workshop: can climate change policies be fair?royal statistical society, july 5th 2012 practices by...

Workshop: Can climate change policies be fair?Royal Statistical Society, July 5th 2012

Practices by ProxyClimate, Consumption and Water

(and troubles with data...)

Dr Ben AndersonUniversity of Essex


Contents Why?

Water 'practices' How?

Proxies What?

Models Problems?

Data Where next?


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


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


What do we want to know? Practices in which water is implicated

Diversityhabituation, routine,

practical consciousness,tacit knowledge,

traditionPerformance often

neither fully conscious

nor reflectiveAlan Warde, 2005

Why people don’t do what they ‘should’ -

Jim Skea, 2011


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 litresImage: Eric Shipton, 1951


Conceptual Framework

Water demand = f(price + demographics + practices + attitudes) + error

Policy levers & Interventions

habituation, routine, neither conscious nor reflective

RegulationMarket Supply ?? ??

EducationInformationPersuasion


Conceptual Framework

Water demand = f(price + demographics + practices + attitudes) + error

Policy levers & Interventions

habituation, routine, neither conscious nor reflective

RegulationMarket Supply ?? ??

EducationInformationPersuasion

Climate change


How: Expenditures as Proxies Ideal Proxy (LCF 2002-2010)

water (l/day)

Attitudes

Demographics

Price

Practices

£ water/week

AttitudesAttitudes

Demographics

PricePrice

£/week

Shampoo,soapdetergents

Garden products

Fruit & Veg

Tea, coffee, juices

RegionalClimate/Weather

linked to survey quarter


How: Modelling Approach 2005 prices Selection:

Metered only Combined water & sewerage

Seasonal models

All households

39121

Metered 11119

Separate water & sewerage

-1387

Remaining 9732

Winter (Dec – Feb) Spring (Mar – May) Summer (Jun – Aug) Autumn (Sep – Nov)02468

101214161820

£4.70£4.72£4.74£4.76£4.78£4.80£4.82£4.84£4.86£4.88£4.90

Water £/week Mean rainfall (cm)

Mean number raindays Mean sunshine hours (/10)

Mean temperature


What: Summary Results

Region, year, income

Accommodation, number of rooms, tenure

N cars, n earners, HRP employment, composition

Age distributions, number of persons

Long-term illness, age of HRP, gender of HRP, ethnicity of HRP

Washing machine/dishwasher

Practices

Weather (contemporary interaction)

Weather (3 year anomly interaction)

0% 5% 10% 15% 20% 25% 30%

change in rsq r sq

Climate/Weather

Practices

Traces of Practices?

Linear regression (OLS), Wald Table, n = 11,192, final r sq = 27%


What: Practice 'effects'

Washing machine

Dishwasher

Potatoes

Leaf & stem vegetables

Rice

Pasta

Tea

Coffee

Fruit juices (incl squash)

Vegetable juices

Mineral/spring water

Soap/shower gel

Laundry/Laundrettes

Detergents/washing powder

Kitchen gloves/cloths

Garden tools

Lawn mowers

Plants, flowers, seeds

-0.5 -0.3 -0.1 0.1 0.3 0.5 0.7

b (coefficient)

Traces of Practices

?


What: Weather 'interaction effects'Proxy Spring Summer

Main effect

Interaction Main effect Interaction

Leaf & stem vegetables 0.069 0.905 (unusually hot)

Detergents/washing powder

0.066 -0.087 (number of rain days)

plants, flowers, seeds, fertilisers, insecticides

N/s 0.018 (temperature)


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!


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


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 (!)

Metered: 769 42%

Agreed to linkage: 282 15%

Agreed to linkage and metered

132 7%

10% didn't know

To date we only have 64 records

To date we only have 32 records

Of whom 4 are metered who said they weren't!


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


Linking 'water': What we get...

21 metered respondents who agreed to data linkage AND estimated monthly water bill

To be refreshed when more data arrives


Aggregating 'electricity' Ia Survey:

LCF 2010 DECC

Sub-regional electricity statistics (aggregated LSOAs)

East Midlands

Eastern

Greater London

North East

South East

South West

Wales

West Midlands

Yorkshire and the Humber

Total

0 2 4 6 8 10 12 14 16 18

Mean £ per week (LCF, 2010)Mean £ per week (DECC 2010, assume 12p per kwh)


Aggregating 'electricity' Ib

East Midlands

Eastern

Greater London

North East

South East

South West

Wales

West Midlands

Yorkshire and the Humber

Total

0 2 4 6 8 10 12 14 16 18

Mean £ per week (EFS, 2010)Mean £ per week (DECC 2010, assume 12p per kwh)

7.5 8 8.5 9 9.5 100

2

4

6

8

10

12

14

16

18

R² = 0.3642018973

Mean £ per week (LCF, 2010)

Me

an

£ p

er w

ee

k (D

EC

C,

20

10

, as

sum

es

12

p p

er

kwh

)


Aggregating 'electricity' IIa Ideally

Geo-referenced clusters of LCF households Compare to DECC LSOA data


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 dataNew data please!

'Spatial Microsimulation'


Aggregating 'electricity' IIb

Forest Heath 002A/Bc. 73% = Born in the USA!

LSOAs East of England


Aggregating 'electricity' IIc


Aggregating 'electricity' IId

Spearman rho: Town: 0.6403 Urban: 0.5915 Village: 0.7948


So what? We can map:

Energy 'poverty' Energy 'inequality'

And we can model Potential policy

effects


So what? We can map:

Energy 'poverty' Energy 'inequality'

And we can model Potential policy

effects But also

The electricity expenditures may be robust


Conclusions Thinking about expenditures as proxies for practices

Has some value BUT there are problems

Zeros? Mis-reporting?

Where next?


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?


Thank you Dr Ben Anderson

[email protected]

Sustainable Practices Research Group www.sprg.ac.uk

Spatial microsimulation: cresi.essex.ac.uk/getPubsByTag?tag=spatial%20microsimulation

workshop: can climate change policies be fair?royal statistical society, july 5th 2012 practices by...

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