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Office of Sustainability Graduate Capstones
2019-08
Optimization of Waste Collection System at
University of Calgary
Farahbakhsh, Samira
http://hdl.handle.net/1880/111560
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1
UNIVERSITY OF CALGARY
Optimization of Waste Collection System at University of Calgary
by
Samira Farahbakhsh
A RESEARCH PROJECT SUBMITTED
IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE
DEGREE OF MASTER OF SCIENCE
GRADUATE PROGRAM IN SUSTAINABLE ENERGY DEVELOPMENT
CALGARY, ALBERTA
August, 2019
© Samira Farahbakhsh 2019
ii
Abstract
This project addresses the following question: How can the existing waste collection system at the
University of Calgary be optimized to be more aligned with the sustainability concept. The University of
Calgary hosts 30,000 to 35,000 people each day. Each resident produces 0.1 tonnes of waste per year
which is equivalent to 3,000 tonnes of waste annually. This magnitude of waste requires an efficient
waste collection system. To find inefficiencies along with improvement opportunities the existing
collection system has been studied and compared with other collection systems used in other
universities. The result of the analysis is a short-term and a long-term optimization proposal. The short-
term proposal suggests a 34 percent and the long-term one leads to 24 percent cost reduction mainly
by reducing the number of waste collection truck pick-ups. In addition, both scenarios demonstrate the
environmental and social benefits, such as greenhouse gas reduction and opportunities for waste
education.
iii
Acknowledgment
This project would not have been possible without the support of Ana Pazmino at facility management
of University of Calgary. Her support through all the steps of this project was invaluable and helped me
to understand and develop thoughts and ideas. Secondly, I want to thank Irene Herremans for her
support in this degree. Her guidance, immense knowledge and support to keep me on track, made this
project happens. Also, thanks to my friend Elshan who always kept me motivated. Finally, I want to
thank my family specially my husband Amir who supported me all the way in this journey with his love,
patience and companion.
i
Table of Contents
Approval Page ................................................................................................................................... i
Abstract ............................................................................................................................................ ii
Acknowledgment ............................................................................................................................. iii
List of Figures ................................................................................................................................... iii
Chapter One: Introduction ................................................................................................................. 1
Chapter Two: Literature Review ........................................................................................................ 4
Chapter Three: Methodology............................................................................................................. 8
3.1 Phase One - Understanding the Existing Collection System ...............................................................8
3.2 Phase Two - Data Clean up and Data Verification .............................................................................8
3.3 Phase Three - Analytical Analysis of Data .........................................................................................9
3.3.1 Interviewing: .......................................................................................................................................................... 9
3.3.2 Visiting U of A site: ................................................................................................................................................. 9
3.3.3 Walking through loading dock stations: .............................................................................................................. 10
3.3.4 In Depth Desk Top Analytical ............................................................................................................................... 10
3.4 Phase Four - Integration of All Information and Final Recommendation .......................................... 10
Chapter Four: Evaluation and Analysis of Existing Waste Management System ............................... 11
4.1 Study Area .................................................................................................................................... 11
4.2 Waste Collection System ............................................................................................................... 13
4.3 Waste Streams Volume ................................................................................................................. 17
4.4 Waste collection system and cost break down ............................................................................... 18
Chapter Five: Results ....................................................................................................................... 20
5.1 Short-Term Optimization ............................................................................................................... 20
5.1.1 Economic .............................................................................................................................................................. 20
5.1.2 Environment ........................................................................................................................................................ 23
5.1.3 Social .................................................................................................................................................................... 24
ii
5.2 Long-Term Optimization ................................................................................................................ 25
5.2.1 Economic .............................................................................................................................................................. 27
5.2.2 Environment ........................................................................................................................................................ 28
5.2.3 Social .................................................................................................................................................................... 29
Chapter Six: Conclusion ................................................................................................................... 30
6.1 Recommendation .......................................................................................................................... 30
6.2 Future work .................................................................................................................................. 31
References ...................................................................................................................................... 32
Appendix A: Solid Waste Calculations for Current System ........................ Error! Bookmark not defined.
Appendix B: Mixed Recycling Calculations for Current System .................. Error! Bookmark not defined.
Appendix C: Wood Pallets Calculations for Current System ...................... Error! Bookmark not defined.
Appendix D: Metal Calculations for Current System ................................. Error! Bookmark not defined.
Appendix E: Organic Waste Calculations for Current System ................... Error! Bookmark not defined.
Appendix F: Solid Waste Calculations for Short-Term Optimization (Scenario 1) .... Error! Bookmark not
defined.
Appendix G: Mixed Recycling Calculations for Short-Term Optimization (Scenario 1) ... Error! Bookmark
not defined.
Appendix I: Organic Waste Calculations for Short-Term Optimization (Scenario 1) Error! Bookmark not
defined.
Appendix J: Calculations for Long-Term Optimization (Scenario 3) ........... Error! Bookmark not defined.
Appendix K: Summary of Current Waste Collection System, Scenario 1 and Scenario 2 Error! Bookmark
not defined.
