1. Analysis Frameworks for Sustainability: Linking Energy and the Environment EECE Seminar, Friday, November 2, 2007, 11:00am, Lopata 101, Washington University E 449/549 Spring 2014 Update

2. Integrative Science and Engineering for ‘Grand Challenges’ The problems of Energy and Environment (EE) are Grand Challenges Solutions require engineering, biological, socio-economic and other sciences A rigorous and practical integrated framework for EE is not available This is an exploration of frameworks for integrated Energy Environmental Analysis Interested in the EE integration challenge? Join us on the wiki!wiki

3. Sustainable Development (SD) A process of reconciling society’s developmental needs with the environmental limits over the long term. But, What should be developed, what should be sustained? SD as an uncertain and adaptive process, “ in which society's discovery of where it wants to go is intertwined with how it might try to get there ”. During the SD ‘ journey ’ toward sustainability, the pathways have to be ‘ navigated ’ adaptively Continuing the metaphors, science is the compass, giving the directions and laws-regulations are the gyroscope for staying on course. National Academy, 1999

4. Analysis Frameworks Sensory-Motor Feedback Loop (System Science; Regulatory) Assessment Controls Monitoring Causality Loop (Combined Social-Physical-Biological System) Biogeochemical Cycling Loop (Engineering; Biology; Conservation Laws)

5. Analysis Framework I: Materials & Energy Flow Loop

6. Life and non-life on Earth depends on the flow of life- sustaining substances Carbon, nitrogen, phosphorus, calcium are in constant circulation between the earth’s major environmental compartments Earth’s compartments remain in balance as long as the rate of flow of matter and energy in and out of the compartments is unchanged. Changes in the environmental compartments will occur if the circulation (in and out flow) of the substances is perturbed. Atmospheric CO 2 has been increasing because the rate of input is larger than the rate of output from the atmosphere.

7. Major Biogeochemical Processes Visualized by Aerosols Dust storms VolcanoesAnthropogenic pollution Fires Anthropogenic pollution perturbs the natural processes and material flows

8. Setting Goals: Air Quality Goal: Attaining Natural Condition by 2064

9. Andrew: PM spatial and temporal pattern

10. Controls: Sustainability Transition

11. Carbon Emission Trends

14. How and what to Control?? Analysis Framework III – Causality Loop Economic Development with Due Care of the Environment The system approach links human activities and their consequences in closed loop It is the minimum set of linked components – if any missing, the system is crippled Each component depends on its causal upstream driver – and external environment The causal loop can be used as an organizing principle for sustainability analysis

15. Analysis Framework III – Causality Loop Economic Development with Due Care of the Environment Health-Welfare Energy- Environment Socio-Economic

16. Causality: Linear System Model

17. Population - Energy/Goods Consumption– Materials Flow - Emissions E k =  c jk EM j =   b ij c jk GE i =    a i b ij c jk P Industr. Energy Transp. Energy ResCom.Engy Coal Oil GasElectric Energy SOx NOx HC PM Goods &Energy,(GE) iFuels&Mater.(FM), j Emission (EM), k Ind. Chemicals Industr. Goods Pop., P Metals Mercury a i Consump./Person b ij Fuels/Energy c jk Emission/Fuel- jjiiij Consumption of Goods and Energy:GE =  a i P Fuels and Materials Flow:FM =   a i b ij P Emission of Pollutants:EM =    a i b ij c jk P Industrial Prod. Transportation ResComercial EconMeasure(EM)

18. Trend of Indicators SOx = Pop x GDP/P x Btu/GDP x Sox/Btu 1960s 1980s 1990s

19. Carbon Emission Drivers for Transportation 1960-2003 Env 449 Class project, SP 2007 The C emission in transportation sector increased 200% since 1960 The upward drivers were Population, Vehicle/Person and Passenger miles The slight improvement resulted from the better fuel energy efficiency/vehicle

20. Carbon Emission Drivers for US Housing The carbon emissions in the housing sector increased 23% since ‘Kyoto’ (1990-2005) The upward drivers were Population, Housing Units/person and Surface Area/person. The key improvement (13%) resulted from the better energy efficiency/sqft Env 449 Class project, SP 2007

21. Initially, only discussing this portion of model, which ends with the emissions. Population P Economy GDP$/yr Energy Use BTU/yr Fuel Cons. T/yr Emissions T/yr Air Quality ppm Per Capita GDP (GDP/P) Energy Intensity (BTU/GDP) Fuel Eny. Factor (T/BTU) Emissions Factor (T/T) Air Quality Factor (ppm/T) Linear Causality Model

