Use of Satellite Imagery for Characterizing the Temporal Dynamics of Fugitive Methane Emissions from Biosolids Treatment Processes

Energy consumption and greenhouse gas (GHG) emissions are the two important factors to consider when water utilities plan for sustainable capital upgrade and operational modifications of wastewater treatment plants (WWTPs). Researchers have reported the use of several methods, such as flux chambers, drone flux methods, optical gas imagers, etc. for monitoring the fugitive GHG emissions, mainly methane (CH4) and nitrous oxide (N2O), from WWTPs. However, limited by the short duration of most monitoring technologies, only 'snapshot' data can be obtained, necessitating extrapolation of the limited data for estimating the annual emissions. Extrapolation introduces substantial errors as it fails to account for the temporal variations of fugitive GHG emissions. This multi-year project, starting in June 2021, has performed a screening and evaluation of a variety of technologies, consisting of sampling- and non-sampling-based, point and long spatial-range, mobile and stationary methods. The technologies that are suitable for monitoring GHG from WWTPs have been selected to develop a tiered, cross-validating approach to cost-effectively characterize the temporal dynamics of both plant-wide and process-specific GHG emissions. This presentation will start with a brief introduction of how the team has combined satellite imagery, ground based open-path and closed-path optical sensing, optical gas imaging, flux chamber, dispersion modeling, and low-cost sensor network, for measuring fugitive GHG emissions from WWTPs, followed by a detailed case study of how a satellite imagery-based algorithm was developed for capturing the complex, temporally and spatially heterogeneous CH4 emissions associated with the biosolids treatment process at wastewater treatment plants. Satellite remote sensing has been widely used in finding and quantifying natural gas leaks in oil & gas facilities and methane emissions from landfills. However, to date, the use of satellite imagery for analyzing methane emissions from wastewater treatment has been extremely rare, if not none, for which the likely reason is that the low pixel resolution of earlier satellite images is not able to capture the relatively smaller plumes from wastewater treatment plants. Recent advances in satellite technology have made significant progress in methane monitoring that high-resolution tracking capability has become available. This allows for the development of image processing algorithms to capture the methane plumes from facilities of smaller footprints such as the WWTPs. This study has developed an algorithm for characterizing the long-term CH4 emissions from the biosolids handling process using the high spatial resolution Sentinel-2 data. Sentinel-2 satellite imaging, despite of its fewer spectral bands than hyperspectral satellites, is of a superior spatial resolution of 20 m x 20 m and a more frequent revisit intervals of 3 days in the study areas. This feature is especially beneficial for tracking time-varying fugitive emissions for sources with relatively lower intensity plumes such as the biosolids treatment process at WWTPs. Three representative WWTPs, with the following three different biosolids handling processes, have been evaluated in this study: Plant #1, conventional anaerobic digestion; Plant #2, intensified anaerobic digestion with thermal hydrolysis process; Plant #3, biosolids dewatering only with no anaerobic digestion. The short-wavelength infrared (SWIR) bands 11 (1560--1660 nm) and 12 (2090--2290 nm) of Sentinel-2 were used to retrieve methane column concentrations by analyzing reflectance differences between the spectral bands and across multiple satellite passes. Satellite images taken between 2019 and 2023 were processed to retrieve the CH4 column concentration distributions. Digital image processing techniques were developed and used for extracting the time- and space- varying features of CH4 emissions, revealing the daily, monthly, seasonal, and annual emission variations. Figure 1 summarizes the data processing procedure. Emission hotspots were identified and corroborated with ground-based measurement using an infrared optical gas imager. The findings reveal the 'ever-changing' dynamic nature of fugitive CH4 emissions from the biosolids handling units, as shown in Figure 2 and Figure 3, indicating the importance of performing continuous measurements for estimating the annual CH4 emissions. Emissions from the three biosolids processing facilities are also quantitatively evaluated for a comparison. This study demonstrates the feasibility of using satellite imagery to capture methane plumes from the biosolids processing area inside a WWTP, demonstrating the value of using satellite images for cost-effectively localizing emission sources and estimating plumes based on the column concentrations. On the other hand, the data also suggests that satellite imagery by itself is not a self-sufficient method. Hence, while satellite imagery serves to cost-effectively provide a 'big picture' view of the long-term emission dynamics as well as to localize emission hotspots, a full quantification of fugitive CH4 emissions requires incorporation of additional data such as meteorological information and ground-based measurements.