Program

Chemical & Biomolecular Engineering, Georgia Tech

Particulate matter (PM, aerosols) play an important role in air quality, climate, and human health. Exposure to fine PM (PM2.5) results in millions of deaths per year. Aerosols also impact climate via absorbing / scattering solar radiation and cloud formation, and their effects represent the single largest uncertainty in our understanding of radiative forcing. Secondary organic aerosols (SOA), formed from atmospheric oxidation chemistry of emissions from natural sources and human activities, dominate PM2.5 worldwide. However, the relative contribution of biogenic and anthropogenic sources to SOA in the atmosphere is poorly constrained. To elucidate this, we conducted multiple field measurement campaigns using advanced mass spectrometry in the greater Atlanta area over the years (2012 onward), encompassing the period of COVID lockdown in 2020, as well as the most recent measurements in summer 2022. We show that biogenic sources are the dominant contributor to SOA, but their formation is largely controlled by anthropogenic SO2 and NOx emissions from the industrial and transportation sectors. Further, various types of organic aerosols drive the decadal decrease trend in PM2.5 in the region, modulated by anthropogenic emissions to different extents. As different types of SOA exhibit different toxicity, the analysis of this comprehensive multi-year dataset not only provides a unique opportunity to understand the effect of anthropogenic emissions on biogenic SOA formation, but also how overall aerosol toxicity might evolve in the future, with rapid changes in energy systems, infrastructure, and land use.

Much of our science communication is based on outdated practices and consensus on what we believe is “effective SciComm practice.” So before you leave the ivory tower to talk about your research and how it may impact the local community or policymaker, there are five fundamental tenets to keep in mind. In this workshop, we will review science communication theory to inform how we inform our practice. You will walk away with a defined understanding of your topic, audience, location, medium, and messaging.

How to make technological innovations more socially responsible and benefiting more people? Or, how to make it WORK? In this workshop, participants will learn the skills and frameworks to map out the social impact of technologies and link the impact with various groups of users and their needs. Through the interactive mapping activity, participants are encouraged to develop their own narratives and stories of technology and use them in practical scenarios such as communication and outreach activities.

Participants don’t need prior knowledge of mapping; they are expected to learn some basic social science concepts during the mapping activities.

Urban Planning, Kennesaw State University

Designing environmental-friendly technologies and developing low-emission cities are the major goals of nations worldwide. Building professionals in Environmental Building Assessment (EBA) are attempting to be proactive in the building industry toward green and low-emission building design. Building façade is one of the most complex systems coupling construction, structural engineering, environmental engineering, architectural and aesthetic aspects. Recently, eco-labeling facades, so-called dynamic facades, have captured the attention of building professionals. Designing the dynamic façade is the trade-off between environmental data (such as luminance and solar radiation) and user comfort and satisfaction. The lack of comprehensive studies on dynamic facades’ structure has persuaded us to explore their response and adaptability to external and internal behavior changes of light and thermal intensity. In particular, this study aimed to investigate state-of-the-art dynamic facades by indicating their typologies, technologies, and techniques in energy saving, user’s thermal and visual comfort, Indoor Air Quality, and acoustic control. Furthermore, the study found that, as dynamic façades vary, the building simulation tools can analyze and evaluate them from diverse aspects; mainly, i) Design (design for flexibility and modularity, aiming full customization to specific requirements), ii) Materials (using micro and nanomaterials and processing techniques with the improved technical and functional performances), iii) Engineering system (using advanced control and monitoring systems for smart behavior of the building envelope), and iv) Architecture (considering the aesthetical acceptance of the building façade). Considering all mentioned aspects, double-skin facades, smart glass, integrated façades, and shading facades are the most promising dynamic façade systems that potentially reduce energy.

Economics, Georgia Tech

Using test score data for K-12 schools in South Atlanta, we find that schools within 500m of interstate highways have 20% lower standardized test pass rates than similar-demographic schools greater than 1km from the highway. To investigate the role of air pollution on cognition, we obtained funding to deploy commercially available PM2.5 sensors in underserved schools near the highway and their statistical twins far from the highway. We describe the monitoring project design, data, and preliminary results. South Atlanta is relatively poor and majority non-white relative to the northern part of the city. The southern half of the city is also distinguished by the prevalence of industries and transportation corridors in closer proximity to schools and residential communities, likely a legacy of past racial bias in land-use planning, and the paradoxical absence of public and private air quality monitors – especially in comparison to the north that has more than a dozen PM2.5 monitors. Thus, this monitoring effort also has potential to reveal information about inequities in environmental exposures for underserved communities.

