International Journal of Health
Geographics
BioMed Central
Open Access
Research
Validation of the geographic position of EPER-Spain industries
Javier García-Pérez*1,2, Elena Boldo1,2, Rebeca Ramis1,2, Enrique Vidal2,1,
Nuria Aragonés1,2, Beatriz Pérez-Gómez1,2, Marina Pollán1,2 and
Gonzalo López-Abente1,2
Address: 1Cancer and Environmental Epidemiology Area, National Centre of Epidemiology, Carlos III Institute of Health, Madrid, Spain and
2CIBER Epidemiología y Salud Pública (CIBERESP), Spain
Email: Javier García-Pérez* - jgarcia@isciii.es; Elena Boldo - eiboldo@isciii.es; Rebeca Ramis - rramis@isciii.es; Enrique Vidal - evidal@isciii.es;
Nuria Aragonés - naragones@isciii.es; Beatriz Pérez-Gómez - bperez@isciii.es; Marina Pollán - mpollan@isciii.es; Gonzalo LópezAbente - glabente@isciii.es
* Corresponding author
Published: 11 January 2008
International Journal of Health Geographics 2008, 7:1
doi:10.1186/1476-072X-7-1
Received: 15 October 2007
Accepted: 11 January 2008
This article is available from: http://www.ij-healthgeographics.com/content/7/1/1
© 2008 García-Pérez et al; licensee BioMed Central Ltd.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Background: The European Pollutant Emission Register in Spain (EPER-Spain) is a public inventory
of pollutant industries created by decision of the European Union. The location of these industries
is geocoded and the first published data correspond to 2001. Publication of these data will allow
for quantification of the effect of proximity to one or more such plant on cancer and all-cause
mortality observed in nearby towns. However, as errors have been detected in the geocoding of
many of the pollutant foci shown in the EPER, it was decided that a validation study should be
conducted into the accuracy of these co-ordinates. EPER-Spain geographic co-ordinates were
drawn from the European Environment Agency (EEA) server and the Spanish Ministry of the
Environment (MOE). The Farm Plot Geographic Information System (Sistema de Información
Geográfica de Parcelas Agrícolas) (SIGPAC) enables orthophotos (digitalized aerial images) of any
territorial point across Spain to be obtained. Through a search of co-ordinates in the SIGPAC, all
the industrial foci (except farms) were located. The quality criteria used to ascertain possible errors
in industrial location were high, medium and low quality, where industries were situated at a
distance of less than 500 metres, more than 500 metres but less than 1 kilometre, and more than
1 kilometre from their real locations, respectively.
Results: Insofar as initial registry quality was concerned, 84% of industrial complexes were
inaccurately positioned (low quality) according to EEA data versus 60% for Spanish MOE data. The
distribution of the distances between the original and corrected co-ordinates for each of the
industries on the registry revealed that the median error was 2.55 kilometres for Spain overall
(according to EEA data). The Autonomous Regions that displayed most errors in industrial
geocoding were Murcia, Canary Islands, Andalusia and Madrid. Correct co-ordinates were
successfully allocated to 100% of EPER-Spain industries.
Conclusion: Knowing the exact location of pollutant foci is vital to obtain reliable and valid
conclusions in any study where distance to the focus is a decisive factor, as in the case of the
consequences of industrial pollution on the health of neighbouring populations.
Page 1 of 11
(page number not for citation purposes)
International Journal of Health Geographics 2008, 7:1
http://www.ij-healthgeographics.com/content/7/1/1
Background
Results
The European Pollutant Emission Register in Spain
(EPER-Spain) [1] is a public inventory of Spanish companies coming within the scope of application of the Integrated Pollution Prevention and Control (IPPC) Act 16/
2002 [2]. It includes all industrial and livestock-sector
installations that have acknowledged exceeding the
reporting thresholds for one or more of the pollutants
listed in European Union Decision 2000/479/CE. The
first data published, corresponding to 2001, included
1,437 companies. An initial analysis of this information,
which includes a preliminary quantification of reported
pollutants released plus a comparison between Spanish
and European data, has recently been published [3].
Information was successfully obtained as to the exact location of EPER-Spain's 639 industrial facilities.
One of the novel features introduced by this registry is
that, in addition to furnishing data on pollutant emissions, it includes the geographic location of each facility,
providing both the postal address and its geographic coordinates.
This information can be extremely useful when studying
the possible effect of these industries on the health of
neighbouring populations (as shown by other studies [412]), since it serves to improve analyses that link geographic morbidity and mortality patterns to the presence
of pollutant foci. Yet, its utility depends, in part, on the
quality of the geocoding of such industries, i.e., on
whether the geographical location reflected in the registry
is in fact correct.
EPER-Spain industrial co-ordinates can be obtained from
two sources, namely, the European Environment Agency
(EEA) and the Spanish Ministry of the Environment
(MOE). This information was compared against the Farm
Plot Geographic Information System (Sistema de Información Geográfica de Parcelas Agrícolas) (SIGPAC).
Geocoding methods and data-validation processes in epidemiological studies have attracted a lot of attention in
recent years. The accuracy of these data could be a critical
point if increases in risk are identified in populations living close to pollutant facilities.
A preliminary analysis of the EPER-Spain highlighted the
existence of errors in the location of many facilities. To
assess the quality of this information, we decided to validate the geographic co-ordinates of all industrial-sector
companies included in the EPER-Spain (639 industrial
facilities). For the purpose, the information contained in
the SIGPAC was used and supplemented with other
locally available resources to geocode each industry anew,
with the aim of identifying incorrectly plotted facilities
and studying the degree of error between the real co-ordinates and those included in the official registries.
