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Practices by Proxy

Explore the challenges and implications of water practices on climate change, energy consumption, and data reliability. Discover the links between water usage behaviors, environmental impact, and potential solutions.

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Practices by Proxy

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  1. Practices by Proxy Climate, Consumption and Water (and troubles with data...) Dr Ben Anderson University of Essex

  2. Contents Why? Water 'practices' How? Proxies What? Models Problems? Data Where next?

  3. Why: Water is (going to be) a problem Energy problems: Carbon cost of `clean' water The water industry currently accounts for 5 million tonnes of carbon dioxide emissions per Year - almost one per cent of UK greenhouse gas emissions. Environment Agency 2009

  4. Why: Water is (going to be) a problem Energy problems: Carbon cost of `clean' water Supply problems Locally/regionally scarce Climate change? Demand problems 50% used by households Poorly understood Climate change? With no 'behaviour' change and no flow controls Source: DEFRA, 2011

  5. What do we want to know? Practices in which water is implicated Diversity habituation, routine, practical consciousness, tacit knowledge, tradition Performance often neither fully conscious nor reflective Alan Warde, 2005 Why people don’t do what they ‘should’ - Jim Skea, 2011

  6. What do we want to know? Practices in which water is implicated Diversity Proxies for practices? 'Traces' of water Relationship with climate? Mediation, adaptation Relationship to demand? From practices to litres Image: Eric Shipton, 1951

  7. Conceptual Framework Water demand = f(price + demographics + practices + attitudes) + error habituation, routine, neither conscious nor reflective Regulation Market Supply ?? ?? Education Information Persuasion Policy levers & Interventions

  8. Conceptual Framework Water demand = f(price + demographics + practices + attitudes) + error Climate change habituation, routine, neither conscious nor reflective Regulation Market Supply ?? ?? Education Information Persuasion Policy levers & Interventions

  9. How: Expenditures as Proxies Ideal Proxy (LCF 2002-2010) water (l/day) £ water/week Demographics Demographics Fruit & Veg Shampoo,soap detergents Practices £/week Garden products Tea, coffee, juices Price Regional Climate/Weather linked to survey quarter Price Attitudes Attitudes

  10. How: Modelling Approach 2005 prices Selection: Metered only Combined water & sewerage Seasonal models

  11. What: Summary Results Linear regression (OLS), Wald Table, n = 11,192, final r sq = 27% Climate/Weather Practices Traces of Practices?

  12. What: Practice 'effects' Traces of Practices?

  13. What: Weather 'interaction effects'

  14. So... The 'proxies for practices' approach has value But Garden/soils etc Period of water use? Expenditures as proxies? High spend != high volume Recall/response 'error'? Zeros! What to do? 72% reported no spend on soaps, shower gels etc in 2010!

  15. Approaches to 'validation' Link 'real' data Model response data Aggregate and compare with other sources

  16. Linking 'water' Practice based survey of water 'habits' 1800 respondents across South & East England Linked metering data for survey respondents For those who agreed to linkage And whose water company also agreed (!) 10% didn't know Of whom 4 are metered who said they weren't! To date we only have 64 records To date we only have 32 records

  17. Linking 'water': What we hope for...

  18. Linking 'water': What we get... To be refreshed when more data arrives 21 metered respondents who agreed to data linkage AND estimated monthly water bill

  19. Aggregating 'electricity' Ia • Survey: • LCF 2010 • DECC • Sub-regional electricity statistics (aggregated LSOAs)

  20. Aggregating 'electricity' Ib

  21. Aggregating 'electricity' IIa Ideally Geo-referenced clusters of LCF households Compare to DECC LSOA data

  22. Aggregating 'electricity' IIa Ideally Geo-referenced clusters of LCF households Compare to DECC LSOA data So: Small Area Estimation East of England LSOA level electricity demand estimates Census 2001 & LCF 2010 Compare to DECC LSOA data 'Spatial Microsimulation' New data please!

  23. Aggregating 'electricity' IIb • LSOAs • East of England Forest Heath 002A/B c. 73% = Born in the USA!

  24. Aggregating 'electricity' IIc

  25. Aggregating 'electricity' IId Spearman rho: Town: 0.6403 Urban: 0.5915 Village: 0.7948

  26. So what? We can map: Energy 'poverty' Energy 'inequality' And we can model Potential policy effects

  27. So what? We can map: Energy 'poverty' Energy 'inequality' And we can model Potential policy effects But also The electricity expenditures may be robust

  28. Conclusions Thinking about expenditures as proxies for practices Has some value BUT there are problems Zeros? Mis-reporting? Where next?

  29. Conclusions Thinking about expenditures as proxies for practices Has some value BUT there are problems Zeros? Mis-reporting? Where next? Data linkage? Micro and area level calibration?

  30. Thank you Dr Ben Anderson benander@essex.ac.uk Sustainable Practices Research Group www.sprg.ac.uk Spatial microsimulation: cresi.essex.ac.uk/getPubsByTag?tag=spatial%20microsimulation

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