scholarly journals Relations between Air Quality and Covid-19 Lockdown Measures in Valencia, Spain

Author(s):  
Gabriele Donzelli ◽  
Lorenzo Cioni ◽  
Mariagrazia Cancellieri ◽  
Agustin Llopis-Morales ◽  
María Morales-Suárez-Varela

The set of measures to contain the diffusion of COVID-19 instituted by the European governments gave an unparalleled opportunity to improve our understanding of the transport and industrial sectors’ contribution to urban air pollution. The purpose of this study was to assess the impacts of the lockdown measures on air quality and pollutant emissions in Valencia, Spain. For this reason, we determined if there was a significant difference in the concentration levels of different particulate matter (PM) sizes, PM10, PM2.5, and NOx, NO2, NO, and O3, between the period of restrictions in 2020 and the same period in 2019. Our findings indicated that PM pollutant levels during the lockdown period were significantly different from the same period of the previous year, even if there is variability in the different local areas. The highest variations reduction in the PM10 and PM2.5 levels were observed for the València Centre, València Avd Francia, and València Pista de Silla (all of the urban traffic type) in which there was a reduction of 58%–42%, 56%–53%, and 60%–41% respectively. Moreover, consistent with recent studies, we observed a significant reduction in nitric oxide levels in all the air monitoring stations. In all seven monitoring stations, it was observed, in 2020, NOx, NO2, and NO concentrations decreased by 48.5%–49.8%–46.2%, 62.1%–67.4%–45.7%, 37.4%–35.7%–35.3%, 60.7%–67.7%–47.1%, 65.5%–65.8%–63.5%, 60.0%–64.5%–41.3%, and 60.4%–61.6%–52.5%, respectively. Lastly, overall O3 levels decreased during the lockdown period, although this phenomenon was more closely related to weather conditions. Overall, no significant differences were observed between the meteorological conditions in 2019 and 2020. Our findings suggest that further studies on the effect of human activities on air quality are needed and encourage the adoption of a holistic approach to improve urban air quality.

Author(s):  
Vlado Spiridonov ◽  
Nenad Ancev ◽  
Boro Jakimovski ◽  
Goran Velinov

Abstract Urban air quality is determined by a complex interaction of factors associated with anthropogenic emissions, atmospheric circulation, and geographic factors. Most of the urban-present pollution aerosols and trace gases are toxic to human health and responsible for damage of flora, fauna, and materials. The air quality prediction system based on state-of-the-art Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) has been configured and designed for North Macedonia. An extensive set of experiments have been performed with different model settings to forecast simultaneously the weather and air quality over the country. The initial results and the finding from other similar studies suggest that chemical initialization plays a significant role in a more accurate, both qualitative and quantitative forecast and assessment of urban air pollution. The main objective of the present research is to develop and test for a novel chemical initialization input in the air quality forecast system in North Macedonia. It is performed using ensemble technique in respect to treatment of the mobile emissions data using scaling factors. The WRF-Chem prediction has shown a high sensitivity to different scaling methods. While scaling of the overall mobile annual emissions tends to produce some discrepancies regarding the PM10 concentration level (overestimation during summer and underestimation during winter), an improved approach that utilizes scaling, in a wider range, only the mobile emissions originated from household heating offers the possibility of more detailed parameter fitting. The verification results indicate that the best accuracy across all scores for the winter months was achieved when scaling up the baseline pollutant input using a higher factor, while in the other seasons, the best results were achieved when scaling down the baseline pollutant emissions by a significant factor. Taking all into account, we can conclude that the seasonal variation in the pollutant input to the atmosphere is a significant factor in simulating the pollution in this region. Therefore, these seasonal variations must be taken into account when fitting the pollutant emission input to any model.


