The document models residential water, energy, greenhouse gas emissions, and costs in California. It develops models to account for variability in location and heterogeneity in household consumption. Monte Carlo simulations are used to generate representative households. Results show potential water and energy savings from conservation strategies. The author concludes that managing water and related energy jointly can significantly reduce emissions, and targeting conservation based on heterogeneity is important for policy.

1. MODELING RESIDENTIAL
WATER, ENERGY, GHG EMISSIONS and COSTS
IN CALIFORNIA
WEC 2014 CONFERENCE MEXICO CITY, MAY 23rd 2014
ALVAR ESCRIVA-BOU
alesbou@gmail.com
@alesbou
notjustwater.wordpress.com

2. MOTIVATION
• In California, 19% of all
electricity and 30% of
all natural gas is used to
extract, move, treat and
heat water (CEC 2005).
• Residential end-uses:
5.4% of all electricity
and 15.1% of all natural
gas used in the state.
OBJECTIVES
• Model to obtain water
end-uses, water-related
energy, GHG emissions
and costs for California
households.
• Implement and analyze
potential conservation
strategies.
INTRODUCTION1
WEC 2014 CONFERENCE MEXICO CITY, MAY 23rd 2014

3. PREVIOUS STUDIES
• Fidar et al. (2010) → Water-related energy and CO2
emissions at household level based on average
end-use values (UK).
• Kenway et al. (2011, 2013) → Water and energy
end-use model and CO2 emissions based in one
standard house (Australia)
• Abdallah and Rosenberg (2013) → End-Use model
accounting for heterogeneity (United States).
INTRODUCTION1
WEC 2014 CONFERENCE MEXICO CITY, MAY 23rd 2014

4. CONTRIBUTIONS2
• VARIABILITY in
location
WEC 2014 CONFERENCE MEXICO CITY, MAY 23rd 2014

5. CONTRIBUTIONS2
WEC 2014 CONFERENCE MEXICO CITY, MAY 23rd 2014
• VARIABILITY in location
• HETEROGENEITY in consumption
Household characteristics User’s behaviors
External conditions

6. CONTRIBUTIONS2
WEC 2014 CONFERENCE MEXICO CITY, MAY 23rd 2014
• VARIABILITY in location
• HETEROGENEITY in consumption
• Water and energy RATE STRUCTURES

7. METHODOLOGY3
WEC 2014 CONFERENCE MEXICO CITY, MAY 23rd 2014
• Data-driven:
• “California Single-Family Water Use Efficiency Study”
(DeOreo, 2011).
• “Residential Energy Consumption Survey” (DOE, 2009).
• Build representative houses:
• Monte Carlo simulations.
• Probability distributions for parameters affecting water
and energy use.

8. METHODOLOGY3
• Water End-Use Model → Using “California Single-Family
Water Use Efficiency Study” (DeOreo, 2011).
• Energy Model → Using “Residential Energy Consumption
Survey” (DOE, 2009).
• GHG Emissions → Using Emission Factors from California
Climate Action Registry (CCAR) and US Energy Information
Administration.
• Simulate Conservation Strategies.
Water End-Use
Model
Water Costs
Energy End-Use
Model
Energy Costs
GHG Emissions
Conservation
Strategies
WEC 2014 CONFERENCE MEXICO CITY, MAY 23rd 2014

9. WATER END-USE MODEL4
WEC 2014 CONFERENCE MEXICO CITY, MAY 23rd 2014
Residential Water Use =

10. WATER END-USE MODEL4
𝑄𝑠ℎ𝑜𝑤𝑒𝑟 =
#𝑆𝑡𝑑 𝑆ℎ𝑤 ∙ 𝑄 𝑆𝑡𝑑 + (#𝐿𝑜𝑤𝐹𝑙𝑜𝑤𝑆ℎ𝑤) ∙ (𝑄 𝐿𝐹𝑆ℎ𝑤)
#𝑆ℎ𝑜𝑤𝑒𝑟𝑠
∙ 𝑆ℎ𝑜𝑤𝑒𝑟 𝐿𝑒𝑛𝑔ℎ𝑡 ∙ (𝑆ℎ𝑜𝑤𝑒𝑟 𝐹𝑟𝑒𝑞𝑢𝑒𝑛𝑐𝑦) ∙ (#𝑅𝑒𝑠𝑖𝑑𝑒𝑛𝑡𝑠)
𝑄𝑜𝑢𝑡𝑑𝑜𝑜𝑟 =
𝐸𝑇 ∙ 𝐴𝑟𝑒𝑎𝐿𝑎𝑤𝑛 ∙ 𝑘 𝑐 𝐿𝑎𝑤𝑛
+ 𝐴𝑟𝑒𝑎𝐺𝑎𝑟𝑑𝑒𝑛 ∙ 𝑘 𝑐 𝐺𝑎𝑟𝑑𝑒𝑛
+ 𝐴𝑟𝑒𝑎𝑃𝑜𝑜𝑙 ∙ 𝑘 𝑐 𝑃𝑜𝑜𝑙
∙ 𝐴𝑝𝑝𝑙𝑖𝑐𝑎𝑡𝑖𝑜𝑛𝑅𝑎𝑡𝑖𝑜
WEC 2014 CONFERENCE MEXICO CITY, MAY 23rd 2014
Household characteristics
Users’ behaviors
External conditions

