Phd Dissertation

Environmental and health benefits of airport congestion pricing - The case of Los Angeles International Airport

Abstract

Airports are a source of greenhouse gases (GHG) and air pollutants such as fine particulate matter with an aerodynamic diameter under 2.5 μm (PM2.5), which adversely affect the climate and human health. This pollution is worsening with increasing aircraft congestion. Even though aviation is the second largest source of GHG emissions in the transportation sector, it was excluded from the recent COP21 Paris Agreement. Little is known about the climate change and adverse health impacts from increasing airports congestion. The purpose of this study is to start filling this gap. In this dissertation, I estimate congestion, health, and climate benefits from airport congestion pricing for Los Angeles International Airport (LAX), the fourth busiest airport in the world by passenger numbers in 2018. I first derive the optimal congestion fee for airports like LAX that primarily serve local and regional markets. To quantify the impacts of airport congestion pricing, I analyze one year of airport operations (2014), which corresponds to 593,547 flights (both inbound and outbound). My simulation results suggest that hourly congestion pricing would on average reduce waiting time by 2.9 minutes per flight and annual PM2.5 emissions by 11.4 percent, thus decreasing the environmental impacts from aircraft landing and takeoff operations (LTO), which extend as far as 19 km downwind from the airport.An analysis of the health gains from implementing a congestion fee that accounts for air pollution cost shows that it would annually reduce premature mortality from PM2.5 exposure by 4.6 cases, avoided hospital admissions for cardiovascular diseases by 167 cases, and avoid 8,539 lost work days. The corresponding monetary value of these health gains are $45.8 million, $21.9 million, and $1.4 million respectively (all in 2014 dollars).For my climate change analysis, I consider both the country-level social cost of carbon (CSCC; $36 per tonne) and the global social cost of carbon (GSCC; $417 per tonne). While pricing GHG emissions with the CSCC only has a minor impact, using the GSCC helps further reduce aircraft congestion and its associated health impacts. Indeed, an aircraft congestion fee with GHG based on the GSCC would reduce premature mortality by 6 cases each year, avoided hospital admissions by 221 cases, and avoid 11,528 lost work days (95 % CI: 4,995, 18,060). The corresponding monetary value of these health gains are $60.7 million, $27.7 million, and $1.9 million respectively.The methodology presented in this study is widely applicable. It provides engineers, planners, and policymakers a tool for reducing airport congestion and for quantifying the resulting health and climate benefits.

Suggested Citation
Sheng-Hsiang Peng (2019) Environmental and health benefits of airport congestion pricing - The case of Los Angeles International Airport. Ph.D.. UC Irvine. Available at: https://escholarship.org/uc/item/9rr5711z (Accessed: October 12, 2023).

Phd Dissertation

Automobile use, public policy, and municipal government : factors influencing the implementation of alternative transportation policies

Suggested Citation
Joshua Hassol (1994) Automobile use, public policy, and municipal government : factors influencing the implementation of alternative transportation policies. PhD Dissertation. UC Irvine. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/17uq3m8/alma991012163629704701.

conference paper

Multipath-optimal UAV trajectory planning for urban UAV navigation with cellular signals

2019 IEEE 90th vehicular technology conference (VTC2019-Fall)

Publication Date

September 1, 2019

Author(s)

Sonya Ragothaman, Mahdi Maaref, Zaher Kassas
Suggested Citation
Sonya Ragothaman, Mahdi Maaref and Zaher M. Kassas (2019) “Multipath-optimal UAV trajectory planning for urban UAV navigation with cellular signals”, in 2019 IEEE 90th vehicular technology conference (VTC2019-Fall). IEEE. Available at: 10.1109/vtcfall.2019.8891218.

working paper

A Tool to Evaluate the Safety Effects of Changes in Freeway Traffic Flow

Abstract

This research involves the development of a tool that can be used to assess the changes in traffic safety tendencies that result from changes in traffic flow. The tool uses data from single inductive loop detectors, converting 30-second observations of volume and occupancy for multiple freeway lanes into traffic flow regimes. Each regime has a specific pattern of crash types, which were determined through nonlinear multivariate analyses of over 1,000 crashes on freeways in Southern California. These analyses revealed ways in which differences in variances in speeds and volumes across lanes, as well as central tendencies of speeds and volumes, combine in complex ways to explain crash taxonomy. This research may provide the foundation to forecast the crash rates, in terms of vehicle miles of travel, for vehicles that are exposed to different traffic flow conditions.

published journal article

Effects of carbon capture on the performance of an advanced coal-based integrated gasification fuel cell system

Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy

Publication Date

March 1, 2011

Author(s)

M Li, A D Rao, Jack Brouwer, G S Samuelsen
Suggested Citation
M Li, A D Rao, J Brouwer and G S Samuelsen (2011) “Effects of carbon capture on the performance of an advanced coal-based integrated gasification fuel cell system”, Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy, 225(2), pp. 208–218. Available at: 10.1177/2041296710394261.

published journal article

Stochastic LWR model with heterogeneous vehicles: Theory and application for autonomous vehicles

