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C339: Greenhouse gas emission monitoring using low cost sensor networks (Lead Supervisor: Rod Jones, Chemistry)

Supervisors: Rod Jones (Chemistry) and Neil Harris (Cranfield University)

Importance of the area of research:

There is wide international recognition of the need to slow the global atmospheric growth rate of GHGs in order to mitigate the humanitarian and economic impacts of future climate change. This is embodied in the United Nations Framework Convention on Climate Change (UNFCCC), to which the EU and its member states are parties.

However, at present, the only way of monitoring GHG reduction targets has been though bottom-up (inventory based) estimates, and as such, they are susceptible to significant errors largely resulting from uncertainties in the underlying emission factors. There is therefore a need to monitor and verify the actual emissions based on atmospheric measurements.

Project summary:

The overarching aim will be an improved methodology for using sensor networks to estimate greenhouse gas emissions.

The student will exploit both atmospheric measurements and inversion models. On the measurement side the student will add a new generation of low-cost CO2 and CH4 sensors to an existing network of standard instruments based at sites around East Anglia. On the modelling side the student will use and develop sophisticated inversion techniques to estimate emissions of methane from East Anglia. As part of this, the student will develop a framework for estimating the measurement potential of hypothetical GHG measurement networks.

What the student will do:

The student will undertake analysis of the existing CH4 East Anglia network data, including measurement and data analysis including Bayesian inversion techniques and the Met Office NAME InTem model. S/he would acquire an understanding of the low cost CH4 and CO2 sensor NDIR technology, and would be involved in the field deployment and assessment of the low cost CH4 and CO2 sensors. As part of this the student would be expected to develop practical and computational skills.

The student would be expected to be involved with field work both in the UK and elsewhere, and to present their work at national and international conferences.

Please contact the lead supervisor directly for further information relating to what the successful applicant will be expected to do, training to be provided, and any specific educational background requirements.


Source attribution of air pollution by spatial scale separation using high spatial density networks of low cost air quality sensors, Heimann, V.B. Bright, M.W. McLeod, M.I. Mead, O.A.M. Popoola, G.B. Stewart, R.L. Jones,  Atmospheric Environment, 113, 10-19, 2015. doi:10.1016/j.atmosenv.2015.04.057

Estimates of tropical bromoform emissions using an inversion method, M.J. Ashfold, N.R.P. Harris, A.J. Manning, A.D. Robinson, N.J. Warwick, J.A. Pyle, Atmospheric Chemistry and Physics, 14, 979, 2014. doi:10.5194/acp-14-979-2014

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