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Arsenic in residential soil and household dust in
Cornwall, south west England: potential human
exposure and the influence of historical mining†
Cite this: Environ. Sci.: Processes
Impacts, 2017, 19, 517
Daniel R. S. Middleton,abc Michael J. Watts,*b Darren J. Beriro,b Elliott M. Hamilton,b
Giovanni S. Leonardi,c Tony Fletcher,c Rebecca M. Closec and David A. Polyaa
Exposure to arsenic (As) via residential soil and dust is a global concern, in regions affected by mining or with
elevated concentrations present in underlying geology. Cornwall in south west England is one such area.
Residential soil (n ¼ 127) and household dust (n ¼ 99) samples were collected from across Cornwall as
part of a wider study assessing exposure to environmental As. Samples were analysed for total As (soil
and dust samples) and human ingestion bioaccessible As (soil samples from properties with homegrown produce). Arsenic concentrations ranged from 12 to 992 mg kg
1
in soil and 3 to 1079 mg kg
1
in
dust and were significantly higher in areas affected by metalliferous mineralisation. Sixty-nine percent of
soils exceeded the 37 mg kg
1
Category 4 Screening Level (C4SL), a generic assessment criteria for As in
residential soils in England, which assumes 100% bioavailability following ingestion. The proportion of
exceedance was reduced to 13% when the bioavailability parameter in the CLEA model was changed to
generate household specific bioaccessibility adjusted assessment criteria (ACBIO). These criteria were
derived using bioaccessibility data for a sub-set of individual household vegetable patch soils (n ¼ 68).
Received 21st December 2016
Accepted 23rd February 2017
Proximity to former As mining locations was found to be a significant predictor of soil As concentration.
DOI: 10.1039/c6em00690f
This study highlights the value of bioaccessibility measurements and their potential for adjusting generic
rsc.li/process-impacts
assessment criteria.
Environmental impact
Arsenic is an environmentally ubiquitous element occurring both naturally and as a result of anthropogenic activities. It is an established carcinogen, categorised as “carcinogenic to humans” (Group 1) by the International Agency for Research on Cancer, as well as being an established cause of numerous other
non-communicable diseases. Cornwall, South West England is an area of notable residential arsenic contamination resulting from the natural geochemical
environment and extensive historical mining operations. This paper assesses the potential for human exposure to arsenic in residential soil and dust on a scale
not previously attempted (127 households). Existing assessment criteria are employed as well as a modied approach incorporating measured bioaccessibility by
reducing the parameter in the contaminated land exposure assessment model from 100% to that determined in vitro. Soil concentrations are also modelled in
relation to historical mining site proximity. This paper addresses important considerations for human exposure assessment and reiterates a potentially
important human exposure pathway in the study location using updated methodologies.
1. Introduction
Chronic exposure to environmental inorganic arsenic (As) is
a recognised risk-factor of numerous cancerous and noncancerous human health effects.1,2 Globally, the most
School of Earth, Atmospheric and Environmental Sciences, Williamson Research
Centre for Molecular Environmental Science, University of Manchester, Manchester,
M13 9PL, UK
a
Inorganic Geochemistry, Centre for Environmental Geochemistry, British Geological
Survey, Nottingham, NG12 5GG, UK. E-mail: mwatts@bgs.ac.uk
b
Environmental Change Department, Centre for Radiation, Chemicals and
Environmental Hazards (CRCE), Public Health England, Chilton, Didcot,
Oxfordshire, OX11 0RQ, UK
c
† Electronic supplementary
10.1039/c6em00690f
information
(ESI)
This journal is © The Royal Society of Chemistry 2017
available.
See
DOI:
signicant non-occupational exposure pathway is the ingestion
of contaminated groundwater, notable examples include Bangladesh3 and West Bengal.4 Other sources include contaminated food, soil and dust.5 The latter two media form the focus
of this paper.
Arsenic exposure via soil and dust can occur as a result of
ingestion, inhalation and dermal absorption.6 Specic pathways include: inhalation of soil dust; direct soil ingestion or
dermal contact; plant uptake and subsequent ingestion; ingestion of soil adhered to vegetables and direct indoor dust
ingestion or dermal contact.6 Depending on the scenario, and
the behavioural patterns of a given ‘receptor’, the relative
importance of these pathways varies. For example, children <6
years old are more likely to be exposed to soil/dust due to the
frequency of hand-to-mouth behaviour and thus accidental
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ingestion.7 Gardeners and home-grown vegetable consumers
are also likely to come into contact with soil more frequently.6
Category 4 Screening Levels (C4SL)8 are, health-based,
generic assessment criteria for chemicals in soil for England.
