Sustainable Drug Manufacturing Planning under Different Regulatory Scenarios

1. Sustainable Drug Manufacturing Planning under Different Regulatory Scenarios AIChE 2005 Annual Meeting Cincinnati, OH October 30-November 4 Paper 540c Session 10A04: Design for Sustainability Andrés Malcolm, Libin Zhang and Andreas A. Linninger 11/03/2005 Laboratory for Product and Process Design, Department of Chemical Engineering, University of Illinois, Chicago, IL 60607, U.S.A.

2. Plant 1 Plant 2 Plant 3 How to Implement Emission Reduction for a Region? Plant 1 Plant 1 Emissions Reduction Plant 2 60 Tons 60 Tons 60 Tons 60 Tons 60 Tons 60 Tons 60 Tons 60 Tons Plant 3 Desired Reduction 50 Tons 44 Tons 44 Tons 44 Tons 44 Tons 44 Tons 44 Tons 44 Tons 44 Tons 44 Tons 44 Tons 44 Tons Plant 4 Manufacturer Sustain production while decreasing emissions Regulator Enforce emission reduction withminimum disturbance • Challenges • Regulator • Set the regulatory levels to reduce emission with minimum impact to plants • Manufacturer • Optimal operation with new regulations : How and when to invest?

3. Overview • Regulatory types • Challenges • Optimal Plant behavior • Optimal regulations

4. Initial Threshold Desired reduction New Threshold Threshold Threshold Time Command-and-Control Regulates the level of emissions allowed • Emissions rates • Concentration • Total quantity of a pollutant • Requires polluters to use specific technologies • Scrubbers with 90% efficiency • Best Available Control Technology (BACT) • Standards assuming firms are using BACT Disadvantages: • Regulator decides when and how plants should invest • Emissions standards do not guarantee a specific ambient pollution level • No incentive for sustainable Process Improvement

5. Technology 2 New Tax Level Initial Tax Level Initial Tax Level Savings Capital Investment Qinitial Emission Reduction Environmental Taxes • Regulator – Sets a tax level per volume of pollutant emitted. • Manufacturers – Invests to Reduce Emissions or Pay Tax Technology 1 Abatement Cost Qfinal Emissions

6. 17 Tons 17 Tons 17 Tons 17 Tons 17 Tons Total Emissions 17 Tons 20 Tons 15 Tons 15 Tons 15 Tons 15 Tons 13 Tons 12 Tons 12 Tons 12 Tons 12 Tons Initial Emissions Initial Emissions Initial Emissions Initial Emissions Initial Emissions Initial Emissions Initial Emissions Initial Emissions 60 Tons 60 Tons 60 Tons 60 Tons 60 Tons 60 Tons 60 Tons 60 Tons New Cap New Cap New Cap New Cap New Cap New Cap New Cap New Cap 17% Desired Reduction 44 Tons 44 Tons 44 Tons 50 Tons 44 Tons 44 Tons 44 Tons 44 Tons 44 Tons 44 Tons 44 Tons 44 Tons Reduction 5 tons Reduction:2 tons Reduction:3 tons Cap-and-Trade Model • Regulator - Distributes allowances equal to the Cap amount • Manufacturers -Invest to Reduce Emissions or Purchase Allowances 22 Tons 20 Tons 22 Tons 22 Tons 20 Tons 18 Tons TRADE PLANT B PLANT A PLANT C Sells 2 allowances

7. Methodology – Optimal Regulation Combinatorial Process Synthesis for Regional Emission Control Regulatory Models Combinatorial Process Synthesis for Regional Emission Control Regulatory Models WASTE MANAGEMENT SCENARIO, W PLANT PRODUCTION Waste forecast for each plant (Amount, FORECAST Composition) Plant 1 Plant 4 1. SUPERSTRUCTURE GENERATION Plant 2 DIAGNOSIS Generation of Treatment Goals Plant 3 POLLUTANTS TRESHOLDS, R PRESELECTION TREATMENT DATABASE, T Dictated by occupational health Treatment Step Identification (Recycle, Distill, Extract, etc.) and safety standards EXECUTION Simulate Residue Estimate Cost Possible Technological Options for Recycle and treatment • Chakraborty A. and Linninger A. A.; Plant-Wide Waste Management. 1. Synthesis and Multi-Objective Design, Industrial and Engineering Chemistry Research, 2002, 41 (18): 4591-4604. • Chakraborty A. and Linninger A. A.; "Plant-Wide Waste Management. 2. Decision Making under Uncertainty", Industrial and Engineering Chemistry Research, 2003, 42:35 –369. • Chakraborty A. and Linninger A. A.; Plant-Wide Waste Management. 3. Long Term Operation and Investment Planning under Uncertainty, Industrial and Engineering Chemistry Research, 2003, 42:4772 – 4788.

