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As engineering programs have begun to infuse sustainability into their undergraduate curricula, assessment tools are needed to further inform these reform efforts. The goal of this project was to demonstrate the use of a new rubric to examine students' abilities to engage in sustainable design. The rubric includes 16 sustainable design criteria and rating scales to capture student performance and instructor/sponsor requirements. Three judges used the rubric to evaluate 40 capstone design projects completed between 2002 and 2011 by civil and environmental engineering seniors at a large, research intensive university. Results indicate that sustainable design performance in the capstone course changed little over 10 years, despite efforts to integrate sustainability into the curriculum. Students tended to address those criteria that were explicitly required of them by instructors or external project sponsors, which were related to social sustainability more than other sustainability dimensions. As a result, more explicit integration of sustainable design requirements into capstone courses may be needed to ensure that students understand the importance of, and are able to practice, developing designs in a sustainable manner.

This study applied a synthetic control method (SCM) to investigate the impacts of state electric vehicle purchase incentives implemented in the United States between 2011 and 2018. The goal was to develop a model to replicate the impacts of PEV (plug-in electric vehicle) incentives on vehicle sales given the socio-economic characteristics of the treatment states. The goodness-of-fit between trajectories reproduced by SCM and the corresponding treatment region provides a clear means of visualizing the effectiveness of the model and results. For example, the results show that Georgia income tax credits appear to have induced 17,000 BEV (battery electric vehicle) sales between January 2011 and July 2015. The SCM analysis was also applied to other states, showing that the SCM methodology can represent PEV sales in many states in the United States. Accordingly, the modeling results suggest that incentives implemented in some U.S. states were effective in promoting PEV sales. The study also concluded that the SCM with a weighting factor between 0 and 1 (i.e., extrapolation avoided) may not be the approach of a choice for the states whose demographic/economic attributes significantly deviate from the control regions, or the states that implement "unique" programs, because there are insufficient system data for counterfactual analysis. [ABSTRACT FROM AUTHOR]

Localized carbon reduction strategies are especially critical in states and regions that lack top-down climate leadership. This paper illustrates the use of coupled systems in assessments of subnational climate solutions with a case study of Georgia, a state located in the southeastern United States that does not have statewide climate goals or plans. The paper illustrates how robust place-specific plans for climate action could be derived from foundational global and national work and by embedding that research into the context of socio-ecological-technological systems. Our replicable methodology advances the traditional additive sectoral wedge analysis of carbon abatement potential by incorporating solution interdependencies and by spanning both carbon sources and sinks. We estimate that a system of 20 solutions could cut Georgia's carbon footprint by 35% in 2030 relative to a business-as-usual forecast and by 50% relative to Georgia's emissions in 2005. We also produce a carbon abatement cost curve that aligns private and social costs as well as benefits with units of avoided CO2-e. The solutions are affiliated with various social cocosts and co-benefits that highlight societal concerns extending beyond climate impacts, including public health, environmental quality, employment, and equity. [ABSTRACT FROM AUTHOR]

Subnational entities are recognizing the need to systematically examine options for reducing their carbon footprints. However, few robust and comprehensive analyses are available that lay out how US states and regions can most effectively contribute. This paper describes an approach developed for Georgia—a state in the southeastern United States called "Drawdown Georgia", our research involves (1) understanding Georgia's baseline carbon footprint and trends, (2) identifying the universe of Georgia-specific carbon-reduction solutions that could be impactful by 2030, (3) estimating the greenhouse gas reduction potential of these high-impact 2030 solutions for Georgia, and (4) estimating associated costs and benefits while also considering how the solutions might impact societal priorities, such as economic development opportunities, public health, environmental benefits, and equity. We began by examining the global solutions identified by Project Drawdown. The resulting 20 high-impact 2030 solutions provide a strategy for reducing Georgia's carbon footprint in the next decade using market-ready technologies and practices and including negative emission solutions. This paper describes our systematic and replicable process and ends with a discussion of its strengths, weaknesses, and planned future research. [ABSTRACT FROM AUTHOR]