11. MONTECARLO SIMULATIONS FOR WATER5
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 50 100 150 200 250
GPD
CDF ToiletModel vs.Real Data in Davis
Modeled
Metered
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 50 100 150 200 250
GPD
CDF Shower Model vs.Real Data in Davis
Modeled
Metered
WEC 2014 CONFERENCE MEXICO CITY, MAY 23rd 2014

12. MONTECARLO SIMULATIONS FOR WATER5
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 100 200 300 400 500 600 700 800
GPD
CDF Indoor Model vs.Real Data in Davis
Modeled
Metered
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 500 1000 1500 2000 2500
GPD
CDF Outdoor Model vs.Real Data in Davis
Modeled
Metered
WEC 2014 CONFERENCE MEXICO CITY, MAY 23rd 2014

13. • From End-Water Uses → Hot water, using hot water prob.
distributions per end-use (EBMUD, 2002).
• Energy Calculation – WHAM (Lutz et al., 1999):
𝑄𝑖𝑛
=
𝑣𝑜𝑙 ∙ 𝑑𝑒𝑛 ∙ 𝐶𝑝 ∙ (𝑇𝑡𝑎𝑛𝑘 − 𝑇𝑖𝑛)
𝜂 𝑟𝑒
∙ 1 −
𝑈𝐴 ∙ 𝑇𝑡𝑎𝑛𝑘 − 𝑇𝑎𝑚𝑏
𝑃𝑜𝑛
+24 ∙ 𝑈𝐴 ∙ (𝑇𝑡𝑎𝑛𝑘 − 𝑇𝑎𝑚𝑏)
ENERGY MODEL6
WEC 2014 CONFERENCE MEXICO CITY, MAY 23rd 2014
Household characteristics
Users’ behaviors
External conditions

14. MONTECARLO SIMULATIONS FOR ENERGY7
WEC 2014 CONFERENCE MEXICO CITY, MAY 23rd 2014

15. MONTECARLO SIMULATIONS FOR ENERGY7
WEC 2014 CONFERENCE MEXICO CITY, MAY 23rd 2014

16. • Electric emission factors obtained from California Climate Action Registry,
and Natural Gas emission factors from US Energy Information
Administration:
GHG EMISSIONS8
WEC 2014 CONFERENCE MEXICO CITY, MAY 23rd 2014
Power Utility
Electricity
(kg CO2/kWh)
Natural Gas
(kg CO2/therm)
PG&E 0.24 5.31
San Francisco City and County 0.30 5.31
San Diego Gas & Electric 0.32 5.31
Los Angeles Department of Water and Power 0.58 5.31
Southern California Edison 0.30 5.31

17. SOME RESULTS
WEC 2014 CONFERENCE MEXICO CITY, MAY 23rd 2014
9
Water

21. SOME RESULTS
WEC 2014 CONFERENCE MEXICO CITY, MAY 23rd 2014
9
Energy and CO2

25. SOME RESULTS
WEC 2014 CONFERENCE MEXICO CITY, MAY 23rd 2014
9
Costs

29. SOME RESULTS
WEC 2014 CONFERENCE MEXICO CITY, MAY 23rd 2014
9
Simulations

31. POLICY
IMPLICATIONS
10
WEC 2014 CONFERENCE MEXICO CITY, MAY 23rd 2014
• Differences in “willingness to adopt”
conservation strategies

33. POLICY
IMPLICATIONS
10
WEC 2014 CONFERENCE MEXICO CITY, MAY 23rd 2014
• Differences in “willingness to adopt”
conservation strategies
• Targeting

34. < 25%
> 75%
<25%
>75%

35. x2.0

36. x2.4

37. x2.3

38. POLICY
IMPLICATIONS
10
WEC 2014 CONFERENCE MEXICO CITY, MAY 23rd 2014
• Differences in “willingness to adopt”
conservation strategies
• Targeting
• Planning scales: Efficiency for whom?

41. • Managing water and water-related energy
jointly is a way to reduce significantly
greenhouse emissions in California
TAKE HOME
MESSAGES
11
• Stimulate customers to save water
adding the water-related energy costs.
• Consideration of
heterogeneity and
variability is essential
to define policies.
WEC 2014 CONFERENCE MEXICO CITY, MAY 23rd 2014

42. WEC 2014 CONFERENCE MEXICO CITY, MAY 23rd 2014
notjustwater.wordpress.com

43. THANK YOU!!!
WEC 2014 CONFERENCE MEXICO CITY, MAY 23rd 2014
ALVAR ESCRIVA-BOU
alesbou@gmail.com
@alesbou
notjustwater.wordpress.com