"Modes of commuting, workplace choice and energy use at home" Paper presented at "What Makes Us Act Green?", June 25 2014, London

1. Modes of commuting, workplace
choice and energy use at home
Dr Ben Anderson
25th June 2014 @dataknut

2. @dataknut: The Distribution of Domestic Energy-Tech in Great Britain: 2008 - 2011
Contents
§ Interlinked ‘choices’ and constraints
§ Commuting ‘choices’
§ Working from/at home
§ A potential problem
§ Concluding thoughts
2

3. @dataknut: The Distribution of Domestic Energy-Tech in Great Britain: 2008 - 2011
Contents
§ Interlinked ‘choices’ and constraints
§ Commuting ‘choices’
§ Working from/at home
§ A potential problem
§ Concluding thoughts
3

4. @dataknut: The Distribution of Domestic Energy-Tech in Great Britain: 2008 - 2011
What?
§ We use energy everywhere
4
Industry
293
Road
transport
459
Air
transport
144
Other
transport
16
Housing
502
Commercial
and public
administra-
tion 197
Non energy
use
88
Other
25
represents a major opportunity to cut energy use and CO2 emissions.
Much of the UK’s housing was built before the links between energy use and
climate change were understood. Much of it was also built when there were
very different expectations of thermal comfort.
To put it simply, most families in 1970 lived in homes that would be cold by
modern standards in winter – as cool as 12°C on average (see Table 6o,
Appendix 1). There may have been ice on the insides of the windows, and
nearly everyone accepted the need to wear thick clothes at home in winter.
Few homes had central heating, and many families used coal for heating.
Added to this, few families owned the household appliances everyone takes
for granted today.
The way energy is used in homes today is very different. Most
homes have central heating, usually fuelled by natural gas,
and most households have fridges, freezers and washing
machines. Many households also own dishwashers, tumble
dryers, PCs and games consoles.
The Housing Energy Fact File aims to draw together most of
the important data about energy use in homes in the UK since
1970. As well as describing the current situation, it also shows
changes over the last 40 years. It is intended for policy-
makers, researchers, and interested members of the public.
(More detailed information about homes in England is
available on DECC’s website, in the Cambridge Housing Energy
Tool, see http://tinyurl.com/HousingFactFile.)
The Fact File is one in a series of reports stretching back to the
early 1970s, previously prepared for the Government by the
Building Research Establishment.
This report is a collaborative endeavour, prepared by Cambridge
Architectural Research and Eclipse Research Consultants, with input from
Loughborough University and UCL.
A significant change in this year’s Fact File is a new chapter on Household
Behaviour, from page 63. This examines how energy use in the home is
The UK’s homes, and how they
are used, has changed
enormously since 1970.
Graph 1a: Final energy consumption by
sector 2012 (UK, TWh, Total 1,724 TWh)
Industry
293
Road
transport
459
Air
transport
144
Other
transport
16
Housing
502
Commercial
and public
administra-
tion 197
Non energy
use
88
Other
25
represents a major opportunity to cut energy use and CO2 emissions.
Much of the UK’s housing was built before the links between energy use
climate change were understood. Much of it was also built when there w
very different expectations of thermal comfort.
To put it simply, most families in 1970 lived in homes that would be cold
modern standards in winter – as cool as 12°C on average (see Table 6o,
Appendix 1). There may have been ice on the insides of the windows, and
nearly everyone accepted the need to wear thick clothes at home in wint
Few homes had central heating, and many families used coal for heating.
Added to this, few families owned the household appliances everyone ta
for granted today.
The way energy is used in homes today is very different. M
homes have central heating, usually fuelled by natural gas,
and most households have fridges, freezers and washing
machines. Many households also own dishwashers, tumble
dryers, PCs and games consoles.
The Housing Energy Fact File aims to draw together most o
the important data about energy use in homes in the UK si
1970. As well as describing the current situation, it also sho
changes over the last 40 years. It is intended for policy-
makers, researchers, and interested members of the public
(More detailed information about homes in England is
available on DECC’s website, in the Cambridge Housing Ene
Tool, see http://tinyurl.com/HousingFactFile.)
The Fact File is one in a series of reports stretching back to
early 1970s, previously prepared for the Government by th
Building Research Establishment.
This report is a collaborative endeavour, prepared by Cambridge
Architectural Research and Eclipse Research Consultants, with input from
Loughborough University and UCL.
A significant change in this year’s Fact File is a new chapter on Household
Behaviour, from page 63. This examines how energy use in the home is
The UK’s homes, and how they
are used, has changed
enormously since 1970.
Graph 1a: Final energy consumption by
sector 2012 (UK, TWh, Total 1,724 TWh)
DECC, 2013 (UK Housing Factfile)
Presumably
working from
home fits
here
But travelling
to work fits
here
And here
And being ‘at
work’ fits
here
And here
§ Our practices
cut across
sectors

