Source apportionment of methane and nitrous oxide in California's San Joaquin Valley at CalNex 2010 via positive matrix factorization

Abstract

Abstract. Sources of methane (CH4) and nitrous oxide (N2O) were investigated using measurements from a site in southeast Bakersfield as part of the CalNex (California at the Nexus of Air Quality and Climate Change) experiment from mid-May to the end of June 2010. Typical daily minimum mixing ratios of CH4 and N2O were higher than daily minima that were simultaneously observed at a mid-oceanic background station (NOAA, Mauna Loa) by approximately 70 ppb and 0.5 ppb, respectively. Substantial enhancements of CH4 and N2O (hourly averages > 500 and > 7 ppb, respectively) were routinely observed, suggesting the presence of large regional sources. Collocated measurements of carbon monoxide (CO) and a range of volatile organic compounds (VOCs) (e.g., straight-chain and branched alkanes, cycloalkanes, chlorinated alkanes, aromatics, alcohols, isoprene, terpenes and ketones) were used with a positive matrix factorization (PMF) source apportionment method to estimate the contribution of regional sources to observed enhancements of CH4 and N2O. The PMF technique provided a "top-down" deconstruction of ambient gas-phase observations into broad source categories, yielding a seven-factor solution. We identified these emission source factors as follows: evaporative and fugitive; motor vehicles; livestock and dairy; agricultural and soil management; daytime light and temperature driven; non-vehicular urban; and nighttime terpene biogenics and anthropogenics. The dairy and livestock factor accounted for the majority of the CH4 (70–90 %) enhancements during the duration of experiments. The dairy and livestock factor was also a principal contributor to the daily enhancements of N2O (60–70 %). Agriculture and soil management accounted for ~ 20–25 % of N2O enhancements over a 24 h cycle, which is not surprising given that organic and synthetic fertilizers are known to be a major source of N2O. The N2O attribution to the agriculture and soil management factor had a high uncertainty in the conducted bootstrapping analysis. This is most likely due to an asynchronous pattern of soil-mediated N2O emissions from fertilizer usage and collocated biogenic emissions from crops from the surrounding agricultural operations that is difficult to apportion statistically when using PMF. The evaporative/fugitive source profile, which resembled a mix of petroleum operation and non-tailpipe evaporative gasoline sources, did not include a PMF resolved-CH4 contribution that was significant (< 2 %) compared to the uncertainty in the livestock-associated CH4 emissions. The uncertainty of the CH4 estimates in this source factor, derived from the bootstrapping analysis, is consistent with the ~ 3 % contribution of fugitive oil and gas emissions to the statewide CH4 inventory. The vehicle emission source factor broadly matched VOC profiles of on-road exhaust sources. This source factor had no statistically significant detected contribution to the N2O signals (confidence interval of 3 % of livestock N2O enhancements) and negligible CH4 (confidence interval of 4 % of livestock CH4 enhancements) in the presence of a dominant dairy and livestock factor. The CalNex PMF study provides a measurement-based assessment of the state CH4 and N2O inventories for the southern San Joaquin Valley (SJV). The state inventory attributes ~ 18 % of total N2O emissions to the transportation sector. Our PMF analysis directly contradicts the state inventory and demonstrates there were no discernible N2O emissions from the transportation sector in the southern SJV region.

Source characterization of volatile organic compounds in the Colorado Northern Front Range Metropolitan Area during spring and summer 2015

“…Source apportionment techniques are statistical analysis approaches used to separate ambient mixing ratios of multiple species into factors that covary simultaneously, thus representing direct sources of species, chemical processes affecting those species, or transport processes [e.g., Guha et al ., ; Lanz et al ., ; Lee et al ., ; Paatero , ; Paatero and Tapper , ; Song et al ., ; Ulbrich et al ., ; Watson et al ., ]. Positive matrix factorization (PMF) is an algorithm for solving a source‐receptor model that assumes that species in a measured data set adhere to a mass‐balance for a number of source profiles with varying contributions to each species over the duration of the data set [ Hopke , ; Paatero , ; Paatero and Tapper , ; Ulbrich et al ., ].…”

Satellite-derived methane hotspot emission estimates using a fast data-driven method

“…17), with the largest values in the southern part of the Central Valley around Bakersfield, an important oil-and gas-producing area (e.g. Jeong et al, 2014;Guha et al, 2015) and an area with significant methane emissions from dairy and livestock (e.g" Wecht et al, 2014b;Guha et al, 2015), extending up to the city of Fresno or even further towards Modesto/San Francisco. This Figure 15.…”

“…Whereas in EDGAR the highest values are around San Francisco and around Los Angeles, the satellite-derived atmospheric methane is highest in the area in between, in the Central Valley, particularly in the area around Bakersfield. Methane emissions in the Bakersfield region are supposed to be dominated by dairy and livestock operations (Guha et al, 2015, and references given therein).…”

Methane emissions from dairies in the Los Angeles Basin

“…Thus, there is an acknowledged need for more accurate atmospheric measurements to verify the bottom-up estimates (Nisbet and Weiss, 2010). This is especially true in urban regions, such as the Los Angeles Basin, where many different CH 4 sources (from farmlands, landfills, and energy sectors) are confined to a relatively small area of ∼ 87 000 km 2 (Wunch et al, 2009;Hsu et al, 2010;Wennberg et al, 2012;Peischl et al, 2013;Guha et al, 2015;Wong et al, 2015). Therefore, improved flux estimations at local scales are needed to resolve discrepancies between bottom-up and top-down approaches and improve apportionment in CH 4 sources.…”