{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T17:24:35Z","timestamp":1787073875375,"version":"build-2736575974"},"reference-count":60,"publisher":"American Chemical Society (ACS)","issue":"32","license":[{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-045"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2023YFC3207404"],"award-info":[{"award-number":["2023YFC3207404"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018806","name":"Department of Science and Technology of Hubei Province","doi-asserted-by":"publisher","award":["2025BCB032"],"award-info":[{"award-number":["2025BCB032"]}],"id":[{"id":"10.13039\/501100018806","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100014219","name":"National Science Fund for Distinguished Young Scholars","doi-asserted-by":"publisher","award":["52425005"],"award-info":[{"award-number":["52425005"]}],"id":[{"id":"10.13039\/501100014219","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52370189"],"award-info":[{"award-number":["52370189"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52470035"],"award-info":[{"award-number":["52470035"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,8,18]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Greenhouse gas (GHG) emissions from wastewater treatment have gained increasing attention in global climate governance. However, conventional emission-factor (EF)-derived inventories lacked the ability to capture nonlinear variations, while existing machine learning (ML) models remained fragmented in scale. Here, we introduce WaterMAP (Wastewater AI Treatment Emission Regression for Multi-scale Accounting and Prediction), a novel ML framework designed for spatiotemporal EF-derived GHG prediction and mitigation evaluation. Using 40,722 inventory-based GHG records from 5155 WWTPs in China during 2009\u20132019 as a case study, the National_Total_Model achieved a test RMSE of 0.19 kg CO2-e\/m3 when predicting the total EF-derived intensity. National_Type_Model showed that scope 1 totaled 7.6 Mt CO2-e, scope 2 accounted for 18.9 Mt CO2-e, and scope 3 contributed 0.5 Mt CO2-e in 2019. We then estimated cumulative GHGs for 2024 to be 36.8 Mt CO2-e, with an average intensity of 0.51 kg CO2-e\/m3. Treated volume, TNinf, sludge yield, latitude, and CODinf were identified as the key predictors influencing EF-derived GHG emissions. We further proposed a GHG spatial heterogeneity index using Provincial_Type_Model, reflecting urban development. Under exploratory sensitivity analysis toward 2060, WaterMAP-guided projections suggested 9.6\u201334.0% potential reduction. Overall, WaterMAP offers a scalable framework for EF-derived GHG emissions screening and prediction, supporting GHG mitigation assessment.<\/jats:p>","DOI":"10.1021\/acs.est.6c03422","type":"journal-article","created":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T14:36:14Z","timestamp":1785854174000},"page":"22627-22640","source":"Crossref","is-referenced-by-count":0,"title":["WaterMAP: A Scalable\nMachine Learning Framework for\nEmission-Factor-Derived Spatiotemporal GHG Prediction and Mitigation\nin Wastewater Treatment Plants"],"prefix":"10.1021","volume":"60","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-0467-7337","authenticated-orcid":true,"given":"Jinqi","family":"Jiang","sequence":"first","affiliation":[{"name":"Huazhong University of Science and Technology (HUST) , , 1037 Luoyu Road , , ,","place":["Wuhan, Hubei, China, 430074"]},{"name":"Huazhong University of Science and Technology , , , ,","place":["Wuhan, Hubei, China, 430074"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhijing","family":"Wu","sequence":"additional","affiliation":[{"name":"Huazhong University of Science and Technology (HUST) , , 1037 Luoyu Road , , ,","place":["Wuhan, Hubei, China, 