Net Zero Heroes Talk_Vincent Woon.pdf

,

1. No Time to Waste:
Advancing Low-carbon Solutions in
Municipal Solid Waste Management
12 June 2024
Net Zero Heroes –A Renewable Energy by KampusMerdeka Program
Vincent Woon Kok Sin, PhD
Associate Professor
Head of PhD Programme
New Energy Science and Engineering
School of Energy and Chemical Engineering
Xiamen University Malaysia

2. •4+ years in strategy consulting (Accenture) and township
development (Country Garden and Lippo), 5+ years in academic
Grants/consultancy received within 2020-2024
•17projects (> RM 1.6million) as PI and co-PI
Paper publication within 2021-2024
•54 papers (26papers in SCI Q1/Q2 as first/corresponding author
including Science, RCR, JCLP, STOTEN, Energy, JEMA)
Awards/Membership
•2023 -SUSI Scholar (US Deptof State)
•2023 -Class of Influential Researchers (ACS I&ECR)
•2022 -UNFCCC-GIR-CASTT Fellowship (UN Climate Change)
•2022 -UN Summer Academy Fellowship
•2021 -CrossCultureFellowship (German Foreign Office)
•2021 -First Prize ORD(GDN through the World Bank)
•2021 -Fulbright Fellow (YSEALI by US Dept of State)
•Member,YSN Academy Sciences Malaysia
•Professional Technologist,MBOT
•GreenREAPProfessional, REHDA
Sustainable Process and Systems Analytical Approaches for Policy Development
Assoc. Prof. Ts. Dr Vincent WoonKokSin
PhD in Environmental Engineering, HKUST
(Hong Kong PhD Fellowship Scheme)

3. | 3
Introduction| About XMUM
Xiamen University Malaysia, Sepang, Malaysia
•First oversea campus set up by a
renowned Chinese university
•Established in 2016(22 Bachelors, 6
Masters, 5 PhDs, 7,100 students from 26
countries, and 350 academic staff)
•Medium of instruction: all
programmesare taught in English
(except Chinese Studies and Traditional
Chinese Medicine)
•New Energy Science and
Engineering Programme–from
Bachelor to PhD
(330 UG, 45 PG, and 15 academic staff -
100% are doctoral degree holders)

4. Table
of
Content
01
Global and Malaysia’s
MSW Scenario
02
Greenhouse Gas Emissions
in MSW
03
Sustainability Analysis of MSW
Management
04
Conclusion

5. | 5
Introduction| Global Municipal Solid Waste Generation
A Global Picture of Municipal Solid Waste (MSW)
Global MSW Generation
a
In Developing Countries
a
Year of 2020
Year of 20501.7×
2020
>3×
2050
2050
1×
2020
2.24
billion tonnes MSW
a
Under Business-as-usual scenario
The World Bank (2022)

6. | 6
Introduction| Global Municipal Solid Waste Treatment and Disposal Methods
A Global Picture of Municipal Solid Waste (MSW)
Global MSW Generation
a
Kazaet al. (2018); The World Bank (2022)
1.7×
2020
2050
2.24
billion tonnes MSW
a
Under Business-as-usual scenario
93%
66%
30%
2%
3%
18%
54%
39%
10%
2%
6%
10%
23%
4%
6%
4%
30%
0 20 40 60 80 100
Low
income
Lower-
middle
income
Upper-
middle
income
High
income
Percent (%)
Open dump
Managed landfill
Composting and anaerobic digestion
Incineration
Recycling
MSW treatment and disposal method by income level, % share

7. | 7
Introduction| Open Landfill in Most Developing Countries
Open landfill practice will cause public health concerns, environmental
pressure, and economic inefficient
Energy. 232, 121094 (2021); Science, 383 (6690), 1499-1504 (2024)
Generate
greenhouse gases
andair pollutants
Contaminate soil and
groundwater due to
toxicity leakage
Spreaddiseaseby
different vectors such
as birds, insects, and
rodents
Create economic
inefficient due to
precious materials
wastage
Photo Courtesy: CanvaWebsite
Consequences of disposing MSW at open landfill

8. | 8
Introduction| Municipal Solid Waste Composition
Food waste has highest proportion among other types of solid waste
The World Bank (2022); ); McKinsey (2021)
•High moisture content
•Perishable
•Odorous
44%
17%
2%
12%
2%
5%
4%
14%
Food Paper
Wood Plastic
Rubber and leatherGlass
Metal Others
~63%
organic
Proper treatment of different MSW compositions is necessary to
reduce its greenhouse gas (GHG) emissions.
Organic content in MSW decomposes and predominantly generates
methane(CH
4) gas, making the solid waste sector one of the top
CH
4-emitting industries.

