Global Distribution of Column Satellite Aerosol Optical Depth to Surface PM2.5 Relationships

Abstract

Using a combined Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) mid-visible aerosol optical depth (AOD) product at 0.1 × 0.1-degree spatial resolution and collocated surface PM2.5 (particulate matter with aerodynamic diameter smaller than 2.5 μm) monitors, we provide a global five-year (2015–2019) assessment of the spatial and seasonal AOD–PM2.5 relationships of slope, intercepts, and correlation coefficients. Only data from ground monitors accessible through an open air-quality portal that are available to the worldwide community for air quality research and decision making are used in this study. These statistics that are reported 1 × 1-degree resolution are important since satellite AOD is often used in conjunction with spatially limited surface PM2.5 monitors to estimate global distributions of surface particulate matter concentrations. Results indicate that more than 3000 ground monitors are now available for PM2.5 studies. While there is a large spread in correlation coefficients between AOD and PM2.5, globally, averaged over all seasons, the correlation coefficient is 0.55 with a unit AOD producing 54 μgm−3 of PM2.5 (Slope) with an intercept of 8 μgm−3. While the number of surface PM2.5 measurements has increased by a factor of 10 over the last decade, a concerted effort is still needed to continue to increase these monitors in areas that have no surface monitors, especially in large population centers that will further leverage the strengths of satellite data.

Impact of lockdown on particulate matter concentrations in Colombia during the COVID-19 pandemic

“…The present research suggests the need for a more detailed study in the interpretation of PM 2.5 estimation and AOD values. The variations in AOD do not show a strictly linear relationship with the values measured by the Terra/MODIS satellite, as shown in some recent studies ( Christopher and Gupta, 2020 ; Wang et al, 2020c ) most likely due to the different measurement scales between what was recorded in the PM 2.5 surface station and the estimates given by the Terra/MODIS satellite, however, a more detailed study can reveal the factors to be considered. Additionally, it is necessary to study the variations in ozone (O3) during this phase of closure by COVID-19 in Colombia.…”

Surface and satellite observations of air pollution in India during COVID-19 lockdown: Implication to air quality

“…The AOD is always measured at a specific wavelength and represents columnar loading of atmospheric aerosols from the surface to top-of-the-atmosphere. There have been many studies ( Gupta et al, 2006 ; Liu, Paciorek, & Koutrakis, 2009 ; van Donkelaar, Martin, Li, & Burnett, 2019 ; Sathe et al, 2019 ; Yang et al, 2019; Christopher & Gupta, 2020 ) over the years to demonstrate the relationship between AOD and surface mass concentration of PM 2.5 . In this study, we have not used AOD to derive PM 2.5 but used it as a surrogate to assess the relative change in particle pollution in the atmosphere due to lockdown.…”

Mapping Carbon Monoxide Pollution of Residential Areas in a Polish City

“…When analyzing the scientific works [45][46][47][48][49][50][51][52][53][54][55][56][57][58][59][60] as well as legal provisions [14], it can be stated that there is currently incomplete information regarding the air quality when it comes to carbon monoxide, which results from a few reasons:…”

“…This level was over 30 mg/m 3 /year; • mathematical modeling of transport and the changes of substances in the air do not account for all air pollutants that were indicated in the European Union directive [14]. Advanced research methods are applied for the assessment of other air pollutants [50][51][52][53] and often the level of carbon monoxide derived from motor vehicle traffic is often overlooked, though a model based on the maximum concentration of CO for the given terrain accounting for dispersion in the vertical and horizontal direction was developed in a publication [55]. The Hadipour team also accounted for the distance of residential areas from the urban transportation network and based the modeling of carbon monoxide pollution on road traffic data.…”