They were developed by contaminated land: applications in real
environments on behalf of the UK Department for Environment, Food and Rural Affairs to support the implementation of
UK Government Statutory Guidance for England in Part 2a of
the Environmental Protection Act 1990. Two C4SLs for residential land use were developed for total As. They are 37 and
40 mg kg 1 for residential properties with and without homegrown produce, respectively. These C4SLs represent the
concentration of a substance in soil that would result in an
average daily exposure equal to the low level of toxicological
concern8 given the generic model parameters, e.g. exposure rate
for soil and dust ingestion (mg per day). For As, the oral low
level of toxicological concern is 0.3 mg per kg of bodyweight
(BW) per day, which aligns with the WHO drinking water
guideline value9 of 10 As mg per L. The residential C4SLs were
derived using the Contaminated Land Exposure Assessment
(CLEA) model under generic exposure parameters, one of which
is that As uptake from soil is equal to intake i.e. the chemical
form once released from soil is 100% bioavailable in humans.
The CLEA model permits the user to adjust the relative
bioavailable fraction from the generic setting of 1.0 to a site
specic value (i.e. bioaccessibility measured in vitro).
Normal Background Concentrations (NBCs) of contaminants
(including As) in soils provide non-health based soil concentrations reecting the observed variation in concentration
attributable to underlying geology and diffuse pollution for
a given geochemical domain.10 Like C4SLs, NBCs were produced
to guide the implementation of Part 2a of the Environmental
Protection Act 1990. NBCs are dened statistically as the upper
95% condence limit of the 95th percentile of the measured soil
concentrations. The underlying geology has been classied into
three domains by BGS. Derivations are made for two pre-dened
domains where soils exhibit signicantly elevated contaminant
concentrations, “ironstone” and “mineralised”, and the
remainder of the country termed “principal”.10 The English
NBCs for As are 32, 290 and 220 mg kg 1 for principal, mineralised and ironstone domains, respectively.10 Fig. 1 shows the
distribution of the different NBC domains for As across
England. As can be seen, much of Cornwall is classied as
a mineralised domain.
Under normal circumstances, soil parent material is the
dominant determinant of As and other elemental concentrations.11 Anthropogenic activities including mining and mineral
processing can lead to further enrichment of As in soils and
household dusts.12 Being a constituent of many sulphide
minerals, notably arsenopyrite (FeAsS), As contamination can
result from the mining of numerous associated metalliferous
ores.13 Global examples of mining related As contamination
include: gold (Au) mining in many parts of Africa (e.g. artisanal
mining in Ghana14,15), South America (e.g. Nicaragua16) and
Oceania (e.g. Australia17,18); copper (Cu) mining in South
America (e.g. Chile19) and Europe (e.g. France20 and Portugal21)
and tin (Sn), Cu and As mining in south west England, UK.12 In
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Mapped domains used for the derivation of normal background
concentrations (NBCs) of As in English soils. Soils from the Cornwall
study area are categorised in either the principal or mineralised
domain. Compiled using ESRI ArcMap 10.1. Contains British Geological
Survey materials © NERC 2016. Contains Ordnance Survey data ©
Crown Copyright and database rights 2016.
Fig. 1
some of these places there is evidence of human exposure such
as elevated biomarker As concentrations (urine,14,18,20 hair22 and
toe/ngernails16,23) and epidemiological evidence of human
health risk.17 At least 74 countries worldwide are reported24 to be
affected by mining (excluding coal mining) related As contamination, making human exposure to mining-related As
contamination an issue of global importance.
Cornwall, in south west England, is an area of elevated
environmental As. Although concentrations in this highly
mineralised region would be expected to be naturally elevated,
a history of extensive mining and mineral processing,
predominantly of Sn, Cu and As, has resulted in further, widespread anthropogenic contamination.25 It has been estimated13
that an area of 722 km2 (7.9% of the region) is contaminated
with As to some extent (>110 As mg per kg was applied as a cutoff in this particular study) in south west England. Contamination may arise from mine tailings of which As concentrations
vary depending on ore grade, processing efficiency and the
economic cut-off point at which the ore was worth processing
(Mitchell and Barr, 1995). Measured As concentrations in tailings have been reported at up to 20% As.26 Cornwall has many
such tailing heaps and the inability of all but the hardiest of
plant species to inhabit them leaves them susceptible to wind
erosion. One report27 describes a 100 m plume of dust when
a former As mining site, Devon Great Consols, was used as a car
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Environmental Science: Processes & Impacts
racing circuit, a potential source of airborne exposure for local
residents. Given Cornwall's former (mid-19th century) status as
the world's leading As exporter, the region is highly appropriate
for investigating the transport and fate of As in the environment
and the implications for human exposure and public health.
Studies conducted in south west England have reported
elevated As concentrations in residential soils (i.e. >100 mg
kg 1),7,28,29 home/locally-grown vegetables (i.e. relative to control
areas),29,30 household dust (i.e. >100 mg kg 1),7,31 private
drinking water supplies (i.e. >10 As mg per L)32 and human
biomarkers (e.g. relative to control volunteers or correlated with
environmental concentrations) such as urine,33–36 toenails23,37
and hair.38 Exposure of infants (0–6 year olds) in the area has
been specically investigated, with modelled As intake estimates as high as 2.43 and 3.53 mg per kg BW per day for soil and
dust, respectively.7
Many of the studies discussed have reported elevated As
concentrations in media (e.g. soil and dust) collected at former
mining areas relative to control locations.23,30,35,38 The relationship between environmental As concentrations (e.g. in soil and
dust) and proximity to former mines has not been investigated
before on a large (e.g. county-wide) scale. One study39 investigated ambient air particulate As concentrations in relation to
proximity to, and surrounding density of former mining sites
and found no signicant correlation.
