scholarly journals Temporal Air Quality (NO2, O3 and PM10) Changes in Urban and Rural Stations in Catalonia during COVID-19 Lockdown: An Association with Human Mobility and Satellite Data

2021 ◽  
Author(s):  
Eva Gorrochategui ◽  
Isabel Hernandez ◽  
Eva Pérez-Gabucio ◽  
Sílvia Lacorte ◽  
Romà Tauler
Keyword(s):  
Air Quality ◽  
Metropolitan Area ◽  
Satellite Data ◽  
Satellite Images ◽  
Human Mobility ◽  
Control Site ◽  
Air Monitoring ◽  
Mobility Index ◽  
Ski Resort ◽  
Monitoring Stations

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 & 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.

scholarly journals Temporal Air Quality (NO2, O3 and PM10) Changes in Urban and Rural Stations in Catalonia During COVID-19 Lockdown: An Association with Human Mobility and Satellite Data

2021 ◽  
Author(s):  
Eva Gorrochategui ◽  
Isabel Hernandez ◽  
Eva Pérez-Gabucio ◽  
Sílvia Lacorte ◽  
Romà Tauler
Keyword(s):  
Air Quality ◽  
Metropolitan Area ◽  
Satellite Data ◽  
Satellite Images ◽  
Human Mobility ◽  
Control Site ◽  
Air Monitoring ◽  
Mobility Index ◽  
Ski Resort ◽  
Monitoring Stations

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 (Observatori Fabra), 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 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 & 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.

scholarly journals Using geo-targeted social media data to detect outdoor air pollution

2016 ◽  
Vol XLI-B2 ◽  
pp. 553-554 ◽  
Author(s):  
W. Jiang ◽  
Y. Wang ◽  
M. H. Tsou ◽  
X. Fu
Keyword(s):  
Social Media ◽  
Air Pollution ◽  
Air Quality ◽  
Environmental Changes ◽  
Real Space ◽  
Air Monitoring ◽  
Outdoor Air ◽  
Outdoor Air Pollution ◽  
Media Messages ◽  
Monitoring Stations

Outdoor air pollution has become a more and more serious issue over recent years (He, 2014). Urban air quality is measured at air monitoring stations. Building air monitoring stations requires land, incurs costs and entails skilled technicians to maintain a station. Many countries do not have any monitoring stations and even lack any means to monitor air quality. Recent years, the social media could be used to monitor air quality dynamically (Wang, 2015; Mei, 2014). However, no studies have investigated the inter-correlations between real-space and cyberspace by examining variation in micro-blogging behaviors relative to changes in daily air quality. Thus, existing methods of monitoring AQI using micro-blogging data shows a high degree of error between real AQI and air quality as inferred from social media messages. &lt;br&gt;&lt;br&gt; In this paper, we introduce a new geo-targeted social media analytic method to (1) investigate the dynamic relationship between air pollution-related posts on Sina Weibo and daily AQI values; (2) apply Gradient Tree Boosting, a machine learning method, to monitor the dynamics of AQI using filtered social media messages. Our results expose the spatiotemporal relationships between social media messages and real-world environmental changes as well suggesting new ways to monitor air pollution using social media.

scholarly journals Spatial and temporal representativeness of point measurements for nitrogen dioxide pollution levels in cities

2020 ◽  
Author(s):  
Ying Zhu ◽  
Jia Chen ◽  
Xiao Bi ◽  
Gerrit Kuhlmann ◽  
Ka Lok Chan ◽  
...  
Keyword(s):  
Air Quality ◽  
Nitrogen Dioxide ◽  
Satellite Data ◽  
World Health ◽  
Horizontal Distance ◽  
Street Level ◽  
The World ◽  
Mobile Measurements ◽  
The Impact ◽  
Monitoring Stations

