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CONCENTRATION OF TOXIC ELEMENTS IN TOPSOILS OF THE METROPOLITAN
AREA OF MEXICO CITY: A SPATIAL ANALYSIS USING ORDINARY KRIGING AND
INDICATOR KRIGING
Thomas IHL
1
, Francisco BAUTISTA
1
*, Fredy Rubén CEJUDO RUÍZ
1
,
María del Carmen DELGADO
1
, Patricia QUINTANA OWEN
2
, Daniel AGUILAR
2
and Avto GOGUITCHAICHVILI
2,3
1
Laboratorio Universitario de Geofísica Ambiental, Centro de Investigaciones en Geografía Ambiental, Univer-
sidad Nacional Autónoma de México, Campus Morelia, Antigua Carretera a Pátzcuaro 8701, Col. Ex-Hacienda
de San José de la Huerta, C.P. 58190, Morelia, Michoacán, México
2
Departamento de Física Aplicada, Centro de Investigación y Estudios Avanzados-Mérida, A.P. 73, Cordemex,
14 97310, Mérida, Yucatán, México
3
Laboratorio Interinstitucional de Magnetismo Natural, Instituto de Geofísica – Sede Michoacán, Universidad
Nacional Autónoma de México, Campus Morelia, Antigua Carretera a Pátzcuaro 8701, Col. Ex-Hacienda de
San José de la Huerta, C.P. 58190, Morelia, Michoacán, México
*Autor de correspondencia: leptosol@ciga.unam.mx
(Recibido mayo 2013; aceptado octubre 2014)
Key words: Pb, V, Ni, Cu, contamination factor, pollution load index
ABSTRACT
In order to generate relevant information for decision-makers to protect the inhabitants
of the Metropolitan Area of Mexico City, 89 samples of topsoil were collected in urban
zones to assess the concentration of toxic elements. For this purpose, the concentration
of Cr, Cu, Ni, Pb, V and Zn were quanti¿ed with X-ray Àuorescence. To evaluate the
pollution, we considered the maximum permissible limits, the contamination factor
and the pollution load index. The spatial distribution was analyzed by geostatistical
methods. Ordinary and indicator Kriging were applied to estimate the values at un-
measured sites and the proportion of the values exceeding the critical concentration for
each element within a region. The study revealed that the Metropolitan Area of Mexico
City has excessive environmental problems related to pollution. The concentrations of
Cr and V are apparently not anthropic, while the high amounts of Cu, Zn and Pb are
largely due to human activities. The pollution of Ni exhibits two single spots, while
Cu and Zn contents are distributed from the city center towards the northern suburbs.
The presence of Pb is spread evenly through the entire urbanized area. The probability
maps clearly identify the most contaminated areas, which requires immediate action
by local decision-makers.
Palabras clave: Pb, V, Ni, Cu, factor de contaminación, índice de carga contaminante
RESUMEN
Con la ¿nalidad de generar información para la toma de decisiones y proteger a los
habitantes del área metropolitana de la ciudad de México, se tomaron 89 muestras de
Rev. Int. Contam. Ambie. 31 (1) 47-62, 2015
Thomas Ihl
et al.
48
suelo super¿cial urbano, con las que se evaluó la concentración de elementos tóxicos.
Se midió la concentración de Cr, Cu, Ni, Pb, V y Zn utilizando un equipo de Àuores
-
cencia de rayos X. Para valorar la contaminación del suelo se utilizaron los límites
máximos permisibles, el factor de contaminación y el índice de carga contaminante. Se
realizó un análisis de la distribución espacial de los elementos medidos por los métodos
geoestadísticos como Kriging ordinario y el indicador Kriging. El análisis reveló que
la zona metropolitana de la Ciudad de México tiene problemas ambientales excesivos.
Las concentraciones de Cr y V al parecer no tienen causas antrópicas, mientras que las
altas cargas de Cu, Zn y Pb son en gran medida de origen humano. La contaminación
por Ni presenta dos puntos esenciales, el Cu y Zn se distribuyen desde el centro hacia
los suburbios del norte. El Pb está distribuido uniformemente sobre el área urbanizada.
Los mapas probabilísticos permiten identi¿car claramente las zonas más contaminadas
en las cuales los tomadores de decisiones locales deben tomar acciones inmediatas de
remediación.
