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Wood Smoke Study: RTF Report Technical Subcommittee Meeting September 26 th, 2014 1.

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Presentation on theme: "Wood Smoke Study: RTF Report Technical Subcommittee Meeting September 26 th, 2014 1."— Presentation transcript:

1 Wood Smoke Study: RTF Report Technical Subcommittee Meeting September 26 th, 2014 1

2 Objectives for Today Seeking subcommittee feedback on whether the report: Accurately capture the RTF's understanding of the relevant issues and fairly reflects the assessment of the reliability of quantification? Can the effect be quantifiable and directly attributable (with uncertainty levels comparable to our existing products)? Focusing on the content: Are there gaps in the report that we need to better address to meet the objectives above? 2

3 Out of Scope for Today We are not seeking subcommittee feedback or discussion on the following: Developing a a policy recommendation as to whether the RTF should consider health benefits in its work Debating the science behind the quantification or monetization of health effects Focusing on format or wordsmithing 3

4 Context of Current Analysis We burn a lot of wood in the Pacific Northwest RTF work on ductless heat pumps (DHP) and weatherization found that these measures displace some wood heat in some residential homes RTF used this analysis to account for the reduction in wood purchasing in the costs Back of the envelope analysis showed the health benefits from avoided wood smoke to be significant, larger than value of electric savings 4

5 Context (cont.) RTF commissioned a screening level study that showed wood smoke benefits could be significant (approx. $0.70 to $1.60/ kWh wood heat displaced) This study focused on large, uniform reductions in wood use across the PNW RTF requested an in-depth study to understand: Can the health benefits from reduced wood smoke be directly attributable to programs? Can the health benefits from reduced wood smoke can be quantified and monetized? 5

6 DHP Example with Approximate Estimates: Total DHP Savings potential = 1,900 GWh Total Wood Heat Displaced = 330 GWh Total Health Effect (High) = $ 339 Million High mortality * VSL high end Total Health Effect (Low) = $ 50 Million Low mortality * VSL Low End Possible range of one year of health impacts: Programmatic savings: 3 cents/ kWh to 18 cents/ kWh Wood heat displaced: 15 cents/ kWh to $1.03/ kWh 6

7 Monetary Value of Reduced Wood Smoke: Four Step Process using DHP Program Example Pacific Northwest Emission Quantification Dispersion Modeling Quantification of Health Effects Monetization of Health Effects 7

8 Monetary Value of Reduced Wood Smoke: Four Step Process (Uncertainty Summary) 8 Contribution to variance Status of Science Availability of Data Confidence in Method of Estimate Pacific Northwest Emission Quantification LowHigh Dispersion ModelingMedHighMedMed-High Quantification of Health Effects High MedHigh Monetization of Health Effects HighMed

9 Emission Quantification: Wood Savings per Measure How much wood heat is displaced by EE programs? Weatherization Weatherized homes have lower heating load so they should use less wood heat. But we need additional research to say how much less DHP A fairy clear picture of wood heat displacement here. Billing data shows DHPs save much less electricity in homes with wood heat than in homes without. Conclusion: When you install a DHP in a home, they use less wood for heating. 9

10 Emission Quantification: DHP Wood-Savings Estimates Have electric billing for 3400 DHP program homes. Homes divided into wood-heat/ no-wood- heat groups. Compare groups to estimate fraction of load met with wood Do separately pre- and post-DHP 10

11 Emission Quantification: DHP Wood-Savings Estimates …Then use calibrated heat load estimates to get wood savings. 11

12 Emission Quantification: Subcommittee Feedback In the subcommittee’s opinion, can this step be quantified with reliability comparable to energy savings estimates? Have we adequately addressed questions of: inputs required, uncertainty around those inputs, and potential costs of reducing uncertainty? 12

13 Dispersion Modeling Once released as wood smoke through a chimney, where do pollutants end up? Wood smoke contains many pollutants. Main pollutant of interest are PM2.5 particles. Apart from being present in wood smoke, PM2.5 are also formed downstream due to chemical reactions. Dispersion modeling mathematically estimates the concentration of PM2.5 after accounting for environmental effects, and downstream chemical reactions. 13

14 Dispersion Modeling (contd.) Dispersion modeling currently conducted using COBRA. EPA recommended screening tool. More sophisticated dispersion modeling tools exist. Model atmospheric chemistry in more detail. Give greater precision at the county level Don’t know if they give better results at a regional level. Critical to estimate post dispersion concentration of PM2.5 relative to high population density areas. More sophisticated models required for this purpose. 14

15 Dispersion Modeling: Subcommittee Feedback In the subcommittee’s opinion, can this step be quantified with reliability comparable to energy savings estimates? Does the report adequately address the important issues related to quantification here? 15

16 Quantification of Health Effects Burn less wood  inhale less PM 2.5 Two types of health impact: Changes in risk of treatable illnesses Changes in risk of premature death Changes in mortality risk are the biggest cost contributor. Report references two studies that quantify mortality effect Harvard Six Cities Cohort (Lepeulle, 2012) American Cancer Society Cohort (Krewski, 2006) Studies published with conclusions from extensive formal review 16

17 Quantification of Health Effects: Subcommittee Feedback Does the report adequately address the important issues related to quantification here? In the subcommittee’s opinion, can this step be quantified with reliability comparable to energy savings estimates? 17

18 Monetization of Health Effects What is the economic value of the health impact caused by decreased PM2.5 concentration? Majority of the health impact (~99%) due to mortality. Mortality characterized by VSL (Value of Statistical Life) 18

19 Monetization (contd.) Value per Statistical Life (VSL) is…  A WTP estimate normalized by the magnitude of mortality risk reduction, i.e. VSL = WTP/Risk Reduction  Not the value of preventing a certain death of a given person  Society’s order of magnitude estimate for risk reduction. EPA VSL is $9.4 Million (2010$ at 2017 income level)  Based on a synthesis of 26 WTP studies that have been identified in the Clean Air Act Section 812 Reports to Congress as “applicable to policy analysis.”  VSL estimate usually between $ 1 and $ 12 million. 19

20 Conceptualizing VSL It’s how much we are willing to pay for sunscreen, not for protection against a ….. LIGHTSABER!!! 20

21 Monetization: Subcommittee Feedback Does the report adequately address the important issues related to quantification here? In the subcommittee’s opinion, can this step be quantified (bounded) with reliability comparable to energy savings estimates? 21

22 Overarching Question Does the report accurately reflect our understanding of these issues? Are there any other content additions? 22


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