1. Michelle M. Rogers, Michigan Department of Environmental Quality Carol J. Miller, Shawn P. McElmurry, Guoyao Xu, Weisong Shi, Caisheng Wang, Cheng-Zhong Xu, PhD Wayne State University – College of Engineering Water Sustainability Workshop A Smart-Phone Application for Home Emissions Estimates

2. Total generation: 4,120 billion (kWh) 3,950 billion (kWh) in 2009 Source: http://www.eia.doe.gov WHY? Energy –Emissions

3. Polluting Emissions from Electricity Generation http://www.gpo.gov/fdsys/pkg/FR-2012-02-16/pdf/2012-806.pdf http://www.epa.gov/mats/actions.html

4.  Air Quality  Visual  Health (asthma)  GHG………Climate (?)  Contaminant Deposition  Surface Water  Soils  Vegetation  Food Chain  Fish Consumption  And,…. Even for the “non-environmentalist”………  Policy: Government Specified Caps Emissions Effects

5. Problem: How to identify emission potential? Locational Marginal Price as Proxy for Generator Type LMP at time t i Hydro & Nuclear Coal Natural Gas Oil Price ($/MWh)

6.  LMPs based on marginal cost of supplying the next increment of electric demand at a specific location  LMP Accounts for:  generation marginal cost (fuel cost)  physical aspects of transmission system (constraint in transmission lines)  Cost of marginal power losses Locational Marginal Prices (LMP)

7. Methodology  Use LMP to point to the marginal fuel type  Calculate emissions associated with that fuel type for a specific area (or specific generator)

8. Environmental Optimization Linking Consumption to Emissions 1. Source Identification Dispatch adjusted every 5 minutes within MISO 2. Emission Quantification Function of generator type

9. Locational Marginal Prices  LMPs available from MISO  (Midwest Independent System Operator)  LMPs for select Commercial Pricing Nodes (CPNs) available every 5 minutes

10. Locational Marginal Prices…spatial variation LMP = f (space,time)

11. Locational Marginal Prices….temporal variation

12. Emission Rates  LMP  Marginal Generator Type  Air Emissions  Measured Air Emissions Data from EPA’s eGRID  (Emissions & Generation Resource Integrated Database)  Data on thousands of power plants in the US  Sort by EGCL code (Electric Generating Company, Location-Based)  i.e., all of DTE-operated plants in SE Michigan WE WANT THIS TO BE DEFINED ON THE FINEST GRID POSSIBLE….compare to an approach based on national averages of emissions/KWh

13. Emission Rates  Calculate average emission rate for entire area for each fuel type  Example, Detroit Edison: (2008 data)  LMP  Marginal Generator Type  Air Emissions Air Emissions in pounds pollutant per MWhr generated (lb/MWh) PollutantNuclearCoalNatural GasDistilled Fuel Oil SO2010.541.652.3445 NOX03.051.5721.73 CO2 equiv0207122921862 Hg05.26E-053.62E-065.81E-06 Pb1.09E-073.10E-051.66E-063.65E-05

14. Putting it Together: the HERO app  HERO = Home Emissions Read-Out  (LMP  Marginal Generator Type  Air Emissions)  Applying this concept to household energy use  Android App for smart phones

15. 14 HERO: Home Emissions Read-Out HERO ARCHITECTURE

16. HERO Input  HERO can automatically find nearest CPN based on phone’s GPS  User also has choice to pick location from map

17. HERO Output  Current, Past, and Projected Future emissions  CO 2, NO X, SO X, Mercury, Lead

18. 17 HERO Screen Shots

19. 18

20.  User can view more to see background information on CO 2, NO X, SO X, Mercury, Lead  Environmental Effects, Human Health Effects  Example: NO X & SO X

21. 20 LEEM: Locational Emissions Estimation Methodology Input: Address Geographic Location Closest LMP Node Link LMP to Marginal Generator Output: Real-Time Emissions

22. 21  HERO published in GooglePlay  https://play.google.com/store/apps/details?id=com. amaker.herotest&feature=search_result#?t=W251b GwsMSwyLDEsImNvbS5hbWFrZXIuaGVyb3Rlc3Q iXQ.. https://play.google.com/store/apps/details?id=com. amaker.herotest&feature=search_result#?t=W251b GwsMSwyLDEsImNvbS5hbWFrZXIuaGVyb3Rlc3Q iXQ

23. 22 Improvements?

24. 23 Server-Based Approach

25. 24 Test Case of Emissions Benefits ApplianceFrequency (d -1 ) Cycle Length (hrs) Power (kW) Energy/ cycle (kWh) Intermittent (Y/N) Preferred Time Hr (1 - 24) Water Heater1.003.001.293.87YES 4 Defrost Cycle2.000.330.700.23NO 1 Dishwasher0.502.00.981.97NO 22 Clothes Washer 1.000.50.610.31NO 20 Clothes Dryer0.860.754.593.44NO 19

26. 25 BEST/WORST CASE PERFORMANCE Region Node LocationYear Based on LMP type Average change in target pollutant Greatest change achieved by any pollutant Least change achieved by any pollutant RFCMMonroe, MI2009RT-68%-84%-33% RFCMMonroe, MI2007RT-78%-88%-49% RFCMMonroe, MI2009DA-27%-61%+1% RFCMSt. Clair, MI2009RT-68%-84%-32% RFCMMidland, MI2009RT-70%-86%-29% SRMWLabadie, MO2009RT-74%-80%-49% MROW Fergus Falls, MN 2009RT-70%-72%-64%

27. 26 Great Lakes Benefits Great Lakes Resident Engages Energy Consuming Device LEEM Optimiza tion Change in Demand Reduction in Hg Emissions Reduced Hg in Fish Fishing Restricti on Lifted Consumer utilizes local resources

28. 27 Extension of Project

29. 28 Thanks to Great Lakes Protection Fund  THANK YOU Water Sustainability Workshop: A Smart-Phone Application for Home Emissions Estimates