Environment

Deconstructing laws of accessibility and facility distribution in cities

Xu, Yanyan
Olmos, Luis E.
Abbar, Sofiane
González, Marta C.
2020

The era of the automobile has seriously degraded the quality of urban life through costly travel and visible environmental effects. A new urban planning paradigm must be at the heart of our road map for the years to come, the one where, within minutes, inhabitants can access their basic living needs by bike or by foot. In this work, we present novel insights of the interplay between the distributions of facilities and population that maximize accessibility over the existing road networks. Results in six cities reveal that travel costs could be reduced in half through redistributing...

Correlation networks of air particulate matter: a comparative study

Vlachogiannis, Dimitrios M.
Xu, Yanyan
Jin, Ling
González, Marta C.
2021

Over the last decades, severe haze pollution constitutes a major source of far-reaching environmental and human health problems. The formation, accumulation and diffusion of pollution particles occurs under complex temporal scales and expands throughout a wide spatial coverage. Seeking to understand the transport patterns of haze pollutants in China, we review a proposed framework of time-evolving directed and weighted air quality correlation networks. In this work, we evaluate monitoring stations’ time-series data from China and California, to test the sensitivity of the framework to...

Big Data Fusion to Estimate Urban Fuel Consumption: A Case Study of Riyadh

Kalila, Adham
Awwad, Zeyad
Di Clemente, Riccardo
González, Marta C.
2018

Falling oil revenues and rapid urbanization are putting a strain on the budgets of oil-producing nations, which often subsidize domestic fuel consumption. A direct way to decrease the impact of subsidies is to reduce fuel consumption by reducing congestion and car trips. As fuel consumption models have started to incorporate data sources from ubiquitous sensing devices, the opportunity is to develop comprehensive models at urban scale leveraging sources such as Global Positioning System (GPS) data and Call Detail Records. This paper combines these big data sets in a novel method to model...

A network spatial analysis simulating response time to calls for service at variable staffing levels

Clark, Callie
Dangwal, Chitra
Kato, Dylan
Gonzalez, Marta
2022

In light of recent events, there has been a surge in discussions of defunding police. On one hand, policy that reduces police presence aims to reduce frequency of police violence. On the other hand, downsizing the police force triggers concerns of public safety and police response time. In this work, we use spatial analysis to examine the impact a reduced police force may have on response time. Modeling the transportation system of Chicago as a network, we simulate the response of police officers from stations to incidents. We then use this simulation to calculate the impacts of resource...

A mesoscopic model of vehicular emissions informed by direct measurements and mobility science

Öztürk, Ayşe Tuğba
Kasliwal, Aparimit
Fitzmaurice, Helen
Kavvada, Olga
Calvez, Philippe
Cohen, Ronald C.
González, Marta C.
2025

Vehicle emissions pose a significant challenge for cities worldwide, yet a comprehensive analysis of the relationship between mobility metrics and vehicle emissions at scale remains elusive. We introduce the Mobile Data Emission System (MODES), a framework that integrates various sources of individual mobility data on an unprecedented scale. Our model is validated with direct measurements from a network of high-density sensors analyzed before and during the COVID-19 pandemic. MODES is used as a laboratory for scaling analysis. Informed by millions of individual trips at a metropolitan...

A cluster-based appliance-level-of-use demand response program design

Wu, Jiaman
Lu, Chenbei
Wu, Chenye
Shi, Jian
Gonzalez, Marta C.
Wang, Dan
Han, Zhu
2024

The ever-intensifying threat of climate change renders the electric power system undergoing a profound transition toward net-zero emissions. Energy efficiency measures, such as demand response, facilitate the transformation to jointly relieve consumers’ financial burden and improve the operability of the electric power grid, in a carbon-free way. In this paper, we design a cluster-based appliance-level-of-use demand response program, based on the massive volume of appliance consumption data, to expand the role demand response can play in the power grid’s low-carbon transition. We...

Optimizing Urban Bus Transit Network Design Can Lead to Greenhouse Gas Emissions Reduction

Griswold, Julia B.
Sztainer, Tal
Lee, Jinwoo
Madanat, Samer
Horvath, Arpad
2017

The high contribution of greenhouse gas (GHG) emissions by the transportation sector calls for the development of emission reduction efforts. In this paper, we examine how efficient bus transit networks can contribute to these reduction measures. Utilizing continuum approximation methods and a case study in Barcelona, we show that efforts to decrease the costs of a transit system can lead to GHG emission reductions as well. We demonstrate GHG emission comparisons between an optimized bus network design in Barcelona and the existing system. The optimization of the system network design...

Vehicle Emissions Estimation Under Oversaturated Conditions Along Signalized Arterials

Skabardonis, Alexander
Geroliminis, Nikolas
Christofa, Eleni
Transportation Research Board
2012

Traditionally, the amount of air pollutant emissions from motor vehicles—hydrocarbons, carbon monoxide, and oxides of nitrogen—is estimated from emission factors based on trip and vehicle miles traveled and aggregate measures of vehicle activity (e.g., average vehicle speed). This method is not reliable for urban networks, as it does not consider the effect of traffic signals and congestion. There is a need to predict vehicle activity by mode of operation, i.e., time spent in cruise, acceleration, deceleration, and idle to obtain improved emission estimates. An analytical model for...

Traffic signal timing as a transportation system management measure : the California experience

Deakin, Elizabeth A
Skabardonis, Alexander
May, Adolf D
1986

Traffic signal retiming has long been suggested as a means of improving traffic operations and reducing fuel consumption and emissions. However, few local agencies have been able to muster the resources to systematically retime their signals. In California, a statewide program--the Fuel Efficient Traffic Signal Management (FETSIM) Program--was established to address this need. The FETSIM Program provides funds, training, and technical assistance to local agencies to retime their signal systems for greater operating efficiency. To date, 62 local jurisdictions have participated in the...

The Fuel-Efficient Traffic Signal Management Program: Evaluation of the Fourth and Fifth Funding Cycles: Report to the California Department of Transportation

Skabardonis, A
Singh, R
Deakin, E A
University of California, Berkeley
California Department of Transportation
1998

The Fuel-Efficient Traffic Signal Management (FETSIM) Program was initiated in 1982 to help local agencies retime their traffic signals to reduce stops, delays, and fuel consumption. This report presents the results of the fourth and fifth grant cycles of the FETSIM Program. During the two grant cycles, local agency staff and their consultants were provided training, technical assistance and funding necessary to optimize the timing of their signal systems and to put the new timing plans into operation. In the 1986 grant cycle, thirty-one local agencies retimed 1169 signals at a total cost...