The Transportation Research Board of the National Academies identifies nine current and critical issues facing the United States transportation sector: congestion, environmental preservation, deteriorating infrastructure, inadequate funding, social equity issues, susceptibility to natural disasters, insufficient safety improvements, outdated government institutions and a lack of investment in innovation. All of these issues directly threaten the sustainability of transportation in the United States. While numerous transportation stakeholders have presented definitions of sustainable transportation, there is significant variation and disagreement over what sustainability actually means in transportation. The absence of a coherent, universal definition has undermined the overall effectiveness of transportation plans, policies and programs, including the current federal highway authorization, the Moving Ahead for Progress in the 21st Century Act (MAP-21) as well as the Congestion Mitigation and Air Quality Improvement (CMAQ) program. Through examining the definitions of sustainable transportation put forth by the European Union, Transport Canada, the Transportation Research Board (TRB), the American Association of State Highway and Transportation Officials (AASHTO), the Interagency Partnership for Sustainable Communities and various state departments of transportation (DOTs), this report seeks to establish a clear definition of sustainable transportation, adopt applicable sustainable transportation indicators and offer meaningful recommendations that help strengthen the overall sustainability of MAP-21 and the CMAQ program. / text

Meteorological variables such as temperature, wind speed, wind directions, and Planetary Boundary Layer (PBL) heights have critical implications for air quality simulations. Sensitivity simulations with five different PBL schemes associated with three different Land Surface Models (LSMs) were conducted to examine the impact of meteorological variables on the predicted ozone concentrations using the Community Multiscale Air Quality (CMAQ) version 4.5 with local perspective. Additionally, the nudging analysis for winds was adopted with three different coefficients to improve the wind fields in the complex terrain at 4-km grid resolution. The simulations focused on complex terrain having valley and mountain areas for ozone SIPs (State Implementation Plans). The ETA M-Y (Mellor-Yamada) and G-S (Gayno-Seaman) PBL schemes were identified as favorite options and promote O3 formation causing the higher temperature, slower winds, and lower mixing height among sensitivity simulations in the area of study. It was found that PX simulation did not always give optimal meteorological and CMAQ model performances at mountain sites. The results of nudging analysis for winds with three different increased coefficients’ values (2.5, 4.5, and 6.0 x 10-4 per second) over seven sensitivity simulations show that the meteorological model performance was enhanced due to improved wind fields, indicating the FDDA (Four Dimensional Data Assimilation) nudging analysis can improve model performance considerably at 4-km grid resolution. Specifically, the sensitivity simulations with the coefficient value (6.0 x 10–4) yielded more substantial improvements than with the other values (2.5 and 4.5 x 10-4). Hence, choosing the nudging coefficient of 6.0 x 10-4 per second for winds in MM5 may be the best choice to improve wind fields as an input, as well as, better model performance of CMAQ in the complex terrain area. The sensitivity of RRFs (Relative Response Factors) to the PBL scheme may be considerably significant with about 1-3 ppb in difference in determining whether the attainment test is passed or failed. Finally, a finer grid resolution was necessary to evaluate and access of CMAQ results for giving a detailed representation of meteorological and chemical processes in the regulatory modeling.

Fine particulate matter (PM2.5) has been associated with adverse effects on human health, but whether specific components of PM2.5 are responsible for specific health effects is still under investigation. The complex chemical composition of PM2.5 and issues such as multi-component interactions, spatial variability and sampling/instrument error further complicates this analysis. A complementary approach to examining species-specific associations is to assess associations between health outcomes and sources contributing to PM2.5, which can provide critical information to regulators to tighten controls on sources that contribute most to adverse health effects and allows for better multi-pollutant epidemiologic analyses, as the number of source-categories is typically far less than the number of PM2.5 species. This study develops and evaluates various air quality modeling approaches for determining daily source contributions to ambient PM2.5. Results from long-term air quality simulations using an emissions-based model (Models-3/CMAQ - Community Multiscale Air-Quality model) were evaluated in terms of the model's ability to simulate short-term (e.g., daily) variability in concentrations of PM2.5 components. To examine source-specific health outcomes, an extended PM2.5 source-apportionment model, CMB-LGO (Chemical Mass Balance incorporating the Lipschitz Global Optimizer) was developed and compared with results based on other approaches such as CMB, PMF (Positive Matrix Factorization), and Models-3/CMAQ in terms of simulating the daily variability of source impacts. Based on findings from spatial and temporal analyses of tracer concentrations and source impacts, PM2.5 source-apportionment results from CMB-LGO and PMF were applied in a health-study for the Atlanta area. Despite methodological differences and uncertainties in the apportionment process, good agreement was observed between the CMB-LGO and PMF based risk ratios, indicating to the usefulness of applying apportionment methods in health studies.

