178
M. O. P. Ramacher et al.
This study investigates the contribution of the four major emission sources—
industry (13%), road traffic (57%), shipping (10%) and residential heating (7%)—on
PM 2.5 concentrations in the harbour city of Hamburg. Moreover, we will investigate
the impact of regional PM 2.5 concentrations, due to missing source attribution of
regional PM 2.5 in the existing Air Quality Plan of Hamburg. For this we use an
urban modelling system comprising meteorological, emission and chemical transport
model systems. Moreover, exposure of the population with regard to the overall air
quality and the emissions sources under investigation was calculated. Based on this
information, which is not available at this point, it is possible to identify sources and
contributions of air pollution for the total urban area instead of evaluating the air
quality situation with measurement stations.
28.2 Detailed Emission Inventories
Emission data are probably the most important input for chemistry transport model
(CTM) systems [12] and have been identified as major source of improvement during
previous model studies in local scale simulations for the city of Hamburg [14].
Therefore, detailed emission inventories for NO x , O 3 , CO, NMVOC, SO 2 , PM 10 and
PM 2.5 have been gathered and created from various data sources to capture the major
emission sources following SNAP (Selected Nomenclature for Air Pollution) of the
European Environmental Agency (EEA).
Spatially gridded annual emission totals with a grid resolution of 1 × 1 km
2 were
provided for this study by the German Federal Environmental Agency (Umweltbundesamt, UBA). The spatial distribution of the annual emission totals for the model
domain has been done at UBA using the ArcGIS based software GRETA (“Gridding Emission Tool for ArcGIS”), which can generate regionalized emission data
sets for all SNAP sectors for the complete area of the Federal Republic of Germany
[16]. Hourly area emissions with 1-km horizontal resolution for SNAP categories
02 (domestic heating), 03 (commercial combustion), 06 (solvent and other product
use), 08 (other mobile sources, not including shipping), and 10 (agriculture and farming) were derived from the UBA area emissions by temporal disaggregation using
monthly, weekly and hourly profiles.
The gridded ship emission inventory (SNAP8) for the port area of Hamburg, is
based on a bottom-up approach using activity data based on the Automatic Identification System (AIS) and activity based emission factors for NO x , SO 2 , CO, CO 2 ,
hydrocarbons (VOC), and PM [1, 6, 10]. The calculated emission totals were spatially
distributed on a 250 m × 250 m grid according to the ship routes inside the harbor
area and ship-specific temporally distributed over a year on hourly time resolution
according to the activity data.
The traffic emission inventory is based on 15,851 line source emissions of NO x ,
NO 2 , PM 10 and PM 2.5 of the Hamburg road network provided by the city of Hamburg
using a bottom-up approach with emission factors from HBEFA version 3.1 [17].
M. O. P. Ramacher et al.
This study investigates the contribution of the four major emission sources—
industry (13%), road traffic (57%), shipping (10%) and residential heating (7%)—on
PM 2.5 concentrations in the harbour city of Hamburg. Moreover, we will investigate
the impact of regional PM 2.5 concentrations, due to missing source attribution of
regional PM 2.5 in the existing Air Quality Plan of Hamburg. For this we use an
urban modelling system comprising meteorological, emission and chemical transport
model systems. Moreover, exposure of the population with regard to the overall air
quality and the emissions sources under investigation was calculated. Based on this
information, which is not available at this point, it is possible to identify sources and
contributions of air pollution for the total urban area instead of evaluating the air
quality situation with measurement stations.
28.2 Detailed Emission Inventories
Emission data are probably the most important input for chemistry transport model
(CTM) systems [12] and have been identified as major source of improvement during
previous model studies in local scale simulations for the city of Hamburg [14].
Therefore, detailed emission inventories for NO x , O 3 , CO, NMVOC, SO 2 , PM 10 and
PM 2.5 have been gathered and created from various data sources to capture the major
emission sources following SNAP (Selected Nomenclature for Air Pollution) of the
European Environmental Agency (EEA).
Spatially gridded annual emission totals with a grid resolution of 1 × 1 km
2 were
provided for this study by the German Federal Environmental Agency (Umweltbundesamt, UBA). The spatial distribution of the annual emission totals for the model
domain has been done at UBA using the ArcGIS based software GRETA (“Gridding Emission Tool for ArcGIS”), which can generate regionalized emission data
sets for all SNAP sectors for the complete area of the Federal Republic of Germany
[16]. Hourly area emissions with 1-km horizontal resolution for SNAP categories
02 (domestic heating), 03 (commercial combustion), 06 (solvent and other product
use), 08 (other mobile sources, not including shipping), and 10 (agriculture and farming) were derived from the UBA area emissions by temporal disaggregation using
monthly, weekly and hourly profiles.
The gridded ship emission inventory (SNAP8) for the port area of Hamburg, is
based on a bottom-up approach using activity data based on the Automatic Identification System (AIS) and activity based emission factors for NO x , SO 2 , CO, CO 2 ,
hydrocarbons (VOC), and PM [1, 6, 10]. The calculated emission totals were spatially
distributed on a 250 m × 250 m grid according to the ship routes inside the harbor
area and ship-specific temporally distributed over a year on hourly time resolution
according to the activity data.
The traffic emission inventory is based on 15,851 line source emissions of NO x ,
NO 2 , PM 10 and PM 2.5 of the Hamburg road network provided by the city of Hamburg
using a bottom-up approach with emission factors from HBEFA version 3.1 [17].