Abstract. In many cities around the world the overall air quality is improving, but at the same time nitrogen dioxide (NO2) trends show stagnating values and in many cases could not be reduced below air quality standards recommended by the World Health Organization (WHO). Many large cities have built monitoring stations to continuously measure different air pollutants. While most stations follow defined rules in terms of measurement height and distance to traffic emissions, the question remains, how representative are those point measurements for the city-wide air quality. The question of the spatial coverage of a point measurement is important because it defines the area of influence and coverage of monitoring networks, determines how to assimilate monitoring data into model simulations or compare to satellite data with a coarser resolution, and is essential to assess the impact of the acquired data on public health. In order to answer this question, we combined different measurement data sets consisting of path averaging remote sensing data and in-situ point measurements in stationary and mobile setups from a measurement campaign that took place in Munich, Germany in June and July 2016. We developed an algorithm to strip temporal diversity and spatial patterns in order to construct a consistent NO2 pollution map for Munich. Continuous long-path differential optical absorption spectroscopy (LP DOAS) measurements were complemented with mobile cavity-enhanced (CE) DOAS, chemiluminescence (CL) and cavity attenuated phase shift (CAPS) instruments and were compared to monitoring stations and satellite data. In order to generate a consistent composite map, the LP DOAS diurnal cycle has been used to normalize for the time of the day dependency of the source patterns, so that spatial and temporal patterns can be analyzed separately. The resulting concentration map visualizes pollution hot spots at traffic junctions and tunnel exits in Munich, providing insights into the strong spatial variations. On the other hand, this database is beneficial to the urban planning and the design of control measures of environment pollution. Directly comparing on-street mobile measurements in the vicinity of monitoring stations resulted in a difference of 48 %. For the extrapolation of the monitoring station data to street level, we determined the influence of the measuring height and distance to the street. We found that a measuring height of 4m, at which the Munich monitoring stations measure, results in 16 % lower average concentrations than a measuring height of 1.5 m, which is the height of the inlet of our mobile measurements and a typical pedestrian breathing height. The horizontal distance of most stations to the center of the street of about 6 m also results in an average reduction of 13 % compared to street level concentration. A difference of 21 % in the NO2 concentrations remained, which could be an indication that city-wide measurements are needed for capturing the full range and variability of concentrations for assessing pollutant exposure and air quality in cities.

Magnetic monitoring of PM filters from Air Monitoring Stations during the COVID-19 lockdown in Rome, Italy (March 10th - May 18th, 2020)

2021 ◽  
Author(s):  
Aldo Winkler ◽  
Antonio Amoroso ◽  
Alessandro Di Giosa ◽  
Giada Marchegiani
Keyword(s):  
Magnetic Susceptibility ◽  
Air Quality ◽  
Urban Areas ◽  
Magnetic Measurements ◽  
Air Monitoring ◽  
Magnetic Minerals ◽  
Concentration Data ◽  
Local Conditions ◽  
The Impact ◽  
Monitoring Stations

&lt;p&gt;An extensive survey of the magnetic properties of PM filters from selected air monitoring stations in Rome and other localities in Latium Region (Sacco Valley, Civitavecchia, Fiumicino) was conducted for outlining the impact of the lockdown measures on air quality.&lt;/p&gt;&lt;p&gt;The magnetic measurements highlighted a relevant content of magnetic minerals, mostly attributable to traffic related sources, on the filters from two stations in Rome and two stations from the urban areas of Civitavecchia and Fiumicino.&lt;/p&gt;&lt;p&gt;The PM filters from the Sacco Valley showed reduced concentrations of magnetic minerals, compared to Rome, however higher than the Castel Di Guido and Civitavecchia Sant'Agostino control stations.&lt;/p&gt;&lt;p&gt;The daily PM concentration data did not generally correlate with the mass susceptibility data, indicating that PM was often dominated by non-ferromagnetic contents, presumably due to wind-driven natural dusts, as stressed by the frequent anticorrelation between mass magnetic susceptibility and PM concentration.&lt;/p&gt;&lt;p&gt;In Magnagrecia air quality station, Rome, the average values &amp;#8203;&amp;#8203;of the concentration depending magnetic parameters resulted about a half of those measured in 2005 on the filters from the same station.&lt;/p&gt;&lt;p&gt;From the Day plot, the filters with higher magnetic susceptibility values showed relatively coarse magnetite-like particles as the main magnetic minerals, ascribable to non-exhaust PM emissions from brakes.&lt;/p&gt;&lt;p&gt;This study confirmed that the interpretation of PM concentration during the lockdown is not straightforward and depends on many factors, such as natural inputs, resuspension and local conditions; anyway, magnetic analyses confirmed to be a valuable tool in PM source apportionment and concentration data interpretation.&lt;/p&gt;

scholarly journals Changes in air quality and human mobility in the USA during the COVID-19 pandemic

