Avient Corporation, an innovator of materials solutions, recently collaborated with Carbon Minds to conduct cradle-to-gate carbon footprint analyses of their products using Carbon Minds data.

In this interview, we sit down with Jan Sueltemeyer and Niki Loura to delve into the project and offer first-hand insights to others who are also working on conducting cradle-to-gate carbon footprint analyses of their products.

When you started this project, what was your goal? What were you trying to achieve?

Our goal was to provide specific carbon footprint values for Avient products to both customers and the public. As sustainability grows increasingly important across industries, our carbon footprint study focused on several key objectives. First, we aimed to drive innovation by enabling strategic product development that prioritizes low-carbon-footprint solutions. Second, we sought to foster internal improvements by maximizing efficiency, identifying GHG emissions hotspots, and reducing both costs and emissions. Third, we wanted to strengthen supplier-customer relationships by offering transparent information, enhancing trust and collaboration throughout the value chain. Additionally, the study supports product differentiation, giving us a competitive edge when comparing different product grades or families. Finally, it aligns with our sales strategy by helping us unlock new market opportunities and expand our reach.

What barriers did you face?

A lack of trusted, high-quality sources for the carbon footprint values of major polymers and chemical compounds in the supply chain presents significant challenges. Additionally, the complex production processes and technologies used to manufacture chemical raw materials often prevent suppliers from providing accurate carbon footprint data for certain products. Without precise values that reflect different technologies and production regions, it becomes challenging to deliver reliable carbon footprint information throughout the supply chain. To address this, we sought carbon footprint data for raw materials that could be combined with our internal data, ensuring compliance with ISO 14067:2018, to develop our cradle-to-gate carbon footprint calculation method.

If you want to reduce Greenhouse Gas Emissions, the first thing to understand is the carbon footprint of your products to have a solid baseline.

Jan Sueltemeyer

Global Sustainability Leader

How did you overcome the barriers?

By identifying raw materials lacking carbon footprint data and using the best available datasets to convert our measurable data into GHG emissions, we were able to address critical data gaps. Carbon Minds supported us by providing reliable, third-party-verified data that is fully compliant with ISO 14067:2018.

What have you achieved in the end?

Developing a carbon footprint calculation method in compliance with ISO 14067 enables us to accurately assess the carbon footprint of Avient products with precision and transparency. Additionally, having access to a trusted and reliable carbon footprint library for raw materials is crucial for supporting our carbon footprint studies, gaining a deeper understanding of the environmental impact of our products, and setting realistic climate goals to reduce GHG emissions.

Working with CarbonMinds data allows us to increase the accuracy of our PCF calculations and enhance credibility and transparency in our PCF reporting and communication.

Niki Loura

Global Carbon Footprint Expert

How did Carbon Minds support you along your journey?

Carbon Minds has played a crucial role in providing us with product carbon footprint data from its chemicals database for key polymers and chemicals in the industry. This has enabled us to calculate the carbon footprint of Avient products transparently and accurately, in compliance with ISO 14067:2018. Additionally, Carbon Minds helps us gain a deeper understanding of the environmental impact of raw materials by considering their production regions and the technologies used.

Discover how we can help you achieve your sustainability goals.

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