How Differential Privacy Will Affect Estimates of Air Pollution Exposure and Disparities in the United States
Census data is crucial to understand energy and environmental justice outcomes such as poor air quality which disproportionately impact people of color in the U.S. Wwith the advent of sophisticated personal datasets and analysis, Census Bureau is considering adding top-down noise (differential priva...
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Format: | Article |
Language: | English |
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Findings Press
2023-05-01
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Series: | Findings |
Online Access: | https://doi.org/10.32866/001c.74975 |
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author | Madalsa Singh |
author_facet | Madalsa Singh |
author_sort | Madalsa Singh |
collection | DOAJ |
description | Census data is crucial to understand energy and environmental justice outcomes such as poor air quality which disproportionately impact people of color in the U.S. Wwith the advent of sophisticated personal datasets and analysis, Census Bureau is considering adding top-down noise (differential privacy) and post-processing 2020 census data to reduce the risk of identification of individual respondents. Using 2010 demonstration census and pollution data, I find that compared to the original census, differentially private (DP) census significantly changes ambient pollution exposure in areas with sparse populations. White Americans have lowest variability, followed by Latinos, Asian, and Black Americans. DP underestimates pollution disparities for SO~2~ and PM~2.5~ while overestimates the pollution disparities for PM~10~. |
first_indexed | 2024-03-08T10:21:08Z |
format | Article |
id | doaj.art-e4326732f8c04230b70f2cbc18e06412 |
institution | Directory Open Access Journal |
issn | 2652-8800 |
language | English |
last_indexed | 2024-03-08T10:21:08Z |
publishDate | 2023-05-01 |
publisher | Findings Press |
record_format | Article |
series | Findings |
spelling | doaj.art-e4326732f8c04230b70f2cbc18e064122024-01-28T00:17:04ZengFindings PressFindings2652-88002023-05-01How Differential Privacy Will Affect Estimates of Air Pollution Exposure and Disparities in the United StatesMadalsa SinghCensus data is crucial to understand energy and environmental justice outcomes such as poor air quality which disproportionately impact people of color in the U.S. Wwith the advent of sophisticated personal datasets and analysis, Census Bureau is considering adding top-down noise (differential privacy) and post-processing 2020 census data to reduce the risk of identification of individual respondents. Using 2010 demonstration census and pollution data, I find that compared to the original census, differentially private (DP) census significantly changes ambient pollution exposure in areas with sparse populations. White Americans have lowest variability, followed by Latinos, Asian, and Black Americans. DP underestimates pollution disparities for SO~2~ and PM~2.5~ while overestimates the pollution disparities for PM~10~.https://doi.org/10.32866/001c.74975 |
spellingShingle | Madalsa Singh How Differential Privacy Will Affect Estimates of Air Pollution Exposure and Disparities in the United States Findings |
title | How Differential Privacy Will Affect Estimates of Air Pollution Exposure and Disparities in the United States |
title_full | How Differential Privacy Will Affect Estimates of Air Pollution Exposure and Disparities in the United States |
title_fullStr | How Differential Privacy Will Affect Estimates of Air Pollution Exposure and Disparities in the United States |
title_full_unstemmed | How Differential Privacy Will Affect Estimates of Air Pollution Exposure and Disparities in the United States |
title_short | How Differential Privacy Will Affect Estimates of Air Pollution Exposure and Disparities in the United States |
title_sort | how differential privacy will affect estimates of air pollution exposure and disparities in the united states |
url | https://doi.org/10.32866/001c.74975 |
work_keys_str_mv | AT madalsasingh howdifferentialprivacywillaffectestimatesofairpollutionexposureanddisparitiesintheunitedstates |