An increasing percentage of US waste methane (CH 4 ) 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 CH 4 emissions from US wastewater treatment, measuring 63 plants with average daily flows ranging from 4.2 × 10 −4 to 8.5 m 3 s −1 (<0.1 to 193 MGD), totaling 2% of the 62.5 billion gallons treated, nationally. We employed Bayesian inference to quantify facilityintegrated emission rates with a mobile laboratory approach (1165 crossplume transects). The median plant-averaged emission rate was 1.1 g CH 4 s −1 (0.1−21.6 g CH 4 s −1 ; 10th/90th percentiles; mean 7.9 g CH 4 s −1 ), and the median emission factor was 3.4 × 10 −2 g CH 4 (g influent 5 day biochemical oxygen demand; BOD 5 ) −1 [0.6−9.9 × 10 −2 g CH 4 (g BOD 5 ) −1 ; 10th/90th percentiles; mean 5.7 × 10 −2 g CH 4 (g BOD 5 ) −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 CO 2 -eq). With increasing urbanization and centralized treatment, efforts to identify and mitigate CH 4 emissions are needed.

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We present localization and quantitative concentration analysis of controlled methane releases using chirped laser dispersion spectroscopy (CLaDS) in conjunction with an unmanned aerial vehicle (UAV) in an open-path sensing configuration. The system was operational with gusts up to 10 m/s, at distances up to 40 meters, and without using jacks to mechanically stabilize of the instrument vehicle.

We present a real-time remote sensing system capable of localizing methane emissions by automatically switching between 16 retroreflectors placed in known locations. The resulting plume reconstructions show good agreement with theoretical distributions.

We present a methane sensing system based on chirped laser dispersion spectroscopy. The system is capable of actively tracking a drone-based retroreflector at up to 40m distance. The system has also shown sensitivities of 2.3 ppm-m.