Dataset Information

Developing a smartphone software package for predicting atmospheric pollutant concentrations at mobile locations.

ABSTRACT: There is considerable evidence that exposure to air pollution is harmful to health. In the U.S., ambient air quality is monitored by Federal and State agencies for regulatory purposes. There are limited options, however, for people to access this data in real-time which hinders an individual's ability to manage their own risks. This paper describes a new software package that models environmental concentrations of fine particulate matter (PM2.5), coarse particulate matter (PM10), and ozone concentrations for the state of Oregon and calculates personal health risks at the smartphone's current location. Predicted air pollution risk levels can be displayed on mobile devices as interactive maps and graphs color-coded to coincide with EPA air quality index (AQI) categories. Users have the option of setting air quality warning levels via color-coded bars and were notified whenever warning levels were exceeded by predicted levels within 10 km. We validated the software using data from participants as well as from simulations which showed that the application was capable of identifying spatial and temporal air quality trends. This unique application provides a potential low-cost technology for reducing personal exposure to air pollution which can improve quality of life particularly for people with health conditions, such as asthma, that make them more susceptible to these hazards.

SUBMITTER: Larkin A

PROVIDER: S-EPMC4489712 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature

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Developing a smartphone software package for predicting atmospheric pollutant concentrations at mobile locations.

Larkin Andrew A Williams David E DE Kile Molly L ML Baird William M WM

The computer journal 20150601 6

There is considerable evidence that exposure to air pollution is harmful to health. In the U.S., ambient air quality is monitored by Federal and State agencies for regulatory purposes. There are limited options, however, for people to access this data in real-time which hinders an individual's ability to manage their own risks. This paper describes a new software package that models environmental concentrations of fine particulate matter (PM<sub>2.5</sub>), coarse particulate matter (PM<sub>10</ ...[more]

PMID: 26146409

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Project description:We observed elevated air pollutant concentrations, especially of ultrafine particles (UFP), black carbon (BC) and NO, across the residential neighborhood of the Boyle Heights Community (BH) of Los Angeles, California. Using an electric vehicle mobile platform equipped with fast response instruments, real-time air pollutant concentrations were measured in BH in spring and summer of 2008. Pollutant concentrations varied significantly in the two seasons, on different days, and by time of day, with an overall average UFP concentration in the residential areas of ~33 000 cm-3. The averaged UFP, BC, and NO concentrations measured on Soto St, a major surface street in BH, were 57 000 cm-3, 5.1 µg m-3, and 67 ppb, respectively. Concentrations of UFP across the residential areas in BH were nearly uniform spatially, in contrast to other areas in the greater metropolitan area of Los Angeles where UFP concentrations exhibit strong gradients downwind of roadways. We attribute this "UFP cloud" to high traffic volumes, including heavy duty diesel trucks on the freeways which surround and traverse BH, and substantial numbers of high-emitting vehicles (HEVs) on the surface streets traversing BH. Additionally, the high density of stop signs and lights and short block lengths, requiring frequent accelerations of vehicles, may contribute. The data also support a role for photochemical production of UFP in the afternoon. UFP concentration peaks (5 s average) of up to 9 million particles cm-3 were also observed immediately behind HEVs when they accelerated from stop lights in the BH neighborhood and areas immediately adjacent. Although encounters with HEV during mornings accounted for only about 6% and 17% of time spent monitoring residential areas and major surface streets, HEV contributed to about 28% and 53% of total ultrafine particles measured on the route, respectively. The observation of elevated pollutant number concentrations across the Boyle Heights community highlights how multiple factors combine to create high pollutant levels, and has important human exposure assessment implications, including the potential utility of our data as inputs to epidemiological studies.

Project description:BackgroundResidual Dipolar Couplings (RDCs) have emerged in the past two decades as an informative source of experimental restraints for the study of structure and dynamics of biological macromolecules and complexes. The REDCAT software package was previously introduced for the analysis of molecular structures using RDC data. Here we report additional features that have been included in this software package in order to expand the scope of its analyses. We first discuss the features that enhance REDCATs user-friendly nature, such as the integration of a number of analyses into one single operation and enabling convenient examination of a structural ensemble in order to identify the most suitable structure. We then describe the new features which expand the scope of RDC analyses, performing exercises that utilize both synthetic and experimental data to illustrate and evaluate different features with regard to structure refinement and structure validation.ResultsWe establish the seamless interaction that takes place between REDCAT, VMD, and Xplor-NIH in demonstrations that utilize our newly developed REDCAT-VMD and XplorGUI interfaces. These modules enable visualization of RDC analysis results on the molecular structure displayed in VMD and refinement of structures with Xplor-NIH, respectively. We also highlight REDCAT's Error-Analysis feature in reporting the localized fitness of a structure to RDC data, which provides a more effective means of recognizing local structural anomalies. This allows for structurally sound regions of a molecule to be identified, and for any refinement efforts to be focused solely on locally distorted regions.ConclusionsThe newly engineered REDCAT software package, which is available for download via the WWW from http://ifestos.cse.sc.edu, has been developed in the Object Oriented C++ environment. Our most recent enhancements to REDCAT serve to provide a more complete RDC analysis suite, while also accommodating a more user-friendly experience, and will be of great interest to the community of researchers and developers since it hides the complications of software development.

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Dataset Information

Developing a smartphone software package for predicting atmospheric pollutant concentrations at mobile locations.

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Developing a smartphone software package for predicting atmospheric pollutant concentrations at mobile locations.

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