An optimal model and its application for the management of municipal solid waste from regional small cities in China

Based on the basic characteristics of municipal solid waste (MSW) from regional small cities in China, some optimal management principles have been put forward: regional optimization, long-term optimization, and integrated treatment/disposal optimization. According to these principles, an optimal MSW management model for regional small cities is developed and provides a useful method to manage MSW from regional small cities. A case study application of the optimal model is described and shows that the optimal management scenarios in the controlling region can be gained, adequately validating and accounting for the advantages of the optimal model.     

Factors Influencing Regional Municipal Solid Waste Management Strategies

Abstract

Although regionalization policies have been proven as good strategies for municipal solid waste (MSW) management in previous studies, the optimal allocation of the waste stream is significantly affected by several influential factors, thus further investigation of the impacts of these factors on regional MSW management strategies is necessary. This study demonstrated the impacts of waste-to-electricity transformation coefficient (WETC) of incinerators and the fluctuation of unit tipping fees on the regional MSW flow/allocation of the Taipei metropolitan area from practical and economic perspectives. Real-world data and linear programming were used to obtain the least-cost alternatives under different scenarios. Analytical results indicated some treatment facilities had geographic superiority and their priorities changed when actual WETCs of incinerators were considered. Treatment facilities located at weighted centers were identified. The allocation of MSW among incinerators and landfills is affected by fluctuation of unit tipping fees within a certain range. Treatment facilities sensitive to the changes in unit tipping fees were also identified. Regression equations were also established that can estimate the cost items of MSW management scenarios with different unit tipping fees. The results of this study are very useful for daily basis regulation of MSW administration.     

An economic evaluation and assessment of environmental impact of the municipal solid waste management system for Taichung City in Taiwan

Municipal solid waste management (MSWM) is an important environmental challenge and subject in urban planning. For sustainable MSWM strategies, the critical management factors to be considered include not only economic efficiency of MSW treatment but also life-cycle assessment of the environmental impact. This paper employed linear programming technique to establish optimal MSWM strategies considering economic efficiency and the air pollutant emissions during the life cycle of a MSWM system, and investigated the correlations between the economical optimization and pollutant emissions. A case study based on real-world MSW operating parameters in Taichung City is also presented. The results showed that the costs, benefits, streams of MSW, and throughputs of incinerators and landfills will be affected if pollution emission reductions are implemented in the MSWM strategies. In addition, the quantity of particulate matter is the best pollutant indicator for the MSWM system performance of emission reduction. In particular, this model will assist the decision maker in drawing up a friendly MSWM strategy for Taichung City in Taiwan.

Implications: Recently, life-cycle assessments of municipal solid waste management (MSWM) strategies have been given more considerations. However, what seems to be lacking is the consideration of economic factors and environmental impacts simultaneously. This work analyzed real-world data to establish optimal MSWM strategies considering economic efficiency and the air pollutant emissions during the life cycle of the MSWM system. The results indicated that the consideration of environmental impacts will affect the costs, benefits, streams of MSW, and throughputs of incinerators and landfills. This work is relevant to public discussion and may establish useful guidelines for the MSWM policies.     

Evaluation of Solid Waste Management Strategies in the Taipei Metropolitan Area of Taiwan

Abstract

Chenfang Lin is with the Department of Soil and Environmental Science at National Chung Hsing University.Municipal solid waste (MSW) management is a major concern for highly urbanized societies. Among proposed MSW management systems, regionalization programs generally have received considerable attention. This study analyzes real-world operational data to assess different MSW management policies, especially regionalization strategies, and their impact on MSW management systems in the Taipei metropolitan area. Linear programming is also used to identify the minimum costs sustained by each policy. The linear programming results show that regionalization programs are more economical and also improve incinerator operation efficiency. Sensitivity analysis indicates that the minimum treatment requirement of incinerators is a very sensitive influence on the MSW flows distributed through the entire region. The MSW of several “sensitive” administrative districts will be allocated to different treatment facilities according to different management strategies. A list of preferential sequences of MSW treatment and disposal facilities can also be identified by the model presented in this study. The results of this study may provide a useful tool for aiding decision-making related to real-world MSW management problems.     