2020 ◽  
Author(s):  
Cristina L. Archer ◽  
Guido Cervone ◽  
Maryam Golbazi ◽  
Nicolas Al Fahel ◽  
Carolynne Hultquist
Keyword(s):  
Air Quality ◽  
Power Plants ◽  
Human Mobility ◽  
Human Movement ◽  
Motor Vehicles ◽  
Mobility Index ◽  
The Usa ◽  
The Mean ◽  
Ground Monitoring ◽  
Average Drop

Abstract The first goal of this study is to quantify the magnitude and spatial variability of air quality changes in the USA during the COVID-19 pandemic. We focus on two pollutants that are federally regulated, nitrogen dioxide (NO2) and fine particulate matter (PM2.5). NO2 and PM2.5 are both primary and secondary pollutants, meaning that they can be emitted either directly into the atmosphere or indirectly from chemical reactions of emitted precursors. NO2 is emitted during fuel combustion by all motor vehicles and airplanes. PM2.5 is emitted by airplanes and, among motor vehicles, mostly by diesel vehicles, such as commercial heavy-duty diesel trucks. Both PM2.5 and NO2 are also emitted by fossil-fuel power plants, although PM2.5 almost exclusively by coal power plants. Observed concentrations at all available ground monitoring sites (240 and 480 for NO2 and PM2.5, respectively) were compared between April 2020, the month during which the majority of US states had introduced some measure of social distancing (e.g., business and school closures, shelter-in-place, quarantine), and April of the prior 5 years, 2015–2019, as the baseline. Large, statistically significant decreases in NO2 concentrations were found at more than 65% of the monitoring sites, with an average drop of 2 parts per billion (ppb) when compared to the mean of the previous 5 years. The same patterns are confirmed by satellite-derived NO2 column totals from NASA OMI, which showed an average drop in 2020 by 13% over the entire country when compared to the mean of the previous 5 years. PM2.5 concentrations from the ground monitoring sites, however, were not significantly lower in 2020 than those in the past 5 years and were more likely to be higher than lower in April 2020 when compared with those in the previous 5 years. After correcting for the decreasing multi-annual concentration trends, the net effect of COVID-19 at the ground stations in April 2020 was a reduction in NO2 concentrations by − 1.3ppb and a slight increase in PM2.5 concentrations by + 0.28 μg/m3. The second goal of this study is to explain the different responses of these two pollutants, i.e., NO2 was significantly reduced but PM2.5 was nearly unaffected, during the COVID-19 pandemic. The hypothesis put forward is that the shelter-in-place measures affected people’s driving patterns most dramatically, thus passenger vehicle NO2 emissions were reduced. Commercial vehicles (generally diesel) and electricity demand for all purposes remained relatively unchanged, thus PM2.5 concentrations did not drop significantly. To establish a correlation between the observed NO2 changes and the extent to which people were actually sheltering in place, thus driving less, we used a mobility index, which was produced and made public by Descartes Labs. This mobility index aggregates cell phone usage at the county level to capture changes in human movement over time. We found a strong correlation between the observed decreases in NO2 concentrations and decreases in human mobility, with over 4 ppb decreases in the monthly average where mobility was reduced to near 0 and around 1 ppb decrease where mobility was reduced to 20% of normal or less. By contrast, no discernible pattern was detected between mobility and PM2.5 concentrations changes, suggesting that decreases in personal-vehicle traffic alone may not be effective at reducing PM2.5 pollution.

scholarly journals The Impacts of the COVID-19 Lockdown on Air Quality in the Guanzhong Basin, China

2020 ◽  
Vol 12 (18) ◽  
pp. 3042
Author(s):  
Kainan Zhang ◽  
Gerrit de Leeuw ◽  
Zhiqiang Yang ◽  
Xingfeng Chen ◽  
Jiashuang Jiao
Keyword(s):  
Air Quality ◽  
Virus Disease ◽  
Human Mobility ◽  
Monitoring Network ◽  
Chinese Government ◽  
Before And After ◽  
Concentration Changes ◽  
Guanzhong Basin ◽  
Pm2.5 And Pm10 ◽  
Monitoring Stations