9. | 9
Introduction| Municipal Solid Waste in Malaysia
For MalaysiaScenario
The Star (2021)
39,000
tonne MSW/day
82.5%end up in landfills
Sanitary landfills
21out of 141

10. | 10
Introduction| Moving Towards Sanitary Landfill System
Sanitary Landfill System (Anaerobic Decomposition)
Layout of a Sanitary Landfill
Landfill covered with liner system, leachate collection, landfill gas
collection and treatment system.
A PFD Example for a Sanitary Landfill
Resour. Conserv. Recycl., 107, 104-114 (2016)

11. | 11
Introduction| Moving Towards Incineration System
Advanced Incineration System
Hong Kong EPD Website

12. | 12
Introduction| Dilemma in Designing Optimal Waste Facility Configurations
MSW is complex with high variations of composition and characteristic,
hence no single dominating facility can treat all wastes!
J. Environ. Manag., 323, 116238 (2022)
Waste
Type
Waste
Facility
Valuable
Resource

13. | 13
Introduction| MSW Management Policy in Malaysia
Malaysia’s Sustainability Targets
Sustainable Energy Development Authority (2021)
29.4%
By the end of 2016
31.5%
By the end of 2021
23%
By the end of 2021
Reduce carbon intensity against GDP by 45% by 2030
Emissions reduction target
Increase solid waste recycling rate to 40%by 2025
Solid waste recycling rate target
31% renewable energy capacity by 2025 and 40% by 2035
Renewable energy target

14. | 14
Introduction| MSW Management Policy in Malaysia
Malaysia Towards the Circular Economy
Economic Planning Unit (2021)
Theme 3: Advancing Sustainability
Game Changer VIII: Embracing the Circular Economy

15. | 15
Introduction| From Linear Economy to Circular Economy
Moving Towards the Circular Economy
Circular Economy
Economic Planning Unit (2021)
Linear Economy
Take
Make
Use
Dispose
Raw Material
Manufacturing
Consumption
Landfilling
✓Recover
✓Recycle
✓Repurpose
✓Remanufacture
✓Refurbish
✓Repair
✓Reuse
✓Reduce
✓Rethink
✓Refuse
Reduce
Total Cost
(Economy)
Reduceandavoid
GHG and pollutants
(Environment)
Increase
Willingness to accept
(Social)

16. | 16
Introduction| Long-term Ambitions for Controlling Global Warming
The current trajectory of rising greenhouse gas emissions is jeopardizing
the ability to achieve the ambitious targetsset by the Paris Agreement
Climate Action Tracker (2022); Nature 596, 461 (2021)
WMO:1.45°Cfor2023

17. | 17
Introduction| Global Warming Potential of Methane
Methane, despite being a smaller contributor, has a much greater short-term
warming impact than carbon dioxide
Nature599, 355-356 (2021)
Methane emissions with 81 times the cumulative warming potential of CO
2in a 20-year timeframe.
CO
2
~45%
Methane
~30%
Nitrous
oxide
~5%
Other
~20%
Global warming by greenhouse gases (GHG) to date, % share
Warming potential of one incremental tonne of CO
2and
methane over time (illustrative)

18. | 18
Introduction| Methane Role in Solid Waste Management
Methanehas shorter atmospheric lifetime and solid waste sector has
significant potential to reduce methane emissions
McKinsey (2021)
•With methane’s short lifespan, rapid
reductions can reduce the methane
concentration cumulated in the atmosphere.
•Gives us a short-term solution to decelerate
near-term global warming.
•Provides short-term relief for negotiations to
cut global emissions.
39%
91%
0
10
20
30
40
50
60
70
80
90
100
By 2030 By 2050
Methane reduction potential (%)
Methane reduction potential
AgricultureOil and gasCoal miningSolid wasteWastewater

19. | 19
Research| Overall of My Research Focus in MSW Management
Utilizing sustainable process and systems analytical approaches for
circular MSW management development
How can we overcome the data gaps due to
insufficient and obsolete data?
▪Artificial intelligence model –Bayesian
optimized neural network
Due to MSW heterogenicity, how can we
design an integrated MSW management
framework?
-Food waste, plastic waste, e-waste?
-Separation, collection to different
treatment facilities?
-Environmental, economic, and social?
▪Life cycle assessment (LCA)
▪Life cycle costing (LCC)
▪Social life cycle assessment
(SLCA)
▪Multi-objective optimization (MOO)
How can we achieve carbon neutrality
in MSW policy making
▪GHG Protocol and LCA

