This paper analyzed neighborhood residents’ cognition of and participation in low-carbon behaviors, basing on a questionnaire survey launched in a neighborhood in Wuhan, China. Results indicate that most respondents concerned the low-carbon impact on their daily lives and expected the government to make differences in low-carbon transition. Neighborhood residents’ participation in low-carbon behaviors was mainly reflected in three aspects: home energy conservation (HEC), efficient resource consumption (ERC), and recycling habits (RH), which were extracted from the five categories out of the 15 observed variables. Many interviewees had high level of participation in low-carbon behaviors that affect their economic interests. But these neighborhood residents rarely participated in public low-carbon behaviors such as planting trees or cooperative low-carbon behaviors. Therefore, these neighborhood residents’ participation in low-carbon behaviors was still on the initial stage. Specific proposals were put forward to promote urban low-carbonization further.
People are responsible for adopting policies and measures of mitigation and adaptation on global warming within the framework of sustainable development. The proposed concept of low-carbon economy is a significant step forward in the global fight against climate change. Cities in China are upgrading into a critical growth period [
Human activities are largely responsible for global warming [
Urban dwellers’ cognition on low-carbon behaviors influences their specific participations. Many literatures expounded the low-carbon related cognition. A human being’s mind includes knowledge, attitude, consciousness, values, affective states, perceptual cognizance and ideas, reasonable thinking, and deep-rooted habits which would greatly affect or reshape individual behaviors [
The literature review shows that previous studies focus on residents’ cognition of and participation in low-carbon behaviors and the correlation between them. Few authors focused on the level of neighborhood residents’ participation in low-carbon behaviors or the main field for residents to perform low-carbon behaviors. To make up this omission, we investigated and discussed neighborhood residents’ cognition of and participation in low-carbon behaviors in this study. A neighborhood was selected for the test project in Wuhan, which devotes oneself to establish a resource-saving and environment-friendly society in low-carbon economy development. The sample data were analyzed in IBM SPSS Statistics 21.0 software. And the methods of statistical descriptive analysis, principal component analysis, and multiple linear regression analysis were used. Suggestions for guidance and correction of the approach for neighborhood residents’ participation in low-carbon behaviors were proposed further.
A questionnaire involving 24 questions was designed in a gradual manner to survey neighborhood residents’ cognition of and their self-reported level of participation in low-carbon behaviors. The questions 1–3 were used to collect respondents’ basic information including their age, education level, and profession. The questions 4–8 were used to obtain their cognition that covered the awareness of global warming, the low-carbon concept and meaning, the low-carbon impaction on their daily lives, energy-saving measures, and government supports.
Questions 9–24 were used to obtain the information of their self-reported level of participation in low-carbon behaviors. Specifically, Question 9 surveyed residents’ overall assessment of their own level of participation in low-carbon behaviors. Questions 10–24 collected statistical information of neighborhood residents’ concrete situation of participation in various low-carbon behaviors in the form of five Likert scale. All questions were straightforward.
The examination results of performance from neighborhood residents’ low-carbon behaviors were divided into five rating levels: always, frequently, occasionally, seldom, and never. In the Likert scale, each issue set out five alternative answers for reviewers on the degree of participation with scores from 5 to 1 (5 = always and 1 = never). These questions on low-carbon behaviors were designed around the subjects of travelling, power use, consumption, and living habits, based on the above literature review. The factors reflecting respondents’ participation in low-carbon behaviors were analyzed with the factor analysis in SPSS tools. Multiple linear regression analysis was used to discuss the relationship between neighborhood residents’ low-carbon behavior factors and their overall degree of participation.
A high-rise residential neighborhood in Wuhan, China was chosen to acknowledge neighborhood residents’ cognition of and participation in low-carbon behaviors. The medium-scale and gated neighborhood is near government, hospital, school, shopping center, transport, and other public service infrastructures. Figure
Situation of field investigation.
The basic information of the valid questionnaires is given below. Table
Structure of the respondent populations in the survey.
