Study finds dramatic boost in air quality from electrifying railways
A new study found that electrifying the San Francisco Bay Area’s Caltrain commuter rail line reduced riders’ exposure to black carbon, a carcinogen, by an average of 89%
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In late summer 2024, Caltrain replaced its diesel fleet with brand new electric trains. A new UC Berkeley study found that the electrification of the commuter rail line led to a dramatic boost in air quality in and around the trains.
view moreCredit: Adam Lau/UC Berkeley
Switching from diesel to electric trains dramatically improved the air quality aboard the San Francisco Bay Area’s Caltrain commuter rail line, reducing riders’ exposure to the carcinogen black carbon by an average of 89%, finds a new study published today in the journal Environmental Science and Technology Letters.
The electrification of the system also significantly reduced the ambient black carbon concentrations within and around the San Francisco station, the study found.
“The transition from diesel to electric trains occurred over just a few weeks, and yet we saw the same drop in black carbon concentrations in the station as California cities achieved from 30 years of clean air regulations,” said study senior author Joshua Apte, a professor of environmental engineering and environmental health at the University of California, Berkeley. “It really adds to the case for electrifying the many other rail systems in the U.S. that still use old, poorly regulated diesel locomotives.”
Caltrain operates the busiest commuter rail system in the western U.S., carrying millions of passengers a year along its 47-mile route between San Francisco and San Jose. Over the course of six weeks in August and September 2024, the system retired all 29 of its diesel locomotives and replaced them with 23 new electric trains. The debut of the new trains was the culmination of a $2.44 billion modernization and decarbonization project that first launched in 2017.
Apte, an expert in air quality monitoring, was inspired to pursue the study after visiting a Caltrain station in August 2024, when the very first electric trains were being introduced.
“I was stunned at how much the station smelled like diesel smoke and how noisy it was from the racket of diesel locomotives idling away at the platforms, dumping smoke out into the community,” Apte said. “A light bulb went off my head — I realized this would all be going away in a few weeks.”
After securing the support of Caltrain, Apte and study lead author Samuel Cliff quickly mobilized, installing black carbon detectors at Caltrain stations and carrying portable air quality detectors aboard the trains. For four weeks, they tracked the rapid improvements in air quality as old diesel locomotives were replaced by new electric trains.
“A lot of these transitions happen pretty slowly. This one happened in a blink of an eye,” Apte said. “We had the unique opportunity to capture the ancillary public health benefits.”
According to Apte and Cliff’s calculations, the reduction in black carbon exposure achieved from Caltrain’s electrification cut excess cancer deaths by 51 per 1 million people for riders and 330 per 1 million people for train conductors. For reference, the U.S. Environmental Protection Agency has a policy that any exposure that increases the average individual’s cancer risk by more than one per million is considered unacceptable.
“If you think about this in the context of the whole of the U.S., where we have millions of people commuting by rail every day, that's hundreds of cases of cancer that could be prevented each year,” said Cliff, a postdoctoral scholar at UC Berkeley.
The majority of U.S. commuter trains are still powered by diesel fuel, despite the fact that electric trains are quieter, more reliable and produce fewer greenhouse gases than diesel locomotives. Apte hopes the study motivates more U.S. municipalities to follow the lead of Asian and European countries in electrifying their railways.
“This is something that we ought to find a way to do as quickly as possible, everywhere,” Apte said. “California has long-term plans to electrify most of its rail systems, but this shows that we shouldn't be waiting another 25 years to get it done. We should be speeding it up.”
Co-authors of the study include Haley McNamara Byrne and Allen Goldstein of UC Berkeley.
UC Berkeley postdoctoral scholar Samuel Cliff (left) and professor Joshua Apte at the San Francisco Caltrain Station. Each is holding one of the portable air quality monitors that they used to measure black carbon concentrations aboard the trains.
Samuel Cliff downloads data from a portable air quality monitor at a Caltrain station.
Credit
Adam Lau/UC Berkeley
Journal
Environmental Science & Technology Letters
Method of Research
Observational study
Subject of Research
Not applicable
Article Title
Dramatic Air Quality Improvements after the Complete Electrification of a Commuter Rail System
Article Publication Date
16-Apr-2025
How do different operating schemes affect urban rail transit resilience?
