Application of elastic lidar to PM10 emissions from agricultural nonpoint sources

PM10 emissions from nonpoint sources need to be quantified in order to effectively meet air quality standards. In California's Central Valley, agricultural operations are highly complex but significant sources of PM10 that are difficult to quantify using point sampling arrays. A remote sensing technique, light detection and ranging (lidar), using a small field portable, fast-scanning lidar shows great potential for measuring PM10 emissions from agricultural nonpoint sources. The qualitative capabilities of the lidar instrument are demonstrated for land preparation operations at a wheat field. The range (>5 km), spatial resolution (2.5 m) and fast response times (s) of the lidar allow the following: (i) plume dynamics to be described in detail and eventually to be modeled as a function of source fluctuations and environmental conditions, (ii) measurements of average wind speed and direction over 50-100 m scales, (iii) quantitative determination of the fraction of dust missed by point sampling arrays, and (iv) currently provide unparalleled information on non point source emission variability, both temporally and spatially. The lidar data indicate the line source nature of plumes from tractor operations and suggest that fast lidar 2D vertical scans downwind of nonpoint sources will provide the best PM10 emission factor measurements. Widespread use of lidar for direct quantitative emission factor measurement depends on careful determination of particulate matter backscatter-mass calibration relationships.