430074"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-6382-4580","authenticated-orcid":true,"given":"Guosen","family":"Zhang","sequence":"additional","affiliation":[{"name":"Huazhong University of Science and Technology (HUST) , , 1037 Luoyu Road , , ,","place":["Wuhan, Hubei, China, 430074"]},{"name":"Huazhong University of Science and Technology , , , ,","place":["Wuhan, Hubei, China, 430074"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuwei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Huazhong University of Science and Technology (HUST) , , 1037 Luoyu Road , , ,","place":["Wuhan, Hubei, China, 430074"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yichao","family":"Lyu","sequence":"additional","affiliation":[{"name":"Huazhong University of Science and Technology (HUST) , , 1037 Luoyu Road , , ,","place":["Wuhan, Hubei, China, 430074"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shen","family":"Qu","sequence":"additional","affiliation":[{"name":"Beijing Institute of Technology , , ,","place":["Beijing, China, 100081"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huabo","family":"Duan","sequence":"additional","affiliation":[{"name":"Huazhong University of Science and Technology (HUST) , , 1037 Luoyu Road , , ,","place":["Wuhan, Hubei, China, 430074"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongxiao","family":"Guo","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology , , ,","place":["Kowloon, Hong Kong, China, 999077"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiang","family":"Xiang","sequence":"additional","affiliation":[{"name":"Huazhong University of Science and Technology , , , ,","place":["Wuhan, Hubei, China, 430074"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zongping","family":"Wang","sequence":"additional","affiliation":[{"name":"Huazhong University of Science and Technology (HUST) , , 1037 Luoyu Road , , ,","place":["Wuhan, Hubei, China, 430074"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guanghao","family":"Chen","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology , , ,","place":["Kowloon, Hong Kong, China, 999077"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6965-8957","authenticated-orcid":true,"given":"Gang","family":"Guo","sequence":"additional","affiliation":[{"name":"Huazhong University of Science and Technology (HUST) , , 1037 Luoyu Road , , ,","place":["Wuhan, Hubei, China, 430074"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"316","published-online":{"date-parts":[[2026,8,1]]},"reference":[{"key":"2026081810415632900_cit1","doi-asserted-by":"publisher","first-page":"578","DOI":"10.1038\/s44359-025-00082-w","article-title":"Technologies and gaps in deep decarbonization of hard-to-abate\nindustrial sectors","volume":"1","author":"Meng","year":"2025","journal-title":"Nat. Rev. Clean Technol."},{"key":"2026081810415632900_cit2","doi-asserted-by":"publisher","first-page":"1133","DOI":"10.1038\/s44221-025-00485-w","article-title":"Benchmarking greenhouse\ngas emissions from US wastewater treatment for targeted reduction","volume":"3","author":"El Abbadi","year":"2025","journal-title":"Nat. Water"},{"key":"2026081810415632900_cit3","doi-asserted-by":"publisher","first-page":"166","DOI":"10.1038\/s44221-022-00021-0","article-title":"Spatiotemporal\npattern of greenhouse gas emissions in China\u2019s wastewater sector\nand pathways towards carbon neutrality","volume":"1","author":"Du","year":"2023","journal-title":"Nat.\nWater"},{"key":"2026081810415632900_cit4","doi-asserted-by":"publisher","first-page":"927","DOI":"10.1038\/s44221-024-00318-2","article-title":"Defining and achieving net-zero emissions\nin the wastewater\nsector","volume":"2","author":"Song","year":"2024","journal-title":"Nat. Water"},{"key":"2026081810415632900_cit5","doi-asserted-by":"publisher","first-page":"70","DOI":"10.3389\/fenvs.2017.00070","article-title":"Enhancing\nthe Energy Efficiency of Wastewater Treatment Plants through Co-digestion\nand Fuel Cell Systems","volume":"5","author":"Gandiglio","year":"2017","journal-title":"Front. Environ. Sci."