Mathematical models to predict soil heavy metal toxicity in the 2012 Olympic site
Radiar, A.R.B. and Purchase, Diane ORCID: https://orcid.org/0000-0001-8071-4385
(2012)
Mathematical models to predict soil heavy metal toxicity in the 2012 Olympic site.
International Journal of Environmental Science and Technology, 9
(2)
.
pp. 219-226.
ISSN 1735-1472
[Article]
Abstract
Heavy metal concentrations in samples collected
from the London 2012 Olympic Village were determined
using a three-step sequential extraction and a rapid extraction method. Metal toxicity was measured by employing the Microtox solid phase analysis. Both extraction methods
produced comparable results (p = 0.996), but the rapid
method produced higher readings. A number of heavy metals
were detected using the two extraction methods, including
aluminum, arsenic, cadmium, chromium, copper, iron, nickel, lead and zinc; beryllium, molybdenum, niobium and titanium were also found in low concentration ranging between 0.16 and 27.10 mg/kg in the total acid digestion. The total metal levels in all the soil samples were within the UK Soil Guideline Value (SGV) except for lead which ranged
between 62.9 and 776.2 mg/kg. The 30 min EC50 of different soil fractions was 2–5.8 g/L. In the absence of any of heavy metals in the SGV, the Dutch Guideline values were
referred. Mathematical models for a number of metals were
generated based on the changes in EC50 values between each
(F1, F2 and F3) soil fractions and the initial toxicity in the non-fractionated samples. The resulting models produced
good R2 values ([96%) for predicting the change in toxicity
of lead, cadmium, zinc and copper by measuring their changes in concentrations. These models could substantially
reduce the time requires to determine the toxicity in the
samples; they would be a useful tool in the clean up process
where monitoring of metal toxicity is required.
Item Type: | Article |
---|---|
Keywords (uncontrolled): | Heavy metals; Microtox; Rapid extraction; Toxicity prediction |
Research Areas: | A. > School of Science and Technology > Natural Sciences |
ISI Impact: | 0 |
Item ID: | 9262 |
Useful Links: | |
Depositing User: | Miss Lucy Caple |
Date Deposited: | 02 Aug 2012 08:49 |
Last Modified: | 11 Oct 2019 13:20 |
URI: | https://eprints.mdx.ac.uk/id/eprint/9262 |
Actions (login required)
![]() |
View Item |
Statistics
Additional statistics are available via IRStats2.