Life cycle cost and environmental assessment research at MIT s Concrete Sustainability Hub

Transcription

1 Spring TTCC/National Concrete Consortium, April 2-4, 2013 Life cycle cost and environmental assessment research at MIT s Concrete Sustainability Hub Jeremy Gregory

2 Governments are being forced to do more with less Feb 14, 2013 Governments Look for New Ways to Pay for Roads and Bridges Slide 2

3 Our actions today affect the financial health of future generations Slide 3

4 Our actions today affect the environmental health of future generations Slide 4

5 A life cycle approach can quantify future impacts Slide 5

6 Every engineering decision is a balance of three main factors 2. Cost & performance equally important; environment not important 1. All factors equally important Environment & performance more important than cost Environmental Impact Slide 6

7 Hub pavement research supports designers and decision-makers Tools Performance: MEPDG or DOTs Cost: LCCA Environmental Impact: LCA Hub research improves existing tools by: Incorporating uncertainty Quantifying risk Highlighting data that are key impact drivers Goal Pavement design that balances: Performance Cost Environmental Impact This enables designers and decision-makers to: Focus on key drivers of decisions Understand risk and uncertainty in decisions Make more informed decisions Slide 7

8 Life Cycle Cost Analysis Slide 8

9 Motivation for Hub LCCA research: improving cost decisions Cost Overruns in Infrastructure Projects Frequency 10% Under 90% Over Size of Cost Overrun (%) Flyvbjerg, Skamris & Buhl, Transport Reviews, 2003 Slide 9

10 It is important to have a life cycle perspective Real Cost Life Cycle Cost Lower initial cost does not necessarily translate to lower life cycle cost Slide 10

11 CSHub LCCA research aims to leverage and extend Leverage existing tools: FHWA s LCCA Technical Bulletin FHWA s RealCost tool Extend existing methods: Quantify sources of risk in infrastructure investment Characterize drivers and trends around those risks Strengthen link between design and LCCA tools Slide 11

12 Hub LCCA research has provided three key insights Uncertainty is pervasive, but tractable Considering possible futures is plausible, valuable Risk is a key perspective for decision makers Slide 12

13 Uncertainty is Pervasive in Pavement LCCA Decisions long before construction Long life-cycle Uncertainty & Risk Cash Flow Uncertainty in unit construction costs Uncertainty in material price evolution Construction Operation Incorporate uncertainty into design inputs, initial construction costs, and future material prices Slide 13

14 CSHub LCCA Methodology Statistically Characterize Uncertainty Present MEPDG Output Propagate uncertainty to understand risk Relative risk Is the difference significant? Future LCCA Model Characterize drivers of uncertainty Slide 14

15 Hub LCCA research has provided three key insights Uncertainty is pervasive, but tractable Considering possible futures is plausible, valuable Risk is a key perspective for decision makers Slide 15

16 Major Construction Material Prices have Evolved Differently Normalized Real Price Index Can these trends be quantified? Will considering trends improve decision-making? Concrete Asphalt Lumber Source: BLS Slide 16

17 Recent construction prices have not matched inflation Why then, should we assume future prices grow with inflation? Can we account for this credibly? 250 Asphalt Normalized Price Index Concrete Consumer Price Index Slide 17

18 Effective Long-term Projections are Plausible, but while all forecasts are wrong some forecasts are useful 140 Real Price of Cement (1998 $) Source: USGS Effective Forecasts Must be built from significant sets of data Must be viewed as probabilistic in nature Slide 18

19 Real Price Forecasting Models 200 Concrete (Direct model) 200 Asphalt (Constituent Based) Real Price Index Real Price Index Slide 19

20 Hub LCCA research has provided three key insights Uncertainty is pervasive, but tractable Considering possible futures is plausible, valuable Risk is a key perspective for decision makers Slide 20

21 Applying the statistical characterization Statistically Characterize Uncertainty Present MEPDG Output Propagate uncertainty to understand risk Relative risk Is the difference significant? Future LCCA Model Characterize drivers of uncertainty Slide 21

22 Sample insight from a Missouri case study Urban Interstate Expected initial AADT of 78,000 Expected initial AADTT of 8,000 HMA 2 Asphalt Surface 3 Asphalt Inter. 7 Base JPCP 11 JPCP w/ 1⅝ in Dowels Located in Joplin, MO Designs and maintenance schedules derived from the recently developed MEPDG software 24 Rock Base Material 6.0 Aggregate Subbase 50 year analysis period Real discount rate of 4% Designs created by independent design firm (ARA) Subgrade Subgrade Slide 22

23 Broadening Scope Alters Relative Competitiveness ~ same 10% difference Net Present value (millions of $ s per mile) JPCP HMA - Initial Cost Discounted Rehabilitation Cost Life Cycle Cost Slide 23

