1. Assessing the Environmental
Impact of Landfill sites in the
East Riding of Yorkshire
Gadogbe Mark
January 2014

2. INTRODUCTION
This project involved the identification of areas within the East Riding of Yorkshire County (ERYC)
with the highest sensitivity to any possible environmental impact from escape of landfill leachate
from landfill sites in the ERYC and the identification of specific landfill sites (three) that could pose
the highest risk in case of possible environmental pollution.
METHODOLOGY
The methodology applied involved a combination of GIS spatial analysis tools and multi criteria
evaluation. Figure 1 provides a schematic overview of the processing methodology and the essential
inputs and outputs. A study area was selected which comprise of eight (8) contiguous parishes out of
a total of 169 parishes stored in the parish dataset. This was done to limit the large amount of time
needed in carrying out the analysis for the entire East Riding (169 parishes). The study site (figure 2)
assessed for landfill impact comprise of the following selected parishes: Kilham, Carnaby, Burton
Agnes, Harpham, Barmston, Nafferton, Kelk and Driffield. Care was taken in the selection so as to
ensure landfill sites were located in all the eight parishes.
The first stage of the analysis involved setting the analysis extent to the parish layer and generating
raster grids for each of the seven criteria considered using the fuzzy classification approach of Multi
Criteria Evaluation modelling. The generated grids were for the following criteria: land-use type,
bedrock and surficial geology, elevation and slope, distance from residential areas, distance from
SSSIs, distance from coast, and distance from surface water.

3. ArcGIS spatial analyst tool, the raster calculator, was then used to add or overlay the contents of
each raster grid, applying appropriate weighting values for all the criteria to produce a grid (figure 3)
delineating areas with high and low sensitivity for environmental impact from landfill leachate in the
study area.
Four weight classes were defined and applied and depending on a criteria’s relative importance, it
was given a weighting of 1, 1.5, 2 or 2.5. For instance, the distance from residential areas criteria had
the highest weighting of 2.5 because it most directly affects the location of the landfill sites. It is
considered the most significant criteria because all other criteria been met, a landfill would most
likely still not be located if its choice location receives huge public disapproval such as locating in a
residential area or within a city.
Also, the criteria distance from SSSIs and distance from surface water were both given an equal
weighting of 2 because of the ecologically sensitive nature of these environments and as such the
huge impact even the smallest landfill leachate will produce in such environments. They were given
a lower weighting than the distance from residential areas criteria because it ranked slightly more
important than them based on discussions with local experts and literature review. The application of
the weights was to ensure that the various criteria are objectively ranked in order of significance to
the decision.

4. Figure 1: Flowchart showing the processing methodology
Set analysis mask
to parish layer;
processing extent
and raster analysis
cell size to
parishmask
Add selected study
sites to map as new
layer (studysites)
Merge and spatial
join ew053 to ew082
layers into one new
layer and convert to
raster (Geo_raster)
Raster Calculator: Ite_clas +
Slope_clas + Geo_clas ×1.5 +
Coast_clas ×1.5 + Water_clas
×2 + SSSI_clas ×2 +
Towns_clas ×2.5
ArcToolbox →
Spatial Analyst
Tools → Distance
→ Euclidean
Distance
Towns_dist layer
Reclassify
Coast_dist layer
SSSI_dist layer
Water_dist layer
Towns_clas layer
Coast_clas layer
SSSI_clas layer
Water_clas layer
Geo_clas layer
Ite_clas layer
3D Analyst Tools →
Raster Surface →
Slope
Slope_Humb layer
Reclassify
Slope_clas layer
Elev_clas layer
model_resultReclassify
Labelled
Sensitivity
map
Use select by
location tool to
select all landfill
sites in study area
and investigate
them
Select the three
landfill sites and
add to map as
new layer
(landfills) Labelled Landfills
location map

5. Figure 2: Location of the study site relative to other parishes in the ERYC.

6. DISCUSSION AND INTERPRETATION OF RESULTS
Because of their environmental health, economic and ecological impacts, landfills are a critical issue
in urban planning (Charnpratheep et al., 1997). As a result, it is common to find many
recommendations being proposed by many studies involving landfills.
According to Dikshit et al. (2000), they should be situated at a fair distance away from biophysical
elements such as water, wetlands, critical habitats, and wells to reduce the risk of contamination
from landfill. Landfills should be located away from the coastline (Despotakis and Economopoulos,
2007), at a significant distance away from urban residential areas due to public concerns, such as
aesthetics, odour, noise, decrease in property value and health concerns (Tagaris et al., 2003; Zeiss
and Lefsrud, 1995) and a slope less than 12% would be suitable for prevention of contaminant runoff
(Lin and Kao, 1999) are common recommendations.
For this project, the study area (comprising of the eight parishes) falls under the Bridlington District
and had 35 landfill sites located within. The dominating land uses in the study comprise of arable,
mown/grazed grass and suburban uses. There were very little wetlands. Not all the data sources were
used in carrying out the analysis. For instance, the roads, railway tracks and electricity transmission
datasets were not used. This is because the seven criteria used were considered more crucial in the
determination of landfill impact to the environment.
Supposing the project was about determining the best sites for locating the landfills, these datasets
would have been given very significant consideration. For instance, landfills are often sited close to
transportation networks in order to save cost on collection and transportation, but in assessing their
impact on the environment these criteria may become not too significant. Also, because woodlands
are generally less sensitive to landfill leachate impacts, the woodland dataset was also not used.