The present study was part of a wider investigation of human
exposure to As in Cornwall which included biomonitoring36,37
and environmental sampling, comprising of water,32 soil and
dust – forming the largest non-occupational focus on environmental As exposure in the UK to-date. This paper aimed to
assess potential human exposure to As via residential soil and
dust including the potential role that historical arsenic mining
has played in its distribution in soils and dusts present in
Cornwall. This aim was addressed with the following objectives:
(i) Measure total As concentrations in residential soils (with
and without home-grown produce) and household dust, in
a sample of Cornwall residents.
(ii) Measure the bioaccessible As concentration in soils used
for home-grown produce.
(iii) Derive health-based household bioaccessibility adjusted
assessment criteria (ACBIO) for the study households with
home grown produce.
(iv) Investigate the relationship between proximity to mining
sites and residential soil As concentrations.
2.
Materials and methods
2.1. Ethical approval and household selection
Ethical approval for the overall study was granted by the
University of Manchester Research Ethics Committee (ref.
13068) and the NHS Health Research Authority National
Research Ethics Committee (ref. 13/EE/0234). Sampling units
consisted of households selected for having a private water
supply as per their participation in a wider study of As exposure
in south west England.36 All householders provided written
informed consent.
This journal is © The Royal Society of Chemistry 2017
2.2. Sample collection
The soil collection protocol was based on the British Geological
Survey's Geochemical Baselines Survey of the Environment
methodology.40 Composite (5 sub samples from different points
within the plot) topsoil (15 cm) samples were collected from
vegetable patches (‘vegetable patch soils’). Where no vegetable
patch was present, other uncovered patches of land (‘garden
soils’) were used. All samples were stored in Kra sample bags.
Householders were asked to provide information on any
modications made to their residential soils such as the presence of any imported soil or application of compost or manure.
Composite indoor dust samples were collected by emptying the
contents of the household vacuum cleaner. Information on
whether or not there were pets at the property was obtained.
2.3. Reagents and standards
Deionised water with resistivity of 18.2 MU (Millipore, UK) was
used throughout. Nitric (HNO3), hydrochloric (HCl), hydrouoric (HF) and perchloric (HClO4) acids and hydrogen
peroxide (H2O2) were of Romil-SpA™ super purity grade (Romil,
UK). Arsenic calibration solutions for dust analysis were from
a 1000 mg L 1 PrimAg® grade solution (Romil, UK). Arsenic QC
standards (25 mg L 1) were prepared from a multi-element
solution with As at 20 mg L 1 (Ultra Scientic, USA). Tellurium (Te) and germanium (Ge) ICP-MS internal standards were
prepared from a PlasmaCAL 10 000 mg L 1 solution (SCP
Science, Canada) and a Fluka Analytical 1000 mg L 1 solution
(Sigma-Aldrich, USA), respectively. Reagents used during the
bioaccessibility protocol were identical to those reported
elsewhere.41
2.4. Sample preparation and dissolution of soil and dust
Soil samples were oven-dried at 40 C before being disaggregated and sieved to <2 mm. From this <2 mm fraction,
samples for total elemental analysis were ground in an agate
ball mill. Pressed sample pellets were prepared using 10 g of
sample and 2.5 g of binder wax (PANalytical, UK) for analysis by
X-ray uorescence spectrometry. Vegetable patch soils were
further sieved (<250 mm) for bioaccessibility testing. Dust
samples were sieved (<250 mm) and weighed (0.25 g) into PFA
vials (Savillex, USA) for mixed acid digestion as described for
soil dissolution elsewhere.42 It is acknowledged that there is
a discrepancy between the size fractions in which total As in soil
(<2 mm) and dust (<250 mm) were determined. This was due to
operational circumstances (the outsourcing of soil analysis) and
was judged to have negligible impact on the key ndings of the
investigation.
Bioaccessible As concentrations in soils were determined
using the Bioaccessibility Research Group of Europe (BARGE)
Unied Bioaccessibility Method (UBM)43 following previously
published methodology.41 In brief, duplicate amounts of 0.6 g of
<250 mm sieved soil were added to Nalgene™ oak ridge polycarbonate centrifuge tubes (Fisher Scientic, UK) followed by
the addition of simulated digestive uids designed to replicate
the mouth, stomach and small intestine. Either duplicate
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underwent one of two extractions as follows: (i) stomach phase:
saliva and gastric uid added; adjusted to pH 1.2 0.5; rotated
end-over-end at 37 C for 1 h in a water bath; centrifuged for
15 min at 4500g; (ii) stomach and intestinal phase: stomach
phase as above; duodenal and bile uids added; adjusted to pH
6.3 0.5; rotated end-over-end at 37 C for a further 4 h;
centrifuged as above. Supernatants (10 mL) were collected and
preserved with 0.2 mL concentrated HNO3 prior to analysis by
ICP-MS. Bioaccessibility was determined by the UBM method in
both the stomach and intestinal compartments of the simulated gastrointestinal tract. The highest concentration from the
two compartments was selected as the bioaccessible concentration in this study, following common practice.44 The bioaccessible fraction (BAF) of As was calculated as a percentage of
the total As concentration and is henceforth employed as an in
vitro estimate of the relatively bioavailable fraction in the CLEA
model.