Greenhouse Gas Mitigation-Induced Rough-Interval Programming for Municipal Solid Waste Management

Abstract

A greenhouse gas (GHG) mitigation-induced rough-interval programming model is proposed in this study. Components of GHG emission and environmental pollution control are incorporated into the objective function and a series of relevant constraints. To explicitly examine more complexities existing in many parameters, rough intervals are also communicated into the modeling framework. The proposed model presents satisfactory capabilities in analyzing complicated interrelationships among municipal solid waste (MSW) management, climate-change impact, and environmental pollution control. It can also provide optimal allocation schemes and facilitate decision-makers regulating environmentally sustainable strategies. The developed model is then applied to a case study for demonstrating its applicability. Two representative scenarios (relatively representing two potential management policies that may be implemented in the future years) are considered. The results indicate that the developed model presents advantages in mitigating GHG emissions and the associated climate-change impact. The comparison between the GHG mitigation-induced model with and without rough-interval parameters is also investigated. Completely different solutions of the two models imply the significant impact of dual-uncertain information on the system, which can hardly be addressed through the existing optimization approaches.     

Minimax Regret Analysis for Municipal Solid Waste Management: An Interval-Stochastic Programming Approach

Abstract

In this study, an interval minimax regret programming (IMMRP) method is developed for the planning of municipal solid waste (MSW) management under uncertainty. It improves on the existing interval programming and minimax regret analysis methods by allowing uncertainties presented as both intervals and random variables to be effectively communicated into the optimization process. The IMMRP can account for economic consequences under all possible scenarios without any assumption on their probabilities. The developed method is applied to a case study of long-term MSW management planning under uncertainty. Multiple scenarios associated with different cost and risk levels are analyzed. Reasonable solutions are generated, demonstrating complex tradeoffs among system cost, regret level, and system-failure risk. The method can also facilitate examination of the difference between the cost incurred with identified strategy and the least cost under an ideal condition. The results can help determine desired plans and policies for waste management under a variety of uncertainties.     

Modeling Municipal Solid Waste Management System under Uncertainty

Abstract

In this study, a dynamic inexact waste management (DIWM) model is developed for identifying optimal waste-flow-allocation and facility-capacity-expansion strategies under uncertainty and is based on an inexact scenario-based probabilistic programming (ISPP) approach. The DIWM model can handle uncertainties presented as interval values and probability distributions, and it can support assessing the risk of violating system constraints. Several violation levels for facility-capacity and waste-diversion constraints are examined. Solutions associated with different risks of constraint violation were generated. The modeling results are valuable for supporting the planning of the study city’s municipal solid waste (MSW) management practices, the long-term capacity expansion for waste management system, and the identification of desired policies regarding waste diversion. Sensitivity analyses are also undertaken to demonstrate that the violations of different constraints have varied effects on the planning of waste-flow allocation, facility expansion, and waste management cost.     

Remedial Strategies for Municipal Solid Waste Management in China

ABSTRACT

The purpose of this investigation is to evaluate the current status and to identify the problems of municipal solid waste (MSW) management in China to determine appropriate remedial strategies. This is the second of two papers proposed on this topic. Major problems or difficulties identified in MSW management in China include MSW land, air, and water pollution, commingled collection, poor administration, shortage of funds, lack of facilities, and problems of training and public awareness.

In order to solve these problems and to improve MSW management in China, remedial strategies in three areas are recommended: institutional reform, technology development, and legislation and administrative improvement. The primary principle involved in institutional reform is unifying legislative responsibilities into one body and developing a market mechanism for handling MSW. Composting, landfills, and incineration should be equally developed in accordance with China's needs. The feasibility of developing technology to handle MSW in China is discussed. Also recommended is the establishment of sound regulatory systems, including a service fee system, a source separation system, and a training program. China is presently undergoing economic and institutional reform at the national and local levels. Results of this study will provide useful information on MSW management in China.     

