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allied
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Page 29
7
th
International Conference on
Recycling and Waste Management
October 03-04, 2019 | Melbourne, Australia
Journal of Environmental Waste Management and Recycling | Volume: 02
Data-Driven sustainability for energy and materials recovery
Masato R Nakamura
The City University of New York (CUNY), USA
D
ata-driven sustainability, a field that attempts to
optimize environmental resources and reduce
environmental impacts using methodologies from data
science and environmental engineering, has been applied
for analyzing energy and materials recovery (recycling)
processes. These processes mainly involve materials
collection, physical separation, volume reduction
(compaction), and size reduction in Materials Recovery
Facilities (MRFs), which are also necessary for Energy
Recovery Facilities (ERFs or waste-to-energy facilities)
as pretreatment processing prior to combustion and/or
other chemical conversion processes. a decision-making
algorithm has been developed for this study and allocates
resources based on real-time data collected from sensors
in various locations such as garbage containers, trucks as
well as, the equipment in MRFs and ERFs. The result of
this numerical analysis shows the optimized operation
can reduce maximum 43% of time used in a separation
process including eddy diffusion, cyclone (air), magnetic
and electrostatic system, and scrubbers, 21% of cost
in a compression (volume reduction) process used in
compactors that applies forces or pressure to the solid
waste materials to achieve volume reduction and density
increase to aid in storage and carriage, and 32% of energy
use for size reduction processes in the form of crushing,
shredding, grinding, and milling.
e:
mnakamura@citytech.cuny.edu