Quantifying Disparities in Air Pollution Exposures across the United States Using Home and Work Addresses.

While human mobility plays a crucial role in determining ambient air pollution exposures and health risks, research to date has assessed risks on the basis of almost solely residential location. Here, we leveraged a database of ∼128-144 million workers in the United States and published ambient PM2.5 data between 2011 and 2018 to explore how incorporating information on both workplace and residential location changes our understanding of disparities in air pollution exposure. In general, we observed higher workplace exposures relative to home exposures, as well as increased exposures for nonwhite and less educated workers relative to the national average. Workplace exposure disparities were higher among racial and ethnic groups and job types than by income, education, age, and sex. Not considering workplace exposures can lead to systematic underestimations in disparities in exposure among these subpopulations. We also quantified the error in assigning workers home instead of a weighted home-and-work exposure. We observed that biases in associations between PM2.5 and health impacts by using home instead of home-and-work exposure were the highest among urban, younger populations.

Using twitter to investigate responses to street reallocation during COVID-19: Findings from the U.S. and Canada.

The COVID-19 pandemic has challenged and encouraged local governments to reallocate street space. The chief purpose of new regimes of street management is to expand spaces for walking and bicycling, and to ease business interactions such as curbside pickup and dining while maintaining social distancing guidelines. We investigated how North Americans on Twitter viewed alternative uses and forms of street reallocation, specifically during the early months of the pandemic from April 1, 2020 to July 1, 2020. Relying on a crowdsourced dataset of government actions (Combs and Pardo 2021), we identified five areas of policy initiative that were broadly representative of government actions: cycling, walking, driving, business, and curbside. First, we identified a corpus of 292,108 geolocated tweets from the U.S. and Canada. Next, we used word vectors, built on this Twitter corpus, to generate similarity scores across the five areas of policy initiative for each tweet. Finally, we selected the top tweets that closely matched ideas contained in the areas of policy initiative, thus creating a finer corpus of 1,537 tweets. Using the five categories as guideposts, we conducted an inductive content analysis to understand opinions expressed on Twitter. Our analysis suggests that renewed use of the curb has opened up possibilities for reimaging this space. Particularly, business uses of the curb for dining and pick up zones have expanded widely, and there is more use of sidewalks; yet both spaces have limited capacity. Planners need to think of expanding these assets while reducing cost burdens for their alternative uses.