INTRODUCTION
The metropolitan area of Mexico City (MAMC)
has more than 20 million inhabitants and a still-grow-
ing population. The MAMC has more than 40000
small and medium-sized industries, and vehicles
use daily more than 40 million L of petroleum fuels
producing thousands of t of pollutants (Molina
et
al
. 2010, UN 2012). However, diagnoses of urban
topsoil contamination with toxic elements (TE) are
still scarce (Morton-Bermea
et al
. 2009, Rodríguez-
Salazar
et al
. 2011, Aguilar
et al
. 2012).
This MAMC is the third-largest urban region in
the world (UN 2012). It lies on an intermountain
basin, with an altitude of approximately 2200 m
above the sea level and is surrounded on three sides
by recent volcanoes. This physical location, together
with local phenomenon such as intense emissions
from private and public transport and high concentra-
tions of industries in the afÀuent suburbs, frequently
causes smog along the city. The winds blow over the
mountains, but there is little circulation to transport
the heavier particles of smog and dust out of the
basin. Therefore, emissions accumulate throughout
the morning and afternoon. During the evening, wind
rises and disperses a lot of the smog, but settles it
again over the basin during the cooler nights. This
pattern is repeated on subsequent days. Furthermore
the air quality is generally worse in winter, when there
is practically no rain and thermal inversions are more
frequent (Molina
et al
. 2010).
Over the last decades the term “heavy metals” is
widely used in environmental studies for their toxic-
ity, although there are still considerable uncertainties
about their de¿nition. In speci¿c literature, the densi
-
ty criteria varies from above 3.5 g/cm to above 7 g/cm
(Duffus 2002). In addition, we have also transition
and post-transition metals as toxic elements or trace
elements with considerable toxicity. Consequently
we use for this study the term “toxic elements” (TE)
instead of “heavy metals” as commonly used by the
United States Environmental Protection Agency
(US-EPA 2012).
There are different anthropic sources of TE in ur-
ban soils (Sutherland 2000, Aguilar
et al
. 2011, 2012,
Alloway 2012, Aguilar
et al
. 2013a,b), their loads
in and around human settlements are a global prob-
lem. They enter the soils by different pathways: 1)
aerial deposition (industries, vehicles and volcanoes),
2) paints, 3) pesticide and fertilizer application,
4) waste utilization, 5) disposal of dredged sediments
and 6) river and irrigation waters (Kabata-Pendias
1993, McClintock 2012, Aguilar
et al.
2013b). They
pass through the air and food into the human organ-
ism, where they are usually not degraded, and hence
they accumulate and may cause cancer, neuropathy
and other serious diseases (Fubini and Otero 1999,
Muhle and Mangelsdorf 2003).
Geostatistic tools are now incorporated in most
geographic information systems. Among them,
ordinary kriging (OK) interpolates the values of a
random ¿eld at unobserved locations by using values
measured nearby sites. This approach is based on the
“¿rst law of geography” that “everything is related to
everything else, but adjacent things are more related
to each other” (Tobler 1970). However, soil pollution
shows a highly skewed nature, and Juang
et al
. (2004)
note that it is inappropriate to use certain geostatisti-
cal methods, such as OK to characterize their spatial
distributions by a Gaussian assumption.
In contrast, indicator kriging (IK) is a non-
parametric geostatistical method, which includes no
assumption of normality and uses a binary transfor-
mation (0-1 indicators) of data to make the predictor
TO&IC ELEMENTS IN TOPSOILS OF ME&ICO CITY
49
less sensitive to outliers. IK builds the cumulative
distribution function at each point on the basis of
the pattern and correlation structure of indicator-
transformed data points in the neighborhood. IK
can be used to estimate the proportion of values that
exceed critical concentrations of TE by incorporating
the uncertainty of the value of variables at unobserved
locations. After the cumulative distribution function
is built, it must be post-processed to produce a prob-
ability map (Goovaerts 1997, 1999, Antunes and
Albuquerque 2013, Aguilar
et al
. 2013b).
The aim of this study was to analyze the spatial
distribution of toxic elements (Pb, Zn, Ni, Cu, Cr and
V) in urban topsoil±s from MAMC, using the IK and
OK geostatistical techniques.
Diagnostic studies of soil pollution by TE should
refer to threshold values established in terms of ef-
fects on human health. For this purpose, we used:
(1) the maximum permissible limits for the Of¿cial
Mexican Standards (Norma Oficial Mexicana
²NOM³), (2) the contamination factor (CF), and (3)
the pollution load index (PLI).