2.5. Elemental analyses of soil and dust
Soil total As concentrations were measured by an Axios
Advanced wavelength-dispersive XRFS instrument (PANalytical,
Nottingham, UK). Dust and bioaccessibility digests were diluted
40 and 100, respectively with 1% v/v HNO3 + 0.5% v/v HCl
and total As concentrations were determined by inductively
coupled plasma mass spectrometry (ICP-MS) (Agilent 7500cx
series) using previously reported operating conditions.41 A
three-point calibration with concentrations at 1, 10 and 100 mg
L 1 and helium collision cell mode was used for total As
determination. A multi-element internal standard was introduced via a T-piece and Ge was used to correct for As signal
dri. Doubly-charged 150Nd++ and 150Sm++ interferences on As
were corrected using single element standards at 100 mg L 1 and
the application of a correction factor as described previously.41
2.6. Quality assurance/quality control
Field duplicate soil samples were collected at seven households
from different auger points at the same location of the initial
sample. For each dissolution batch of 50 dust samples (2
batches in total), 4 certied reference materials (CRMs), 5
digestion duplicates and 5 reagent blanks were digested. The
CRMs used were National Institute of Standards and Technology (NIST) 2584 Indoor Dust (2 0.25 g per batch) and NIST
2711a Montana II Soil (2 0.25 g per batch). Pearson correlation between soil eld duplicate total As concentrations was
0.996 (n ¼ 7) with a mean difference of 8% (geometric mean
(GM): 5%; range: 1–21%). The Pearson correlation between dust
digestion duplicate total As concentrations was 0.98 (n ¼ 10)
with a mean difference of 13% (GM: 5%; range: 1–69%). The
mean recovery for NIST 2584 digested with vacuum bag samples
was 93 3% (n ¼ 4) and 101 4% (n ¼ 4) for NIST 2711a.
2.7. Bioaccessibility adjusted household assessment criteria
Individual household bioaccessibility adjusted assessment
criteria (ACBIO) values were derived by changing the soil relative bioavailable fraction parameter in the CLEA soware
(version 1.071)6 from 1.0 to the bioaccessible fraction measured
520 | Environ. Sci.: Processes Impacts, 2017, 19, 517–527
Paper
for individual vegetable patch soils in vitro (n ¼ 68). The CLEA
land use and chemical parameters applied were the same as
those used for the As C4SL (with produce), of which full details
can be found in the C4SL report.8 Only soil relative bioavailable
fraction was altered to derive ACBIO values. Total As concentrations measured in this subset of households were then
compared with the ACBIO value for that household and recorded as an exceedance if the ACBIO value was lower than the As
concentration.
2.8. Spatial and historical mining variables
Mapping and spatial analysis was performed using ArcMap
version 10.1 (ESRI, USA). Metalliferous mineralisation classication (1 km squares shapele) was produced by BGS using
a dataset originally compiled by Ove Arup.45 This was used
during the development of As NBCs for English soils (Fig. 1) to
dene the mineralised domain. All other areas in Cornwall are
classied as principal domain locations as they fall outside of
this mineralised classication. A spatial dataset of historical As
mining sites was compiled using (i) a BGS publication46 containing details, gathered by George Dines, of former mining
sites across south-west England and (ii) the BGS BRITPITS
database,47 containing entries of active and inactive mineral
workings across the UK. Those listed in Dines' publication as
having produced As were located in BRITPITS. Ninety three
percent of the sites listed by Dines were obtainable from
BRITPITS and a further 5% were located via Google Maps.
Where multiple points were present in BRITPITS for the same
name, all points were extracted if they were in the expected
location. Household proximities to Cu, Sn and As mines from
BRITPITS and then to the rened As-specic records were
calculated using the ArcMap ‘near’ tool.
2.9. Statistical analysis
Data analyses were performed in the R programming environment version 3.2.2 48 (base package unless otherwise specied).
Concentration data in soil and dust were found to be positively
skewed leading to the calculation of geometric means (GMs) in
addition to arithmetic means. For the same reason, data were
natural log(ln)-transformed prior to statistical analyses.
