The book provides a comprehensive overview of vehicular emissions modeling and its implications for air quality management. Ensuring a clear and logical flow of information will facilitate readers' understanding and engagement with the content. It delves into the realm of vehicular air dispersion modeling and emission estimation along the State Highway-5 corridor (SH-5) from Indira Chowk to Rampur, situated in Ambala Cantonment. Leveraging CALINE-4, a highway dispersion model tailored for vehicular air dispersion modeling, the study provides insights into the prediction and forecasting of CO concentrations. By meticulously collecting traffic data for both weekdays and weekends along the designated corridor and monitoring CO concentrations at the roadside, the study validates the model's efficacy. Statistical descriptors are judiciously employed to evaluate the model's performance, ensuring robustness and reliability. The book encompasses vehicular emission load and modeling for the base year 2013 and the projected year 2017, with additional analysis under management scenarios, including the integration of CNG vehicles.
Table of Contents
CHAPTER 1 INTRODUCTION
1.1 Vehicular Pollution
1.2 Vehicular Pollution in India
1.3 Vehicular Pollution Modelling
1.4 Objectives of the Study
1.5 Organization of the Book
CHAPTER 2 LITERATURE REVIEW
2.1 Modelling Studies
2.2 Deterministic Mathematical Models
2.3.1 Analytical Models
2.3.2 Numerical Models
2.3 Statistical Models
2.4 Physical Models
2.5 Urban Models
2.5.1 Line Source Dispersion Models
2.6 CALINE4 Model
2.7 Vehicular Emissions Related Legislations in India
2.8 Vehicular Emissions Norms in India
CHAPTER 3 METHODOLOGY
3.1 Site Description
3.2 Data Collection
3.2.1 Traffic Data
3.2.2 Fuel Station Survey
3.2.3 Measurement of CO Concentrations and Meteorological Data
3.3 Vehicular Emission Load Estimation
3.4 CALINE4 Model Description
3.4.1 Input Requirements of CALINE4
3.5 Weighted Emission Factor
3.6 Model Evaluation
CHAPTER 4 RESULTS AND DISSCUSION
4.1 Estimation of Vehicular Emission Load
4.2 Scenario Evaluation
4.2.1 1st Scenario: Base Year 2013 (Present Scenario)
4.2.2 2nd Scenario: Projected Year 2017(Without CNG)
4.2.3 3rd Scenario: Projected year 2017 (With 25% CNG)
4.2.4 Comparison of Emission Load in 2013, 2017 (Without CNG) and 2017 (With CNG)
4.3 Vehicular Pollution Modeling using CALINE4 Model
4.3.1 1st Scenario: CO Concentrations Prediction for the Base Year 2013 (Present Scenario)
4.3.2 2nd Scenario: CO Concentrations Prediction for the Projected Year 2017 (Without CNG)
4.3.3 3rd Scenario-CO Concentrations Prediction for the Projected Year 2017 (With CNG)
4.3.4 Comparison of Predicted CO Concentrations for the Base Year 2013, Projected Year 2017 With and Without CNG
4.6 Model Performance and Evaluation
CHAPTER 5 CONCLUSION AND RECOMMENDATIONS
CHAPTER 6 REFERENCES
ANNEXURE
Objectives and Topics
The primary aim of this research is to estimate vehicular pollution loads and predict carbon monoxide (CO) concentrations along the state highway corridor (SH-5) at Ambala Cantonment using the CALINE4 dispersion modeling framework, comparing results across different traffic growth scenarios and evaluating the impact of CNG introduction.
- Modeling of vehicular air dispersion along urban highways.
- Estimation of annual vehicular emission loads using representative factors.
- Evaluation of future traffic growth and CNG integration scenarios.
- Validation of the CALINE4 modeling performance against measured field data.
- Identification of sustainable urban transport management practices.