MATERIALS AND METHODS
Study area, sampling and chemical analysis
The study area covers almost the entire urbanized
area of the MAMC (
Fig. 1
). Soils were collected using
a systematic method. For this purpose, the study area
of 1600 km´ was divided into a grid of 10 rows and
10 columns, so that each cell had an edge length of 4
km and an area of 16 km´. The high degree to which
the soil was covered made necessary to change some
sampling sites within the grid, depending on local
conditions. For some sparsely populated peripheral
areas by the surroundings of Texcoco and Cuernavaca
cities, sampling was omitted for ¿nancial reasons.
Fig. 1
Location of sampling sites in Mexico City and metropolitan area
Thomas Ihl
et al.
50
For analysis, samples from 89 sites were collected at
a depth of 2 inches using a polyvinyl chloride (PVC)
cylinder of 2.5 inches in diameter. The amount of
sample sites depends much less on a ¿xed minimum
number than other facts, including the kriging predic-
tion variance and the accuracy which the variogram
can estimate. As a rule of thumb is often mentioned
a number between 30 and 100 samples (Webster and
Oliver 1990). In practice there are only few studies
that use more than 100 sampling data.
Each sample was dried for two weeks under the
shade and then pulverized in a 2-mm mesh sieve.
The total concentrations of Pb, Zn, Ni, Cu, Cr and V
were analyzed by energy dispersive X-ray Àuores
-
cence (ED-XRF) in the laboratory at the Advanced
Research and Studies Center, called Centro de Inves-
tigaci&n y de Estudios Avanzados (CINVESTAV), in
MØrida, YucatÆn. This technique is precise quantita-
tive, fast and non-destructive and can measure a wide
range of elements concentrations (C (6)-Fm (100);
Khodeir
et al
2012, Ramírez
et al
2012), with a de-
tection limit of 1 mg/kg even in complex matrices
as soils. Only in the case of Ni, the minimum value
was below the detection limit.
The powdered soils were pressed into pellets of 1
cm diameter without any chemical treatment or bind-
ing agents and inserted into a plastic sample holder
covered with a polyester ¿lm. ED-XRF analyses
were performed with a Jordan Valley EX-6600 spec
-
trometer, equipped with a Si (Li) detector with a 20
mm
2
active area and 140 eV resolutions at 5.9 keV,
performed at a maximum of 54 kV and 4800 mA. TE
were acquired in an air atmosphere using a change-
able secondary target. The typical measurement time
was 300 s. Each measurement was replicated ¿ve
times in order to obtain the average concentration.
Quantitative data was calculated with a calibration
curve of intensity versus concentration of several
geological standard reference materials (Lozano and
Bernal 2005, Khodeir
et al
2012).
Data analyses
The data obtained was analyzed in four stages:
a) descriptive statistics were generated, including
arithmetic means, standard deviations, minimum
and maximum values for TE, b) data was compared
with the maximum permissible values, c) pollution
indices were applied and d) the geostatistic analysis
was conducted.
Permissible limits
The Official Mexican Standards “NOM-
147-SEMARNAT” of Soil Contamination was
published by the Ministry of Environment and
Natural Resources (Secretaría de Medio Ambiente
y Recursos Naturales; SEMARNAT) and include
only the permissible limits of Pb (400 mg/kg), V (78
mg/kg), Ni (1600 mg/kg) and Cr (280 mg/kg), but
exclude Cu and Zn (SEMARNAT 2007). The Of¿cial
Mexican Standards are largely based on those of the
US Environment Protection Agency (US-EPA 2012).
Pollution indices
Pollution indices are used to quantify TE in soils
and sediments and exist as a single index for one
metal, as well as an integrated index as a combina-
tion of the six elements. In the past, a large number
of indices were derived, which include CF, the eco-
logical risk factor, the enrichment factor, the index
of geo-accumulation, and the PLI. Unfortunately,
there is not always congruence between the different
indices and publications (Sutherland 2000, Buccolieri
et al
. 2006). Therefore, the indices used in this study
were de¿ned as follows:
Contamination factor (CF)
The level of soil contamination by TE is a ratio
calculated as follows:
CF
=
C
m
Sample
C
m
Background
(1)
Where,
CF
is the TE contamination factor,
C
m
Sample
is the metal concentration of the sample and
C
m
Background
is the natural metal content.
