While populations in low- and middle-income countries are exposed to some of the highest levels of air pollution and its consequences, the majority of economics research on the topic is focused on high-income settings where there is greater data availability. This paper compares and evaluates the three principal sources of air pollution data (regulatory-grade monitors, satellites, and low-cost monitors) in a Sub-Saharan African context in terms of the accuracy of measurements of inhalable fine particulate matter across spatial and temporal frequencies and their performance when studying policy impacts. Satellite data is closely aligned with data from the regulatory-grade monitors at lower temporal frequencies. The low-cost monitors underestimate the amount of fine particulate matter relative to the other data sources. Calibration, especially context-specific calibration, of the low-cost monitors' data improves its alignment with other data sources. The paper uses each data source to evaluate the air pollution externality of mobility reduction policies using a difference-in-differences design and finds similar results, especially in terms of percent reduction. The paper considers policy makers' constraints to air pollution monitoring in low-income settings and demonstrates that co-locating one regulatory-grade monitor in a network of low-cost monitors can capture the spatial variation of pollution across an urban area and achieve better accuracy than either of these data sources alone. This provides a framework for policy makers to generate the data needed to evaluate environmental policies and externalities.
Authors
- DOI
- https://dx.doi.org/10.1596/1813-9450-10957
- Disclosure Date
- 2024/10/24
- Disclosure Status
- Disclosed
- Doc Name
- Designing Air Quality Measurement Systems in Data-Scarce Settings
- Originating Unit
- Off of Sr VP Dev Econ/Chief Econ (DECVP)
- Pages
- 42
- Product Line
- Advisory Services & Analytics
- Published in
- United States of America
- Rel Proj ID
- SN-Impact Evaluation Of The Brt And Ter In Dakar -- P166486
- Series Name
- Policy Research working paper; PLANET; RRR; COVID-19 (Coronavirus);
- TF No/Name
- TF0A6453-DIME_ieConnect_SEN_ConstructionWorkers,TF0A6454-DIME_ieConnect_SEN_MobilityDataSystem,TF0A8651-KCPIII - Measuring and Enhancing Mobility in Dakar,TF0B2710-DIME_ieConnect_SEN_AirQuality
- Unit Owning
- DIME Infra & Climate Change (DIME4)
- Version Type
- Final
- Volume No
- 1
Table of Contents
- Designing Air Quality Measurement Systems in Data-Scarce 3
- Settings 3
- 1 Introduction 4
- 2 Context 7
- 3 Data 8
- Regulatory-Grade Monitors 8
- Low-Cost Monitors 9
- Satellite-based Measurement 11
- 4 Methods 13
- 4.1 Calibration 13
- 4.2 Comparison of Different Measures and Policy Analysis 15
- 5 Results 16
- 5.1 Comparison of PM2.5 Levels 16
- 5.2 Policy Analysis 24
- 6 Conclusion 31
- References 32
- 7 Appendix 36
- Type Source Products Temporal Spatial Availability 40
- MERRA-2 AOD Gases Aerosols Hourly 55 x 69 km² 1980- Present 40
- Copernicus Atmosphere Monitoring Service AOD Gases Aerosols PM Daily 44 x 44 km² 2003 - Present 40
- Van Donkelaar et al 2021 PM2.5 Monthly 10 x 10 km² 1998 - 2022 40
- MODIS on TerraAqua AOD Daily 1 x 1 km² 2000-02-26 - Present 40
- SLSTR on Sentinel-3 AOD Daily 9.5 x 9.5 km² 19-08-2020 - Present 40
- VIIRS on S-NPP AOD Daily 6 x 6 km² 2012-03-01 - Present 40
- OMI on Aura Gases Aerosols Daily 13 x 24 km² 2004-10-01 - Present 40
- TROPOMI on Sentinel 5-P Gases Aerosols Daily 1.1 x 1.1 km² 2018-06-28 - Present 40
- SEVIRI on MSG AOD Daily 3 x 3km² 01-02-2004 - 31-12-2012 40
- AVHRR GOME-2 and IASI on METOP AOD aerosol type Daily 510 40 km² 10-07-2007 - 31-08-2019 40