iii
iv
List of Figures
FIGURE 1-WASTE HIERARCHY CHART ................................................................................................................... 4
FIGURE 2-METHODOLOGY FLOW CHART .............................................................................................................. 8
FIGURE 3-UNIVERSITY OF CALGARY, FOOTHILLS AND SPYHILL CAMPUSES MAP .......................................................... 12
FIGURE 4-UNIVERSITY OF CALGARY SORTED BINS ................................................................................................. 13
FIGURE 5-LOADING DOCKS AT UNIVERSITY OF CALGARY ........................................................................................ 14
FIGURE 6-FROM LEFT: 0.4 CY TOTE, 8 CY FRONT-LOADER BIN, 8 CY VERTICAL COMPACTOR, 25 CY HORIZONTAL
COMPACTOR .......................................................................................................................................... 15
FIGURE 7-FROM LEFT; FRONT-LOADER TRUCK AND ROLL-OFF TRUCK ...................................................................... 16
FIGURE 8-VOLUME OF WASTE PRODUCED IN EACH STREAM PER MONTH ................................................................. 18
FIGURE 9-COST OF WASTE TRANSPORTATION BY WM IN EACH STREAM PER MONTH ................................................. 19
FIGURE 10-NUMBER OF LIFTS VS SIZE OF CONTAINERS .......................................................................................... 21
FIGURE 11-OPTIMIZATION SCENARIO ONE ECONOMICS ........................................................................................ 22
FIGURE 12-LOCATION OF PROPOSED CENTRAL FACILITIES A & B ............................................................................. 27
FIGURE 13-SCENARIO TWO OPERATIONAL AND CAPITAL COST SUMMARIES ................................................................ 28
FIGURE 14-WASTE HIERARCHY ......................................................................................................................... 29
1
1 Chapter One: Introduction
The University of Calgary (U of C) is a Canadian post-secondary education institution and a leader in
sustainability within Canadian universities. The University hosts 30,000-35,000 people including
staff and a student community. As of 2018 sustainability report, each resident produces 0.1tonnes
of waste per year which adds up to annually 3,000tonnes. 38 percent of annual total waste diverts
to composting or recycling facilities and the remaining 62 percent transfers to landfill facilities.
According to U of C’s sustainability reports, total volume transfers to composing and recycling
facilities can be increased from 38 percent to 80 percent (University of Calgary, 2018).
Higher education institutions are continuously in the public spotlight through reporting tools such
as the Sustainability Tracking, Assessment, and Rating System (STARS), various green building
metrics (LEED, Green Globes, BOMA BEST), and public awards (e.g. the Emerald Awards). Waste
diversion systems are a very visible way for the University to demonstrate its commitment to a
sustainable future (University of Alberta Waste Diversion Working Group, 2017). As part of the
Sustainability Leadership Plan, the University of Calgary strives to be a Zero-Waste community and
plans to divert 80 percent of its solid waste by 2020 from landfill. In alignment with the Zero-Waste
goal, the Waste Facility Management team took the first initiative by installing four stream bins
including trash, refundable, mixed recycling, and compostable streams outside of all buildings
which covers 100 percent of the campus (University of Calgary, 2018). The present project is
defined as another step toward the Zero-Waste goal set by U of C to address how the existing
waste collection system at the University of Calgary can be optimized to be more aligned with the
sustainability concept. Waste collection and transportation is an important waste management
service that involves high expenditures if not handled efficiently. In this study, the current
University waste collection schedule has been used to determine the volume of waste bins and
volume of waste collected at each loading dock to optimize travel trips and collection time, which
leads to maximizing total waste collection, yielding large savings and keeping the environment
clean. This goal was executed, firstly, by understanding the existing waste collection system
through an in-depth, analysis study and then, secondly by introducing two proposed short-term
and long-term optimization solutions considering the environmental, economic, and social
2
sustainability pillars. The study suggested the best waste collection schedule and determined
suitable waste bin volumes for each loading dock. The use of the suggested optimization scenario
led to the reduction in the total number of trips and travel distances and use of compactors, which
decreased fuel or energy consumption and vehicle emissions. In addition, the significant cost saving
of this project can be invested in waste education throughout the University in order to reduce
waste in the first place.
Sustainability Tracking, Assessment and Reporting (STARS) system is the primary tool in North
America for measuring performance in all aspects of sustainability in post-secondary institutions
(AASHE, 2019). Based on the data pulled from STARS, the University of Calgary is a leader in
sustainability within Canadian Universities. But to stay in the leadership role University of Calgary
must continue using the Institutional Sustainability Strategy guidance as a roadmap for continuous
improvement in its pursuit of excellence and leadership in sustainability (AASHE, 2019).
This project is an interdisciplinary project and optimizes the waste collections system at University
of Calgary from three aspects of economic, environmental and energy dimensions. The first
interdisciplinary pillar is energy on which this project has a considerable impact. The main energy
consumers in this project are the trucks and the compactors. Both suggested optimization
scenarios decrease the consumption of energy by trucks and compactors. For example, replacing all
vertical compactors by few front-loaders will hugely decrease the electricity consumption.
The second interdisciplinary pillar in this project is economics. The best outcome of the
optimization scenario is the cost savings that can be invested in many other sustainable aspects as
discussed in the paper. Both suggested scenarios have up to an annual 35 percent cost reduction
for the waste management facility at the University. The economic benefits are the main driver for
this project.
In addition, there are environmental benefits for society from the project. As an example,
optimization scenarios will reduce the number of lifts per each loading dock which greatly impacts
the greenhouse gas (GHG) and air pollutant emissions produced by the lifting trucks. The lifting
trucks are used for transportation of waste from loading docks to the designated landfills.
3
As stated by the Association for the Advancement of Sustainability in Higher Education (AASHE,
p.1.), “Institutions that are moving toward Zero-Waste plan by reducing, reusing, recycling, and
composting… These actions mitigate the need to extract virgin materials from the earth, such as
trees and metals. Reducing the generation of waste also reduces the flow of waste to incinerators
and landfills, which produce greenhouse gas emissions, can contaminate air and groundwater
supplies, and tend to have disproportionate negative impacts on low-income communities. Source
reduction and waste diversion also save institutions costly landfill and hauling service fees. In
addition, waste reduction campaigns can engage the entire campus community in contributing to a
tangible sustainability goal.”
4
2 Chapter Two: Literature Review
The main principles behind the University’s Waste and Resource Management Strategy should be
based on the well-established Waste Hierarchy (Figure 1). The waste Hierarchy not only explains
the importance of each of the stages in the waste management field but also is the foundation of a
Zero-Waste plan. This must become a foundation of sustainable waste management practices, in
which waste management measures should be prioritized based on environmental impact.
Figure 1: Waste Hierarchy Chart
(AASHE, 2019)
Waste Prevention and Reduction at Source refers to reducing the production of waste in the first
place before it enters the recycling stream, energy recovery stream, or residuals disposal stream
(AASHE, 2019). Preventing waste also means reducing the amount of waste generated, reducing
the hazardous content of that waste and reducing its impact on the environment. Generating less
waste translates to fewer natural resources extracted and less energy used in the production,
distribution and consumption of products. It also an avenue for spending less money on recycling
and disposal programs and generating some revenue for the University.
