How 102 different operations use proactive ambient air quality monitoring and forecasting systems as a critical tool for success

We've analysed usage data from real-time and predictive systems for air quality management systems using data from 102 of Envirosuite's ongoing projects over the last last 12 years.

So, what's really driving adoption at industrial and municipal operations and how are they used in daily activities?


7 min

Forecasting of ambient air quality impacts has been occurring globally for decades.  
Originally undertaken by local, regional and national governments there is now a highly established use case within the private sector.  

Near-field, near real-time predictive air quality modelling and management systems, which focussed on air quality management of specific facilities, or groups of facilities, were first adopted by mining, minerals processing, wastewater treatment and governmental organisations 10 to 15 years ago.  

What has driven adoption of ambient air quality monitoring and forecasting systems?  

In short, acting on ambient air quality issues to mitigate risk requires information. It's not enough to just know that there is an issue, it’s imperative to know how to focus the action efficiently on the cause of the problem.  

For many types of emissions, seeing the problem is not possible because the pollutant is invisible. Emissions are also often highly variable over time and their impact strongly depends on weather conditions. 

Initially, proactive ambient air quality monitoring systems seemed to be driven by the need for industry to improve environmental performance. New methods were needed to achieve existing ambient air quality compliance requirements or new compliance requirements were introduced that required new approaches to ambient air quality management. 

In some cases, environmental permits required the adoption of near, real-time ambient air quality monitoring or some sort of forecasting of air quality by the facility in question. 

Typically delivered and supported by private enterprises, but used by the organisations themselves, there has been little public analysis of the uptake and characteristics associated with these types of systems. 

Analysis of use cases from 102 ongoing projects using proactive ambient air quality monitoring and forecasting 

As part of the 2022 CASANZ Conference in Adelaide, Australia Envirosuite’s Global Head of Mining, Matt Scholl, and Manager - EVS Water, Chaim Kolominskas, published a paper titled “Uptake and evolution of predictive and near real time air quality modelling, forecasting and management systems”.  
The objective of this paper 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.  

This paper analyses trends in design and use of real-time and predictive systems for air quality management over the last 12 years from anonymised data from Envirosuite’s ongoing projects in this area, 102 projects in total. 

Projects were categorised in 1 of 3 ways as follows: 

  • Air quality/metrological modelling and forecasting 

    • These types of systems use some sort of automated meteorological modelling and/or dispersion modelling for the purposes of air quality management. 

  • Emission source identification modelling 

    • This category included solutions that were used to identify the source of an air quality impact, incident or complaint. Modelling, such as reverse trajectory modelling was common to all solutions in this category. 

  • Rapid analysis of ambient air quality monitoring data  

    • This category of solution included the automated analysis, reporting and distribution of monitoring information related to air quality management

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.

Adoption insights from 102 municipal or industrial applications using ambient air quality monitoring and forecasting systems

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 (ending in April 2022) 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.  

Usage statistics provided several further interesting insights: 

  • 62% of projects were associated with more than 1 type of solution. 

  • Projects with the most frequent users accessed the solution over 20 times per day. 

  • Users at 28% of sites access the solution at least daily, on average. 

It’s clear from these insights that detailed, actionable insights are imperative for taking meaningful action on ambient air quality issues across multiple solutions.


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.

How can ambient air quality monitoring networks be used to identify problematic emissions sources? 

Today’s industrial operators or municipal authorities cannot rely on ambient air quality monitoring networks alone for ongoing analysis to be proactive or risk being a nuisance. 

It's not enough to just know that there is an issue, you need to know how to focus the action efficiently on the cause of the problem.

An upcoming capability in Envirosuite's Omnis software called Activity Location is designed to help customers who experience an emissions problem at their operation who don’t know the source.  

Information from Activity Location provides users with accurate insights to effectively target areas creating emission concerns. Users can ‘nowcast’ to make specific operational decisions more accurately than ever before. Historical activity location can provide a definitive analysis to effectively investigate emissions events.
Additionally, the Source Identification capability in Omnis provides value for operators conducing ambient air quality monitoring at their facilities that need to understand which emission sources at their site require immediate attention.   
The example below shows how powerful visualisations can give landfill operators context of their current emissions and where on their facility they should focus their mitigation energy.  

Ask us how you can achieve the same with your ambient air quality monitoring network today 

Interested in finding out how you can do the same?   
Our solutions assist operators from a growing number of operations around the world with ambient air quality monitoring, mitigating emissions impact and daily management of complex infrastructure.
Get in touch with us today to find more.