Differences in magnitude and spatial distribution of urban forest pollution deposition rates, air pollution emissions, and ambient neighborhood air quality in New York City

2014 ◽  
Vol 128 ◽  
pp. 14-22 ◽  
Author(s):  
Kristen L. King ◽  
Sarah Johnson ◽  
Iyad Kheirbek ◽  
Jacqueline W.T. Lu ◽  
Thomas Matte
2021 ◽  
Vol 193 ◽  
pp. 110555
Author(s):  
Frederica Perera ◽  
Alique Berberian ◽  
David Cooley ◽  
Elizabeth Shenaut ◽  
Hollie Olmstead ◽  
...  

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 290
Author(s):  
Akvilė Feiferytė Skirienė ◽  
Žaneta Stasiškienė

The rapid spread of the coronavirus (COVID-19) pandemic affected the economy, trade, transport, health care, social services, and other sectors. To control the rapid dispersion of the virus, most countries imposed national lockdowns and social distancing policies. This led to reduced industrial, commercial, and human activities, followed by lower air pollution emissions, which caused air quality improvement. Air pollution monitoring data from the European Environment Agency (EEA) datasets were used to investigate how lockdown policies affected air quality changes in the period before and during the COVID-19 lockdown, comparing to the same periods in 2018 and 2019, along with an assessment of the Index of Production variation impact to air pollution changes during the pandemic in 2020. Analysis results show that industrial and mobility activities were lower in the period of the lockdown along with the reduced selected pollutant NO2, PM2.5, PM10 emissions by approximately 20–40% in 2020.


JAMA ◽  
1962 ◽  
Vol 182 (2) ◽  
pp. 161 ◽  
Author(s):  
Leonard Greenburg

2008 ◽  
Vol 47 (8) ◽  
pp. 2105-2114 ◽  
Author(s):  
Xiangde Xu ◽  
Lian Xie ◽  
Xinghong Cheng ◽  
Jianming Xu ◽  
Xiuji Zhou ◽  
...  

Abstract A major challenge for air quality forecasters is to reduce the uncertainty of air pollution emission inventory. Error in the emission data is a primary source of error in air quality forecasts, much like the effect of error in the initial conditions on the accuracy of weather forecasting. Data assimilation has been widely used to improve weather forecasting by correcting the initial conditions with weather observations. In a similar way, observed concentrations of air pollutants can be used to correct the errors in the emission data. In this study, a new method is developed for estimating air pollution emissions based on a Newtonian relaxation and nudging technique. Case studies for the period of 1–25 August 2006 in 47 cities in China indicate that the nudging technique resulted in improved estimations of sulfur dioxide (SO2) and nitrogen dioxide (NO2) emissions in the majority of these cities. Predictions of SO2 and NO2 concentrations in January, April, August, and October using the emission estimations derived from the nudging technique showed remarkable improvements over those based on the original emission data.


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