scholarly journals Predictive Analysis of Municipal Solid Waste Generation Using an Optimized Neural Network Model

Processes ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 2045
Author(s):  
Nehal Elshaboury ◽  
Eslam Mohammed Abdelkader ◽  
Ghasan Alfalah ◽  
Abobakr Al-Sakkaf
Keyword(s):  
Neural Network ◽  
Waste Management ◽  
Municipal Solid Waste ◽  
Solid Waste ◽  
Mean Squared Error ◽  
Pearson Correlation ◽  
Mean Bias Error ◽  
Bias Error ◽  
P Value ◽  
Waste Generation

Developing successful municipal waste management planning strategies is crucial for implementing sustainable development. The research proposed the application of an optimized artificial neural network (ANN) to forecast quantities of waste in Poland. The neural network coupled with particle swarm optimization (PSO) algorithm is compared to the conventional neural network using five assessment metrics. The metrics are coefficient of efficiency (CE), Pearson correlation coefficient (R), Willmott’s index of agreement (WI), root mean squared error (RMSE), and mean bias error (MBE). Selected explanatory factors are incorporated in the developed models to reflect the influence of economic, demographic, and social aspects on the rate of waste generation. These factors are population, employment to population ratio, revenue per capita, number of entities by type of business activity, and number of entities enlisted in REGON per 10,000 population. According to the findings, the ANN–PSO model (CE = 0.92, R = 0.96, WI = 0.98, RMSE = 11,342.74, and MBE = 6548.55) significantly outperforms the traditional ANN model (CE = 0.11, R = 0.68, WI = 0.78, RMSE = 38,571.68, and MBE = 30,652.04). The significant level of the reported outputs is evaluated using the Wilcoxon–Mann–Whitney U-test, with a significance level of 0.05. The p-values of the pairings (ANN, observed) and (ANN, ANN–PSO) are all less than 0.05, suggesting that the models are statistically different. On the other hand, the P-value of (ANN–PSO, observed) is more than 0.05, suggesting that the difference between the models is statistically insignificant. Therefore, the proposed ANN–PSO model proves its efficiency at estimating municipal solid waste quantities and may be regarded as a cost-efficient method of developing integrated waste management systems.

Municipal solid waste generation, composition, and management: the global scenario

2020 ◽  
Vol 16 (6) ◽  
pp. 917-948
Author(s):  
Kapil Dev Sharma ◽  
Siddharth Jain
Keyword(s):  
Waste Management ◽  
Municipal Solid Waste ◽  
Solid Waste ◽  
Solid Waste Management ◽  
Management Strategies ◽  
Technology Selection ◽  
Waste Generation ◽  
Content Type ◽  
The World ◽  
Solid Waste Generation

Purpose Due to the increasing population and prosperity, the generation rate of municipal solid waste (MSW) has increased significantly, resulting in serious problems on public health and the environment. Every single person in the world is affected by the municipal solid waste management (MSWM) issue. MSWM is reaching a critical level in almost all areas of the world and seeking the development of MSW strategies for a sustainable environment. This paper aims to present the existing global status of MSW generation, composition, management and related problems. Design/methodology/approach A total of 59 developed and developing countries have been grouped based on their gross national income to compare the status of various MSWM technologies among them. A total of 19 selection criteria have been discussed to select appropriate MSWM technology(s) for a city/town, which affects their applicability, operational suitability and performance. All risks and challenges arising during the life cycle of the waste to energy (WtE) project have also been discussed. This paper also gives a comparative overview of different globally accepted MSWM technologies and the present market growth of all WtE technologies. Findings It was found that most developed countries have effectively implemented the solid waste management (SWM) hierarchy and are now focusing heavily on reducing, reusing and recycling of MSW. On the other hand, SWM has become very serious in low-income and low-middle-income countries because most of the MSW openly dumps and most countries are dependent on inadequate waste infrastructure and the informal sector. There are also some other major challenges related to effective waste policies, availability of funds, appropriate technology selection and adequacy of trained people. This study clears the picture of MSW generation, composition, management strategies and policies at the worldwide context. This manuscript could be valuable for all nations around the world where effective MSWM has not yet been implemented. Originality/value This study clears the picture of solid waste generation, composition, management strategies and policies at the worldwide context. This manuscript could be valuable for all nations around the world where effective MSWM has not yet been implemented. In this study, no data was generated. All supporting data were obtained from previously published papers in journals, the outcomes of the international conferences and published reports by government organizations.

