RIVM report xxxxxx xxx
RIVM report xxxxxx xxx
RIVM report xxxxxx xxx
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page 80 of 142 <strong>RIVM</strong> <strong>report</strong> 773301 001 / NRP <strong>report</strong> 410200 051<br />
Within the project, available information on time profiles of anthropogenic sources has been<br />
collected and listed, focussing on their monthly variation. Within GEIA, however, a full study of time<br />
profiles for all sources is in progress. The presented results of the NRP-MLK project feed into this<br />
larger study. In this section the temporal variation of anthropogenic sources is illustrated by a<br />
selection of graphs. In Appendix 2 you will find a more detailed summary of the available data.<br />
As a first approximation seasonal variation of anthropogenic emissions may be considered as an<br />
uniform distribution, as illustrated in Fig. 4.10 showing the limited monthly variation in global total<br />
fossil fuel consumption.<br />
1.60<br />
Global total profile per fuel type<br />
Difference w.r.t. uniform distribution<br />
1.40<br />
1.20<br />
1.00<br />
0.80<br />
0.60<br />
0.40<br />
0.20<br />
gas<br />
liquids<br />
solids<br />
total<br />
0.00<br />
JAN<br />
FEB<br />
MAR<br />
APR<br />
MAY<br />
JUN<br />
JUL<br />
AUG<br />
SEP<br />
OCT<br />
NOV<br />
DEC<br />
JAN<br />
FEB<br />
MAR<br />
APR<br />
MAY<br />
JUN<br />
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An clear exception to this rule is biomass burning (see Appendix 2), which is limited to the dry<br />
season (deforestation, savanna burning, field burning of agricultural waste). Other climatic, cultural<br />
and economic influence contributing to non-uniformity of human activities is:<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<br />
ú<br />
holiday periods, influencing both road traffic intensity and manufacturing activities<br />
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 />
However, regarding monthly indicator data for specific economic sectors at country level, data are<br />
not so easily available, in particular with global coverage. In general one can say that for OECD<br />
countries more statistics are available than for non-OECD countries.<br />
In the LOTOS approach (Veldt, 1992) time profiles are based on reasonable, simplified assumptions<br />
for key sources (Fig. 4.11).