Developing a GIS-based model to quantify spatiotemporal pattern of home appliances and e-waste generation—A case study in Xiamen, China

2022 ◽  
Vol 137 ◽  
pp. 150-157
Author(s):  
Yupeng Liu ◽  
Lulu Song ◽  
Wanjun Wang ◽  
Xiaomei Jian ◽  
Wei-Qiang Chen
Keyword(s):  
Spatiotemporal Pattern ◽  
Waste Generation ◽  
Home Appliances

Solid Waste Generation of Household in Azad Kashmir: Case Study of Mirpur

2018 ◽  
Author(s):  
Waqas mname Ali ◽  
Rashid mname Khalil ◽  
Shujahat mname Ali
Keyword(s):  
Solid Waste ◽  
Waste Generation ◽  
Solid Waste Generation ◽  
Azad Kashmir

scholarly journals Identification of inference fallacies in solid waste generation estimations of developing countries. A case-study in Panama

2021 ◽  
Vol 126 ◽  
pp. 454-465
Author(s):  
Jorge M. Torrente-Velásquez ◽  
Maddalena Ripa ◽  
Rosaria Chifari ◽  
Mario Giampietro
Keyword(s):  
Developing Countries ◽  
Solid Waste ◽  
Waste Generation ◽  
Solid Waste Generation

Development of machine learning - based models to forecast solid waste generation in residential areas: A case study from Vietnam

2021 ◽  
Vol 167 ◽  
pp. 105381
Author(s):  
X. Cuong Nguyen ◽  
T. Thanh Huyen Nguyen ◽  
D. Duong La ◽  
Gopalakrishnan Kumar ◽  
Eldon R. Rene ◽  
...  
Keyword(s):  
Machine Learning ◽  
Solid Waste ◽  
Waste Generation ◽  
Residential Areas ◽  
Solid Waste Generation

scholarly journals Characterization and Analysis of Household Solid Waste Composition to Identify the Optimal Waste Management Method: A Case Study in Hanoi City, Vietnam

Earth ◽  
2021 ◽  
Vol 2 (4) ◽  
pp. 1046-1058
Author(s):  
Ngo Phuong ◽  
Helmut Yabar ◽  
Takeshi Mizunoya
Keyword(s):  
Solid Waste ◽  
Rural Areas ◽  
Waste Generation ◽  
Household Solid Waste ◽  
Physical Composition ◽  
Challenges And Opportunities ◽  
Solid Waste Generation ◽  
Management Method ◽  
Lifestyle Patterns

A survey on household solid waste generation and physical composition was conducted in Hanoi City, the capital of Vietnam. The study sampled 110 households in specific areas with different population density and household scale. Household solid waste was classified into 13 main categories and 25 sub-categories. The results showed that average generation rate of waste in Hanoi City is 0.63 kg per person per day with a slightly higher rate in rural areas than urban ones. The largest proportion was food and garden waste at 78.9% followed by plastic and paper. Plastic waste was segregated into plastic and nylon, and nylon was double that of plastics in household solid waste. Compared to previous studies, this study found a higher portion of organic matter in the waste characterization that could be attributed to the changes in lifestyle patterns associated with COVID-19. This situation provides challenges and opportunities for introducing biomass technology to recover energy.

Time-series-based hybrid mathematical modelling method adapted to forecast automotive and medical waste generation: Case study of Lithuania

2018 ◽  
Vol 36 (5) ◽  
pp. 454-462 ◽  
Author(s):  
Aistė Karpušenkaitė ◽  
Tomas Ruzgas ◽  
Gintaras Denafas
Keyword(s):  
Time Series ◽  
Mathematical Modelling ◽  
Error Rate ◽  
Medical Waste ◽  
Waste Generation ◽  
Prediction Horizon ◽  
Modelling Method ◽  
Forecasting Method ◽  
Hybrid Forecasting

The aim of the study was to create a hybrid forecasting method that could produce higher accuracy forecasts than previously used ‘pure’ time series methods. Mentioned methods were already tested with total automotive waste, hazardous automotive waste, and total medical waste generation, but demonstrated at least a 6% error rate in different cases and efforts were made to decrease it even more. Newly developed hybrid models used a random start generation method to incorporate different time-series advantages and it helped to increase the accuracy of forecasts by 3%–4% in hazardous automotive waste and total medical waste generation cases; the new model did not increase the accuracy of total automotive waste generation forecasts. Developed models’ abilities to forecast short- and mid-term forecasts were tested using prediction horizon.

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