Quantifying the Health Benefits of Reduced Wood Smoke from Energy Efficiency Programs in the Pacific Northwest (The Wood Smoke Report). Presentation to the RTF October 14 th,

Presentation Objective Seeking RTF approval on The Wood Smoke report. The report concludes that health impacts due to wood smoke are quantifiable and attributable with a large possible range of estimates. Health impact exists, impact on cost effectiveness is likely to be significant for some measures. Report, once approved, will be presented to the Council as an RTF product. Council will consider the report’s findings in it’s deliberations on the Methodology for Determining Quantifiable Environmental Costs and Benefits in the Seventh Power Plan. 2

Presentation Objectives: Shaping the Discussion Seeking RTF approval on whether the report adequately presents relevant issues and fairly assesses if health impacts from reduced wood smoke can be reliably quantified and attributed to EE program activity? Are there any gaps in the report that we need to better address to meet the objectives above? We are not developing a policy recommendation as to whether or how the RTF should consider health impacts in its work. 3

Presentation Outline Background: o Northwest Power Act: Cost Effectiveness Requirement and o Context of current analysis (History) Methodology: four step process o Investigation into each step o Conclusion and recommendation on each step o RTF feedback on each step RTF Decision & Discussion 4

Northwest Power Act Cost Effectiveness Definition, Section 3(4): … requires the Council to estimate and compare the “incremental system cost” of different generating and conservation resources. “System cost” is defined as: “an estimate of all direct costs of a measure or resource over its effective life, including, if applicable, the cost of distribution and transmission to the consumer and, among other factors, waste disposal costs, end-of-cycle costs, and fuel costs (including projected increases), and such quantifiable environmental costs and benefits as the Administrator determines, on the basis of a methodology developed by the Council as part of the plan, or in the absence of the plan by the Administrator, are directly attributable to such measure or resource.” 5

Context of Current Analysis We burn a lot of wood in the Pacific Northwest RTF work on ductless heat pumps (DHP) found that DHP displace some supplemental wood heat in some residential homes o RTF uses this analysis to account for the reduction in wood purchasing in costs for measure level cost effectiveness calculations Back of the envelope analysis showed the health benefits from avoided wood smoke to be significant, larger than value of electric savings 6

Context (contd.) RTF commissioned a screening level study that showed wood smoke benefits could be significant (approx. $0.70 to $1.60/ kWh wood heat displaced) o This study focused on large, uniform reductions in wood use across the PNW RTF requested an in-depth study to understand: o Can the health effects from changes in wood smoke be directly attributable to programs? o Can the health effects from changes in wood smoke can be quantified and monetized? 7

Potential Annual Impact of DHP Program with Approximate Estimates: Magnitude of benefit is comparable to the retail price of electricity Note: Numbers will vary by region. 8 Total potential: Health benefits against electric savings Health Benefit ($million) Electric energy savings (GWh) Health benefit per electric kWh saved Low$74 1,255 $0.06 High$167$0.13 Total potential: Health benefits against wood savings Health Benefit ($million) Wood savings (GWh) Health benefit per wood kWh saved Low$ $0.23 High$167$0.52

Monetary Value of Reduced Wood Smoke: Four Step Process using DHP Program Example 1. Quantify Emission Changes 2.Dispersion Modeling 3. Estimate of Health Effects 4. Monetize Health Effects 9

Investigating the Four Step Process: Each of the four steps, were assessed for the following: Uncertainty in estimates produced by each step Status of science behind the calculations conducted in each step Availability of data to conduct thorough analysis for each step. 10

Step 1. Quantify Emission Changes How much supplemental wood heat is displaced by EE programs? DHP o Billing data: After installing DHPs, homes with supplemental heat tend to increase the larger portion of heat load met with electric appliances. o Conclusion: When you install a DHP in a home, the home uses less wood for supplemental heating. Weatherization and other measures o Weatherized homes have lower heating loads, so they should use less wood heat. (But RTF hasn’t studied this directly) o RTF currently gives a wood-reduction credit for Wx measures. o For interactive measures that tend to increase heat load, this would go the other way. 11

Step 1. Quantify Emission Changes: DHP Wood-Savings Estimates Have electric billing for 3,400 DHP program homes. Homes divided into supplemental-heat/ no-supplemental- heat groups. Compare groups to estimate fraction of load met with supplemental fuels Do separately pre- and post-DHP 12

Step 1. Quantify Emission Changes: DHP Wood-Savings Estimates … then use calibrated heat load estimates to get supplemental fuel savings. 13

Step 1. Conclusions and Recommendation This step is quantifiable, changes in wood smoke can be attributed to EE program activity. The RTF can determine changes in wood smoke on a per measure basis. Uncertainty: Variance depends on granularity and sample sizes. o For DHPs, the zone 1 sample size is large enough that variance for zone 1 is low; in zones 2 and 3 the variance is moderate. Status of science: Methods for DHP based on pre-/post- billing data and basic site characteristics can be transparent and sound. o Since billing data tends to be highly variable, there are limits to the precision to such methods. o Control groups should be considered for future studies. o Other measures may require different methods, possibly less reliable. Availability of data: Currently-available data is sufficient for estimating average wood smoke savings due to DHP. Estimates for weatherization and other measures would require additional data. 14

Step 1. Quantify Emission Changes Does the RTF agree that the report accurately characterizes this step in terms of: Can wood smoke reduction be attributed to EE program activity? Is wood smoke reduction quantifiable? Does the RTF agree with the report’s conclusions on: Uncertainty Status of science Availability of data 15