The sample was normalized with a background
that reÀects the natural metal content of the parent
material. The background can be determined by
various methods. However, it is often problematic.
Certainly, the classical method takes a sample out-
side of anthropic inÀuence, or at least where it is
as low as possible. Estimated minimum distances
are given from the study area or the sample is col-
lected in a natural protected area; in this context,
literature gives some reference on the concentrations.
Hakanson (1980) provides concentrations before the
industrialization of Cu 50 mg/kg, Pb 70 mg/kg, Cr
90 mg/kg and Zn 175 mg/kg. It remains question-
able any transmission to different conditions (soils,
substrate, source rocks). Fortunately, Morton-Bermea
et al
. (2009) have measured the backgrounds for the
MAMC (
Table I
). These natural concentrations of
TE are used for the CF.
CF indicates pollution according to the follow-
ing intervals: a value below 1 indicates insigni¿cant
TO&IC ELEMENTS IN TOPSOILS OF ME&ICO CITY
51
pollution of the site, a value of 1-3 moderate, 4-6
considerable and >6 very high pollution.
Pollution load index (
PLI
)
All sites were also analyzed by a synopsis of six
elements, which indicates the degree of contamina-
tion of the site. The “pollution load index” (
PLI
)
is derived from the unique CF for each site and is
calculated as:
PLI
=
CF
1
*
CF
2
*
CF
3
...
*
CF
n
n
(2)
Where,
CF
is the TE contamination factor,
n
represents the number of metals analyzed.
The
PLI
is simple to interpret: a value of zero
indicates excellent quality, a value of 1 the pres-
ence of only baseline levels of pollutants and values
above 1 is a progressive deterioration of site quality
(Tomlinson
et al
. 1980).
Geostatistic analysis
A georeferenced data matrix based on TE
concentration and indices was constructed. Sub-
sequently a geostatistical analysis was performed
with the Gamma Design Software (Robertson
2008), following the sequence: 1) Exploratory
data analysis and 2) Spatial autocorrelation. We
calculated the experimental semivariograms with
the equation:
γ
h
=
1
n
i
=1
2
n
Z
(
x
i
) – Z(
x
i
+
h
)
2
(3)
Where, γ
(
h
) is the experimental semivariance
value for all pairs at a lag distance
h
,
Z
(
x
i
) is the TE
concentration and the indices values at the point
i
,
Z
(
x
i
+
h
) is the TE concentration and the indices values
of other points separated from
x
i
by a discrete distance
h
,
x
i
is the georeferenced position where the
Z
(
x
i
)
values were measured,
n
is the number of pairs of
observations separated by a distance
h
(Isaaks and
Srivastava 1989, Hernández-Stefanoni and Ponce-
Hernández 2006, Delgado
et al
. 2010).
TABLE I
. TOXIC ELEMENT CONCENTRATIONS REPORTED FOR MEXICO CITY
Elements
Min
Max
Mean
Background
Reference
(mg /kg)
Cr
41
138
84
This study
50
265
116
105
Morton-Bermea
et al.
2009.
65
559
135
Rodríguez-Salazar
et al
. 2011.
280
Recommended by SEMARNAT (2007).
Ni
dl
a
186
45
This study.
20
146
39
56
Morton-Bermea
et al
. 2009.
29
151
49
Rodríguez-Salazar
et al.
2011.
1600
Recommended by SEMARNAT (2007).
Cu
7
550
92
This study.
15
398
54
32
Morton-Bermea
et al
. 2009
26
461
93
Rodríguez-Salazar
et al
. 2011.
3100
Recommended by EPA (region 9).
Zn
82
933
287
This study.
36
1641
219
76
Morton-Bermea
et al.
2009.
95
1890
447
Rodríguez-Salazar
et al.
2011.
32000
Recommended by EPA (region 9).
Pb
20
654
163
This study.
5
452
82
19
Morton-Bermea
et al
. 2009.
15
693
116
Rodríguez-Salazar
et al
. 2011.
400
Recommended by SEMARNAT (2007).
V
57
111
83
This study.
50
179
97
87
Morton-Bermea
et al
. 2009.
60
229
186
Rodríguez-Salazar
et al
. 2011.
78
Recommended by SEMARNAT (2007).
a
below detection limit (dl)
Thomas Ihl
et al.
