High-resolution urban air pollution mapping.


Journal

Science (New York, N.Y.)
ISSN: 1095-9203
Titre abrégé: Science
Pays: United States
ID NLM: 0404511

Informations de publication

Date de publication:
26 Jul 2024
Historique:
medline: 26 7 2024
pubmed: 26 7 2024
entrez: 25 7 2024
Statut: ppublish

Résumé

Variation in urban air pollution arises because of complex spatial, temporal, and chemical processes, which profoundly affect population exposure, human health, and environmental justice. This Review highlights insights from two popular in situ measurement methods-mobile monitoring and dense sensor networks-that have distinct but complementary strengths in characterizing the dynamics and impacts of the multidimensional urban air quality system. Mobile monitoring can measure many pollutants at fine spatial scales, thereby informing about processes and control strategies. Sensor networks excel at providing temporal resolution at many locations. Increasingly sophisticated studies leveraging both methods can vividly identify spatial and temporal patterns that affect exposures and disparities and offer mechanistic insight toward effective interventions. This Review summarizes the strengths and limitations of these methods and discusses their implications for understanding fine-scale processes and impacts.

Identifiants

pubmed: 39052801
doi: 10.1126/science.adq3678
doi:

Substances chimiques

Air Pollutants 0
Particulate Matter 0

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

380-385

Auteurs

Joshua S Apte (JS)

Department of Civil and Environmental Engineering, University of California, Berkeley, Berkeley, CA 94720, USA.
School of Public Health, University of California, Berkeley, Berkeley, CA 94720, USA.

Chirag Manchanda (C)

Department of Civil and Environmental Engineering, University of California, Berkeley, Berkeley, CA 94720, USA.

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Classifications MeSH