Figure 1 depicts three examples of industries whose situation was classified according to the quality criteria outlined above. In the first example, i.e., high quality, the
facility is shown in the centre of the orthophoto. The topographic map furnished by the SIGPAC (in which the
name of the industrial complex appears), as well as the
aerial photograph confirm that this is the industry sought.
The second example shows an industry with mediumquality geocoding. The last example is an instance of low
quality, in which the orthophoto obtained from the original co-ordinates shows no industrial plant.
Figure 2 shows the quality of the official geocoding of
industries by the two data sources used (the EEA and the
Spanish MOE). The graphs depict the percentage distribution of industries according to the defined quality criteria
and the absolute number of industries in each category for
each Autonomous Region and for Spain as a whole.
Only 7% of industries were accurately located (high quality), using information from the EEA, a percentage that
rose to 34% when we used data from the 2006 update furnished by the Spanish MOE. Overall, data sourced from
the Spanish web page were of better quality than the European data. Analysis by Autonomous Region highlighted
the fact that this difference was due to the effort made by
certain regional authorities, the bodies required to report
this information: specifically, in the Basque Country the
number of accurately situated industries rose from 11% to
96%. Further Autonomous Regions with relevant
improvements in their data were Andalusia, the Valencian
Region and Castile-La Mancha. In contrast, other regions
displayed very poor quality information in both sources,
with 100% of their industries inaccurately positioned
(e.g., Murcia, La Rioja and Extremadura).
Table 1 summarises the distribution of distances (in kilometres) between the original location of the industries
and their correct location, according to the co-ordinates
supplied by the two servers, for each Autonomous Region
and for Spain overall. The median distance between the
corrected location and the data furnished by the EEA was
2.55 kilometres for the whole of Spain, though there was
wide variability among the different Autonomous
Regions. While the Balearic Islands registered the smallest
difference between the two co-ordinates, with a median
distance of 0.57 kilometres, this measure was in excess of
6 kilometres in Murcia and the Canary Islands (6.48 and
6.17 kilometres respectively). Special mention should be
made of errors of note, such as the case of the industrial
plant owned by Desgasificación y limpieza de tanques S.A.,
Page 2 of 11
(page number not for citation purposes)
International Journal of Health Geographics 2008, 7:1
http://www.ij-healthgeographics.com/content/7/1/1
HIGH QUALITY
Thermal power station of Narcea. Barrio Soto de la Barca, Tineo (Asturias)
ORTHOPHOTO
AERIAL PHOTOGRAPH
TOPOGRAPHIC MAP
MEDIUM QUALITY
Sugar refinery of La Bañeza. La Bañeza (León)
ORTHOPHOTO
Original co-ordinates:
x = 260889.12 / y = 4687451.05
Corrected co-ordinates:
x = 260425.27 / y = 4687776.98
Distance between the original and
corrected co-ordinates: 567 m.
TOPOGRAPHIC MAP
LOW QUALITY
Fiberglass factory of Rockwool Peninsular. Caparroso (Navarra)
ORTHOPHOTO
Original co-ordinates:
x = 632827.2 / y = 4675807.68
Corrected co-ordinates:
x = 610640.35 / y = 4691719.49
Distance between the original and
corrected co-ordinates: 27.3 Km.
CORRECTED LOCATION
Figure 1 of industries broken down by different quality criteria to identify their geographical location
Examples
Examples of industries broken down by different quality criteria to identify their geographical location.
Page 3 of 11
(page number not for citation purposes)
International Journal of Health Geographics 2008, 7:1
20
40
60
80
20
ANDALUSIA (94)
1-High
(4)
ASTURIAS (26)
(35)
(23)
CANTABRIA (28)
CASTILE-LA MANCHA (45)
(20)
(3)
CATALONIA (129)
EXTREMADURA (5)
(104)
MURCIA (6)
(6)
NAVARRE (9)
60
80
40
60
80
20
40
60
80
SPAIN OVERALL (639)
VALENCIAN REGION (38)
(537)
(33)
(1)
20
(24)
(6)
20
40
60
80
7.04% high quality
(45)
(2)
20
40
60
84.04% low quality
8.92% medium quality
(57)
(3)
(2)
40
GALICIA (25)
(5)
(1)
1-High
20
80
(15)
(2)
(20)
(1)
2-Medium
60
(1)
(10)
MADRID (21)
(3)
40
(9)
(15)
(49)
(3)
(3)
LA RIOJA (3)
20
CANARY ISLANDS (10)
(11)
(3)
CASTILE & LEÓN (54)
80
(75)
(2)
(36)
(6)
60
BASQUE COUNTRY (101)
(1)
(1)
(5)
3-Low
BALEARIC ISLES (6)
(2)
(1)
3-Low
QUALITY CRITERIA
Source:
EUROPEAN
ENVIRONMENT
AGENCY
80
20
40
60
80
20
40
60
80
20
40
(3)
(2)
2-Medium
1-High
60
ARAGON (39)
(88)
3-Low
2-Medium
40
http://www.ij-healthgeographics.com/content/7/1/1
80
Source: SPANISH MINISTRY OF THE ENVIRONMENT
ANDALUSIA (94)
(28)
3-Low
2-Medium
ARAGON (39)
(62)
(1)
CASTILE-LA MANCHA (45)
(23)
(16)
(6)
(1)
NAVARRE (9)
VALENCIAN REGION (38)
(7)
(1)
(1)
40
60
80
20
40
60
80
20
40
60
80
20
(381)
(4)
60
80
20
40
60
59.62% low quality
6.10% medium quality
(39)
(21)
40
SPAIN OVERALL (639)
(13)
(1)
1-High
20
(22)
(2)
(15)
MURCIA (6)
(20)
GALICIA (25)
(5)
(10)
MADRID (21)
(3)
(97)
EXTREMADURA (5)
(104)
(5)
LA RIOJA (3)
2-Medium
(10)
CATALONIA (129)
(49)
(5)
(2)
3-Low
CANARY ISLANDS (10)
(4)
(1)
CASTILE & LEÓN (54)
(24)
(3)
BASQUE COUNTRY (101)
(4)
(1)
(2)
CANTABRIA (28)
3-Low
1-High
BALEARIC ISLES (6)
(25)
(3)
1-High
2-Medium
ASTURIAS (26)
(34)
(4)
(219)
34.27% high quality
80
% OF INDUSTRIES
Figure
Initial
quality
2
of EPER-Spain industry geocoding
Initial quality of EPER-Spain industry geocoding.
