Use of residential wood heating in a context of climate change: a population survey in Québec (Canada)

1471-2458-8-184 1471-2458 Research article Use of residential wood heating in a context of climate change: a population survey in Québec (Canada) Bélanger Diane diane.belanger@crchul.ulaval.ca Gosselin Pierre pierre-l.gosselin@crchul.ulaval.ca Valois Pierre pierre.valois@fse.ulaval.ca Abdous Belkacem belkacem.abdous@crchul.ulaval.ca

Institut national de santé publique du Québec and Centre de recherche du CHUQ, 945 Avenue Wolfe, Québec (Québec), G1V 5B3, Canada

Institut national de santé publique du Québec, Ouranos and Université Laval, 945 Avenue Wolfe, Québec (Québec), G1V 5B3, Canada

Faculté des Sciences de l'éducation, Université Laval, Québec (Québec), G1K 7P4, Canada

Centre de recherche du CHUQ, 2875 boulevard Laurier, Édifice Delta 2, Québec (Québec), G1V 2M2, Canada

BMC Public Health 1471-2458 2008 8 1 184 http://www.biomedcentral.com/1471-2458/8/184 18507833 10.1186/1471-2458-8-184 04 1 2008 28 5 2008 28 5 2008 2008 Bélanger et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background

Wood heating is recommended in several countries as a climate change (CC) adaptation measure, mainly to increase the autonomy of households during power outages due to extreme climatic events. The aim of this study was to examine various perceptions and individual characteristics associated with wood heating through a survey about CC adaptations.

Methods

A telephone survey (n = 2,545) of adults living in the southern part of the province of Québec (Canada) was conducted in the early fall season of 2005. The questionnaire used closed questions and measured the respondents' beliefs and current adaptations about CC. Calibration weighting was used to adjust the data analysis for the respondent's age and language under stratified sampling based on health regions.

Results

More than three out of four respondents had access to a single source of energy at home, which was mainly electricity; 22.2% combined two sources or more; 18.5% heated with wood occasionally or daily during the winter. The prevalence of wood heating was higher in the peripheral regions than in the more urban regions, where there was a higher proportion of respondents living in apartments. The prevalence was also higher with participants completely disagreeing (38.5%) with the eventual prohibition of wood heating when there is smog in winter, compared to respondents somewhat disagreeing (24.2%) or agreeing (somewhat: 17.5%; completely: 10.4%) with the adoption of this strategy. It appears that the perception of living in a region susceptible to winter smog, smog warnings in the media, or the belief in the human contribution to CC, did not influence significantly wood heating practices.

Conclusion

Increased residential wood heating could very well become a maladaptation to climate change, given its known consequences on winter smog and respiratory health. It would thus be appropriate to implement a long-term national program on improved and controlled residential wood heating. This would constitute a "no-regrets" adaptation to climate change, while reducing air pollution and its associated health impacts.

Background

In Canada, minimum and maximum temperatures have increased over the last few decades, particularly in winter 1. For instance, in southern Québec (south of the 49th parallel) average temperatures have increased by 0.5°C to 1.2°C based on an east-west trajectory 2. These increases however, do not mean that climate warming is linear 3. In fact, periods of intense cooling and severe storms are still predicted to occur. People will have to adapt appropriately, if only to prevent the health impacts of concern due to the cold 45.

A winter adaptation strategy is the use of residential wood heating. In Canada, more than 3 million dwellings use it as the primary or secondary source of heat 6. Furthermore, the popularity of this type of heating grew in Québec to the point that its penetration rate increased by approximately 60% between 1987 and 2000 while the number of dwellings increased by less than 20% 7. The massive and prolonged power outages that occurred in the middle of winter during the ice storm of 1998 8 are thought to have played a significant role in this increase. In fact, the Web site of the Department of Natural Resources of Canada highlights this extreme climatic event in referring to evolved wood burning techniques as a means of coping with the worst winter storms 9.

Residential wood heating is also one of the main causes of winter smog in Canada. This type of heating is in fact responsible for 29% of Canadian emissions of fine particulates – one of the two key components of smog and its main winter component 10 from anthropogenic sources 11. This relative contribution of fine particulates to emissions is even higher in Quebec at 47% 12 compared to most jurisdictions using fossil fuels for power generation, because hydroelectricity accounts for 96% of electricity production in the province and a great many homes use electric heat as the main source of heating.

