Ammonia and methane dairy emission plumes in the San Joaquin Valley of California from individual feedlot to regional scales

Abstract

Agricultural ammonia (NH3) emissions are highly uncertain, with high spatiotemporal variability and a lack of widespread in situ measurements. Regional NH3 emission estimates using mass balance or emission ratio approaches are uncertain due to variable NH3 sources and sinks as well as unknown plume correlations with other dairy source tracers. We characterize the spatial distributions of NH3 and methane (CH4) dairy plumes using in situ surface and airborne measurements in the Tulare dairy feedlot region of the San Joaquin Valley, California, during the NASA Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality 2013 field campaign. Surface NH3 and CH4 mixing ratios exhibit large variability with maxima localized downwind of individual dairy feedlots. The geometric mean NH3:CH4 enhancement ratio derived from surface measurements is 0.15 ± 0.03 ppmv ppmv−1. Individual dairy feedlots with spatially distinct NH3 and CH4 source pathways led to statistically significant correlations between NH3 and CH4 in 68% of the 69 downwind plumes sampled. At longer sampling distances, the NH3:CH4 enhancement ratio decreases 20–30%, suggesting the potential for NH3 deposition as a loss term for plumes within a few kilometers downwind of feedlots. Aircraft boundary layer transect measurements directly above surface mobile measurements in the dairy region show comparable gradients and geometric mean enhancement ratios within measurement uncertainties, even when including NH3 partitioning to submicron particles. Individual NH3 and CH4 plumes sampled at close proximity where losses are minimal are not necessarily correlated due to lack of mixing and distinct source pathways. Our analyses have important implications for constraining NH3 sink and plume variability influences on regional NH3 emission estimates and for improving NH3 emission inventory spatial allocations.

Emissions of volatile organic compounds (VOCs) from concentrated animal feeding operations (CAFOs): chemical compositions and separation of sources

“…But, waste cleaning time/practices in the facility were unknown, owing to no access to the facility. Previous mobile and aircraft measurements have also observed enhancements of NH 3 and CH 4 concentrations downwind of animal pens in cattle feedlots (Miller et al, 2015;Hacker et al, 2016). The time variations of two VOCs, acetic acid and acetone, followed reasonably well with both NH 3 and CO 2 , suggesting that animals and their waste contributed to the enhancements of the two VOCs.…”

Evaluation of ambient ammonia measurements from a research aircraft using a closed-path QC-TILDAS operated with active continuous passivation

“…PFA tubing then brings sample flow from the inertial inlet box to the QC-TILDAS, which is co-located in the same equipment rack inside the aircraft cabin. As shown in previous studies, PFA tubing and fittings are used wherever possible along the sample pathway, and tubing lengths are kept to a minimum and heated wherever possible (Neuman et al, 1999;Schmohl et al, 2001;Mukhtar et al, 2003;Leifer et al, 2017). Components housed within the aircraft inlet strut are heated to 40 • C. The tubing between the inlet strut and the inertial inlet and between the inertial inlet and the QC-TILDAS are not actively heated; however, they are wrapped in flame-resistant polymer felt (DuPont Nomex) for thermal isolation.…”

Introduction of Water‐Vapor Broadening Parameters and Their Temperature‐Dependent Exponents Into the HITRAN Database: Part I—CO2, N2O, CO, CH4, O2, NH3, and H2S

“…Its accurate spectroscopic parameters are needed for a variety of gas‐sensing applications including those for environmental monitoring, industrial process control, and human breath analysis in medical science (e.g., Manne et al, ; Owen & Farooq, ; Schilt et al, ). While each of these applications involved significant concentrations of water vapor in the system, the impact of water vapor on ammonia absorption features is not negligible for high‐sensitivity detections of ammonia to ppb or ppm levels (D. J. Miller et al, ; Sun et al, , ). In fact, recent experimental results from Schilt () had demonstrated that water vapor was a significant cross‐sensitivity source especially in a high‐temperature environment.…”

“…While each of these applications involved significant concentrations of water vapor in the system, the impact of water vapor on ammonia absorption features is not negligible for high-sensitivity detections of ammonia to ppb or ppm levels (D. J. Miller et al, 2015;Sun et al, 2015Sun et al, , 2017. In fact, recent experimental results from Schilt (2010) had demonstrated that water vapor was a significant cross-sensitivity source especially in a high-temperature environment.…”