22. Population, per capita GDP, and energy intensity are the same as they were for carbon emissions, because we are dealing with U.S. totals. Unlike the carbon emissions factor, the sulfur emissions factor has decreased considerably since 1970. The overall emissions trend moves with the emissions factor trend. Clean Air Act (1970) Clean Air Act (1990) Sulfur Emissions Change Drivers Graphs found here with original data (“Trend Drivers” tab), and discussed on the Wiki here.here

23. Sulfur Emissions Change Drivers Graphs found here with original data (“Trend Drivers” tab), and discussed on the Wiki here.here

24. Population increases at constant rate of approximately 1%/year. Energy intensity decreases at a decreasing rate; note the shift in derivative magnitude that occurs around 1985. The emissions factor decreases slightly, and relatively constantly over time. Per capita GDP increases at an increasing rate. Oil embargo (1973) Recessio n (2008) Energy Intensity Driven Per Capita GDP Driven Carbon Emissions Change Drivers Graphs found here with original data (“Trend Drivers” tab), and discussed on the Wiki here.here

25. First decade with decrease in overall carbon emissions occurs. Carbon Emissions Change Drivers Graphs found here with original data (“Trend Drivers” tab), and discussed on the Wiki here.here

26. Only difference between two sets of drivers: the emissions factor. Comparison of Emissions Graphs found here with original data (“Trend Drivers” tab), and discussed on the Wiki here.here

27. Comparison of Historical Emissions Graphs found here with original data (“Additional Emissions Data” tab), and discussed on the Wiki here.here Initial Divergence (~1945) Sulfur Emissions Controlled (~1970)

28. Now, extend the linear causality model for sulfur emissions to include ambient sulfur concentrations Linear Causality Model Population P Economy GDP$/yr Energy Use BTU/yr Fuel Cons. T/yr Emissions T/yr Air Quality ppm Per Capita GDP (GDP/P) Energy Intensity (BTU/GDP) Fuel Eny. Factor (T/BTU) Emissions Factor (T/T) Air Quality Factor (ppm/T)

29. Extension of Model to Ambient Sulfur Concentration Graphs found here with original data (“Trend Drivers” tab), and discussed on the Wiki here.here The population, per capita GDP, energy intensity, and emissions factor were all discussed in the previous model. Concentration/e missions term increases over time. Not as constant as would be expected. Ambient average concentrations vary considerably over this time period as well.

30. Extension of Model to Ambient Sulfur Concentration Graphs found here with original data (“Trend Drivers” tab), and discussed on the Wiki here.here

31. Analysis Framework I: Sensory-Motor Loop Assessment Compare to Goals, Plan Reductions Track Progress Controls (Actions) Monitoring (Sensing) Set Goals Assessment turns data into knowledge for decision making & actions through analysis (science & eng.) Monitoring collects multi-sensory data from surface and satellite platforms and Human activities exert pressures, e.g burning fossil fuels, that alter the state of environment. The impaired environmental state, elicits responses, such as regulations in a feedback loop All living organisms use this type of sensory-motor feedback to maintain their existence. Monitoring, Assessment, Control are the necessary steps for sustainable development.

32. Jen: Societal Control Approaches, Measures

33. Class (Les & Jen): Combine causality and Control frameworks; Apply to US, India

34. Class (Andrew): Man-made-natural PM levels

35. Class: Man-made-natural causality drivers for PM

36. Plan for SP 2014 semester Objective: Complete Class Report on Sustainable PM Air Quality ----- Last class: April 23 Final presentations: April 29, AM ---- For the remaining 3 weeks of Apr 7, 14, 21: Expected time allocated: 10 hours/week for each student (3 class + 7 self) Monday class + 2 hours of ‘lab’ work session/week with instructor

37. Summary Frameworks for Energy-Environment Integration: –Sensory-Motor Feedback Loop (System Science) –Biogeochemical Cycling Loop (Materials Balance) –Causality Loop (Socio-economic, Physical, Heatlh/Welfare Sciences) Opportunities: –There is a sensing revolution for monitoring energy-environmental systems –The web facilitates accessing and metabolizing the new observations –There is a more collaborative culture for faster, adoptive learning Key Challenges: –Augmenting reductionist science with integrative systems science –Enhancing information exchange and synergy between disciplines –Inherent structural and dynamic complexity of environmental systems