7. Thus, the important datasets employed in the analysis included both vector and raster datasets such
as the land-use/land-cover (Ite), bedrock and surficial geology (ew053 to ew082), surface water line
and area, sites of specific scientific interest (sssi_er), landfill, coastline (coast_EY) the DEM of East
Riding (Humb_dem25) and the parish datasets. A resolution of 25m (same as for the Humber DEM)
was deemed most favourable for setting the analysis extent and producing the output grids because
data analysis in terms of processing speed and storage would be very costly if a higher resolution is
used.
However, even the 25m resolution quite affected the system’s cost effectiveness in terms of it been
quite computationally demanding. The large amounts of data considered made the system expensive
on computer time and space as it slowed down the pace of analysis and made the system take a long
time to process and produce required outputs. Studies of this nature have often been regarded as
complex and tedious because of the many different factors or criteria considered (Allanach, 1992)
and the increasingly sophisticated spatial analysis and modeling required (Chang et al, 2008).
Results of the environmental impact sensitivity grid (Figure 3) showed that out of the 35 landfill
sites, eleven (11) fell within the zone of high sensitivity of environmental impact from landfill
leachate. These included the Driffield (Negas/Eastgate) C, Bells Mils (Driffield), Kilham (Green
Lane), Gransmoor Quarry Site A and B, Gransmoor (Kelk), Gransmoor Lodge, Thorneholme,
Carnaby, Carnaby (Moor Lane) and Blakedale Farm landfill sites. The results also showed that
almost the entire area of Kelk and Driffield and a high proportion of Carnaby areas could be possibly
impacted by landfill leachate. The parish with the least impact was Kilham parish.
After careful assessment of the physiochemical danger of landfill sites taking into consideration area,
volume, waste and landfill type, leachate escape history and presence of nearby boreholes, the

8. Carnaby (Moor Lane), Gransmoor Quarry Site A and the Thorneholme landfill sites were identified
as having the highest environmental pollution potential (Figure 4).
Of the three, the Carnaby (Moor Lane) landfill site is the biggest (covering 15.8Ha in area and
2300000m3
in volume), has 5 boreholes (3 Private and 2 Public) in close proximity and has
household and commercial waste component (97%). The Gransmoor Quarry Site A landfill is also
very big, with water sources in close proximity but unknown waste composition as well as whether
capped or not. These unknown statuses could make it a potential hazard as it could contain
potentially dangerous chemical wastes. The Gransmoor Quarry Site B landfill though the second
biggest in the high sensitivity zone and with unknown cap status was not identified as one with
highest pollution potential because it contains 100% inert wastes which by their nature are not
considered harmful in landfill operation sense.

9. Figure 3: Map showing areas with high and low sensitivity for environmental impact of
leachate from landfill sites in the studied area (boundaries in blue).

10. Figure 4: Map showing the location of the three landfills within the study site (blue
boundaries) with the highest potential of causing significant environmental pollution.

11. Figure 5: Location of the three landfill sites without the sensitivity zones.

12. CONCLUSIONS
The unavailability of crisp data and the large number of data considered in the analysis made the use
of binary or Boolean classification approach fairly a limitation for this project.
Thus, fuzzy classification approach to multi criteria evaluation was deemed the most appropriate
method of choice for generating grids for the criteria under consideration. It was also more suitable
because of its superior ability of dealing quantitatively with imprecision in expressing the
importance of each criterion. According to Hall et al, (1992), it is a better way to handle uncertainty
and complexity in the application of MCE.
Another limitation observed is the cut-off values employed in defining the final site selection into
suitable and unsuitable. This can affect the number of sites that fall under each category as defining a
value to high will be restrictive and produce very few possible sites and vice versa.
Nonetheless, the methodology employed is deemed a valid methodology because it produced a good
site sensitivity grid when compared with empirical datasets and also because it is a commonly used
method for researches or analysis of this nature, for instance, in the study by Higgs (2006) which
used multi-criteria techniques and GIS in siting of a waste facility. Sener et al. (2006) also integrated
GIS and multicriteria decision analysis to solve the landfill site selection problem and developed a
ranking of the potential landfill areas based on a variety of criteria.
The criteria considered and the corresponding datasets employed for this project are however
deemed fundamental and thus not exhaustive. For a detailed and more efficient assessment, and for a
better management of environmental impacts, many other criteria and datasets need to be given great
consideration in future analyses of this nature.

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