Presentation Title

Portable Air Quality Data Logging Device to Investigate the Relationship between Particulate (PM2.5) and Carbon Dioxide Concentration in Urban Locations

Faculty Mentor

Jayesh Bhakta

Start Date

17-11-2018 8:30 AM

End Date

17-11-2018 10:30 AM

Location

HARBESON 44

Session

POSTER 1

Type of Presentation

Poster

Subject Area

engineering_computer_science

Abstract

Air quality is increasingly important for populations living in cities. Using the hypothesis that vehicles are a significant source of outdoor particulate concentration (PM2.5), it is expected that it may be correlated with local C02 concentration in urban locations. In order to investigate this, a portable, Arduino based, data logging device incorporating PM2.5, C02, temperature, humidity, and GPS sensors was developed to acquire data at different locations and situations for analysis. The covariance between the acquired time series data for each sensor will be investigated as will the existence of diurnal variations in data acquired at static locations. The design of the instrument and the results of the statistical analysis of that data will be presented.

Summary of research results to be presented

A design for a portable environmental sensor for measuring particulate and C02 concentration will be presented. An analysis of the relationship between CO2 and PM2.5 measurements around roadways will be presented. The covariance between the acquired time series data for each sensor will be investigated as will the existence of diurnal variations in data acquired at static locations.

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Nov 17th, 8:30 AM Nov 17th, 10:30 AM

Portable Air Quality Data Logging Device to Investigate the Relationship between Particulate (PM2.5) and Carbon Dioxide Concentration in Urban Locations

HARBESON 44

Air quality is increasingly important for populations living in cities. Using the hypothesis that vehicles are a significant source of outdoor particulate concentration (PM2.5), it is expected that it may be correlated with local C02 concentration in urban locations. In order to investigate this, a portable, Arduino based, data logging device incorporating PM2.5, C02, temperature, humidity, and GPS sensors was developed to acquire data at different locations and situations for analysis. The covariance between the acquired time series data for each sensor will be investigated as will the existence of diurnal variations in data acquired at static locations. The design of the instrument and the results of the statistical analysis of that data will be presented.