ARS | Publication request: Estimation of dairy particulate matter emission rates by lidar and inverse modeling

Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: March 1, 2011
Publication Date: July 1, 2011
Citation: Marchant, C.C., Moore, K.D., Wojick, M.D., Martin, R.S., Pfeiffer, R.L., Prueger, J.H., Hatfield, J.L. 2011. Estimation of dairy particulate matter emission rates by lidar and inverse modeling. Transactions of the ASABE. 54(4):1453-1463.

Interpretive Summary: Air quality issues from agricultural operations are becoming more of a concern to the general public. These concerns range from health issues arising from different gases and particulates to safety issues linked with large amounts of dust affecting visibility to general air quality degradation around livestock facilities. One of the problems is there is little data on the emissions of different air quality components from livestock facilities and even less information which is applicable to be able to state the air quality impact from a whole facility. We have begun to address this question through a combination of measurement techniques which integrate a laser-based technology with air quality samplers placed near the ground and then use these data to help evaluate different air quality models to estimate the overall emissions from a facility. The initial study was completed on a dairy operation in the lower San Joaquin Valley of California using measurements we obtained over a month long period in late May and early June. The observations revealed that the dust emissions were larger than expected and also larger than reported from previous research studies. This method produced these higher values because the technique allows for a sampling of the complete facility and not an isolated portion of the facility and also that this period of measurement was at the drier time of the year with more dust being produced in the dry areas of the dairy farm. The results show that we need to expand our research capabilities to measure around whole facilities in order to more accurately assess the impact of agricultural operations on air quality. This information will help guide policymakers and also those scientists who are developing potential control practices for air quality.

Technical Abstract: Particulate matter (PM) emissions from agricultural operations are an important issue for air quality and human health and a topic of interest to government regulators. PM emission rates from a dairy in the San Joaquin Valley of California were investigated during June 2008. The facility had 1,885 total animals - 950 milking cows housed in free-stall pens with open lot exercise areas and 935 dry cows, steers, bulls, and heifers housed in open lots. Point sensors, including filter-based aerodynamic mass samplers and optical particle counters (OPC), were deployed at select points around the facility to measure optical and aerodynamic particulate concentrations. Simultaneously, vertical PM concentration profiles were measured both upwind and downwind of the facility using lidar. The lidar was calibrated to provide mass concentration information using the OPCs and filter measurements. Emission rates were estimated over this period using both an inverse modeling technique coupled with the filter-based measurements and a mass balance technique applied to lidar data. Mean emission rates calculated using inverse modeling (± 95% confidence interval) were 2.8 (± 2.3), 17.4 (± 10.2), and 53.8 (± 22.2) g/d/AU for PM2.5, PM10, and TSP, respectively. Mean emissions rates based on lidar data were 1.3 (± 0.2), 15.1 (± 2.2), and 46.4 (± 7.0) g/d/AU for PM2.5, PM10, and TSP, respectively. The PM10 findings are roughly twice as high as those reported from other dairy studies with different climatic conditions and/or housing types, but of similar magnitude as those from a study with similar conditions, housing, and emission rate calculation technique.