5. @dataknut: The Distribution of Domestic Energy-Tech in Great Britain: 2008 - 2011
What we want to know…
§ Are ‘eco’ attitudes & behaviours
– Correlated with ‘green’ commuting
‘choices’?
– Correlated with working from home?
§ Does working from home
– Increase energy consumption?
5

6. @dataknut: The Distribution of Domestic Energy-Tech in Great Britain: 2008 - 2011
Contents
§ Interlinked ‘choices’ and constraints
§ Commuting ‘choices’
§ Working from/at home
§ A potential problem
§ Concluding thoughts
6

7. @dataknut: The Distribution of Domestic Energy-Tech in Great Britain: 2008 - 2011
Patterns of commuting over time
§ Commuting ‘choices’: prevalence
7
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
2009
2010
2011
2012
Car,
van,
motorcyle
etc
Gets
a
li=
or
taxi
Public
transport
Walk,
cycle,
other
Source: Own calculations of USOC (W1-3) weighted for non response and correcting for survey design
Error bars = 95% Confidence intervals
• 75% of those who walked/cycled
at one wave were still doing so
at the next
• 14% had switched to car
• 3% of those who used a car had
switched to walking
• 1.6% had switched to public
transport

8. @dataknut: The Distribution of Domestic Energy-Tech in Great Britain: 2008 - 2011
Patterns of commuting over time
§ Commuting ‘choices’: distance from work
8
Source: Own calculations of USOC (W1-3) weighted for non response and correcting for survey design
Error bars = 95% Confidence intervals
0.00
2.00
4.00
6.00
8.00
10.00
12.00
14.00
16.00
2009
2010
2011
2012
Mean
distance
to
workplace
Car,
van,
motorcyle
Gets
a
li=
or
taxi
Public
transport
Walk,
cycle,
other

9. @dataknut: The Distribution of Domestic Energy-Tech in Great Britain: 2008 - 2011
‘Eco-friendly’
Walk or cycle (‘active
commute’)
9
Source: Own calculations of USOC (W1-3) weighted for non response and correcting for survey design
Error bars = 95% Confidence intervals
Public transport
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
2009
2010
2011
2012
Enviro
Friendly
Q4
(highest)
Q3
Q2
Enviro
Friendly
Q1
(lowest)
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
2009
2010
2011
2012
Enviro
Friendly
Q4
(highest)
Q3
Q2
Enviro
Friendly
Q1
(lowest)

10. @dataknut: The Distribution of Domestic Energy-Tech in Great Britain: 2008 - 2011
Equivalised household income
Walk or cycle (‘active
commute’)
10
Source: Own calculations of USOC (W1-3) weighted for non response and correcting for survey design
Error bars = 95% Confidence intervals
Public transport
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
2009
2010
2011
2012
Equivalised
household
income
Q4
(highest)
Q3
Q2
Equivalised
household
income
Q1
(lowest)
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
2009
2010
2011
2012
Equivalised
household
income
Q4
(highest)
Q3
Q2
Equivalised
household
income
Q1
(lowest)

11. @dataknut: The Distribution of Domestic Energy-Tech in Great Britain: 2008 - 2011
Self/employment situation
Walk or cycle (‘active commute’)
11
Source: Own calculations of USOC (W1-3) weighted for non response and correcting for survey design
Error bars = 95% Confidence intervals
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
2009
2010
2011
2012
NS-­‐SEC1
NS-­‐SEC
2
NS-­‐SEC
3
NS-­‐SEC
4
NS-­‐SEC
5
NS-­‐SEC
1:
Managerial/Professional
NS-­‐SEC
2:
Intermediate
NS-­‐SEC
3:
Smaller
employers
&
own
account
NS-­‐SEC
4:
Lower
supervisory
&
technical
NS-­‐SEC
5:
Semi-­‐rouZne,
rouZne
&
never
worked/LT
unemployed