},{"key":"2026081810415632900_cit6","doi-asserted-by":"publisher","first-page":"1348","DOI":"10.1038\/s41893-024-01420-9","article-title":"Oversimplification and misestimation\nof nitrous oxide\nemissions from wastewater treatment plants","volume":"7","author":"Song","year":"2024","journal-title":"Nat. Sustain."},{"key":"2026081810415632900_cit7","doi-asserted-by":"publisher","first-page":"116196","DOI":"10.1016\/j.watres.2020.116196","article-title":"Mitigating\nnitrous oxide emissions at a full-scale wastewater treatment plant","volume":"185","author":"Duan","year":"2020","journal-title":"Water Res."},{"key":"2026081810415632900_cit8","doi-asserted-by":"publisher","first-page":"7768","DOI":"10.1021\/es201489n","article-title":"Modeling\nNitrous Oxide Production during Biological Nitrogen Removal via Nitrification\nand Denitrification: Extensions to the General ASM Models","volume":"45","author":"Ni","year":"2011","journal-title":"Environ. Sci. Technol."},{"key":"2026081810415632900_cit9","doi-asserted-by":"publisher","first-page":"100345","DOI":"10.1016\/j.ese.2023.100345","article-title":"Methane and nitrous\noxide emissions from municipal wastewater treatment plants in China:\nA plant-level and technology-specific study","volume":"20","author":"Li","year":"2024","journal-title":"Environ. Sci. Ecotechnology"},{"key":"2026081810415632900_cit10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.scitotenv.2015.06.122","article-title":"Seasonal and diurnal\nvariability of N2O emissions from a full-scale municipal wastewater\ntreatment plant","volume":"536","author":"Daelman","year":"2015","journal-title":"Sci. Total Environ."},{"key":"2026081810415632900_cit11","doi-asserted-by":"publisher","first-page":"4700","DOI":"10.1016\/j.watres.2011.04.040","article-title":"Including\ngreenhouse gas emissions during benchmarking of wastewater treatment\nplant control strategies","volume":"45","author":"Flores-Alsina","year":"2011","journal-title":"Water Res."},{"key":"2026081810415632900_cit12","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1038\/s44284-024-00194-7","article-title":"Smart cities:\nthe data to decisions process","volume":"2","author":"Tsybina","year":"2025","journal-title":"Nat. Cities"},{"key":"2026081810415632900_cit13","doi-asserted-by":"publisher","first-page":"12741","DOI":"10.1021\/acs.est.1c01339","article-title":"Machine Learning:\nNew Ideas and Tools in Environmental Science and Engineering","volume":"55","author":"Zhong","year":"2021","journal-title":"Environ. Sci. Technol."},{"key":"2026081810415632900_cit14","doi-asserted-by":"publisher","first-page":"12989","DOI":"10.1021\/acs.est.4c03160","article-title":"Optimization\nof a Novel Engineered Ecosystem Integrating Carbon, Nitrogen, Phosphorus,\nand Sulfur Biotransformation for Saline Wastewater Treatment Using\nan Interpretable Machine Learning Approach","volume":"58","author":"Jiang","year":"2024","journal-title":"Environ. Sci. Technol."},{"key":"2026081810415632900_cit15","doi-asserted-by":"publisher","first-page":"19860","DOI":"10.1021\/acs.est.3c06482","article-title":"Modeling Indirect Greenhouse\nGas Emissions Sources from Urban Wastewater Treatment Plants: Integrating\nMachine Learning Models to Compensate for Sparse Parameters with Abundant\nObservations","volume":"57","author":"Huang","year":"2023","journal-title":"Environ. Sci. Technol."},{"key":"2026081810415632900_cit16","doi-asserted-by":"publisher","first-page":"246","DOI":"10.1038\/s42256-022-00462-y","article-title":"Quantifying the spatial homogeneity\nof urban road networks via graph neural networks","volume":"4","author":"Xue","year":"2022","journal-title":"Nat. Mach. Intell."