ArticleInternational journal of environmental research and public health2015
High resolution spatial and temporal mapping of traffic-related air pollutants.
Article in International journal of environmental research and public health, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- Development of Life Course Exposure Estimates Using Geospatial Data and Residence History.International journal of environmental research and public health · 2025Article
- Spatial variation, temporal evolution, and source direction apportionment of PMEnvironmental monitoring and assessment · 2024Article
- Characterizing Determinants of Near-Road Ambient Air Quality for an Urban Intersection and a Freeway Site.Research report (Health Effects Institute) · 2022Article
- Seasonal Variation, Chemical Composition, and PMF-Derived Sources Identification of Traffic-Related PMInternational journal of environmental research and public health · 2021Article
- Improving Road Traffic Forecasting Using Air Pollution and Atmospheric Data: Experiments Based on LSTM Recurrent Neural Networks.Sensors (Basel, Switzerland) · 2020Article
- Application of the Public Health Exposome Framework to Estimate Phenotypes of Resilience in a Model Ohio African-American Women's Cohort.Journal of urban health : bulletin of the New York Academy of Medicine · 2019Article
- Operational evaluation of the RLINE dispersion model for studies of traffic-related air pollutants.Atmospheric environment (Oxford, England : 1994) · 2018Article
- Disease and Health Inequalities Attributable to Air Pollutant Exposure in Detroit, Michigan.International journal of environmental research and public health · 2017Article
- Residential Proximity to Major Roadways and Risk of Type 2 Diabetes Mellitus: A Meta-Analysis.International journal of environmental research and public health · 2016Article
- Particulate Matter Exposure in a Police Station Located near a Highway.International journal of environmental research and public health · 2015Article
- Biological Monitoring of Air Pollutants and Its Influence on Human Beings.The open biomedical engineering journal · 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.
Funding
Abstract
Vehicle traffic is one of the most significant emission sources of air pollutants in urban areas. While the influence of mobile source emissions is felt throughout an urban area, concentrations from mobile emissions can be highest near major roadways. At present, information regarding the spatial and temporal patterns and the share of pollution attributable to traffic-related air pollutants is limited, in part due to concentrations that fall sharply with distance from roadways, as well as the few monitoring sites available in cities. This study uses a newly developed dispersion model (RLINE) and a spatially and temporally resolved emissions inventory to predict hourly PM2.5 and NOx concentrations across Detroit (MI, USA) at very high spatial resolution. Results for annual averages and high pollution days show contrasting patterns, the need for spatially resolved analyses, and the limitations of surrogate metrics like proximity or distance to roads. Data requirements, computational and modeling issues are discussed. High resolution pollutant data enable the identification of pollutant "hotspots", "project-level" analyses of transportation options, development of exposure measures for epidemiology studies, delineation of vulnerable and susceptible populations, policy analyses examining risks and benefits of mitigation options, and the development of sustainability indicators integrating environmental, social, economic and health information.
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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.