{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,10]],"date-time":"2025-11-10T13:59:53Z","timestamp":1762783193276,"version":"build-2065373602"},"reference-count":50,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2024,11,26]],"date-time":"2024-11-26T00:00:00Z","timestamp":1732579200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council (NSERC) of Canada","doi-asserted-by":"publisher","award":["RGPIN-2020-05223"],"award-info":[{"award-number":["RGPIN-2020-05223"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Wastewater treatment (WWT) contributes 2\u20139% of global greenhouse gas (GHG) emissions. The noticeable uncertainty in emissions estimation is due in large part to the lack of measurement data. Several methods have recently been developed for monitoring fugitive GHG emissions from WWT. However, limited by the short duration of the monitoring, only \u201csnapshot\u201d data can be obtained, necessitating extrapolation of the limited data for estimating annual emissions. Extrapolation introduces substantial errors, as it fails to account for the spatial and temporal variations of fugitive emissions. This research evaluated the feasibility of studying the long-term CH4 emissions from WWT by analyzing high spatial resolution Sentinel-2 data. Satellite images of a WWT plant in Calgary, Canada, taken between 2019 and 2023, were processed to retrieve CH4 column concentration distributions. Digital image processing techniques were developed and used for extracting the time- and space-varying features of CH4 emissions, which revealed daily, monthly, seasonal, and annual variations. Emission hotspots were also identified and corroborated with ground-based measurements. Despite limitations due to atmospheric scattering, cloud cover, and sensor resolution, which affect precise ground-level concentration assessments, the findings reveal the dynamic nature of fugitive GHG emissions from WWT, indicating the need for continuous monitoring. The results also show the potential of utilizing satellite images for cost-effectively evaluating fugitive CH4 emissions.<\/jats:p>","DOI":"10.3390\/rs16234422","type":"journal-article","created":{"date-parts":[[2024,11,26]],"date-time":"2024-11-26T07:40:32Z","timestamp":1732606832000},"page":"4422","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["First Investigation of Long-Term Methane Emissions from Wastewater Treatment Using Satellite Remote Sensing"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3734-9922","authenticated-orcid":false,"given":"Seyed Mostafa","family":"Mehrdad","sequence":"first","affiliation":[{"name":"Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada"}]},{"given":"Bo","family":"Zhang","sequence":"additional","affiliation":[{"name":"Stantec, Atlanta, GA 30303, USA"}]},{"given":"Wenqi","family":"Guo","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Mathematics, Physics and Statistics, University of British Columbia, Okanagan Campus, Kelowna, BC V1V 1V7, Canada"},{"name":"Weathon Software, Kelowna, BC V1X 2Z3, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2281-5150","authenticated-orcid":false,"given":"Shan","family":"Du","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Mathematics, Physics and Statistics, University of British Columbia, Okanagan Campus, Kelowna, BC V1V 1V7, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8251-2928","authenticated-orcid":false,"given":"Ke","family":"Du","sequence":"additional","affiliation":[{"name":"Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada"}]}],"member":"1968","published-online":{"date-parts":[[2024,11,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/j.desal.2008.03.020","article-title":"A review of the effects of emerging contaminants in wastewater and options for their removal","volume":"239","author":"Bolong","year":"2009","journal-title":"Desalination"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.desal.2011.11.056","article-title":"Progress in real-time control applied to biological nitrogen removal from wastewater. A short-review","volume":"286","author":"Zanetti","year":"2012","journal-title":"Desalination"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1016\/j.desal.2010.07.063","article-title":"Membrane bioreactors: Two decades of research and implementation","volume":"273","author":"Santos","year":"2011","journal-title":"Desalination"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1016\/j.biortech.2016.01.098","article-title":"Aerobic granular processes: Current research trends","volume":"210","author":"Zhang","year":"2016","journal-title":"Bioresour. Technol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1016\/j.jenvman.2013.05.007","article-title":"Energy\u2013nutrients\u2013water nexus: Integrated resource recovery in municipal wastewater treatment plants","volume":"127","author":"Mo","year":"2013","journal-title":"J. Environ. Manag."