},{"key":"2026081810415632900_cit17","doi-asserted-by":"publisher","first-page":"317","DOI":"10.1038\/s41597-022-01439-7","article-title":"Greenhouse gas emissions\nfrom municipal wastewater treatment facilities in China from 2006\nto 2019","volume":"9","author":"Wang","year":"2022","journal-title":"Sci. Data"},{"key":"2026081810415632900_cit18","doi-asserted-by":"publisher","first-page":"4298","DOI":"10.1021\/acs.est.5c07998","article-title":"Bridging Microscopic\nDynamics and Macroscopic Fate: A Molecular Dynamics-Machine Learning\nApproach for Predicting PFAS Solid\u2013Liquid Distribution in Soils\nand Sediments","volume":"60","author":"Zhang","year":"2026","journal-title":"Environ. Sci. Technol."},{"key":"2026081810415632900_cit19","unstructured":"The Statistical Yearbook of China, https:\/\/www.stats.gov.cn\/sj\/ndsj\/ (accessed June 01, 2026)."},{"key":"2026081810415632900_cit20","unstructured":"Report on the State\nof the Ecology and Environment, https:\/\/english.mee.gov.cn\/Resources\/Reports\/ (accessed June 01, 2026)."},{"key":"2026081810415632900_cit21","unstructured":"The Ministry of Housing and Urban-Rural Development of China.\n          , https:\/\/www.mohurd.gov.cn\/ (accessed June 01, 2026)."},{"key":"2026081810415632900_cit22","doi-asserted-by":"publisher","first-page":"1114","DOI":"10.1038\/s44221-025-00490-z","article-title":"Comprehensive assessment\nof the contribution of wastewater treatment to urban greenhouse gas\nand ammonia emissions","volume":"3","author":"Moore","year":"2025","journal-title":"Nat. Water"},{"key":"2026081810415632900_cit23","doi-asserted-by":"publisher","first-page":"647","DOI":"10.1038\/s41467-025-67374-4","article-title":"Uncertainty-aware machine learning\nto predict non-cancer human toxicity for the global chemicals market","volume":"17","author":"von Borries","year":"2026","journal-title":"Nat. Commun."},{"key":"2026081810415632900_cit24","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1038\/s44286-024-00047-z","article-title":"Reducing uncertainties\nin greenhouse gas emissions from chemical production","volume":"1","author":"Cullen","year":"2024","journal-title":"Nat. Chem. Eng."},{"key":"2026081810415632900_cit25","doi-asserted-by":"publisher","first-page":"13462","DOI":"10.1021\/acs.est.6c00574","article-title":"Mapping PFAS\nExceedance Risk in China\u2019s Surface Water: A Machine Learning\nApproach Informed by Source Distribution","volume":"60","author":"Wang","year":"2026","journal-title":"Environ.\nSci. Technol."},{"key":"2026081810415632900_cit26","unstructured":"Hubei Urban Planning and Design Institute.\n          . https:\/\/www.hbsghy.com\/ (accessed June 01, 2026)."},{"key":"2026081810415632900_cit27","doi-asserted-by":"publisher","first-page":"4050","DOI":"10.1021\/acs.est.2c07073","article-title":"Enhancing Biochar-Based Nonradical Persulfate Activation Using Data-Driven\nTechniques","volume":"57","author":"Wang","year":"2023","journal-title":"Environ. Sci. Technol."},{"key":"2026081810415632900_cit28","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1016\/j.inffus.2021.11.011","article-title":"Tabular data: Deep learning is not\nall you need","volume":"81","author":"Shwartz-Ziv","year":"2022","journal-title":"Inf. Fusion"},{"key":"2026081810415632900_cit29","doi-asserted-by":"publisher","first-page":"100341","DOI":"10.1016\/j.ese.2023.100341","article-title":"Mitigating\ngreenhouse\ngas emissions from municipal wastewater treatment in China","volume":"20","author":"Tong","year":"2024","journal-title":"Environ. Sci. Ecotechnology"},{"key":"2026081810415632900_cit30","doi-asserted-by":"publisher","first-page":"119536","DOI":"10.1016\/j.watres.2022.119536","article-title":"China\u2019s\nenhanced urban wastewater treatment increases greenhouse gas emissions\nand regional inequality","volume":"230","author":"Huang","year":"2023","journal-title":"Water Res."