China’s green future and household solid waste: Challenges and prospects

Ye, Qing; Anwar, Muhammad; Zhou, Rongting; Asmi, Fahad; Ahmad, Intikhab

doi:10.1016/j.wasman.2020.02.025

Cited by 46 publications

(46 citation statements)

References 103 publications

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“…In essence, training the rural residents on how to classify the solid wastes and how to become environmentally conscious influences the frequent occurrences of waste classification and environmental protection. The policymakers in China have similarly embarked in implementing several policies in line with rural waste management, particularly in Jiangsu Province, because of the increasing pressure from environmental pollution [1]. Particularly, the main policy that has been implemented in Jiangsu regarding the rural waste management and environmental protection consists of rural waste classification before disposal as well as environmental protection awareness.…”

Section: Discussionmentioning

confidence: 99%

“…China has experienced fast economic development during the last several decades, a trend that has given rise to unprecedented solid waste production. Even more, China became the largest solid waste generator in 2004 and is projected to have the fastest and largest waste growth historically [1]. The authors of [2] observed that the per capita annual growth rate of solid waste generation in China ranges from 8% to 10%.…”

Section: Introductionmentioning

confidence: 99%

“…Yet, rural areas account for about 60% of mainland China. That is, the rural population totals approximately 675 million people residing in about 40,000 small towns [1]. Researchers estimate that the rural solid waste generation rate ranges from 0.25 kg to 2.1 kg per capita per day [3].…”

Section: Introductionmentioning

confidence: 99%

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Rural Residents’ Awareness of Environmental Protection and Waste Classification Behavior in Jiangsu, China: An Empirical Analysis

Liu

Osewe

Wang

et al. 2020

IJERPH

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Achieving waste classification and environmental protection awareness assists in enhancing the rural ecological environment, improves the quality of the rural residents’ life, and augments the rate of reusing resources within the rural setups. In order to study the factors influencing rural waste classification and environmental protection awareness, we conducted a project among rural residents of Jiangsu, China. We used both the logistic regression model and the ordinary least squares model to achieve the goals of this paper. Similarly, we found that the households’ level of education influenced the rural residents’ decision to classify waste and to protect the environment regarding whether a household consists of a village cadre; the availability of public waste collection facilities; the distance between households and the waste collection points; whether the waste is picked, assorted, and collected locally; and the cost of waste disposal. In light of all these factors, we recommended that the authorities should increase the rural residents’ waste classification and environmental protection awareness. Also, through the local government, the national government should strengthen and sustain rural waste disposal funds. Finally, there should be stringent laws and regulations outlining the role of the rural residents regarding waste classification and environmental protection awareness.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Rural Residents’ Awareness of Environmental Protection and Waste Classification Behavior in Jiangsu, China: An Empirical Analysis

Liu

Osewe

Wang

et al. 2020

IJERPH

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“…The new standard is to classify waste into four types, namely wet waste, recycling, harmful waste, and dry waste [13]. The ways by which to improve the efficiency of waste treatment rely not only on scientific criteria of waste classification, but also on the reliable and fast implementation of waste classification [14].…”

Section: Introductionmentioning

confidence: 99%

EnCNN-UPMWS: Waste Classification by a CNN Ensemble Using the UPM Weighting Strategy

Zheng

2021

Electronics

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The accurate and effective classification of household solid waste (HSW) is an indispensable component in the current procedure of waste disposal. In this paper, a novel ensemble learning model called EnCNN-UPMWS, which is based on convolutional neural networks (CNNs) and an unequal precision measurement weighting strategy (UPMWS), is proposed for the classification of HSW via waste images. First, three state-of-the-art CNNs, namely GoogLeNet, ResNet-50, and MobileNetV2, are used as ingredient classifiers to separately predict and obtain three predicted probability vectors, which are significant elements that affect the prediction performance by providing complementary information about the patterns to be classified. Then, the UPMWS is introduced to determine the weight coefficients of the ensemble models. The actual one-hot encoding labels of the validation set and the predicted probability vectors from the CNN ensemble are creatively used to calculate the weights for each classifier during the training phase, which can bring the aggregated prediction vector closer to the target label and improve the performance of the ensemble model. The proposed model was applied to two datasets, namely TrashNet (an open-access dataset) and FourTrash, which was constructed by collecting a total of 47,332 common HSW images containing four types of waste (wet waste, recyclables, harmful waste, and dry waste). The experimental results demonstrate the effectiveness of the proposed method in terms of its accuracy and F1-scores. Moreover, it was found that the UPMWS can simply and effectively enhance the performance of the ensemble learning model, and has potential applications in similar tasks of classification via ensemble learning.

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“…Solid waste management is one of the greatest worldwide challenges, especially in China because of its large rural population and low economic development level [ 1 , 2 ]. It is reported that 300 million tons of solid waste is generated each year in rural China, and nearly 60% of them are discarded directly to the land or the water, causing profound adverse impacts on environmental protection, economic development, and human health [ 3 , 4 ].…”

Section: Introductionmentioning

confidence: 99%

Determinants of Public-Private Partnership Adoption in Solid Waste Management in Rural China

Pan

Chen

Zhou

et al. 2020

IJERPH

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Rural solid waste management is a severe challenge in China. The Public-Private Partnership (PPP) is an effective method for rural solid waste management. However, policy efforts aimed at stimulating the adoption of PPP in rural solid waste management have been limited in their success. This study aims to empirically investigate the determinants of rural solid waste management PPP adoption in China. First, this study builds a theoretical model that consists of factors related to the institutional environment and market and proposes theoretical hypotheses. Then, using the balanced provincial panel data of 150 samples from 2015 to 2019, this study applies various count regression models and truncated regression models to empirically test the theoretical hypotheses. The results show that provinces with higher fiscal transparency, financial burdens, and market demand tend to adopt more PPP, while provinces with lower per capita GDP and market openness index ratings have a stronger motivation to initiate more PPP. In contrast, investment institutional environment factors have no impact on PPP adoption. To stimulate the development of PPP in rural solid waste management, this study proposed that a good-governed government and a strong market demand are critical foundations, and also a debt-risk prevention and evaluation system should be established to avoid local debt risks resulting from over-adoption of PPP.

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China’s green future and household solid waste: Challenges and prospects

Cited by 46 publications

References 103 publications

Rural Residents’ Awareness of Environmental Protection and Waste Classification Behavior in Jiangsu, China: An Empirical Analysis

Rural Residents’ Awareness of Environmental Protection and Waste Classification Behavior in Jiangsu, China: An Empirical Analysis

EnCNN-UPMWS: Waste Classification by a CNN Ensemble Using the UPM Weighting Strategy

Determinants of Public-Private Partnership Adoption in Solid Waste Management in Rural China

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