The Corona Virus Disease 2019 (COVID-19) appeared in Wuhan, China, at the end of 2019, spreading from there across China and within weeks across the whole world. In order to control the rapid spread of the virus, the Chinese government implemented a national lockdown policy. It restricted human mobility and non-essential economic activities, which, as a side effect, resulted in the reduction of the emission of pollutants and thus the improvement of the air quality in many cities in China. In this paper, we report on a study on the changes in air quality in the Guanzhong Basin during the COVID-19 lockdown period. We compared the concentrations of PM2.5, PM10, SO2, NO2, CO and O3 obtained from ground-based monitoring stations before and after the COVID-19 outbreak. The analysis confirmed that the air quality in the Guanzhong Basin was significantly improved after the COVID-19 outbreak. During the emergency response period with the strictest restrictions (Level-1), the concentrations of PM2.5, PM10, SO2, NO2 and CO were lower by 37%, 30%, 29%, 52% and 33%, respectively, compared with those before the COVID-19 outbreak. In contrast, O3 concentrations increased substantially. The changes in the pollutant concentrations varied between cities during the period of the COVID-19 pandemic. The highest O3 concentration changes were observed in Xi’an, Weinan and Xianyang city; the SO2 concentration decreased substantially in Tongchuan city; the air quality had improved the most in Baoji City. Next, to complement the sparsely distributed air quality ground-based monitoring stations, the geographic and temporally weighted regression (GTWR) model, combined with satellite observations of the aerosol optical depth (AOD) and meteorological factors was used to estimate the spatial and temporal distributions of PM2.5 and PM10 concentrations with a resolution of 6 km × 6 km before and after the COVID-19 outbreak. The model was validated by a comparison with ground-based observations from the air quality monitoring network in five cities in the Guanzhong Basin with excellent statistical metrics. For PM2.5 and PM10 the correlation coefficients R2 were 0.86 and 0.80, the root mean squared errors (RMSE) were 11.03 µg/m3 and 14.87 µg/m3 and the biases were 0.19 µg/m3 and −0.27 µg/m3, which led to the conclusion that the GTWR model could be used to estimate the PM concentrations in locations where monitoring data were not available. Overall, the PM concentrations in the Guanzhong Basin decreased substantially during the lockdown period, with a strong initial decrease and a slower one thereafter, although the spatial distributions remained similar.

scholarly journals Emission Scenario Assessment of Gasohol Reformulation Proposals and Ethanol Use in the Metropolitan Area of São Paulo

2008 ◽  
Vol 2 (1) ◽  
pp. 166-175 ◽  
Author(s):  
L.D. Martins ◽  
M.F. Andrade
Keyword(s):  
Air Quality ◽  
Metropolitan Area ◽  
Sao Paulo ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Emission Scenarios ◽  
Ozone Concentrations ◽  
Air Quality Monitoring Stations ◽  
The Impact ◽  
Monitoring Stations

The frequent episodes of high concentrations of ozone and of inhalable particulate matter occurring in the Metropolitan Area of Sao Paulo (MASP) are primarily associated with vehicle emissions. The objective of this study was to evaluate the impact of the use of reformulations of the gasoline-ethanol blend known as gasohol and of ethanol on the ozone formation. A three-dimensional photochemical model was employed to estimate the sensitivity of ozone and evaluate the implementation of emission scenarios, considering various fuel formulations, in the MASP. The base case ozone concentrations were consistent with the observations over six air quality monitoring stations located in the MASP, suggesting that the model can be used to evaluate the impact that various emission scenarios would have on ozone levels. Six scenarios were analyzed; scenarios 1 to 5 involved reductions in compounds found in gasohol in various proportions compared with the base emission inventory and scenario 6 specified that the entire light duty fleet would burn pure ethanol. In scenario 3 (reductions in olefins, aromatics and benzene) and scenario 5 (reductions in the five species that are associated with higher ozone sensitivity), ozone concentrations were below the national standard only at the air quality monitoring stations (not domain-wide). Our results suggest that implementing scenario 6 would improve air quality in the MASP.

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