Reusing waste can be interpreted as considering the waste as a resource. Several waste streams
produced at the U of C have considerable market value and if collected and segregated properly,
the University can receive rebates from recyclers or sell items that are in good condition (AASHE,
2019). The University should consider waste as a resource and raise revenue wherever possible or
identify opportunities for disposing of material free of charge (AASHE, 2019). Waste prevention,
reduction and reuse must be given the highest priority in the University’s Waste Management
Facility as it is a priority in the waste hierarchy.
5
The next steps in the waste hierarchy scheme are recycling and recovering before the final stage,
which is disposing. Reviewing the waste hierarchy indicates the most cost effective and
environmentally friendly approach is to focus on first three stages before the last step which is
disposing. In other words, increasing the diversion rate should be the focus to reach more
sustainable or Zero-Waste community. The waste diversion rate is one of the key performance
indicators to measure a successful recycling and recovering program. It represents the amount of
waste that is diverted from the landfill for recycling and recovering (Giroux, 2014). When looking to
improve the success of a solid waste management program, it is critical to know your current
waste diversion rate to use as a benchmark and to try to increase it. University of Calgary diversion
rate is currently 40 percent with a target to increase it to 80 percent by 2020 to meet its Zero-
Waste target. This project’s result will directly and indirectly help the University to increase its
diversion rate and be able to sustain it toward its Zero-Waste plan.
With regard to reaching a higher diversion rate, universities have taken different actions based on
their current waste facility infrastructure. The waste management process involves a many
different segments from where the waste is produced to the end of its cycle. But, the waste
collection stage is the most aggravated due to the high costs it involves (UNEP, 2009). The waste
collection cost by itself constitute 60 percent of the solid waste management budget in most
municipalities and communities (Cheng, 2003). The waste collection cost includes the total cost of
storage or loading dock facilities maintenance, the loading dock’s bin and compactors, and waste
transportation from collection point to designated landfills, recycling or composting facilities. The
common objective of waste collection optimization is to minimize travel frequency to reduce
transportation costs and emissions. Most of the research at the municipal scale on waste collection
optimization advocates for route optimization by using a GIS tool to reduce travel time and
distance (Kinobe, 2015). Following other universities work regarding a Zero-Waste plan, in most
organizations an efficient waste management system relies on both sufficient infrastructure (e.g.,
well-labeled and consistent waste bins) and correct behaviors or waste education (e.g., sorting
waste in the appropriate bin). In response to waste collection optimization, other universities with
a similar size and population have taken different approaches based on their infrastructure. In this
extent relevant works in similar size universities have been reviewed to help with a better research
6
outcome. University of Exeter located in Devon, United Kingdom with a 30,000 population has
introduced a raft of initiatives to ensure its compliance with sustainable waste management and in
accordance with the waste hierarchy and to reduce its costs. Concentrating on the waste collection
section, University of Exeter has applied a few strategies which affect the cost associated with
waste collection segment (Cozens, 2017). University of Exeter trialed an on-site aerobic composting
facility on campus for managing food waste. Having this facility on site will reduce the
transportation cost corresponding to organic waste transportation (Cozens, 2017). Also, this
university has developed a central area for sorting recyclable materials. A dedicated central
resource area enables the secure segregation of metal, electrical items, wood, plasterboard and
non-recyclable items. Having this facility on site not only reduces the transportation cost of these
items to a designated recyclable facility but also has generated revenue for Exeter University. Only
within the first six months of the facility’s operation, a total of 10 tonnes of good quality office
furniture reused across the campus and over two tonnes of quality furniture has been distributed
across campus representing a financial saving of £47,421 on the current market value during
August 2016 as well as £350 in disposal costs (Cozens, 2017). Using a central facility as it has been
used in Exeter and Alberta universities is an efficient option for University of Calgary. The long-term
optimization scenario in this research project adopted the idea of having a central facility based on
University of Calgary’s infrastructure and operational system.
University of Alberta (U of A) in Edmonton, Canada has an approximate population of 32,000 and is
changing toward a Zero-Waste community (University of Alberta Waste Diversion Working Group,
2017). The University of Alberta Waste Diversion Working Group (the “Working Group”) is focused
on the University’s commitment to waste reduction and diversion (University of Alberta Waste
Diversion Working Group, 2017). University of Alberta has applied some strategies specifically for
waste collection optimization. They developed a Recycle Transfer Station (RTS) to reduce and divert
the University’s waste more efficiently. The RTS is a central facility with three large compactors and
two large roll-off bins (University of Alberta, 2019). Each day a hybrid truck collects recyclable and
organic materials on campus and brings them to RTS and sort them into the appropriate
compactors. The RTS also has a rolling cart wash system on campus to keep carts clean and reduce
7
odor and pests (University of Alberta, 2019) . Using its own hybrid truck to collect recyclable and
organic materials limits large trucks use, reduce labor, traffic, noise and emissions.
The travel routes optimization using GIS is another approach for optimizing waste collection at the
municipal scale. This scenario has been also considered for University of Calgary but as waste
transportation is limited to University of Calgary campuses the route options are restricted within
loading docks and therefore using GIS in this case in not applicable.
The best approach to increase diversion rate is to focus on reducing waste at the first stage which
will be achievable through correct behavior and infrastructure in place. One of the indirect
outcomes of this project is social benefits through waste education that will directly affect the
diversion rate. The focus of this project is on waste collection optimization that provided a short-
term and a long-term optimization proposal. Both these optimization scenarios elevate energy and
environmental efficiency of waste management at the University. The short-term proposal suggests
a 34 percent and the long-term one leads to a 24 percent cost reduction mainly by reducing the
number of waste collection truck pick-ups. The economic benefits of the results are amalgamated
with energy, environmental and social benefits. The environmental and social benefits are
greenhouse gas reduction and opportunities for waste education.
8
3 Chapter Three: Methodology
This project has been conducted in four main phases as described below and demonstrated in
Figure 2 flow chart.
