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Description
The Toledo Core Based Statistical Area (CBSA) presents an interesting case study for the new sulfur dioxide (SO2) one hour standard. Since no SO2 monitor within 75 miles to estimate the attainment status of the area, American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) was used in this study to predict potential problems associated with the newly revised standard. The Toledo CBSA is home to two oil refineries, a glass making industry, several coal fired lime kilns, and a sulfuric acid regeneration plant, The CBSA 3 has coal fired power plants within a 30 mile radius of its center. Additionally, Toledo is a major Great Lakes shipping port visited by both lake and ocean going vessels. As a transportation hub, the area is also traversed by several rail lines which feed four rail switching yards. Impacts of older generation freighters, or "steamers", utilizing high sulfur "Bunker C" fuel oil in the area is also an issue. With the unique challenges presented by an SO2 one hour standard, this study attempted to estimate potential problem areas in advance of any monitoring data being gathered. Based on the publicly available data as inputs, it appears that a significant risk of non-attainment may exist in the Toledo CBSA. However, future on-the-books controls and currently proposed regulatory actions appear to drive the risk below significance by 2015. Any designation as non-attainment should be self-correcting and without need for controls other than those used in these models. The outcomes of this screening study are intended for use as a basis for assessments for other mid-sized, industrial areas without SO2 monitors. The results may also be utilized by industries and planning groups within the Toledo CBSA to address potential issues in advance of monitoring system deployment to lower the risk of attaining long term or perpetual non-attainment status.
ContributorsMyers, Greg Francis (Author) / Olson, Larry (Thesis advisor) / Edwards, David (Committee member) / Hristovski, Kiril (Committee member) / Arizona State University (Publisher)
Created2011
Description
As air quality standards become more stringent to combat poor air quality, there is a greater need for more effective pollutant control measures and increased air monitoring network coverage. Polluted air, in the form of aerosols and gases, can impact respiratory and cardiovascular health, visibility, the climate, and material weathering. This work demonstrates how traditional networks can be used to study generational events, how these networks can be supplemented with low-cost sensors, and the effectiveness of several control measures. First, an existing network was used to study the effect of COVID-19 travel restrictions on air quality in Maricopa County, Arizona, which would not have been possible without the historical record that a traditional network provides. Although this study determined that decreases in CO and NO2 were not unique to the travel restrictions, it was limited to only three locations due to network sparseness. The second part of this work expanded the traditional NO2 monitoring network using low-cost sensors, that were first collocated with a reference monitor to evaluate their performance and establish a robust calibration. The sensors were then deployed to the field to varying results; their calibration was further improved by cycling the sensors between deployment and reference locations throughout the summer. This calibrated NO2 data, along with volatile organic compound data, were combined to enhance the understanding of ozone formation in Maricopa County, especially during wildfire season. In addition to being in non-attainment for ozone standards, Maricopa County fails to meet particulate matter under 10 μm (PM10) standards. A large portion of PM10 emissions is attributed to fugitive dust that is either windblown or kicked up by vehicles. The third part of this work demonstrated that Enzyme Induced Carbonate Precipitation (EICP) treatments aggregate soil particles and prevent fugitive dust emissions. The final part of the work examined tire wear PM10 emissions, as vehicles are another significant contributor to PM10. Observations showed a decrease in tire wear PM10 during winter with little change when varying the highway surface type.
ContributorsMiech, Jason Andrew (Author) / Herckes, Pierre (Thesis advisor) / Fraser, Matthew P (Committee member) / Shock, Everett (Committee member) / Arizona State University (Publisher)
Created2023