scholarly journals Optimization of the Solid Waste Management System in Saint-Petersburg Based on the Morphological Composition Study

2018 ◽  
Vol 193 ◽  
pp. 02037 ◽  
Author(s):  
Alexander Chusov ◽  
Ekaterina Neguliaeva ◽  
Mikhail Romanov
Keyword(s):  
Waste Management ◽  
Municipal Solid Waste ◽  
Solid Waste ◽  
Management System ◽  
Solid Waste Management ◽  
Waste Generation ◽  
Saint Petersburg ◽  
Morphological Composition ◽  
Composition Study ◽  
Solid Waste Management System

The article presents the results of research (2013-2017) on the seasonal morphological composition of Municipal Solid Waste and forecasting the waste generation volume for Saint Petersburg. The authors propose ways to improve the system of solid waste management in St. Petersburg based on these researches.

scholarly journals Life-cycle assessment of the municipal solid waste management system in Hangzhou, China (EASEWASTE)

2009 ◽  
Vol 27 (4) ◽  
pp. 399-406 ◽  
Author(s):  
Yan Zhao ◽  
Hong-Tao Wang ◽  
Wen-Jing Lu ◽  
Anders Damgaard ◽  
Thomas H. Christensen
Keyword(s):  
Life Cycle ◽  
Waste Management ◽  
Municipal Solid Waste ◽  
Solid Waste ◽  
Energy Production ◽  
Solid Waste Management ◽  
Municipal Solid Waste Management ◽  
Waste Generation ◽  
Plastic Bags ◽  
Solid Waste Management System

With the purpose of assessing the environmental impacts and benefits of the current municipal solid waste management system and two modified systems, EASEWASTE, a life-cycle-based model, was used to evaluate the waste system of Hangzhou city in China. An integrated model was established, including waste generation, collection, transportation, treatment, disposal and accompanying external processes. The results showed that CH4 released from landfilling was the primary pollutant contributing to global warming, and HCl and NH3 from incineration contributed most to acidification. Material recycling and incineration with energy recovery were important because of the induced savings in material production based on virgin materials and in energy production based on coal combustion. A modified system in which waste is transported to the nearest incinerators would be relatively better than the current system, mainly due to the decrease of pollution from landfilled waste and the increase in energy production from waste avoiding energy production by traditional power plants. A ban on free plastic bags for shopping was shown to reduce most environmental impacts due to saved oil resources and other materials used in producing the plastic bags. Sensitivity analysis confirmed the robustness of the results. LCA methodology and a model like EASEWASTE are very suitable for evaluating the overall environmental consequences, and can be used for decision support and strategic planning in developing countries such as China where pollution control has become increasingly important with the rapid increase of waste generation as well as the increasing public awareness of environmental protection.

scholarly journals Prediction of Municipal Waste Generation in Poland Using Neural Network Modeling

2020 ◽  
Vol 12 (23) ◽  
pp. 10088
Author(s):  
Monika Kulisz ◽  
Justyna Kujawska
Keyword(s):  
Neural Network ◽  
Waste Management ◽  
Mean Squared Error ◽  
Cost Effective ◽  
Municipal Waste ◽  
Neural Network Modeling ◽  
Waste Generation ◽  
Crucial Component ◽  
Ann Models ◽  
The Impact

Planning is a crucial component of short- and long-term municipal waste management. Establishing the relationships between the factors that determine the amount of waste generated by municipalities and forecasting the waste management needs plays a fundamental role in the development of effective planning strategies and implementation of sustainable development. Artificial Neural Network employed for verifying the forecasts pertaining to the amount of rainfall in Poland were presented in the studies. The proposed models included selected explanatory indices in order to reflect the impact of social, demographic and economic factors on the amount of generated waste. Mean squared error (MSE) and regression value (R) are used as indices of efficiency of the developed models. The ANN models exhibited high accuracy of forecasts at high R values (R = 0.914, R = 0.989) and low MSE values. Derived from the socioeconomic data for 2003–2019, the model predicts that the future waste generation in 2024 will increase by 2%. The results indicate that the employed ANN models are effective in predicting the amount of waste and can be considered a cost-effective approach to planning integrated waste management systems.