2021 ◽  
pp. 94-106
Author(s):  
Porush Kumar ◽  
Kuldeep ◽  
Nilima Gautam

Air pollution is a severe issue of concern worldwide due to its most significant environmental risk to human health today. All substances that appear in excessive amounts in the environment, such as PM10, NO2, or SO2, may be associated with severe health problems. Anthropogenic sources of these pollutants are mainly responsible for the deterioration of urban air quality. These sources include stationary point sources, mobile sources, waste disposal landfills, open burning, and similar others. Due to these pollutants, people are at increased risk of various serious diseases like breathing problems and heart disease, and the death rate due to these diseases can also increase. Hence, air quality monitoring is essential in urban areas to control and regulate the emission of these pollutants to reduce the health impacts on human beings. Udaipur has been selected for the assessment of air quality with monitored air quality data. Air quality monitoring stations in Udaipur city are operated by the CPCB (Central Pollution Control Board) and RSPCB (Rajasthan State Pollution Control Board). The purpose of this study is to characterize the level of urban air pollution through the measurement of PM10, NO2, or SO2 in Udaipur city, Rajasthan (India). Four sampling locations were selected for Udaipur city to assess the effect of urban air pollution and ambient air quality, and it was monitored for a year from 1st January 2019 to 31st December 2019. The air quality index has been calculated with measured values of PM10, NO2, and SO2. The concentration of PM10 is at a critical level of pollution and primarily responsible for bad air quality and high air quality Index in Udaipur city.


2016 ◽  
Vol 113 (28) ◽  
pp. 7756-7761 ◽  
Author(s):  
Jun Liu ◽  
Denise L. Mauzerall ◽  
Qi Chen ◽  
Qiang Zhang ◽  
Yu Song ◽  
...  

As part of the 12th Five-Year Plan, the Chinese government has developed air pollution prevention and control plans for key regions with a focus on the power, transport, and industrial sectors. Here, we investigate the contribution of residential emissions to regional air pollution in highly polluted eastern China during the heating season, and find that dramatic improvements in air quality would also result from reduction in residential emissions. We use the Weather Research and Forecasting model coupled with Chemistry to evaluate potential residential emission controls in Beijing and in the Beijing, Tianjin, and Hebei (BTH) region. In January and February 2010, relative to the base case, eliminating residential emissions in Beijing reduced daily average surface PM2.5 (particulate mater with aerodynamic diameter equal or smaller than 2.5 micrometer) concentrations by 14 ± 7 μg⋅m−3 (22 ± 6% of a baseline concentration of 67 ± 41 μg⋅m−3; mean ± SD). Eliminating residential emissions in the BTH region reduced concentrations by 28 ± 19 μg⋅m−3 (40 ± 9% of 67 ± 41 μg⋅m−3), 44 ± 27 μg⋅m−3 (43 ± 10% of 99 ± 54 μg⋅m−3), and 25 ± 14 μg⋅m−3 (35 ± 8% of 70 ± 35 μg⋅m−3) in Beijing, Tianjin, and Hebei provinces, respectively. Annually, elimination of residential sources in the BTH region reduced emissions of primary PM2.5 by 32%, compared with 5%, 6%, and 58% achieved by eliminating emissions from the transportation, power, and industry sectors, respectively. We also find air quality in Beijing would benefit substantially from reductions in residential emissions from regional controls in Tianjin and Hebei, indicating the value of policies at the regional level.


2020 ◽  
Author(s):  
Christopher Cantrell ◽  
Vincent Michoud ◽  
Paola Formenti ◽  
Jean-Francois Doussin ◽  
Aline Gratien ◽  
...  

<p>In recent decades, significant progress has been made in understanding the causes and impacts of urban air pollution, generally leading to improved air quality through enhanced knowledge and regulatory action. While a significant number of people still die prematurely each year from air pollution, progress continues to be made. Scientific investigation has exposed the processes by which primary pollutants, such as oxides of nitrogen and volatile organic compounds, are processed in the atmosphere, leading to their oxidation and ultimate removal, while at the same time producing secondary species such as ozone and organic aerosols.</p><p>Research has uncovered the complex chemistry of natural organic compounds released from trees and other plants. Because of the chemical structures of these compounds, they react somewhat differently than organic substances typically found in urban environments. The ACROSS (<strong>A</strong>tmospheric <strong>C</strong>hemist<strong>R</strong>y <strong>O</strong>f the <strong>S</strong>uburban fore<strong>S</strong>t) project focuses on scientific research to understand the detailed chemistry and physics of urban air mixed with biogenic emissions with the goals to increase detailed understanding of the chemical processes and to use this knowledge to improve the performance of air quality models. Enhanced knowledge and improved models will allow society to develop better strategies to improve air quality and save lives.</p><p>The central component of ACROSS is a comprehensive summertime field study with many instruments for the measurement of primary and secondary constituents. Measurements will be made from research aircraft, a tower located in a forest, tethered balloons and/or drones, and mobile platforms. Observations from the field study will be analyzed in a variety of ways involving statistical approaches and comparisons with different types of numerical models.</p><p>This presentation describes activities in preparation of the ACROSS measurement campaign and provides information for interested parties to become involved.</p>