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1159","DOI":"10.2166\/wst.2013.681","article-title":"Reductions in greenhouse gas (GHG) generation and energy consumption in wastewater treatment plants","volume":"67","author":"Yerushalmi","year":"2013","journal-title":"Water Sci. Technol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2679","DOI":"10.1016\/j.watres.2009.02.040","article-title":"Impact of process design on greenhouse gas (GHG) generation by wastewater treatment plants","volume":"43","author":"Shahabadi","year":"2009","journal-title":"Water Res."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/j.watres.2014.06.002","article-title":"Identifying sensitive sources and key control handles for the reduction of greenhouse gas emissions from wastewater treatment","volume":"62","author":"Sweetapple","year":"2014","journal-title":"Water Res."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1016\/S0269-7491(00)00222-0","article-title":"Methane emissions from wastewater management","volume":"114","author":"Massoud","year":"2001","journal-title":"Environ. Pollut."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Zhang, B., Mehrdad, S., Li, S., and Du, K. (2023, January 16\u201319). To Measure or Not to Measure, that is the Question! Optical Remote Sensing of Greenhouse Gas Emissions from Wastewater Treatment. Proceedings of the 2023 Water Environment Federation, Odors and Air Pollutants Conference, Charlotte, NC, USA.","DOI":"10.3390\/rs16234422"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Li, X., Liu, J., and Ni, P. (2021). The impact of the digital economy on CO2 emissions: A theoretical and empirical analysis. Sustainability, 13.","DOI":"10.3390\/su13137267"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"3961","DOI":"10.1016\/j.watres.2008.07.001","article-title":"Nitrite effectively inhibits sulfide and methane production in a laboratory scale sewer reactor","volume":"42","author":"Mohanakrishnan","year":"2008","journal-title":"Water Res."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"3657","DOI":"10.1016\/j.watres.2012.04.024","article-title":"Methane emission during municipal wastewater treatment","volume":"46","author":"Daelman","year":"2012","journal-title":"Water Res."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"5479","DOI":"10.1016\/j.biortech.2010.10.090","article-title":"Methane emissions from a full-scale A\/A\/O wastewater treatment plant","volume":"102","author":"Wang","year":"2011","journal-title":"Bioresour. Technol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1814","DOI":"10.1007\/s11270-013-1814-8","article-title":"Methane emissions from aerated zones in a full-scale nitrifying activated sludge treatment plant","volume":"225","author":"Aboobakar","year":"2014","journal-title":"Water Air Soil Pollut."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2853","DOI":"10.5194\/amt-8-2853-2015","article-title":"Methane emission estimates using chamber and tracer release experiments for a municipal waste water treatment plant","volume":"8","author":"Caldow","year":"2015","journal-title":"Atmos. Meas. Tech."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1016\/j.biortech.2014.08.081","article-title":"Methane and nitrous oxide emissions following anaerobic digestion of sludge in Japanese sewage treatment facilities","volume":"171","author":"Oshita","year":"2014","journal-title":"Bioresour. Technol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"3796352","DOI":"10.1155\/2016\/3796352","article-title":"Greenhouse Gases Emissions from Wastewater Treatment Plants: Minimization, Treatment, and Prevention","volume":"2016","author":"Campos","year":"2016","journal-title":"J. Chem."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"468","DOI":"10.1016\/j.scitotenv.2018.11.373","article-title":"Methane emissions from anaerobic sludge digesters in Mexico: On-site determination vs. IPCC Tier 1 method","volume":"656","author":"Paredes","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"4082","DOI":"10.1021\/acs.est.2c05373","article-title":"Underestimation of Sector-Wide Methane Emissions from United States Wastewater Treatment","volume":"57","author":"Moore","year":"2023","journal-title":"Environ. Sci. Technol."