},{"key":"2026081810415632900_cit31","doi-asserted-by":"publisher","first-page":"5432","DOI":"10.1038\/s41467-024-49817-6","article-title":"Data-driven approaches linking wastewater\nand source estimation hazardous\nwaste for environmental management","volume":"15","author":"Xie","year":"2024","journal-title":"Nat. Commun."},{"key":"2026081810415632900_cit32","doi-asserted-by":"publisher","first-page":"590","DOI":"10.1038\/s42256-023-00657-x","article-title":"Algorithms\nto estimate\nShapley value feature attributions","volume":"5","author":"Chen","year":"2023","journal-title":"Nat. Mach.\nIntell."},{"key":"2026081810415632900_cit33","doi-asserted-by":"publisher","first-page":"125580","DOI":"10.1016\/j.watres.2026.125580","article-title":"Activating specific\nN2O production pathways to understand\nemission dynamics in wastewater treatment","volume":"296","author":"Strubbe","year":"2026","journal-title":"Water\nRes."},{"key":"2026081810415632900_cit34","doi-asserted-by":"publisher","first-page":"125096","DOI":"10.1016\/j.watres.2025.125096","article-title":"An N2O emissions model\nfeaturing newly integrated abiotic pathways in nitrification","volume":"290","author":"Yu","year":"2026","journal-title":"Water Res."},{"key":"2026081810415632900_cit35","doi-asserted-by":"publisher","DOI":"10.1126\/sciadv.aec0536","article-title":"Measurement-based\nassessment reveals key drivers and mitigation potential\nof methane emissions from China\u2019s wastewater treatment","volume":"12","author":"Sun","year":"2026","journal-title":"Sci. Adv."},{"key":"2026081810415632900_cit36","doi-asserted-by":"publisher","first-page":"117224","DOI":"10.1016\/j.watres.2021.117224","article-title":"Dynamic load shifting for the abatement\nof GHG emissions, power demand, energy use, and costs in metropolitan\nhybrid wastewater treatment systems","volume":"200","author":"Reifsnyder","year":"2021","journal-title":"Water Res."},{"key":"2026081810415632900_cit37","doi-asserted-by":"publisher","first-page":"124641","DOI":"10.1016\/j.watres.2025.124641","article-title":"Enhancing nitrogen\nremoval in low C\/N wastewater via carbon resource recovery from biochar-mediated\nanaerobic digestion of discarded cefradine residues","volume":"288","author":"Shi","year":"2026","journal-title":"Water Res."},{"key":"2026081810415632900_cit38","doi-asserted-by":"publisher","first-page":"124048","DOI":"10.1016\/j.watres.2025.124048","article-title":"Unveiling\nthe synergy between pollutant reduction and\nGHG mitigation to support cross-media management in wastewater treatment","volume":"285","author":"He","year":"2025","journal-title":"Water Res."},{"key":"2026081810415632900_cit39","doi-asserted-by":"publisher","first-page":"1995","DOI":"10.1021\/acsestengg.5c00133","article-title":"Innovative\nFeature Engineering Driven\nby Chemical Category in Machine Learning for Optimizing the Prediction\nof Hydroxyl Radical Reaction Rate Constants","volume":"5","author":"Zhang","year":"2025","journal-title":"ACS ES&T Eng."},{"key":"2026081810415632900_cit40","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1016\/j.eng.2024.01.021","article-title":"Carbon Footprint\nDrivers in China\u2019s\nMunicipal Wastewater Treatment Plants and Mitigation Opportunities\nthrough Electricity and Chemical Efficiency","volume":"50","author":"Qu","year":"2025","journal-title":"Engineering"},{"key":"2026081810415632900_cit41","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1038\/s41893-024-01487-4","article-title":"Recasting China\u2019s\nurban wastewater management standards","volume":"8","author":"Li","year":"2025","journal-title":"Nat.\nSustain."