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Indicator 21: Specific emissions
Figure 6.5: Specific NOx emissions
by mode (Austria)
Source: Federal Ministry for the Environment, Youth
and Family (Austria, 1997)
Objective
Reduce
emissions per transport unit (passenger-km or tonne-km).
Definition
Emissions of air pollutants per transport
unit, distinguishing between type (freight or passenger), mode and vehicle category.
Policy and targets
Air pollution is one of the main environmental consequences of transport use and reducing specific emissions (emissions per transport unit) is an important aim of air pollution abatement policies. The policy framework for this indicator is described in Indicator 2. The principal elements are:
Findings
Since no EU-wide data is available, this assessment is based mainly on data from Austria and the Netherlands. Although this data probably indicates general trends, caution is needed when extrapolating the findings to other countries. Specific emissions depend on factors such as the composition of the car fleet and the level of maintenance, which vary significantly between countries. In particular, Austria and the Netherlands have the highest penetration of catalytic converters.
The Austrian data (Figure 6.6) shows a dramatic reduction in NOx, NMVOC and particulate matter emissions per passenger-km for air and heavy rail during 1950-1980. The reduction for heavy rail emissions is due mainly to electrification and the use of hydropower. Specific emissions from passenger cars fell significantly (60 %) during the 1990s, mainly as a result of the introduction of catalytic converters. Specific emissions of NMVOC from motorcycles (2-wheelers) on the other hand, increased markedly during the 1960s and fell again only in the early 1990s. Motorcycles still have very high specific emissions.
Figure 6.6: Air
emissions per passenger-kilometre and per tonne-kilometre by mode (Austria,
1950-1996)
Source:
Federal Ministry for the Environment, Youth and Family (Austria, 1997)
A similar pattern is seen in the Netherlands for 1980-1997 (Figure 6.7). The reductions resulted from ever-stricter emission regulations (particularly for diesel vehicles), improvements in fuel efficiency and fuel quality and, most importantly, the mandatory use of catalytic converters on new petrol cars.
Figure 6.7: Air emissions per vehicle-kilometre
- road vehicles (the Netherlands, 1980-1997)
Source: Dutch National Institute of Public Health
and the Environment (Bilthoven, 1998)
Future work
Box 6.3: Environmental balance of transport in Austria An example of an indicator report where life-cycle analysis has (to a certain extent) been applied is the environmental balance of transport in Austria. In this analysis the major environmental impacts are related to the operation process as well as to the production of fuel process. The indirect environmental impacts caused by the maintenance and the production of vehicles, and the construction and operation of infrastructure (e.g. road lighting), usually constitute less than 20 % of the total environmental impact of transport. Figure 6.8: Emissions of NOx per passenger-km and
for the various process steps (Austria, 1995) |
Box 6.4: Transport and Environment Database System (TRENDS) Eurostat and DG Transport are jointly developing a database system (TRENDS) that links transport and other data with methodologies for estimating emissions and other environmental pressures. An important aim is to produce a consistent set of estimates to be used for EU policy purposes including TERM. Both absolute and specific emissions will be calculated. TRENDS will enable the effects of specific policy measures on emissions and other environmental pressures to be monitored. By linking calculated emissions to transport statistics it will be possible to estimate emissions from different types of transport, e.g. vehicle type, passenger/goods, national/international/transit, inter-regional flows, origin/destination, type of goods and mode. It will also be possible to estimate emissions per vehicle-km, passenger-km or tonne-km, enabling comparisons between environmental