8. PLANT 4 PLANT 3 PLANT 2 ONSITE ONSITE ONSITE LEACH ONSITE ONSITE ONSITE ONSITE ONSITE ONSITE ONSITE ONSITE REUSE ONSITE REUSE REUSE REUSE REUSE SCRUB SCRUB SCRUB SCRUB SCRUB REUSE REUSE REUSE REUSE REUSE REUSE REUSE REUSE REUSE REUSE SWER SWER REUSE REUSE Ion Ex Ion Ex SWER SWER SWER SWER Ion Ex EVAP EVAP EVAP EVAP EVAP EVAP EVAP WAO WAO ATM ATM ATM ATM ATM ATM ATM ATM ATM ATM ATM ATM ATM ATM ATM ATM ATM ATM ATM ATM ATM ATM ATM ATM ATM ATM ATM ATM ATM ATM ATM SCR ATM INC INC INC INC INC INC INC INC INC INC SCR INC INC INC INC INC BIO INC INC INC INC BIO INC BIO LF LF LF LF LF PLANT 1 PLANT 2 PLANT 3 PLANT 4 Regional Superstructure SynthesisIdentify all feasible recovery and treatment options for a whole region

9. Combinatorial Process Synthesis for Regional Emission Control Regulatory Models Combinatorial Process Synthesis for Regional Emission Control Regulatory Models WASTE MANAGEMENT SCENARIO, W PLANT PRODUCTION Waste forecast for each plant (Amount, FORECAST Composition) Plant 1 Plant 4 1. SUPERSTRUCTURE GENERATION Plant 2 DIAGNOSIS Generation of Treatment Goals Plant 3 POLLUTANTS TRESHOLDS, R PRESELECTION TREATMENT DATABASE, T Dictated by occupational health Treatment Step Identification (Recycle, Distill, Extract, etc.) and safety standards EXECUTION Simulate Residue Estimate Cost Possible Technological Options for Recycle and treatment 2. SUPERSTRUCTURE OPTIMIZATION PLANT MODELS REGULATORY FORECASTS Actual inventory of equipment NETWORK OF TREATMENT PLAN A - Command and Control types and capacities, d B - Emission Tax max C - Emission Trading TREATMENT PLAN OPTIMIZATION PLANT BUDGETS FOR ALL PLANTS (MILP) Maximum investments, I max REGION - WIDE OPTIMAL TREATMENT POLICY Methodology – Optimal Regulation

10.  Environmental Regulations Site Specific Permits Map Superstructure into Plant infrastructure Market Forecast Business Forecast Plant Model To Offsite Recovery Chemical Tr. Plant To Offsite Treatment REGULATORY MODELS Incinerators WasteWater Solvent Rec. Plant ??? Planning for Operations and Investments

11. Challenge: Compliance for CO2 reduction • Predict Compliance Cost & Expected Emissions under: • Command-and-Control • Tax • Cap-and-Trade • Optimal regulatory design for desired CO2 reduction with minimal disturbance to manufacturers Emissions Reduction 60 Tons 60 Tons 60 Tons 60 Tons 60 Tons 60 Tons 100 Tons 15% Desired Reduction 85 Tons 44 Tons 44 Tons 44 Tons 44 Tons 44 Tons 44 Tons 44 Tons 44 Tons 44 Tons 44 Tons

12. I. Command-and-Control Regulatory Forecast Production Forecast Raw Materials Products Process time Waste Waste Forecast Initial Infrastructure Production / Emission Forecast