Item | Subitem | % | Item | Subitem | % |
---|---|---|---|---|---|
Age | ≤20 years | 7.4 | Education level | Junior high school and below | 6.9 |
21–39 years | 66.1 | High school or technical school | 19.6 | ||
40–59 years | 20.6 | College or bachelor degree | 61.4 | ||
≥60 years | 5.9 | Graduate degrees | 12.1 | ||
Profession | Enterprise employee | 32.8 | Profession | Student | 10.6 |
Government or institution employees | 15.3 | Retirees | 5.9 | ||
Self-employed person | 14.8 | Other | 20.6 |
Data were collected using the stratified random sampling method. The investigation was carried out in public places for residents living in the neighborhood and willing to be interviewed voluntarily. Questionnaires were distributed during their weekend breaks. Subjects were randomly selected in the neighborhood. And all respondents were well informed that their responses would remain confidential and only be used for research purposes. A questionnaire was filled in approximately 15 minutes. The survey process mainly contained self-administered questionnaires and was supplemented by the nonstructured interview method to perfect questionnaires.
Residents’ low-carbon cognition was analyzed using the descriptive statistic method. Neighborhood residents’ participation was analyzed with principal component analysis and multiple linear regression analysis. Before carrying out these analyses, it is needed to judge the feasibility of the sample data through reliability test and Bartlett and KMO test.
Cronbach’s
The appropriation for the initial sampling was measured through the Bartlett spherical test and KMO (Kaiser–Meyer–Olkin) index basing on the factor analysis. When the KMO index is greater than 0.7, the data are suitable for factor analysis [
The analysis results are as follows. In the aspect of global warming, 95.2% respondents said that they knew and felt the climate change and 4.8% respondents said that they were unclear about the change. In the aspect of low-carbon concept cognition, 43.4% respondents were familiar with low-carbon concept and its content, 54.5% respondents said they knew low-carbon concept without noticing its exact meaning, and 2.1% never know low-carbon concept. From the interview in the investigative process, it was known that residents gained low-carbon knowledge mainly from television, internet, newspapers, friends, and neighbors. In the aspect of relationship between low-carbon theory and residents’ daily lifestyles, 59.8% residents believed that the two sides were closely related to each other, 37.6% considered that the two sides were relevant, and 2.6% thought that the two sides were unrelated. The results show that most respondents had understood and cared about the impact of low-carbon concept on their daily life. Their cognition had consistency.
Figure
Neighborhood residents’ preferential selection of domestic low-carbon-related measures.
In the aspect of cognition on urban low-carbon policies, respondents believed that the government would focus on low-carbon transition of communities. Figure
Main aspects needed to be supported by the government.
In sum, a considerable part of neighborhood residents had sufficient cognition on low-carbon concept. Most of them believed that the low-carbon theory is closely related to their daily life. Majority of respondents were willing to perform low-carbon lifestyles. Additionally, over 40% residents expected the government to make differences in low-carbon transition. Neighborhood residents’ cognition had no obvious difference.
Through statistical analysis, it was found that most respondents’ overall self-reported level of participation in low-carbon behaviors was intermediate. Among the 189 questionnaires, 5%, 21%, 65%, and 9% of residents evaluated their own degree of participation in low-carbon behaviors as “high,” “relatively high,” “general,” and “low,” respectively. The factors of low-carbon behaviors with high scores among the observed variables contained four aspects, namely, natural ventilation and lighting, use of energy-saving lamps, taking public transport, and poweroff for unused electrical appliances. It was followed in order by plant cultivation, shopping with carry-on bags or baskets, reuse of waste paper, walking trip, and clothing recycling. What is more, there were big differences in three areas including refusal of one-time service or consumption, waste water reuse, and waste classification and recycling. The average scores of the three were 3.02, 2.99, and 2.95, respectively, which were close to the median value of 3. Thus, it can be seen that residents had a neutral view to participate in these three low-carbon behaviors. During the interview, some residents expressed their dissatisfaction with imperfect construction of waste classification system, roadway travel, and clothe recycling facilities. Meanwhile, they expressed willingness to accept improved local products with quality and safety assurance and to support the promotion of home water recycling system.
According to the inclusion criteria of characteristic roots greater than 1 [
Principal component extraction and rotation results of each low-carbon behavior variable.
