daily average across hours as well as the maximum hourly value of the day as outcomes. We use data from 2020 and 2023, and we include controls for weather variables and indicator variables for day of the week and month of the year. We also study a longer time period, allowing us to better control for seasonality and overall high variance in the outcome variable. We use the satellite data and the data from regulatory-grade monitors for 2017-2020 and use the Purple Air data for 2020, 2022 and 2023.<sup>18</sup> We include results for these analyses using the longer time period at both the hourly and daily levels. For these robustness checks, we analyze both the unadjusted low-cost monitor data and the locally calibrated data, using the hourly calibration values for regressions at the hourly level and the daily calibration values for regressions at the daily level.

# **5 Results**

## **5.1 Comparison of PM2.5 Levels**

First, we compare the PM2.5 estimates generated using satellite data from MERRA-2 with the data from the regulatory-grade monitors. Figure 4 demonstrates that there is a strong alignment of values at the monthly level (Figure 4A), weekly level (Figure 4B), and daily level (Figures 4C and 4D), and that aggregating the data temporally improves alignment. The satellite data is able to capture the peaks in pollution that occur in the first two months of each calendar year (January - February), but the satellite measures also record increases in pollution in May-June for 2013-2015 that are not reflected in the data from the regulatory-grade monitors (Figure 4A). Particularly in 2019-2020, the PM2.5 estimates from the satellite data at the monthly-level are very closely aligned with the PM2.5 data from the regulatory-grade monitors (Panel 4A). This reflects the fact that in 2019-2020, the regulatory data comes primarily from a new monitor installed in 2018 in Guediawaye, which measures much higher levels of PM2.5 compared to the other regulatory monitors in the city, and thus aligns more closely with the higher estimates of pollution generated with the satellite data.<sup>19</sup> When aggregated to the weekly level, the two data sources still track each other closely for 2019-2020 but there is greater disparity in the levels than when aggregated to the monthly level. There are some discrepancies between the two measures at the daily level, with the satellite data recording greater levels of PM2.5 than the regulatory-grade data at some times and lower levels at other times (Figures 4C and 4D).

Next, we look at alignment between the two data sources at higher frequency. One of the advantages of the data from MERRA-2 over other sources of satellite data is that it can generate estimates of PM2.5 at the hourly level. The estimates from MERRA-2 and the data from the regulatory-grade monitor are not as closely aligned at this higher temporal frequency. Figure 5 uses data from March 2020 to illustrate that the measurements of PM2.5 at the hourly level from these two data sources frequently diverge by

> 50 _μ_ g _/m_<sup>3</sup> or more and are often moving in the opposite direction (i.e. one data series is not a level shift

> 18Because of the inconsistent availability of data from the regulatory-grade monitors across years, we combined data from different monitors, using data from Bel Air for 2017, data from Republique in 2018, from Guediewaye in 2019 and data for Republique and Guediewaye in 2020.

> 19The higher levels of pollution measured by the monitor at Guediawaye may reflect higher levels of pollution in this part of the city or may be due to the calibration of the instrument.

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