Municipal Solid Waste Characteristics and Management in China

ABSTRACT

The purpose of this investigation is to evaluate the current status and identify the problems of municipal solid waste (MSW) management in China in order to determine appropriate remedial strategies. This is the first of two papers, discussing primarily the general characteristics of MSW and its management in China. The second paper focuses on specific remedial strategies. MSW generation in China has increased rapidly in the past 20 years from 31.3 million tons in 1980 to 113.0 million tons in 1998. The annual rate of increase is 3–10%. The average generation per capita is 1.0 kg/day (0.38 t/year). Nearly one-half of the waste generated is dumped in the suburbs, where the accumulated quantity has reached 6 billion tons, which has caused heavy environmental pollution. This paper provides information on MSW management in China, such as MSW generation and its physical, chemical, and biological properties. Low calorific value and high moisture content characterize China's municipal waste. Other issues related to MSW management in China are also discussed, including the factors that influence MSW generation quantity and quality, MSW collection, transfer and transport, treatment and disposal, material recovery, legislation, enforcement, and administration.     

Factors influencing regional municipal solid waste management strategies

Although regionalization policies have been proven as good strategies for municipal solid waste (MSW) management in previous studies, the optimal allocation of the waste stream is significantly affected by several influential factors, thus further investigation of the impacts of these factors on regional MSW management strategies is necessary. This study demonstrated the impacts of waste-to-electricity transformation coefficient (WETC) of incinerators and the fluctuation of unit tipping fees on the regional MSW flow/allocation of the Taipei metropolitan area from practical and economic perspectives. Real-world data and linear programming were used to obtain the least-cost alternatives under different scenarios. Analytical results indicated some treatment facilities had geographic superiority and their priorities changed when actual WETCs of incinerators were considered. Treatment facilities located at weighted centers were identified. The allocation of MSW among incinerators and landfills is affected by fluctuation of unit tipping fees within a certain range. Treatment facilities sensitive to the changes in unit tipping fees were also identified. Regression equations were also established that can estimate the cost items of MSW management scenarios with different unit tipping fees. The results of this study are very useful for daily basis regulation of MSW administration.     

Compromising economic cost and air pollutant emissions of municipal solid waste management strategies by fuzzy multiobjective optimization model

Municipal solid waste management (MSWM) is an important environmental challenge and subject in urban planning. A sustainable MSWM strategy should consider not only economic efficiency but also life-cycle assessment of environmental impact. This study employs the fuzzy multiobjective linear programming (FMOLP) technique to find the optimal compromise between economic optimization and pollutant emission reduction for the MSWM strategy. Taichung City in Taiwan is evaluated as a case study. The results indicate that the optimal compromise MSWM strategy can reduce significant amounts of pollutant emissions and still achieve positive net profits. Minimization of the sulfur oxide (SO_x) and nitrogen oxide (NO_x) emissions are the two major priorities in achieving this optimal compromise strategy when recyclables recovery rate is lower; however, minimization of the carbon monoxide (CO) and particulate matter (PM) emissions become priority factors when recovery rate is higher.

Implications: This paper applied the multiobjective optimization model to find the optimal compromise municipal solid waste management (MSWM) strategy, which minimizes both life-cycle operating cost and air pollutant emissions, and also to analyze the correlation between recyclables recovery rates and optimal compromise strategies. It is different from past studies, which only consider economic optimization or environmental impacts of the MSWM system. The result shows that optimal compromise MSWM strategy can achieve a net profit and reduce air pollution emission. In addition, scenario investigation of recyclables recovery rates indicates that resource recycling is beneficial for both economic optimization and air pollutant emission minimization.     

A Life-Cycle Inventory Model of Municipal Solid Waste Combustion

ABSTRACT

Evaluation of alternate strategies for municipal solid waste (MSW) management requires models to calculate environmental emissions as a function of both waste quantity and composition. A methodology to calculate waste component-specific emissions associated with MSW combustion is presented here. The methodology considers emissions at a combustion facility as well as those avoided at an electrical energy facility because of energy recovered from waste combustion. Emission factors, in units of kg pollutant per metric ton MSW entering the combustion facility, are calculated for CO₂-biomass, CO₂-fossil, SO_x , HCl, NO_x , dioxins/furans, PM, CO, and 11 metals. Water emissions associated with electrical energy offsets are also considered. Reductions in environmental emissions for a 500-metric-ton-per-day combustion facility that recovers energy are calculated.     