},{"key":"ref_21","unstructured":"Du, K., Mehrdad, S.M., Li, S., and Zhang, B. (2024, January 21\u201324). Development of a Tiered Approach for Cost-Effectively Measuring Real-time Direct Greenhouse Gas Emissions from Wastewater Treatment. Proceedings of the Innovations in Treatment Technology Conference, Virginia Beach, VA, USA."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"7036","DOI":"10.1038\/s41467-024-50334-9","article-title":"Deep learning for detecting and characterizing oil and gas well pads in satellite imagery","volume":"15","author":"Ramachandran","year":"2024","journal-title":"Nat. Commun."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"113708","DOI":"10.1016\/j.rse.2023.113708","article-title":"S2MetNet: A novel dataset and deep learning benchmark for methane point source quantification using Sentinel- 2 satellite imagery","volume":"295","author":"Radman","year":"2023","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2143","DOI":"10.1021\/acs.est.1c04873","article-title":"Satellites Detect Abatable Super-Emissions in One of the World\u2019s Largest Methane Hotspot Regions","volume":"56","author":"Roger","year":"2022","journal-title":"Environ. Sci. Technol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"89","DOI":"10.5194\/amt-16-89-2023","article-title":"Understanding the potential of Sentinel-2 for monitoring methane point emissions","volume":"16","author":"Varon","year":"2023","journal-title":"Atmos. Meas. Tech."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"10517","DOI":"10.1021\/acs.est.1c08575","article-title":"Global Tracking and Quantification of Oil and Gas Methane Emissions from Recurrent Sentinel-2 Imagery","volume":"56","author":"Ehret","year":"2022","journal-title":"Environ. Sci. Technol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2771","DOI":"10.5194\/amt-14-2771-2021","article-title":"High-frequency monitoring of anomalous methane point sources with multispectral Sentinel-2 satellite observations","volume":"14","author":"Varon","year":"2021","journal-title":"Atmos. Meas. Tech."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"3801","DOI":"10.1038\/s41467-024-47754-y","article-title":"Automatic detection of methane emissions in multispectral satellite imagery using a vision transformer","volume":"15","author":"Hulbert","year":"2024","journal-title":"Nat. Commun."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"103097","DOI":"10.1016\/j.scs.2021.103097","article-title":"Prediction of fugitive landfill gas hotspots using a random forest algorithm and Sentinel-2 data","volume":"73","author":"Karimi","year":"2021","journal-title":"Sustain. Cities Soc."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"113716","DOI":"10.1016\/j.rse.2023.113716","article-title":"Daily detection and quantification of methane leaks using Sentinel-3: A tiered satellite observation approach with Sentinel-2 and Sentinel-5p","volume":"296","author":"Pandey","year":"2023","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1007\/s10333-024-00974-w","article-title":"Assessing paddy methane emissions through the identification of rice and winter crop areas using Sentinel-2 imagery in Korea","volume":"22","author":"Jang","year":"2024","journal-title":"Paddy Water Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"e2021GL092556","DOI":"10.1029\/2021GL092556","article-title":"Effects of Using High Resolution Satellite-Based Inundation Time Series to Estimate Methane Fluxes from Forested Wetlands","volume":"48","author":"Hondula","year":"2021","journal-title":"Geophys. Res. Lett."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"114321","DOI":"10.1016\/j.rse.2024.114321","article-title":"Estimating surface NO2 concentrations over Europe using Sentinel-5P TROPOMI observations and Machine Learning","volume":"312","author":"Shetty","year":"2024","journal-title":"Remote Sens. Environ."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"2745","DOI":"10.5194\/acp-22-2745-2022","article-title":"Variability of nitrogen oxide emission fluxes and lifetimes estimated from Sentinel-5P TROPOMI observations","volume":"22","author":"Lange","year":"2022","journal-title":"Atmos. Chem. Phys."