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Spatial pattern recognition of arsenic in topsoil using high-density regional data
- Source :
- Geochemistry: Exploration, Environment, Analysis. 18:319-330
- Publication Year :
- 2018
- Publisher :
- Geological Society of London, 2018.
-
Abstract
- Digital image processing analysis was carried out on As in topsoils of the Campania Region (Italy) to recognise any unknown spatial patterns. The highest As concentration is related to topsoils developed on the NW–SE-trending carbonate massifs overlain by pyroclastic rocks where the highest spatial variability and gradient magnitude of As concentration and the highest fault density were also observed. High As concentrations were also found in topsoils over volcanic rocks which played a control on its distribution pattern. The low As values are associated with topsoils along large fluvial valleys where the activity of rivers disturbed the As pattern by transporting larger grain-sized stream sediments with low As concentrations.
- Subjects :
- Fluvial
Pyroclastic rock
Soil science
010501 environmental sciences
010502 geochemistry & geophysics
01 natural sciences
chemistry.chemical_compound
Geochemistry and Petrology
Campania
0105 earth and related environmental sciences
General Environmental Science
geography
Topsoil
geography.geographical_feature_category
Bedrock geology
General Chemistry
Volcanic rock
chemistry
Fault density
Spatial ecology
General Earth and Planetary Sciences
Common spatial pattern
Carbonate
Spatial variability
Digital image processing
Geology
Terra rossa soils
Subjects
Details
- ISSN :
- 20414943 and 14677873
- Volume :
- 18
- Database :
- OpenAIRE
- Journal :
- Geochemistry: Exploration, Environment, Analysis
- Accession number :
- edsair.doi.dedup.....9223986a18bcdfc5dff9b1b062fa442e
- Full Text :
- https://doi.org/10.1144/geochem2017-060