which was shown to be situated at a distance of 780.90
kilometres from its real location, possibly due to an error
in data entry.
In the case of data furnished by the Spanish MOE, the
median error decreased to 1.63 kilometres for Spain as a
whole, though there continued to be wide geographical
variability in the quality of the information. The Autonomous Regions with worst quality data were Murcia
(median error of 5.86 kilometres), Balearic Isles (median
error of 4.25 kilometres) and Asturias (median error of
4.11 kilometres). In contrast, there were Autonomous
Table 1: Percentiles of distribution of the distances between original and corrected EPER-Spain industry co-ordinates, shown by
Autonomous Region and for Spain overall (in km).
n
P 10
Source: European Environment Agency
P 25 P 50 (median) P 75 P 90 Maximum
SPAIN
639 0.72 1.45
ANDALUSIA
94 1.48 2.63
ARAGON
39 1.09 1.70
ASTURIAS
26 0.89 1.76
BALEARIC ISLES
6 0.24 0.39
BASQUE COUNTRY
101 0.48 1.00
CANARY ISLANDS
10 1.93 3.06
CANTABRIA
28 0.45 0.95
CASTILE-LA MANCHA
45 0.69 1.14
CASTILE & LEÓN
54 1.15 2.20
CATALONIA
129 0.35 1.14
EXTREMADURA
5 1.13 1.16
GALICIA
25 1.54 1.66
LA RIOJA
3 1.47 1.81
MADRID
21 1.65 2.81
MURCIA
6 3.44 4.11
NAVARRE
9 0.33 0.83
VALENCIAN REGION
38 0.91 1.59
2.55 4.71 7.51
4.34 6.69 9.28
3.43 5.52 7.00
3.91 5.77 10.43
0.57 0.89 3.33
1.63 2.59 3.86
6.17 11.24 38.49
1.73 2.35 3.25
2.72 3.72 6.40
3.31 4.85 6.90
2.17 3.63 6.96
1.63 4.34 8.67
2.79 5.57 8.31
2.38 2.64 2.79
4.76 6.22 16.65
6.48 7.42 10.97
2.29 3.66 4.92
2.52 3.53 5.60
P 10
Source: Spanish Ministry of the Environment
P 25 P 50 (median) P 75 P 90 Maximum
780.90 0.00 0.00
780.90 0.00 0.00
9.43 0.87 1.86
12.89 1.36 2.99
5.71 0.33 1.20
24.01 0.00 0.00
271.98 2.38 2.57
5.67 0.71 1.29
653.08 0.00 0.00
128.49 1.12 2.05
27.38 0.35 1.14
11.55 1.13 1.15
9.88 0.87 1.61
2.89 1.29 1.63
127.58 1.73 2.15
14.46 3.52 4.03
4.98 0.40 1.32
7.49 0.00 0.00
1.63 3.53 6.79
0.00 2.01 6.05
3.32 5.42 7.38
4.11 5.72 10.59
4.25 6.42 6.98
0.00 0.00 0.00
3.18 7.79 45.41
1.99 2.72 3.43
1.10 2.72 3.63
3.36 4.42 5.59
2.17 3.63 6.96
1.63 4.35 8.67
2.55 3.88 7.33
2.21 2.51 2.69
3.71 6.22 11.75
5.86 7.18 11.27
2.94 7.55 11.72
0.00 1.41 3.09
269.80
140.12
21.73
14.73
7.30
84.62
269.80
5.67
9.99
12.70
27.38
11.55
10.09
2.81
92.96
15.06
27.30
22.66
Page 4 of 11
(page number not for citation purposes)
International Journal of Health Geographics 2008, 7:1
http://www.ij-healthgeographics.com/content/7/1/1
Regions, such as the Basque Country, Andalusia and
Valencian Region, which registered a median error of 0
kilometres, thereby reinforcing the fact that quality of the
geographic co-ordinates of industrial facilities shown on
the Spanish MOE server is higher than that of the EEA
server, though both sources were far from achieving optimal geocoding of EPER-Spain industries.
4) Plants in extensive industrial areas being located at the
same point (centre of the zone), where poor geocoding of
this type can lead to errors amounting to kilometres, e.g.,
as in the case of industrial areas extending over several kilometres devoted to petroleum processing, where there are
mineral oil and gas refineries, chemical industries and cogeneration plants.
By way of illustration, Table 2 lists the statistics of the distribution of distances (in kilometres) by EPER industrial
activity and industrial activity group. The 'Waste management' group of industries registered the greatest errors in
both sources studied.
