• To develop activity-emission factor matrices as tool for developing emission scenarios for Europe including all European cities.
• To develop activity-emission factor matrices for the participating cities in ICARUS as tools for developing urban emission scenarios.
• To generate life cycle emission factors and integration of the factors into the activity-emission matrices.
In this WP, tools for generating emission scenarios will be developed. The tools generate emissions for the whole of Europe (task 2.1), for the participating cities (task 2.2) taking into account life cycle emissions (task 2.3). Emissions are generated here for a business as usual scenario, the tool will then be used in WP 5 to estimate the changes in emissions, if policies are implemented (policy scenarios). The reference case is defined as the development of activities and emission factors for future years, where the currently implemented policies for emission reduction and already decided policies to be used in the future are implemented, whereas no further policies are used.
Task 2.1: Generation of future activity-emission factor matrices for the whole of Europe
In order to simulate the effect of policies on emissions an activity-emission factor matrix will be generated. This matrix contains for each emission source category activities, that cause emissions t (e.g. km of a Euro 6 diesel passenger car driven in urban areas) and the emission factors for all air pollutants and greenhouse gases related to this activity. Thus changes in activities will automatically result in consistent changes of greenhouse gas and air pollutant emissions. Emission factors include factors for greenhouse gas emissions (CO2, CH4, N2O) and for air pollutants including PM10, PM2.5, NMVOC, CO, SO2, NOX, NH3, organic carbon (OC), black carbon (BC), selected heavy metals, PAHs/benzo(a)pyrene (BaP), dioxins and furans. Emissions will be then estimated by multiplying activities and emission factors. The effect of technical measures that change emission factors, and non-technical measures that change activities, can thus be simulated. The data in the established activity-emission factor matrices represent the business-as-usual scenario for a recent year (e.g. 2015) and the years 2020 and 2030. Policy scenarios will be created in WP 5.1 by developing operators that – when applied to the matrices – change emission factors and activities to reflect the effect of the policies analyzed.
Starting with the scenarios of future activities and emission factors that have been generated for the clean air policy package of the EU, these data bases will be improved by (a) adding newly decided and implemented policies and (b) adding further emission factors (e.g. for dioxins, PAHs (benzo(a)pyrene), BC, heavy metals). The annual country specific data will then be further spatially disaggregated using methods developed by USTUTT in many projects, e.g. for DG Env to spatially disaggregate E-PRTR data .
The spatial disaggregation will be carried out in 2 steps:
a) Activity emission factor matrices will be estimated for all 892 cities/densely populated zones with more than 50,000 inhabitants in Europe so that analyses for urban policies implemented in all cities above a certain number of inhabitants become possible. The method was first developed in TRANSPHORM and will be here refined. The cities/built areas will be identified using CORINE land cover maps and population maps. The distribution of emissions will be mainly made using proxy data/statistical data such as number of inhabitants or population density, area and more. This allows to simulate policies, that can only be implemented in cities of different size classes and to analyse the effect in these cities.
b) Both urban and rural emissions will be further disaggregated into emissions per grid cell for an European wide grid, so that they can serve directly as input for the atmospheric dispersion models used. Basically a combination of land use data, statistical data, results of traffic counts and traffic models will be used. It follows a further temporal disaggregation from annual to 8760 hourly values (as required by the atmospheric models) by using available data that are related to the temporal course of the emissions.
The final result will be integrated urban and regional emission inventories for a recent year (e.g. 2015) and baseline emissions scenario for years 2020 and 2030. Model-ready gridded sector-specific emissions at a high spatial resolution will be derived for the pollutants and GHs considered. For CO2, a separation between anthropogenic and biogenic origin will be made to support CFP calculations. These emission inventories will be used as input for the atmospheric pollution models applied in WP3.
Task 2.2: Generation of future activity-emission factor matrices for the participating cities
In this task activity-emission factor matrices for the participating cities will be prepared for a recent year (e.g. 2015) and the future years 2020 and 2030. ‘Bottom-up’ emission data will be generated here. Thus, they will be more accurate than the emissions estimated for the same cities with a top down approach as in Task 2.1. Thus, the results can be used to validate the top-down method used in Task 2.1. The steps necessary to achieve the generation of the matrices will vary depending on the available information. All cities have already emission inventories and most have some emission scenarios that are used as a basis; however unlike for the European case (see task 2.1) no activity – activity matrices are available. Thus a ‘backward calculation’ will be applied by adjusting available emission data and available activity data in such a way that consistent activity – emission factor matrices will be generated. Working with projects such as ECOMOV.E and ICT-EMISSIONS emission factors for road traffic performance under new ICT / ITS scenarios for the future in smart cities will be quantified and impact scenarios developed by science partners and stakeholders (car manufactures, oil companies). Other major sectors such as residential combustion, agriculture will be also taken into account.
This task will provide the ICARUS participating cities with an easy to use tool to make estimates of the effect of environmental policies they plan. As far as scenarios for future years do not exist, the development of emission factors and activities derived for all cities in the respective country are used.
Task 2.3: Life cycle emissions and carbon footprint estimation
In order to estimate the change in the carbon footprint, air pollutant emissions and health impacts when implementing a measure, we have to include the emissions of relevant up- and downstream processes. This becomes all the more important when considering non-technical measures which affect behavioural and consumer choice patterns or institutional change. A three-step process will be followed to estimate life cycle emissions and carbon footprint modulation from policy measures at the urban scale:
(a) We will analyse the measures determined in WP 5 in order to identify those activities and processes that cause significant changes in life cycle emissions.
(b) For the respective activities, life cycle emission data will be collected and added to the activity-emission factor matrices developed in tasks 2.1 and 2.2 using the SimaPro 7.0 up-to-date databases and results of the NEEDS project.
(c) With the up-to-date data compiled in SimaPro (the industry standard in life cycle assessment) an automated system will be created allowing for updating life cycle inventories consistently with changes in direct urban-level emissions. This tool will be readily usable in all cities participating in ICARUS in order for its applicability and robustness to be tested so that it can be offered as useful tool for sustainable city authorities across the EU.
|Deliverable Number||Deliverable Title||Lead beneficiary||Type||Dissemination level||Due Date (in months)|
|D2.1||Report and data on
at EU-wide level
for the considered
pollutants and GHs
for the years 2015,
2020 and 2030
|2 – USTUTT||Report||Public||12|
|D2.2||Report and data on
at city level for
pollutants and GHs
for the years 2015,
2020 and 2030
|2 – USTUTT||Report||Public||15|
emission based on
life cycle analysis
and software tool
updating of the
|2 – USTUTT||Report||Public||18|