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Analysing Forest Hydrocarbons with Networks of Sensors

Periodic Reporting for period 1 - AlFHoNSo (Analysing Forest Hydrocarbons with Networks of Sensors)

Reporting period: 2015-06-01 to 2017-05-31

In this project the fellow (Dr. Peter M. Edwards) has taken a multidisciplinary approach to develop a novel methodology for the study of atmospheric variability using low cost sensor technologies. Our ability to accurately represent atmospheric chemical and physical processes in predictive models is central to the management of global issues such as air pollution and climate change. Measurements of atmospheric composition are vital if we are to challenge and improve our understanding of the atmospheric system. The current research paradigm for atmospheric chemical observation is the use of highly technical and expensive instruments to provide extremely detailed and accurate information at a particular location. Unfortunately the high cost and size of these instruments prohibits the deployment over long time periods or of large numbers over large spatial scales. This means that although our understanding of processes occurring at particular locations is supported by detailed observations, our understanding of the spatial and temporal variability in these processes is much more uncertain. What is needed is an observational methodology that compliments existing approaches, but enables the study of atmospheric spatial and temporal variability. This fellowship has taken a first step towards this, by developing a small, low power instrument based on low cost sensors that will provide information on atmospheric variability.
Volatile organic compounds (VOCs) are emitted both naturally from vegetation, and from human activities. These compounds play an important role in controlling the regional and global concentration of ozone, aerosol and methane, all of which are key players in climate change and air quality degradation. Current detection techniques, such as gas chromatography, provide detailed information of the concentrations of individual VOCs. The existing body of literature suggests that we have a reasonable understanding of the dominant VOCs in different regions of the globe, but representing the spatial and temporal variability of these compounds in models remains challenging. Recent developments in cheap, small, lower power sensors for atmospheric gas detection offer a potential opportunity to address this measurement gap, as such instruments could readily be deployed over long timescales or as a distributed network over large spatial scales. This fellowship used the fellows experience in instrument development combined with expertise in VOC detection, electronic engineering and advanced statistical techniques at the University of York to develop a prototype instrument that uses low cost sensors for the study of VOC variability (in particular those from forested ecosystems). The individual objectives that were identified to achieve this goal were:

• Laboratory characterisation of low cost VOC sensors.
• Develop an observational methodology that could be applied over large spatial and/or temporal scales.
• Develop a data analysis methodology that maximises the potential of low cost sensor technologies.
• Demonstrate the new methodology alongside established techniques.

Through an extensive program of laboratory experiments a range of commercially available low cost VOC sensors were characterized for atmospherically relevant conditions. Sensor signal stability and detection limits where improved through improvements in electronics and signal handling and a sensor was identified that will enable the study of atmospheric VOC variability. During these laboratory experiments it was identified that in order to provide the required information on total VOC variability, it will be necessary to correct for multiple interferences on the sensor signal from other atmospheric constituents. The complexity of these interferences prevent simple corrections, and it was decided that the most practical approach, while maintaining the instruments low cost, was to use signals from a range of different low cost sensors and an advanced regression algorithm to separate the signals from different atmospheric constituents. Although the findings from these laboratory experiments, and the development of new statistical tools, delayed the overall project, the public interest in low cost sensors for atmospheric measurement meant the results proved very timely and resulted in multiple invited presentations and publications from the fellow. Further experiments focused on improving the reliability of data from low cost sensor devices by targeting inter-sensor variability.
Ultimately this work resulted in the development of a low cost sensor based instrument being developed, and comparison experiments with existing techniques are currently underway in an urban environment in China and a tropical rainforest in Malaysia. This data will demonstrate the performance of this novel instrument for the detection of VOCs from both human activities and forested ecosystems. As the project has outrun the fellowship timescales, funding for its continuation have been secured from The University of York and the UKs National Centre for Atmospheric Science. The fellowship will ultimately produce new earth system science, but also a transferable chemical technology applicable to other research questions as well as high value European industries.