scholarly journals The Spatiotemporal Variability of Temperature and Precipitation Over the Upper Indus Basin: An Evaluation of 15 Year WRF Simulations

2020 ◽  
Vol 10 (5) ◽  
pp. 1765 ◽  
Author(s):  
Ghulam Hussain Dars ◽  
Courtenay Strong ◽  
Adam K. Kochanski ◽  
Kamran Ansari ◽  
Syed Hammad Ali
Keyword(s):  
Mean Squared Error ◽  
Pearson Correlation ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Indus Basin ◽  
Spatiotemporal Variability ◽  
Mean Bias Error ◽  
Bias Error ◽  
Upper Indus Basin ◽  
Precipitation And Temperature

Investigating the trends in the major climatic variables over the Upper Indus Basin (UIB) region is difficult for many reasons, including highly complex terrain with heterogeneous spatial precipitation patterns and a scarcity of gauge stations. The Weather Research and Forecasting (WRF) model was applied to simulate the spatiotemporal variability of precipitation and temperature over the Indus Basin from 2000 through 2015 with boundary conditions derived from the Climate Forecast System Reanalysis (CFSR) data. The WRF model was configured with three nested domains (d01–d03) with horizontal resolutions increasing inward from 36 km to 12 km to 4 km horizontal resolution, respectively. These simulations were a continuous run with a spin-up year (i.e., 2000) to equilibrate the soil moisture, snow cover, and temperature at the beginning of the simulation. The simulations were then compared with TRMM and station data for the same time period using root mean squared error (RMSE), percentage bias (PBIAS), mean bias error (MBE), and the Pearson correlation coefficient. The results showed that the precipitation and temperature simulations were largely improved from d01 to d03. However, WRF tended to overestimate precipitation and underestimate temperature in all domains. This study presents high-resolution climatological datasets, which could be useful for the study of climate change and hydrological processes in this data-sparse region.

Status of municipal solid waste generation and disposal in Nigeria

2015 ◽  
Vol 26 (1) ◽  
pp. 53-71 ◽  
Author(s):  
Charles Chidozie Nnaji
Keyword(s):  
Heavy Metals ◽  
Waste Management ◽  
Municipal Solid Waste ◽  
Solid Waste ◽  
Solid Waste Management ◽  
Municipal Solid Waste Management ◽  
Waste Generation ◽  
Content Type ◽  
Municipal Waste Management ◽  
Solid Waste Generation

Purpose – This paper examined the current status of municipal solid waste management across Nigeria. The core aspects covered are generation, characterization, collection, scavenging, open dumping, disposal and environmental implications of poor solid waste management. The purpose of this paper is to present a comprehensive overview of the current state of municipal solid waste management in Nigeria. Design/methodology/approach – This study was executed by a combination of an extensive literature search and field study. Solid waste generation rates for 31 Nigerian cities were obtained from literature. In addition, characteristics of municipal solid waste from 26 Nigerian cities were also obtained from literature. Other aspects such as characterization of solid waste obtained from final dumpsite and heavy metals accumulation in solid waste dumpsites were undertaken first hand. Findings – Solid waste generation rate was found to vary from 0.13 kg/capita/day in Ogbomosho to 0.71 kg/capita/day in Ado-Ekiti. Factors affecting solid waste generation rates were identified. Typically, food waste was found to constitute close to 50 percent of overall municipal solid waste in Nigerian cities. This study shows that the rate of generation of plastics, water proof materials and diapers has assumed an upward trend. Due to the dysfunctional state of many municipal waste management authorities, many cities have been overrun by open dumps. For instance, more than 50 percent of residents of Maiduguri in northern Nigeria and Ughelli in southern Nigeria dispose of their waste in open dumps. Indiscriminate disposal of waste has also resulted in the preponderance of toxic heavy metals in agricultural soils and consequent bioaccumulation in plants as well as groundwater contamination. Research limitations/implications – The main limitation of this research is municipal waste management authorities do not have relevant data. Hence, there was heavy reliance on published materials. The status of waste management in Nigeria is very deplorable and therefore poses serious threats to public and environmental health. There is urgent need for both government and individuals to adopt holistic and sustainable waste management strategies in order to safeguard public/environmental health. Practical implications – Findings from this paper can form a veritable resource for the formulation and implementation of sustainable municipal solid waste management framework and strategies in Nigeria. Originality/value – While most studies on municipal solid waste management in Nigeria are focussed on selected cities of interest, this particular study cuts across most cities of Nigeria in order to present a broader and holistic view of municipal solid waste management in Nigeria. The paper has also unraveled core municipal solid waste management challenges facing Nigerian cities.

