Particulate-matter emission estimates from agricultural spring-tillage operations using LIDAR and inverse modeling
Journal of Applied Remote Sensing
Particulate-matter (PM) emissions from a typical spring agricultural tillage sequence and a strip–till conservation tillage sequence in California’s San Joaquin Valley were estimated to calculate the emissions control efficiency (ηη) of the strip–till conservation management practice (CMP). Filter-based PM samplers, PM-calibrated optical particle counters (OPCs), and a PM-calibrated light detection and ranging (LIDAR) system were used to monitored upwind and downwind PM concentrations during May and June 2008. Emission rates were estimated through inverse modeling coupled with the filter and OPC measurements and through applying a mass balance to the PM concentrations derived from LIDAR data. Sampling irregularities and errors prevented the estimation of emissions from 42% of the sample periods based on filter samples. OPC and LIDAR datasets were sufficiently complete to estimate emissions and the strip–till CMP ηη, which were ∼90%∼90% for all size fractions in both datasets. Tillage time was also reduced by 84%. Calculated emissions for some operations were within the range of values found in published studies, while other estimates were significantly higher than literature values. The results demonstrate that both PM emissions and tillage time may be reduced by an order of magnitude through the use of a strip–till conservation tillage CMP when compared to spring tillage activities.
Moore, K.D., M.D. Wojcik, R.S. Martin, C.C. Marchant, D.S. Jones, W.J. Bradford, G.E. Bingham, R.L. Pfeiffer, J.H. Prueger, and J.L. Hatfield (2015), Particulate-matter emission estimates from agricultural spring-tillage operations using LIDAR and inverse modeling, J. Applied Remote Sensing, Vol. 9, 096066-1 – 0960966-23.
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