RIVM report xxxxxx xxx
RIVM report xxxxxx xxx
RIVM report xxxxxx xxx
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page 98 of 142 <strong>RIVM</strong> <strong>report</strong> 773301 001 / NRP <strong>report</strong> 410200 051<br />
In this Appendix we focus on anthropogenic time profiles for seasonality (monthly variation). Table<br />
A.2.1 summarises the priority setting for compiling time profiles per source category in relation with<br />
their contribution to total emissions of specific compounds.<br />
In general climatic, cultural and economic influences contributing to non-uniformity of human activities<br />
are:<br />
ú space heating, influencing the demand on fuels in the residential and commercial sectors;<br />
ú space cooling, affecting the demand for electricity in the residential and commercial sectors;<br />
ú availability of hydropower, influencing the use of fossil fuels or electricity production;<br />
ú holiday periods, influencing both road traffic intensity and manufacturing activities;<br />
ú maintenance periods for large plants relating to favourable periods (e.g. due to holidays, demand<br />
drops, weather conditions), influencing the demand for fossil fuels and the activity level of<br />
industrial processes;<br />
ú seasonality of agricultural production, influencing the amount of national and international<br />
transport (predominantly road and shipping, respectively);<br />
ú car cooling, influencing emissions of CFCs and HFCs from mobile air conditioners.<br />
In the LOTOS approach (Veldt, 1992) time profiles on different time scales are based on reasonable,<br />
simplified assumptions for key sources (Table A.2.2). In Figure A.2.1 the weekly and seasonal variation<br />
of these profiles is presented graphically, showing the straightforward character of these datasets.<br />
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Category/sector Winter/Summer 1 Working/Weekend day Day-time/Night-time 1 Temp. dependent<br />
1 Power plants 1.1/0.9 1.06/0.85 1.1/0.9 no<br />
2 Area source combustion 1.04/0.96 1.08/0.8 1.24/0.76 no<br />
3 Small combustion sources 1.55/0.45 1/1 1.5/0.5 no<br />
4 Refineries 1/1 1/1 1/1 no<br />
5 Industrial processes 1/1 1/1 1/1 no<br />
6 Solvent use 1/1 1/1 1/1 no<br />
7-9 Traffic 1/1 1/1 1.8/0.2 yes<br />
10-12 Vegetation 1/1 1/1 1/1 yes<br />
1 Each of each length.<br />
As an example of a more detailed approach, in Figure A.2.2 time profiles are presented that have been<br />
defined and used in the USA for estimating quarterly emissions of NAPAP emission inventories.<br />
Obviously there is an enormous amount of data available on economic activities at the smallest scale<br />
(plant level, city, street, individual farmers). Within Europe, comprehensive effort has been made by the<br />
GENEMIS project (Generation of European Emission Data for Episodes), which is part of EUROTRAC,<br />
to produce time profiles at a very high spatial and temporal resolution (Heymann, M, 1992; 1994)(see<br />
Table A.2..3). This approach extended and generalised the LOTOS approach discussed above. The<br />
GENEMIS project showed that the availability of high temporal resolution indicator data is limited.<br />
Some examples of this project are summarised in the Section of temporal variation in the<br />
(0(3&25,1$,5(PLVVLRQ,QYHQWRU\+DQGERRN (EMEP-CORINAIR, 1999).