Figure 2: Methodology Flow Chart
(Author, 2019)
3.1 Phase One - Understanding the Existing Collection System
It is critical to understand the current waste collection system at University of Calgary and what has
been done toward the Zero-Waste target. In phase 1, the following information has been collected
and studied: area map, number of buildings, loading dock stations, type of containers and their
sizes, compactor types and their capacities and finally third-party operational data including cost.
3.2 Phase Two - Data Clean up and Data Verification
After collecting information in phase 1, the data has been reviewed and edited during the cleanup
process. Missing information and gaps in data were identified and collected from different sources.
In addition to data cleaning, verification of data has been performed by visiting the sites and cross-
checking the provided data with actual information and physical observation and counts. For
example, the data provided including number and size of the bins for each waste stream has been
verified or corrected wherever it was needed, by physically visiting the loading docks and
comparing the data with actual bins. Verification of data is one of the most important parts of the
process since the analytical analysis totally depends on the quality of data which eventually is the
foundation of the optimization recommendations.
Data GatheringUnderstanding the Existing Collection
System
Data Cleanup & Data Verification
Analytical Analisis of Data
Integration of All Information into
Final Recommendation
9
3.3 Phase Three - Analytical Analysis of Data
Phase 3 or analytical analysis of data is the basis of ultimate optimization solutions; hence due to
its importance this phase has been broke down into three sections as described below. It is worth
mentioning the quality of phase 3 is totally related to accuracy of phase 1 and 2.
3.3.1 Interviewing:
The recycling and waste diversion coordinator at facility management of U of C
has been interviewed to better understand the collection system and the data.
Another objective of the interview was to collect current problems, challenges
and limitations faced with the current system. This information was vital to
understand the compactors’ efficiency and where the optimization
recommendations could have the most impact. Furthermore, as part of the long-
term strategy and what could work best in a long run, the Marathon Equipment
sales representation has been interviewed to grasp the compactors specification.
3.3.2 Visiting U of A site:
One of the early steps on planning any project is selecting the technology or
system. Unfortunately, there were no data available to show what was the basis
for selecting the current system. With a goal of comparing the existing system
with different waste collection systems, a day tour to U of A waste collection
system was performed in July. The Waste Diversion/Recycling Supervisor at
University of Alberta gave a tour of their waste collection process. U of A waste
management system is a central type and has been a good comparison base.
Valuable information has been collected and further follow up questions were
answered by the U of A team. This info was used for the final recommendation.
10
3.3.3 Walking through loading dock stations:
A couple of days were spent on capturing information on loading dock stations
at University of Calgary. The data collected comprises the size of loading docks
space and container and compactor dimensions. Photos has been captured as
well to help with the recommendation section of this study.
3.3.4 In Depth Desk Top Analytical
In this step, an in-depth desk top study has been performed. Volume of waste
was calculated at every docking station. Lifting costs verified with the latest
schedule. In this section saving opportunities as well as some other opportunities
were captured in this section and used for the final recommendation.
3.4 Phase Four - Integration of All Information and Final Recommendation
This phase is the integration of all other phases in one place. At this point the analyzed data has
been reviewed and compared with the current system in term of economic, environment and
social aspects. In addition, other related waste collection optimization articles and waste collection
system in other high ranked universities have been studied to assist with the final
recommendation. Ultimately a short-term and a long-term optimization approach are
recommended and presented in this study.
11
4 Chapter Four: Evaluation and Analysis of Existing Waste Management System
4.1 Study Area
University of Calgary includes 52 buildings over three campuses: main campus, SpyHill campus, and
Foothills campus which are the focus of this study (Figure 3). These three campuses have 36
loading docks and therefore some of the buildings are sharing them. Everyday, University of
Calgary hosts a population of 30,000 to 35,000 people including staff, students and visitors
(University of Calgary, 2018) . Each of the residences generates 0.1 tonne of wastes daily which
adds up to 3000 tonnes of annual waste. Additionally, as it is demonstrated in Figure 3 buildings are
scattered over a large area, and therefore they have scattered loading dock stations as well.
Managing this many loading docks and waste needs a systematic structure and arrangement to
handle the logistics properly. Currently University Waste Facility Management group operate and
manage the entire University waste. This study is focusing on the transferring of the waste from
loading docks to designated facilities.
Moving toward a Zero-Waste plan, the University has taken the first step which is adopting a four-
waste stream bin strategy including trash, refundable, mixed recycling and compostable streams to
help increase the diversion rate (Figure 4). Using sorted bins facilitate segregation and sorting
waste at the first place which will ease the way for better diverting the waste. Along with launching
the sorted bins some educational posters and videos have been published around the University to
assist students and staff to better understand the instruction and importance of it.
12
Figure 3: University of Calgary, Foothills and Spyhill Campuses Map
(University of Calgary, 2019)
13
Figure 4: University of Calgary Sorted Bins
(University of Calgary, 2019)
4.2 Waste Collection System
University of Calgary has 36 loading docks for its 52 buildings. Some buildings which have an
internal connection are mingled together and are using one loading dock in common. All the
loading docks are located outside of the buildings except three of them which are in the basement
of McEwan Center, Education Tower, and Foothills Hospital. In general, the area associated with
the loading dock occupies approximately 500 square feet including the containers for each waste
14
stream (Figure 5). Not all the loading docks have the exact same plan and area, and this is just an
approximate calculation.
Figure 5: Loading Docks at University of Calgary
(Author, 2019)
There are three type of containers used in the loading docks at the University; totes that have volumes
of 0.4 cubic yards and are used for organic waste; front-loader containers with a volume of 3, 4, 6 and
8 cubic yards and mostly are used for solid waste and mixed recycle waste; and finally the compactors
which are used for both solid and mixed recycle waste collection (Figure 6). Compactors in the
University are used to decrease the total volume of waste and as a result reduces the number of
pickups per loading dock. The compactors are varied in size between 8 to 25 to 34 cubic yards and they
work using city power. The power usage of the compactors is 2.2 Kwh for vertical 8 cubic yard
compactors and 7.2 Kwh for 25 horizontal cubic yard compactors (Marathon Equipment Company ,
2019). The efficiency of compactors examined, based on their compaction ratio, is 4:1 or compacting
original volume to one fourth the original size (Marathon Equipment Company , 2019) This ratio is
subjected to factors such as humidity of region, age of compactors, and level of maintenance.
