ArticleACS omega2023
Impacts of Proximity to Primary Source Areas on Concentrations of POPs at Global Sampling Stations Estimated from Land Cover Information.
Article in ACS omega, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Twenty-Five Years of Research and Monitoring Using PUF Disk Passive Air Samplers.Environmental science & technology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Given the considerable financial and logistical resources supporting long-term monitoring for air pollutants, and the use of these data for performance evaluation of mitigation measures, it is important to account for contributions from primary versus secondary sources. We demonstrate a simple approach for using open source Global land cover raster data from the National Mapping Organization from the Geospatial Information Authority of Japan to assess local source inputs for air measurements of legacy persistent organic pollutants (POPs)-polychlorinated biphenyls (PCBs) and organochlorine pesticides-reported under the Global atmospheric passive sampling (GAPS) Network at 119 locations for the time period 2005-2014. The land cover composition within a 10 km radius around the GAPS sites was identified to create source impact indicator (SII) vectors to quantify and rank the remoteness of the sites from human infrastructure. Using principal component analysis, three SII vectors were established to rank sites by impact of (i) general infrastructure/remoteness, (ii) urban infrastructure, and (iii) agricultural infrastructure. General infrastructure describes the combined effects of settlements and agricultural infrastructure. We found significant correlations (
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Registered trials
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