Unequal variances (determined by F tests) and unequal group
sizes led to the use of Welch's test to compare concentration
data (ln-transformed) between different groups (e.g. NBC
domains). Pearson correlation coefficients (rp) were calculated
(including p-values and 95% condence intervals) to test relationships between, for example, soil total As concentrations and
those in dust (ln-transformed). The signicance between
strength in correlations was determined using Williams' test in
the ‘psych’ package.49 Linear regression was used to investigate
the relationship between soil As concentration and mine proximity (ln-transformed variables). To assess the spatial correlation of residuals, variogram analysis was performed using the
‘sp’ and ‘gstat’ packages.50,51 Generalised linear modelling was
used to assess the relationship between soil As concentrations
and proximity to mines with adjustment for spatial correlation
using the ‘nlme’ package.52
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3.
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Results and discussion
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3.1. Soil total and bioaccessible As concentrations
Summary statistics for soil As are shown in Table 1.
One hundred and twenty nine households were visited for this
study. Residential soil was collected from 127 (98%) households,
68 of which (54%) were using the soil for home-grown produce
(vegetable patch soils) and the remaining 59 (46%) were garden
soils. Soils (vegetable patch and garden) from 56 (44%) households were located within the principal NBC domain and 71
(56%) from within the mineralised NBC domain. Resident
reports shows that 26 (38%) of the vegetable patches had been
modied in some way (e.g. addition of imported soil, compost or
manure). Welch's tests found no signicant difference between
As concentrations in vegetable patch and garden soils within NBC
domains (principal: p ¼ 0.12; mineralised: p ¼ 0.88). Higher total
As concentrations were measured in modied vegetable patch
soils compared to unmodied soils but the difference was not
signicant (principal: p ¼ 0.12; mineralised: p ¼ 0.06). These
analyses were constrained by small group sizes and no conclusions can be drawn. The distinction between modied and
unmodied soils, while not a focal point of the paper, is presented for reference only. Soils from the mineralised domain
were found to contain signicantly higher total As concentrations
than those from the principal domain (GM: 74 versus 40 As mg
per kg). No signicant difference was found in the BAF of vegetable patch soils between different NBC domains (p ¼ 0.33) or soil
modications (p ¼ 0.07).
Summary statistics for total As, bioaccessible As and As bioaccessible fraction (BAF) for various sample groups and soil Normal
Background Concentration (NBC) geochemical domains
Table 1
Sample type or NBC
domain
Total As (mg kg 1)
All
All vegetable patch
All garden
All principal
Principal vegetable patch
Principal garden
Principal modieda
Principal unmodieda
All mineralised
Mineralised vegetable
patch
Mineralised garden
Mineralised modieda
Mineralised unmodieda
n
Min
Max
Arithmetic
mean
Geometric
mean
127
68
59
56
32
24
13
19
71
36
12
12
16
16
16
17
22
16
12
12
992
992
474
436
436
106
436
146
992
992
89
94
82
55
65
41
96
44
115
120
57
58
55
40
45
34
59
38
74
73
35
13
23
16
40
12
474
992
395
111
171
91
75
107
59
2
87
15
10
Bioaccessible As (mg kg 1)
All vegetable patch
68
Bioaccessible fraction (BAF) (%)
All vegetable patch
68
3
Soil As concentrations are comparable with previously reported As concentrations in residential soils in south west
England overall, but lower than three reports of samples taken
from mining areas. Those measured in 1154 topsoil samples
collected for the G-BASE40 south west England (Devon and
Cornwall) campaign ranged from 5 to 1949 mg kg 1 (mean:
50 mg kg 1).53 Culbard and Johnson (1984) reported a range of
119–1130 mg kg 1 in garden soils collected from the former
Cornwall mining area of Camborne and Hayle.28 Farago and
Kavanagh (1999) reported concentrations of 120–1695 mg kg 1
from gardens in the former mining area of Gunnislake and 345–
52 600 mg kg 1 at the Devon Great Consols mine.31 Xu and
Thornton (1985) reported a range of 144–892 mg kg 1 in soils
used for home-grown vegetable production in the former
Cornwall mining areas of Hayle, Camborne and Godolphin.29
The BAF of vegetable patch soils in the present study (range:
3–57%; mean: 19%; 25th percentile: 13%; 75th percentile: 23%)
are comparable with previously reported As bioaccessibility in
soils from across the UK (2 to 68%)44 and south west England
10–20%;7 16% (single measurement);54 10 to 34% (mean:
19%).55 Whilst BAF estimates have been found to be higher in
mining areas (mean: 15%) compared to other mineralised soils
with no previous history of mining activity (mean: 9%), the
overall BAF of As in soils is still far below 100%.56 These ndings
are important because it has been reported that the generic and
conservative assumption of 100% relative bioavailability in
human health risk assessment can lead to unnecessary remediation of potentially contaminated land and potential blight
for homeowners who live within such areas.57,58
3.2. Dust total As concentrations
Dust samples were collected from 99 (77%) households.
Summary statistics for total As concentrations measured in
these dust samples are presented in Table 2.
Previous studies have measured total As concentrations in
household dust samples in south west England and the ndings
presented in this paper are within a similar range. Farago and
Kavanagh (1999) reported As concentrations of 24 to 3740 and
33 to 1160 mg kg 1 in two separate mining locations.31 Culbard
and Johnson (1984) reported a lower concentration range of 1 to
330 mg kg 1 in a former mining village,28 as did Rieuwerts et al.