15
Figure 6: From Left: 0.4 CY Tote, 8 CY Front-Loader Bin, 8 CY Vertical Compactor, 25 CY Horizontal Compactor
(Marathon Equipment Company , 2019)
Totes are small and emptied manually into collecting trucks. The front-loader containers have two
pockets on their side designed specifically to be picked up by front-loader trucks (Figure 7). The front-
loader trucks have two arms that fit into container pockets and roll the container back in the truck’s
trunk. The compactors at the University are three sizes: the 8 cubic yard vertical compactors and the
25 to 34 cubic yard horizontal compactors (Figure 6) (Marathon Equipment Company , 2019). The
vertical compactors have a container with pockets that can be unloaded using the same front-loader
trucks. The horizontal compactors have a bigger container and therefore need a different truck to load
the whole container of compactor and unload it at designated landfill. Roll-off trucks are used for
horizontal compactors to load the whole container and unburden it in designated landfill (Figure 7)
(Waste Management Company, 2019).
16
Figure 7: From Left; Front-Loader Truck and Roll-Off Truck
(Waste Management Company, 2019)
The compactors’ compaction ratio is assumed to be 4:1 at its efficient level (Marathon Equipment
Company , 2019). This means the volume of waste should be collapsed into one fourth of its
original volume. Using this ideal ratio at 4:1 and calculating back to the volume of waste produced
per loading docks having compactors is not realistic. Based on the research and site visits
performed, the vertical compactors do not work efficiently and therefore compaction ratio is
assumed to be 2:1. The horizontal compactors are working more efficiently and thus the
compaction ratio used is 4:1. The University owns 13 compactors of which 10 of them are 8 cubic
yard vertical compactors and 3 of them are 25 to 27 cubic yard horizontal compactors. These
compactors are using University power to operate, and the power usage is limited to when the
compactor is self-compacting the waste. The exact power usage of compactors is unknown as we
don’t have specific data on it.
Caretakers or custodians transfer the waste from sorted bins inside and outside of the buildings
into containers or compactors at University’s loading docks. Collecting the waste from totes, front-
loader containers and compactors is being operated by a third party called Waste Management Inc.
(WM). WM dump the collected waste at the designated station, for example mixed recyclable
waste is unloaded at Capital Paper Company.
17
4.3 Waste Streams Volume
For this study, the volume of waste at each loading dock has been calculated in five existing
streams separately. The five waste streams being used currently are; solid waste, mixed recycling,
wood pallets (recycling), metals (recycling), and organic waste streams. The solid, organic, and
recycle streams exist in most of the loading docks but metal is only collected in one location at the
General Services Transfer Station. Carboard is being collected separately at MacEwan Student
Center and packed to be delivered to a recycling station. Therefore, volume calculations do not
contain cardboards numbers. Appendices 1 through 5 indicate the calculation made for each waste
stream. For the calculations and analysis of data a few assumptions have been made;
1. All the bins have been loaded fully at each scheduled pick-up plan.
2. The compaction ratio for vertical compactors assumed to be 2:1 base on the field visits and
research has been done to support this assumption. As the vertical compactors at University
didn’t have maintenance service therefore they are not working efficiently. In addition, the field
visits at loading docks with vertical compactors show the volume of waste going in with the
volume of waste compacted is in ratio of 2:1 and not 4:1 as it should be. The number of pickups
at this loading docks compared with those without vertical compactor also confirm the low
efficiency of these compactors.
3. The compaction ratio for horizontal compactors assumed to be 4:1 base on the field visits and
research has been done to support this assumption.
4. The compaction ratio for the front-loaders and totes is considered 1:1 just for sake of
calculations.
5. The average number of weeks per month is prorated to 4.3 for a year for ease of the lift
frequency calculations.
6. The cost of transportation was determined from third party (WM) pricing list (Waste
Management Company, 2019).
Taking the assumptions from above, the formula stated bellow is used to determine monthly
volume of waste per stream per loading dock:
18
Volume of waste/Stream/Loading Dock/Month = Number of containers* Size of containers (CY)*
Number of lifts/Week * Average Number of weeks/Month * Compaction ratio
Base on the evaluation made, the volume of each stream is determined in cubic yard per month
and results are shown below in Figure 8. Wood pallets are not shown in the chart as they are
counted per pallet not volume and counts are 503 pallet per month.
Figure 8: Volume of Waste Produced in Each Stream per Month
(Author, 2019)
4.4 Waste collection system and cost break down
The cost incorporated with the waste collection system at University of Calgary are mainly the
salary of caretakers, Waste Management Transportation Service charges and power usage by
compactors. WM charges contributes the most into the total cost. Waste Management is a
subcontractor company that specializes in transferring waste of commercial institutes. They charge
different rates for transferring containers to its designated landfills, composting facilities and
recyclable stations for each stream. The price is predominantly dependent on the container size
and frequency of lifts at each loading dock. Front-loader bins and totes are all owned by WM and
their costs are imbedded in the transportation charges so there is no direct charge to the
associated bins and totes. As mentioned before, the power usage by the compactors is unknown
and the largest portion of cost is associated with WM transportation costs. In appendices 1 through
5037.45 CY2481.10 CY
172.00 CY
442.73 CY
Solid Waste Mixed Recycling Metal Recycling Organics Waste
19
5 the cost breakdown of transportation is determined for each loading dock per 5 waste streams. In
Figure 9 the total cost of transportation per each stream is shown. It worth mentioning that
currently the University doesn’t receive any revenue from any of the recycling waste streams such
as wood pallets and cardboards unlike University of Alberta. The revenue from bottles at the
University is used to pay the staff and the rest of it goes to a charity institute.
