東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back to Search results for [ null ]

Switch To: Labeled | MARC Mode | ISBD

Transportation-related air quality m...

Boriboonsomsin, Kanok.

Linked to FindBook

Google Book

Amazon

博客來

Transportation-related air quality modeling and analysis based on remote sensing and geospatial data.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Transportation-related air quality modeling and analysis based on remote sensing and geospatial data./
Author:	Boriboonsomsin, Kanok.
Description:	523 p.
Notes:	Source: Dissertation Abstracts International, Volume: 65-06, Section: B, page: 3048.
Contained By:	Dissertation Abstracts International65-06B.
Subject:	Engineering, Civil. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3136216
ISBN:	0496834142

Transportation-related air quality modeling and analysis based on remote sensing and geospatial data.
Boriboonsomsin, Kanok.

Transportation-related air quality modeling and analysis based on remote sensing and geospatial data. - 523 p.

Source: Dissertation Abstracts International, Volume: 65-06, Section: B, page: 3048.

Thesis (Ph.D.)--The University of Mississippi, 2004.

Ground-level Ozone (O3) and Nitrogen Dioxide (NO2) air pollutants adversely affect public health in many urban areas nationwide and some rural areas of Southeastern states. The objective of this research was the development of decision-making tools for air quality management. Regression equations were developed for predicting daily maximum 8-hr average O 3 and daily average NO2 concentrations using 1996--2000 data as functions of meteorological variables, roadway traffic data, emissions from mobile and point sources, and aircraft operations. The predictions of O3 for the hottest day in Tupelo and Hernando in Summer 2001 are reasonable and within 12% of the measured values. A new imagery-based surface classification (IMAGES) algorithm was developed using the spectral reflectance data of high-resolution multispectral imagery. Integer nonlinear optimization formulations were solved, which improved the overall accuracy of the surface class results by 6%. The IMAGES analysis of 1-m resolution satellite imagery taken in March 2000 showed 15.2% built-up area for Oxford in Mississippi. A methodology for estimating surface class areas based on the traditional topographic map and aerial photo provided comparable results with the IMAGES results for Oxford. The surface class areas for Tupelo and Hernando in Mississippi were used to calculate historical surface temperatures and enhance O 3 and NO2 regression models. An estimated 14.4% growth in built-up areas and traffic near the MS Highway 6-Jackson Avenue intersection in Oxford increased the surface temperature by 1.9°C, O3 by 0.006 ppm, and NO2 by 0.002 ppm in 2003. These models can be used to assess air quality degradation in rural areas considering growth in built-up areas, traffic volume, and congestion.

ISBN: 0496834142Subjects--Topical Terms:

783781
Engineering, Civil.

Transportation-related air quality modeling and analysis based on remote sensing and geospatial data.
LDR:02736nmm 2200301 4500 001 1852048
005 20051229075126.5
008 130614s2004 eng d
020 $a 0496834142
035 $a (UnM)AAI3136216
035 $a AAI3136216
040 $a UnM $c UnM
100 1 $a Boriboonsomsin, Kanok. $3 1939924
245 1 0 $a Transportation-related air quality modeling and analysis based on remote sensing and geospatial data.
300 $a 523 p.
500 $a Source: Dissertation Abstracts International, Volume: 65-06, Section: B, page: 3048.
500 $a Adviser: Waheed Uddin.
502 $a Thesis (Ph.D.)--The University of Mississippi, 2004.
520 $a Ground-level Ozone (O3) and Nitrogen Dioxide (NO2) air pollutants adversely affect public health in many urban areas nationwide and some rural areas of Southeastern states. The objective of this research was the development of decision-making tools for air quality management. Regression equations were developed for predicting daily maximum 8-hr average O 3 and daily average NO2 concentrations using 1996--2000 data as functions of meteorological variables, roadway traffic data, emissions from mobile and point sources, and aircraft operations. The predictions of O3 for the hottest day in Tupelo and Hernando in Summer 2001 are reasonable and within 12% of the measured values. A new imagery-based surface classification (IMAGES) algorithm was developed using the spectral reflectance data of high-resolution multispectral imagery. Integer nonlinear optimization formulations were solved, which improved the overall accuracy of the surface class results by 6%. The IMAGES analysis of 1-m resolution satellite imagery taken in March 2000 showed 15.2% built-up area for Oxford in Mississippi. A methodology for estimating surface class areas based on the traditional topographic map and aerial photo provided comparable results with the IMAGES results for Oxford. The surface class areas for Tupelo and Hernando in Mississippi were used to calculate historical surface temperatures and enhance O 3 and NO2 regression models. An estimated 14.4% growth in built-up areas and traffic near the MS Highway 6-Jackson Avenue intersection in Oxford increased the surface temperature by 1.9°C, O3 by 0.006 ppm, and NO2 by 0.002 ppm in 2003. These models can be used to assess air quality degradation in rural areas considering growth in built-up areas, traffic volume, and congestion.
590 $a School code: 0131.
650 4 $a Engineering, Civil. $3 783781
650 4 $a Engineering, Environmental. $3 783782
650 4 $a Operations Research. $3 626629
650 4 $a Engineering, Automotive. $3 1018477
690 $a 0543
690 $a 0775
690 $a 0796
690 $a 0540
710 2 0 $a The University of Mississippi. $3 1019522
773 0 $t Dissertation Abstracts International $g 65-06B.
790 1 0 $a Uddin, Waheed, $e advisor
790 $a 0131
791 $a Ph.D.
792 $a 2004
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3136216