• CEM exhibitors release a study on the use of near real-time and predictive systems for air quality management at 102 ongoing operations
    Envirosuite’s Omnis software contains combines real-time ambient air quality monitoring data, weather forecasting and emissions modelling to enable uses allows users to manage surrounding ambient air quality.)
  • The image above shows a conceptual mockup of Activity Location – an upcoming feature in Envirosuite’s Omnis software that will allow users to identify unknown emissions sources across their facilities.

Air Monitoring

CEM exhibitors release a study on the use of near real-time and predictive systems for air quality management at 102 ongoing operations

Jul 25 2023

Envirosuite, who will be exhibiting at the upcoming CEM Exhibition and Conference in Barcelona, has publicly released a study on trends in the design and use of real-time and predictive systems for air quality management over the last 12 years from anonymised data from 102 of the company’s ongoing projects in this area.

Envirosuite Global Head of Mining Industrial Matt Scholl and Manager EVS Water Chaim Kolominskas authored a paper on the study entitled ‘Uptake and evolution of predictive and near real-time air quality modelling, forecasting and management systems’. The objective was to understand whether a larger dataset of projects could be used to guide how the design and implementation of nearfield, near real-time and predictive air quality modelling and management systems can be further improved.

Of the 102 ongoing projects considered globally, modelling-based solutions (39%) and monitoring-based solutions (36%) are used equally, with emission source identification modelling solutions used in 25% of projects.

In terms of usage, when 90 days of usage statistics were considered of the 102 active projects, 74% of interactions with the solution were related to monitoring-based solutions. 16% related to modelling and forecasting and 10% related to emission source identification modelling of some kind.

Co-author of the paper, Matt Scholl commented, "This study has reviewed the approaches of market leading companies, who are applying continuous monitoring and predictive management solutions to improve their environmental performance. It shows that the best solutions are where monitoring supports and validates predictive techniques, which provide operations with sufficient time to plan and act in advance of problems, rather than responding to them. It all comes together when these systems are linked with systems for operational decision support to translate the information from these solutions into actions, which enable companies to optimize productivity while also delivering great environmental performance."


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