SBIR/STTR Award attributes
Air quality data from top-of-the-line platforms, such as satellites, are difficult to obtain without a high- level of technical knowledge. For this reason, local air quality patterns and trends are often inaccessible to disadvantaged communities (DACs). Many technologies that will be used for deep decarbonization of industrial and power facilities have the added co-benefit of reducing non-CO2 pollutants, such as criteria air pollutants, but there is a lack of information regarding the economic, social, health, and climate benefits from these emissions reductions. The impacts of pollutants from point-source emitters often affect communities of lower socioeconomic status or composed of ethnic and racial minorities. Understanding the full suite of benefits offered by advanced decarbonization, such as carbon capture and storage and hydrogen-fuel switching, will be important for advocate for equitable climate and energy solutions. We will develop the Local Climate and Air Quality Emissions Tracking Atlas (LOCAETA), an interface that enables local stakeholders, commercial users, urban researchers, and decision-makers to evaluate the impact of point-source emitters on local communities. We will apply machine learning to rapidly identify and characterize areas affected by point-sources and deploy atmospheric models to determine likely sources of pollutant transport at a neighborhood level. We will identify data sources necessary to quantify the impacts from point-source emitters in the state of Louisiana, which will serve as the initial proofing region before a larger geographic expansion that will eventually target nationwide data coverage. This analysis will be done using a range of public models and international, national, and regional datasets. LOCAETA will use 1) cutting-edge machine learning techniques to identify relationships between pollutant concentrations, point-source emitters, public health trends, and environmental justice; 2) investigate local transport of primary pollutants using atmospheric dispersion models to evaluate impacts to environmental systems and human health; 3) create a free online interface that is optimized for ease-of-use to share these data products; and 4) develop a database of detailed impacts from point-source emitters to facilitate more accurate modeling of changes to earth and environmental systems regarding critical infrastructure, natural resource, and energy resilience. There are currently no publicly available, up-to-date inventory of pollutant impacts from point source emitters in North America. Existing products are limited by scope and or scale. We will develop an inventory with LOCAETA, which could have tremendous applications because of the importance of air pollutants on human health and the quantity of point-source emitters that will need to be decarbonized. Decisions informed by LOCAETA data could save thousands of lives per year and help the United States achieve its decarbonization goals. The commercial aspect of LOCAETA will aid researchers, decision- makers, and key industry personnel to understand the impact of point-source emissions and pollutant reduction pathways.
