ArticleAtmospheric environment (Oxford, England : 1994)2015
Temporal variation of traffic on highways and the development of accurate temporal allocation factors for air pollution analyses.
Article in Atmospheric environment (Oxford, England : 1994), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed, 63 citations in OpenAlex.
- Impacts of Vehicle Emission Regulations and Local Congestion Policies on Birth Outcomes Associated with Traffic Air Pollution.Research report (Health Effects Institute) · 2025Article
- Impact of traffic on air pollution in a mid-sized urban city during COVID-19 lockdowns.Air quality, atmosphere, & health · 2023Article
- A population-based cohort study of traffic congestion and infant growth using connected vehicle data.Science advances · 2022Article
- Characterizing Determinants of Near-Road Ambient Air Quality for an Urban Intersection and a Freeway Site.Research report (Health Effects Institute) · 2022Article
- A community noise survey in Southwest Detroit and the value of supplemental metrics for truck noise.Environmental research · 2021Article
- Enhancing Models and Measurements of Traffic-Related Air Pollutants for Health Studies Using Dispersion Modeling and Bayesian Data Fusion.Research report (Health Effects Institute) · 2020Article
- Near-road Vehicle Emissions Air Quality Monitoring for Exposure Modeling.Atmospheric environment (Oxford, England : 1994) · 2020Article
- A new approach for inferring traffic-related air pollution: Use of radar-calibrated crowd-sourced traffic data.Environment international · 2019Article
- Operational evaluation of the RLINE dispersion model for studies of traffic-related air pollutants.Atmospheric environment (Oxford, England : 1994) · 2018Article
- Sensitivity analysis of the near-road dispersion model RLINE - an evaluation at Detroit, Michigan.Atmospheric environment (Oxford, England : 1994) · 2018Article
- Influential factors affecting black carbon trends at four sites of differing distance from a major highway in Las Vegas.Air quality, atmosphere, & health · 2018Article
- Finely Resolved On-Road PMRisk analysis : an official publication of the Society for Risk Analysis · 2017Article
- Trends in PMAtmospheric environment (Oxford, England : 1994) · 2016Article
- Elevated Atmospheric Levels of Benzene and Benzene-Related Compounds from Unconventional Shale Extraction and Processing: Human Health Concern for Residential Communities.Environmental health insights · 2016Article
- Temporal and spatial variation in allocating annual traffic activity across an urban region and implications for air quality assessments.Transportation research. Part D, Transport and environment · 2015Article
- High resolution spatial and temporal mapping of traffic-related air pollutants.International journal of environmental research and public health · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
Traffic activity encompasses the number, mix, speed and acceleration of vehicles on roadways. The temporal pattern and variation of traffic activity reflects vehicle use, congestion and safety issues, and it represents a major influence on emissions and concentrations of traffic-related air pollutants. Accurate characterization of vehicle flows is critical in analyzing and modeling urban and local-scale pollutants, especially in near-road environments and traffic corridors. This study describes methods to improve the characterization of temporal variation of traffic activity. Annual, monthly, daily and hourly temporal allocation factors (TAFs), which describe the expected temporal variation in traffic activity, were developed using four years of hourly traffic activity data recorded at 14 continuous counting stations across the Detroit, Michigan, U.S. region. Five sites also provided vehicle classification. TAF-based models provide a simple means to apportion annual average estimates of traffic volume to hourly estimates. The analysis shows the need to separate TAFs for total and commercial vehicles, and weekdays, Saturdays, Sundays and observed holidays. Using either site-specific or urban-wide TAFs, nearly all of the variation in historical traffic activity at the street scale could be explained; unexplained variation was attributed to adverse weather, traffic accidents and construction. The methods and results presented in this paper can improve air quality dispersion modeling of mobile sources, and can be used to evaluate and model temporal variation in ambient air quality monitoring data and exposure estimates.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.