13. REGION Formulation Predict plant behavior under different regulatory scenarios • Hypothesis: All plants will minimize their costs while satisfy the constraints • Minimize each plant’s cost as a multi-objective optimization Plant 3 Plant 1 Plant 2

14. Command-and-Control : Multiperiod Formulation (MILP) Min. Total Cost s.t. Net Present Op. Cost Net Present Investment Cost Infrastructure Augmentation Equipment Allocation Path Constraints for Superstructure C&C Environmental Constraints

15. I. Command and Control Scenario 15% Emission Reduction by Year 5 • Most of the investments in year 5 • 15% reduction enforced for each plant • Little flexibility for planning Environmental Constraints Projected Annual Investments Expected Annual Emissions

16. 0.1 0.09 0.08 0.07 0.06 Price [$/kg] 0.05 0.04 0.03 0.02 0.01 0 0 1 2 3 4 5 6 7 8 9 10 Period II. Tax Change Scenario Objective Formulation Min. Total Cost 160% Tax Increase to induce a 15% Emission Reduction by Year 5 Environmental Constraints Tax increase Annual Investments Annual Emissions • Need information of plant’s marginal costs to determine tax level (difficult to implement) • Manufacturers have some freedom to plan • No guarantee a specific ambient pollution level is met

17. III. Cap and Trade Scenario Objective Formulation Min. Total Cost 15% Cap reduction by Year 5 Environmental Constraints

18. III. Cap and Trade Scenario: Results 15% Cap reduction by Year 5 Annual Emissions Annual Investments Annual Emission Trading Buy Sell • Investment schedules are flexible • 15% reduction enforced region is guaranteed

19. Comparison: Cost for Enforcing Emission Reduction Predicted Cumulative Cost • Command and control • Forces to invest in the year of change. • Difficult to control the total level emissions • Tax • Difficult to set tax level (trial and error) • Cap and Trade • Flexibility to time investments • Less expensive Policy • Effective way to accurately control emissions Total Annualized Cost and total Emissions

20. Design of ‘optimal’ regulations (optimal control) • Minimal environmental impact compatible with manufacturers’ budget • Regulatory decisions as design variables, C(t) • Optimal Plant behavior and Optimal Regulation

21. Conclusions and Future Work • Cap-and-Trade gives the minimum compliance cost • Construct a whole region map of feasible treatments (superstructure) • Mathematical model to estimate compliance cost for different regulatory policies • Rigorous optimization to obtain optimal plant’s behavior (MILP) • Solved optimal policy design problem Future work • Include uncertainty in market and price forecasts (game theory) • Include price flexibility in formulation

22. Acknowledgements • NSF Grant DMI-0328134 • Environmental Manufacturing Management (EvMM) fellowship from the UIC Institute for Environmental Science and Policy

23. Thank you!

24. Emission Trading Formulation Exp (Net Present ET. Cost ) Permits Balance Environmental Constraint Close Market Constraint Regulator Allocation Constraint

25. Tax Multiperiod Formulation s.t. Net Present Op. Cost Net Present Investment Cost Infrastructure Augmentation Equipment Allocation Path Constraints for Superstructure Net Present Tax Cost

26. Emission Trading Multiperiod Formulation s.t. Net Present Op. Cost Net Present Investment Cost Infrastructure Augmentation Equipment Allocation Path Constraints for Superstructure

27. Emission Trading Formulation Net Present ET. Cost Permits Balance Environmental Constraint Regulator Allocation Constraint

28. Optimal Emission Trading Multiperiod Design s.t. Net Present Op. Cost Net Present Investment Cost Infrastructure Augmentation Equipment Allocation Path Constraints for Superstructure

29. Emission Trading Formulation Net Present ET. Cost Permits Balance Environmental Constraint Regulator Allocation Constraint Budget Constraint Emission Reduction Constraint

30. Regulatory Practices • Need to reduce air emissions in a sustainable way. • Different alternatives to enforce emission reduction. • Existing command-and-control approach • Environmental taxes • Market based approaches : Cap-and-trade • Environmental policies affect manufacturing planning • Challenges: • Regulator • Set the regulatory levels : emission thresholds, tax level or emission cap • Manufacturer • Optimal operation with new regulations : How and when to invest?