The NSAPH Subcollection, part of the Climate-Health CAFÉ Dataverse, features data contributions from the National Studies on Air Pollution and Health (NSAPH) group based at the Harvard T.H. Chan School of Public Health.

This subcollection is focused on providing datasets related to air pollution, climate change, and public health. These datasets result from NSAPH's work in studying the environmental impacts on health outcomes and regulatory policy.

Instructions

The NSAPH Subcollection is open for reuse of the general public, but contributions are restricted to NSAPH collaborators. Instructions for NSAPH collaborators that want to upload datasets are offered in the CAFÉ Dataverse upload instructions.

Featured Dataverses

In order to use this feature you must have at least one published or linked dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Advanced Search

1 to 10 of 22 Results
SpaCE: The Spatial Confounding Environment
Jun 28, 2025
Tec, Mauricio; Trisovic, Ana; Audirac, Michelle; Dominici, Francesca, 2023, "SpaCE: The Spatial Confounding Environment", https://doi.org/10.7910/DVN/SYNPBS, Harvard Dataverse, V29, UNF:6:EjV+pwtl9QyaygkCiEYBUA== [fileUNF]
SpaCE: The Spatial Confounding Environment is a benchmarking dataset for causal inference incorporating spatial structure. In particular, SpaCE datasets contain real confounder and exposure/treatment data inspired by environmental health studies. The synthetic outcome and counterfactual are generated according to recommended practices for causal ev...
Spatial Aggregations of USHAP PM2.5 dataset
May 19, 2025
Kaur, Mahima, 2025, "Spatial Aggregations of USHAP PM2.5 dataset", https://doi.org/10.7910/DVN/4GDRB1, Harvard Dataverse, V1
USHAP (US High Air Pollutants) is a high-resolution, full-coverage dataset of ground-level air pollution across the U.S. from 2000 to 2020 (Wei et al., LPH, 2023). USHAP integrates ground measurements, satellite observations, reanalysis data, and model outputs using Artificial Intelligence techniques that account for the spatiotemporal complexity o...
County and ZCTA-Aggregated U.S. gridMET variables
May 14, 2025
Kitch, James, 2025, "County and ZCTA-Aggregated U.S. gridMET variables", https://doi.org/10.7910/DVN/3PP3ZE, Harvard Dataverse, V1
Dataset Description This dataset contains aggregated meteorological variables for U.S. counties and ZIP Code Tabulation Areas (ZCTAs) derived from the gridMET dataset. The gridMET product combines high-resolution spatial climate data (e.g., temperature, precipitation, humidity) from the PRISM Climate Group with daily temporal attributes and additio...
Five-year dataset depicting electric power generation and CO2 emissions within the U.S. electricity sector, spanning from July 2018 to June 2023
Feb 6, 2025
Biswas, Arpita; Daniel Mork; Minghao Qiu; Danielle Braun; Francesca Dominici, 2023, "Five-year dataset depicting electric power generation and CO2 emissions within the U.S. electricity sector, spanning from July 2018 to June 2023", https://doi.org/10.7910/DVN/OKEATQ, Harvard Dataverse, V3, UNF:6:+OzALX7cCvNx6Ez7Zsv1kw== [fileUNF]
These datasets, namely .csv, are snapshots of the regional datasets published by the U.S. Energy Information Administration (EIA) between July 1, 2018 and June 30, 2023. EIA publishes hourly operational data across the United States electricity grid, including demand, net generation of electricity from various sources (such as coal, natural gas, so...
Co-exposure patterns of heat, wildfire, and wildfire smoke in Western US
Dec 26, 2024
Hu, Kate; Trisovic, Ana; Ankita Bakshi, 2024, "Co-exposure patterns of heat, wildfire, and wildfire smoke in Western US", https://doi.org/10.7910/DVN/9VDUAP, Harvard Dataverse, V2
We provide data on three heat-related natural hazards: extreme heat, wildfire burn zones, and wildfire smoke from 2006-2020 in eleven Western US states.
Daily meteorological Gridmet variables by United States administrative boundaries
Oct 15, 2024
Audirac, Michelle, 2024, "Daily meteorological Gridmet variables by United States administrative boundaries", https://doi.org/10.7910/DVN/FYTME3, Harvard Dataverse, V1, UNF:6:6B86BMLfgFTH6W7howGaQQ== [fileUNF]
This dataset provides spatial aggregations of meteorological Gridmet variables for US counties and ZIP Code Tabulation Areas (ZCTA). The spatial aggregations are performed for gridded raster data (netCDF) to US polygon features (shapefile).
Global Aggregations Climate Types
Sep 30, 2024
Gilmour, Jonathan, 2024, "Global Aggregations Climate Types", https://doi.org/10.7910/DVN/JOEZDP, Harvard Dataverse, V2, UNF:6:4+Xc41Qa92WTIikReQ4OLw== [fileUNF]
Global polygon spatial aggregations of Koppen-Geiger climate types.
ZIP to County Crosswalk
Aug 12, 2024
Kitch, James, 2024, "ZIP to County Crosswalk", https://doi.org/10.7910/DVN/0U2TCB, Harvard Dataverse, V1, UNF:6:Ille9Yav2FM1Vg8kkPZlgA== [fileUNF]
The following crosswalks are the result of a data pipeline that pulls crosswalks from the U.S. Department of Housing and Urban Development (HUD) database, compiling a comprehensive ZIP --> FIPS crosswalk from 2010 to 2023. The crosswalks are available in four different forms: "one2one": one row, per ZIP code, per year. Each ZIP is matched to its be...
Multifactorial Zip Code-Year Dataset: Socio-Economic, Demographic, and Environmental Variables in the Contiguous United States (2000-2016)
Jul 30, 2024
Khoshnevis, Naeem; Wu, Xiao; Braun, Danielle, 2024, "Multifactorial Zip Code-Year Dataset: Socio-Economic, Demographic, and Environmental Variables in the Contiguous United States (2000-2016)", https://doi.org/10.7910/DVN/5XBJBM, Harvard Dataverse, V1
This dataset aggregates extensive public data corresponding to 34,928 zip codes from the contiguous United States, spanning from 2000 to 2016. It encompasses 580,244 zip code-year observations, capturing a myriad of variables to portray a comprehensive picture of each region. The variables include, but are not limited to, education rate, median hou...
Köppen-Geiger Climate Classifications by United States administrative boundaries
May 1, 2024
Audirac, Michelle, 2024, "Köppen-Geiger Climate Classifications by United States administrative boundaries", https://doi.org/10.7910/DVN/BG0OHO, Harvard Dataverse, V1, UNF:6:9ltwF8jHVJK6CJJGd7bTJA== [fileUNF]
This dataset provides spatial aggregations of Köppen-Geiger climate classifications for US counties and ZIP Code Tabulation Areas (ZCTA). The spatial aggregations are performed for climate classification information going from approximately 1-km gridded global raster data (geoTIFF) to US polygon features (shapefile). The datasets include the predom...
Add Data

Sign up or log in to create a dataverse or add a dataset.

Sign Up Log In
Share Dataverse

Share this dataverse on your favorite social media networks.

Link Dataverse
Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.