Sum of road, rail and inland waterway freight data from Eurostat Dataset selection EUROSTAT (Source 1) data has been used where it is available. Where Eurostat data is missing, the following procedure was used to determine how to fill the gap:
1. DG TREN (Source 2) data is used where available, unless: 2. Inserting the DG TREN data would lead to a large change that is unrealistic. In this case: 3. The trend of known values for EUROSTAT is compared to the trend of known values for DG TREN. If known values match closely, the DG TREN data is used. 4. If the known values do not match closely, it is assumed that there is a systematic difference between DG TREN and EUROSTAT data, and so DG TREN data is not used. 5. Instead, gapfilling procedures outlined below are used: Gapfilling procedures Where data is missing or different data sources have been used across the time series and this leads to large changes which are unrealistic, gap filling procedures have been employed to ensure a complete dataset and to improve the reliability of the trends found.
The approach used is in accordance with that used for greenhouse gas inventories under the EU MM Where appropriate extrapolation of data has been used. This can be divided into 2 types: 1. Linear trend extrapolation - this is used where there is a smooth trend in the time series i.e. No large annual variations. In general the linear trend extrapolation is based on the most recent 10-year-period; however, if only a limited number of years were available or a more consistent time series was available for specific years then these years were used for the linear trend extrapolation. 2. Use of previous year’s values were used in case of large annual variations (dips and jumps) because in this case the previous year value is considered to be as robust as any other value. If emission estimates are not available for years within the time series, linear trend interpolation is used
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Don't forget about your local shops.
New supermarkets in the area can reduce business for smaller shops. Pollution and congestion would be significantly less if consumers frequented their local shops, rather than travelling long distances to out-of-town shopping centres.
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