Component | Initial eigenvalues | Extraction sums of squared loadings | Rotation sums of squared loadings | ||||||
---|---|---|---|---|---|---|---|---|---|
Total | % of variance | Cumulative % | Total | % of variance | Cumulative % | Total | % of variance | Cumulative % | |
1 | 4.360 | 29.070 | 29.070 | 4.360 | 29.070 | 29.070 | 2.088 | 13.922 | 13.922 |
2 | 1.443 | 9.623 | 38.693 | 1.443 | 9.623 | 38.693 | 1.977 | 13.182 | 27.104 |
3 | 1.312 | 8.748 | 47.441 | 1.312 | 8.748 | 47.441 | 1.865 | 12.432 | 39.536 |
4 | 1.178 | 7.851 | 55.293 | 1.178 | 7.851 | 55.293 | 1.838 | 12.254 | 51.790 |
5 | 0.914 | 6.092 | 61.384 | 0.914 | 6.092 | 61.384 | 1.439 | 9.594 | 61.384 |
6 | 0.840 | 5.601 | 66.985 | — | — | — | — | — | — |
7 | 0.733 | 4.883 | 71.868 | — | — | — | — | — | — |
8 | 0.726 | 4.842 | 76.710 | — | — | — | — | — | — |
9 | 0.639 | 4.259 | 80.969 | — | — | — | — | — | — |
10 | 0.608 | 4.055 | 85.025 | — | — | — | — | — | — |
11 | 0.562 | 3.744 | 88.769 | — | — | — | — | — | — |
12 | 0.447 | 2.982 | 91.750 | — | — | — | — | — | — |
13 | 0.437 | 2.915 | 94.665 | — | — | — | — | — | — |
14 | 0.416 | 2.775 | 97.440 | — | — | — | — | — | — |
15 | 0.384 | 2.560 | 100.000 | — | — | — | — | — | — |
The varimax method was selected to orthogonally rotate the variance axis such that load factors of initial common factors were split toward 0 and 1 for summing up explanatory variables among common factors. Through naming high-load variables, five dimensions of indicator variables were confirmed, namely, efficient resource consumption (ERC), recycling habits (RH), home energy conservation (HEC), green travel (GT), and spontaneous environmental behaviors (SEB). Table
Loading matrix and cumulative explained variance after rotation.
Factors | Factor loading | Explained variance (%) | Cumulative explained variance (%) |
---|---|---|---|
Efficient resource consumption (ERC) | 13.922 | 13.922 | |
Waste water reuse | 0.776 | ||
Use of water-saving devices (such as water-efficient closestools and showers) | 0.635 | ||
Reuse of waste paper | 0.558 | ||
Support of local products | 0.653 | ||
Recycling habits (RH) | 13.182 | 27.104 | |
Clothing recycling | 0.682 | ||
Refusal of one-time services or consumptions | 0.532 | ||
Waste classification and recycling | 0.747 | ||
Home energy conservation (HEC) | 12.432 | 39.536 | |
Use of energy-saving lamps | 0.735 | ||
Natural ventilation and lighting | 0.780 | ||
Poweroff for unused household appliances | 0.619 | ||
Green travel (GT) | 12.254 | 51.790 | |
Taking public transport | 0.771 | ||
Walking trip | 0.732 | ||
Transportation by bikes or electromobiles | 0.569 | ||
Spontaneous environmental behaviors (SEB) | 9.594 | 61.384 | |
Shopping with carry-on bags or baskets | 0.592 | ||
Plant cultivation | 0.786 |
The resultant five common factors were set as independent variables, and the neighborhood residents’ overall level of participation was set as a dependent variable. Their correlations were analyzed using the Pearson correlation analysis. The Pearson coefficient was used for two-tailed
Correlation between factors of low-carbon behaviors and the overall degree of participation.
