XII. CREATION OF AMBIENT AIR POLLUTION MAPS

The Directive No. 2008/50/EC on ambient air quality and cleaner
air for Europe, implemented in the Czech legislation (i.a.
Decree No. 330/2012 Coll.), requires that air quality should be
assessed in all zones and agglomerations throughout the
territory of each member state. Further it requires that the
fixed measurements should be used as a primary source of
information for such assessment. The measured concentrations may
be supplemented by modelling techniques and by indicative
measurement, so that the resulting estimate provided adequate
information on the spatial distribution of the ambient air
pollutants concentrations. The requirement to use the fixed
measurements as the primary source of information refers in
particular to the areas, in which the pollutants concentrations
exceed the upper assessment threshold. In order to keep the
unified method of mapping this requirement is applied for the
whole territory of the CR.

Therefore, concentrations of ambient air pollutants measured at
individual measuring stations are the fundamental source of data
for the creation of maps. The number of measuring stations is
limited. In addition to the measured (primary) data the mapping
procedure uses also various supplementary (secondary) data
providing the complex information about the whole territory and
at the same time showing the regression relation with the
measured data. The main secondary source of information is
represented by the models of chemical transport and dispersion
of pollutants, based on the data from emission inventories and
on meteorological data. In the Czech Republic, mainly the
Eulerian chemical dispersion model CAMx is used supplemented
also by the Gaussian model SYMOS and European Eulerian model
EMEP. Furthermore, for individual pollutants
e.g. information on altitude or population density is used (see
the details in the Annex I). When combining the primary and
secondary data both the accuracy of the primary measured data
and the complete coverage of the whole territory with the
secondary data are utilised. The maps created regularly for the
yearbook are based on the linear regression model followed by
spatial interpolation of its residuals. As concerns
interpolation methods, kriging and IDW are applied (see the
details in the Annex I).

The character of urban and rural ambient air pollution is
different, urban air pollution is, due to the impact of
emissions, generally higher than air pollution in rural areas.
There is one exception, and namely air pollution caused by
ground-level ozone, for which the opposite is true. Urban and
rural maps
are therefore constructed separately, and the final map is
produced by merging the urban map and the rural map using the
grid of population density. For several pollutants (see the
Annex I) also the traffic layer is taken into consideration, in
addition to the urban and rural layers. This layer is merged
with the urban and rural background layers using the grid of
traffic emissions. For the construction of the rural map the
measured air pollution data from rural background stations are
used as primary data. In the case of the urban map air pollution
data from the urban and suburban background stations are used.
For the potential traffic layer data from traffic stations are
used. The mapping procedure uses the classification of
individual stations according to the ISKO database.

The maps are created in the geographic information systems
environment (GIS). The main source of data is the ISKO relation
database of the measured data on air pollution concentrations
and chemical composition of atmospheric precipitation. The maps
are constructed in spatial resolution 1x1 km, in Gauss-Krüger
projection. The detailed specification of mapping procedure for
individual pollutants is presented in the Annex I.

Since 1994 the DMÚ 200, DMR-2, DMÚ 25 and later ZABAGED digital
layers have been used to create the basic geographical and
thematic layers in standardised projection (conformal
Gauss-Krüger projection). In the recent years the latest layers
of administrative division are created on the basis of materials
provided by the CSO.

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*Mapping of rural and urban (and potential traffic) layers *

The maps of rural and urban background pollution (and the potential pollution caused by traffic) are produced separately, they are constructed by the combination of the primary (measured) data and the secondary (model and further supplementary) data, see Horálek et al. (2007). The method used in this process is the linear regression model followed by spatial interpolation of its residuals. This method enables the use of supplementary data for the whole mapped territory. In case there are no suitable supplementary data, simple interpolation of the measured data is used. The estimate is calculated according to the relation:

(1)

where

is the estimated value of the concentration in the point *s*_{0},

*X*_{i}(s)
are various supplementary parameters in the point *s*_{0} for
*i *= 1, 2, …*p*,

*c*, *a*_{1}, *a*_{2},… are
the parameters of the linear regression model,

h(*s*_{0})
is the spatial interpolated value of the residuals of the linear
regression model in the point *s*_{0},
calculated on the basis of the residuals in the points of
measurement.