efficiencies in different places and over time. Forecasts are currently based on projections of past trends, combined with prediction of social and technological developments. By bringing estimates for all modes into a single system, it will be possible to calculate the effects of modal changes on overall emissions, such as shifting a given tonnage of freight from roads to water. Policy-makers will be able to identify the most environmentally damaging components of the transport system and compare the probable outcomes of different policies. TRENDS is now being developed as a tool to assist in producing many of the TERM indicators. The figure below provides some preliminary results showing typical emissions of NOx per passenger-km. A range of values is provided for each means of transport, based on operating conditions and occupancy rates. Member States also prepare detailed estimates and projections of transport emissions for policy making, monitoring and evaluating the effect of policies and measures, and reporting according to international emission-reduction obligations. These estimates need to be improved, and comparison with TRENDS estimates could help to identify and remove gaps and inconsistencies. Member States are increasingly using COPERT3, a software tool developed and distributed by the EEA in 1999, to estimate emissions from road transport. COPERT3 uses methodologies developed by the MEET project (Methodologies for estimating emissions from transport), an international collaboration targeted particularly on newer types of vehicle, non-road transport, and future emissions, which was finalised in 1999. TRENDS also uses MEET, and COPERT3 and TRENDS are therefore fully compatible. The results of the comparisons should be communicated to Member States to improve the consistency, transparency, comparability and reliability of national and also of TRENDS estimates. Figure 6.9: Estimated NOx emissions per passenger-km |
Data |
||||||||
Road (passenger car) |
Road (bus) |
Rail |
Air |
|||||
Year |
NMVOC |
NOx |
NMVOC |
NOx |
NMVOC |
NOx |
NMVOC |
NOx |
1970 |
1.87 |
1.16 |
0.134 |
0.271 |
0.152 |
0.389 |
0.810 |
1.582 |
1975 |
1.69 |
1.20 |
0.126 |
0.298 |
0.058 |
0.220 |
0.388 |
1.120 |
1980 |
1.57 |
1.32 |
0.120 |
0.310 |
0.025 |
0.135 |
0.235 |
1.044 |
1985 |
1.35 |
1.33 |
0.107 |
0.323 |
0.022 |
0.133 |
0.138 |
0.939 |
1990 |
0.79 |
0.87 |
0.090 |
0.333 |
0.015 |
0.101 |
0.073 |
0.739 |
1991 |
0.72 |
0.79 |
0.083 |
0.339 |
0.015 |
0.102 |
0.081 |
0.891 |
1992 |
0.63 |
0.69 |
0.078 |
0.339 |
0.015 |
0.102 |
0.068 |
0.755 |
1993 |
0.56 |
0.63 |
0.073 |
0.338 |
0.014 |
0.100 |
0.065 |
0.727 |
1994 |
0.49 |
0.57 |
0.068 |
0.331 |
0.013 |
0.094 |
0.063 |
0.706 |
1995 |
0.44 |
0.53 |
0.063 |
0.323 |
0.012 |
0.084 |
0.060 |
0.675 |
1996 |
0.39 |
0.49 |
0.059 |
0.313 |
0.011 |
0.075 |
0.060 |
0.675 |
Source: Federal Ministry for the Environment, Youth and Family (Austria, 1997) |
Emission efficiency of freight transport in Austria Unit: gram NOx NMVOC/ tonne-km |
Road (HDV) |
Rail |
Inland waterways |
Air |
||||||
Year |
NMVOC |
NOx |
NMVOC |
NOx |
NMVOC |
NOx |
NMVOC |
NOx |
|
1970 |
1.03 |
17.40 |
0.136 |
0.348 |
0.039 |
0.286 |
5.24 |
10.23 |
|
1975 |
0.87 |
17.18 |
0.051 |
0.197 |
0.036 |
0.286 |
2.51 |
7.24 |
|
1980 |
0.78 |
17.32 |
0.022 |
0.121 |
0.033 |
0.286 |
1.52 |
6.75 |
|
1985 |
0.65 |
15.17 |
0.020 |
0.119 |
0.031 |
0.287 |
0.89 |
6.07 |
|
1990 |
0.48 |
11.80 |
0.014 |
0.091 |
0.029 |
0.288 |
0.47 |
4.78 |
|
1991 |
0.42 |
11.22 |
0.013 |
0.091 |
0.028 |
0.289 |
0.52 |
5.76 |
|
1992 |
0.38 |
10.44 |
0.013 |
0.091 |
0.027 |
0.283 |
0.44 |
4.88 |
|
1993 |
0.36 |
9.92 |
0.013 |
0.090 |
0.027 |
0.279 |
0.42 |
4.70 |
|
1994 |
0.32 |
9.41 |
0.012 |
0.084 |
0.026 |
0.274 |
0.41 |
4.57 |
|
1995 |
0.30 |
8.98 |
0.011 |
0.075 |
0.025 |
0.269 |
0.39 |
4.37 |
|
1996 |
0.27 |
8.68 |
0.009 |
0.067 |
0.025 |
0.264 |
0.39 |
4.36 |
|
Source: Federal Ministry for the Environment, Youth and Family (Austria, 1997) |
For references, please go to https://www.eea.europa.eu/publications/ENVISSUENo12/page028.html or scan the QR code.
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