(2006) (43–486 mg kg 1).7 These concentrations can be
considered elevated compared to a non-mining area in Cornwall (e.g. 1.7–29 mg kg 1).7 A Canadian survey of household
vacuum cleaner dust samples (n ¼ 1025) reported lower
concentrations (range: 0.1–153 mg kg 1; GM: 7.7; 95th
Summary statistics of total As in composite indoor dust
(vacuum cleaner) samples
Table 2
NBC domain
57
19
a
17
Modied indicates that the householder reported vegetable patch soils
had been modied.
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n
Total As (mg kg 1)
All
99
Principal
40
Mineralised
59
Min
Max
Arithmetic
mean
Geometric
mean
3
5
3
1078
903
1078
84
54
104
41
28
54
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Paper
percentile: 40.6)59 than this study, indicating that many
households in Cornwall have elevated As in dust relative to
a nationally representative (Canadian) urban background. It
was recognised that a Canadian background may not be directly
applicable to a UK scenario and, in the absence of background
data from the UK, the comparison should be interpreted
cautiously.
Dust from households in the mineralised domain contained
signicantly (p ¼ 0.001) higher As concentrations than those in
the principal domain. A weak, but signicant (p < 0.01), Pearson
correlation was observed between residential soil and dust As
concentrations (rp ¼ 0.26; 95% CI ¼ 0.07, 0.44). The median
ratio of dust/soil total As concentration was 0.62, broadly
comparable to the soil-to-dust transport factor of 0.5 used in the
CLEA model.6 Rieuwerts et al. (2006) did not report a signicant
correlation between soil and dust As concentrations7 whereas
Keegan and Hong60 reported a weak (0.40), albeit signicant
correlation. Of the 97 households where both soil and dust was
collected, 48 reported having pets in the house and 29 reported
having no pets. For the remaining 20 households, pets were
reportedly kept outside or results were ambiguous. A signicant
(p ¼ 0.01), weak correlation (rp ¼ 0.35; 95% CI ¼ 0.08, 0.58) was
found between soil and dust As concentrations in households
with pets. There was no signicant (p ¼ 0.55) correlation
between soil and dust As concentrations in households without
pets (rp ¼ 0.12; 95% CI ¼ 0.26, 0.46). Chemical elements and
other toxicants have the potential to be tracked indoors by pets
and on the surfaces of footwear.8,61 The stronger correlation for
houses with pets is consistent with this mechanism, though
numbers are small and the p-value for the difference between
correlations of dust As versus soil As concentrations for households with and without pets was only 0.31, using Williams' test.
Factors such as the number of householders and their occupation as well as environmental considerations such as climatic
conditions have previously been associated with indoor As and
other element concentrations,62 but were not investigated in the
present study.
3.3. Generic assessment criteria (C4SL) and normal
background concentrations
Study soil concentrations compared to the As C4SL (with and
without produce) and the As NBC are shown in Table 3.
A high proportion of households across the study region
exceeded the As C4SL, both for soils with home-grown produce
(71%) and without (66%). This proportion was higher in the
mineralised domain, especially for the group without home
grown produce. The NBC for the mineralised domain (290 mg
kg 1) is almost 10-times the value of the C4SL, suggesting that
an appreciable number of households in England, located
within the mineralised domain for As, are also likely to be in
exceedance. In this study, only 8% of households in the mineralised domain exceeded the NBC, whereas 52% exceeded the
lower NBC in the principal domain. It is possible that the spatial
resolution of the NBC domains may have resulted in the
misclassication of households in the study area. For example,
households categorised as principal domain that reside on
localised, unmapped mineralisation.
3.4. Bioaccessibility-adjusted household assessment criteria
ACBIO values were derived using CLEA by changing the default
C4SL relative bioavailable fraction of 1.0 to the in vitro BAF
estimates for each household with vegetable patches as determined by UBM. The land-use scenario applied was residential
with consumption of home-grown produce, which assumes As
exposure of a 0–6 year old female child receptor. This is
conservative since children were not resident in most households (16% of households with occupants <16 years old) and
46% did not grow their own produce. It was not justiable to use
anything but the generic female child receptor because detailed
quantitative risk assessment for each property is outside the
scope of this paper.
Eight (13%) of the 68 households for which a bioaccessibility
adjusted assessment criteria (ACBIO value) was derived exceeded their respective values. Six (9%) households in the
Exceedances of the C4SL for total As in residential soils and the NBCs of total As in English soils. Results are presented for different
sample types and NBC domains
Table 3
Sample type or NBC domain
n
Value (As mg per kg)
n exceeding
% exceeding
C4SL (with home-grown produce)
All vegetable patch
Principal
Mineralised
68
32
36
37
48
20
28
71
63
78
C4SL (without home-grown produce)
All garden
Principal
Mineralised
59
24
35
40
39
9
30
66
38
86
Principal NBC
All principal
56
32
29
52
Mineralised NBC
All mineralised
71
290
6
8
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mineralised NBC domain exceeded their ACBIO values, whilst
only two (3%) exceeded in the principal NBC domain. Household exceedances of total As concentrations with respect to both
the C4SL and the household specic ACBIO values are shown in
Fig. 2 for the 68 households with a vegetable patch present.