Step 2. Dispersion Modeling Once released as wood smoke through a chimney, where do the pollutants end up? o Wood smoke contains many pollutants, main pollutant of interest are PM 2.5 particles. o In addition to being present in wood smoke, PM 2.5 are also formed downstream due to chemical reactions involving wood smoke pollutants. Dispersion modeling mathematically estimates the concentration of PM 2.5 after accounting for environmental effects, and downstream chemical reactions. 16

Step 2. Dispersion Modeling (contd.) Dispersion modeling currently conducted using COBRA. o EPA recommended screening tool. More sophisticated dispersion modeling tools exist. o Model atmospheric chemistry in more detail. o Give greater precision at the county level. o Don’t know if they provide better results at a regional level. Critical to estimate post dispersion concentration of PM 2.5 relative to high population density areas. o More sophisticated models required for this purpose. 17

This step is quantifiable; changes in ambient levels of PM 2.5 can be modeled once wood smoke changes in the region are known. Uncertainty and status of science: Dispersion modeling is a well established science, validated software packages with varying level of precision and detail are available. Availability of data: EPA regularly collects and publishes detailed data on pollutant concentration levels on a county by county basis. Recommendation: Explore the use of a higher precision dispersion models to better inform the local impacts from efficiency program delivery. o Because total health benefit from a fixed PM 2.5 decrease is proportional to the population of a county, o Efficiency programs may not reduce wood use proportionally in all counties. 18 Step 2. Conclusions and Recommendation

Step 2. Dispersion Modeling Does the RTF agree that the report accurately characterizes this step in terms of: Can decrease in ambient PM 2.5 levels be attributable to decrease in wood smoke caused by EE program activity? Is decrease in ambient levels of PM 2.5 quantifiable w.r.t geography and population? Does the RTF agree with the report’s conclusions on: Uncertainty Status of science Availability of data 19

Step 3. Estimate Health Effects What is the relationship between change in PM 2.5 and human health? Inhale less PM 2.5  Change health outcomes o Treatable illnesses o Premature mortality Changes in mortality risk are the biggest cost contributor. o EPA Integrated Science Assessment: Accumulated evidence sufficient to establish a causal link: Lower PM 2.5  lower premature mortality rate 20

Step 3. Conclusion and Recommendation This step is quantifiable; the ISA quantification of the epidemiological link can be used to estimate health impact from decrease in ambient level PM 2.5 within a range. Uncertainty: Most ISA approved studies report results that are statistically significant and independent of the other studies. Individual studies provide wide error bands, but collectively studies yield reasonably reliable estimates. Status of science: Health effects can be difficult to study quantitatively. EPA’s ISA is result of a rigorous scientific process with extensive peer review. o RTF recommendations based on the rigor and openness of ISA process. o ISA indicates that there is still uncertainty around the exact form of the concentration-response mechanism. Availability of data: If required, the RTF can use ISA results “off-the- shelf”. (Don’t need access to the raw data.) 21

Step 3. Estimate Health Effects Does the RTF agree that the report accurately characterizes this step in terms of: Can health impacts be attributed to change in ambient PM 2.5 levels? Are health effects due to changes in ambient levels of PM 2.5 quantifiable? Does the RTF agree with the report’s conclusions on: Uncertainty Status of science Availability of data 22

Step 4. Monetize of Health Effects What is the economic value of the health impact due to decreased PM 2.5 concentration? Two types of health impact: morbidity and mortality. Majority of the health impact (> 98%) due to adult mortality. o Adult mortality characterized by VSL (Value of Statistical Life) 23

Step 4. Monetize Health Effects (contd.) Value of Statistical Life (VSL) is… o How much is a micro-risk reduction to mortality worth to you?  Would you be willing to pay $10 to reduce the risk of future death by %?  Hard question to answer, has been studied extensively. o Not the value of preventing a certain death of a given person. 24

Conceptualizing VSL It’s how much we are willing to pay for a little improvement in long term health/ reduction in mortality, …. not for protection against sure DEATH. 25

Step 4. Monetize Health Effects A WTP (willingness to pay) estimate normalized by the magnitude of mortality risk reduction, i.e. VSL = WTP/Risk Reduction. o Two types of VSL WTP studies:  Revealed Preference  Stated Preference EPA recommends a VSL of $7.4 Million (2008 $) with a standard deviation of $ 4.7 million. o 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.” o Most of the 26 studies estimate VSL between $1 and $12 million. 26

Step 4. Conclusion and Recommendation The monetary value from reduced mortality is quantifiable. As a technical body the RTF could be used to inform methods for interpreting the cost effectiveness results from different VSL values. Uncertainty: Most studies estimate of VSL between $1 million and $12 million. o What we really know, is the order of magnitude of VSL. o Different govt. agencies use slightly different VSL values.  EPA conducted meta-analysis and recommends a mean value for its policy analysis. Status of science: Economists have settled on WTP methods to estimate VSL. The science behind the methods of estimation continue to evolve and refine. Availability of data: If required, RTF can use existing VSL study results “off-the-shelf” 27

Step 4. Monetize Health Effects Does the RTF agree that the report accurately characterizes this step in terms of: Can health effects due to decrease in ambient levels of PM 2.5 be quantified in economic terms? Does the RTF agree with the report’s conclusions on: Uncertainty Status of science Availability of data 28

RTF Proposed Motion: “I _________ move that The Wood Smoke Report be approved as an RTF product.” 29