Impacts of Proximity to Primary Source Areas on Concentrations of POPs at Global Sampling Stations Estimated from Land Cover Information

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.