Impacts of Climate-responsive Controls and Land Usage on Regional Climate and Air Quality Marcus A. Trail 201 pages Directed by Dr. Armistead G. Russell Regional air quality impacts public health, visibility and ecosystem health, and is significantly affected by changes in climate, land use and pollutant emissions. Predictions of regional air quality responses to such changes can help inform policy makers in the development of effective approaches to both reduce greenhouse gases and improve air quality. However, major sources of uncertainty exist in predicting future air quality including limitations in the tools used to project future emissions, land use changes and uncertainties associated with predicting future climate. Recently, technical advances in downscaling global climate simulations to regional scales, and, the development of bottom-up operational tools used to forecast emissions have enhanced our ability to account for the complex interactions between population, socio-economic development, technological change, and federal and regional environmental policies. The results show that emissions reductions strategies will continue to play a vital role in improving air quality over the U.S. while CO2 emission reduction policies can have mixed positive and negative impacts on air quality. However, additional costs will be necessary to reach air quality goals due to climate change because deeper emission reductions will be required to compensate for a warmer climate, even if current efforts are predicted to show improvement. The results of this study also show that regional climate and O3 and aerosol concentrations are highly sensitive to reforestation and cropland conversion in the Southeast and these land use changes should be considered in air quality management plans.

The fine and ultra fine size of diesel particulate mater (DPM) are of great health concern and significantly contribute to the overall cancer risk. In addition, diesel particles may contribute a warming effect on the planet's climate. The composition of these particles is composed principally of elemental carbon (EC) with adsorbed organic compounds, sulfate, nitrate, ammonia, metals, and other trace elements. The purpose of this study was to depict the seasonality and modeling of particulate matter in the Southeastern US produced by the diesel fueled sources (DFSs). The modeling results came from four one-month cases including March, June, September, and December to represent different seasons in 2003 by linking Models-3/CMAQ and SMOKE. The 1999 National Emissions Inventory Version 3 (NEI99) was used in this analysis for point, area, and non-road sources, whereas the National Mobile Inventory Model (NMIM) was used to create the on-road emissions. Three urban areas, Atlanta, Birmingham, and Nashville were selected to analyze the DPM emissions and concentrations. Even though the model performance was not very strong, it could be considered satisfactory to conduct seasonal distribution analysis for DPM. Important hourly DPM seasonality was observed in each city, of which higher values occurred at the morning traffic rush hours. The EC contributions of primary DPM were similar for all three sites (~ 74%). The results showed that there is no significant daily seasonality of DPM contribution to PM2.5 for any of these three cities in 2003. The annual DPM contribution to total PM2.5 for Atlanta, Nashville, and Birmingham were 3.7%, 2.5%, and 2.2%, respectively.

This work is aimed to study the capabilities of CMAQ and WRF-Chem models for predicting the PM10 and PM2.5 pollution in the west side of Saudi Arabia. To do this fairly, one-month simulations (April, 2021) are done in both models using same initial and boundary conditions, meteorology and anthropogenic emissions. Unique configurations in both models allow to compare differences in the chemical processes and natural emissions estimation of each model. Simulated PM (PM10 and PM2.5) surface concentrations and AOD are compared with available observations to assess models’ performance. Moreover, CMAQ is used to study a real air pollution episode generated by a fire in the Rabigh Electricity Power Station between April 8 and April 11, 2021.