Moreover, among the approximately one hundred atmospheric pollutants in wood smoke, several are greenhouse gases, while others are precursors of tropospheric ozone – the other key component of smog 13. Furthermore, human exposure to fine particulates and tropospheric ozone is of particular concern because there are still no established concentration thresholds below which these pollutants are known to be safe and not pose a human health risk 13. Young children, the elderly and people with respiratory problems (e.g., asthmatics) or heart problems are the most vulnerable, while healthy people who are repeatedly exposed, such as users of combustion units and their neighbours may also be at risk 71415. Finally, a well-known relationship exists between the harmful effects of these atmospheric pollutants and the increase in the number of visits to emergency rooms, hospitalizations, health care costs, absenteeism, the reduction in the labour force participation rate, as well as premature death 16.

Clearly, the rise in popularity of residential wood heating is a public health concern 16. And it will continue to grow should the supply and demand for this type of heating increase as extreme climatic events become more frequent and intense 1. The aim of this study was to examine diverse perceptions and characteristics associated with wood heating through a survey carried out in 2005 in southern Québec, Canada 17 in the context of a research program aiming to propose climate change (CC) adaptation strategies that respect the environment as well as health and well-being.

Methods

Population studied and sample

The population studied consisted of adults aged 18 years or older, resident of the Province of Québec south of the 49th parallel, namely all the health regions presented in Figure 1, except for regions 10, 17 and 18.

Figure 1

Health regions of Québec (Canada)

Health regions of Québec (Canada). 1 : Bas-Saint-Laurent ; 2 : Saguenay-Lac-Saint-Jean ; 3 : Québec ; 4 : Mauricie-Centre-du-Québec; 5 : Estrie; 6 : Montréal; 7 : Outaouais; 8 : Abitibi-Témiscamingue; 9 : Côte-Nord; 11 : Gaspésie-Îles-de-la-Madeleine; 12 : Chaudière-Appalaches; 13 : Laval; 14 : Lanaudière; 15 : Laurentides; 16 : Montérégie. Source: MSSS, Service des Infocentres, 2006.

The sample was stratified by the health region of residence, and post-stratified by gender (in order to take into account the greater difficulty in reaching men 18) (Table 1). Due to operational and budgetary constraints, we used random household sampling rather than within-household sampling. The respondents were contacted by a polling firm from random digit dialing of published residential telephone numbers. Confidential numbers were not used for ethical considerations. The study obtained ethical approval from Laval University's Comité d'éthique de la recherche avec des êtres humains. The consent was implicit as only adults whose phone number was published were interviewed; Laval University's ethics committee does not request any formal consent for such phone surveys.

Table 1

Stratification process by data collection

Name of the health regions of residence (number of the region)

Men ≥ 18 years¹

Proportion

Men: n²

Women ≥ 18 years¹

proportion

Women: n²

Men and women: n

Bas-Saint-Laurent (01)

77 455

0,014

82 070

0,015

Saguenay-Lac-Saint-Jean (02)

106 700

0,019

110 230

0,020

Capitale-Nationale (03)

246 320

0,044

112

271 710

0,048

122

234

Mauricie et Centre-du-Québec (04)

181 185

0,032

193 805

0,034

167

Estrie (05)

107 805

0,019

114 940

0,020

Montréal (06)

690 890

0,122

310

775 560

0,137

348

658

Outaouais (07)

116 260

0,021

124 345

0,022

109

Abitibi-Témiscaminque (08)

54 720

0,010

55 435

0,010

Côte-Nord (09)

37 710

0,007

36 900

0,007

Gaspésie-Îles-de-la-Madeleine (11)

37 635

0,007

39 550

0,007

Chaudière-Appalaches (12)

146 365

0,026

151 090

0,027

135

Laval (13)

127 755

0,023

138 870

0,025

122

Lanaudière (14)

144 030

0,026

148 550

0,026

132

Laurentides (15)

171 535

0,030

178 430

0,032

157

Montérégie (16)

474 705

0,084

213

505 235

0,090

229

442

TOTAL

2, 721, 070

1228

2, 926, 720

1322

2550

¹Institut de la statistique du Québec (20).

²Thompson (21).

