Searching quality data for municipal solid waste planning |
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| Authors: | Moe Chowdhury |
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| Institution: | 1. College of Environmental Science and Engineering, Yangzhou University, Yangzhou 225127, China;2. College of Environmental Science and Engineering, Nanjing University, Nanjing 210023, China;3. College of Civil Science and Engineering, Yangzhou University, Yangzhou 225127, China;4. College of Environmental Science and Engineering, Suzhou University of Science and Technology, Suzhou 215011, China;5. Suzhou Environmental Sanitation Administration Agency, Suzhou 215000, China;1. Department of Water and Environmental Sciences and Techniques, Environmental Engineering Group, School of Civil Engineering, University of Cantabria, Santander Campus, Avda. de los Castros s/n, 39005 Cantabria, Spain;2. Department of Applied Mathematics and Computer Science, Information Technologies Group, School of Industrial Engineering and Telecommunications, University of Cantabria, Santander Campus, Avda. de los Castros s/n, 39005 Cantabria, Spain;1. Department of Shipping and Transportation Management, National Taiwan Ocean University, Taiwan;2. Institute of Innovation and Circular Economy, Asia University, Taiwan;3. Department of Medical Research, China Medical University Hospital, Taiwan;4. School of Business, Dalian University of Technology, China;2. Centre for Sustainable Waste Management, School of Science and Technology, University of Northampton, Northampton, UK |
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| Abstract: | Effective waste reduction and recycling is predicated upon credible data on refuse generation and disposal. Despite improvements in the quality of data for municipal solid wastes (MSW) disposal, dependable generation and recycling statistics to support planning, regulation and administration are lacking. The available aggregates on national waste production from two sources do not conform to each other and fail to serve the requirements of local solid waste planning. As recycling estimates will be difficult to discern, the collection of generation data based on weighing waste samples at generator sites has been portrayed as the key for developing sustainable local databases. The coefficients developed from the databases for the various categories of residential, commercial, industrial and institutional wastes can be used as variables for waste generation models. |
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