Air quality in the Shenandoah Valley has deteriorated in recent years. The valley exceeds the National Ambient Air Quality Standards for ozone (O3) a few days each year, and with stricter fine particulate matter (PM2.5) standards coming into effect, the valley risks exceeding those as well. Visibility is poor in the valley region, and the haze obscures the spectacular vistas from the Shenandoah National Park. To solve the growing problem local governments in the valley joined forces to find economically and politically feasible ways to reduce air pollution. In this study we aim to provide the scientific basis for air quality management strategies through modeling the sensitivity of various pollutants to changes in emissions. We distinguish between locally generated versus regionally transported air pollution as well as assess the impacts of proposed local air pollution control measures on ambient air quality in the valley. The first part of this thesis assesses air pollutant emissions in the Shenandoah Valley. Emissions were assigned to one of 14 source categories and allocated by county or city. Biogenic sources were responsible for 56% of the volatile organic compounds (VOCs) emitted in the valley. VOCs are important because they, together with nitrogen oxides (NOx) react to form O3 in the presence of sunlight. On-road and off-road mobile sources were the largest anthropogenic sources of VOCs as well as 63% of the NOx. PM2.5 emissions were not dominated by any single source, but fuel combustion, dust, and agriculture were important contributors. The second part of this thesis focuses on modeling ambient air pollution concentrations in the Shenandoah Valley based on the emissions generated in the first portion. We developed a set of three alternative emissions scenarios for comparison to the base case. We first zeroed anthropogenic emissions in the valley, allowing us to determine how much pollution was produced by local sources versus transported into the valley from upwind areas. We then developed a scenario that contained nine different pollution reduction strategies being considered by local governments. Finally we modeled a similar scenario in which we predicted the impact of ten proposed greenhouse gas reduction strategies on concentrations of O3 and PM2.5. We found that PM2.5 concentrations fell when emissions in the valley were reduced, but O3 did not. PM2.5 concentrations fell by 26-57% for the Zero Case and by 10-27% for the other two cases, depending on the time of year and location. Conversely for O3 there was either no change in most seasons or a small increase in concentrations in the fall. These results suggest that PM2.5 in the valley can be controlled with local measures but O3 is a more geographically wide problem. / Master of Science

In this thesis, I apply the adjoint for the Community Multiscale Air Quality model (hereafter CMAQ-ADJ) in a high spatial resolution study of the sensitivity of ozone to several of its precursors in the regions surrounding the Great Lakes. CMAQ-ADJ was originally developed for low spatial resolution applications. In order to use it in high spatial resolution (12 km) studies, it was necessary to resolve a conflict between the pre-set fixed output time step interval in CMAQ-ADJ and the CMAQ-calculated irregular synchronization time-step and also to modify the meteorological interface for the backward model integrations. To increase computation efficiency, the chemistry time-step in the modified CMAQ-ADJ is checkpointed instead of being re-calculated in the backward part of the model as before. I used the modified model to analyze the sensitivity of ozone to precursor species for cases of assumed high ozone episode in two target locations in southwestern and east-central Ontario. The studies examined the influence of pre-existing ozone, NO, CO, anthropogenic volatile organic compounds (VOCs) and isoprene on ozone level changes for the 69 hours immediately preceding the assumed high ozone event. The results are dominated by the long-distance advection, local meteorology (lake breezes), air temperature, the underlying surface features, and emissions in the pollutant pathway. Both production and titration of ozone by NOx is evident at different times and locations in the simulations. The industrial Midwest U.S. and Ohio Valley have been shown to be an important source of anthropogenic emission of NO and most VOCs that contribute to high ozone events in southwestern and east-central Ontario. Isoprene from the northern forest suppresses ozone in both target regions, with a greater magnitude in east-central Ontario. The response of ozone level in the two selected receptor regions in Ontario to different VOCs depends on the type of VOC, the time and location they are emitted, and the air temperature. Increasing VOC emissions in urban areas such as Toronto and Ottawa in the morning can enhance the ozone level by late afternoon. Increasing VOCs except ethylene and formaldehyde in regions with large VOC/NOx ratio in the morning tends to suppress the ozone level by late afternoon. Among all the species examined, NO has the largest impact on the target ozone level changes. CO is very unlikely to significantly influence the ozone level changes in southwestern or east-central Ontario.

In this thesis, I apply the adjoint for the Community Multiscale Air Quality model (hereafter CMAQ-ADJ) in a high spatial resolution study of the sensitivity of ozone to several of its precursors in the regions surrounding the Great Lakes. CMAQ-ADJ was originally developed for low spatial resolution applications. In order to use it in high spatial resolution (12 km) studies, it was necessary to resolve a conflict between the pre-set fixed output time step interval in CMAQ-ADJ and the CMAQ-calculated irregular synchronization time-step and also to modify the meteorological interface for the backward model integrations. To increase computation efficiency, the chemistry time-step in the modified CMAQ-ADJ is checkpointed instead of being re-calculated in the backward part of the model as before. I used the modified model to analyze the sensitivity of ozone to precursor species for cases of assumed high ozone episode in two target locations in southwestern and east-central Ontario. The studies examined the influence of pre-existing ozone, NO, CO, anthropogenic volatile organic compounds (VOCs) and isoprene on ozone level changes for the 69 hours immediately preceding the assumed high ozone event. The results are dominated by the long-distance advection, local meteorology (lake breezes), air temperature, the underlying surface features, and emissions in the pollutant pathway. Both production and titration of ozone by NOx is evident at different times and locations in the simulations. The industrial Midwest U.S. and Ohio Valley have been shown to be an important source of anthropogenic emission of NO and most VOCs that contribute to high ozone events in southwestern and east-central Ontario. Isoprene from the northern forest suppresses ozone in both target regions, with a greater magnitude in east-central Ontario. The response of ozone level in the two selected receptor regions in Ontario to different VOCs depends on the type of VOC, the time and location they are emitted, and the air temperature. Increasing VOC emissions in urban areas such as Toronto and Ottawa in the morning can enhance the ozone level by late afternoon. Increasing VOCs except ethylene and formaldehyde in regions with large VOC/NOx ratio in the morning tends to suppress the ozone level by late afternoon. Among all the species examined, NO has the largest impact on the target ozone level changes. CO is very unlikely to significantly influence the ozone level changes in southwestern or east-central Ontario.