5) Industries belonging to the same industrial estate being
located at the same geographical point. Here, the errors,
albeit not quite as large as in the above case, can nevertheless amount to several hundreds of metres.
Discussion
This study reports the results of assessing the data quality
of the geographic co-ordinates for EPER-Spain industrial
complexes, obtainable from the official European and
Spanish web pages. Our results highlight both the poor
overall quality and the wide variability in quality in Spain.
Similarly, the data reflect the different attitudes adopted
by the regional authorities in this regard. Although there
has been an improvement in quality between the initial
and 2006-updated data, these changes are restricted to certain specific regions, and the Basque Country, Andalusia,
Valencian Region and Castile-La Mancha in particular.
The errors detected in the geographic co-ordinates of
industrial installations are attributable to one or more of
several reasons, namely:
1) Different industries situated in a single town being allocated the same geographic co-ordinates, e.g., as in the case
of municipal centroid reporting.
2) Industries having the same name as the parent company being sited at the same point, e.g., as in the case of
companies having a number of plants situated at different
sites.
3) Spain is divided into the following 4 Universal Transverse Mercator (UTM) areas (zones): 28 (Canary Islands);
29 (Galicia and Western Asturias, Castile & León, Extremadura and Andalusia); 30 (central Spain); and 31 (Catalonia, Balearic Isles, eastern Aragon and the Valencian
Region). There is an equivalence among the zones, and it
is likely that industries may have committed errors in calculations leading to their complexes being situated in
zone 30, which has been used as reference for the reporting of co-ordinates nationwide. Other reason for this
potential problem could be the use of a wrong projection
or not communicating the projection that has been used
by the facilities.
6) Geocoding of industries situated hundreds of kilometres away, in provinces or Autonomous Regions that do
not correspond to the correct location: this problem
would appear to stem from data-entry errors.
Although we have no evidence of the quality of the geographical data supplied by other EPER member countries,
the possibility cannot be rule out that these may display
similar problems to those of the EPER-Spain, given that
quality assurance is in all cases the responsibility of the
Member States and the industries subject to reporting. The
European Commission and the EEA only conduct a limited verification of certain quality aspects linked to the
completeness and coherence of reported data. In our case,
both the co-ordinates and the remaining mandatory data
(pollutant quantities released, address of complexes,
number of workers, hours of production and type of
industrial activity) are reported by the industries to the
Regional Environmental Authorities, and it would be
advisable if such data were submitted to quality control
before being sent to the EEA.
One of the aspects that may have influenced the initial
quality of EPER-Spain geographic co-ordinates stems
from the indications included in the EPER Directive as
regards the geocoding of facilities. The Guidance Document for EPER implementation proposes the address
(street name and number, and postal code) and the coordinates as mandatory fields for the geographic location
of the industrial complex. In addition, it proposes that,
"The co-ordinates should be expressed in longitude and
latitude co-ordinates (to be read from a topographic map
in degrees and minutes, giving a precision of the order of
one kilometre and referring to the geographical centre of
the site of the facility)" [13]. This marked precision of one
kilometre could be insufficient for positioning companies
correctly.
The EPER is soon to be replaced by the European Pollutant Release and Transfer Register (E-PRTR), which will
include more comprehensive information on industrial
pollution from 91 substances and 65 industrial activities,
Page 5 of 11
(page number not for citation purposes)
International Journal of Health Geographics 2008, 7:1
http://www.ij-healthgeographics.com/content/7/1/1
Table 2: Percentiles of distribution of the distances between the original and corrected EPER-Spain industry co-ordinates, shown by
industrial activity and industrial activity group (in kilometres).
TOTAL GROUP 1: ENERGY
INDUSTRIES
Combustion installations (> 300 MW)
Combustion installations (> 50 and <
300 MW)
Combustion in gas turbines
Combustion in stationary engines
Mineral oil and gas refineries
TOTAL GROUP 2:
PRODUCTION AND
PROCESSING OF METALS
Production of primary and secondary
metals or sintering installations
Characteristic processes in the
manufacture of metals and metal
product
Surface treatment of metals and
plastics
TOTAL GROUP 3: MINERAL
INDUSTRIES
Manufacture of plaster, asphalt,
concrete, cement, glass, fibres, bricks,
tiles or ceramic products
TOTAL GROUP 4: CHEMICAL
INDUSTRY
Manufacture of basic organic
chemicals
Manufacture of basic inorganic
chemical products or fertilisers
Manufacture of biocides and
explosives
Manufacture of pharmaceutical
products
TOTAL GROUP 5: WASTE
MANAGEMENT