Author(s):  
P. Misra ◽  
W. Takeuchi

Abstract. This study demonstrates relationship between remote sensing satellite retrieved fien aerosol concentration and web-based search volumes of air quality related keywords. People’s perception of urban air pollution can verify policy effectiveness and gauge acceptability of policies. As a serious health issue in Asian cities, population may express concern or uncertainty for air pollution risk by performing search on the web to seek answers. A ‘social sensing’ approach that monitors such search queries, may assess people’ perception about air pollution as a risk. We hypothesize that trend and volume of searches show impact of air pollution on general population. The objectives of this research are to identify those atmospheric conditions under which relative search volume (RSV) obtained from Google Trends shows correlation with measured fine aerosol concentration, and to compare search volume sensitivity to rise in aerosol concentration in seven Asian megacities. We considered weekly relative search volumes from Google Trends (GT) for a four year period from January, 2015 to December, 2018 representing diverse PM2.5 concentrations. Search volumes for keywords corresponding to perception of air quality (‘air pollution’) and health effects (‘cough’ and ‘asthma’) were considered. To represent PM2.5 we used fine aerosol indicator developed in an earlier research. The results suggest that tendency to search for ‘air pollution’ and ‘cough’ occurs when AirRGB R is in excess and temperature is below the baseline values. Consistent with this, in cities with high baseline concentrations, sensitivity to rise in AirRGB R is also comparatively lower. The result of this study can used as an indirect measure of awareness in the form of perception and sensitivity of population to air quality. Such an analysis could be useful for forecasting health risks specially in cities lacking dedicated services.


2019 ◽  
Author(s):  
Bas Mijling

Abstract. In many cities around the world people are exposed to elevated levels of air pollution. Often local air quality is not well known due to the sparseness of official monitoring networks, or unrealistic assumptions being made in urban air quality models. Low-cost sensor technology, which has become available in recent years, has the potential to provide complementary information. Unfortunately, an integrated interpretation of urban air pollution based on different sources is not straightforward because of the localized nature of air pollution, and the large uncertainties associated with measurements of low-cost sensors. In this study, we present a practical approach to producing high spatio-temporal resolution maps of urban air pollution capable of assimilating air quality data from heterogeneous data streams. It offers a two-step solution: (1) building a versatile air quality model, driven by an open source atmospheric dispersion model and emission proxies from open data sources, and (2) a practical spatial interpolation scheme, capable of assimilating observations with different accuracies. The methodology, called Retina, has been applied and evaluated for nitrogen dioxide (NO2) in Amsterdam, the Netherlands, during the summer of 2016. The assimilation of reference measurements results in hourly maps with a typical accuracy of 39 % within 2 km of an observation location, and 53 % at larger distances. When low-cost measurements of the Urban AirQ campaign are included, the maps reveal more detailed concentration patterns in areas which are undersampled by the official network. During the summer holiday period, NO2 concentrations drop about 10 % due to reduced urban activity. The reduction is less in the historic city center, while strongest reductions are found around the access ways to the tunnel connecting the northern and the southern part of the city, which was closed for maintenance. The changing concentration patterns indicate how traffic flow is redirected to other main roads. Overall, we show that Retina can be applied for an enhanced understanding of reference measurements, and as a framework to integrate low-cost measurements next to reference measurements in order to get better localized information in urban areas.


2020 ◽  
Author(s):  
Elena Spinei ◽  
Jeffrey Geddes ◽  
Taylor Adams ◽  
Moritz Müller ◽  
Manuel Gebetsberger

<p>Increasing urbanization worldwide raise serious concerns about urban air quality and its effects on large human populations. This study presents application of the Differential Optical Absorption Spectroscopy technique to multi scale urban air quality (NO<sub>2</sub>) monitoring. A Pandora spectroscopic instrument (SciGlob Inc) has been deployed on top of a 30 m building in Boston, MA, USA, since September 2019. It performs over the roof sky scans (local to meso scales), into the street canyon "target" (micro-scale), and direct sun measurements. In situ NO<sub>2</sub> measurements are also being conducted on top of the roof (co-located with Pandora) and at the street level near the "target" building. NO<sub>2</sub> spatial and temporal heterogeneity within different scales is discussed.</p>


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