PMID- 37810729
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20231010
IS  - 2470-1343 (Electronic)
IS  - 2470-1343 (Linking)
VI  - 8
IP  - 39
DP  - 2023 Oct 3
TI  - Impacts of Proximity to Primary Source Areas on Concentrations of POPs at Global 
      Sampling Stations Estimated from Land Cover Information.
PG  - 36016-36024
LID - 10.1021/acsomega.3c04065 [doi]
AB  - 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 (p < 0.05) between POP 
      concentrations in air and specific SIIs. PCB levels in air had a statistically 
      significant correlation to the SII ranking urban impacts around the sampling 
      sites, while Endosulfan I, Endosulfan II, and Endosulfan sulfate had a 
      statistically significant correlation with SII ranking agricultural impacts. The 
      complete GAPS data set from 2004-2014 (1040 samples at 119 locations) was 
      standardized based on the SII rankings to assess the global temporal trends of 
      legacy POPs. SIIs were incorporated in the multiple regression analysis to 
      determine global halving times. This includes short-term monitoring data from 79 
      locations that were previously excluded. Furthermore, the SII approach allows the 
      integration of global monitoring data from different studies for broader global 
      temporal trend analysis. This ability to link the results of independent and 
      small-scale studies can enhance temporal trend analysis in support of the larger 
      scale initiatives, such as inter alia, the Global Monitoring Plan and 
      Effectiveness Evaluation of the Stockholm Convention in the case of POPs. This 
      simple approach using open source data has a broad potential for application for 
      other classes of air pollutants.
CI  - Crown (c) 2023. Published by American Chemical Society.
FAU - Schuster, Jasmin K
AU  - Schuster JK
AUID- ORCID: 0000-0002-1972-0337
AD  - Air Quality Processes Research Section, Environment and Climate Change Canada, 
      Toronto, Ontario M3H 5T4, Canada.
FAU - Harner, Tom
AU  - Harner T
AUID- ORCID: 0000-0001-9026-3645
AD  - Air Quality Processes Research Section, Environment and Climate Change Canada, 
      Toronto, Ontario M3H 5T4, Canada.
FAU - Rauert, Cassandra
AU  - Rauert C
AUID- ORCID: 0000-0002-2543-9023
AD  - Air Quality Processes Research Section, Environment and Climate Change Canada, 
      Toronto, Ontario M3H 5T4, Canada.
AD  - Queensland Alliance for Environmental Health Sciences (QAEHS), The University of 
      Queensland, Woolloongabba, Queensland 4102, Australia.
LA  - eng
PT  - Journal Article
DEP - 20230921
PL  - United States
TA  - ACS Omega
JT  - ACS omega
JID - 101691658
PMC - PMC10552113
COIS- The authors declare no competing financial interest.
EDAT- 2023/10/09 12:42
MHDA- 2023/10/09 12:43
PMCR- 2023/09/21
CRDT- 2023/10/09 06:07
PHST- 2023/06/08 00:00 [received]
PHST- 2023/09/12 00:00 [accepted]
PHST- 2023/10/09 12:43 [medline]
PHST- 2023/10/09 12:42 [pubmed]
PHST- 2023/10/09 06:07 [entrez]
PHST- 2023/09/21 00:00 [pmc-release]
AID - 10.1021/acsomega.3c04065 [doi]
PST - epublish
SO  - ACS Omega. 2023 Sep 21;8(39):36016-36024. doi: 10.1021/acsomega.3c04065. 
      eCollection 2023 Oct 3.