# **6.1 Linking emissions to health outcomes (DALYs)**

The simulations reported above give some sense of what happens to CO2 emissions and their cost. While there tends to be a relationship between CO2 and other pollution measures of relevance in a health or productivity context (such as PM10 and PM2.5), this is not mechanical. And it is these latter indicators that are used to make the link to health status.

At this point, we can retrieve some baseline data are from the World Bank Cairo Air Pollution study (2009). This estimates the total DALY (Disability Adjusted Life Years) due to pollution at 164,124. Dhont et al (2013) estimate the impact of a 20% increase in the price of fuel on the changes of DALY using data from Belgium. They find that a 20% increase in the price of fuel would be associated with a rough improvement of 1650 DALYs. If applied to the Egypt base estimate from WB (2009) this would correspond to a decrease in DALY of around 1 percentage point.

However, an important caveat is in order. The pollution particulates responsible for increased mortality/morbidity in Belgium are very much lower than in Cairo. For instance, PM10 and PM2.5 concentrations in Brussels are 26 and 18 milligrams per cubic meter – significantly lower than the PM10 and PM2.5 concentration in Cairo of 144 and 83 milligrams per cubic meter respectively. This suggests that the calculated 1% decrease in DALYs as a result of a price increase is a significant underestimate.

# **7. Modeling external effects in transport**

In this section, we now move to modeling external effects using a multi-year framework developed by the UN named _ForFITS_ .<sup>_6_</sup> This model has two objectives. The first is the estimation of emissions in transport for a given transport stock and its composition and intensity of use. The second is the evaluation of transport policies for, in particular, mitigating CO2 emissions. The model also permits simulation of fuel price changes on transport activity. In an extension, we link CO2 emissions to those for particulates – as measured by PM10 – and then in a further step link to the impact on mortality and morbidity using the measure of DALYs.

The model evaluates transport activity expressed in units such as passenger kilometers (pkm) and vehicle kilometers (vkm), stocks of vehicle types, energy use and CO2 emissions. A range of possible policy contexts can be introduced that include changes in international oil prices as well as the level and structure of domestic fuel taxes/subsidies. The model is essentially sectoral, as it covers both passenger and freight transport services across all transport modes and the focus is mainly on inland transport (especially road and rail). Each mode is further characterized in submodes (when relevant) and vehicle classes. Vehicle classes are further split to take into account different engine or powertrain technologies and vintages. Finally, powertrains are coupled with fuel blends that are consistent with the particular engine technology.

Although in extended form the model requires very detailed information that is not available in the Egyptian context, the core requires a minimum amount of data including information on the

> 6 An acronym: ‘For Future Inland Transport Systems’.

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