Methane Emissions from Domestic Waste Management Facilities in Jordan—Applicability of IPCC Methodology

ABSTRACT

In this paper, methane emissions from municipal wastewater treatment plants and municipal solid waste (MSW) landfills in Jordan for 1994 have been estimated using the methodology developed by the Intergovernmental Panel on Climate Change (IPCC). For this purpose, the 14 domestic wastewater treatment plants in the country were surveyed. Generation rates and characterization of MSW components as well as dumping and landfilling practices were surveyed in order to estimate 1994 CH₄ emissions from these sites. Locally available waste statistics were used in cases where those of the IPCC guidelines were not representative of Jordan's statistics.

Methane emissions from domestic wastewater in Jordan were estimated at 4.66 gigagrams (Gg). Total 1994 CH₄ emissions from MSW management facilities in Jordan are estimated at 371.76 Gg—351.12 Gg (94.45%) from sanitary landfills, 19.83 Gg (5.33%) from MSW open dumps, and 0.81 Gg (0.22%) from raw sewage-water dumping ponds. Uncertainties associated with these estimations are presented.     

城市固体废物优化管理模型及管理成本影响因素研究

采用不确定性多目标动态优化模型,以优化环境和经济为目标,对中国佛山市固体废物管理进行规划.结果表明,该模型能大幅度降低固体废物管理与处理成本,节省财政支出.研究得出影响固体废物总处理费用的3个重要影响因素为产生量、回收量、处理容量.针对以上3个因素深入分析比较,提出了广义和狭义的综合处理技术,这是经济、环保、可行的技术策略:首先,将广义综合处理应用到实际中,采用分类回收、压缩收集、优化模型对废物进行合理配置,尽量降低经济成本和环境影响;其次,从狭义角度出发,采用多种技术组合,达到处理率高、资源化程度高、环境影响小的目的.     

Long short-term memory neural network and improved particle swarm optimization–based modeling and scenario analysis for municipal solid waste generation in Shanghai,China

Accurate estimations of municipal solid waste (MSW) generation are vital to effective MSW management systems. While various single-point estimation approaches have been developed, the non-linearity and multiple site-specific influencing factors associated with MSW management systems make it challenging to forecast MSW generation quantities precisely. To address these concerns, this study developed a two-stage modeling and scenario analysis procedure for MSW generation and taking Shanghai as a test case demonstrated its viability. In the first stage, nine influencing factors were selected, and a hybrid novel forecasting model based on a long short-term memory neural network and an improved particle swarm optimization (IPSO-LSTM) was proposed for the forecasting of the MSW generation quantities, after which actual Shanghai data from 1980 to 2019 were used to test the performance. In the second stage, the future influencing variable values in different scenarios were predicted using an improved grey model, after which the predicted Shanghai MSW generation quantities from 2025 to 2035 were evaluated under various scenarios. It was found that (1) the proposed IPSO-LSTM had higher accuracy than the benchmark models; (2) the MSW generation quantities are expected to respectively increase to 9.971, 9.684, and 9.090 million tons by 2025 and 11.402, 11.285, and 10.240 by 2035 under the low, benchmark, and high scenarios; and (3) the MSW generation differences between the high and medium scenarios were decreasing.

     

Municipal solid waste management planning for Xiamen City,China: a stochastic fractional inventory-theory-based approach

In this study, a stochastic fractional inventory-theory-based waste management planning (SFIWP) model was developed and applied for supporting long-term planning of the municipal solid waste (MSW) management in Xiamen City, the special economic zone of Fujian Province, China. In the SFIWP model, the techniques of inventory model, stochastic linear fractional programming, and mixed-integer linear programming were integrated in a framework. Issues of waste inventory in MSW management system were solved, and the system efficiency was maximized through considering maximum net-diverted wastes under various constraint-violation risks. Decision alternatives for waste allocation and capacity expansion were also provided for MSW management planning in Xiamen. The obtained results showed that about 4.24 × 10⁶ t of waste would be diverted from landfills when p _i is 0.01, which accounted for 93% of waste in Xiamen City, and the waste diversion per unit of cost would be 26.327 × 10³ t per $10⁶. The capacities of MSW management facilities including incinerators, composting facility, and landfills would be expanded due to increasing waste generation rate.     

