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Clearing the skies over Cairo, one policy at a time

???? ?????? ?? ???????. ???? ?????: ??? ??? ??? / ????? ?????? Air pollution in Cairo. Photo credit: Kim Eun Yeul/World Bank

Imagine counting every car, truck, and bus in your metropolis’ streets for several days over eight years. That is exactly what we did in Cairo, with a little help from a satellite. We fed this high-frequency data into a Machine Learning Algorithm to understand traffic patterns in the city. This vehicle data was linked to the air pollution data from ground monitoring stations to understand how changing traffic affects air pollution, and how traffic needs to be altered to improve air quality. We found that reducing cars by 1% leads to a corresponding Fine Particulate Matter (PM10) reduction of 0.27%. We applied impact evaluation methods to estimate the effect of several policies, most notably the opening of a metro line, and the slashing of fuel subsidies, and found that Metro Line 3 resulted in the reduction of PM10 by 3% and the first two waves of fuel subsidy removal reduced it by nearly 4%. These findings summarized in a recent report offer a way to make Egypt’s Vision for Clean Air a reality.

Note: The first graph shows the identified vehicles by the trained Machine Learning Algorithm. The second graph shows the vehicle density map that was produced from the collection of each counted vehicle.
Note: The first graph shows the identified vehicles by the trained Machine Learning Algorithm. The second graph shows the vehicle density map that was produced from the collection of each counted vehicle (the darker the blue, the lower the car density; the brighter the yellow, the higher the car density. Credit: Motor Vehicle Density and Air Pollution In Greater Cairo report.

As part of the Sustainability Development Strategy: Egypt 2030, the country committed to halving its fine particulate matter (PM10) air pollution by 2030. Significant improvements have been made towards that goal. In fact, Cairo’s PM10 concentration fell by about 25% over the past decade. Despite these improvements, the city’s pollution levels are still several times the WHO recommended concentrations and higher than national guidelines, and therefore it is important not to lose momentum and continue to build on what has been achieved so far.

Air pollution is a pressing issue because of its adverse impact on human health.  It has been found the world over, with fighting regularity, that high air pollution episodes trigger immediate health reactions, resulting in more patients flocking to hospitals. Egypt is much like the rest of the world in terms of this pollution-health nexus, as is becoming apparent in an epidemiological study we are working on with the government in Egypt. The study assesses to what degree more patients are admitted to chest hospitals because of pollution. Air pollution also has negative economic effects and affects the productivity and appeal of a city. Assessing the negative welfare effects of air pollution, we carried out a Cost of Environmental Degradation (COED) study. The COED estimated that the current cost of air pollution in Greater Cairo to Egypt’s economy is the equivalent of 1.35 percent of GDP per year (this counts only damages to health in Greater Cairo).

Knowing the detailed contributions of each source of pollution is a crucial first step.  In the case of Egypt, about a third of the anthropogenic components of PM10 come from transport, another third from waste burning (agriculture and municipal waste), and the remainder from a mix of agriculture, industry and energy (see Lowenthal, Gertler, and Labib, 2014). Egypt has made progress on addressing the burning of agricultural waste, for example by nudging farmers to change their behavior by buying back rice straw that was previously being burned.

Egypt has taken steps to reduce traffic emissions and recently passed legislation to force the retirement of old vehicles.  It also opened a third Metro line and slashed fuel prices subsidies. Understanding which policies worked to reduce air pollution is tremendously helpful in designing future policies. The Machine Learning Algorithms helped us to evaluate the most important interventions - the opening of Metro Line 3, and the removal of fuel subsidies. Once we had the impact of reduced cars on PM10, using concentration-response relationships from the epidemiology literature, we estimated that these two enacted policies contributed to the avoidance of hundreds of premature deaths each year. Read the paper for more details on how we came to this estimate of lives that were potentially saved by these policies.

By continuing to implement these kinds of policies, Egypt will also improve the lives and health of its citizens.

The funding of the cited reports was provided by the Pollution Management and Environmental Health Program (PMEH) and the Korean Green Growth Trust Fund (KGGTF).


Martin Heger

Senior Environmental Economist

Craig M. Meisner

Senior Environmental Economist in the Middle East & North Africa Region.

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