Installations for incineration of
hazardous or municipal waste
Installations for physico-chemical and
biological treatment of waste
Installations for regeneration/recovery
of waste materials
Installations for the disposal of nonhazardous waste and landfills
TOTAL GROUP 6: OTHER
ACTIVITIES
Installations for the manufacture of
paper, pulp and paper products
Plants for the pre-treatment of fibres
or textiles
Slaughterhouses, installations for the
production of milk and other animal
or vegetable raw materials
Source: European Environment Agency
Source: Spanish Ministry of the Environment
n P10 P 25 P 50
P75
P 90 Maximum P10 P 25 P 50
P75
P 90 Maximum
69 0.71 1.69 3.74 5.71
7.93
271.98 0.00 0.17 2.06 4.16
6.83
269.80
27
18
1.61
1.36
4.54
2.07
5.72
3.48
7.88
5.17
12.55
9.20
27.00
271.98
0.28
0.00
2.48
1.92
5.27
2.63
5.71
4.81
10.09
11.02
27.00
269.80
10 1.45 1.89
4 0.29 0.53
10 1.59 2.11
117 0.50 1.05
3.99
0.91
4.19
2.10
4.54
1.29
6.98
3.64
6.04
1.53
7.56
5.81
8.73 0.00 0.15
1.70 0.10 0.26
8.12 0.00 0.00
24.01 0.00 0.00
2.17
0.51
0.48
0.67
2.87
0.93
2.72
2.64
3.70
1.39
7.54
4.61
7.30
1.69
8.12
84.62
17
1.02
1.69
2.87
4.93
6.89
12.89
0.00
1.18
3.01
4.31
5.01
14.73
50
0.36
0.90
1.62
3.76
6.37
24.01
0.00
0.00
0.00
1.40
3.50
22.61
50
0.77
1.21
2.29
3.13
5.55
13.38
0.00
0.00
1.05
2.62
5.32
84.62
141 0.79 1.39
2.72
3.86
6.28
653.08 0.00 0.00
1.44
2.95
5.02
139.22
141
1.39
2.72
3.86
6.28
653.08
0.00
1.44
2.95
5.02
139.22
115 0.77 1.58
2.70
4.73
7.21
14.46 0.00 0.00
2.11
3.55
6.88
15.06
0.79
0.00
61
0.77
1.56
2.45
4.69
7.00
14.46
0.00
0.90
2.21
4.08
7.14
15.06
34
1.56
2.47
3.68
5.65
8.00
9.43
0.00
0.00
1.61
3.53
6.12
10.28
5
1.27
1.45
1.58
1.85
3.27
4.21
0.00
0.00
1.45
2.48
3.52
4.21
15
0.29
0.98
2.08
3.55
3.72
11.81
0.00
0.47
2.15
3.41
3.59
11.68
60 1.39 2.49
4.56
7.76
11.73
780.90 0.00 0.94
3.16
6.90 11.84
27.38
2.98
4.11
8
1.63
2.28
5.40
10.56
18.82
2.27
2.51
6.74
8.44
11.75
6
1.44
3.69 10.09 16.00
22.01
27.38
1.44
3.70 10.03 14.02
20.73
27.38
7
1.52
1.62
2.53
5.47 316.79
780.90
0.00
0.00
1.01
1.42
1.71
1.88
39
1.70
3.35
5.25
7.81
9.27
13.71
0.00
0.48
3.36
6.91
8.98
12.94
137 0.67 1.39
2.12
4.53
6.58
128.49 0.00 0.00
1.48
3.55
6.78
140.12
40
0.69
1.14
1.73
4.76
8.31
128.49
0.00
0.00
1.18
3.58
9.99
140.12
15
0.78
1.61
2.23
2.63
8.64
26.12
0.00
0.00
0.00
1.68
2.66
9.93
51
0.55
1.21
1.98
4.63
6.33
16.12
0.00
0.58
1.68
3.95
5.81
15.03
Page 6 of 11
(page number not for citation purposes)
International Journal of Health Geographics 2008, 7:1
http://www.ij-healthgeographics.com/content/7/1/1
Table 2: Percentiles of distribution of the distances between the original and corrected EPER-Spain industry co-ordinates, shown by
industrial activity and industrial activity group (in kilometres). (Continued)
Application of paint in installations for
surface treatment or products using
organic solvents
Other activities (installations for
disposal or recycling of animal waste,
production of carbon or graphite,
printing industries, and degreasing for
surface treatment with solvents)
22
1.51
1.93
2.47
3.39
5.41
127.58
0.00
0.00
2.14
4.93
7.53
92.96
9
1.43
1.65
2.48
3.39
4.62
4.98
0.78
1.34
2.21
3.48
4.89
5.21
as well as information on waste management by industrial installations. It will also compile pollutionreports
from a range of sources, such as road and air transport,
shipping and agriculture. It should be noted that the
Guidance Document for the implementation of the European PRTR [14] proposes that, "The co-ordinates of the
location should be expressed in longitude and latitude coordinates giving a precision of the order of at least ± 500
metres and referring to the geographical centre of the site
of the facility". This will amount to an improvement in
precision with respect to the EPER and will very probably
have a positive impact on the geocoding of complexes in
forthcoming reports. Furthermore, this precision of 500
metres coincides with the high-quality criterion used in
our study to obtain orthophotos of industrial complexes.
One of the key factors in this study was the use of the SIGPAC for locating pollutant foci. This is a rigorous, reliable
and updated Geographic Information System (GIS) that
provides numerous details about the geography of Spain.
Attention should be drawn to the fact that the data
reported by industries correspond to 2001 and that the
dates of the flights which produced the SIGPAC orthophotos correspond to 2001–2002.
One limitation of the SIGPAC is the information furnished by its topographic maps. Although the names of
industries, industrial estates, roads, streets and buildings
appear, this information is not available for all industries
or for all towns. Almost all the major complexes (thermal
power stations, mineral oil and gas refineries, chemical
industries, cement industries, metallurgical industries and
automobile plants) are identified in the topographic
maps, as are a great many middle-sized industries (paper
mills, incinerators and chemical facilities). Yet, the names
of most of the small industries (slaughterhouses, tile
works, textile factories, small-sized metal production and
processing plants or landfills) do not appear. To compensate for this shortcoming and to check the accuracy of the
SIGPAC vis-à-vis the remaining complexes, we resorted to
other means for help (described under the Methods section).
