Decomposition analysis of the decoupling and driving factors of municipal solid waste: Taking China as an example

Zhao, Xin; Liu, Heng-shuo; Ding, Lili

doi:10.1016/j.wasman.2021.11.003

Cited by 14 publications

(5 citation statements)

References 50 publications

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“…The LMDI method has also been widely used in studies targeting the drivers of carbon emissions in industries such as electricity [17,25], transportation [21], and construction [20]. In addition to carbon emissions, the LMDI method has been applied reasonably well in the analysis of drivers in several other areas (e.g., NOx [27,28], industrial energy consumption and emission reduction [59][60][61], municipal solid waste [62], power generation variance [63], etc. ).…”

Section: Decomposition Methodsmentioning

confidence: 99%

Analysis of the Social and Economic Factors Influencing PM2.5 Emissions at the City Level in China

Huang,

Jiang,

Chen

2023

Sustainability

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Respirable suspended particles (PM2.5) are one of the key components of haze, which not only causes a variety of lung, intestinal, and vascular diseases, but also affects cognitive levels. China is facing the challenge of severe PM2.5 concentrations, especially in urban areas with a high population density. Understanding the key factors that influence PM2.5 concentrations is fundamental for the adoption of targeted measures. Therefore, this study used the Logarithmic Mean Divisia Index (LMDI) method to identify the key factors influencing PM2.5 concentrations in 236 cities in northeastern, western, central, and eastern China. The findings were as follows. The emission intensity (EI) played an important suppressing role on PM2.5 concentrations in all cities from 2011–2020. The energy intensity (EnI) inhibited PM2.5 concentrations in 157 cities; the economic output (EO) stimulated PM2.5 concentrations in some less economically developed regions; and population (P) spurred PM2.5 concentrations in135 cities, mainly concentrated in developed eastern cities. This study provides a whole picture of the key factors influencing PM2.5 concentrations in Chinese cities, and the findings can act as the scientific basis and guidance for Chinese city authorities in formulating policies toward PM2.5 concentration reduction.

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Section: Decomposition Methodsmentioning

confidence: 99%

Analysis of the Social and Economic Factors Influencing PM2.5 Emissions at the City Level in China

Huang,

Jiang,

Chen

2023

Sustainability

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“…The debt-to-income ratio promotes MSW growth, but the debt-to-output ratio restrains it. Thus, the debt-to-income ratio should be used to promote economic development in conjunction with a reduction in MSW production and an improvement in ecological standards [31]. The third hypothesis of the investigation is as follows:…”

Section: H1mentioning

confidence: 99%

Environmental Effects of Bio-Waste Recycling on Industrial Circular Economy and Eco-Sustainability

et al. 2022

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Few prior studies have examined the social and environmental consequences of waste generation and recycling, resulting in a policy gap in the sustainability agenda. The research filled a knowledge vacuum in the literature by investigating the environmental repercussions of different waste generation and recycling processes in the Chinese economy. The study analyzed waste production and recycling statistics over the last 46 years, from 1975 to 2020, and their impact on the nation’s emissions per capita. This study used four primary approaches to determine the links between the examined variables, beginning with the unit root test, which identifies the stationary process of the variables’ underlying processes. Second, the autoregressive distributed lag (ARDL) model was used to produce the variables’ short- and long-run estimates. Third, estimations of Granger causality examined the causal relationships between the variables. Finally, innovation accounting matrices (IAM)were utilized to predict the relationships between variables during the following decade. The unit root estimates imply the mix order of variable integration; hence, it is appropriate to employ ARDL modeling for parameter estimations. The ARDL estimations demonstrate that combustible renewables and waste decrease a nation’s carbon emissions by boosting industrial waste recycling. Despite recycling systems, carbon emissions have escalated to uncontrolled levels owing to the massive production of municipal solid garbage. Sustainable waste management and recycling are vital to reducing carbon emissions. Granger’s estimations of causation imply that combustible renewables and waste and carbon emissions cause industrial and municipal solid waste recycling. Additionally, population growth is responsible for greenhouse gas emissions, biowaste recycling, and industrial waste recycling. Furthermore, this shows the two-way connections between combustible renewables and waste and carbon emissions, implying the need to develop green waste recycling strategies in a nation. The IAM method identified future relationships between variables, which aids policymakers in implementing sustainable waste management practices for a nation. This study concludes that the environmental consequences of waste generation and recycling impede the nation’s circular economy agenda, which can be sustained by knowledge spillovers, chemical reduction in manufacturing, and allocating a certain amount of US dollars to ecological resource conservation.

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“…As China's waste classification management is still in its infancy, statistics and monitoring of waste generation at each collection point are not yet available. According to the findings of relevant studies, the population is the primary factor influencing the volume of domestic waste generation (Cheng et al, 2020;Zhao et al, 2022), so the waste generation was estimated based on the population of the selected domestic waste collection points in the Baohe District. According to the Hefei City Statistical Yearbook 2021, the average household population in Baohe District in 2020 was 2.86 people, and the total number of households in each district was determined by checking the total number of households in each district on the websites of Anjuke and Chain Home.…”

Section: Data Sourcesmentioning

confidence: 99%

Municipal Solid Waste Collection and Transportation Routing Optimization Based on Iac-Sfla

Hu,

Ju,

Peng

et al. 2024

Journal of Environmental Engineering and Landscape Management

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In order to realize the efficient collection and low-carbon transport of municipal garbage and accelerate the realize the “dual-carbon” goal for urban transport system, based on the modeling and solving method of vehicle routing problem, the municipal solid waste (MSW) collection and transport routing optimization of an Improved Ant Colony-Shuffled Frog Leaping Algorithm (IAC-SFLA) is proposed. In this study, IAC-SFLA routing Optimization model with the goal of optimization collection distance, average loading rate, number of collections, and average number of stations is constructed. Based on the example data of garbage collection and transport in southern Baohe District, the comparative analysis with single-vehicle models, multiple-vehicle models, and basic ant colony algorithms. The multi-vehicle model of collection and transportation is superior to the single-vehicle model and the improved ant colony algorithm yields a total collection distance that is 19.76 km shorter and an average loading rate that rises by 4.15% from 93.95% to 98.1%. Finally, the improved ant colony algorithm solves for the domestic waste collection and transportation path planning problem in the north district of Baohe. Thus, the effectiveness and application of the proposed algorithm is verified. The research result can provide reference for vehicle routing in the actual collection and transport process, improve collection and transport efficiency, and achieve the goal of energy conservation and emission reduction.

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Decomposition analysis of the decoupling and driving factors of municipal solid waste: Taking China as an example

Cited by 14 publications

References 50 publications

Analysis of the Social and Economic Factors Influencing PM2.5 Emissions at the City Level in China

Analysis of the Social and Economic Factors Influencing PM2.5 Emissions at the City Level in China

Environmental Effects of Bio-Waste Recycling on Industrial Circular Economy and Eco-Sustainability

Municipal Solid Waste Collection and Transportation Routing Optimization Based on Iac-Sfla

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