Figure 9: Cost of Waste Transportation by WM in Each Stream per Month
(Author, 2019)
The cost has been determined using WM pricing tables. These costs are provided by WM
contractor which is depends on the size of bin and frequency of lifts per week. The prices for
compactors are different and much higher than front-loader bins. For example, the price provided
by WM for once a week frequency of lifts for 8 CY front-loader bins is $182 per month and for 8CY
compactors is $487 monthly. Using WM price chart and the number of lifts per week from the
schedule, the cost has been calculated. The total cost of transportation for all streams is roughly
$52,117 which can be increased if unplanned pickups occur during the month. As shown in Figure
9, solid waste transportation cost mostly covers more than half of the total cost while it is expected
with Zero-Waste plan and the implementation, the sorted bins will be decreased significantly over
next few years.
$26,545.14
$8,864.25
$3,520.23
$1,169.10
$12,017.94
Solid Waste Mixed Recycling Wood Pallet Recycling
Metal Recycling Organics Waste
20
5 Chapter Five: Results
The current system of waste collection at the University has been reviewed and evaluated based on
the data available and activities that occur in phase 1 to 4 as mentioned in the Methodology
section. The result of the evaluation shows that the waste collection structure at the University
requires optimization to be more efficient; and therefore, two scenarios has been proposed as
short-term and long-term optimization scenarios. Project optimization can be defined as finding
the solution, from the available alternative options, with the most cost effective or highest
achievable performance under the given constraints, by maximizing desired factors and minimizing
undesired ones. The purpose of these two scenarios is largely dedicated to alignment with the
Zero-Waste goal and furthermore improve the efficiency of the current waste collection system
from the economy, environment and social aspects. Below the two scenarios are discussed and
elaborated.
5.1 Short-Term Optimization
The short-term optimization scenario is based on executing an easy, cost effective and fast
resolution to have higher economic, environmental and social impacts. This study is only focusing
on the waste collection from loading docks to the designated waste facilities section of the waste
management cycle. As mentioned before, the largest portion of waste collection is allocated to
transferring waste to designated stations by WM. The transferring stage also has a high negative
impact on the environment by producing GHG emissions and is labor intensive. This scenario
focuses on decreasing the number of transportations by heavy duty trucks (front-loader and roll-off
trucks) to reduce the overall cost and GHG emissions.
5.1.1 Economic
The cost analysis indicates that the cost of transportation increases predominantly by
compactor’s waste collection and number of lifts per loading dock. Accordingly, these two factors
were targeted to be addressed for better efficiency.
After current data were collected and field visits were completed, it appears that the vertical
compactors have an efficiency ratio of 2:1 which is half of its theoretical efficiency of4:1.
Meanwhile the transportation charge of 8 cubic yard vertical compactors is $490 before GST versus
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$180 for an 8 cubic yard front-loader container for just once per week lift. This suggests that the
transportation price of an 8 cubic yard compactor is 272% or 2.7 times higher than an 8 cubic yard
front-loader bin while the compaction ratio of compactor is only 2 times that of a simple front-
loader. In addition, the cost of power usage by compactors must be added to the transportation
price. Thus, replacing the 8 cubic yard containers with front-loaders will drop the cost in this case
and elevate the efficiency.
Furthermore, the number of lifts have a considerable effect on the transportation cost which is
controlled by the size of bins and volume of waste produced in each stream. As shown in Figure 10,
there is a direct relationship between the number of the lifts per week and size of the containers.
Considering this relationship, these two factors were targeted to be addressed for better efficiency.
Data assessment and observation (visiting the loading dock locations) suggests that the size of bins
can be increased in stations that have enough space and loading dock architecture is provided. This
can decrease the number of lifts per week which results in considerable economic savings.
Figure 10: Number of Lifts vs Size of Containers
(Author, 2019)
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Appendices 6 through 8 provide the calculations for the short-term scenario considering mainly the
two factors of replacing all the existing vertical compactors by front-loaders and increasing bins
sizes where it is applicable.
The results indicate that these adjustments in the short term can lower the transportation cost
significantly from $52,100 to $34,400 per month which is 34% or 1.5 times less than current system
charges. Figure 11 shows the comparison of current system with Scenario One in terms of number
of lifts and cost saving.
Figure 11: Optimization Scenario One Economics
(Author, 2019)
Additionally, waste facility management must focus on receiving revenue from cardboard and
wood pallets that can add a significantly to the University budget. It must be mentioned that
University of Calgary needs to add cardboard balers for collecting cardboard at a few of its loading
docks with enough space to collect cardboard separately and generate revenue from it. According
to University of Alberta, wood pallets in good conditions can be re-sold at $4 per pallet and
cardboard at $100 per tonnes. This can generate a good revenue for University of Calgary.
23
5.1.2 Environment
Engines that power trucks are designed to operate on gasoline or diesel fuel. The diesel motors are
considered as the principle cause of ecological contamination these days. Internal combustion
engines are large contributors to air pollution, which has a damaging impact on our health and the
environment and is suspected of causing global climate changes (Air Pollution Prevention
Directorate Environmental Protection Service Environment Canada, 2001).
All internal combustion engines produce emissions of the following:
• Hydrocarbons (HC). The formation of HC in diesel engines is caused by incomplete combustion
and insufficient temperature which occur due to the lack of oxygen supply in the combustion
chamber. The environment is badly affected by HC emissions. The formation of ground-level ozone
results (Keskin, 2010).
• Carbon Monoxide (CO). CO is an odorless and colorless gas. Incomplete combustion occurs due
to incomplete oxidation which produces CO formation (Keskin, 2010). The human respiratory
system inhales CO from the air and transmits it into the bloodstream.
• Nitrogen Oxides (NOx). NOx is the product of high-temperature combustion of nitrogen (present
in air); the combination of nitrogen dioxide (NO2) and nitrogen oxide (NO) is referred as NOx. There
is 85-95% of NO contribution in NOx. NO2 gas has a pungent smell with reddish brown color while
NO is an odorless and colorless gas (Robbind, 2012). NOx used for transportation has 40-70% of the
contribution to the worldwide pollution level. Now, diesel combustion is considered as the main
contributor to NOx emissions.