The methodology envisaged in this study could be applied
to the validation of EPER-Spain companies engaged in the
livestock sector (farms, organic manure management),
though this step would be fairly laborious, due to the fact
that these are small facilities whose names are not shown
on the SIGPAC topographic maps in the majority of cases.
Methods or processes for geocoding co-ordinates and validating data in epidemiological studies have recently
attracted a considerable amount of attention. While some
studies have examined different methods of geocoding
address co-ordinates [15-23], others have assessed the
effect of positional error when automatic geocoding
methods are used [20,24-26] or different errors in the
geocoding process [27,28].
Studies on this topic have recently been published, evaluating the importance of correct geocoding in environmental studies [22,24]. In spatial-epidemiology studies,
allocation of geographic co-ordinates may lead to a given
area being subsequently classified in accordance with
other variables for which there is information at a geographic level (e.g., allocation of a specific socio-economic
level in accordance with the census section to which it
belongs). Accumulation of classification errors renders
assessment of the precision or coherence of the final result
difficult [22,24,29].
Figure 3 is an example of the way in which inaccurate
geocoding can negatively affect pollutant foci in a study
on the health consequences of industrially generated pollution for populations living in the environs of such facilities. The original situation corresponds to the data
furnished by the EEA for the town of Avilés, where 5
industries appear, whilst the second image corresponds to
the correct location. If one wished to study the effect produced by pollutant foci in a radius of 2 kilometres around
the centroid of Avilés, no industry would be included in
such a study, whereas in the original (i.e., the incorrect)
situation, 4 industries would be included. Taking a radius
of 3 kilometres around the municipal centroid, 2 industries would be included in the study, whereas in the original (i.e., the incorrect) situation, 4 pollutant foci would
be included. In this case, exposure would be overestimated if one were to choose the original EPER-Spain file
co-ordinates, since industries would be included that were
not really as close to the centroid as they appear to be.
Page 7 of 11
(page number not for citation purposes)
International Journal of Health Geographics 2008, 7:1
http://www.ij-healthgeographics.com/content/7/1/1
ORIGINAL SITUATION
AVILÉS (ASTURIAS)
2 Km
1 Km
1.2 Km
1 mineral industry
3 metallurgicalindustries
5.8 Km
3 Km
1 chemicalindustry
=Municipal centroid
=Original location of the industries
CORRECT SITUATION
AVILÉS (ASTURIAS)
Metallurgical
industry
2 Km
Mineral
industry
3 Km
2.2 Km
1 Km
Metallurgicalindustry
5 Km
5 Km
Chemicalindustry
3 Km
15.9 Km
=Correct location of the industries
GIJÓN (ASTURIAS)
Metallurgical
industry
Figure 3of poor geocoding applied to the town of Avilés (Asturias)
Example
Example of poor geocoding applied to the town of Avilés (Asturias).
Page 8 of 11
(page number not for citation purposes)
International Journal of Health Geographics 2008, 7:1
Lastly, it should be pointed out that one of the industries
which was originally situated in Avilés actually corresponds to Gijón, so that if the original co-ordinates were
chosen, one would be underestimating exposure to pollutant foci in the latter city.
Finally, we want to highlight some interest aspects derived
from this validation study:
1) Data entry problems, like the errors in the location or
geocoding of many facilities shown in the EPER-Spain
may cause large errors in subsequent studies that use these
data. The expenses of double entry protocols or validation
studies are justified by the observed data entry problems
and subsequent errors.
2) The local efforts of regional authorities and high standards of accuracy can lead to improve the quality of the
geocoding of the industries, as observed in some Autonomous Regions in Spain.
3) The common use of municipal centroids instead of the
exact co-ordinates by many of the facilities is inadequate.
http://www.ij-healthgeographics.com/content/7/1/1
EPER-Europe and EPER-Spain furnish geographic
WGS84-projection co-ordinates (longitude/latitude).
These co-ordinates were converted into UTM Zone 30
(ED50) co-ordinates (X, Y) and incorporated into a GIS.
Currently, there are different tools that enable any point
of Spanish territory to be accurately located. In a first
phase, the quality of registry data was evaluated using the
SIGPAC, a GIS belonging to the Spanish Ministry of Agriculture, Fisheries & Food. This system is designed to monitor Common Agricultural Policy (CAP) grants and
includes orthophotos of the entire surface of Spanish territory, along with topographic maps showing the names
of industries, industrial estates, roads, buildings and
streets [31]. An orthophoto is a photographic depiction of
an area of the Earth's terrestrial surface, on which all the
elements are shown error- and distortion-free on the same
scale, with the same validity as a cartographic plan. In
other words, it can be regarded as a photograph that displays the images of objects in their true orthographic position, and is geometrically equivalent to a plan [32].
Although an orthophoto is an image, its geometrical precision and radiometrical accuracy are of crucial importance [33].
Conclusion
Our results highlight the errors in the information furnished by the EPER, on its official web pages, both European and Spanish, though there has been an
improvement in quality between the initial data and those
updated in 2006. There is great variability within Spain,
with the Basque Country, Andalusia, Valencian Region
and Castile-La Mancha being the Autonomous Regions
that furnish the best-quality data. There are methods, the
SIGPAC in particular, which allow for all industries to be
accurately located.
The SIGPAC enables any point of Spanish geography to be
visualised, whether by searching directly (by region, province, town, industrial estate or plot) or by co-ordinates (by
UTM, X and Y co-ordinates, zone and radius of visualisation of the point sought).