Subregion districting analysis for municipal solid waste collection privatization

Privatization of municipal solid waste (MSW) collection can improve service quality and reduce cost. To reduce the risk of an incapable company serving an entire collection area and to establish a competitive market, a large collection area should be divided into two or more subregions, with each subregion served by a different company. The MSW subregion districting is generally done manually, based on the planner's intuition. Major drawbacks of a manual approach include the creation of a districting plan with poor road network integrity for which it is difficult to design an efficient collection route. The other drawbacks are difficulty in finding the optimal districting plan and the lack of a way to consistently measure the differences among subregions to avoid unfair competition. To determine an MSW collection subregion districting plan, this study presents a mixed-integer optimization model that incorporates factors such as compactness, road network integrity, collection cost, and regional proximity. Two cases are presented to demonstrate the applicability of the proposed model. In both cases, districting plans with good road network integrity and regional proximity have been generated successfully.     

Analysis of Long-Term Settlement of Municipal Solid Waste Landfills as Determined by Various Settlement Estimation Methods

Abstract

In this study, several existing municipal solid waste (MSW) settlement estimation methods are reviewed and applied to analyze the settlement data of nine MSW land-fills. Because a biodegradation-related settlement contributes differently to a long-term total settlement depending on the age of landfills, the actual MSW landfill sites are classified into three groups to specifically address the validity of each method in its prediction of a long-term settlement for each age category. Results demonstrate that there are considerable decreases in predicted settlement potentials as fill age increases. Comparisons indicate that the individual estimation methods display a considerable variation in predicting settlements in the fresh MSW landfills. On the other hand, for the old refuse landfills, all of the estimation methods, except the extended soil model, predict low settlement potentials.     

An economic evaluation and assessment of environmental impact of the municipal solid waste management system for Taichung City in Taiwan

Municipal solid waste management (MSWM) is an important environmental challenge and subject in urban planning. For sustainable MSWM strategies, the critical management factors to be considered include not only economic efficiency of MSW treatment but also life-cycle assessment of the environmental impact. This paper employed linear programming technique to establish optimal MSWM strategies considering economic efficiency and the air pollutant emissions during the life cycle of a MSWM system, and investigated the correlations between the economical optimization and pollutant emissions. A case study based on real-world MSW operating parameters in Taichung City is also presented. The results showed that the costs, benefits, streams of MSW, and throughputs of incinerators and landfills will be affected if pollution emission reductions are implemented in the MSWM strategies. In addition, the quantity of particulate matter is the best pollutant indicator for the MSWM system performance of emission reduction. In particular this model will assist the decision maker in drawing up a friendly MSWM strategy for Taichung City in Taiwan. Implications: Recently, life-cycle assessments of municipal solid waste management (MSWM) strategies have been given more considerations. However, what seems to be lacking is the consideration of economic factors and environmental impacts simultaneously. This work analyzed real-world data to establish optimal MSWM strategies considering economic efficiency and the air pollutant emissions during the life cycle of the MSWM system. The results indicated that the consideration of environmental impacts will affect the costs, benefits, streams of MSW, and throughputs of incinerators and landfills. This work is relevant to public discussion and may establish useful guidelines for the MSWM policies.     

81st APCA Annual Meeting & Exhibition

Abstract

This study introduces a two-stage interval-stochastic programming (TISP) model for the planning of solid-waste management systems under uncertainty. The model is derived by incorporating the concept of two-stage stochastic programming within an interval-parameter optimization framework. The approach has the advantage that policy determined by the authorities, and uncertain information expressed as intervals and probability distributions, can be effectively communicated into the optimization processes and resulting solutions. In the modeling formulation, penalties are imposed when policies expressed as allowable waste-loading levels are violated. In its solution algorithm, the TISP model is converted into two deterministic submodels, which correspond to the lower and upper bounds for the desired objective-function value. Interval solutions, which are stable in the given decision space with associated levels of system-failure risk, can then be obtained by solving the two submodels sequentially. Two special characteristics of the proposed approach make it unique compared with other optimization techniques that deal with uncertainties. First, the TISP model provides a linkage to prede?ned policies determined by authorities that have to be respected when a modeling effort is undertaken; second, it furnishes the reflection of uncertainties presented as both probabilities and intervals. The developed model is applied to a hypothetical case study of regional solid-waste management. The results indicate that reasonable solutions have been generated. They provide desired waste-flow patterns with minimized system costs and maximized system feasibility. The solutions present as stable interval solutions with different risk levels in violating the waste-loading criterion and can be used for generating decision alternatives.