The sample was calculated using 2001 survey data 19, for a 95% confidence level and a precision level of 1.5%, for a 4-point Likert-type scale including 6 items 20. The total sample was 5,088 respondents: half of them were contacted in the spring of 2005 (n = 2,543) on heat-related adaptation measures 21, and the other half during the following autumn (n = 2,545) on cold-related adaptation measures 17. The present article pertains to the autumn data collection, in which 70.2% of the eligible people (n = 3,726) completed the questionnaire; 4.9% were not interviewed because data collection ended before the date of the appointment made with the polling firm; 6.6% could not be reached (e.g., answering machine); less than one percent (n = 7) did not complete the interview; and 18.2% refused to answer the study. The percentage of respondents and non-respondents were similar across health regions (p = 0.4).

Data collection method

The polling firm collected individual responses by telephone (average duration: 20 minutes), seven days a week, from 9:30 a.m. to 9:30 p.m., using a computer system that allowed the order of the questions (essentially closed) to be randomly redistributed. More precisely, collection (from 15-09-2005 to 25-10-2005) allowed information to be gathered on behaviours adopted during a period of intense cold, socio-demographic characteristics, health status, dwelling, region of residence, the use of an automobile and a remote starter during the winter, consultation of weather reports, as well as on various perceptions and beliefs relating to climate change.

The questionnaire was developed according to the following six steps: 1/identifying the important issues to consider in the exploratory interviews 22 based on the literature on health and climate change; 2/conducting 21 face-to-face interviews (average duration: two hours), mainly to verify the understanding of some terms, identify the items to be retained as well as the sensitive issues to be excluded; 3/development of an initial version of the questionnaire; 4/conducting telephone interviews with 61 people aged 18 years or older (on average, four people per health region studied) to validate the clarity and precision of the questions, to comment on the questionnaire and to shorten it; 5/validation of the content of the questionnaire (French and English versions) by five experts working in the field of health and climate change in Canada; 6/conducting a qualitative pretest (n = 50) (two versions of the questionnaire) by the polling firm, at the start of each data collection.

Analyses

The collected information was calibration weighted for the respondents' age and language, on the basis of 2001 census data 19. Coefficients of variation (CV) were calculated (CV ≤ 15%: sufficiently precise estimates; CV between 15% and 25%: acceptable precision, estimates to be carefully interpreted; CV > 25%: low precision, estimates to be interpreted with circumspection) 23. The percentage totals for a given variable may not be exactly 100%, due to rounding to the closest decimal (To simplify the presentation, percentages below 2% for missing data have not been reported). The analyses took into account the sample scheme stratified according to the health regions 2425. Wood heating was related to the independent variables using the Rao-Scott likelihood ratio chi-square test, which is a design-adjusted version of the Pearson chi-square test. The multivariate analyses were done using a logistic regression model with a stepwise method. The significance level required to be retained by the model: 0.2; to stay in the model: 0.1). The c index (area under the ROC curve; expected value = 0.5 to 1.0) 26 was used as an indicator of the discriminant capacity of the final multivariate statistical model. Finally, the presence of collinearity between the independent variables was checked (VIF > 10; condition > 30) 27.

Results

Characteristics of the respondents

Women, as well as people 35 to 64 years of age accounted for slightly more than half of the sample (Table 2). At least two participants out of three lived in a house and spoke only French (Table 2), except in Montréal and Laval (Table 3).

Table 2

Sociodemographic characteristics of the respondents: percentages corrected for stratified sampling and coefficients of variation

Variables

%¹

CV²

Gender

Women

51.6

0.02

Men

48.3

0.02

Age

18 to 34 years

29.1

0.03

35 to 64 years

54.6

0.02

65 years or more

16.2

0.05

First language learned at home

French only

81.0

0.01

English only

6.1

0.09

Language other than French or English

10.1

0.15

English or French plus another language

2.9

0.08

Status of activities (last 12 months)

Employed

67.0

0.02

Unemployed

8.4

0.07

Student

3.4

0.15

Retired

21.8

0.04

Income (before tax/from all sources/last 12 months)

Less than $ 15 000

9.3

0.07

Between $ 15 000 and $ 29 999

17.2

0.05

Between $ 30 000 and $ 44 999

17.8

0.05

Between $ 45 000 and $ 59 999

14.1

0.05

$ 60 000 or more

26.2

0.03

Undisclosed³

15.2

0.05

Lives alone

Yes

18.2

0.04

81.8

0.01

Region of residence

Eastern Québec

5.7

0.02

Northern part of southern Québec

5.9

0.02

Québec City region

14.6

0.01

Centre of the province

6.4

0.02

South of Montréal

21.1

0.01

North of Montréal

15.7

0.01

Montréal and Laval

30.8

0.01

Type of dwelling

House

64.9

0.01

Apartment: ≤ 4 storeys

31.1

0.03

Apartment > 4 storeys

3.9

0.11

¹%: percentages. The total percentages for a given variable may not be exactly 100%, due to rounding to the closest decimal. To simplify the presentation, percentages below 2% for missing data have not been reported.