Cyclic volatile methyl siloxanes (cVMS) are anthropogenic chemicals present in a range of consumer personal care products such as antiperspirants and lotions. They are highly volatile, and readily released to the atmosphere by personal care product use. Generally unreactive, they are found in high concentrations in indoor environments, and transported long distances in the atmosphere. A major removal pathway for these silicon-containing gases is reaction with the OH radical, which has been recently shown to yield secondary Si-containing aerosol compounds in addition to the gas phase products. Despite the significance of the atmospheric fate of these compounds, much of the previous work has focused on the aquatic fate, and almost exclusively on the parent compounds. The oxidation products and potential aerosol species have received much less attention, with almost no ambient measurements or experimental physical property data. This work investigates cVMS with a focus on providing much needed information on potential loadings of the oxidation products, their distribution, and particle phase properties using an atmospheric model and laboratory experiments. Specifically, cVMS was added to the Community Multiscale Air Quality (CMAQ) model; expected concentrations, spatial distribution, and seasonal trends were quantified; cVMS secondary aerosols generated and physical properties characterized; and secondary aerosol parameters for atmospheric modeling developed. The CMAQ model code was modified to update the chemical mechanism with cVMS, develop emissions, boundary, and deposition parameters to simulate four separate seasons at a spatial resolution of 36 km over North America. Typical model concentrations showed parent compounds were highly dependent on population density as cities had monthly averaged peak decamethylcyclopentasiloxane (D5) concentrations up to 432 ng m−3. Peak oxidized D5 concentrations were significantly less, up to 9 ng m−3, and were located downwind of major urban areas. Model results were compared to available measurements and previous simulation results. Parent compound concentrations in urban locations were sensitive to transport factors, while parent compounds in rural areas and oxidized product concentrations were influenced by large-scale seasonal variability in OH. Secondary aerosols were formed by reacting cVMS gas in an oxidation flow reactor. The particles were characterized for concentration, size, aerosol yield, morphology, energy-dispersive spectroscopy (EDS) individual particle chemical composition, hygroscopicity (cloud condensation nuclei formation potential), and volatility. Aerosol concentrations were 68 – 220 µg m-3 with aerosol mass fractions (i.e. yields) of 0.22-0.50. Aerosol yield was sensitive to chamber OH, indicating an interplay between oxidation conditions and the concentration of lower volatility species. The D5 oxidation products were non-volatile, with only the smallest particles (10 nm) exhibiting more than 4% of diameter decrease upon heating to 190°C temperature. The D5 oxidation aerosols were relatively non-hygroscopic, with average hygroscopicity kappa of ~0.01. Experimental data was analyzed to develop secondary aerosol parameters for the CMAQ model. Chamber yield data was fit to a two-product Odum volatility model with yield values of 0.14 and 0.82, corresponding to saturation concentrations of 0.95 and 484 µg m-3, respectively. The recommended enthalpy of vaporization is 18 kJ mol-1 based on other modeled secondary organic aerosol. Recommended molecular weights for the D5 low volatility Odum, high volatility Odum, and non-volatile oligomerization species are 588, 373, and 733 g mol-1 corresponding to OH substituted ring-opened, monomer, and dimer species, respectively. This work provides simulations of expected concentrations, spatial patterns, and seasonal influence of the parent and oxidized cVMS species to extend beyond the few parent cVMS measurements and nonexistent oxidation product measurements. The modeling work serves as an important tool to guide future field measurements especially important for the confirmation of particle phase oxidation products. Extensive aerosol characterization measurements provide much needed physical property data important for future modeling, risk, and exposure studies.