Factors | Overall degree of participation in low-carbon behaviors | ||
---|---|---|---|
Pearson correlation | Significance (2-tailed) | Significance level | |
ERC | 0.207 | 0.004 | 0.01 |
RH | 0.205 | 0.005 | 0.01 |
HEC | 0.300 | 0.000 | 0.01 |
GT | 0.147 | 0.044 | 0.05 |
SEB | 0.042 | 0.562 | Uncorrelated |
Note:
To further explore the influence extent and the direction of each factor, factors SEB and GT that had weak or no correlation with neighborhood residents’ overall degree of participation were excluded. ERC, RH, and HEC were set as three independent variables which had high correlation with neighborhood residents’ overall participation level. The overall degree of residents’ participation was set as dependent variable. The correlation between independent variables and the dependent variable was analyzed using the stepwise regression method. Table
Coefficient analysis of regression models.
Model | Unstandardized coefficients | Standardized coefficients |
|
Significance | Collinearity statistics | |||
---|---|---|---|---|---|---|---|---|
B | Stdandard error | Beta | Tolerance | VIF | ||||
1 | Constant | 3.138 | 0.061 | — | 51.445 | 0.000 | — | — |
HEC | 0.263 | 0.061 | 0.300 | 4.294 | 0.000 | 1.000 | 1.000 | |
2 | Constant | 3.138 | 0.060 | — | 52.556 | 0.000 | — | — |
HEC | 0.263 | 0.060 | 0.300 | 4.387 | 0.000 | 1.000 | 1.000 | |
ERC | 0.181 | 0.060 | 0.207 | 3.027 | 0.003 | 1.000 | 1.000 | |
3 | Constant | 3.138 | 0.058 | — | 53.734 | 0.000 | — | — |
HEC | 0.263 | 0.059 | 0.300 | 4.485 | 0.000 | 1.000 | 1.000 | |
ERC | 0.181 | 0.059 | 0.207 | 3.095 | 0.002 | 1.000 | 1.000 | |
RH | 0.180 | 0.059 | 0.205 | 3.071 | 0.002 | 1.000 | 1.000 |
In sum, ERC, RH, HEC, GT, and SEB were the five principal factors related to respondents’ level of participation in low-carbon behaviors. Excluding SEB which was not correlated with neighborhood residents’ level of participation, the rest of the components that had significant effect were HEC, ERC, RH, and GT in order. These four had linear relationships with respondents’ overall level of participation. Specifically, HEC had a significant positive impact on neighborhood residents’ overall level of participation in low-carbon behaviors. ERC presented a high positive correlation with neighborhood residents’ degree of participation. Meanwhile most residents expressed their willingness to buy local products with quality and safety assurance. RH largely contributed to improve neighborhood residents’ degree of participation. GT was not obviously correlated with residents’ level of participation.
The following points could be drawn from the above results. Neighborhood residents have high cognition on low-carbon theory but intermediate-level participation in low-carbon behaviors through their self-reported survey, which is similar to the results which were generally identified from the previous studies [ The results in this paper revealed people’s level of participation in low-carbon behaviors at the neighborhood scale, while many previous literatures emphasized on the impact of individual low-carbon behavior change [ In spite of considerable advances in residents’ recognition and implementation of low-carbon related behaviors, there is still space for improvement. For example, most neighborhood residents would like to donate and recycle used clothing but were always hindered by the absence of standardized and effective channels or systems. Meanwhile, quite a number of respondents emphasized particularly on increasing waste separation facilities and improving supervision mechanisms and agreed to abstain and resist various disposable consumer products such as disposable chopsticks, toiletries, and plastic bags, though some expressed their difficulties to do so in their daily lives. Furthermore, due to the restrictions of haze, air pollution, or travel distance, few people adopted pedestrian way to travel. Especially, people who were far away from the subway or bus stops preferred to drive cars. However, most residents expressed their willingness to participate in low-carbon travel if their convenient travel was offered. In addition, though young male residents generally refused to carry reusable bags, some residents have gradually formed the habit of carrying shopping bags after the promulgation of limited use of plastic. In short, neighborhood residents’ level of participation is improving.