Transportation Research Procedia

Publication Date

January 1, 2020

Abstract

The introduction of autonomous vehicles (AV) will increase the vehicle heterogeneity on our roads. It is claimed that these vehicles will be able to achieve lower spacings for the same speed than human driven ones. Therefore, a good understanding of the influence of heterogeneous driver behavior on macroscopic traffic flow characteristics is crucial. This paper presents a stochastic Lighthill-Whitham Richards model by introducing heterogeneous, i.e., vehicle dependent, jam densities. The model is solved in Lagrangian coordinates, and the nature of the model allows for investigating the impact of driver heterogeneity on macroscopic relations of traffic flow, both through simulations and analytically. The results show that both static and dynamic macroscopic characteristics of the model, such as average speed, capacity drop and flow rate evolution at a bottleneck, are consistent with the deterministic version with an equivalent jam density, which is the harmonic mean of the distribution. Establishing the theoretical way to average the parameters will allow us to develop some control strategies for connected AV in a mixed environment to control the platoon behavior and drive traffic flow to the desired state. In this line, this paper discusses the relation between the desired AV characteristics and the market penetration rate to maximize the flow rate at bottlenecks by reducing the capacity drop effects. This further motivates future research on the technology development for AVs.

Suggested Citation
Irene Martínez and Wen-long Jin (2020) “Stochastic LWR model with heterogeneous vehicles: Theory and application for autonomous vehicles”, Transportation Research Procedia, 47, pp. 155–162. Available at: 10.1016/j.trpro.2020.03.088.

published journal article

Eco-Driving Algorithm with a Moving Bottleneck on a Single-Lane Road

Transportation Research Record

Publication Date

December 1, 2020

Abstract

Eco-driving strategies have been applied to smooth traffic flow and reduce greenhouse gas emissions along with air pollution. In this paper, we propose an eco-driving strategy to reduce traffic oscillation and smooth trajectories for connected vehicles following a moving bottleneck on a single-lane road. The eco-driving strategy, which leverages vehicle-to-vehicle (V2V) communications, designs advisory speed limits for each following vehicle through a control algorithm. The algorithm is based on the prediction of the following vehicle trajectories dictated by a moving bottleneck. The following vehicle trajectories are obtained by analytically solving the moving bottleneck problem in which the moving bottleneck speeds vary over time. In addition, the bounded acceleration rate is imposed in car-following behavior. The benefits of this strategy are demonstrated by applying it to four scenarios with different bottleneck movements. By simulating the scenarios with Newell’s car-following model with bounded acceleration and VT-Micro emission model, we find that both speed fluctuations and emissions are reduced with the algorithm in the scenarios in which the moving bottleneck has a constant speed, accelerates, decelerates and stops-and-goes. The results indicate that the proposed eco-driving algorithm can smooth traffic flow behind a moving bottleneck.

Suggested Citation
Pengyuan Sun, Dingtong Yang and Wen-Long Jin (2020) “Eco-Driving Algorithm with a Moving Bottleneck on a Single-Lane Road”, Transportation Research Record, 2674(12), pp. 493–504. Available at: 10.1177/0361198120961381.

working paper

Review and Evaluation of Transport-Related Fuel-Use Forecasting Models

Publication Date

April 1, 1991

Author(s)

Thomas Golob, Ryuichi Kitamura, David Brownstone, Trucy Cameron, Will Recker

Working Paper

UCI-ITS-WP-91-2

Areas of Expertise

Abstract

This report provides an exhaustive review of the state-of-the-art in transportation-related energy demand forecasting models. Models used for forecasting fuel demand and consumption in the passenger vehicle, transit and freight sectors of the transportation economy are described and discussed. Based on the review, recommendations are made on how the accuracy and robustness of the forecasts can be improved while explicitly incorporating behavioral relationships among various users of transportation services.

Suggested Citation
Thomas F. Golob, Ryuichi Kitamura, David Brownstone, Trucy Cameron and Will Recker (1991) Review and Evaluation of Transport-Related Fuel-Use Forecasting Models. Working Paper UCI-ITS-WP-91-2. Institute of Transportation Studies, Irvine. Available at: https://escholarship.org/uc/item/2rn804mt.

published journal article

Adaptive lookup of open WiFi using crowdsensing

IEEE/ACM Transactions on Networking

Publication Date

December 1, 2016

Author(s)

Di Wu, Qiang Liu, Yong Li, Julie A. McCann, Amelia Regan, Nalini Venkatasubramanian
Suggested Citation
Di Wu, Qiang Liu, Yong Li, Julie A. McCann, Amelia C. Regan and Nalini Venkatasubramanian (2016) “Adaptive lookup of open WiFi using crowdsensing”, IEEE/ACM Transactions on Networking, 24(6), pp. 3634–3647. Available at: 10.1109/tnet.2016.2533399.

published journal article

DON'T HOP in the bus GUS – an analysis of recent trends in octa (Orange county transit authority) bus ridership (2nd highest scoring doctoral abstract award sponsored by the transport & health science group)

Journal of Transport & Health

Publication Date

September 1, 2019
Suggested Citation
Farzana Khatun and Jean-Daniel Saphores (2019) “DON'T HOP in the bus GUS – an analysis of recent trends in octa (Orange county transit authority) bus ridership (2nd highest scoring doctoral abstract award sponsored by the transport & health science group)”, Journal of Transport & Health, 14, p. 100784. Available at: 10.1016/j.jth.2019.100784.