RESUMEN
An increasing percentage of US waste methane (CH4) emissions come from wastewater treatment (10% in 1990 to 14% in 2019), although there are limited measurements across the sector, leading to large uncertainties in current inventories. We conducted the largest study of CH4 emissions from US wastewater treatment, measuring 63 plants with average daily flows ranging from 4.2 × 10-4 to 8.5 m3 s-1 (<0.1 to 193 MGD), totaling 2% of the 62.5 billion gallons treated, nationally. We employed Bayesian inference to quantify facility-integrated emission rates with a mobile laboratory approach (1165 cross-plume transects). The median plant-averaged emission rate was 1.1 g CH4 s-1 (0.1-21.6 g CH4 s-1; 10th/90th percentiles; mean 7.9 g CH4 s-1), and the median emission factor was 3.4 × 10-2 g CH4 (g influent 5 day biochemical oxygen demand; BOD5)-1 [0.6-9.9 × 10-2 g CH4 (g BOD5)-1; 10th/90th percentiles; mean 5.7 × 10-2 g CH4 (g BOD5)-1]. Using a Monte Carlo-based scaling of measured emission factors, emissions from US centrally treated domestic wastewater are 1.9 (95% CI: 1.5-2.4) times greater than the current US EPA inventory (bias of 5.4 MMT CO2-eq). With increasing urbanization and centralized treatment, efforts to identify and mitigate CH4 emissions are needed.
Asunto(s)
Metano , Purificación del Agua , Estados Unidos , Teorema de Bayes , Aguas Residuales , Óxido Nitroso/análisisRESUMEN
A large-scale study of methane emissions from well pads was conducted in the Marcellus shale (Pennsylvania), the largest producing natural gas shale play in the United States, to better identify the prevalence and characteristics of superemitters. Roughly 2100 measurements were taken from 673 unique unconventional well pads corresponding to â¼18% of the total population of active sites and â¼32% of the total statewide unconventional natural gas production. A log-normal distribution with a geometric mean of 2.0 kg h-1 and arithmetic mean of 5.5 kg h-1 was observed, which agrees with other independent observations in this region. The geometric standard deviation (4.4 kg h-1) compared well to other studies in the region, but the top 10% of emitters observed in this study contributed 77% of the total emissions, indicating an extremely skewed distribution. The integrated proportional loss of this representative sample was equal to 0.53% with a 95% confidence interval of 0.45-0.64% of the total production of the sites, which is greater than the U.S. Environmental Protection Agency inventory estimate (0.29%), but in the lower range of other mobile observations (0.09-3.3%). These results emphasize the need for a sufficiently large sample size when characterizing emissions distributions that contain superemitters.