Sustainable drug manufacturing planning under different regulatory scenarios
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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 Andr é s Malcolm, Libin Zhang and Andreas A. Linninger 11/03/2005

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Sustainable drug manufacturing planning under different regulatory scenarios

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.


How to implement emission reduction for a region

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?


Overview

Overview

  • Regulatory types

  • Challenges

  • Optimal Plant behavior

  • Optimal regulations


Command and control

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


  • Environmental taxes

    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


    Cap and trade model

    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


    Methodology optimal regulation

    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.


    Sustainable drug manufacturing planning under different regulatory scenarios

    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


    Methodology optimal regulation1

    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


    Map superstructure into plant infrastructure

    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


    Challenge compliance for co 2 reduction

    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


    I command and control

    I. Command-and-Control

    Regulatory Forecast

    Production Forecast

    Raw Materials

    Products

    Process

    time

    Waste

    Waste Forecast

    Initial Infrastructure

    Production / Emission Forecast


    Formulation

    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


    Command and control multiperiod formulation milp

    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


    I command and control scenario

    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


    Ii tax change scenario

    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


    Iii cap and trade scenario

    III. Cap and Trade Scenario

    Objective Formulation

    Min. Total Cost

    15% Cap reduction by Year 5

    Environmental Constraints


    Iii cap and trade scenario results

    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


    Comparison cost for enforcing emission reduction

    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


    Design of optimal regulations optimal control

    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


    Conclusions and future work

    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


    Acknowledgements

    Acknowledgements

    • NSF Grant DMI-0328134

    • Environmental Manufacturing Management (EvMM) fellowship from the UIC Institute for Environmental Science and Policy


    Sustainable drug manufacturing planning under different regulatory scenarios

    Thank you!


    Emission trading formulation

    Emission Trading Formulation

    Exp (Net Present ET. Cost )

    Permits Balance

    Environmental Constraint

    Close Market Constraint

    Regulator Allocation Constraint


    Tax multiperiod formulation

    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


    Emission trading multiperiod formulation

    Emission Trading Multiperiod Formulation

    s.t.

    Net Present Op. Cost

    Net Present Investment Cost

    Infrastructure Augmentation

    Equipment Allocation

    Path Constraints for Superstructure


    Emission trading formulation1

    Emission Trading Formulation

    Net Present ET. Cost

    Permits Balance

    Environmental Constraint

    Regulator Allocation Constraint


    Optimal emission trading multiperiod design

    Optimal Emission Trading Multiperiod Design

    s.t.

    Net Present Op. Cost

    Net Present Investment Cost

    Infrastructure Augmentation

    Equipment Allocation

    Path Constraints for Superstructure


    Emission trading formulation2

    Emission Trading Formulation

    Net Present ET. Cost

    Permits Balance

    Environmental Constraint

    Regulator Allocation Constraint

    Budget Constraint

    Emission Reduction Constraint


    Regulatory practices

    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?


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