LOCAETA Background
The LOCal Air Emissions Tracking Atlas (LOCAETA) is an air quality analysis tool designed to help government agencies, regulators, community groups, industry professionals, and other interested parties understand the impacts of industrial decarbonization on emissions and public health. This work incorporates various datasets from industrial facilities across the United States and integrates satellite and in situ observations with atmospheric modeling to quantify the effects of various decarbonization scenarios. LOCAETA can be used nationally, at a screening level, or at a local scale.Ā
During the first phase of LOCAETAās development, we launched an interactive online map that showcased fine particulate matter data, along with industrial sources, in an easily digestible way (LINK). As we continue with the second phase of LOCAETA, our offerings have expanded to include flexible, userādriven products. Depending on a projectās goals, we are able to provide local, custom maps, detailed technical reports, oneāpage summaries, and other tailored deliverables.
On this page, we showcase some of the decarbonization technologies and project attributes that have been explored.
Carbon Capture and Storage
Carbon capture and storage (CCS) technologies can be added to existing industrial facilities to reduce carbon emissions. By capturing emissions at the source, CCS offers a pathway for industry to achieve netāzero goals. Implementing CCS requires careful assessment to ensure the positives outweigh any negative air quality effects on nearby communities. This is due to the various CCS technologies and how they possibly mitigate or produce criteria air pollutants (LINK). In the US, the most mature and widely used CCS method is amine-based (LINK). However, traditional amine-based technology can produce ammonia or volatile organic compounds, a harmful effect on the nearby environment. This method can utilize additional measures to decrease these unwanted emissions (LINK).
We utilized the COā National Capture Opportunities and Readiness Database (COāNCORD) to identify candidate facilities for CCS retrofit. We estimated reductions and potential increases of non-COā pollutants. In the map below, we offer a screening-level view of the facilities in the U.S. with CCS opportunities and how PM2.5 can potentially be reduced using literature-based estimates.
Electrification
Electrifying industrial facilities is a process in which fossil-fuel-fired equipment is replaced with electric alternatives. This directly eliminates combustion and dramatically reduces carbon emissions. Electric systems improve energy efficiency and do not emit criteria air pollutants, improving local air quality near electrified facilities.
We utilized the National Emissions Inventory (LINK) to determine unit types at facilities in the U.S. An algorithm was developed to quantify the amount of energy consumption by facility units, using available emissions amounts, unit descriptors, and emissions factors in the NEI dataset. NRELās standard scenarios and Cambium model (LINK) were utilized to understand regional electricity demand and corresponding emissions with various electrification scenarios. This work directly informed our air quality and public health modeling described in the next section by characterizing different scenarios for future US grid possibilities.
Air Quality and Health Benefits
We utilized the Intervention Model for Air Pollution (InMAP), along with the Environmental Benefits Mapping and Analysis Program (BenMAP) to quantify the resulting PM2.5 impacts on public health for various decarbonization scenarios nationwide. InMAP is a reduced-complexity air quality model designed to assess the distribution of emissions changes, whereas BenMAP estimates health outcomes associated with the InMAP emissions changes. BenMAP estimates the number of health cases and associated costs based on poor air quality exposure.
The map below shows example scenarios based on decarbonizing the US electric grid: our current grid, a future 2050 grid without any IRA tax credits, and a 2050 grid that is 95% decarbonized. Criteria air pollutant emissions can increase or decrease depending on how and where electrification occurs. As a result, the local air quality can change, subsequently affecting the health of nearby residents. This map highlights several health outcomes linked to PM2.5, including asthma-related symptoms (coughing, wheezing, and shortness of breath). It also includes the number of workdays lost due to pollution-related illness, and estimates of deaths avoided or added because of PM2.5 exposure.
Case Study: Denver
The Denver metropolitan area was selected as the first project for a local LOCAETA use case. Denver faces unique air quality challenges; it is well-known for its historical ābrown cloud.ā It has been classified as a severe NAAQS non-attainment area for 8-hour ozone by the U.S. EPA. The region boasts a large residential population of over 3 million people and a strong industrial presence. In addition, the topography and climate are highly unique.
Before assessing any health impacts of a chosen decarbonization technology, evaluating the present-day emissions characteristics are necessary to define baseline conditions. For this work, we selected 10 facilities with large CO2 and criteria air pollutant emissions based on annual emissions reporting. To understand their emissions characteristics on shorter temporal scales, we utilized HYSPLIT air dispersion modeling (LINK) to assess plume distribution of fine particulate matter. These plumes allow us to assess average characteristics of PM2.5 behavior in an urban environment, where many sources exist.
For the Denver case study, health impact modeling was also conducted. We considered hypothetical health benefits when applying CCS and electrification to the 10 selected facilities. Our results showcased health effects from PM2.5 exposure, including asthma-related illness, workdays lost, and deaths avoided or added.