Tracing geochemical pollutants in stream water and soil from mining activity in an alpine catchment

Li, J; Li, Z; Brandis, KJ; Bu, J; Sun, Z; Yu, Q; Ramp, D

Tracing geochemical pollutants in stream water and soil from mining activity in an alpine catchment

Li, J

Li, Z Brandis, KJ Bu, J Sun, Z Yu, Q

Ramp, D

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Publication Type:: Journal Article
Citation:: Chemosphere, 2020, 242
Issue Date:: 2020-03-01

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Field	Value	Language
dc.contributor.author	Li, J https://orcid.org/0000-0001-9757-9765	en_US
dc.contributor.author	Li, Z	en_US
dc.contributor.author	Brandis, KJ	en_US
dc.contributor.author	Bu, J	en_US
dc.contributor.author	Sun, Z	en_US
dc.contributor.author	Yu, Q https://orcid.org/0000-0001-6950-1821	en_US
dc.contributor.author	Ramp, D https://orcid.org/0000-0003-3202-9898	en_US
dc.date.available	2019-10-20	en_US
dc.date.issued	2020-03-01	en_US
dc.identifier.citation	Chemosphere, 2020, 242	en_US
dc.identifier.issn	0045-6535	en_US
dc.identifier.uri	http://hdl.handle.net/10453/136722
dc.description.abstract	© 2019 Elsevier Ltd This research developed a method of tracing major water chemical parameters (WCP) and soil heavy metals (HM) to identify the processes of mining pollution in topographically complex landscapes. Ninety-nine spatially distributed water samples were collected to characterise the hydrochemical characteristics of an alpine river in north-west China. Sixty river WCP and fifty-six soil HM samples from areas near mining sites were then used to analyse the mining pollution process. Geographical and mining activity characteristics were derived from topographic and mine site information. The occurrence of sulphates (SO42−) and nitrates (NO3−) in river water were highly correlated (up to 0.70), providing strong evidence of pollution from nearby mining activities. Levels of arsenic and cadmium were high in first and fifth order streams, where mining activities were most concentrated. The modelling results showed that geographical patterns and mining activity account for predicting HM distribution, and WCP can be reasonable predictors to trace soil mining pollution. This research can help improve the accuracy of predicting the mining pollution process.	en_US
dc.relation.ispartof	Chemosphere	en_US
dc.relation.isbasedon	10.1016/j.chemosphere.2019.125167	en_US
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.subject.classification	Meteorology & Atmospheric Sciences	en_US
dc.subject.classification	Environmental Sciences	en_US
dc.subject.mesh	Altitude	en_US
dc.subject.mesh	Arsenic	en_US
dc.subject.mesh	Cadmium	en_US
dc.subject.mesh	China	en_US
dc.subject.mesh	Environmental Monitoring	en_US
dc.subject.mesh	Mining	en_US
dc.subject.mesh	Nitrates	en_US
dc.subject.mesh	Rivers	en_US
dc.subject.mesh	Soil	en_US
dc.subject.mesh	Soil Pollutants	en_US
dc.subject.mesh	Sulfates	en_US
dc.subject.mesh	Water Pollutants, Chemical	en_US
dc.title	Tracing geochemical pollutants in stream water and soil from mining activity in an alpine catchment	en_US
dc.type	Journal Article
utslib.citation.volume	242	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
utslib.copyright.status	open_access	*
utslib.copyright.embargo	2022-03-02T00:00:00+1100
pubs.publication-status	Accepted	en_US
pubs.volume	242	en_US

Abstract:

© 2019 Elsevier Ltd This research developed a method of tracing major water chemical parameters (WCP) and soil heavy metals (HM) to identify the processes of mining pollution in topographically complex landscapes. Ninety-nine spatially distributed water samples were collected to characterise the hydrochemical characteristics of an alpine river in north-west China. Sixty river WCP and fifty-six soil HM samples from areas near mining sites were then used to analyse the mining pollution process. Geographical and mining activity characteristics were derived from topographic and mine site information. The occurrence of sulphates (SO42−) and nitrates (NO3−) in river water were highly correlated (up to 0.70), providing strong evidence of pollution from nearby mining activities. Levels of arsenic and cadmium were high in first and fifth order streams, where mining activities were most concentrated. The modelling results showed that geographical patterns and mining activity account for predicting HM distribution, and WCP can be reasonable predictors to trace soil mining pollution. This research can help improve the accuracy of predicting the mining pollution process.

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http://hdl.handle.net/10453/136722