scholarly journals Characterisation of Municipal Solid Waste for Planning Sustainable Waste Management in Kumba Municipality – South Western Cameroon

2016 ◽  
Vol 9 (1) ◽  
pp. 19-27 ◽  
Author(s):  
E.B. Tambe ◽  
G.C. Ayongwa ◽  
N.M. Ngwabie ◽  
G.T. Forbid
Keyword(s):  
Waste Management ◽  
Municipal Solid Waste ◽  
Solid Waste ◽  
Low Income ◽  
Solid Waste Management ◽  
Waste Generation ◽  
Residential Areas ◽  
Systematic Random Sampling ◽  
West Region ◽  
Per Capita

Municipal solid waste (MSW) characterisation across socioeconomic residents is necessary for planning sustainable solid waste management. In view of planning for Kumba municipality in the South West Region of Cameroon, three types of socioeconomic residents classified as low, medium and high income residential areas were randomly sampled. In each residential area, 32 households were sampled following systematic random sampling. Over a period of eight weeks within three periods characterised with varying activities, statistically designed number of samples for waste composition were hand sorted and weighed at source of generation. The study revealed that the per capita generation of putrescible and miscellaneous wastes (predominantly sand, ash and dust) were statistically different (p < 0.05) across residents and were inversely related to income while the generation of plastics, metals, papers, glass except textiles were statistically different across residents and were positively related to income. Putrescible waste was the most predominant waste category constituting more than 75% across residents. No significant differences were observed for per capita waste generation across residents during the entire period of study and within residents during the different periods over which the waste categories were measured. However, within the different periods, waste generation was significantly different across residents with more waste being produced in low income residents. The waste density was found to decrease with increasing income. The observed variation of waste generation and composition has implications for collection frequency, equipment needs, composting and digestion of the biodegradable for biogas generation to sustain the solid waste management sector.

Data uncertainties in material flow analysis: Municipal solid waste management system in Maputo City, Mozambique

2016 ◽  
Vol 35 (1) ◽  
pp. 120-125 ◽  
Author(s):  
Leticia Sarmento dos Muchangos ◽  
Akihiro Tokai ◽  
Atsuko Hanashima
Keyword(s):  
Waste Management ◽  
Municipal Solid Waste ◽  
Solid Waste ◽  
Material Flow ◽  
Solid Waste Management ◽  
Flow Analysis ◽  
Material Flow Analysis ◽  
Municipal Solid Waste Management ◽  
Waste Generation ◽  
Maputo City

Material flow analysis can effectively trace and quantify the flows and stocks of materials such as solid wastes in urban environments. However, the integrity of material flow analysis results is compromised by data uncertainties, an occurrence that is particularly acute in low-and-middle-income study contexts. This article investigates the uncertainties in the input data and their effects in a material flow analysis study of municipal solid waste management in Maputo City, the capital of Mozambique. The analysis is based on data collected in 2007 and 2014. Initially, the uncertainties and their ranges were identified by the data classification model of Hedbrant and Sörme, followed by the application of sensitivity analysis. The average lower and upper bounds were 29% and 71%, respectively, in 2007, increasing to 41% and 96%, respectively, in 2014. This indicates higher data quality in 2007 than in 2014. Results also show that not only data are partially missing from the established flows such as waste generation to final disposal, but also that they are limited and inconsistent in emerging flows and processes such as waste generation to material recovery (hence the wider variation in the 2014 parameters). The sensitivity analysis further clarified the most influencing parameter and the degree of influence of each parameter on the waste flows and the interrelations among the parameters. The findings highlight the need for an integrated municipal solid waste management approach to avoid transferring or worsening the negative impacts among the parameters and flows.

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