• Particulates or particulate matter (PM). PM consist of agglomerations of fuel soot and Sulphur
particulates caused by incomplete combustion. Insufficient supply of oxygen in a combustion
chamber produces incomplete combustion of the HCs which produce PM. An experimental study
indicates that PM consists of sulphates, moisture, unburnt lubricating oil, carbon element, unburnt
fuel and metals and other substances (Diat-Sanchez, 1997). In the diesel engine, PM emissions are
six to ten times greater than petrol engines. (Robbind, 2012) (Diat-Sanchez, 1997) (Keskin, 2010).
• Carbon Dioxide (CO2). CO2 is the complete combustion product of carbon in the fuel.
24
• Sulphur Oxides (SOx). SOX are created by the combustion of the Sulphur contained in fuel,
especially diesel fuel.
Major contributors to environmental impact in this study is the reoccurrence of transportation
from loading docks to designated dump sites and thus the production of GHG emissions and air
pollutants as mentioned above. Decreasing the number of trips will reduce a portion of emissions
related to transportation in this case study. Applying the two factors explained earlier and shown in
Appendices 6 through 10 will reduce the number of lifts per week from 219 to 178. This is
equivalent to a 20% improvement and saving 41 routes per month.
Based on an Environment Protection Agency (EPA) report, the main air pollutants from diesel engine
heavy duty vehicles are NOx, CO2, and PM. Using emission factors published by Canadian Energy
Systems Analysis Research (CESAR), a typical trip of a heavy duty truck was calculated to contribute
804 kg CO2e/750 km, releases 841 g NOX/750 km and producing a total of 117 g PM2.5/750 km from
the tailpipe to the atmosphere (J. Lof, 2019). This value is based on an average load factor of 80% of
the maximum vehicle payload and 25% of empty running for trucks with empty weight of 40,000
pounds ( Cefic and ECTA, 2011). Both front-loader and Roll-off trucks used by WM for waste
transportation have an empty weight of 32,000 to 36,000 pounds (Figure 7). By applying the short-
term scenario, 41 routes will be saved per month assuming a 20 km round trip for each route will
save 820 km trips per month. Applying the CESAR estimation to this scenario by saving 820 km routes
per month, an average amount of 879.04 kg CO2e/820 km, 919.5 g NOX/820 km and a total of 128 g
PM2.5/820 km will be saved which has a significant positive impact on GHG emissions and air
pollutant reduction and on consequently on our health and environment.
Furthermore, this scenario results in the decommissioning of 10 vertical compactors; accordingly,
the GHG emissions related to the power generation for compactors will be saved and added to the
environmental benefits of GHG emissions saving through minimizing the lift trips.
5.1.3 Social
The main driver of the short-term scenario is its economic and environmental rewards, and
consequently its social outcomes. $18,000/year cost saving outcome of this short-term scenario
can be budgeted for planning strategies toward waste reduction and reuse. The most effective way
25
to reach Zero-Waste plan is to manage waste at its first source which is mostly generated by
students at the University. Training programs can be conducted to help with educating students
about waste reduction and separation. Moreover, engaging students in the waste collection
process can be an effective way to educate students and show them the importance of a Zero-
waste plan. This can be done by implementing new strategies. Some of them are suggested
bellow:
Phase Out Plastic: One of the strategies that can help to divert waste from landfill is to ban use of
plastic bags or containers in the Food Court and events held at the University. This will also help
with promoting good habits for students who are eventually future parents.
Waste Educator Programs: A program can be designed to hire interested students to form a group
to promote effective waste management practices. Each year in Orientation Week the waste
educator groups or unions can inform new students of proper waste sorting practices and to
answer any questions pertaining to composting. This program has shown a drastic positive result
on diversion rate for some universities such as McGill University (McGill, 2015).
Innovative Waste Management Engagement: As the University is an educational and research
institution, it can leverage its expertise to ask undergraduate and graduate students and professors
to work on innovative solutions to reduce waste as a project.
Update Sustainable Purchasing Guide Within Procurement Department: Developing a guide
specifically for procurement department is a great way to practice waste reduction in the
University and can be done by hiring student. Vendor waste reduction best practices can be
considered as content for the guide. Purchasing products that are readily recyclable, have recycled
content, have less packaging, and/or are recyclable could also be included in the guide.
All these strategies and other innovative ones are easily achievable by implementing the cost saved
from Scenario One toward waste educating programs.
5.2 Long-Term Optimization
To evaluate what would work best for the University of Calgary and what other options are available
and applicable, further study and research was done on some of the North American universities by
performing an on-line search. In addition, a field visit took place at University of Alberta in Edmonton
to evaluate their waste collection system. University of Alberta has one central facility at its site along
26
with different arrangement of bins. After further evaluation and discussion with Calgary Waste
management team it was agreed that the U of A model is not fully pragmatic and cannot be applied to
U of C; however, the research and study lead to a new fit for purpose approach that can be adapted for
University of Calgary. Therefore, a second scenario is suggested which is a longer-term approach as it
needs a longer planning time. This scenario is built on Scenario One and essentially involves changing
bins sizes where it is needed and decommissioning vertical compactors and only keeping the three
efficient horizonal compactors owned by the University as was discussed in Scenario One. To continue
the changes, the long-term scenario suggests building two main central facilities at the University with
three horizontal compactors at each center. The internal transportation of bins from loading docks to
two central facilities can be done by hiring a third company and then the second part of transportation
(external transportation) which is from the central facility to designated locations still can be operated
by WM. The containers at the University are owned by WM and therefore proceeding with this
scenario requires purchasing containers by the University to be able to contract a third company for
internal waste transferring. The map in Figure 12 presents the possible location of two central facilities.
The suggested Central Facility A covers loading docks in zone 1,3,6 and Central Facility B covers loading
docks located in zone 2,4 and 5 as shown in Figure 12. It must be noted that Central Facility A is
currently under construction at Professional Faculty loading Location but not for the purpose of having
a central facility but just to expand the loading dock capacity. This facility is big enough that it can be
remodeled to satisfy the long-term optimization scenario. Appendix 9 presents the calculations done to
evaluate this proposed scenario. The construction cost of the central facilities, purchasing compactors
and hiring a third company for internal transportation has been evaluated based on similar existing
projects in other universities.
