Community-driven research and capacity building to address environmental justice concerns with industrial air pollution in Curtis Bay, South Baltimore.

Introduction: Curtis Bay (CB) is an environmental justice (EJ) community in South Baltimore. With a high concentration of industrial polluters and compounding non-chemical stressors, CB has experienced socioeconomic, quality of life, and health burdens for over 100 years. Today, these polluters include the open-air CSX Coal Terminal, waste-to-energy incinerators, and heavy diesel traffic through residential areas. The Community of Curtis Bay Association, Free Your Voice, and South Baltimore Community Land Trust are local organizations enacting a vision for equitable, healthy, and community-led development without industrial encroachment. In response to community-identified EJ concerns and an explosion at the CSX Coal Terminal, CB community groups partnered with academic researchers to develop a community-driven hyperlocal air monitoring and capacity building approach. This paper describes this approach to characterizing hyperlocal air quality in CB, building bridges between community residents and regulatory agencies, and nurturing a cohesive and effective community-academic partnership toward EJ. Methods: Using hyperlocal air monitoring, we are collecting real-time air pollution (particulate matter, black carbon, and ground-level gas species) and meteorological data from 15 low-cost sensors in residential and industrial areas of CB. We also use trail cameras to record activities at the CSX Coal Terminal. We merge air pollution and industrial activity data to evaluate the following: overall air quality in CB, multi-air pollutant profiles of elevated events, spatiotemporal changes in air quality in the community, patterns of industrial activity, and potential correlations between air quality and observed industrial activity. Members of our partnership also lead a high school course educating students about the history and ongoing efforts of the EJ movement in their community. Students in this course learn how to employ qualitative and quantitative data collection and analysis methods to bring scientific support to community EJ concerns. Results and Discussion: Our hyperlocal air monitoring network and community-academic partnership are continuing to evolve and have already demonstrated the ability to respond to community-identified EJ issues with real-time data while developing future EJ leaders. Our reflections can assist other community and academic groups in developing strong and fruitful partnerships to address similar EJ issues.

Emergency department visits associated with satellite observed flooding during and following Hurricane Harvey.

BACKGROUND: Flooding following heavy rains precipitated by hurricanes has been shown to impact the health of people. Earth observations can be used to identify inundation extents for subsequent analysis of health risks associated with flooding at a fine spatio-temporal scale. OBJECTIVE: To evaluate emergency department (ED) visits before, during, and following flooding caused by Hurricane Harvey in 2017 in Texas. METHODS: A controlled before and after design was employed using 2016-2018 ED visits from flooded and non-flooded census tracts. ED visits between landfall of the hurricane and receding of flood waters were considered within the flood period and post-flood periods extending up to 4 months were also evaluated. Modified Poisson regression models were used to estimate adjusted rate ratios for total and cause specific ED visits. RESULTS: Flooding was associated with increased ED visits for carbon monoxide poisoning, insect bite, dehydration, hypothermia, intestinal infectious diseases, and pregnancy complications. During the month following the flood period, the risk for pregnancy complications and insect bite was still elevated in the flooded tracts. SIGNIFICANCE: Earth observations coupled with ED visits increase our understanding of the short-term health risks during and following flooding, which can be used to inform preparedness measures to mitigate adverse health outcomes and identify localities with increased health risks during and following flooding events.

Quantifying Neighborhood-Scale Spatial Variations of Ozone at Open Space and Urban Sites in Boulder, Colorado Using Low-Cost Sensor Technology.

Recent advances in air pollution sensors have led to a new wave of low-cost measurement systems that can be deployed in dense networks to capture small-scale spatio-temporal variations in ozone, a pollutant known to cause negative human health impacts. This study deployed a network of seven low-cost ozone metal oxide sensor systems (UPods) in both an open space and an urban location in Boulder, Colorado during June and July of 2015, to quantify ozone variations on spatial scales ranging from 12 m between UPods to 6.7 km between open space and urban measurement sites with a measurement uncertainty of ~5 ppb. The results showed spatial variability of ozone at both deployment sites, with the largest differences between UPod measurements occurring during the afternoons. The peak median hourly difference between UPods was 6 ppb at 1:00 p.m. at the open space site, and 11 ppb at 4:00 p.m. at the urban site. Overall, the urban ozone measurements were higher than in the open space measurements. This study evaluates the effectiveness of using low-cost sensors to capture microscale spatial and temporal variation of ozone; additionally, it highlights the importance of field calibrations and measurement uncertainty quantification when deploying low-cost sensors.