The ndings presented in Fig. 2 illustrate that the derivation
of ACBIO for this study resulted in a large reduction in the
number of household exceedances relative to comparing to the
C4SL without incorporating bioaccessibility data. However,
a small number of residential soil As concentrations (n ¼ 8),
particularly in the mineralised domain, still exceeded their
respective ACBIO values. Rieuwerts et al. (2006) used the CLEA
model to derive average daily exposures (mg per kg per day)
using bioaccessibility data and reported that 0.3 mg per kg per
day was exceeded by 75% of households.7 However, this
proportion applied exclusively to a former mining area. Whilst
it is acknowledged that the household-specic ACBIO value
estimates made in the present study were still conservative, they
are consistent with previous reports25 that infants and small
children may be particularly vulnerable to As exposure in
particularly elevated spatial locations such as mineralisation
and in proximity to former mining sites. The geochemical
controls on bioaccessibility were not investigated in this study,
but likely dictate how the number of assessment criteria
exceedances varies by region.
An additional line of useful research would be to assess the
importance of home-grown vegetable consumption in the adult
population within the study area. This would be approached by
surveying residents to quantify their intake and compare this to
the generic parameters in CLEA. The generic assumption used
to derive C4SLs is that the fraction contribution of home-grown
produce to vegetable intake is between 2 and 9% depending on
product type. It is noted in the C4SL guidance document8 that
this probably underestimates the contribution for many population sub-groups. This is likely the case in Cornwall, where
a high prevalence of home-grown vegetable production was
observed during eldwork. Studies conducted elsewhere have
found this to be a substantial pathway of exposure. One study63
investigated
gardening
and
home-grown
vegetable
Environmental Science: Processes & Impacts
consumption at properties in the vicinity of a former mining
and smelting site in Arizona. They reported that garden soils
and home-grown vegetables accounted for 16 and 7% of daily As
intake, respectively. In a different approach to that used in this
paper, the authors used correlations between As concentrations
in soils and vegetables to derive maximum allowable concentrations in soils to limit excess cancer risk to 10 6 (i.e. one in
a million). These estimates ranged from 1.56 mg kg 1 to
12.4 mg kg 1 As in soil depending on the different vegetable
families grown in them. All of the soils collected in the present
study exceeded the estimates previously presented,63 barring
one soil in the case of the upper estimate. A detailed assessment
of home-grown vegetables consumption was not conducted in
the present study, but the ndings mentioned above make this
a topic worthy of further investigation.
3.5. Spatial inuences on residential As concentrations
A dataset containing the names and locations of 103 Asproducing mines in Cornwall was generated from BRITPITS
and Dines' publication.46 These mines, in addition to other Cu
and Sn mines and mineralisation in relation to households are
plotted in Fig. 3. The names of individual mines are shown in
Fig. S1.† Geometric mean household distances to all mining
sites were 4.4 and 1.2 km for the principal and mineralised
domains, respectively and 7.1 and 3.2 km for As-specic
mines. Due to the inter-domain differences and the signicantly higher soil As concentrations in the mineralised
domain, regression analysis was performed on separate
domains.
Several linear regression models were initially tested for logresidential As concentrations as a function of log-mining
proximity (log transformed because mining proximities were
negatively skewed). These models showed that distance to all
mines was not a signicant predictor (r2 ¼ 0.03; p ¼ 0.15) of
total soil As in the mineralised domain, however, it was
signicantly, but weakly, (r2 ¼ 0.11; p ¼ 0.01) inversely associated with soil As in the principal domain. Distance to As-specic
mines was signicantly (r2 ¼ 0.28; p < 0.001) inversely related
with total soil As in the mineralised domain but not (r2 < 0.01; p
Fig. 2 Individual vegetable patch soil (n ¼ 68) total As concentrations (ordered) for the mineralised (blue) and principal (grey) NBC domains.
Concentrations are plotted in comparison with the residential As C4SL with home-grown produce (37 mg kg 1 – red line) and household specific
derived ACBIO values (red points joined with black line).
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Paper
Fig. 3 The spatial distribution of As-specific former mining sites, located from BRITPITS and Dines (1956), in relation to sampled households. The
mineralised NBC domain and additional Cu and Sn mines are also plotted. Compiled using ESRI ArcMap 10.1. Contains British Geological Survey
materials © NERC 2016. Contains Ordnance Survey data © Crown Copyright and database rights 2016.
¼ 0.65) in the principal domain. Distance to mine (all or Asspecic) was not a signicant predictor of dust As concentration in either domain.
The inverse relationship between soil As concentration and
As-specic mine proximity (both ln transformed) in the mineralised domain was chosen for further investigation. Model 1
is the simplest – with no spatial correlation adjustment (simply,
ln(soil As) as a function of ln(distance to nearest mine)).