27
Figure 12: Location of Proposed central Facilities A & B
(University of Calgary, 2019)
5.2.1 Economic
This scenario incorporates an upfront capital cost including the construction cost of Central Facility
A as the other Central Facility B in Professional Faculty has been built and its cost are budgeted.
Upfront costs also included to purchase three horizontal compactors for Central Facility B and
remodeling three purchased horizontal compactors for Central Facility A. Additionally, operational
cost is embedded in the project, which includes internal transportation and external transportation.
Internal transportation of bins from loading docks to the central facilities can be operated by WM or
hiring a different company. External transportation from the central facility to designated locations
can be continued to be operated by WM and the costs used in this scenario is based on the WM
price list. Total capital cost is estimated to be $343,00 (Figure 13), including three horizontal
A
B
28
compactors at $21,000 each (Marathon Equipment Company , 2019) plus $100,000 construction
cost for the second central facility (H. Cozens, 2017) and $33,370 for purchasing the front-load
containers for the loading docks (Waste Management Company, 2019). The operational cost is
estimated to be $39,000 per month and comprises $32,000 of external transportation by WM
(Waste Management Company, 2019) and assumed $6,000 cost of internal transportation by a third
company plus $700 annual maintenance fee. The external operational cost includes transportation
of nine (9) horizontal compactors from the two Central Facilities A & B, MacEwan Student Centre,
Science Center and Science Theatre loading docks. The summary of the capital cost and operational
cost of optimization Scenario two is shown in Figure 13.
Figure 13: Scenario two operational and capital cost summaries
(Author, 2019)
The cost saving in this scenario compared with the current system is $13,100 per month and with
this saving the breakeven point for the $433,400 capital cost will be after two years and five months.
Cost of power usage by compactors must be added to the total value, which is left for future
research and not calculated for this study.
5.2.2 Environment
This scenario is proposing two central facilities; therefore, the commute will be less. The internal
collection has a shorter route to travel between loading dock locations and the central facilities at
the University in comparison with traveling between loading docks to designated dumping stations.
This will contribute to a reduction of GHG emissions and thus our environment.
Through researching the compactor company, it has been observed that Marathon Company which
is a compactor company offers solar-hybrid powered compactors that can operate with solar
29
power and not use the power grid and its associated cost. These solar-hybrid models connect to
the power grid as a backup that automatically switches when necessary. They use less energy than
conventional power units, and the batteries recover as the compactor continues to be available for
operation. These units are a great alternative for reducing the GHG emissions integrated with
power use and will save cost of energy for the University.
5.2.3 Social
The social benefits of this project, in addition to money savings that can be spent on training and
education of students and employees toward Zero-Waste plan, will be creating jobs for a third
company who operates the internal transportation at U of C. Figure 14 emphasize the training and
educating stage to avoid and reduce waste with the lowest cost and highest environmental
benefits.
Figure 14: Waste Hierarchy
(AASHE, 2019)
30
6 Chapter Six: Conclusion
The priority for waste management at the University is to achieve the Zero-Waste plan by 2020.
To reach this goal some work has been initiated and the results of this project can help to achieve
this goal and sustain it. Implementation of the project results has a considerable economic,
environmental, and social benefits for University. The outcome of this project is presented in two
sections bellow as recommendations and future work.
6.1 Recommendation
The priority for waste management at the University is to achieve the Zero-Waste plan by 2020
and to reach this goal some works has been initiated such as the implementation of sorted bins all
over the campus. In addition to this first step other opportunities have to be followed up and this
study’s result can be reviewed and applied as future steps. The first focus should be arranging
strategic training programs and engaging students into learning about wastes basics and therefore
understanding the importance of sorting their waste by using sorted bins properly as it is
explained in social benefits of Scenario One. In terms of the collection system Appendix 10
presents a summary of all current waste collection systems at University of Calgary plus Scenario 1
and 2. It is highly recommended to execute the short-term strategy scenario as early as possible
since it can be done quickly, and the economic and environmental benefits can be captured right
away. Savings in operating costs can be spent on educational purposes as proposed in this report
or at any other area in the University. Also, the revenue coming from cardboard and wood pallets
can be invested in training purposes or new infrastructures at the University. Another addition to
this scenario is to plan a strategic waste pickup schedule for the academic year excluding the
summer time. Currently there is only one pickup schedule for all the year round even though
campus is less busy in summer and consequently lift frequencies can drop for most of the loading
docks and this can add to cost savings and also the environmental benefits.
Regarding the longer-term scenario, since three (3) horizontal compactors are already ordered, it
is highly recommended to immediately modify their design in a way that they could receive 8 CY
bins. In other words, with adding a small amount of capital to the current scope of work for site A,
50% of the long-term scenario is completed. More accurate cost analysis on the internal
31
transportation and upfront capital to set up Site B followed by re-running the economics is also
recommended in the near future for possible execution of the project in 2020.
6.2 Future work
Waste management at University of Calgary is on the right path toward the Zero-Waste plan.
Implementation of this study’s short-term optimization result can provide significant economic,
environmental and social benefits in the short time. Nevertheless, over the next few years some
work needs to be investigated in alignment with achieving sustainability goals. The long-term
scenario can be studied in greater detail regarding cost and compared with short-term
optimization efficiency. The waste management facility has to organize a tracking system to
complete its database. This tracking data base can include data such as: volume of waste per
stream per week per each loading dock station, power usage of compactors, efficiency of
compactors and cardboard volume. Based on the new database a pickup schedule can be
modified to the academic calendar and summer calendar. Replacing this suggested pickup
schedule by the current one can bring up to 5% economic benefits for waste management at the
University.
Furthermore, for the purposes of increasing the life span and efficiency of compactors, the
University should consider adding the compactor’s maintenance service. Maintaining the
compactors not also affect their efficiency but also covers managing leachate in horizontal
compactors.
Waste management is a principal task and needs a great infrastructure to operate effectively
and constant optimization.
32
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“Raw data has been removed from this report due to confidentiality”
