Predictive Emission Monitoring System

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Predictive (or Parametric) Emission Monitoring Systems (PEMS) predict the air pollutant emissions from industrial sources using the known emission characteristics of the sources and combining these with key inputs (e.g., fuel consumption, ambient conditions, etc.). PEMS can save 60% cost than traditional continuous emission systems (CEMS) over a five-year period of implementation. Although PEMS are being widely adopted in other countries, the acceptance in Canada, particularly in Alberta is low. A key reason for this is apparently negative past experience, but also the "black box" nature of current PEMS systems does not provide regulators with the level of understanding they need to have confidence in its results. Many PEMS systems use proprietary predictive processes (i.e. the black box). SNC-Lavalin develops and/or applies innovative environmental technologies related to environmental performance measurement. The company is interested in development of promotion of PEMS through collaboration with the University of Calgary. The ultimate goal of this collaborative study is to make PEMS acceptable by Alberta Environment and other governments for air emission monitoring. To achieve this goal, the PEMS models need to be improved by adapting their parameters and algorithms to typical sources in Alberta industry and making the algorithms "open-box" to the users so that they can understand and manipulate the variables as needed under different circumstances. In addition, pilot studies for Alberta industrial sources are needed to better understand the feasibility of the improved PEMS and demonstrate its effectiveness to Alberta and other regulators and stakeholders. The outcome of this research will advance SNC-Lavalin's frontline position in emission monitoring technology and service in Alberta and Canada.