52
The experimental semivariance was adjusted to
the theoretical model of spatial distribution of TE,
concentration and TE indices.
OK was used as the interpolation method to obtain
point data to plot Cr and PLI maps. IK was used as
the interpolation method to obtain point data to plot
TE probability maps. The variable measured on a
continuous scale is converted to several indicator
variables. Each variable takes a value of 1 or 0 at
each sampling site and the value of each variable
is estimated elsewhere in the study area, with < 1
indicating a value below the threshold level (Cetin
and Kırda 2003, Longley
et al
. 2005).
The TE are continuous variables
Z
(
x
i
), the indica-
tor variable
I
(
x
i
;
z
k
) where
z
k
is the desired threshold
limit is de¿ned as follows (Goovaerts 1997, 1999):
K
,
1,
k
,
0
)
(
1
)
;
(
=
=
otherwise
z
x
Z
if
z
x
I
k
i
k
i
(4)
Where
K
is the number of cutoff. The experimen-
tal indicator semivariogram,
gI
* (
h
), is then de¿ned
for every set of indicators at each cutoff
zk
as:
[ ]
2
)
(
1
)
;
(
)
;
(
)
(
2
1
)
(
=
*
+
-
=
h
N
i
k
i
k
i
I
z
h
x
I
z
x
I
h
N
h
γ
(5)
Where
N
(
h
) is the number of indicator pairs that
transform
I
(
xi
;
zk
) and
I
(
xi
+
h
;
zk
) separated by vector
h
. The conditional cumulative distribution function
at location
x
0
is:
=
=
=
n
i
k
i
i
k
k
z
x
I
z
x
I
n
z
x
F
1
0
0
)
;
(
)
;
(
*
))
(
;
(
λ
(6)
Where
I
* (
x
0
;
z
k
) is the estimated indicator level
at “unsampled location” (all other locations within
a raster, where no samples were collected)
x
0
and
l
i
is the weight assigned to the known indicator value
I
(
x
i
;
z
k
).
In this case, permissible limits for Pb (400 mg/kg)
and V (78 mg/kg) were used as threshold level, for
Cu and Zn there are no de¿ned limits (SEMARNAT
2007). A threshold value of CF = 3 was applied to
Ni, Cu, Zn, Pb and PLI = 2.
The ArcGIS 9.0 (ESRI 2004) software was
used for mapping. For a study of this scale level
we used the UTM projection, zone 14, horizontal
datum ellipsoid and the World Geodetic System 84
(WGS84).
RESULTS AND DISCUSSION
Permissible limits and indices
Mean and ranges of concentrations are compa-
rable to others previously recorded for Mexico City
(
Table I
). In all these studies, Cu, Zn and Pb show a
wide range of values, whereas the concentrations of
V, Cr and Ni are closer to their means (
Fig. 2
).
Alloway (2012) speci¿ed general background
values according to their different parent material.
The background concentrations outside parenthesis
indicate values for igneous rocks (basic). While those
in round brackets represents sedimentary rocks (silt
and clay): Cr 200 (90) mg/kg, Ni 150 (68) mg/kg, Cu
90 (39) mg/kg, Zn 100 (120) mg/kg, Pb 3 (23) mg/kg
and V 250 (130) mg/kg.
The bedrock of MAMC is divided in two major
units: basic igneous rocks, such as basalt, andesite
and tuff in the south and west and lacustrine sedi-
ments in the east, from the former lake of Texcoco.
The backgrounds mentioned (
Table I
) for the Valley
of Mexico City by Morton-Bermea
et al.
(2009) are
close to those of lacustrine sediments in Alloway
(2012), with the exception of Zn. The mean concen-
tration of V, Ni and Cr in the present study is similar to
their background values published in Morton-Bermea
et al
. (2009). Accordingly, we conclude that concen-
trations of V, Ni and Cr are determined apparently
by the parent material (soils and pollution), whereas
elevated concentrations of Pb, Cu and Zn are from
anthropic origin.
10
Log normalized (mg/kg)
Box Plots
1
0.1
Ni
Cr
Cu
Zn
Pb
V
Fig. 2
. Boxplot of contamination factor for toxic elements in
urban soils of Mexico City. (Log normalized mg/kg.
Boxes: 25th percentile and 75th percentile. Line between
boxes: median.