Knowing the exact location of pollutant foci is vital to
obtain reliable and valid conclusions in any study where
distance to the focus is a decisive factor, as in case of the
consequences of industrial pollution on the health of
neighbouring populations.
1) high quality, where industrial facilities were really
located at a distance of less than 500 metres from the centre of the orthophoto (which corresponds with the original co-ordinates);
Methods
EPER-Spain industrial co-ordinates are obtainable from
two sources. In February 2004, the EEA, acting through
the EPER registry in Europe [30] published the co-ordinates of EPER-Spain industries, using 2001 data based on
information furnished by the respective Environmental
Authorities of Spain's Autonomous Regions. Subsequently, as a consequence of the application of Spanish
legislation [2], the Autonomous Regions sent updated
information on the industries to the Spanish MOE, which
in turn disseminated this via the EPER's Spanish-based
web page in 2006 [1].
The initial UTM co-ordinates of each of the industries
were fed into the SIGPAC and orthophotos were obtained
with various radiuses of visualisation. The original location was classified using the following quality criteria:
2) medium quality, where industrial facilities were shown
to be situated more than 500 metres but less than 1 kilometre from the centre of the orthophoto; and,
3) low quality, where industrial facilities were shown to
be situated at a distance of more than 1 kilometre from
the centre of the orthophoto.
Based on the orthophotos, and using the information
from the topographic maps, we plotted the exact location
of those industries whose co-ordinates were not correct
and corroborated the location of those whose initial coordinates were correct.
Page 9 of 11
(page number not for citation purposes)
International Journal of Health Geographics 2008, 7:1
Facilities whose SIGPAC situation was in doubt were
located using other means, such as the GoogleMaps server
[34] (which allows for a search of addresses and companies, and offers high-quality aerial photographs), yellow
pages web page [35] (which allows for a search of
addresses and companies), Internet aerial photographs,
and the web pages of the industries themselves (e.g., web
page of Spanish cement industries [36]) and various local
and regional institutions.
http://www.ij-healthgeographics.com/content/7/1/1
Luis Javier Viloria Raymundo, Cantabrian Regional Health Authority;
This study was funded by grant FIS 040041 from the Health Research Fund
(Fondo de Investigación Sanitaria);
The research group forms part of the MEDEA project (Mortalidad en áreas
pequeñas Españolas y Desigualdades socio-Económicas y Ambientales –
Mortality in small Spanish areas and socio-economic and environmental inequalities).
References
Industry percentages, broken down by the respective quality criteria, are shown for each Autonomous Region and
for Spain as a whole. For each of the industries studied,
the distance between the corrected and original European
and Spanish registry co-ordinates was also calculated and
a descriptive analysis of this information was performed
for each Autonomous Region, for Spain overall, and for
the different activities and industrial groups.
1.
2.
3.
4.
5.
Competing interests
The author(s) declare that they have no competing interests.
6.
Authors' contributions
7.
JGP and GLA conceived the idea and JGP wrote the manuscript. EB contributed to manuscript writing. EB, RR, EV,
NA, BPG, MP and GLA revised the manuscript for important intellectual content. All authors contributed to the
final version of the manuscript.
8.
9.
10.
Acknowledgements
Thanks must go to the following persons who collaborated in the search
for correct co-ordinates:
11.
Sergio Cuadrado, Ministry of the Environment;
12.
Koldo Cambra, Basque Regional Health Authority;
Federico Arribas, Aragon Regional Health & Consumer Affairs Authority;
Agustín Montes, University of Santiago de Compostela;
13.
14.
15.
Margarita Castro, Galician Regional Health Authority;
16.
Isabel Sevillano, Castile & León Regional Health Authority;
Valentín Rodríguez Suárez, Asturian Regional Health & Health Services
Authority;
17.
Marc Saez, University of Girona;
18.
Miguel Ruiz Ramos, Andalusian Statistics Institute;
Antonio Escolar Pujolar, Cadiz Cancer Registry;
Ana Gandarillas, Madrid Regional Health Authority;
Óscar Zurriaga, Valencian Regional Health Authority;
19.
20.
Registro Estatal de Emisiones y Fuentes Contaminantes
(EPER-España) 2008 [http://www.eper-es.es/].
Boletín Oficial del Estado : LEY 16/2002, de prevención y control
integrados de la contaminación (IPPC). 2002.
Garcia-Perez J, Boldo E, Ramis R, Pollan M, Perez-Gomez B, Aragones
N, Lopez-Abente G: Description of industrial pollution in
Spain. BMC Public Health 2007, 7:40.
Dahlgren J, Takhar H, Schecter A, Schmidt R, Horsak R, Paepke O,
Warshaw R, Lee A, Anderson-Mahoney P: Residential and biological exposure assessment of chemicals from a wood treatment plant. Chemosphere 2007, 67:S279-S285.
Downey L, Van Willigen M: Environmental stressors: the mental
health impacts of living near industrial activity. J Health Soc
Behav 2005, 46:289-305.
Hodgson S, Nieuwenhuijsen MJ, Colvile R, Jarup L: Assessment of
exposure to mercury from industrial emissions: comparing
"distance as a proxy" and dispersion modelling approaches.
Occup Environ Med 2007, 64:380-388.
Hurtig AK, San Sebastian M: Geographical differences in cancer
incidence in the Amazon basin of Ecuador in relation to residence near oil fields. Int J Epidemiol 2002, 31:1021-1027.
Hurtig AK, San Sebastian M: Incidence of childhood leukemia
and oil exploitation in the Amazon basin of Ecuador. Int J
Occup Environ Health 2004, 10:245-250.
