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Which persistent organic pollutants can we map in soil using a large spacing systematic soil monitoring design? A case study in Northern France
- Source :
- Science of the Total Environment, Science of the Total Environment, Elsevier, 2011, 409 (19), pp.3719-3731. ⟨10.1016/j.scitotenv.2011.05.048⟩
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Abstract
- Sci Total Environ 824WW Times Cited:5 Cited References Count:62; Persistent organic pollutants (POPs) impact upon human and animal health and the wider environment. It is important to determine where POPs are found and the spatial pattern of POP variation. The concentrations of 90 molecules which are members of four families of POPs and two families of herbicides were measured within a region of Northern France as part of the French National Soil Monitoring Network (RMQS: Réseau de Mesures de la Qualité des Sols). We also gather information on five covariates (elevation, soil organic carbon content, road density, land cover and population density) which might influence POP concentrations. The study region contains 105 RMQS observation sites arranged on a regular square grid with spacing of 16 km. The observations include hot-spots at sites of POP application, smaller concentrations where POPs have been dispersed and observations less than the limit of quantification (LOQ) where the soil has not been impacted by POPs. Fifty nine of the molecules were detected at less than 50 sites and hence the data were unsuitable for spatial analyses. We represent the variation of the remaining 31 molecules by various linear mixed models which can include fixed effects (i.e. linear relationships between the molecule concentrations and covariates) and spatially correlated random effects. The best model for each molecule is selected by the Akaike Information Criterion. For nine of the molecules, spatial correlation is evident and hence they can potentially be mapped. For four of these molecules, the spatial correlation cannot be wholly explained by fixed effects. It appears that these molecules have been transported away from their application sites and are now dispersed across the study region with the largest concentrations found in a heavily populated depression. More complicated statistical models and sampling designs are required to explain the distribution of the less dispersed molecules.
- Subjects :
- lindane
Environmental Engineering
polluant organique persistant
géostatistique
[SDV]Life Sciences [q-bio]
PEDOLOGIE
Soil science
Land cover
010501 environmental sciences
01 natural sciences
Generalized linear mixed model
DDT
IPPMU
Soil
Environmental Chemistry
Soil Pollutants
geostatistics
POPs
Waste Management and Disposal
RMQS
0105 earth and related environmental sciences
Pollutant
Ecology
Sampling (statistics)
04 agricultural and veterinary sciences
Soil carbon
15. Life on land
Random effects model
polychlorinated-biphenyls
Pollution
13. Climate action
040103 agronomy & agriculture
réseau de mesures
Linear Models
0401 agriculture, forestry, and fisheries
Environmental science
Common spatial pattern
France
Akaike information criterion
DDD
Environmental Monitoring
Subjects
Details
- ISSN :
- 00489697 and 18791026
- Database :
- OpenAIRE
- Journal :
- Science of the Total Environment, Science of the Total Environment, Elsevier, 2011, 409 (19), pp.3719-3731. ⟨10.1016/j.scitotenv.2011.05.048⟩
- Accession number :
- edsair.doi.dedup.....2f30c4259bce38398b70284ba9b620bb
- Full Text :
- https://doi.org/10.1016/j.scitotenv.2011.05.048