Symbol +, mean. Whisker: range. Cir-
cles: outliers. Stars: the extreme values)
TO&IC ELEMENTS IN TOPSOILS OF ME&ICO CITY
53
Skewness values indicate that only Cr (0.36) and
V (0.17) are approximately normally distributed. All
other metals show a positive skew towards the lower
concentrations. This reinforces the assumption that
the concentrations of Cr and V had a natural origin
as principal component. Localized anthropic sources
would act against a normal distribution.
There are some positive correlations between Cu and
Zn (0.78), Cu and Pb (0.64), Zn and Ni (0.62) and
Pb and Zn (0.58;
Table II
).
The permissible limits established by the Ministry
of Environment and Natural Resources (SEMAR-
NAT 2007) are legal references to be applied in
studies and reports, yet the limit for Pb was exceeded
at four sites (4.5 %) and for V at 63 sites (70.8 %).
The limit for Cr or Ni was not exceeded at any
analyzed site. Since no limits for Cu or Zn are speci-
¿ed in the Of¿cial Mexican Standards, the values
recommended by the US EPA were considered,
however the reading for Cu or Zn did not exceed the
limit at any site.
These concentrations of TE are slightly lower than
those reported in previous studies (
Table I
). Only 4.5 %
of the samples were beyond the permissible limit of
Pb, although in 70.8 % of samples, V exceeded the
Of¿cial Mexican Standards for TE concentration
in soils (SEMARNAT 2007). The Of¿cial Mexican
Standard (SEMARNAT 2007) is largely based on
those of the US Environment Protection Agency (US-
EPA 2012). The limits set is very high. Although a
high load is expected, only a few samples were above
the permissible limit. If we take the background into
consideration, it becomes clear that the high loads of
V are due to the parent material and not to anthropic
pollution. Either way, the V is dangerous. However,
more research is needed to elucidate the sources of
potentially toxic elements.
The background values and the skewness differ-
entiated two groups of metals: a) Cr, Ni and V with
a concentration very close to the background and a
normal Gaussian distribution and b) Cu, Zn and Pb
with a load signi¿cantly above the background and a
clear skewness. Therefore, the parent rocks cause the
concentrations of Cr, Ni and V, while the concentra-
tions of Cu, Zn and Pb are largely of human origin.
Results based on Of¿cial Mexican Standards are
dif¿cult to interpret in relation to the real load of pol
-
lution in urban soils because countries differ in their
standards. One of the strictest is the Netherlands where,
the standard for Ni is 615 times the Mexican Norm.
Accumulated CF means that although Cr, Ni and
V are under the baseline of 1, which is the critical
value between insigni¿cant and moderate pollution,
Cu (2.87), Zn (3.78) and Pb (8.59) are above it. Pb,
Zn and Cu are found in high concentrations in several
parts of the city (
Table III
).
With the obtained results, sites are classi¿ed con
-
sidering the pollutant load, those with a CF below 1
are insigni¿cantly polluted. Polluted sites are divided
into three categories: moderate (CF 1-3), high (4-6)
TABLE II
. PEARSON’S CORRELATIONS MATRIX FOR
TOXIC ELEMENTS
Cr
Ni
Cu
Zn
Pb
V
Cr
1
Ni
–0.11
1
Cu
0.31
0.01
1
Zn
0.21
0.62
0.78
1
Pb
0.32
0.15
0.64
0.58
1
V
0.51
–0.29
0.05
–0.12
0.04
1
TABLE III
. CONTAMINATED SITES BASED ON CONTAMINATION FACTOR
AND CLASSIFIED BY POLLUTION
Element
Type of data
Insigni¿cant
Moderate
High
Very high
Total
Cr
Absolute
77
12
89
Relative
87%
13%
100%
Ni
Absolute
71
18
2
89
Relative
80%
20%
2%
100%
Cu
Absolute
17
72
30
6
89
Relative
19%
81%
34%
7%
100%
Zn
Absolute
0
89
50
10
89
Relative
0%
100%
56%
11%
100%
Pb
Absolute
0
89
77
55
89
Relative
0%
100%
87%
62%
100%
V
Absolute
60
29
89
Relative
67%
33%
100%
Thomas Ihl
et al.
54
and very highly polluted (> 6). Moreover they are
(inversely) cumulated, which means samples that
were classi¿ed as very high are also included in the
considerable and moderate categories, in order that
only the two “insigni¿cant” and “moderate” records
together add up to 100 %.
