Data and Code for: U.S. Embassy Air-Quality Tweets Led to Global Health Benefits

Principal Investigator(s): View help for Principal Investigator(s) Akshaya Jha, Carnegie Mellon University and NBER; Andrea La Nauze, The University of Queensland and CESifo

Version: View help for Version V1

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Project Citation:

Jha, Akshaya, and La Nauze, Andrea. Data and Code for: U.S. Embassy Air-Quality Tweets Led to Global Health Benefits. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2022-08-30. https://doi.org/10.3886/E178921V1

Project Description

Summary: The World Health Organization estimates that over 90% of the world's population is exposed to hazardous levels of local air pollution. Air pollution is markedly worse in low- and middle-income countries yet air-quality monitoring is typically sparse. In 2008, the United States Embassy in Beijing began tweeting hourly air-quality information from a newly installed pollution monitor, dramatically improving the information on air quality available to Beijing residents. Since then, the United States has installed over 50 monitors around the world, tweeting real-time reports on air quality in those locations. Using spatially granular measurements of local air pollution from satellite data that span the globe, we employ variation in whether and when U.S. embassies installed monitors to evaluate the impact of air-quality information on pollution. We estimate that embassy monitors led to reductions in fine particulate concentration levels in host countries of 2-4 micrograms per cubic meter. Our central estimate of the annual monetized benefit of the decrease in premature mortality due to this reduction in pollution is 127 million dollars for the median city in 2019. Our findings point to the substantial benefits of improving the availability and salience of air-quality information in low- and middle-income countries.

Scope of Project

Subject Terms: Air-quality monitoring; Information interventions; Local air pollution; Fine particulates; Developing countries

Geographic Coverage: 466 cities in 136 countries

Time Period(s): 1998 – 2019

Universe: We evaluate the impacts of the embassy monitoring program using satellite-derived measurements of pollution at 466 cities in 136 countries, of which 50 cities in 36 countries received embassy monitors by 2020.

Data Type(s): administrative records data; geographic information system (GIS) data; observational data

Methodology

Data Source:

The analyses in this paper utilize data from a variety of different sources.

City Location Data: The latitude and longitude corresponding to the center of each of 466 cities in 136 non-OECD countries is sourced from BatchGeo. Link: https://batchgeo.com/map/latitude-longitude; Accessed June 8, 2022

Embassy Monitor Data: Historical air-quality reports from monitors installed at U.S. diplomatic locations are available from the U.S. Government website AirNow. Link: www.airnow.gov; Accessed 18 April, 2020. Additional reports from monitors in India were accessed from the embassy website. Link: https://in.usembassy.gov/embassy-consulates/new-delhi/air-quality-data/, Accessed June 1, 2021.

Global Monitoring Data: State of global monitoring data are from the World Health Organization's Outdoor Air Quality Database. Link: https://www.who.int/data/gho/data/themes/air-pollution/who-air-quality-database; Accessed May 27, 2021.

Pollution Data: van Donkelaar et al. (2021) provide gridded estimates of fine particulate concentration levels across the world by combining satellite measurements of aerosol optical depth with chemical transport modelling. The resulting measurements are calibrated to global ground-based observations using a Geographically Weighted Regression (GWR). In sensitivity analyses, we use annual averages of gridded estimates of PM2.5 from the Modern-Era Retrospective analysis for Research and Applications (MERRA) data-set. The MERRA-2 reanalysis product combines satellite data on aerosol optical depth with an atmospheric chemistry model (GEOS-5) to calculate pixel-level average concentration levels of five types of aerosols (dust, sea salt, sulfate, and black and organic carbon). A weighted sum of these five aerosols gives us PM2.5 concentration levels. See Gelaro et al. (2017) and Buchard et al. (2017) for more details.

Google Trends Data: We take the annual average of the monthly data on search intensity, which can be downloaded from https://trends.google.com/trends/?geo=US. Data were not available for 3 treatment cities. Google search intensity is normalized as follows (quotation from Google Trends FAQ):

Search results are normalized to the time and location of a query by the following process:

(1) Each data point is divided by the total searches of the geography and time range it represents to compare relative popularity. Otherwise, places with the most search volume would always be ranked highest.

(2) The resulting numbers are then scaled on a range of 0 to 100 based on a topic’s proportion to all searches on all topics.

Post-Hardship Differential Data: We collect information on the wage premium paid to U.S. Diplomats to compensate them for living standards that differ from conditions in the United States. This wage premium, called the Post-Hardship Differential, is a proportional increase in salary determined by the U.S. Department of State based on measures of social and physical isolation, violence, crime, health care, and environmental conditions (which includes air pollution). The State Department publishes current and historical rates by diplomatic post, and provides information on hardship categories. Link: https://aoprals.state.gov/Web920/hardship.asp; Accessed December 14, 2019. For our main analysis, we utilize the Post-Hardship Differential rates for 201 locations in 144 countries from 2001-2019.

Embassy Staffing and Salary Data: Staffing levels were collected from the Congressional Budget Justification 2020, which provides staffing levels by post for 2019. Link: https://www.state.gov/wp-content/uploads/2020/03/FY21-CBJ-Appendix-1-FINAL-for-GPA-Mar-26-2020.pdf; Accessed 6 May, 2022. Salary schedules for 2019 and the distribution of staff across pay scales were collected from the U.S. Department of State. Links: https://www.state.gov/wp-content/uploads/2019/05/2019_FS_salary_table.pdf; Accessed 6 May, 2022. https://www.state.gov/wp-content/uploads/2019/05/Workforce-and-Leadership-Succession-Plan-FY18/_FY22...; Accessed 28 July, 2021.

Population Data: We utilize two different data sources for population. Our primary estimates of premature avoided deaths and mortality benefits are based on population calculated using gridded data derived from underlying NASA satellite measurements. Link: https://sedac.ciesin.columbia.edu/data/collection/gpw-v4/population-estimation-service; Accessed November 27, 2021. The "full city population" results and supplementary materials are based on city-level data on population, population density, and land size from Demographia, supplemented by other publicly available resources on city information.

Mortality Rates Data: Annual country-specific all-cause all-age mortality rates are collected from the World Health Organization (WHO). Link: https://data.worldbank.org/indicator/SP.DYN.CDRT.IN; Accessed June 12, 2022.

Unit(s) of Observation: 466 cities in 136 countries

Geographic Unit: City

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