Wednesday, November 21, 2012

Monitoring and Mapping Roadside Emissions in London

Air Pollution Monitoring and Mining Based on Sensor Grid in London (23 page pdf, Yajie Ma, Mark Richards, Moustafa Ghanem, Yike Guo and John Hassard, Sensors, Jun1. 2008)

Also discussed here: (8.5 min video, Institute of Physics, Imperial College London, Mar. 16, 2012)

And here: A Wireless Sensor Network Air Pollution Monitoring System - arXiv (Kavi K. Khedo, Rajiv Perseedoss and Avinash Mungur, International Journal of Wireless & Mobile Networks, May 2010)

Today we review research from London, UK, aimed at monitoring vehicle emissions using a relatively low cost approach that makes use of the spectral discrimination of absorption of UV wavelength by various pollutants to estimate roadside pollution levels. This type of instrument (named “GUSTO”) may be combined in a network to produce pollution maps that show how and where high and low levels are produced during the day- and how these in turn may affect health of vulnerable populations such as at schools.  

Key Quotes:

 Road traffic makes a significant contribution to the following emissions of pollutants: benzene(C6H6), 1,3~butadiene, carbon monoxide(CO), lead, nitrogen dioxide(NO2), Ozone(O3), particulate matter(PM10 and PM2.5) and sulphur dioxide(SO2)”  

we present a distributed infrastructure based on wireless sensors network and Grid computing technology for air pollution monitoring and mining, which aims to develop low-cost and ubiquitous sensor networks to collect real-time, large scale and comprehensive environmental data from road traffic emissions for air pollution monitoring in urban environment.”

 a hierarchical network architecture formed by the mobile sensors and stationary sensors is designed, which makes full use of the roadside devices to fix the stationary sensors as well as the public vehicles to carry the mobile sensors; a ultra violet sensor unit GUSTO which can realize up to 1Hz data collection frequency with high accuracy and low unit cost; a sensor grid framework to provide the processing, integrating, and analyzing heterogeneous sensor data in both centralized and distributed ways”

“GUSTO is an acronym for Generic Ultraviolet Sensors Technologies and Observations based on open-path DUVASTM (Differential= Ultraviolet Absorption Spectroscopy) technology and measures and transmits the volume mixing ratios (at ppb levels) of key urban pollutants in real-time.”

 the GUSTO sensor technology itself that measures pollutants accurately at pbb (part per billion levels) at very short intervals (~2 seconds).”

 at 9am, the Red cloud that covers the main roads and the area around the main roads is characterized by high volumes of NO and SO2…At 15:30 in the afternoon, the Blue clouds cover the school areas, which are in high volumes of NO2 and O3 with low volume of NO. While Yellow cloud featured by high volume of SO2 covers the factory area…At 17:00 in the afternoon, it seems to be the worst pollution distribution time within a day. Besides the transport emission around the roads and the factory emission, some other locations such as the hospitals contribute some kind of pollutants, including the sulphide and nitride.”  

provided an overview of the urban air pollution analysis within MoDisNet project, describing the network framework, the GUSTO sensor technology, the mobile sensor grid architecture and the distributed data mining algorithm.” And here:
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