D E S C R I P T I O N O F W O R K - MEGAPOLI - Dmi

MEGAPOLI 212520
of state-of-the-art datasets (the MILAGRO campaign of 2006 and the MCMA-2003 campaign) and
the existing links to the MILAGRO team and the Mexico City studies. Specific activities will be
devoted to trans-continental transport of megacity pollutants (WP5: influence of Boston/New
York/Washington area emissions on Europe). The effects of all the megacities distributed
worldwide will be considered to quantify their overall effects on global air quality and climate
(WP5 and WP6).
B.1.3.3 Methodological descriptions for each WP
WP1: Emissions
Overview and Background
Emissions of air pollutants cause air quality degradation and result in climate change. Reducing
emissions is one of the most important options for abating these negative impacts. A proper
knowledge of emission sources and their location in time and space is a crucial component of being
able to modelling air quality and climate, predict their future change, and design feasible mitigation
scenarios. Recently improved “bottom-up” emission inventories of various pollutants such as
particulate matter (PM) and its carbonaceous components (black Carbon (BC) and Organic carbon
(OC)) are better underpinned than before, and are more detailed, including technology
differentiation. Some of these new emission inventories have been reduced down to nearly half of
previous inventories, which, however, results in lower predicted concentrations by the models that
are not supported by the observations at many locations. Major sources of uncertainty and error in
emissions datasets include the use of incorrect “real-world” emission factors, emission
measurement artefacts, missing or falsified information on activity data, and wrong assumptions
about the hygroscopic nature of aerosols. More accurate emission inventories of e.g. carbonaceous
aerosols (BC and OC) are prerequisite model inputs for quantification of the aerosol climate
forcing, which is the largest uncertainty in estimating total anthropogenic climate forcing. To
quantify and abate the adverse health impacts of air pollution, chemical speciation and source
identification of particulate matter is essential. Currently it is widely acknowledged that the
uncertainty in emission inventories is a key feature in the limitations of predictive modelling as well
as mitigating adverse impacts of the emissions.
Methodology and Advancement Beyond the State-of-the-Art
This WP will provide state-of-the-art regional and global emission inventories and high resolution
emission maps, which will be available for community use after the project completion, and which
are needed as model input for WPs 4, 5, 6 and 7. The emission inventories will be based on
activities speciated according to fuel use, fuel type and technology, which will allow quantification
and spatial allocation of emission reductions due to mitigation scenarios developed in WP8.
In order to advance beyond the current state-of-the-art in megacity emissions, improvements will be
made in relevant emission characteristics, especially the spatial allocation of sources, chemical
speciation of emissions, and resolution of the gridded emission maps. Special emphasis will be
placed on the consistent integration of higher resolution megacity data into the lower resolution
regional or global emission maps. To accomplish this, the work will be divided into seven tasks:
1) Global anthropogenic and natural emission inventories:
Global emission inventories will be needed to model the impact of MCs. We will use current state
of the art inventories for anthropogenic sources (e.g. the EDGAR information system, of which
TNO and MPI are co-developers; the database developed in the framework of EU-IP RETRO
(TNO); and the global carbonaceous aerosol inventory of Bond et al (2004)). The effort in this task
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