24 Probabilistic Analysis Provides Insight on Relative Risks Cumulative Probability 100% 80% 60% 40% Probabilistic Life-Cycle Cost JPCP 6% mean diff HMA 1% 23% 20% 0% Net Present Value (millions of $'s per mile) Slide 24

25 How frequently does one alternative have lower cost? JPCP Lower Cost HMA Lower Cost 25% 20% In this particular case study, JPCP was lower cost for 69% of the simulations 15% 10% 85% is preferred for statistical significance 5% 0% NPV JPCP/NPV HMA Slide 25

26 Method provides insight on drivers of uncertainty JPCP HMA Percent Contribution to Variance Percent Contribution to Variance Concrete Layer Price Price MEPDG Projection Reliability Other - Asphalt Base Layer Price Subgrade Base Price MEPDG Price Reliability Projection Other Slide 26

27 Life Cycle Assessment Slide 27

28 Life cycle assessment: the tool for quantifying environmental impact Process Inventory Life Cycle Impact Raw Materials Materials Production Energy Processing Chemicals Process Releases to Land Air Emissions Water Effluents Disposal / Recycling Use Manufacture Product Slide 28

29 Pavement LCA scope Scope includes all effects attributable to the pavement design. Extraction and production Transportation Materials Onsite equipment Construction Incorporating use phase in pavement LCA is a recent innovation Pavement-Vehicle Interaction Roughness Deflection Albedo Carbonation Lighting Use Maintenance Excavation Landfilling Recycling Transportation End-of-Life/ Rehabilitation Materials Construction Slide 29

30 Model-based assessment of PVI Pavement Deflection MIT-Model Pavement Roughness MEPDG+HDM4 Structure and Material Deflection & Roughness Fuel consumption Environmental Impact Slide 30

31 Incorporating uncertainty into pavement LCA Environmental Impact We cannot draw meaningful conclusions from this analysis by itself Product A Product B There is significant uncertainty in LCA data and scenarios Incorporating uncertainty into LCA enables us to answer these questions: Is the difference between products statistically significant? What are the key drivers of the difference? Which parameters are most likely to change the relative impacts? Slide 31

32 Hub LCA research has provided three key insights Incorporating uncertainty facilitates robust decision-making A full life cycle perspective is important Uncertainty approach illuminates key drivers of differences in designs Slide 32

33 Case study: dry no-freeze urban interstate HW in Arizona AC 2.5 Asphalt Surface 3 Asphalt Inter. 8.0 Base 12 Agg subbase Subgrade PCC 11.0 JPCP w/ 1.5 in Dia Dowels 6.0 Agg Subbse Subgrade Parameter Value AADTT two Directions 8000 vehicles/day Number of Total Lanestwo 6 Directions AADTT Linear Annual 3% Increase Climate: dry no-freeze AZ Soil Type A-2-6 ADOT Rehabilitation Schedule Functional Unit: 1 center-lane mile over a 50-year analysis period and MEPDG Rehabilitation Schedule Designs created by independent design firm (ARA) Slide 33

34 Is the difference statistically significant? 4.0E E-04 AC PCC PDF 2.0E E E Global Warming Potential (Mg CO2e/km) X 1000 The difference is statistically significant Frequency (%) 18% 15% 12% 9% 6% 3% 0% PCC AC αα Comparison indicator : CCII GGGGGG = ZZ GGGGGG,cccccccc. ZZ GGGGGG,aaaaaaa. αα = PP CCII GGGGGG < 1 α% of the time PCC has lower impact CI GWP =Z GWP,Conc. /Z GWP,Asph Slide 34

35 Hub LCA research has provided three key insights Incorporating uncertainty facilitates robust decision-making A full life cycle perspective is important Uncertainty approach illuminates key drivers of differences in designs Slide 35

36 Case study: dry no-freeze urban interstate HW in Arizona Contribution of different phases 95 th Total Initial const. Use phase M & R End of Life 75 th median 25 th GWP (Mg CO2e/mi) th AC PCC AC PCC AC PCC AC PCC AC PCC AC PCC Use phase is a significant driver of impact Slide 36

37 Case study: dry no-freeze urban interstate HW in Arizona Contribution of use phase components 95 th GWP (Mg CO2e/mi) Carbonation Lighting Fuel loss: Fuel loss: Albedo IRI deflection AC PCC AC PCC AC PCC AC PCC AC PCC Use phase drivers are highly dependent on pavement design and context Slide th 25 th 5 th AC PCC median

38 Hub LCA research has provided three key insights Incorporating uncertainty facilitates robust decision-making A full life cycle perspective is important Uncertainty approach illuminates key drivers of differences in designs Slide 38

39 The key drivers of differences between designs contribution to variance of CI GWP 80% 70% 60% 50% 40% 30% 20% 10% 0% Percentage variation in the difference between alternatives due to variability in parameters Slide 39

40 Please contact me with any questions Additional details: Slide 40