12. @dataknut: The Distribution of Domestic Energy-Tech in Great Britain: 2008 - 2011
Walk or cycle (‘active commute’)
12
Source: Cross-sectional logistic regression models using USOC (W1-3) weighted for non response and correcting for survey design
Wave 1 item on why prefer to use car omitted
Error bars = 95% Confidence intervals
-­‐0.6
-­‐0.4
-­‐0.2
0
0.2
0.4
0.6
0.8
Equivalised
Income
quarZle
2
(q1)
Equivalised
Income
q3
Equivalised
Income
q4
Social
rent
(Owned)
Other/private
rent
Walk
or
cycle
(occupaZon
included)
Walk
or
cycle
-­‐1
-­‐0.5
0
0.5
1
1.5
In
poor
health
Disabled
Environmentally
Friendly
quarZle
2
Environmentally
Friendly
q3
Environmentally
Friendly
q4
Self
employed
NS-­‐SEC:
Intermediate
(Managerial/
NS-­‐SEC:
Smaller
employers
&
own
NS-­‐SEC:
Lower
supervisory
&
NS-­‐SEC:
Semi-­‐rouZne,
rouZne
&
Distance
from
work
Degree
Walk
or
cycle
(occupaZon
included)
Walk
or
cycle

13. @dataknut: The Distribution of Domestic Energy-Tech in Great Britain: 2008 - 2011
0%
10%
20%
30%
40%
50%
60%
lack
of
or
no
cycle
lanes
weather
traffic,
congesZon,
or
roadwork
poor
info
about
public
transport
personal
disability
concerns
over
personal
safety
find
public
transport
unpleasant
combine
trip
with
other
journeys
other
reason
cost
of
public
transport/taxis
unreliable
public
transport
too
far
or
long
journey
vehicle
essenZal
for
job
poor
connecZons
not
possible
by
public
transport
%
rated
as
most
important
%
menZoning
Reasons for car/van use: constraints?
13
Source: USOC Wave 1 only weighted for non response and correcting for survey design
Error bars = 95% Confidence intervals

14. @dataknut: The Distribution of Domestic Energy-Tech in Great Britain: 2008 - 2011
Contents
§ Interlinked ‘choices’ and constraints
§ Commuting ‘choices’
§ Working from/at home
§ A potential problem
§ Concluding thoughts
14

15. @dataknut: The Distribution of Domestic Energy-Tech in Great Britain: 2008 - 2011
Stasis and churn…
§ Working from/at home
– Includes the self-employed
15
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
2009
2010
2011
2012
Mainly
at
or
from
home
Premises
Other
(travelling,
client's
locaZon
etc)
Source: Own calculations of USOC (W1-3) weighted for non response and correcting for survey design
Error bars = 95% Confidence intervals
• 70% of those who worked from
home at one wave were still
working from home at the next
• 20% were now ‘other’
• 1% of those at premises at one
wave were working from/at
home at the next
• 5% of ‘other’ were now mainly at
home

16. @dataknut: The Distribution of Domestic Energy-Tech in Great Britain: 2008 - 2011
Eco effects?
§ Working from/at home
– Includes the self-employed
16
Source: Own calculations of USOC (W1-3) weighted for non response and correcting for survey design
Error bars = 95% Confidence intervals
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
7.0%
8.0%
9.0%
10.0%
2009
2010
2011
2012
Enviro
Friendly
Q4
(highest)
Q3
Q2
§

17. @dataknut: The Distribution of Domestic Energy-Tech in Great Britain: 2008 - 2011
Income effects?
§ Working from/at home
– Includes the self-employed
17
Source: Own calculations of USOC (W1-3) weighted for non response and correcting for survey design
Error bars = 95% Confidence intervals
0.0%
2.0%
4.0%
6.0%
8.0%
10.0%
12.0%
14.0%
2009
2010
2011
2012
Equivalised
household
income
Q4
(highest)
Q3
Q2
Equivalised
household
income
Q1
(lowest)

18. @dataknut: The Distribution of Domestic Energy-Tech in Great Britain: 2008 - 2011
Work status effects?
§ Working from/at home
– Includes the self-employed
18
Source: Own calculations of USOC (W1-3) weighted for non response and correcting for survey design
Error bars = 95% Confidence intervals
-­‐10.0%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
2009
2010
2011
2012
NS-­‐SEC
5
NS-­‐SEC
4
NS-­‐SEC
3
NS-­‐SEC
2
NS-­‐SEC1
NS-­‐SEC
1:
Managerial/Professional
NS-­‐SEC
2:
Intermediate
NS-­‐SEC
3:
Smaller
employers
&
own
account
NS-­‐SEC
4:
Lower
supervisory
&
technical
NS-­‐SEC
5:
Semi-­‐rouZne,
rouZne
&
never
worked/LT
unemployed