},{"key":"2026081810415632900_cit42","doi-asserted-by":"publisher","first-page":"780","DOI":"10.1038\/s44284-024-00137-2","article-title":"Rooftop photovoltaic\nsolar panels warm up and cool down cities","volume":"1","author":"Khan","year":"2024","journal-title":"Nat.\nCities"},{"key":"2026081810415632900_cit43","doi-asserted-by":"publisher","first-page":"121238","DOI":"10.1016\/j.watres.2024.121238","article-title":"A review of\ngraph and complex network theory in water distribution\nnetworks: Mathematical foundation, application and prospects","volume":"253","author":"Yu","year":"2024","journal-title":"Water Res."},{"key":"2026081810415632900_cit44","doi-asserted-by":"publisher","first-page":"146","DOI":"10.1016\/j.watres.2015.02.033","article-title":"Principles\nfor scaling of distributed direct potable\nwater reuse systems: A modeling study","volume":"75","author":"Guo","year":"2015","journal-title":"Water\nRes."},{"key":"2026081810415632900_cit45","doi-asserted-by":"publisher","first-page":"231","DOI":"10.1016\/j.jclepro.2014.11.005","article-title":"A synthesis\napproach for industrial\ncity water reuse networks considering central and distributed treatment\nsystems","volume":"89","author":"Alnouri","year":"2015","journal-title":"J. Cleaner Prod."},{"key":"2026081810415632900_cit46","doi-asserted-by":"publisher","first-page":"149677","DOI":"10.1016\/j.scitotenv.2021.149677","article-title":"Spatial-temporal\ndistribution and evolutionary characteristics of water environment\nsudden pollution incidents in China from 2006 to 2018","volume":"801","author":"Xu","year":"2021","journal-title":"Sci. Total Environ."},{"key":"2026081810415632900_cit47","doi-asserted-by":"publisher","first-page":"107927","DOI":"10.1016\/j.envint.2023.107927","article-title":"Towards the\ncarbon neutrality of sludge treatment and disposal in China: A nationwide\nanalysis based on life cycle assessment and scenario discovery","volume":"174","author":"Zhou","year":"2023","journal-title":"Environ. Int."},{"key":"2026081810415632900_cit48","doi-asserted-by":"publisher","first-page":"340","DOI":"10.1029\/2018ef001058","article-title":"Spatial and\nTemporal Distribution of Greenhouse Gas Emissions From\nMunicipal Wastewater Treatment Plants in China From 2005 to 2014","volume":"7","author":"Yan","year":"2019","journal-title":"Earth\u2019s Future"},{"key":"2026081810415632900_cit49","doi-asserted-by":"publisher","first-page":"4908","DOI":"10.1109\/JSEN.2020.3030584","article-title":"A Data-Driven\nSoft Sensor to Forecast Energy Consumption in Wastewater Treatment\nPlants: A Case Study","volume":"21","author":"Harrou","year":"2021","journal-title":"IEEE Sens. J."},{"key":"2026081810415632900_cit50","doi-asserted-by":"publisher","first-page":"360","DOI":"10.1021\/acsestengg.2c00306","article-title":"Prediction\nand Evaluation of Indirect Carbon Emission from Electrical\nConsumption in Multiple Full-Scale Wastewater Treatment Plants via\nAutomated Machine Learning-Based Analysis","volume":"3","author":"Xu","year":"2023","journal-title":"ACS\nES&T Eng."},{"key":"2026081810415632900_cit51","doi-asserted-by":"publisher","first-page":"1061","DOI":"10.1016\/j.jenvman.2018.06.092","article-title":"Machine learning\nfor energy cost modelling in wastewater treatment plants","volume":"223","author":"Torregrossa","year":"2018","journal-title":"J. Environ. Manage."},{"key":"2026081810415632900_cit52","doi-asserted-by":"publisher","first-page":"108147","DOI":"10.1016\/j.resconrec.2025.108147","article-title":"Optimizing the chemical\nremoval of phosphorus for wastewater treatment: Insights from interpretable\nmachine learning modeling with binary classification of elasticity\nand productivity","volume":"215","author":"Huang","year":"2025","journal-title":"Resour., Conserv. Recycl."