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.

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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.

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1,061 to 1,070 of 1,094 Results
Replication Data for: Evaluation of Model-Based PM2.5 Estimates for Exposure Assessment During Wildfire Smoke Episodes in the Western U.S.
Jan 9, 2023
Considine, Ellen; Hao, Jiayuan, 2023, "Replication Data for: Evaluation of Model-Based PM2.5 Estimates for Exposure Assessment During Wildfire Smoke Episodes in the Western U.S.", https://doi.org/10.7910/DVN/MBAVER, Harvard Dataverse, V1
This analytic dataset contains fine particulate matter (PM2.5) estimates at the locations of air quality monitors across the western US, both mobile smoke monitors deployed by the US Forest Service and stationary monitors maintained by the US EPA. All original sources of this data are open access; we share this processed dataset to facilitate repli...
Revisions_Merged_EPA_Di_Reid_with_CMAQ.rds
Jan 9, 2023 - Replication Data for: Evaluation of Model-Based PM2.5 Estimates for Exposure Assessment During Wildfire Smoke Episodes in the Western U.S.
Gzip Archive - 18.9 MB - MD5: 876e70817ecbc0b8ee5875ccb39cb62d
Supplementary analysis: comparing Di and Reid estimates from 2008-2016 with EPA monitor observations (not wildfire smoke specific) across the western US.
Revisions_Merged_FINAL_monitor_Di_Reid_with_CMAQ.rds
Jan 9, 2023 - Replication Data for: Evaluation of Model-Based PM2.5 Estimates for Exposure Assessment During Wildfire Smoke Episodes in the Western U.S.
Gzip Archive - 735.7 KB - MD5: 66be31b4a004f173e3b64b98d15e7ee7
Main analytic dataset: comparing Di and Reid estimates (2008-2016) with USFS smoke monitor observations across the western US.
Revisions_Merged_monitor_Reid_without_CMAQ.rds
Jan 9, 2023 - Replication Data for: Evaluation of Model-Based PM2.5 Estimates for Exposure Assessment During Wildfire Smoke Episodes in the Western U.S.
Gzip Archive - 551.8 KB - MD5: e07729546d59c28ee1f7182fc8aa5700
Supplementary analysis: comparing Reid estimates from 2017-2018 with USFS smoke monitor observations from those years; also includes data from 2008-2016 (from the same model) for comparison.
Replication Data for: Investigating Use of Low-Cost Sensors to Increase Accuracy and Equity of Real-Time Air Quality Information
Dec 8, 2022
Considine, Ellen, 2022, "Replication Data for: Investigating Use of Low-Cost Sensors to Increase Accuracy and Equity of Real-Time Air Quality Information", https://doi.org/10.7910/DVN/QR4N7V, Harvard Dataverse, V1, UNF:6:J+iWb1dGAgHgWN62soaKLA== [fileUNF]
This analytic dataset contains various environmental and socio-demographic characteristics of the state of California, daily at the resolution of 1km x 1km. All original sources of this data are open access; we share this processed dataset to facilitate replication of our paper and other exploration.
CA_NA_pos.rds
Dec 8, 2022 - Replication Data for: Investigating Use of Low-Cost Sensors to Increase Accuracy and Equity of Real-Time Air Quality Information
Gzip Archive - 6.4 KB - MD5: b159c010295a3fe0a886063ad93e00a5
Vector of location-days where the Di et al. daily estimates are missing
CA_with_CES_projected.rds
Dec 8, 2022 - Replication Data for: Investigating Use of Low-Cost Sensors to Increase Accuracy and Equity of Real-Time Air Quality Information
Gzip Archive - 16.2 MB - MD5: bb80180470b2013dd94b0a9cb153d1aa
Dataframe of static characteristics (environmental, socio-demographic) of 1km x 1km grid points across California. First 38 columns are the exact same as CA_clean_projected.rds (which is referenced in several scripts).
Daily_AQS_PA_2020.tab
Dec 8, 2022 - Replication Data for: Investigating Use of Low-Cost Sensors to Increase Accuracy and Equity of Real-Time Air Quality Information
Tabular Data - 155.1 KB - 9 Variables, 1409 Observations - UNF:6:QFu+R1vf8hCLNaL6DyZwww==
Dataframe of 24h-avg. measurements from PurpleAir LCS located within 50 meters of EPA (AQS) monitors
Daily_PM25_CA.rds
Dec 8, 2022 - Replication Data for: Investigating Use of Low-Cost Sensors to Increase Accuracy and Equity of Real-Time Air Quality Information
Gzip Archive - 1.3 GB - MD5: e054832a8821cc2bf83bc41e34e6df6e
Di et al. daily PM2.5 estimates (1km x 1km) extracted for just California in 2016 (original dataset is national, 2000-2016)
Daily_PM_AQI-class.rds
Dec 8, 2022 - Replication Data for: Investigating Use of Low-Cost Sensors to Increase Accuracy and Equity of Real-Time Air Quality Information
Gzip Archive - 6.8 MB - MD5: 3a4a54a0189342190a97156b3d28bc77
Vector of AQI classifications of daily PM2.5 (from the Di et al. estimates)
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