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(a, d, g) The percolation transition processes during the morning peak, off-peak, and evening peak periods for the URT system. (b, c) The network phase transitions occurring during the morning peak period. (e, f) The network phase transitions during the off-peak period. (h, i) The network phase transitions during the evening peak period. (j) The trend of critical percolation threshold throughout the entire day.
view moreCredit: Communications in Transportation Research
To answer this question: How do different operating schemes affect urban rail transit resilience? researchers at Beijing Jiaotong University, Beijing Mass Transit Railway Operation Corporation Ltd., The Hong Kong Polytechnic University, and Dalian University of Technology, constructed a passenger-train coupled network percolation model to investigate the impact of different operating schemes on urban rail transit system.
They published their study on 1 April 2025, in Communications in Transportation Research.
“We develop a percolation-based resilience framework to analyze the Beijing urban rail transit system resilience under different operating schemes. This framework is based on multi-source data, such as train timetable data, smart card data, train routing data etc. Therefore, a more precise result can be obtained from our framework.” says Xin Yang, a researcher at the School of Systems Science at Beijing Jiaotong University.
Percolation transition on URT network
When a given threshold q=0, the URT network during morning and evening rush hours is not intact, too heavy commuting passenger flow causes this phenomenon. As the threshold q increases, the URT network experiences gradual collapse at a given point in time. However, the same network exhibits substantial differences in terms of resilience for the threshold q.
During the morning rush hours, due to longer commuting times from suburban areas, traffic flows mainly from the fringes of the network towards its center currently, with failure links predominantly clustered around the network's periphery.
Conversely, at noon, traffic is distributed homogeneously across the URT network, resulting in improved network connectivity. And the evening rush hour, the performance of the URT network is better than in the morning rush hour.
Identification of bottleneck during phase transition
Identifying bottlenecks during the dynamic network evolution of URT is pivotal. Enhancing the capacity of bottlenecks and ensuring they do not malfunction after accidental damage can prevent the network from breaking into several small clusters and improve connectivity at a reasonable cost.
Therefore, we counted the number of times a bottleneck appeared in the network. The results show that the occurrence frequency and probability exhibit a typical power law distribution, indicating the links that become bottlenecks more often are very rare, and most of them become bottlenecks only a few times within a day.
About Communications in Transportation Research
Communications in Transportation Research was launched in 2021, with academic support provided by Tsinghua University and China Intelligent Transportation Systems Association. The Editors-in-Chief are Professor Xiaobo Qu, a member of the Academia Europaea from Tsinghua University and Professor Shuai’an Wang from Hong Kong Polytechnic University. The journal mainly publishes high-quality, original research and review articles that are of significant importance to emerging transportation systems, aiming to become an international platform and window for showcasing and exchanging innovative achievements in transportation and related fields, to promote the exchange and development of transportation research between China and the international academic community. It has been indexed in ESCI, Ei Compendex, Scopus, DOAJ, TRID and other databases. In 2022, it was selected as a high-starting-point new journal project of the “China Science and Technology Journal Excellence Action Plan”. This year, it received the first impact factor of 12.5. The 2023 IF is 12.5, ranking in the Top1 (1/57, Q1) among all journals in "TRANSPORTATION" category. At its discretion, Tsinghua University Press will pay the open access fee for all published papers in 2025.
About Tsinghua University Press
Established in 1980, as a department of Tsinghua University, Tsinghua University Press (TUP) is a leading comprehensive higher education and professional publisher in China. TUP publishes 58 journals and 38 of them are in English. There are 18 journals indexed by SCIE/ESCI. Three of them have the highest impact factor in its field. In 2022, TUP launched SciOpen. As a publishing platform of TUP, SciOpen provides free access to an online collection of journals across diverse academic disciplines and serves to meet the research needs of scientific communities. SciOpen provides end-to-end services across manuscript submission, peer review, content hosting, analytics, identity management, and expert advice to ensure each journal’s development.
Journal
Communications in Transportation Research
Article Title
Urban rail transit resilience under different operation schemes: A percolation-based approach
Article Publication Date
15-Apr-2025
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