| LDR | | 00000nam u2200205 4500 |
| 001 | | 000000431935 |
| 005 | | 20200224111018 |
| 008 | | 200131s2019 ||||||||||||||||| ||eng d |
| 020 | |
▼a 9781088313749 |
| 035 | |
▼a (MiAaPQ)AAI13901571 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
| 082 | 0 |
▼a 628 |
| 100 | 1 |
▼a Eltarkawe, Mohamed A B. |
| 245 | 10 |
▼a Industrial Toxic Air Pollutants in Colorado Communities: Investigating Source and Health Impact of Odors and Benzene. |
| 260 | |
▼a [S.l.]:
▼b University of Colorado at Boulder.,
▼c 2019. |
| 260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2019. |
| 300 | |
▼a 180 p. |
| 500 | |
▼a Source: Dissertations Abstracts International, Volume: 81-04, Section: B. |
| 500 | |
▼a Advisor: Miller, Shelly L. |
| 502 | 1 |
▼a Thesis (Ph.D.)--University of Colorado at Boulder, 2019. |
| 506 | |
▼a This item must not be sold to any third party vendors. |
| 520 | |
▼a Exposure to industrial odors and toxic air pollutants are major public health concerns in urban areas. It is difficult to link industrial odors to physical health due to their low toxicity thresholds. However, industrial odors do have serious impact on mental health. In 2014, North Denver communities identified industrial odor pollution as a top priority. The first goal of this work was to investigate the impact of industrial odors on residents' subjective well-being in North Denver and similar communities. A novel approach was used to evaluate subjective well-being based on three aspects. Odors were evaluated using perceived odor and odor acceptability. The data were collected using an online survey. Based on the analysis, the participants who reported that air was very fresh or the odor was highly acceptable, also reported higher levels of well-being. North Denver and Greeley were the most affected communities by odors. The second goal was to test the feasibility of a new method that identifies odor sources by linking wind direction and odor data from social participation. For more than one year, residents reported time, date, location and description of the odor occurrence using smartphone technology. Using the date and time of the odor report submission, wind data were collected from local air monitoring stations. The method has proven its applicability and important odor sources in North Denver and Greeley were identified. Unlike industrial odors, the link between exposure to benzene (an important toxic air pollutant) and physical health is well-documented. Benzene is a known carcinogenic. Understanding benzene concentration distribution is important which can be done by dispersion air quality models. An essential input requirement for dispersion models is the spatial allocation of emissions. The final goal of this work was to develop a new method of county-level benzene emission allocation using transportation analysis zones (TAZs). The resolution provided by the TAZ allocation method helped visualizing different flux patterns generated from five emission sectors. The new method identified key emission areas where more effort is needed to reduce benzene concentrations. The new allocation method was also tested using an AERMOD model to estimate morning benzene concentrations in Denver area. The model preliminary results showed an acceptable model-to-monitor ratio. The model was also used to investigate the impact of temperature inversions on morning benzene concentrations. Benzene predicted concentrations were higher during temperature inversions and model-to-monitor ratios during investigated days were within a factor of two. However, the model results presented in this study should be interpreted with caution because the meteorological data were obtained from a station that was located far from Denver urban area. |
| 590 | |
▼a School code: 0051. |
| 650 | 4 |
▼a Environmental engineering. |
| 690 | |
▼a 0775 |
| 710 | 20 |
▼a University of Colorado at Boulder.
▼b Mechanical Engineering. |
| 773 | 0 |
▼t Dissertations Abstracts International
▼g 81-04B. |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0051 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2019 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15492303
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
| 980 | |
▼a 202002
▼f 2020 |
| 990 | |
▼a ***1008102 |
| 991 | |
▼a E-BOOK |