20. | 20
Multi-objective optimization (MOO) model development for MSW
AUGMENCON2methodreplacesweightingmethodwhen
consideringmorethanoneobjectivefunctioninthe
optimizationmodel–solvedviaCPLEXGAMS
Past Publications Sharing | Optimization in MSW
J. Clean. Prod., 316, 128366 (2021)
g

21. | 21
Multi-objective optimization (MOO) model development for MSW
•ComparedtothecurrentscenarioinMalaysia,theleast-costsolutionshows26%reductionforbothcostandGHGemissions,
whiletheleastGHGemissionssolutionindicates159%reductionofGHGemissionswith15%increaseincost.
•The10
th
solution(34%sanitarylandfill,21%anaerobicdigestion,21%composting,17%materialrecyclingfacilities,and8%
plasmagasification)reduces3%ofnationalgreenhousegasemissions(basedon2019)andisrecommendedforfutureMSW
managementinMalaysia.
Past Publications Sharing | Optimization in MSW
J. Clean. Prod., 316, 128366 (2021)

22. | 22
Life Cycle Assessment | What is LCA?
A Cradle-to-Grave (Cradle) Environmental Evaluation
The International Journal of Environmental, Cultural, Economic, and Social Sustainability: Annual Review 7 (3): 237-246 (2011)
Image Credit: https://www.innovationservices.philips.com

23. | 23
Life Cycle Assessment | LCA Steps
LCA is a technique assessing the potential environmental aspects
associated with a product or process throughout its life cycle
Adapted from ISO14040 (2006)
Climate change
Carcinogens
Respiratory organics
Respiratory inorganics
Ecotoxicity
Acidification/
Eutrophication
1. Goal and
scope
definition
2.
Inventory
analysis
(LCI)
1
3. Impact
assessment
(LCIA)
2
4.
Interpretation
Note:
1)LCI –Life Cycle Inventory
2) LCIA –Life Cycle Impact Assessment

24. Unilever
Johnson &
Johnson
Levi Strauss
& Co.
Apple Inc.
Samsung
SDI Co

25. | 25
Meta-analysis review of LCA on solid waste management
Past Publications Sharing | Review of LCA on Solid Waste
Sci. Total Environ., 831, 154903 (2022)

26. | 26
Integrating the 3Ps (Planet-Prosperity-People) nexus in MSW management
Past Publications Sharing | Environmental + Economic + Social on MSW
J. Clean. Prod., 415, 137698 (2023)

27. | 27
Integrating the 3Ps (Planet-Prosperity-People) nexus in MSW management
•A scenario with 40% recycling coupled with composting and AD is the most sustainable scenario for fulfilling the 3Ps.
•Waste segregation is essential for sustainable waste management and can be supported bytechnologyimprovement, financial
subsidy, and legislative enforcement.
Past Publications Sharing | Environmental + Economic + Social on MSW
J. Clean. Prod., 415, 137698 (2023)

28. | 28
A review on carbon emissions neutrality in urban development
Past Publications Sharing | Review on Carbon Neutrality
Energy, 267, 126502 (2023)

29. | 29
GHG Protocol and LCA for palm waste to pellet production
Past Publications Sharing | GHG Protocol + LCA for Net-Zero
Sci. Total Environ., 856, 159007 (2023)

30. | 30
GHG Protocol and LCA for palm waste to pellet production
•The pellet plants generate 534.7–732.3 kg CO
2-eq/tonnepelletper hour, in which Scope 1 (i.e., direct emissions)is the major
emission scope due to high emissions from wastewater production (169.2–439.0 kg CO
2-eq/tonnepelletper hour) and
dryingfuel combustion (87.1–214.5 kg CO
2-eq/tonnepelletper hour).
•Empty fruit bunch pellet and oil palm trunk pellet are recommended to co-fire with coal to phase down coal usage in achieving
carbon neutrality
Past Publications Sharing | GHG Protocol + LCA for Net-Zero
Sci. Total Environ., 856, 159007 (2023)