²CV, coefficients of variation. CV ≤ 15%: sufficiently precise estimates; CV between 15% and 25%: acceptable precision, estimates to be carefully interpreted; CV > 25%: low precision, estimates to be interpreted with circumspection [25].

³These participants, compared to those who disclosed their income strata, were more often women, individuals at least 65 years of age, and retired people.

Table 3

Some characteristics of the respondents by region of residence: percentages corrected for stratified sampling

Region of residence

Variables

Eastern Québec

Northern part of southern Québec

Centre of the province

Québec City region

South of Montréal

North of Montréal

Montréal and Laval

Type of dwelling:

• House

87.4%¹

78.8%

76.0%

67.2%

73.8%

85.0%

38.4%

• Apartment

12.6%

21.2%

24.0%

32.9%

26.3%

15.0%

61.6%

First language learned at home:

• French only

96.0%

95.0%

96.2%

93.4%

86.1%

85.3%

60.8%

• other than French only

4.0%

5.0%

3.8%

6.6%

13.9%

14.7%

39.2%

Region of residence perceived as conducive to cold waves:

• a lot

27.0%

41.5%

23.3%

31.9%

34.6%

33.9%

41.1%

• Average

44.6%

39.9%

55.1%

49.6%

46.9%

46.8%

40.8%

• not much

19.3%

17.1%

16.0%

15.4%

15.0%

14.1%

• not at all

9.2%

1.6%

5.6%

2.5%

3.2%

4.3%

4.0%

Region of residence perceived as conducive to winter smog:

• a lot

5.4%

0.6%

1.2%

3.3%

6.6%

4.4%

15.4%

• Average

12.4%

8.8%

19.2%

17.2%

22.5%

20.3%

31.5%

• not much

21.9%

21.4%

28.7%

33.5%

29.1%

29.4%

29.6%

• not at all

60.3%

69.3%

50.9%

46.1%

41.8%

45.9%

23.5%

Wood heating:

• Yes

35.0%

34.8%

30.7%

23.0%

21.9%

24.9%

4.0%

• No

65.0%

65.2%

69.3%

77.0%

78.1%

75.2%

96.0%

Prohibition of wood heating when there is winter smog:

• completely agree

26.2%

33.8%

29.8%

27.5%

36.1%

37.3%

48.5%

• do not completely agree

73.8%

66.2%

70.2%

72.5%

63.9%

62.7%

51.5%

Belief of the contribution of anthropogenic causes to climate change in the last fifty years:

• average or a lot

79.3%

76.9%

82.8%

78.0%

85.2%

85.0%

84.1%

• not much or not at all

20.7%

23.1%

17.2%

22.0%

14.8%

15.0%

15.9%

¹The total percentages for a given variable may not be exactly 100%, due to rounding to the closest decimal.

To simplify the presentation, percentages below 2% for missing data have not been reported.

More than three out of four respondents had access to a single source of energy at home, as follows: 60.8%, electricity; 8.0%, oil; 3.8%, natural gas or propane; 3.7%, firewood. The other participants (22.2%) combined some of these sources (e.g., oil, gas, wood), with three out of five (59.5%) combining electricity and wood.

Factors associated with residential wood heating

During the winter, 18.5% of the respondents heated with wood occasionally or daily and more precisely: 1.7%, less than once a week; 4.5%, a few days a week but not every day; and 11.9%, every day.

Respondents with higher incomes used wood as a primary or secondary source of energy in a higher proportion than the other participants, as well as the respondents aged between 35 to 64 years, who spoke French only or in addition to another language, or who lived with children or with other people (Table 4).

