Using infrared geostationary remote sensing to determine particulate matter ground-level composition and concentration

Author Identifier

David Blake

https://orcid.org/0000-0003-3747-2960

Document Type

Journal Article

Publication Title

Air Quality, Atmosphere & Health

Publisher

Springer

School

School of Science / Centre for Ecosystem Management

RAS ID

36348

Funders

The Australian Postgraduate Award

National Computational Infrastructure

Pawsey Supercomputing Centre

Australian Government

Comments

Sowden, M., & Blake, D. (2021). Using infrared geostationary remote sensing to determine particulate matter ground-level composition and concentration. Air Quality, Atmosphere & Health. Advance online publication. https://doi.org/10.1007/s11869-021-01061-3

Abstract

Speciated ground-level aerosol concentrations are required to understand and mitigate health impacts from dust storms, wildfires, and other aerosol emissions. Globally, surface monitoring is limited due to cost and infrastructure demands. While remote sensing can help estimate respirable (i.e. ground level) concentrations, current observations are restricted by inadequate spatiotemporal resolution, uncertainty in aerosol type, particle size, and vertical profile. One key issue with current remote sensing datasets is that they are derived from reflectances observed by polar-orbiting imagers, which means that aerosol is only derived during the daytime and only once or twice per day. Newer quantification methods using geostationary infrared (IR) data have focussed on detecting the presence, or absence, of an event. The determination of aerosol composition or particle size using IR exclusively has received little attention. This manuscript summarizes four scientific papers, published as part of a larger study, and identifies requirements for (a) using infrared radiance observations to obtain continual (i.e. day and night) concentration estimates; (b) increasing temporal resolution by using geostationary satellites; (c) utilizing all infrared channels to maximize spectral differences due to compositional changes; and (d) applying a high-pass filter (brightness temperature differences) to identify compositional variability. Additionally, (e) a preliminary calibration methodology was tested against three severe air quality case study incidents, namely, a dust storm, smoke from prescribed burns, and an ozone smog incident, near Sydney in eastern Australia which highlighted the ability of the method to determine atmospheric stability, clouds, and particle size. Geostationary remote sensing provides near-continuous data at a temporal resolution comparable to monitoring equipment. The spatial resolution (~ 4 km2 at NADIR) is adequate for large sources but coarse for localized sources. The spectral sensitivity of aerosol is limited and appears to be dominated by humidity changes rather than concentration or compositional changes. Geostationary remote sensing can be used to determine the timing, duration, and spatial extent of an air quality event. Brightness temperature differences can assist in qualifying composition with an order of magnitude estimate of concentration.

DOI

10.1007/s11869-021-01061-3

Access Rights

free_to_read

Share

 
COinS