Jo WK, Lee JW, Shin DC: Exposure to volatile organic compounds in residences adjacent to dyeing industrial complex.
Int Arch Occup Environ Health 2004, 77:113-120.
Johnson KC, Pan S, Fry R, Mao Y: Residential proximity to industrial plants and non-Hodgkin lymphoma. Epidemiology 2003,
14:687-693.
Mirabelli MC, Wing S: Proximity to pulp and paper mills and
wheezing symptoms among adolescents in North Carolina.
Environ Res 2006, 102:96-100.
Yang CY, Chang CC, Chuang HY, Ho CK, Wu TN, Chang PY:
Increased risk of preterm delivery among people living near
the three oil refineries in Taiwan. Environ Int 2004, 30:337-342.
European Commission Directorate General for Environment: Guidance Document for EPER Implementation. 2000.
Guidance Document for the implementation of the European PRTR 2006 [http://eper.ec.europa.eu/eper/documents/EN_EPRTR_fin.pdf].
Bonner MR, Han D, Nie J, Rogerson P, Vena JE, Freudenheim JL: Positional accuracy of geocoded addresses in epidemiologic
research. Epidemiology 2003, 14:408-412.
Gilboa SM, Mendola P, Olshan AF, Harness C, Loomis D, Langlois PH,
Savitz DA, Herring AH: Comparison of residential geocoding
methods in population-based study of air quality and birth
defects. Environ Res 2006, 101:256-262.
Krieger N, Waterman P, Lemieux K, Zierler S, Hogan JW: On the
wrong side of the tracts? Evaluating the accuracy of geocoding in public health research. Am J Public Health 2001,
91:1114-1116.
Lovasi GS, Weiss JC, Hoskins R, Whitsel EA, Rice K, Erickson CF,
Psaty BM: Comparing a single-stage geocoding method to a
multi-stage geocoding method: how much and where do
they disagree? Int J Health Geogr 2007, 6:12.
McElroy JA, Remington PL, Trentham-Dietz A, Robert SA, Newcomb
PA: Geocoding addresses from a large population-based
study: lessons learned. Epidemiology 2003, 14:399-407.
Ward MH, Nuckols JR, Giglierano J, Bonner MR, Wolter C, Airola M,
Mix W, Colt JS, Hartge P: Positional accuracy of two methods of
geocoding. Epidemiology 2005, 16:542-547.
Page 10 of 11
(page number not for citation purposes)
International Journal of Health Geographics 2008, 7:1
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
http://www.ij-healthgeographics.com/content/7/1/1
Whitsel EA, Rose KM, Wood JL, Henley AC, Liao D, Heiss G: Accuracy and repeatability of commercial geocoding. Am J Epidemiol 2004, 160:1023-1029.
Whitsel EA, Quibrera PM, Smith RL, Catellier DJ, Liao D, Henley AC,
Heiss G: Accuracy of commercial geocoding: assessment and
implications. Epidemiol Perspect Innov 2006, 3:8.
Yang DH, Bilaver LM, Hayes O, Goerge R: Improving geocoding
practices: evaluation of geocoding tools. J Med Syst 2004,
28:361-370.
Cayo MR, Talbot TO: Positional error in automated geocoding
of residential addresses. Int J Health Geogr 2003, 2:10.
Zandbergen PA: Influence of geocoding quality on environmental exposure assessment of children living near high traffic roads. BMC Public Health 2007, 7:37.
Zimmerman DL, Fang X, Mazumdar S, Rushton G: Modeling the
probability distribution of positional errors incurred by residential address geocoding. Int J Health Geogr 2007, 6:1.
Nuckols JR, Ward MH, Jarup L: Using geographic information
systems for exposure assessment in environmental epidemiology studies. Environ Health Perspect 2004, 112:1007-1015.
Oliver MN, Matthews KA, Siadaty M, Hauck FR, Pickle LW: Geographic bias related to geocoding in epidemiologic studies.
Int J Health Geogr 2005, 4:29.
Copeland KT, Checkoway H, McMichael AJ, Holbrook RH: Bias due
to misclassification in the estimation of relative risk. Am J Epidemiol 1977, 105:488-495.
European Pollutant Emission Register (EPER) 2008 [http://
eper.ec.europa.eu/eper/].
Ministerio de Agricultura Pesca y Alimentación: Sistema de Información Geográfica de Parcelas Agrícolas (SIGPAC). 2008
[http://www.mapa.es/es/sig/pags/sigpac/intro.htm].
Wolf PR: Elements of Photogrammetry with Air Photo Interpretation and
Remote Sensing New York: McGraw-Hill; 1983.
Hohle J: Experiences with the production of digital orthophotos.
Photogrammetric Engineering & Remote Sensing 1996,
62:1189-1190.
Google Maps España 2008 [http://maps.google.es/].
Páginas Amarillas España 2008 [http://www.paginasamarillas.es/].
IECA: Instituto Español del Cemento y sus Aplicaciones. 2008
[http://www.ieca.es/nquienes.php].
Publish with Bio Med Central and every
scientist can read your work free of charge
"BioMed Central will be the most significant development for
disseminating the results of biomedical researc h in our lifetime."
Sir Paul Nurse, Cancer Research UK
Your research papers will be:
available free of charge to the entire biomedical community
peer reviewed and published immediately upon acceptance
cited in PubMed and archived on PubMed Central
yours — you keep the copyright
BioMedcentral
Submit your manuscript here:
http://www.biomedcentral.com/info/publishing_adv.asp
Page 11 of 11
(page number not for citation purposes)