Excerpt from the Book
1.1 Vehicular Pollution
Environmental pollution has emerged as one of the most prominent problems in the transportation sector. Motor vehicles generate significant amounts of carbon monoxide (CO), hydrocarbons (HC), nitrogen oxides (NOx), suspended particulate matter (SPM), and other air pollutants into the atmosphere, posing substantial environmental and health risks. In many nations, air pollution from motor vehicles has surpassed other smoke as the leading source of concern. However, as vehicle use continues to expand, attempts to cut emissions from individual cars are being surpassed by an increase in traffic volume. The transport industry accounts for around 14% of worldwide GHG emissions (CPCB, 2010). Indian cities, despite reduced vehicle ownership and fossil fuel use, are grappling with rising traffic congestion, overcrowded public transport, poor pedestrian and cyclist conditions, and high motor vehicle-generated air pollution and accidents. CO2 emissions from the transport industry have climbed faster than those from all other sectors over the last three decades, and they are expected to rise much faster in the future. Between 1990 and 2004, CO2 emissions from the world's transport industry climbed by 36.5%. During the same time, road transport emissions grew by 29% in industrialized countries and 61% in other countries (CPCB, 2010). Worldwide, the transport sector accounts for roughly 23% of energy-related CO2 and 13% of total GHGs generated by diverse sources. Furthermore, CO2 emissions are predicted to rise by 1.7% per year between 2004 and 2030, owing mostly to rising demand for mobility in emerging nations, which is projected to expand by an average of 2.8% per year during the same period.
Summary of Chapters
CHAPTER 1 INTRODUCTION: This chapter provides an overview of environmental challenges caused by vehicular pollution and outlines the study's scope and objectives.
CHAPTER 2 LITERATURE REVIEW: This chapter surveys existing dispersion models, focusing on mathematical and statistical approaches used in air quality assessment.
CHAPTER 3 METHODOLOGY: This chapter details the site characteristics, data collection procedures for traffic and meteorology, and the technical approach for using the CALINE4 model.
CHAPTER 4 RESULTS AND DISSCUSION: This chapter presents the data analysis, emission load estimations, and model prediction outcomes for various traffic simulation scenarios.
CHAPTER 5 CONCLUSION AND RECOMMENDATIONS: This chapter summarizes findings regarding pollution dispersion and provides policy recommendations for sustainable urban traffic management.
Keywords
Vehicular Pollution, CALINE4 Model, Carbon Monoxide, Air Dispersion Modeling, Emission Load Estimation, Highway Corridor, Traffic Congestion, Sustainability, CNG Vehicles, Atmospheric Stability, Emission Factors, Urban Air Quality, Meteorological Parameters, Ambala Cantonment, Pollutant Dispersion.
Frequently Asked Questions
What is the primary focus of this research?
The research focuses on assessing air quality impacts, specifically carbon monoxide concentrations, along the SH-5 highway corridor in Ambala Cantonment using the CALINE4 dispersion model.
What are the central themes of the work?
Key themes include the quantification of vehicular emissions, the evaluation of traffic volume growth, and the impact of introducing alternative fuels like CNG on air quality.
What is the main overarching research question?
The study primarily investigates how vehicular emissions vary under different traffic scenarios and whether the integration of CNG can effectively mitigate CO levels below current standards.
Which scientific methodology is applied?
The study combines field-based data collection for traffic counts and ambient pollutants with the analytical application of the CALINE4 Gaussian dispersion modeling system.
What is covered in the main body of the work?
The main body examines existing literature, describes the data-gathering methodology for traffic and weather inputs, and discusses empirical results from modeled emission scenarios.
What are the key terms associated with this study?
Major keywords include vehicular pollution, dispersion modeling, emission load estimation, CALINE4, highway corridor, and sustainability.
How does the introduction of CNG affect the dispersion model findings?
The study uses scenario evaluation to show that shifting approximately 25% of the vehicle fleet to CNG leads to a measurable reduction in emission loads compared to "without CNG" growth projections for 2017.
Why was the Ambala Cantonment highway chosen for the study?
This corridor was selected as a representative case study due to high traffic volume, its role as a regional interchange, and the availability of specific geometric factors suitable for testing the CALINE4 model.
- Quote paper
- Dr. Chadetrik Rout (Author), Dr. Bikram Jit Singh (Author), 2024, Roads to Sustainability: Modeling Vehicular Emissions along Urban Highways, Munich, GRIN Verlag, https://www.grin.com/document/1473993
