Resolving and predicting neighborhood vulnerability to urban heat and air pollution: insights from a pilot project of community science, GeoHealth

Wang, J., L. Castro-Garcia, G.D. Jenerette, M. Chandler, C. Ge, D. Kucera, S. Koutzoukis, and J. Zeng (2022), Resolving and predicting neighborhood vulnerability to urban heat and air pollution: insights from a pilot project of community science, GeoHealth, J. Zeng., 6, e2021GH000575.
Abstract

Urban heat and air pollution, two environmental threats to urban residents, are studied via a community science project in Los Angeles, CA, USA. The data collected, for the first time, by community members, reveal the significance of both the large spatiotemporal variations of and the covariations between

m air temperature (2mT) and ozone (O3) concentration within the (4 km) neighborhood scale. This neighborhood variation was not exhibited in either daily satellite observations or operational model predictions, which makes the assessment of community health risks a challenge. Overall, the 2mT is much better predicted than O3 by the weather and research forecast model with atmospheric chemistry (WRF-Chem). For O3, diurnal variation is better predicted by WRF-Chem than spatial variation (i.e., underestimated by 50%). However, both WRF-chem and the surface observation show the overall consistency in describing statistically significant covariations between O3 and 2mT. In contrast, satellite-based land surface temperature at 1 km resolution is insufficient to capture air temperature variations at the neighborhood scale. Community engagement is augmented with interactive maps and apps that show the predictions in near real time and reveals the potential of green canopy to reduce air temperature and ozone; but different tree types and sizes may lead to different impacts on air temperature, which is not resolved by the WRF-Chem. These findings highlight the need for community science engagement to reveal otherwise impossible insights for models, observations, and real-time dissemination to understand, predict, and ultimately mitigate, urban neighborhood vulnerability to heat and air pollution. Plain Language Summary Heat waves and air pollution events can often occur at the same time, posing a dual threat to the public health in many urban neighborhoods. However, at or within the neighborhood scale (a couple of kilometers or less), few measurements have been taken via community engagement and little is known quantitatively about the covariation of ozone and temperature. Here, we present a summer pilot project of community science that involved ∼1,000 (including ∼750 K-12 students) people to study urban heat and ozone pollution in various neighborhoods in Los Angeles, CA. We summarize the methods and findings of the community engagement. Precious data collected by the community members reveals large spatial variations of ozone and temperature at the neighborhood scale, which are not resolved in the current generation of the operational (hourly) air quality forecast predictions or satellite data products. However, with observations suggesting the significant impact of canopy on air temperature and model's reliable performance in predicting observed strong ozone-temperature covariations, we suggest that green space has the potential to simultaneously mitigate the community's vulnerability to high temperature and air pollution. Future work is needed, especially via community engagement in other urban areas, to study ozone, temperature, and vegetation nexus.

Research Program
Applied Sciences Program (ASP)
Modeling Analysis and Prediction Program (MAP)
Atmospheric Composition
Atmospheric Composition Modeling and Analysis Program (ACMAP)

 

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