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"3682","DOI":"10.1002\/2018GL077259","article-title":"Toward Global Mapping of Methane With TROPOMI: First Results Intersatellite Comparison to GOSAT","volume":"45","author":"Hu","year":"2018","journal-title":"Geophys. Res. Lett."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1038\/s41586-019-1720-3","article-title":"California\u2019s methane super-emitters","volume":"575","author":"Duren","year":"2019","journal-title":"Nature"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2127","DOI":"10.5194\/amt-14-2127-2021","article-title":"The GHGSat-D imaging spectrometer","volume":"14","author":"Jervis","year":"2021","journal-title":"Atmos. Meas. Tech."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"5655","DOI":"10.5194\/amt-12-5655-2019","article-title":"Potential of next-generation imaging spectrometers to detect and quantify methane point sources from space","volume":"12","author":"Cusworth","year":"2019","journal-title":"Atmos. Meas. Tech."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"e2020GL090864","DOI":"10.1029\/2020GL090864","article-title":"Multisatellite Imaging of a Gas Well Blowout Enables Quantification of Total Methane Emissions","volume":"48","author":"Cusworth","year":"2021","journal-title":"Geophys. Res. Lett."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"7741","DOI":"10.1002\/2014JD021551","article-title":"Mapping of North American methane emissions with high spatial resolution by inversion of SCIAMACHY satellite data","volume":"119","author":"Wecht","year":"2014","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"9617","DOI":"10.5194\/acp-22-9617-2022","article-title":"Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane","volume":"22","author":"Jacob","year":"2022","journal-title":"Atmos. Chem. Phys."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1126\/science.abj4351","article-title":"Global assessment of oil and gas methane ultra-emitters","volume":"375","author":"Lauvaux","year":"2022","journal-title":"Science"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.rse.2011.11.026","article-title":"Sentinel-2: ESA\u2019s optical high-resolution mission for GMES operational services","volume":"120","author":"Drusch","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1023\/A:1024048429145","article-title":"The solar spectral irradiance from 200 to 2400 nm as measured by the SOLSPEC spectrometer from the ATLAS and EURECA missions","volume":"214","author":"Thuillier","year":"2003","journal-title":"Sol. Phys."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"3172","DOI":"10.21105\/joss.03172","article-title":"Semi-Automatic Classification Plugin: A Python tool for the download processing of remote sensing images in QGIS","volume":"6","author":"Congedo","year":"2021","journal-title":"J. Open Source Softw."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.jqsrt.2016.03.005","article-title":"HITRAN Application Programming Interface (HAPI): A comprehensive approach to working with spectroscopic data","volume":"177","author":"Kochanov","year":"2016","journal-title":"J. Quant. Spectrosc. Radiat. Transf."},{"key":"ref_47","unstructured":"Tiemann, E., Zhou, S., Kl\u00e4ser, A., Heidler, K., Schneider, R., and Zhu, X. (2024). Machine Learning for Methane Detection and Quantification from Space\u2014A survey. arXiv."},{"key":"ref_48","first-page":"1","article-title":"CH4Net: A deep learning model for monitoring methane super-emitters with Sentinel-2 imagery","volume":"2023","author":"Vaughan","year":"2023","journal-title":"EGUsphere"},{"key":"ref_49","first-page":"29","article-title":"Detection of Methane Point Sources with High-Resolution Satellites","volume":"28","author":"Roger","year":"2023","journal-title":"Environ. Sci. Proc."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"113818","DOI":"10.1016\/j.envres.2022.113818","article-title":"A comprehensive carbon footprint analysis of different wastewater treatment plant configurations","volume":"214","author":"Wu","year":"2022","journal-title":"Environ. Res."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/23\/4422\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T16:39:46Z","timestamp":1760114386000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/23\/4422"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,26]]},"references-count":50,"journal-issue":{"issue":"23","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["rs16234422"],"URL":"https:\/\/doi.org\/10.3390\/rs16234422","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2024,11,26]]}}}