Environmental Engineering, Georgia Tech

Increases in E-commerce over the last 5 to 10 years has increased demand for warehouse space and distribution centers. In response, warehouses and distribution centers are increasing in number, size, and closeness to urban areas. With increased warehouse activity comes environmental justice concerns about the siting of warehouses and about potential increases in traffic-related air pollution (TRAP) from large diesel trucks. The goal of this research is to better understand present-day capability to pinpoint and quantify warehouse associated emissions and impacts on air quality. For this presentation, we focus on the Greater Los Angeles area from 2018 to 2022 and use Community Multiscale Air Quality Modeling System (CMAQ). CMAQ modeling was performed at a 4-km resolution using the EPA National Emissions Inventory. TROPOspheric Monitoring Instrument (TROPOMI) satellite NO2 retrievals were used as remote observations to compare to the model. In our analysis of Fontana, a high-density location in the Greater Los Angeles area, 3 NO2 hotspots were identified: the first originating over downtown Los Angeles, the second overlapping a high concentration of warehouses and distribution centers in the city, and the third covering downtown San Bernardino. These increased NO2 hotspots persisted across multiple years, were discernible from one another in the seasonal analysis, and presented in both the CMAQ model and TROPOMI satellite data.

Environmental Engineering, Georgia Tech

Formaldehyde (HCHO) is a carcinogenic volatile organic compound (VOC) that is dominantly produced in the atmosphere through secondary oxidation and contributes to over half of the total cancer risks related to all hazardous air pollutants (HAPs) in the US. Chemical transport models (CTMs) are often used to estimate HCHO concentrations and its related risks, although urban HCHO enhancement estimates are often impacted by uncertainties in emission inventories and from model configuration. Here, we use 1-month simulations in July 2020 around Atlanta using the WRF-GC regional air quality model to assess the response of modeled HCHO concentrations to changes in urban biogenic VOC (BVOC), rural BVOC, anthropogenic VOC (AVOC), and nitrogen dioxide (NOx¬) emissions, at ±50% of each emission category. Using our model setup, urban HCHO in Atlanta is sensitive to changes in BVOC (both urban and rural) and NOx emissions by a ±15% difference, whereas AVOC emissions do not show significant impact to modeled HCHO (<5%). A source contribution analysis identifies rural BVOC sources to be the largest source of urban HCHO (37%), followed by urban BVOCs (31%), background HCHO (24%), and AVOCs (8%). Comparison of simulations at four different horizontal resolutions (4.4 km, 7.4 km, 11 km, and 22 km) demonstrate that 4.4 km and 7.4 km yield similar HCHO concentrations, and 22 km simulations are biased low by <15% in urban regions. Whereas modeled HCHO responds to emission perturbations more linearly at 4.4 km, such responses shift in the positive direction at 22 km, with the largest differences in the +50% NOx scenarios at +23% (22 km) vs. +12% (4.4 km). Model resolution impacts population based HCHO exposure with differences of up to 13% in median values. A co-benefit analysis shows that a 50% reduction in urban anthropogenic NOx would reduce median urban exposure by ~7%, and up to 20% in the highest-HCHO regions.

Environmental Engineering, Georgia Tech

Regulatory actions in the US have improved urban air quality by decreasing emissions from a range of sources, including power plants. A question arises as to how much the policies on power plant emissions have led to air quality improvements compared to other factors. Particularly, the large decline in natural gas prices in the late 2000s incentivized use of natural gas over coal, which decreased emissions and challenges efforts to attribute air quality improvements to regulatory actions. Our work separates the impacts of regulations and fuel prices on air pollution in Atlanta and New York City between 2006 and 2019. We developed a novel method that that links emission changes to air quality improvements by connecting an economic model of electricity generation to a machine learning model trained on emissions, meteorology, and pollutant data. From these models, we estimate counterfactual (hypothetical) air pollutant concentrations under different historical fuel price scenarios. When compared to observed emissions and air quality, these counterfactual scenarios identify the impact of cheaper natural gas on power plant emissions and resultant air pollution to better isolate the individual impact of prior regulations on air quality. Such information can be used to estimate the health benefits of past controls and aids the development of effective future emissions reductions strategies. The method is found to provide robust economic and environmental analyses without the need for computationally expensive or proprietary models, which can aid future research that aims to link changes in electricity generation to urban air quality and health.

Economics, Georgia State University

We examine the relationship between contemporaneous fine particulate matter exposure and COVID-19 morbidity and mortality using an instrumental variable approach. Harnessing daily changes in county-level wind direction, we show that arguably exogenous fluctuations in local air quality impact the incidence of confirmed COVID-19 cases and deaths. We find that a one $\mu g / m^3$ increase in PM 2.5, or 15\% of the average PM 2.5 concentration in a county, increases the number of same-day confirmed cases by 1.8\% from the mean case incidence in a county. A one $\mu g / m^3$ increase in PM 2.5 increases the same-day death rate by just over 4\% from the mean. These effects tend to increase in magnitude over longer time horizons and are robust to a host of sensitivity tests. When analyzing potential mechanisms, we also demonstrate that an additional unit of PM 2.5 increases COVID-19-related hospitalizations by 0.8\% and use of intensive care units by 0.5\% on the same day. Using individual case records, we also show that higher PM 2.5 exposure at the time of case confirmation increases risk of later mechanical ventilation and mortality. These results suggest that air pollution plays an important role in mediating the severity of respiratory syndromes such as COVID-19.

Interdisciplinary Engineering, Kennesaw State University

The full research project is to sample fine particulate at elementary school carpools. We need to verify the samplers are calibrated. One sampler was collocated with EPD monitor and calibrated. Now three samplers will be calibrated to the one. Data and statics will be shown.