Dylan Orpen

The cost of monitoring greenhouse gas emissions from landfill sites is of major concern for regulatory authorities. The current monitoring procedure is recognised as labour intensive, requiring agency inspectors to physically travel to perimeter borehole wells in rough terrain and manually measure gas concentration levels with expensive hand-held instrumentation. In this article we present a cost-effective and efficient system for remotely monitoring landfill subsurface migration of methane and carbon dioxide concentration levels. Based purely on an autonomous sensing architecture, the proposed sensing platform was capable of performing complex analytical measurements in situ and successfully communicating the data remotely to a cloud database. A web tool was developed to present the sensed data to relevant stakeholders. We report our experiences in deploying such an approach in the field over a period of approximately 16 months.

This paper describes multiple field deployments of autonomous gas monitoring platforms spanning durations in excess of 12 months. These trials form part of an on-going collaboration with the Environmental Protection Agency (EPA) in monitoring landfill migration of greenhouse gases, i.e. methane (CH <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sub> ) and carbon dioxide (CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ). Target gas concentrations were automatically recorded via infrared (IR) gas sensors calibrated for the respective gases, with this data being logged remotely every six hours to a central base-station. The autonomous platform with its web-based portal interface provides a flexible alternative to the existing labor-intensive, manual monitoring routines. The duration of the data herein represents one of the longest continuous field deployments of an environmental monitoring device. The real-time monitoring of the gas levels achieved by the bespoke platforms has proven to contribute significantly towards the improved management of landfill sites.

Society is increasingly accustomed to instant access to real-time information, due to the ubiquitous use of the internet and web-based access tools. Intelligent search engines enable huge data repositories to be searched, and highly relevant information returned in real time. These repositories increasingly include environmental information related to the environment, such as distributed air and water quality. However, while this information at present is typically historical, for example, through agency reports, there is increasing demand for real-time environmental data. In this paper, the issues involved in obtaining data from autonomous chemical sensors are discussed, and examples of current deployments presented. Strategies for achieving large-scale deployments are discussed.