Zobrazeno 1 - 10
of 157
pro vyhledávání: '"deSouza, Priyanka"'
Unequal exposure to air pollution by race and socioeconomic status is well-documented in the U.S. However, there has been relatively little research on inequities in the collection of PM2.5 data, creating a critical gap in understanding which neighbo
Externí odkaz:
http://arxiv.org/abs/2410.18692
Autor:
deSouza, Priyanka N., Rees, Amanda, Oscilowicz, Emilia, Lawlor, Brendan, Obermann, William, Dickinson, Katherine, McKenzie, Lisa M., Magzamen, Sheryl, Miller, Shelly, Bell, Michelle L.
Background Odors are a documented environmental justice challenge in Denver, Colorado. Complaints are an important modality through which residents express their concerns. Objective We investigated disparities in environmental justice related-variabl
Externí odkaz:
http://arxiv.org/abs/2402.03336
Autor:
deSouza, Priyanka N., Anenberg, Susan, Fann, Neal, McKenzie, Lisa M., Chan, Elizabeth, Roy, Ananya, Jimenez, Jose L., Raich, William, Roman, Henry, Kinney, Patrick L.
We evaluated the sensitivity of estimated PM2.5 and NO2 health impacts to varying key input parameters and assumptions including: 1) the spatial scale at which impacts are estimated, 2) using either a single concentration-response function (CRF) or u
Externí odkaz:
http://arxiv.org/abs/2309.13703
Autor:
deSouza, Priyanka, Anenberg, Susan, Makarewicz, Carrie, Shirgaokar, Manish, Duarte, Fabio, Ratti, Carlo, Durant, John, Kinney, Patrick, Niemeier, Deb
While human mobility plays a crucial role in determining air pollution exposures and health risks, research to-date has assessed risks based solely on residential location. Here we leveraged a database of ~ 130 million workers in the US and published
Externí odkaz:
http://arxiv.org/abs/2303.12559
Autor:
deSouza, Priyanka, Wang, An, Machida, Yuki, Duhl, Tiffany, Mora, Simone, Kumar, Prashant, Kahn, Ralph, Ratti, Carlo, Durant, John L., Hudda, Neelakshi
Low-cost sensors (LCS) for measuring air pollution are increasingly being deployed in mobile applications but questions concerning the quality of the measurements remain unanswered. For example, what is the best way to correct LCS data in a mobile se
Externí odkaz:
http://arxiv.org/abs/2301.03847
Autor:
deSouza, Priyanka, Barkjohn, Karoline, Clements, Andrea, Lee, Jenny, Kahn, Ralph, Crawford, Ben, Kinney, Patrick
Low-cost sensors (LCS) are increasingly being used to measure fine particulate matter (PM2.5) concentrations in cities around the world. One of the most commonly deployed LCS is the PurpleAir with about 15,000 sensors deployed in the United States. H
Externí odkaz:
http://arxiv.org/abs/2210.14759
Autor:
Considine, Ellen M., Hao, Jiayuan, deSouza, Priyanka, Braun, Danielle, Reid, Colleen E., Nethery, Rachel C.
Investigating the health impacts of wildfire smoke requires data on people's exposure to fine particulate matter (PM$_{2.5}$) across space and time. In recent years, it has become common to use machine learning models to fill gaps in monitoring data.
Externí odkaz:
http://arxiv.org/abs/2209.01479
Autor:
deSouza, Priyanka
Ambient air pollution is responsible for ~ 4.2 million premature deaths every year making it the world’s single largest environmental health risk. Although 90% of this burden is borne by countries in the Global South, effective air pollution govern
Autor:
Considine, Ellen M., Braun, Danielle, Kamareddine, Leila, Nethery, Rachel C., deSouza, Priyanka
Environmental Protection Agency (EPA) air quality (AQ) monitors, the gold standard for measuring air pollutants, are sparsely positioned across the US due to their costliness. Low-cost sensors (LCS) are increasingly being used by the public to fill i
Externí odkaz:
http://arxiv.org/abs/2205.03499
Numerous studies have examined the associations between long-term exposure to fine particulate matter (PM2.5) and adverse health outcomes. Recently, many of these studies have begun to employ high-resolution predicted PM2.5 concentrations, which are
Externí odkaz:
http://arxiv.org/abs/2109.15264