To enhance the overall level of neighborhood residents’ participation in low-carbon behaviors and to meet the demand of low-carbon development, the following are recommended: A typical model of low-carbon survival pattern should be set up for neighborhood residents to learn and refer to. The organization of low-carbon activities related to clothing, food, housing, and behaviors would effectively promote personal involvement in low-carbon behaviors. In addition, appropriate material rewards and spiritual encouragements would encourage individuals to lead a low-carbon lifestyle and help improve residents’ enthusiasm in participation. Neighborhood residents’ awareness of low-carbon theory needs to be reinforced. Low-carbon cognition can offer an enduring base for residents to participate in low-carbon behaviors. Neighborhood residents’ understanding about low-carbon concept can be enhanced through lectures and cultural and product exhibitions. Low-carbon concept can constantly penetrate toward residents’ living. Therefore, individual living and consumption habits could be reshaped gradually for suitable low-carbon pattern. The employment of sharing mechanism of responsibility will be conducive to the construction of harmonious and healthy relationships among neighborhoods. Good neighborhood relations help increase neighborhood residents’ interaction and participation initiatives in their daily lives. The implementation of burden sharing helps gradually achieve the low-carbon transition of residents’ behaviors by performing and undertaking the responsibility of low-carbon construction. The use of high-tech innovation technology contributes to residents’ innovative behaviors in urban low-carbon transition. Especially the employment of new energy technology, advanced sanitation technology, and high-performance technology could provide support for low-carbon transition of neighborhoods. So the encouragement of low-carbon innovation and the improvement of energy efficiency are inevitable choices to build low-carbon neighborhoods. Matching mechanism and policy and public service infrastructures contribute to individual participation in low-carbon behaviors. The formulation and revision of low-carbon related regulations such as domestic energy-saving ordinances and detailed rules could regulate residents’ consuming behaviors and provide deep pulling power for low-carbon transition in neighborhoods. Simultaneously, mature physical infrastructures such as public transportation, urban greenways, parkland, squares, and sanitation facilities offer convenience for residents to participate in low-carbon behaviors.
Personal energy consumption takes up a crucial part of carbon dioxide emissions. Residents’ cognition of and participation in low-carbon behaviors have significant roles in the low-carbon transformation in neighborhoods for coping with the climate change. Basing on a questionnaire survey, individual cognition of and participation in low-carbon behaviors were analyzed. Several findings were achieved through an investigation in Wuhan, China. First, most respondents believed the low-carbon impact on their daily lives and participated in low-carbon behaviors from traditional aspects of domestic energy or resource conservation. Second, many interviewees tended to participate in low-carbon behaviors with the motivation of economic interest. When the behaviors are related to the aspects of energy, resource, or consumption that are directly related to personal monetary benefits, respondents showed high level of participation. Finally, they rarely participate in public low-carbon behaviors such as planting trees or other low-carbon behaviors that are done through cooperation or interchange among residents, although there are big potential powers for residents to implement this kind of low-carbon behaviors. Therefore, neighborhood residents’ participation in low-carbon behaviors is still at exploratory stage.
These findings have a large amount of implications for the implementation of low-carbon development. Recently, a number of projects have been launched for sewage treatment, waste recycling, and new energy exploration. But the cognition of low-carbon knowledge is still recognized to be the pushing hand for further encouraging neighborhood residents’ participation in low-carbon behaviors. In addition, policies, standard, and rules need to be made for the guarantee of their performance.
Though this explorative study can help us to acknowledge neighborhood residents’ degree of participation in low-carbon behaviors and cognition status, there are still some limitations as follow. (1) The relevance of neighborhood residents’ cognition or the sociodemographic variables with their participation in low-carbon behaviors, and the relationship between neighborhood residents’ low-carbon cognition and their participation in low-carbon behaviors are worth for further study. (2) The factors affecting household energy consumption behaviors and the basic conditions for individual participation in low-carbon lifestyles are worth to be discussed further. (3) Questionnaires need to be designed more comprehensively and to cover other public low-carbon behaviors. (4) There may appear the tendency of intermediate value choice which leads to some bias and lacking property differences because the social investigation is basing on neighborhood residents’ self-reported data-related low-carbon issues. Therefore, further research is needed to adopt other methods or tools to collect data and reduce subjectivity.
The authors declare that they have no conflicts of interest.
This work was supported by the Key Project of National Science and Technology Support Program for the Twelfth Five-Year Plan of China, “Research and Demonstration of Planning and Construction Monitoring Technology in Green Ecological Village” (2014BAL04B03-3).