Process Mass Intensity calculator.

Process Mass Intensity (PMI), developed and championed by the ACS Green Chemistry Institute Pharmaceutical Roundtable, measures the total mass of all materials used in a process relative to the mass of desired product obtained. Unlike atom economy — which is theoretical and molecular-weight-based — PMI uses real experimental masses, capturing reagents, solvents, catalysts, and workup materials alike. The ideal value of PMI = 1 means every gram of input became one gram of product: zero waste.

The formula

PMI is directly related to E-factor: PMI = E-factor + 1. A PMI of 1 is the theoretical ideal — all input mass becomes product. In practice, solvents and aqueous workup typically account for 80–90% of process mass.

Typical PMI by industry sector

Sector	Typical E-factor (Sheldon)	Derived PMI	Key driver of waste
Oil refining	< 0.1	< 1.1	Highly optimized, continuous, large-scale processes
Bulk / commodity chemicals	< 1–5	< 2–6	Continuous processes; minimal solvent use
Fine chemicals	5–50	6–51	Batch processes; moderate solvent volumes
Pharmaceuticals	25–100+	26–101+	Multi-step batch synthesis; solvent-intensive workup
Ideal (theoretical minimum)	0	1	Zero waste — all inputs become desired product

Sector E-factor ranges adapted from R. A. Sheldon, "The E factor at 30: a passion for pollution prevention", Green Chem., 2023, 25, 1704–1728; PMI values are derived using PMI = E-factor + 1.

Strengths and limitations

PMI in context: complementary green metrics

Metric	What it measures	Stage
Atom Economy (AE)	Theoretical fraction of reactant molecular weight ending up in desired product, from the balanced equation	Design
% Yield	Fraction of theoretical product actually isolated	Experimental
E-factor	Mass of all waste per mass of product (E-factor = PMI − 1)	Experimental
PMI (this tool)	Total mass of all inputs per mass of product, the most holistic process-level metric; PMI = E-factor + 1	Experimental
RME (Reaction Mass Efficiency)	AE × yield × stoichiometric factor, a combined practical efficiency	Both

PMI vs. E-factor: what's the difference?

PMI and E-factor describe the same underlying process mass data from two different reference points. E-factor counts only the waste generated per unit of product, while PMI counts all material that entered the process per unit of product, including the product itself. Because every input either leaves the process as product or as waste, the two metrics differ by exactly one unit — as the derivation below shows.

Derivation

1. Start from the two definitions: $$PMI = \frac{m_{\text{inputs}}}{m_{\text{product}}} \qquad\qquad E\text{-factor} = \frac{m_{\text{waste}}}{m_{\text{product}}}$$
2. Apply mass balance: every gram of input either leaves the process as product or as waste, so $$m_{\text{inputs}} = m_{\text{product}} + m_{\text{waste}}$$
3. Substitute this into the PMI definition: $$PMI = \frac{m_{\text{product}} + m_{\text{waste}}}{m_{\text{product}}}$$
4. Split the fraction into two terms: $$PMI = \frac{m_{\text{product}}}{m_{\text{product}}} + \frac{m_{\text{waste}}}{m_{\text{product}}} = 1 + \frac{m_{\text{waste}}}{m_{\text{product}}}$$
5. The second term is E-factor by definition, giving the relation: $$PMI = 1 + E\text{-factor}$$

The "+1" is the product's own mass expressed as a fraction of itself — always exactly 1. PMI carries this extra term because it counts the product as part of the inputs it's tracking; E-factor doesn't, since it only counts waste.

Worked check: 100 g of total inputs yielding 10 g of isolated product means 90 g is waste. E-factor = 90/10 = 9, and PMI = 100/10 = 10 = 9 + 1. A process with PMI = 1 has an E-factor of 0 (no waste at all); a process with E-factor = 9 has a PMI of 10 (nine parts waste for every one part product). Use whichever framing suits the audience: E-factor emphasises waste to minimise, PMI emphasises total material consumed.

References are sorted alphabetically by first author.

1. ACS Green Chemistry Institute Pharmaceutical Roundtable. PMI Benchmarking Report. 2018. Available at acsgcipr.org. — Industry PMI benchmarking data across pharmaceutical processes.
2. P. T. Anastas and J. C. Warner, Green Chemistry: Theory and Practice, Oxford University Press, 1998. ISBN 978-0-19-850698-0. — Original statement of the 12 Principles; frames waste prevention as Principle 1.
3. D. J. C. Constable, A. D. Curzons and V. L. Cunningham, Green Chem., 2002, 4, 521–527. DOI. — Comparative assessment of green chemistry metrics including PMI and E-factor.
4. A. D. Curzons, D. J. C. Constable, D. N. Mortimer and V. L. Cunningham, Green Chem., 2001, 3, 1–6. DOI. — Originates Reaction Mass Efficiency (RME); basis for the AE × yield × stoichiometric-factor decomposition referenced in the metric-comparison table.
5. C. Jiménez-González, C. S. Ponder, Q. B. Broxterman and J. B. Manley, Org. Process Res. Dev., 2011, 15, 912–917. DOI. — Defines PMI; demonstrates that solvents account for ~85% of process mass in pharmaceutical synthesis.
6. R. A. Sheldon, Green Chem., 2007, 9, 1273–1283. DOI. — E-factor fifteen years on: typical values across chemical sectors; relationship to PMI.
7. R. A. Sheldon, Green Chem., 2017, 19, 18–43. DOI. — E-factor 25 years on: updated metrics, solvent recovery, and relationship with PMI.
8. R. A. Sheldon, The E factor at 30: a passion for pollution prevention, Green Chem., 2023, 25, 1704–1728. DOI. — E-factor 30-year retrospective; source of the industry-sector E-factor benchmarks from which the PMI values above are derived.

If you use this tool in teaching or published work, please cite the DodecaGreen portal as the source.