This article presents findings from a study on residential development patterns and urban heat island formation in the Atlanta, Georgia, metropolitan region. High-resolution thermal imagery collected by the National Aeronautical and Space Administration (NASA) is used in conjunction with parcel-level tax records to examine the interaction between the design of single-family residential parcels and the emission of radiant heat energy. Re-suits from a path analysis illustrate that lower density patterns of residential development contribute more radiant heat energy to surface heat island formation than higher density development patterns within the Atlanta region. Compact moderate-to-high-density new construction and area-based tree ordinances are recommended as policy strategies for mitigating the effects of urban development on regional climate change. [ABSTRACT FROM AUTHOR]

• Proposed a two-phase data-driven modeling framework for EV purchase and adoption prediction. • Combined the modeling of household potential for adopting EVs with the assignment of EV use to specific trips in the assessment of energy use and emissions before-and-after EV adoption. • Demonstrated a network level of 40% reduction in energy consumption and 25% reduction in greenhouse gas emissions under 5% and 10% EV market penetration scenarios. • Compared with two averaging methods for avoidance of overestimation of EV impacts and benefits. In this paper, a methodological framework is proposed to assess the potential of electric vehicle (EV) penetration and corresponding reduction in energy use and emissions in Georgia, U.S., using 2017 National Household Travel Survey data. A two-phase, data-driven model assesses the potential for household purchases of EVs and the assignment of EVs to household trips. Households sharing the highest similarities are selected as candidates for EV purchases, with household trips identified as EV-amenable or not. Potential EV-purchasing families were also matched to specific EV makes and models. Energy use, greenhouse gas emissions, and criteria air pollutants were analyzed and compared for all original trips and for those trips that shifted to EVs. By comparing against two traditional averaging methods, the framework demonstrates an advancement that helps to avoid the overestimation of EV benefits. By integrating household-level demographics and trip-level attributes from open-source travel survey data in EV adoption and trip assignment, this paper demonstrates the benefits associated with EV adoption (a potential 45% reduction in energy consumption and 30% reduction in greenhouse gas emissions), moreover, the proposed methodology could serve as an innovative framework that is scalable and transferable to predict the future market penetration and actual on-road EV activities under various contexts. [ABSTRACT FROM AUTHOR]

This research evaluated the accessibility of federal- and states-level Plug-in Electric Vehicles (PEVs) Income Tax Credits (ITC) policy in the United States, and identified potential barriers for households with diverse income levels, family types and number of children in participation. For example, a two-adults one-child family with an annual income of $82,600 (2019 U.S. national median income for three-people family) is eligible for only 70% of $7,500 federal ITC. Credits are even less available for families with lower income or more children. Based on a demographic case study in Georgia, 62.1% of Atlanta households are not eligible for full federal ITC. Further complicating any policy benefits assessments is that vehicles from lower-income households (less eligible for ITCs) produce higher emissions, which would yield criteria pollutant emission reduction benefits if replaced with PEVs. The study provided a reference for policy-makers to identify potential equity issues concealed in PEV tax credit programs. [ABSTRACT FROM AUTHOR]

