A factor analysis of residents’ performance in municipal solid waste source-separated collection: A case study of pilot cities in China

Abstract

To explore the potential effectiveness of a localized waste recycling system in Chinese cities, several rounds of a municipal solid waste source-separated collection (MSWSC) program were implemented throughout China from 2000 to 2017. In our study, to evaluate the achievements of the MSWSC program, a structured questionnaire survey and face-to-face interviews were conducted in eight representative cities from the MSWSC pilot cities. Influencing factors were examined via a Hierarchical Linear Model (HLM) on both the individual level and the city level. The differences in MSWSC performance among the eight research cities were investigated through a comparative analysis. The results suggested that gender, age, knowledge of MSWSC, satisfaction with sanitation and satisfaction with publicity had significant impacts on MSWSC, and we further found that the city-level factors influenced the relationship between MSWSC performance and the individual-level variables. Differences among the eight research sites indicated that Nanjing and Hangzhou exhibited relatively high achievements in the implementation of MSWSC program, while Yichun and Guiyang showed poor performance. The experiences of these advanced pilot cities suggest that specific containers for designated waste types, widespread public education, and sufficient MSWSC incentives must be provided and publicized to promote municipal solid waste recycling behaviors. Given the unique status of municipal solid waste management in China and its regional heterogeneity, the MSWSC system should be further discussed with regard to local conditions in a wider range of city settings.Implications: This study attempts to discuss the factors affecting performance on municipal solid waste source-separated collection (MSWSC) by considering the nested data of two levels of individual and city from a structured questionnaire survey. Therefore, a Hierarchical Linear Model is established which can analyze the intra-group and inter-group effects of two-level variables. The proposed method can be expanded to other cities to determine the main factors affecting MSWSC or to evaluate the residents' performance on MSWSC.

Determinants of Satisfaction with Solid Waste Management Services: A Central–Local Comparison in China

“…Many studies focus on residents' satisfaction with SWMS from local government in rural or urban regions before a mandatory or demonstration policy, but there is a lack of evaluations about the satisfaction with national policy or services and the central-local and urban-rural comparison [43][44][45][46][47][48][49][50][51][52]. In China, many studies have analyzed rural residents' satisfaction in specific regions-for example, Jiangsu, Beijing, Hunan and Hangzhou Province-and showed that the level of satisfaction is 77%, 67%, 65% and 58%, respectively [43][44][45][46].…”

“…Only a few studies have analyzed satisfaction with SWMS using national data; for example, Li et al showed that 85% of households were satisfied with waste collection facilities provided by local government using the data from 1450 households of seven provinces in rural China [47]. Other research works showed urban residents' satisfaction with municipal solid waste management services-for example, the detailed non-pilot city of Tongling, some pilot cities of Harbin and Xining and all pilot cities-and found that 34%, 44%, 17% and 20% residents were satisfied with SWMS, respectively [48][49][50][51]. There are a few studies that have analyzed satisfaction with SWMS using nationwide data; for example, Wang et al showed that 65% of residents were satisfied with waste separation bins using data from 672 respondents of 31 provinces in urban China [38].…”

Evaluation of the household solid waste mandatory sorting policy in Shanghai: A 1-year public opinion survey

“…The NCs and PMCs are responsible for HSW sorting in the model. Thus, we focus on two aspects: (i) the constraints of laws and regulations, including levying financial penalties for not sorting and rewarding points for participation (Zou et al, 2019); and (ii) the promotion of publicity and education. Specifically, the responsible parties should actively promote sorting to create an atmosphere where all residents participate.…”

Identifying the influencing factors and constructing incentive pattern of residents’ waste classification behavior using PCA-logistic regression

“…Although residents in Jinan have begun to pay attention to waste classification, many problems hinder them from engaging in waste sorting, including a long-term lack of relevant education and a sound waste classification system. These problems are prevalent in other waste classification pilot cities (Zou et al 2019). Therefore, a more nuanced understanding of barriers and dilemmas to sorting waste in China is warranted and Jinan city offers an important case to investigate the affecting factors of community residents engaged in waste classification.…”