Monitoring airborne particulates has been the primary approach to collecting data on spatial and temporal patterns of wind erosion for decades.39 Monitoring in the US is coordinated through meteorological observation networks and aerosol measurement networks. Indicators of airborne particulates used by these networks include: dust event frequencies obtained from visual observations made by the National Weather Service; atmospheric particulate matter (PM) concentrations measured using high volume air samplers, lidar, and light-scattering laser photometers (e.g., Hand et al.40); and aerosol optical depth (AOD) obtained from ground-based sun photometers and satellite observations (e.g., Holben et al.;41 Prospero et al.;42 Ginoux et al.43). Each of these indicators provides different information about airborne particulates. Dust event frequency data by event type (e.g., locally blowing dust, dust storm, dust haze) can be used to understand the timing of wind erosion and dust emission around an observation site and regional dust event patterns and trends. Atmospheric PM concentrations and AOD provide additional information on how much airborne particulates are at a sampling location or through the vertical column of atmosphere over an observation location or area. PM concentrations and AOD directly inform air quality, human health and climate impacts of blowing dust. Spatial patterns and temporal trends of PM and AOD have been used to interpret the very general location of dust sources, and dust emission responses to climate variability, but do not inform which landscapes are eroding and why with enough accuracy to inform land management. Site-specific information about soils and vegetation are needed to identify why particular landscapes are eroding and when they are most susceptible.
Nationally, airborne particulates are monitored by federal, state and county networks, with data accessible online through the US Environmental Protection Agency (EPA) Interactive Map of Air Quality Monitors.44 This tool provides access to concentration data for PM10 and PM2.5 in addition to other aerosols and enables users to identify mapped non-attainment areas and Federal Class 1 Areas. Interagency Monitoring of Protected Visual Environments (IMPROVE) Program data that include PM and haze composition can be accessed through the EPA or dedicated IMPROVE Program data portal.45 The National Wind Erosion Research Network31 is actively incorporating PM10, PM4, PM2.5 and PM1 concentration monitoring at sites, including measurements at two levels (2 m and 4 m above ground level) to enable estimates of vertical dust flux across agroecosystems and support calibration of predictive models.
References
31. National Wind Erosion Research Network Sites. https://winderosionnetwork.org/.
39. Goudie AS, Middleton NJ. Desert Dust in the Global System. Berlin, Heidelberg: Springer; 2006.
40. Hand JL, White WH, Gebhart KA, Hyslop NP, Gill TE, Schichtel BA. Earlier onset of the spring fine dust season in the southwestern United States. Geophys Res Lett. 2016;43(8):4001-4009. doi:10.1002/2016GL068519
41. Holben BN, Eck TF, Slutsker I, et al. AERONET—A federated instrument network and data archive for aerosol characterization. Remote Sens Environ. 1998;66(1):1-16. doi:10.1016/S0034-4257(98)00031-5
42. Prospero JM, Ginoux P, Torres O, Nicholson SE, Gill TE. Environmental characterization of global sources of atmospheric soil dust identified with the Nimbus 7 Total Ozone Mapping Spectrometer (TOMS) absorbing aerosol product. Rev Geophys. 2002;40(1):2-31. doi:10.1029/2000RG000095
43. Ginoux P, Prospero JM, Gill TE, Hsu NC, Zhao M. Global-scale attribution of anthropogenic and natural dust sources and their emission rates based on MODIS Deep Blue aerosol products. Rev Geophys. 2012;50(3). doi:10.1029/2012RG000388
44. US EPA O. Interactive Map of Air Quality Monitors. US EPA. https://www.epa.gov/outdoor-air-quality-data/interactive-map-air-quality-monitors. Published August 17, 2016.
45. IMPROVE – Interagency Monitoring of Protected Visual Environments. http://vista.cira.colostate.edu/Improve/.