Due to the spatial nature of the data under investigation,
points occupying nearby locations in space with similar
mining proximities and soil As concentrations had the
potential to violate model independence from confounding
spatial factors. To validate the relationship between soil As
concentration and mine proximity, the Model-1 residuals were
investigated for spatial correlation using a variogram. Residuals exhibited a spatial correlation up to approximately 8 km
and, therefore a spatial correlation structure was added to
a generalised least squares model (Model-2) of soil As
concentration against mine proximity (the same structure as
Model 1). Several correlation structures64 were tested and,
using Akaike's Information Criterion (AIC), a spherical structure yielded the best t and was signicantly better than the
GLS without the addition of the correlation structure (AIC: 159
versus 168; ANOVA p ¼ 0.002). The Model-2 residuals exhibited
no spatial correlation following normalisation with the
spherical structure and soil As concentration remained
signicantly inversely correlated with mine proximity. The
regression coefficient in Model 1 was 0.54 per ln-unit and
0.47 in Model 2, both signicant (p < 0.001). A description of
the methods employed in this paper for spatial correlation
normalisation has been published in detail.64
524 | Environ. Sci.: Processes Impacts, 2017, 19, 517–527
The widespread As contamination resulting from the extensive mining operations in Cornwall's past have been widely reported12,13,25,27 as well as high concentrations at specic, heavily
contaminated locations.65,66 The utility of the As-specic rened
mining dataset generated in this study highlights the importance of individual mining site characteristics in how residential As, and other elemental contamination is distributed in the
study region.
It is noted that the observed correlation between soil As and
mining proximity does not necessarily reect emissions from
mining operations. For example, the locations of As mining
were likely dictated by local As ore grades – dependant on local
geochemistry. Therefore, it is possible that the correlation
between soil As and mining proximity is an indirect relationship
between residential soil and parent material As concentrations.
Further investigation would require a representative spread of
households across a range of lithology groups. Another limitation of the data used in the present paper is acknowledged, in
that site-specic variables were not available to include in
analyses. Sites require investigation to quantify the levels of
contamination present at a given mining site26 and the spread
of contamination around former workings.65 Nevertheless, this
paper presents a correlation between residential soil As
concentrations and proximity to historical As mining sites in
the study region using datasets not previously exploited for this
purpose.
4. Conclusions
This study is the largest of its kind to be conducted at residential properties in Cornwall to date and has conrmed
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Environmental Science: Processes & Impacts
widespread elevated concentrations of As in soil and dust in the
region. A high proportion of households exceeded the C4SL for
As in residential soils. The human ingestion soil As bioaccessibility data measured for this study using the UBM
enabled the derivation of ACBIO that accounted for the low
bioaccessibility of As in the soils collected in the study region.
The number of household exceedances of ACBIO were
substantially reduced in comparison to the C4SL. A small
number (n ¼ 8) of households, particularly in mineralised areas,
remained in exceedance of ACBIO. Further investigation is
warranted to assess the exposure of the local population,
particularly small children and home-grown vegetable
consumers, to As in residential soil and dust. Using an Asspecic historical mining dataset, residential soil As concentration were found to be inversely correlated with proximity to
historical As workings, but more work is needed to qualify this
as a causal relationship.
Terminology
In this text, “relative bioavailability” refers to the parameter in
the contaminated land assessment model and “bioaccessible
fraction” is that which is determined in vitro using the unied
bioaccessibility method. In this context, bioaccessibility is
employed as a proxy of bioavailability.
Disclaimer
This paper does not reect the organisational opinions or
recommendations of Public Health England (PHE). The
methods used in this paper are for research purposes and are
not endorsed by PHE for the purpose of contaminated land risk
assessment.
Abbreviations
ACBIO
AIC
BAF
BW
C4SL
CLEA
GM
NBC
UBM
Bioaccessibility adjusted assessment criteria
Akaike's information criterion
Bioaccessible fraction
Bodyweight
Category 4 screening level
Contaminated land exposure assessment (model)
Geometric mean
Normal background concentration
Unied bioaccessibility method
Acknowledgements
The authors gratefully acknowledge the contributions of Mark
Cave for statistical and scientic review of the manuscript.
Andrew Dunne and Andrew Marriott are thanked for their
participation in eld work and Louise Ander for help with
constructing the eld database. Joshua Coe is thanked for
contributions to laboratory analysis. Helen Crabbe, Karen Exley,
Amy Rimell and Mike Studden are thanked for their
This journal is © The Royal Society of Chemistry 2017
contributions to the wider project. Funding for this research
was provided by the Natural Environment Research Council
(NERC) via a University of Manchester/British Geological Survey
(BGS) University Funding Initiative (BUFI) PhD studentship
(Contract No. GA/125/017, BUFI Ref: S204.2) and the Centre for
Environmental Geochemistry, BGS. The participation of the 215
volunteers in the wider study is gratefully acknowledged.
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