The spatial interpolation is carried out using the inverse
distance weighting method (IDW) or using ordinary kriging
(specifications for individual pollutants – in the Annex I). The
IDW method is a simple deterministic method, where the weight of
individual measuring stations in the interpolation depends only
on their distance from the estimated point. Kriging, on the
contrary, is a more advanced geostatistic method taking into
account the structure of air pollution field. However, the
advantage of the IDW method consists in respecting the measured
values in the points of measuring stations. Kriging does not
generally respect the measured values. There exists a certain
solution, and namely the interpolation with the use of kriging,
followed by the application of IDW on its residuals in the
points of measurement.

Interpolation of residuals using IDW is calculated according to
the relation:

(2)

where

is the estimate of the field of residuals in the point *s*_{0},

*R*(s_{i})
is the residual of linear regression model in the point of
measurement *s*_{i},

*N *
is the number of surrounding stations used in interpolation,

*d*_{0i}
is the distance between points *s*_{0}
and *s*_{i},

b
is
the weight.

In ordinary kriging the interpolation of residuals is
calculated according to the relation:

při
(3)

where

l_{1},
…,l_{N}
are the weights estimated on the basis of fitted variogram (see
below),

*R*(*s*_{i})
is the residual of linear regression model in the point of
measurement *s*_{i}.

The variogram describes the dependence of the between-points
variability on the mutual distance of points, it is a measure of
a spatial correlation (see e.g. Cressie 1993). The variogram is
estimated by fitting spherical function in empirical variogram,
calculated according to the relation:

where

is the empirical variogram of the field of residuals,

*R*(*s*_{i}), *R*(*s*_{j}) are
the residuals in the points of measurement *s*_{i} and
*s*_{j},

*d*_{ij}
is the distance of points *s*_{i}
and *s*_{j},

*n*
is the number of station couples *s*_{i} and *s*_{j},
with their mutual distance *h*±d,

d is
the tolerance.

Spherical function and variogram parameters range, nugget and
sill are illustrated in
Fig. XII.1.

The calculated urban and rural (and potential traffic) layers
are subsequently merged.

#####

*The merging of urban and rural (and potential traffic) layers
*

For the merging of the urban and rural layers the layer of
population density is used, see e.g. Horálek et al. (2007), De
Smet et al. (2011). The merging is carried out according to the
relation:

for

for
(5)

for

where

is the result estimate of the concentration in the point *s*_{0},

is
the concentration in the point *s*_{0 }for the rural or
urban map,

a(*s*_{0})
is the population density in the point *s*_{0},

a_{1},
a_{2}
are classification intervals of the respective population
density (see the Annex I).

The whole conception of separate mapping of ambient air
pollution in rural and urban areas is based on the assumption
that
for all common pollutants with the exception of ozone, or
or ozone. For the areas where this assumption is not
fulfilled the layer created similarly as the urban and rural
layers is used, nevertheless it is created on the basis of all
background stations, without making the difference between the
urban and the rural ones.

If also air pollution caused by traffic is mapped for the given
pollutant, the traffic layer is added to the background (merged
urban and rural) layer using the grid of traffic emissions:

for

for
(6)

for

where

is the result estimate of the concentration in the point *s*_{0},

is the concentration in the point *s*_{0} for the
background layer,

is the concentration in the point *s*_{0} for the traffic
layer,

t(*s*_{0})
are traffic emissions in the point *s*_{0},

t_{1},
t_{2}

are the classification intervals of the respective traffic emissions (see the Annex I).

The above function is based on the assumption that for common pollutants with the exception of ozone, or for ozone. For the areas where this assumption is not fulfilled the background layera is used.

Fig. XII.1 Diagram showing the variogram parameters and the fitted spherical functions in 2013