Lidar based emissions measurement at the whole facility scale: Method and error analysis

Abstract

Particulate emissions from agricultural sources vary from dust created by operations and animal movement to the fine secondary particulates generated from ammonia and other emitted gases. The development of reliable facility emission data using point sampling methods designed to characterize regional, well-mixed aerosols are challenged by changing wind directions, disrupted flow fields caused by structures, varied surface temperatures, and the episodic nature of the sources found at these facilities. We describe a three-wavelength lidar-based method, which, when added to a standard point sampler array, provides unambiguous measurement and characterization of the particulate emissions from agricultural production operations in near real time. Point-sampled data are used to provide the aerosol characterization needed for the particle concentration and size fraction calibration, while the lidar provides 3D mapping of particulate concentrations entering, around, and leaving the facility. Differences between downwind and upwind measurements provide an integrated aerosol concentration profile, which, when multiplied by the wind speed profile, produces the facility source flux. This approach assumes only conservation of mass, eliminating reliance on boundary layer theory. We describe the method, examine measurement error, and demonstrate the approach using data collected over a range of agricultural operations, including a swine grow-finish operation, an almond harvest, and a cotton gin emission study.

Polarization Lidar Detection of Agricultural Aerosol Emissions

“…Agricultural activities are responsible for 5% of all particles less than 2.5 μm in diameter (PM 2.5 ) and 25% of all particles less than 10 μm (PM 10 ) [1]. The main agricultural activities responsible for PM emissions are tilling, harvesting, agricultural fires, and emissions from fertilizer use and livestock [2].…”

“…Lidar systems can provide real-time aerosol measurements with high temporal and spatial resolution. In previous studies, nonpolarized lidar systems have been used to measure PM 10 emissions from land preparation operations [6][7][8][9] to determine vertical PM concentration profiles. Several lidar studies have also been carried out to estimate the PM emissions due to livestock housing.…”

“…Several lidar studies have also been carried out to estimate the PM emissions due to livestock housing. For example, PM concentration and fluxes generated by a swine-feeding facility have been measured using a threewavelength lidar system in combination with mass samplers and optical particle counters [10]. An alternative methodology has been recently developed to estimate the PM emission rates from animal production facilities departing from single-wavelength lidar data [11].…”

Integration of remote lidar and in-situ measured data to estimate particulate flux and emission from tillage operations

“…Typically, monitoring systems for agricultural systems have employed instrumentation designed to evaluate the concentrations of gases or particulates at a specific location around the facility or within the operation. The dynamics of airflow and particulate movement around facilities raise the question of how improved methods of measuring particulate emission and movement might aid in our understanding of emissions from agricultural facilities and in the long-term provide a method of comparing systems or management practices [1]. Light detection and ranging (lidar) technology has been successfully applied to qualitatively characterize particulate emissions from agricultural sources [1][2][3].…”

“…The dynamics of airflow and particulate movement around facilities raise the question of how improved methods of measuring particulate emission and movement might aid in our understanding of emissions from agricultural facilities and in the long-term provide a method of comparing systems or management practices [1]. Light detection and ranging (lidar) technology has been successfully applied to qualitatively characterize particulate emissions from agricultural sources [1][2][3]. The physical properties of an aerosol can be retrieved from lidar data using the measured backscatter coefficients and the known relationship between aerosol physical properties and backscatter [4][5][6].…”