Abstract

Research

Synthetic chemicals are an integral part of almost every product value-chain in the modern society. Hence, sustainability analysis of any product or technology involves assessment of environmental impacts from the chemicals used in its life cycle. Life cycle assessment (LCA), a widely used sustainability analysis methodology, facilitates comprehensive analysis of environmental impacts of a product or technology throughout its life cycle right from extraction of resources to manufacturing, use phase and end-of-life. LCA is being increasingly used in the industry for decision making. LCA enables comparison of environmental performance of products, identification of “hot-spots” in manufacturing processes and scope for improving efficiency in value chains. LCA is also at the core of setting and achieving sustainability KPIs (key performance indicators) and for certifications such as Environmental Product Declarations (EPDs).¹

Application of LCA to chemical product systems have faced a major challenge of lack of scientifically robust life-cycle inventory (LCI) data at the production stage. From approximately 80,000 chemicals available in the US market, less than 1% have been accounted for in chemical LCI databases. The lack of chemical LCI data has led to LCA practitioners using simplistic methods such as proxy processes, stoichiometric calculations or completely omitting chemical production data from the analysis. Use of such methods may lead to misrepresentation of environmental impacts associated with use of chemicals while also eliminating opportunities for process improvement and optimization.²

This work presents a methodological framework for generating chemical life-cycle inventories based on core principles of process design and engineering. Chemical production data from patent literature and process industry encyclopedia in combination with process scale-up design calculations and streamlined process simulations have been used to generate chemical life cycle inventory data for more than 200 organic chemicals and pharmaceutical intermediates. This includes data for material input, energy use and emissions from the chemical manufacturing processes. Pinch analysis for heat integration and selection of hot and cold utilities based on energy analysis were used to improve the quality of chemical LCI data generated. Streamlined process simulations for 138 different processes for production of organic chemicals was completed in Aspen Plus V10. Further, process energy data from the simulations is used to develop time-efficient models through multi-variate statistical methods such as regression analysis and machine learning methods such as random forest for predicting energy requirements in chemical manufacturing, a key data input in a chemical LCI.

The chemical LCI data from process scale-up and design calculations was applied for estimating life-cycle greenhouse gas (GHG) emissions from production 20 intravenous anesthetic APIs (active pharmaceutical ingredients) and subsequently to estimate GHG emissions from different anesthetic procedures used in the hospital.³ The GHG emissions for per kg anesthetic APIs ranged from 11 kg CO₂ eq. to 3000 kg CO₂ eq. and had a moderate and positive correlation with the number of synthesis steps involved. This work has been central in several recent studies of sustainability in clinical health care. Key findings from process energy analysis showed that average heating and cooling requirements for the chemical processes were 3 MJ/kg and 4.5 MJ/kg product respectively. Heat integration enables average energy saving of 51% for hot utilities and 30% for cold utilities. The process-based methodology improves the accuracy and comparability of chemical LCI datasets.

Methodologies for rapid and robust generation of chemical LCIs presented in this research promote scientifically accurate chemical LCI data which are crucial for assessing the true health and environmental impacts of chemicals. Further, these methodologies have been used to substantially increase the chemical LCI data available in the literature with a twofold increase in detailed inventory data for APIs and using a uniform methodology to estimate energy requirement in 138 different organic chemicals compared to empirical estimations used in commercial LCI databases.

Candidate Background

Abhijeet Parvatker has a bachelor’s degree in chemical engineering and a master’s degree in Advanced Chemical Process Design from University of Manchester, UK. In his master’s thesis, he worked on a sustainability assessment tool for production of biodiesel from microalgae. In his two-and half-year stint as the Research Engineer in the Sustainability team at SABIC, he performed life-cycle assessment (LCA) for a very diverse product portfolio which included fertilizers, plastics, basic and specialty chemicals, and metals. He also played a key role in developing methodology for calculating avoided emissions from application of SABIC products and in creating an interactive online game which was used for sustainability training in the organization.

Now, a fourth year PhD candidate in the Department of Chemical Engineering, Abhijeet has used his experience in the industry to work on research topics intended at addressing the shortcomings and challenges in effectively using LCA as a sustainability assessment tool. Lack of life-cycle inventory (LCI) data for chemicals is a key-challenge in most LCAs. In addressing this challenge, Abhijeet has worked on projects aimed at developing novel methods to generate rapid and robust chemical LCIs.

Abhijeet gained valuable leadership experience as a Production Engineer and shift leader at Syngenta’s agrochemical production plant in his first job. He has developed excellent interpersonal and negotiation skills working in various cross-functional roles during his time at Syngenta and SABIC. In addition to the experience and the necessary skills, Abhijeet has the vision, dedication, and the resourcefulness required to excel in an industrial role in a sustainability team.

References

(1) International Council of Chemical Association. How to Know If and When It’s Time to Commission a Life Cycle Assessment.

(2) Parvatker, A. G.; Eckelman, M. J. Comparative Evaluation of Chemical Life Cycle Inventory Generation Methods and Implications for Life Cycle Assessment Results. ACS Sustain. Chem. Eng. 2019, 7 (1), 350–367. https://doi.org/10.1021/acssuschemeng.8b03656.

(3) Parvatker, A. G.; Tunceroglu, H.; Sherman, J. D.; Coish, P.; Anastas, P.; Zimmerman, J. B.; Eckelman, M. J. Cradle-to-Gate Greenhouse Gas Emissions for Twenty Anesthetic Active Pharmaceutical Ingredients Based on Process Scale-Up and Process Design Calculations. ACS Sustain. Chem. Eng. 2019. https://doi.org/10.1021/acssuschemeng.8b05473.