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<Article>
<Journal>
				<PublisherName>University Of Tehran Press</PublisherName>
				<JournalTitle>Pollution</JournalTitle>
				<Issn>2383-451X</Issn>
				<Volume>12</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2026</Year>
					<Month>01</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Satellite-Based Assessment of Air Pollution in Southern Districts of Tamil Nadu Using Sentinel-5P and Google Earth Engine: A Comparative Study</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>313</FirstPage>
			<LastPage>326</LastPage>
			<ELocationID EIdType="pii">105155</ELocationID>
			
<ELocationID EIdType="doi">10.22059/poll.2025.399751.3049</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Gayathri</FirstName>
					<LastName>P S</LastName>
<Affiliation>Department of Physics, S.T. Hindu College, Nagercoil-629002, Kanyakumari, Affiliated to Manonmaniam Sundaranar University, Abishekapatti, Tirunelveli, Tamil Nadu-627012, India</Affiliation>

</Author>
<Author>
					<FirstName>Krishna Sharma</FirstName>
					<LastName>R</LastName>
<Affiliation>Department of Physics, S.T. Hindu College, Nagercoil-629002, Kanyakumari, Affiliated to Manonmaniam Sundaranar University, Abishekapatti, Tirunelveli, Tamil Nadu-627012, India</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2025</Year>
					<Month>07</Month>
					<Day>30</Day>
				</PubDate>
			</History>
		<Abstract>This study investigates the spatial distribution of key air pollutants—NO₂, SO₂, CO, and surface O₃—across three southern districts of Tamil Nadu, India: Tuticorin, Tirunelveli, and Kanniyakumari, for the period April 2024 to March 2025. Pollutant data were derived from the Copernicus Sentinel-5P satellite and analyzed using the Google Earth Engine (GEE) platform to map annual variations and identify pollution patterns. The results showed that Tuticorin experienced the highest pollutant levels due to its dense industrial and port activities, followed by Tirunelveli, where urban growth and traffic contributed to moderate concentrations. Kanniyakumari, characterized by its coastal setting and minimal industrialization, recorded the lowest levels. Satellite-derived data were further compared with ground-based measurements from TNPCB and AQI India for validation. The novelty of this work lies in its use of satellite-based atmospheric observations and cloud computing (GEE) for air quality analysis in southern Tamil Nadu, a region where such remote sensing studies remain limited.</Abstract>
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			<Param Name="value">remote sensing</Param>
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			<Object Type="keyword">
			<Param Name="value">Spatial Analysis</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Satellite data</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Pollutant distribution</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Environmental monitoring</Param>
			</Object>
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<ArchiveCopySource DocType="pdf">https://jpoll.ut.ac.ir/article_105155_a20348d8715b6d922a5297d6ec28a11f.pdf</ArchiveCopySource>
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