{"id":"https://openalex.org/W4402376203","doi":"https://doi.org/10.3390/rs16173320","title":"Estimating Ground-Level NO2 Concentrations Using Machine Learning Exclusively with Remote Sensing and ERA5 Data: The Mexico City Case Study","display_name":"Estimating Ground-Level NO2 Concentrations Using Machine Learning Exclusively with Remote Sensing and ERA5 Data: The Mexico City Case Study","publication_year":2024,"publication_date":"2024-09-07","ids":{"openalex":"https://openalex.org/W4402376203","doi":"https://doi.org/10.3390/rs16173320"},"language":"en","primary_location":{"id":"doi:10.3390/rs16173320","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16173320","pdf_url":null,"source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/rs16173320","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065395591","display_name":"Jesus Rodrigo Cedeno Jimenez","orcid":"https://orcid.org/0000-0003-3736-808X"},"institutions":[{"id":"https://openalex.org/I93860229","display_name":"Politecnico di Milano","ror":"https://ror.org/01nffqt88","country_code":"IT","type":"education","lineage":["https://openalex.org/I93860229"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Jesus Rodrigo Cedeno Jimenez","raw_affiliation_strings":["Department of Civil and Environmental Engineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Civil and Environmental Engineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy","institution_ids":["https://openalex.org/I93860229"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075778487","display_name":"Maria Antonia Brovelli","orcid":"https://orcid.org/0000-0003-3161-5561"},"institutions":[{"id":"https://openalex.org/I93860229","display_name":"Politecnico di Milano","ror":"https://ror.org/01nffqt88","country_code":"IT","type":"education","lineage":["https://openalex.org/I93860229"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Maria Antonia Brovelli","raw_affiliation_strings":["Department of Civil and Environmental Engineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Civil and Environmental Engineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy","institution_ids":["https://openalex.org/I93860229"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5075778487"],"corresponding_institution_ids":["https://openalex.org/I93860229"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":0.8235,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.69521052,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"16","issue":"17","first_page":"3320","last_page":"3320"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10190","display_name":"Air Quality and Health Impacts","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/2307","display_name":"Health, Toxicology and Mutagenesis"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11588","display_name":"Atmospheric and Environmental Gas Dynamics","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5738537907600403},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.5013906955718994},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.21887311339378357}],"concepts":[{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5738537907600403},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.5013906955718994},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.21887311339378357}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/rs16173320","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16173320","pdf_url":null,"source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:62f90725179245df9de2165ab9982d5d","is_oa":true,"landing_page_url":"https://doaj.org/article/62f90725179245df9de2165ab9982d5d","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 16, Iss 17, p 3320 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/rs16173320","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16173320","pdf_url":null,"source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2047118236","https://openalex.org/W2082207547","https://openalex.org/W2963609560","https://openalex.org/W2970310584","https://openalex.org/W3025949386","https://openalex.org/W3111978681","https://openalex.org/W3195262235","https://openalex.org/W4200120856","https://openalex.org/W4223655068","https://openalex.org/W4238530616","https://openalex.org/W4311777063","https://openalex.org/W4323314692","https://openalex.org/W4392360090"],"related_works":["https://openalex.org/W2121524756","https://openalex.org/W782553550","https://openalex.org/W1987967678","https://openalex.org/W2633218168","https://openalex.org/W4235897794","https://openalex.org/W2059707233","https://openalex.org/W2095126257","https://openalex.org/W2085738998","https://openalex.org/W2031511989","https://openalex.org/W1606936601"],"abstract_inverted_index":{"This":[0,138],"study":[1,165],"explores":[2],"the":[3,26,30,49,52,61,101,110,114,125,141,178],"estimation":[4],"of":[5,16,57,136,143,184],"ground-level":[6,111],"NO2":[7,27,58,79,112,185],"concentrations":[8,59],"in":[9,155],"Mexico":[10],"City":[11],"using":[12,113],"an":[13],"integrated":[14],"approach":[15],"machine":[17,42],"learning":[18],"(ML)":[19],"and":[20,54,70,157,173,181],"remote":[21],"sensing":[22],"data.":[23],"We":[24],"used":[25],"measurements":[28],"from":[29],"Sentinel-5P":[31],"satellite,":[32],"along":[33],"with":[34,128,147,160],"ERA5":[35],"meteorological":[36,65],"data,":[37],"to":[38,99,104,176],"evaluate":[39],"a":[40,129],"pre-trained":[41],"learing":[43],"model.":[44],"Our":[45],"findings":[46],"indicate":[47],"that":[48,120],"model":[50,123],"captures":[51],"spatial":[53],"temporal":[55],"variability":[56],"across":[60],"urban":[62],"landscape.":[63],"Key":[64],"parameters,":[66],"such":[67,91],"as":[68,75,92],"temperature":[69],"wind":[71],"speed,":[72],"were":[73],"identified":[74],"significant":[76],"factors":[77],"influencing":[78],"levels.":[80],"The":[81,117,164],"model\u2019s":[82,102],"adaptability":[83],"was":[84],"further":[85],"tested":[86],"by":[87],"incorporating":[88],"additional":[89],"variables,":[90],"atmospheric":[93],"boundary":[94],"layer":[95],"height.":[96],"In":[97],"order":[98],"compare":[100],"performance":[103,127],"alternative":[105],"ML":[106,148],"models,":[107],"we":[108],"estimated":[109],"state-of-the-art":[115],"TimeGPT.":[116],"results":[118],"demonstrate":[119],"our":[121],"baseline":[122],"has":[124],"best":[126],"mean":[130,133],"normalised":[131],"root":[132],"square":[134],"error":[135],"84.47%.":[137],"research":[139],"underscores":[140],"potential":[142],"combining":[144],"satellite":[145],"observations":[146],"for":[149,169],"scalable":[150],"air":[151,170],"quality":[152,171],"monitoring,":[153],"particularly":[154],"low-":[156],"middle-income":[158],"countries":[159],"limited":[161],"ground-based":[162],"infrastructure.":[163],"provides":[166],"critical":[167],"insights":[168],"management":[172],"policy-making,":[174],"aiming":[175],"mitigate":[177],"adverse":[179],"health":[180],"environmental":[182],"impacts":[183],"pollution.":[186]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2024-09-10T00:00:00"}
