Stochastic Analysis Of Particulate Ano Gaseous Pollutant Concentrations To Support Satellite Observations Of The Athens Aerosol

Author(s):  
K.I. Lambiris ◽  
N.I. Sifakis ◽  
F. Aumonier
1976 ◽  
Vol 15 (5) ◽  
pp. 1222 ◽  
Author(s):  
W. F. Herget ◽  
J. A. Jahnke ◽  
D. E. Burch ◽  
D. A. Gryvnak

2020 ◽  
Vol 6 (49) ◽  
pp. eabd4998 ◽  
Author(s):  
Bo Zheng ◽  
Guannan Geng ◽  
Philippe Ciais ◽  
Steven J. Davis ◽  
Randall V. Martin ◽  
...  

Changes in CO2 emissions during the COVID-19 pandemic have been estimated from indicators on activities like transportation and electricity generation. Here, we instead use satellite observations together with bottom-up information to track the daily dynamics of CO2 emissions during the pandemic. Unlike activity data, our observation-based analysis deploys independent measurement of pollutant concentrations in the atmosphere to correct misrepresentation in the bottom-up data and can provide more detailed insights into spatially explicit changes. Specifically, we use TROPOMI observations of NO2 to deduce 10-day moving averages of NOx and CO2 emissions over China, differentiating emissions by sector and province. Between January and April 2020, China’s CO2 emissions fell by 11.5% compared to the same period in 2019, but emissions have since rebounded to pre-pandemic levels before the coronavirus outbreak at the beginning of January 2020 owing to the fast economic recovery in provinces where industrial activity is concentrated.


2021 ◽  
Vol 9 ◽  
Author(s):  
Iván Y. Hernández-Paniagua ◽  
S. Ivvan Valdez ◽  
Victor Almanza ◽  
Claudia Rivera-Cárdenas ◽  
Michel Grutter ◽  
...  

Meteorology and long-term trends in air pollutant concentrations may obscure the results from short-term policies implemented to improve air quality. This study presents changes in CO, NO2, O3, SO2, PM10, and PM2.5 based on their anomalies during the COVID-19 partial (Phase 2) and total (Phase 3) lockdowns in Mexico City (MCMA). To minimise the impact of the air pollutant long-term trends, pollutant anomalies were calculated using as baseline truncated Fourier series, fitted with data from 2016 to 2019, and then compared with those from the lockdown. Additionally, days with stagnant conditions and heavy rain were excluded to reduce the impact of extreme weather changes. Satellite observations for NO2 and CO were used to contrast the ground-based derived results. During the lockdown Phase 2, only NO2 exhibited significant decreases (p < 0.05) of between 10 and 23% due to reductions in motor vehicle emissions. By contrast, O3 increased (p < 0.05) between 16 and 40% at the same sites where NO2 decreased. During Phase 3, significant decreases (p < 0.05) were observed for NO2 (43%), PM10 (20%), and PM2.5 (32%) in response to the total lockdown. Although O3 concentrations were lower in Phase 3 than during Phase 2, those did not decrease (p < 0.05) from the baseline at any site despite the total lockdown. SO2 decreased only during Phase 3 in a near-road environment. Satellite observations confirmed that NO2 decreased and CO stabilised during the total lockdown. Air pollutant changes during the lockdown could be overestimated between 2 and 10-fold without accounting for the influences of meteorology and long-term trends in pollutant concentrations. Air quality improved significantly during the lockdown driven by reduced NO2 and PM2.5 emissions despite increases in O3, resulting in health benefits for the MCMA population. A health assessment conducted suggested that around 588 deaths related to air pollution exposure were averted during the lockdown. Our results show that to reduce O3 within the MCMA, policies must focus on reducing VOCs emissions from non-mobile sources. The measures implemented during the COVID-19 lockdowns provide valuable information to reduce air pollution through a range of abatement strategies for emissions other than from motor vehicles.


Epidemiology ◽  
2004 ◽  
Vol 15 (4) ◽  
pp. S68-S69 ◽  
Author(s):  
Polina Maciejczyk ◽  
Dritan Xhillari ◽  
John H. Offenberg ◽  
George D. Thurston ◽  
Lung Chi Chen

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