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.
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.
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).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
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.
paper for more details on how we came to this estimate of lives that were potentially saved by these policies.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
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).