Most of the samples with Cr (87 %), Ni (80 %) and
V (67 %) are unpolluted, while not a single sample
with Zn and Pb was classi¿ed as insigni¿cant. This
means that 100 % of the samples were contaminated
with Zn and Pb. In this study, Cu shows a similar
pattern as Zn and Pb, although not as immoderate.
There is no general agreement on permissible
limits and therefore different thresholds have been
suggested (Dosskey and Adriano 1991, Tyler 1992,
De Vries and Bakker 1996). For this reason, we also
used the contamination factor (CF) and the pollution
load index (PLI), which are indicators that have been
applied elsewhere worldwide (Caeiro
et al.
2005,
Mmolawa
et al
. 2011, Özkan 2012). The application
of these two indices to this study area show a consid-
erable TE loads but no consistent pattern.
Spatial analysis
The normal probability plot for Cr and V is suf-
¿ciently closed to linear, thus indicating that their
concentrations in Mexico City are approximately
normally distributed.
The nugget variance, structural variance and the
coef¿cient of determination (r
2
; ¿tness) between
experimental and theoretical semivariograms were
used to evaluate the model simulations. The TE con-
centrations and CF were represented by exponential
and spherical semivariograms (
Table IV
) with r
2
oscillating from 0.70 to 0.98. The structural variance
calculated by [C/(Co + C)]×100 had values oscillat-
ing from 73 to 99.8 %. In general, the nugget variance
values were low in relation to the structural variance,
indicating that the spatial distribution pattern for TE
and indices were well identi¿ed. Only CF
of Zn had
nugget values higher than 20 % (
Fig. 3
).
Figures 4
and
5
show the probability based on IK,
that the permissible limit of 400 mg/kg for Pb and
78 mg/kg for V will be exceeded. Pb concentrations
highlight a few hotspots in the city center and the west
area. For V > 70 % of the sampling sites are above
the permissible limit, with a gradient increasing from
north to south.
Until now different CF values were considered.
Insofar as the maps, however, a ¿xed uniform limit
must be chosen. For the maps started from
¿gures 6
to
9
a CF of 3 is set. For this reason, in this section we
can only present maps for Ni, Cu, Zn and Pb (compare
Table IV
). Cr and V have no single value in excess of 3.
The map for Ni shows bright less polluted areas,
with the exception of two distinct hotspots in the
northern suburbs. Thus it becomes clear why there
is a difference between Ni from both Cr and V. Cr
and Ni have only a slight impact on the study area
and are signi¿cantly different from the group of ele
-
ments with very high anthropic loads (Cu, Zn, Pb).
The maps for Cu (
Fig. 7
), Zn (
Fig. 8
) and Pb (
Fig. 9
)
show dark, highly contaminated areas, in this increas-
ing order.
A synthesis of all six of the TE shows high prob-
ability of moderate pollution in the districts (Benito
TABLE IV
. CHARACTERISTICS OF SEMIVARIOGRAM MODELS OF TOXIC ELEMENTS
Parameters/
Threshold
Model
Nugget
variance
Total
variance
Range
Structural variance
(%)
Model
r
2
Pb
400 mg/kg
Exponential
3.79
20.47
15720
81.5
0.98
V
78 mg/kg
Exponential
0.200
117
5640
99.8
0.91
Ni
CF
= 3
Spherical
0.0001
0.056
3970
99.8
0.70
Cu
CF
= 3
Exponential
0.018
0.300
14490
94
0.96
Zn
CF=3
Exponential
0.080
0.30
12090
73
0.95
Pb
CF
= 3
Exponential
0.042
0.51
12120
91.8
0.94
PLI
CF
=2
Exponential
0.0077
0.0591
13320
87
0.91
CF
= Contamination Factor;
PLI
= Pollution Load Index
TO&IC ELEMENTS IN TOPSOILS OF ME&ICO CITY
55
Juárez, Iztapalapa, Iztacalco, Venustiano Carranza,
Cuauhtémoc, Álvaro Obregón and Gustavo A.
Madero precincts) and the northern municipalities
(Ecatepec and Tlalnepantla), while the spatially
marginal areas of the metropolitan zone have lower
probabilities. The map with a PLI = 2 was chosen to
identify areas of urgent remediation action (
Fig. 10
).
Cartographic ¿gures have a practical utility for
illustration; however, selecting speci¿c thresholds
(CF, PLI) can cause visual impressions to serve a
political agenda.
