ZEMCH 2019 International Conference Proceedings April.2020 | Page 231
Standard deviation across emissions reductions across the UK were assessed, with domestic (3.2%)
and transport (6.0%) sectors demonstrating a relatively small variation in emissions reduction levels
between local authorities. This may be due to developments in both sectors which has influenced the
entirety of the UK emissions‐producing technology stock, such as advancements in modern vehicles
and increased efficiency of the electricity grid. Conversely, a value of 11.5% was observed in the
Industrial and Commercial sector, which suggests a higher level of variation in emissions reduction
across UK local authorities.
A rank‐order plot presenting the domestic emissions reductions achieved by each local authority
across the UK is presented in Figure 1. On average, per capita domestic emissions were reduced by
32.5% across all local authorities; a number of the most successful authorities were located in Greater
London, though substantial decreases in emissions across all authorities, as suggested by the mean and
standard deviation (Table 2).
Figure 1. Rank‐order plot of local for percentage domestic emissions reductions, ranked by per capita
emissions reductions achieved 2005‐2016
The regression analysis completed in Figure 2 shows the relationship between population density
and domestic emissions reduction per capita from 2005‐2016. As shown in the graph there is a
relationship between the two variables; high population density areas are found to be slightly more
successful in reducing domestic emissions than the less dense authorities. The coefficient of
determination (R 2 value) produced suggests that the model predicted 27% of the domestic emissions
reductions, however the p value (6.04E‐31) suggests a strong correlation between the two variables.
The anomaly shown is Kensington and Chelsea, which showed the lowest level of domestic
emissions reduction across the entirety of the UK. As one of the densest authorities in the UK, it is
somewhat surprising that it was the least successful across the country in reducing its domestic
emissions levels. There is a high level of unoccupied housing within the borough which may impact
the emission levels per capita; a large quantity of the most expensive housing in the borough is
identified as “second homes” for very affluent people who are therefore not likely to be considered at
the time the census data is collected [6]. According to 2016 statistics, 1.6% of houses are vacant in
Kensington and Chelsea, nearly double the national average of 0.9% [7].
Figure 3 highlights the domestic electricity emissions change from 2005‐2016 from across the UK,
with the orange line highlighting the reduction in emissions intensity of the grid. This is to say that 14%
emissions reductions were due to the changes in the grid intensity which would be influenced by
schemes such as feed in tariffs. The remaining difference across local authorities can be attributed to
other factors such as the retrofitting of housing, change of fuel use, improved efficiency of lighting etc.
Reducing GHGs from UK Households - An Examination of Local Authority-Level Data
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