firm survey are both geo-located and were collected in the same geographical areas and at the same time, which then allows us to combine them together for the analysis.

More specifically, our sampling units are sub-counties. For a sense of scale, the average sub-county spans about 64 square miles and consists of about 5,000 households. A sample of 52 sub-counties was randomly extracted for our study, stratifying by population and by whether the sub-county is in the broader Kampala area (the capital city).<sup>14</sup> Notably, our sample includes several sub-counties within Kampala and within other major cities (such as Jinja, Iganga, Mbale and Fortportal) over these three regions. Our pollution measurement and survey activities took place within these sub-counties and are described in the next sub-sections.

# **4.2 Pollution Measurements**

We create a unique database of pollution measures with geo-coordinates and time stamps that we collected in Uganda in partnership with AirQo and the World Bank.<sup>15</sup>

**Stationary and mobile measurements.** Pollution measurements come from two distinct types of monitors, subsequently referred to as _stationary_ and _mobile_ monitors. The former were attached to a number of fixed locations (e.g., lamp posts) within our sampled sub-counties. The latter were attached to the front of motorcycle taxis (boda-bodas) circulating on the streets within our sampled areas.<sup>16</sup> Additional details on the technical details of monitors and processes used for data collection are summarized in Okure et al. (2021).

Our budget allowed us to place 33 separate stationary monitors in distinct sub-counties for a period of roughly 8 months, from January to August 2019, covering 24 out of the 25 districts in our sample. Within a district, stationary monitor locations were determined to reflect local pollution exposure.<sup>17</sup> Monitoring devices were installed between 2.5 and 4 meter high to ensure that captured pollution levels are reflective of population exposure. The stationary monitors were active 24 hours a day. The average number of PM2.5 measurements by monitor-day-hour is 41 (median 45), for a total of 3,179,575 measurements across all stationary monitors and days in the dataset.

In addition, we used 10 mobile monitors placed on motorcycle taxis for roughly 4 months, from February to May 2019. These mobile monitors were deployed in 32 of our 52 sampled sub-counties. The partner taxi drivers were instructed to keep the monitors on at all times and

> 14Appendix Figure A13 shows the final sample of sub-counties.

> 15AirQo was founded in 2015 at Makerere University and works to improve air quality data in Uganda using AI. AirQo develops and deploys low-cost air quality monitors across urban areas in Uganda. In 2019, it received a $1.3m grant from Google as one of the 20 winners of the Google AI Impact Challenge.

> 16Appendix Figure A14 reports pictures of a stationary and mobile monitor.

> 17Most major emission sources being close to the ground, they predominantly have localized effects on PM2.5 concentration. Stationary monitors were thus deployed within a maximum of 1-2 km from identified activities likely to affect local air quality.

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