
Amanda Rehbein ◽  
Sameh A. Abou Rafee ◽  
...  
Keyword(s):  
Air Quality ◽  
Air Pollutants ◽  
Large Scale ◽  
Hospital Admissions ◽  
Air Pollutant ◽  
Government Officials ◽  
Social Unrest ◽  
The Public ◽  
Containment Measure ◽  
Mobility Reduction

Social distancing policies put in place during COVID-19 epidemic in addition to helping to limit the spread of the disease also contributed to improving urban air quality. Here we show a decrease in air pollutant concentration as a consequence of mobility reduction in São Paulo during the containment measure which began on 22nd March 2020. When comparing to foregoing weeks to equivalent periods of 2019, the concentration of most air pollutants sharply decreased in the first days of mobility restriction, to then increase again after government officials downplayed the threat of the disease. This trend is also followed by a decrease in hospital admissions by SARS-influenza. Therefore, despite the great economic and social unrest caused by the pandemic, this unique situation shows that large-scale mobility reduction policy had a significant impact on air quality, benefiting, directly and indirectly, the public health system.

scholarly journals Study of Trends in Concentrations of Basic Air Pollutants in the Malopolska Province

2020 ◽  
Vol 27 (4) ◽  
pp. 567-578
Author(s):  
Mariusz Filak ◽  
Szymon Hoffman
Keyword(s):  
Air Quality ◽  
Environmental Protection ◽  
Tropospheric Ozone ◽  
Air Pollutants ◽  
Linear Equations ◽  
Measurement Data ◽  
Automatic Monitoring ◽  
Air Pollutant ◽  
Long Term Measurement

Abstract The purpose of the paper was to analyse the trends observed at air monitoring stations in the Malopolska Province - one of the most polluted regions in Poland. The study was carried out on the basis of long-term measurement data registered at five selected stations of automatic monitoring of air quality in the Malopolska Province. Trends evaluation was made on the basis of mean annual concentrations, taken from the database of the Chief Inspectorate for Environmental Protection in Poland. Separately for each basic air pollutant, such as SO2, NO2, NOx, CO, PM10 and O3, trend lines and their linear equations were determined to illustrate the direction of changes in concentrations. The obtained equations of the trend lines indicate the threat to the environment in the Malopolska Province. Based on the results obtained it can be concluded that for recent years there has been observed the concentration decrease of main air pollutants, except of tropospheric ozone.

scholarly journals Emission level of air pollutants during 2019 pre-haze, haze, and post-haze episodes in Kuala Lumpur and Putrajaya

2021 ◽  
Vol 4 (2) ◽  
pp. 137
Author(s):  
Safari Zainal ◽  
Nurfatiha Mursyida Zamre ◽  
Md. Firoz Khan
Keyword(s):  
Carbon Monoxide ◽  
Air Quality ◽  
Wind Direction ◽  
Air Pollutants ◽  
Power Plants ◽  
Meteorological Factors ◽  
Ambient Air ◽  
Kuala Lumpur ◽  
North East ◽  
East Malaysia

Nowadays, due to population growth and industrialisation, air quality in Malaysia is becoming a critical threat. Air pollution has become a serious issue due to its impacts on humans, animals, and the environment. Malaysia experienced air quality deterioration in 2019 when the episodes of haze happened from July to September. It was due to the local and transboundary sources such as vehicles, factories, power plants, and biomass burning from Sumatra. This study aims to differentiate the level of the potential air pollutants, examine the influence of meteorological factors on the potential air pollutants and determine the local and transboundary impact on the potential air pollutants during episodes of pre-haze, haze, and post-haze in Kuala Lumpur and Putrajaya in 2019. Secondary physical and data on meteorology were obtained from the continuous ambient air quality monitoring (CAQM) stations by the Malaysian Department of Environment (DOE). The data obtained from CAQM were physical: particulate matters (PM2.5 & PM10), carbon monoxide (CO), nitrogen dioxide (NO2), sulphur dioxide (SO2), and level ozone (O3); as well as meteorological: temperature (T), relative humidity (RH), wind speed (WS) and wind direction (WDir). Overall, the particulate matter (PM2.5, PM10) and carbon monoxide which are the pollutants that involve the formation of haze in Kuala Lumpur and Putrajaya are higher during haze episodes compared to pre-haze and post-haze episodes while the other pollutants (NO2, SO2, O3) are fluctuated throughout the entire episode due to its sources and the influence of meteorological factors. The backward trajectory indicated that the air pollutants are influenced by wind direction from South West Malaysia (SWM) and North East Malaysia (NEM) throughout the entire year.