19. @dataknut: The Distribution of Domestic Energy-Tech in Great Britain: 2008 - 2011
-­‐0.5
0
0.5
1
1.5
2
2.5
Environmentally
Friendly
quarZle
2
(Q1)
Environmentally
Friendly
q3
Environmentally
Friendly
q4
Self
employed
NS-­‐SEC:
Intermediate
(Managerial/
Professional)
NS-­‐SEC:
Smaller
employers
&
own
account
NS-­‐SEC:
Lower
supervisory
&
technical
NS-­‐SEC:
Semi-­‐rouZne,
rouZne
&
never
worked/LT
unemployed
Degree
Disabled
Who is most likely to work from home?
19
Model: Cross-sectional logit model using USOC (W1-3) weighted for non response and correcting for survey design
Error bars = 95% Confidence intervals
Adding detailed occupation removes
-­‐1.2
-­‐1
-­‐0.8
-­‐0.6
-­‐0.4
-­‐0.2
0
0.2
0.4
Equivalised
Income
quarZle
2
(q1)
Equivalised
Income
q3
Equivalised
Income
q4
Detached
House
SemiDetached
Terraced
Flat
Number
of
rooms

20. @dataknut: The Distribution of Domestic Energy-Tech in Great Britain: 2008 - 2011
Effect on energy consumption?
20
§ Understanding Society
– Waves 1-3
§ Longitudinal regression model
– Household energy costs wave 2 & wave 3
– Eco-attitudes/behaviours from wave 1
– Work location (at or mainly from home)
– Work situation (NS-SEC)
– Plus a wide range of household level controls
• Accommodation type, occupants, tenure, whether
moved

21. @dataknut: The Distribution of Domestic Energy-Tech in Great Britain: 2008 - 2011
-­‐20%
-­‐15%
-­‐10%
-­‐5%
0%
5%
10%
15%
Works
mainly
from
or
at
home
Environmentally
Friendly
quarZle
2
(Q1)
Environmentally
Friendly
q3
Environmentally
Friendly
q4
Self
employed
NS-­‐SEC:
Intermediate
(Managerial/Professional)
NS-­‐SEC:
Smaller
employers
&
own
account
NS-­‐SEC:
Lower
supervisory
&
technical
NS-­‐SEC:
Semi-­‐rouZne,
rouZne
&
never
worked/LT
unemployed
Urban
Overall
energy
cost
(ln),
n
=
35,449
Electricity
cost
(ln),
n
=
20,851
Gas
cost
(ln),
n
=
16793
Effect on energy consumption
21
Source: Own calculations of USOC (W1-3) weighted for non response and correcting for survey design
Error bars = 95% Confidence intervals

22. @dataknut: The Distribution of Domestic Energy-Tech in Great Britain: 2008 - 2011
Contents
§ Interlinked ‘choices’ and constraints
§ Commuting ‘choices’
§ Working from/at home
§ A potential problem
§ Concluding thoughts
22

23. @dataknut: The Distribution of Domestic Energy-Tech in Great Britain: 2008 - 2011
‘Average’ reported consumption
23Data: Mean monthly water bill expenditure
Source: Own calculations from ESRC SPRG 2011 ‘Patterns of water’ survey &linked billing data and Living Costs & Food Survey, 2010

24. @dataknut: The Distribution of Domestic Energy-Tech in Great Britain: 2008 - 2011
Microlevel consumption…
24Reported in a survey
Measured

25. @dataknut: The Distribution of Domestic Energy-Tech in Great Britain: 2008 - 2011
What I suspect we will see…
25Source: Own calculations from ESRC SPRG 2011 ‘Patterns of water’ survey and linked billing data,
colours denote different water companies
Reported in a survey
Measured

26. @dataknut: The Distribution of Domestic Energy-Tech in Great Britain: 2008 - 2011
Concluding thoughts
26
§ Commuting ‘choice’
– Key constraints: distance, occupation, vehicle needed for job, poor public transport
– But eco-friendliness plays a big role
§ Those who work from home tend to be
– Professionals & self-employed with larger homes, more eco-friendly, disabled but also
occupational dimensions
§ This appears to increase their domestic energy use by c. 6%
– But electricity/gas effects difficult to separate
§ BUT
– We need much more reliable consumption data
– We’d like to know if this is heat/light/kettle/computing/fridge/cooking etc
– We’d like to know when this demand occurs

27. @dataknut: The Distribution of Domestic Energy-Tech in Great Britain: 2008 - 2011
Thank you
§ Questions?
– b.anderson@soton.ac.uk
– @dataknut
§ http://www.energy.soton.ac.uk/esrc-sdai-attitudes
27