Table 4

Use of residential wood heating in southern Québec for various respondents characteristics: percentages corrected for stratified sampling and p value

Wood heating

p value¹

Variables

yes

Sociodemographic characteristics

• Gender:

0.1885

• men

20.3%²

79,7%

• women

18.2%

81.8%

Age:

0.0004

• 18–34 years

16.2%

83.8%

• 35–64 years

22.4%

77.6%

• 65 years or more

14.5%

85.5%

Status of activities (last 12 months):

0.0374

• employed

20.3%

79.7%

• unemployed

21.8%

78.2%

• student

11.6%

88.4%

• retired

15.7%

84.3%

Income before tax, from all sources (last 12 months):

< 0.0001

• < $45,000

16.8%

83.2%

• ≥ $45,000

23.6%

76.4%

• not disclosed

14.4%

85.6%

First language learned at home:

< 0.0001

• French only

21.9%

78.2%

• English only

4.9%

95.1%

• other language in addition to French or English

20.6%

79.4%

• language other than French and English

6.1%

93.9%

Status as parent:

< 0.0001

• no children

14.7%

85.3%

• adult children only

20.0%

80.0%

• at least one minor child

23.2%

76.8%

Cohabitation:

< 0.0001

• lives with other people (related or not)

21.0%

79.0%

• lives alone

11.9%

88.1%

Health status

Perceived health status:

0.1624

• very good

20.1%

79.9%

• good

19.8%

80.2%

• average

15.6%

84.4%

• bad

12.8%

87.2%

Having at least one chronic disease diagnosed by a physician and having had it for at least six months

0.0809

• yes

16.9%

83.1%

• no

20.0%

80.0%

Observance of behaviours according to the preventive advice issued by health professionals

0.5748

• always

19.3%

80.7%

• often

18.3%

81.7%

• sometimes

21.8%

78.2%

• rarely

17.6%

82.4%

• never

19.4%

80.6%

Perceived influence of extreme meteorological conditions (e.g., heat waves) on health:

0.0179

• a lot

15.2%

84.8%

• average

15.4%

84.6%

• not much

18.0%

82.0%

• not at all

21.2%

78.8%

Dwelling

Type of dwelling:

< 0.0001

• house

28.1%

71.9%

• apartment

2.6%

97.4%

Perceived efficiency of the dwelling's insulation against moisture:

< 0.0001

• very good

25.2%

74.8%

• good

18.9%

81.1%

• average

15.6%

84.5%

• poor

7.3%

92.7%

Perceived efficiency of the dwelling's insulation against cold:

< 0.0001

• very good

24.5%

75.6%

• good

20.4%

79.6%

• average

12.8%

87.2%

• poor

6.3%

93.8%

Perceived efficiency of the dwelling's insulation against heat:

< 0.0001

• very good

27.1%

72.9%

• good

19.9%

80.2%

average

13.6%

86.4%

• poor

3.7%

96.3%

Addition of insulating materials since the dwelling was built:

< 0.0001

• yes

26.6%

73.4%

• no

18.1%

81.9%

• don't know

6.4%

93.6%

Replacement of doors or windows since the dwelling was built:

0.3479

• yes

20.5%

79.5%

• no

18.9%

81.1%

Dwelling built before 1983³:

0.1684

• yes

18.7%

81.3%

• no

21.5%

78.5%

• unknown⁴

17.4%

82.6%

Region of residence

Region lived in:

< 0.0001

• Eastern Québec

35.0%

65.0%

• Northern part of southern Québec

34.8%

65.2%

• Central Québec

30.7%

69.3%

• Québec City region

23.0%

77.0%

• North of Montréal

24.9%

75.2%

• South of Montréal

21.9%

78.1%

• Montréal and Laval

4.0%

96.0%

Region of residence perceived as conducive to ice storms

0.0828

• a lot

15.2%

84.8%

• average

19.6%

80.4%

• not much

20.1%

79.9%

• not at all

22.8%

77.2%

Region of residence perceived as conducive to winter smog

0.0002

• a lot

11.6%

88.4%

• average

15.8%

84.2%

• not much

20.2%

79.8%

• not at all

23.3%

76.7%

Region of residence perceived as conducive to cold waves

0.0003

• a lot

14.0%

86.0%

• average

21.8%

78.2%

• not much

24.3%

75.7%

• not at all

23.6%

76.4%

Transport

Frequency of use of an automobile:

< 0.0001

• daily

21.9%

78.1%

• occasionally

21.5%

78.5%

• never

6.8%

93.2%

Use of a remote starter in winter

0.2007

• yes

23.4%

76.6%

• no

20.8%

66.1%

Consultation of meteorological information in the media

• Temperature:

0.2666

• always

20.2%

79.8%

• often

19.2%

80.8%

• sometimes

19.5%

80.5%

• rarely

17.7%

82.3%

• never

12.5%

87.5%

Smog warning:

0.1205

• always

17.3%

82.7%

• often

16.4%

83.6%

• sometimes

19.2%