Impacts of wind power on air quality, premature mortality, and exposure disparities in the United States

This repo includes supporting material for the publication:

Qiu, M., Zigler, C. M., & Selin, N. E. (2022). Impacts of wind power on air quality, premature mortality, and exposure disparities in the United States. Science Advances, 8(48), eabn8762.

Please download and unzip the file "mhqiu/wind_pollution_EJ-v1.0.zip". Please see README for a full description of the sample data included in this repo. 

README

1. Regression results: 
EGU_regression_scenario_results.xlsx 
It includes regression results for each EGU in our sample (1264 EGUs in total). 

2. Air quality simulation results:
2.1 GEOS-Chem simulation
GC_daily_pm25_o3_scenarios.nc 
It contains surface level annual mean PM2.5 and MDA8 O3 concentration under different emission scenarios. We include four scenarios in total:
- baseline scenario: air quality **without** the amount of wind power associated with 2014 RPS targets 
- expost scenario:  air quality with the wind power associated with 2014 RPS targets under the current dispatch decisions
- health damage minimizing scenario: air quality with the wind power associated with 2014 RPS targets under a hypothetical dispatch scenario that minimizes the health damage
- CO2 minimizing scenario: air quality with the wind power associated with 2014 RPS targets under a hypothetical dispatch scenario that minimizes the CO2 emissions

Therefore, to calculate the air quality impacts of wind power under different dispatch decisions:  
current (ex post) = ex post - baseline.  
health damage minimizing =  health damage minimizing - baseline.  
CO2 minimizing scenario = CO2 minimizing - baseline.  

2.2 InMAP simulations
InMAP/xx.shp  
The shapefiles contain annual mean PM2.5 concentration simulated with InMAP under different emission scenarios.  
baseline.shp: baseline scenario  
ex post.shp: ex post scenario  
health_damage_minimizing.shp: health damage minimizing scenario  
co2_minimizing.shp: CO2 minimizing scenario

Descriptions of the four scenarios are the same as above for GEOS-Chem.

3. County-level air quality change for different demographic groups (GEOS-Chem)
county_pm_o3_changes_by_groups_GEOS_CHEM.xlsx  
This file contains changes in county-level simulated PM2.5 and O3 concentrations due to wind power under different scenarios. It also includes the total population at the county level and the population for each subgroup. This data can be used to calculate the distributional effects of air quality benefits across different population groups.