},{"key":"2026081810415632900_cit53","doi-asserted-by":"publisher","first-page":"121890","DOI":"10.1016\/j.watres.2024.121890","article-title":"Deep learning-based\nflocculation sensor for automatic control of flocculant dose in sludge\ndewatering processes during wastewater treatment","volume":"260","author":"Yokoyama","year":"2024","journal-title":"Water Res."},{"key":"2026081810415632900_cit54","doi-asserted-by":"publisher","first-page":"3592","DOI":"10.1021\/acs.est.4c10644","article-title":"Deciphering and\nMitigating of Dynamic Greenhouse Gas Emission in Urban Drainage Systems\nwith Knowledge-Infused Graph Neural Network","volume":"59","author":"Yin","year":"2025","journal-title":"Environ. Sci. Technol."},{"key":"2026081810415632900_cit55","doi-asserted-by":"publisher","first-page":"120667","DOI":"10.1016\/j.watres.2023.120667","article-title":"Machine\nlearning for modeling N2O emissions from wastewater treatment plants:\nAligning model performance, complexity, and interpretability","volume":"245","author":"Khalil","year":"2023","journal-title":"Water Res."},{"key":"2026081810415632900_cit56","doi-asserted-by":"publisher","first-page":"2816","DOI":"10.1021\/acs.est.1c05020","article-title":"An Integrated First Principal and\nDeep Learning Approach for Modeling Nitrous Oxide Emissions from Wastewater\nTreatment Plants","volume":"56","author":"Li","year":"2022","journal-title":"Environ. Sci. Technol."},{"key":"2026081810415632900_cit57","doi-asserted-by":"publisher","first-page":"131640","DOI":"10.1016\/j.biortech.2024.131640","article-title":"Microbial-Guided prediction of methane and sulfide\nproduction in Sewers: Integrating mechanistic models with Machine\nlearning","volume":"415","author":"Yin","year":"2025","journal-title":"Bioresour. Technol."},{"key":"2026081810415632900_cit58","doi-asserted-by":"publisher","first-page":"121502","DOI":"10.1016\/j.jenvman.2024.121502","article-title":"Novel extended hybrid\ntool for real\ntime control and practically support decisions to reduce GHG emissions\nin full scale wastewater treatment plants","volume":"365","author":"Lancioni","year":"2024","journal-title":"J.\nEnviron. Manage."},{"key":"2026081810415632900_cit59","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1038\/s41558-025-02540-6","article-title":"Discrepancies in\nnational inventories reveal a large emissions gap in the wastewater\nsector","volume":"16","author":"Song","year":"2026","journal-title":"Nat. Clim. Change"},{"key":"2026081810415632900_cit60","doi-asserted-by":"publisher","first-page":"1395","DOI":"10.1038\/s41893-024-01423-6","article-title":"Pathways to advanced resource recovery\nfrom sewage","volume":"7","author":"Zheng","year":"2024","journal-title":"Nat. Sustain."}],"container-title":["Environmental Science &amp;\nTechnology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/pubs.acs.org\/doi\/pdf\/10.1021\/acs.est.6c03422","content-type":"application\/pdf","content-version":"vor","intended-application":"unspecified"},{"URL":"https:\/\/pubs.acs.org\/esthag\/article-pdf\/60\/32\/22627\/66354075\/acs.est.6c03422.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/pubs.acs.org\/esthag\/article-pdf\/60\/32\/22627\/66354075\/acs.est.6c03422.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T16:26:34Z","timestamp":1787070394000},"score":1,"resource":{"primary":{"URL":"https:\/\/pubs.acs.org\/esthag\/article\/60\/32\/22627\/5238294\/WaterMAP-A-Scalable-Machine-Learning-Framework-for"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,1]]},"references-count":60,"journal-issue":{"issue":"32","published-online":{"date-parts":[[2026,8,1]]},"published-print":{"date-parts":[[2026,8,18]]}},"URL":"https:\/\/doi.org\/10.1021\/acs.est.6c03422","relation":{},"ISSN":["0013-936X","1520-5851"],"issn-type":[{"value":"0013-936X","type":"print"},{"value":"1520-5851","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,1]]}}}