In my experience, there are two common challenges associated with environmental data: (1) it tends to be some of the most isolated data of an organization and (2) it is primarily oriented towards past events.
Let’s consider emissions data as an example.
(1) While the operations, inventory, supply chain, and financial data of an organization are generally tightly integrated, environmental and sustainability data are often siloed into a single department or even a single laptop’s hard drive. Because of this, both the upstream data required for emissions calculations and the downstream generated emissions data do not flow through the organization.
(2) Emission calculations are generally quantified months or years after the emissions have been generated. At best, this only provides a static snapshot of past emissions. From a compliance standpoint, we only know if we had an exceedance after it has occurred. From a sustainability and emissions reductions standpoint, we only know if we happen to have met our goals.
A digital twin is a virtual representation of a system or process that is created using real-time, simulation, or modeling data. The application of environmental digital twins addresses the issues outlined above by first building the appropriate data pipelines that join operation and instrumentation data with emission factors in real-time, and then makes that data readily accessible through informative metrics, visualizations, and dashboards. There’s no reason that an organization should not be able to know what emissions are being generated by their assets in real-time. There’s no reason that they couldn’t project whether they will be in compliance or meet a sustainability goal by the end of the month based on trends and simulations.
I’m looking forward to presenting on this topic at the AISTech Environmental Solutions conference next week! I’m also working on putting together the main points of the presentation in a Barr Insights blog in the near future. In the meantime, if you’re curious about learning more feel free to reach out or comment below.
We’ll be at the AIST - Association for Iron & Steel Technology‘s Environmental Solutions: Air & Decarbonization training on November 12–14! Check your schedule for “Data-Driven Decarbonization: A Case for Digital Twins and Digital Threads” presented by Kyong Song on Wednesday, November 13, at 2:15 p.m.
Corporate Advanced Quality Assurance Manager
3 个月Congratulations, Joe!