After ascertaining the most polluted areas, it is
necessary to identify the chemical compounds of TE
in the soil by chemical fractionation (Bautista 1999,
Contamination factor
20.4
15.3
10.2
Semivariance
Permisible limits
5.2
0.0
0.00
5983.60
Pb
V
11967.19
17950.79
0.00
6983.60
13967.19
20950.79
125
93
62
31
0
0.0639
0.0479
0.0319
Semivariance
0.0160
0.0000
0.00
3316.67
CF Ni
CF Cu
6633.33
Distance (m)
Distance (m)
Distance (m)
Distance (m)
Distance (m)
Distance (m)
Distance (m)
9950.00
0.00
6983.33
13966.67
20950.00
304
228
152
076
000
Semivariance
0.310
0.232
0.155
0.077
0.000
0.00
6983.33
CF Zn
CF Pb
13966.67
20950.00
0.00
6983.33
13966.67
20950.00
0.518
0.389
0.259
0.130
0.000
Pollution load index
Semivariance
0.0611
0.0458
0.0305
0.0153
0.0000
0.00
6983.33
PLI
13966.67
20950.00
Fig. 3
. Variogram models of toxic elements and indices
Thomas Ihl
et al.
56
Fig. 4
. Map with permissible limit of Pb (400 mg/kg)
Fig. 5
. Map with permissible limit of V (78 mg/kg)
TO&IC ELEMENTS IN TOPSOILS OF ME&ICO CITY
57
Fig. 7
. Map of Cu with contamination factor of 3
Fig. 6
. Map of Ni with contamination factor of 3
Thomas Ihl
et al.
58
Fig. 8
. Map of Zn with contamination factor of 3
Fig. 9
. Map of Pb with contamination factor of 3
TO&IC ELEMENTS IN TOPSOILS OF ME&ICO CITY
59
Fitamo
et al
. 2007). This will allow the construction
of a mitigation strategy in order to address the prob-
lem of soil contamination.
One of the main contributions of this study is the
generation of reliable maps of an area of 1600 km²
with 89 sampling points, using geostatistical tools
and indicators of pollution.
CONCLUSIONS
After applying interpolation and geostatisti-
cal models according to various data management
options, the most signi¿cant ¿ndings of the study are:
The mexican maximum permissible limits are not
completely reported for all TE which is concerning,
as evidenced by examples of V and Pb.
High loads of Cr and V can be put into another
perspective by using the CF with “backgrounds”:
The high values are originated primarily from the
parent rock. However, the danger of Cr and V does
not depend on its origin.
The observed high loads of Cu, Zn and Pb are caused
mainly by anthropic sources and human activities.
Probability maps as a result of the indicator krig-
ing demonstrate very clearly the spatial distribution
Fig. 10
.Areas of soil pollution by toxic elements; map of probability that a pollution
load index of 2 will be exceeded
Thomas Ihl
et al.
60
of toxic elements all over the urbanized area and
identify easily hotspots.
Ni depicts two extreme spots of pollution close to
the city limits of Mexico City and Naucalpan. The sec-
ond one in the municipality of Ecatepec. Based on the
map, potential pollutant sources can be ¿xed spatially.
The TE of Cu and Zn are widespread over the
central and northern parts of the urbanized area, es-
pecially in the districts of Mexico City: Benito Juárez,
Iztapalapa, Iztacalco, Venustiano Carranza, Cuauh-
témoc, Alvaro Obregón and Gustavo A. Madero,
and the municipalities of Ecatepec and Tlalnepantla.
The high load of Pb is uniformly distributed in
high concentration over the entire urbanized area.
It represents an important environmental problem.
Results suggest an urgent mitigation strategy for
the MAMC. The pollution load index map is an easy
and clear way to illustrate the spatial relationships
and demonstrate this urgency to the decision-making
authorities and local stakeholders as well as to the
general community.
ACKNOWLEDGMENTS
We thank to the National Science and Technol-
ogy Council (Consejo Nacional de Ciencia y Tec-
nología;
CONACyT) for the ¿nancial support to the
projects CB-2011-01-169915. Rubén Cejudo and
Carmen Delgado acknowledge the postdoctoral fel-
lowship awarded by the National Autonomous Uni-
versity of Mexico (Universidad Nacional Autónoma
de México; UNAM) and CONACyT, respectively.
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