scholarly journals Association between respiratory hospital admissions and air quality in Portugal: A count time series approach

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0253455
Author(s):  
Ana Martins ◽  
Manuel Scotto ◽  
Ricardo Deus ◽  
Alexandra Monteiro ◽  
Sónia Gouveia
Keyword(s):  
Time Series ◽  
Air Quality ◽  
Air Pollutants ◽  
Hospital Admissions ◽  
Past History ◽  
Outcome Variable ◽  
Count Time Series ◽  
The Past ◽  
History Of ◽  
One Step

Although regulatory improvements for air quality in the European Union have been made, air pollution is still a pressing problem and, its impact on health, both mortality and morbidity, is a topic of intense research nowadays. The main goal of this work is to assess the impact of the exposure to air pollutants on the number of daily hospital admissions due to respiratory causes in 58 spatial locations of Portugal mainland, during the period 2005-2017. To this end, INteger Generalised AutoRegressive Conditional Heteroskedastic (INGARCH)-based models are extensively used. This family of models has proven to be very useful in the analysis of serially dependent count data. Such models include information on the past history of the time series, as well as the effect of external covariates. In particular, daily hospitalisation counts, air quality and temperature data are endowed within INGARCH models of optimal orders, where the automatic inclusion of the most significant covariates is carried out through a new block-forward procedure. The INGARCH approach is adequate to model the outcome variable (respiratory hospital admissions) and the covariates, which advocates for the use of count time series approaches in this setting. Results show that the past history of the count process carries very relevant information and that temperature is the most determinant covariate, among the analysed, for daily hospital respiratory admissions. It is important to stress that, despite the small variability explained by air quality, all models include on average, approximately two air pollutants covariates besides temperature. Further analysis shows that the one-step-ahead forecasts distributions are well separated into two clusters: one cluster includes locations exclusively in the Lisbon area (exhibiting higher number of one-step-ahead hospital admissions forecasts), while the other contains the remaining locations. This results highlights that special attention must be given to air quality in Lisbon metropolitan area in order to decrease the number of hospital admissions.

scholarly journals Implication of Secondary Atmospheric Pollutants in the Air Quality: A Case-Study for Ozone

2021 ◽  
Author(s):  
David Galán Madruga
Keyword(s):  
Public Health ◽  
Air Quality ◽  
Human Health ◽  
Tropospheric Ozone ◽  
Air Pollutants ◽  
Ground Level ◽  
Atmospheric Pollutants ◽  
Emission Sources ◽  
Rural Environments ◽  
Harmful Effects

Air quality and Public Health are concepts linked to each other. Within the frame of Public Health, a wide range of external factors, derived from rising wastes towards all environmental compartments, may generate harmful effects on human health. In particular, the release of polluting compounds into the ambient air coming from emission sources is a paramount concern, given that atmospheric pollution is considered the most significant environmental risk for human beings. In this context, while this chapter to provide an overview of the most critical air pollutants that can depict air quality status in terms of exposure, potential effects, emission sources, and types of pollutants, the principal purpose is focused on secondary atmospheric pollutants, emphasizing to tropospheric ozone as a significant pollutant within this group. In this sense, aspects such as the atmospheric ozone chemistry responsible for its formation and its spatial distribution into vast territories, including urban, suburban, and rural environments, were conveniently explained. Based on displayed evidence, primaries air pollutants, mainly nitrogen oxides, volatile organic compounds, and carbon monoxide, are responsible for the tropospheric ozone’s formation; therefore, reducing their levels could be translated into a decrease of ozone concentrations at the ground-level. Attending to the ozone distribution, the revealed findings lead to the next concentration gradient: higher ozone levels in rural, followed by suburban and urban sites, respectively. Finally, it can be concluded that the importance of tropospheric ozone within air quality lies in the possibility of producing harmful effects on human health and generating climate changes, either directly or indirectly.