Cyclists and pedestrians account for a disproportionate amount of the world's 1.3 million road deaths every year. This is a growing problem in the United Sates where bicyclist and pedestrian fatalities have increased steadily since 2009. A large body of research suggests vehicle speeds are a key contributing factor for crashes. However, few studies of bicycle or pedestrian crash probability incorporate detailed vehicle speed data. This study uses probe vehicle speed data to examine the impact of vehicle speeds on bicycle and pedestrian crashes on the state of Georgia's network of major arterial roadways. The analysis examines 7000 road segments throughout the state in 2017. A Negative Binomial model relates annual crash and speed data on each segment. Models using speed percentiles (85th, 50th and 15th) are contrasted with models using speed differences (85th-50th and 50th-15th percentile). A small set of covariates are included: segment length, number of lanes, Average Annual Daily Traffic, and urbanicity. Results indicate that larger differences in high-end speed percentiles are positively associated with bicycle and pedestrian crash frequency on Georgia arterials. Furthermore, the coefficients on the high end of the speed distribution, measured by the difference in 85th and 50th percentile speeds, have greater magnitude and statistical significance than the low end of the distribution. This research shows a negative relationship between speed and crashes may be flawed, as it does not account for the distributions of speed. The findings in this study suggest that planners and engineers should identify areas with large speed distributions, especially at the high vehicle speeds, and work to reduce the fastest speeds on these roadways. To do so, differences in speed percentiles measured using probe vehicle speeds can be used to determine where high risk areas are located., (Copyright © 2021. Published by Elsevier Ltd.)

Based on requirements under the Clean Air Act Amendments of 1990, most state vehicle inspection and maintenance (I/M) programs have, since 2002, replaced the tailpipe emission testing with the on-board diagnostic (OBD) II testing for 1996 model and newer vehicles. This test relies on the OBD II system to give the pass or fail result, depending on certain conditions that might cause the vehicle to emit pollution 1.5 times higher than the regulated standard. The OBD II system is a computer and sensors installed in the vehicle to monitor the emission control units and signal if there is any malfunction. As a vehicle ages, its engine, pollution control units, and OBD II system deteriorate. Because the OBD II system's durability directly influences the test outcome, it is important to examine the fleetwide trend in the OBD II test results in comparison with an alternative measure of identifying high emitting vehicles. This study investigates whether the validity and reliability of the OBD II test is related to the age of the OBD II system installed in the fleet. Using Atlanta's I/M testing records and remote sensing device (RSD) data collected during 2002-2005, this research establishes the convergent validity and interobserver reliability criteria for the OBD II test based on on-road emissions measured by RSDs. The study results show that older vehicles exhibit significantly lower RSD-OBD II outcome agreement than newer vehicles. This suggests that the validity and reliability of the OBD II test may decline in the older vehicle fleets. Explanations and possible confounding factors for these findings are discussed.

The research presented in this paper employs the Step Method of Inspection/Maintenance (I/M) program evaluation to estimate the emissions reduction for an Atlanta I/M program. Stedman et al. (Stedman, D. H.; Bishop, G. A.; Aldrete, P.; Slott, R. S. Environ. Sci. Technol. 1997, 31, 927-931) introduced the Step Method of evaluation when they presented the results of a 1995 Denver I/M program evaluation. The research presented here replicates the original Denver Step Method analysis for a 1997 Atlanta I/M program. This evaluation was conducted separately for the nine outlying Atlanta counties and the four counties that are closest to the center of the city. The results of the analysis are similar to those found by Stedman et al. in Denver. While the Denver carbon monoxide (CO) weighted program benefit was 6.9%, the Atlanta area CO weighted program benefit is found to be 11.5% and 4.9% for the nine-county and four-county Atlanta areas, respectively. We conclude that the 1997 I/M program change in Atlanta yielded a noteworthy and observable change in fleet emissions.

On-road remote sensing data is an increasingly popular source of evaluation information for vehicle inspection/maintenance (I/M) programs. This article conducts one such remote sensing data evaluation for the Atlanta, Georgia, I/M program. The reference method involves comparing emissions differences in I/M and non-I/M fleet vehicles with those predicted by a regulatory computer model. Assuming that on-road emissions differences represent observed effectiveness and model-predicted emissions differences represent effectiveness goals, the Atlanta enhanced I/M program appears to be achieving 83% of its targeted emissions reductions. The method compares favorably with other remote sensing evaluation methods in its ability to be applied over time and its relatively small sample size requirement. The chief limitation to the approach is its reliance on a representative non-I/M fleet, which may differ in characteristics for which controls are difficult to locate. Such potential confounding factors include discrepancies in maintenance trends, socioeconomic conditions, and vehicle quality.