scholarly journals Spatio-temporal variations of lower tropospheric pollutants and their relation with meteorological factors in Karachi, Pakistan

2021 ◽  
Author(s):  
Dilshad Ahmed ◽  
Zafar Iqbal Shams ◽  
Moinuddin Ahmed ◽  
Muhammad Fahim Siddique
Keyword(s):  
Air Quality ◽  
Air Pollutants ◽  
Meteorological Factors ◽  
Temporal Variations ◽  
Motor Vehicles ◽  
Oxides Of Nitrogen ◽  
Housing Authority ◽  
Emission Standards ◽  
Spatio Temporal ◽  
The City

Abstract Despite being one of the most populated cities globally, the air quality of Karachi is hardly ever comprehended. The present paper investigates the outdoor concentrations of 10 air pollutants, viz. NO, NO2, NOx, SO2, CO, O3, CH4, methane carbon, non-methane hydrocarbons, and total hydrocarbons at three different city sites, viz., Sohrab Goth, Defense Housing Authority, and North Nazimabad. The results demonstrate that these pollutants severely affected the city's air quality. The annual mean concentrations of both NO2 and SO2 exceeded the WHO guidelines at some study sites. The city experiences varied concentrations of major air pollutants because three types of fuel, viz. diesel, gasoline, and compressed natural gas, operate the motor vehicles in this conurbation. The study also correlates the various air pollutants with each other and with various meteorological factors. All the three oxides of nitrogen are statistically associated at all three sites with one another, with SO2 at Defense Housing Authority, with CO at North Nazimabad, and with meteorological factors at Sohrab Goth and Defense Housing Authority. Carbon monoxide is statistically associated with the meteorological factors only at North Nazimabad. The study suggests that higher air pollution in the city is due to the adoption of lenient vehicular emission standards because stringent emission standards cannot be adopted due to the non-availability of low or zero sulfur fuel. Moreover, ineffective regulation of exiting standards also contributes to higher vehicular emissions in the city.

The impact analysis of traffic and meteorological factors on air pollution risk in Taiwan, Taipei City

2021 ◽  
Author(s):  
Yu-Ting Lin ◽  
Yuan-Chien Lin
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Linear Regression ◽  
Regression Model ◽  
Air Pollutants ◽  
Stepwise Regression ◽  
Meteorological Factors ◽  
Multivariate Linear Regression ◽  
The Impact ◽  
Significant Factors

<p>Air pollution has always been one of the serious issues around the world, not only related to the large-scale climate environment, but also related to local-scale vehicles-caused air pollutants in the city. Generally, diesel-burning vehicles emit NO<sub>X</sub>, SO<sub>2, </sub>CO; gasoline burning vehicles emit CO, CO<sub>2</sub>, NO<sub>X</sub> respectively. The common air pollutants CO and NO<sub>X</sub> are widely regarded as the primary traffic-caused air pollutants. Therefore in this study, we take vehicle detector data including car speed, car volume, lane occupy as well as meteorological data and the air pollutants concentration in consider. Firstly, we use the Stepwise Regression Model(SRM) to select the significant factors for the target air pollutants and predict them with multivariate linear regression. Secondly, we also combine Long Short-Terms Memory (LSTM) Model to simulate the highly nonlinear and unstationary complex chemical interaction between air pollutants. In this study we got high model accuracy performance in primary pollutants prediction (CO,NO<sub>X</sub>) by including the vehicle detector data with both Multivariate linear regression Model and LSTM model which conclude that the vehicle detector data can significantly improve the quality of model prediction. This process select the statistically significant factors of the pollutants, and also establishes a neural network model including traffic, meteorological factors and air quality which contribute to the air pollutants risk management of government agency.</p><p><strong>Keywords: traffic pollutants, air quality, stepwise regression, LSTM model</strong></p>

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