31. | 31
There is a significant gap in understanding of how solid waste emissions affect the
progress towards climate goals like the Paris Agreement and the Global Methane Pledge
Potential of global MSW system to mitigate emissions
Paris Agreement goals
Global Methane Pledge
•Addressthe unprecedented climate crisis.
•Monitor progress toward long-term climate
goals.
•Support policymakers in developing
methane mitigation strategies.
Past Publications Sharing | Global MSW Emissions for Net-Zero Warming

32. | 32
Can the global waste emissions achieve net-zero warming futures?
Past Publications Sharing | Global MSW Emissions for Net-Zero Warming
Science, 382 (6672), 797-800 (2023)

33. | 33
The methodology of this study is divided into 4 steps to achieve the research objective
•Collect socioeconomicand MSWdata (divided into high-income, upper-middle income, lower-middle income, and low income)
•Calculate the GHG emissions from MSW disposal and treatment using a bottom-up approach according to the Intergovernmental
Panel on Climate Change (IPCC) guidelines
•Predict MSW generation by 2050 using the panel data regression model with projected population and GDP per capita based on
Shared Socioeconomic Pathways (SSPs)
•Assess the GHG emissions reduction potential of business-as-usual and mitigation scenarios based on the cumulative emissions
budget for the global MSW system (1.7% of the total GHG emissions)
•Optimize model hyperparameters for minimizing root mean square error of the predictions using Bayesian optimization
•Forecast GHG emissions from 2021-2050 based on Shared Socioeconomic Pathways using the ensemble learning approach to
reduce the forecast variance and generalization errors
Step 1: Data collection
and GHG inventory
development
Step 2: MSW
generation forecasting
Step 3: ANN model
development,
optimization, and GHG
forecasting
Step 4: Cumulative
emissions budget
assessment based on
scenario analysis
Past Publications Sharing | Global MSW Emissions for Net-Zero Warming
Science, 382 (6672), 797-800 (2023)

34. | 34
Socioeconomic and MSW data of 43 highest MSW-generating countries and regions are
collected and their GHG emissions are calculated
•Collect socioeconomicand MSWdata (divided into high-income, upper-middle income, lower-middle income, and low income)
•Calculate the GHG emissions from MSW disposal and treatment using a bottom-up approach according to the Intergovernmental
Panel on Climate Change (IPCC) guidelines
•Predict MSW generation by 2050 using the panel data regression model with projected population and GDP per capita based on
Shared Socioeconomic Pathways (SSPs)
•Assess the GHG emissions reduction potential of business-as-usual and mitigation scenarios based on the cumulative emissions
budget for the global MSW system
•Optimize model hyperparameters for minimizing root mean square error of the predictions using Bayesian optimization
•Forecast GHG emissions based on Shared Socioeconomic Pathways using the ensemble learning approach
Step 1: Data collection
and GHG inventory
development
Step 2: MSW
generation forecasting
Step 3: ANN model
development,
optimization, and GHG
forecasting
Step 4: Cumulative
emissions budget
assessment based on
scenario analysis
Past Publications Sharing | Global MSW Emissions for Net-Zero Warming
Science, 382 (6672), 797-800 (2023)

35. | 35
MSW generation by 2050 is predicted with projected population and GDP per capita based
on Shared Socioeconomic Pathways
•Predict MSW generation by 2050 using the panel data regression model with projected population and GDP per capita based on
Shared Socioeconomic Pathways (SSPs)
•Assess the GHG emissions reduction potential of business-as-usual and mitigation scenarios based on the cumulative emissions
budget for the global MSW system
•Optimize model hyperparameters for minimizing root mean square error of the predictions using Bayesian optimization
•Forecast GHG emissions based on Shared Socioeconomic Pathways using the ensemble learning approach
Step 2: MSW
generation forecasting
Step 3: ANN model
development,
optimization, and GHG
forecasting
Step 4: Cumulative
emissions budget
assessment based on
scenario analysis
Shared socioeconomic pathways:
•Five future scenarios regarding the world’s ability to mitigate and adapt to climate change challenges.
•Narrated by five projected socioeconomic global changes (population and GDP).
Past Publications Sharing | Global MSW Emissions for Net-Zero Warming
Science, 382 (6672), 797-800 (2023)

36. | 36
Bayesian optimized artificial neural network (ANN) model is developed to forecast the GHG
emissions from waste sector based on SSPs
•Assess the GHG emissions reduction potential of business-as-usual and mitigation scenarios based on the cumulative
emissions budget for the global MSW system
•Optimize model hyperparameters for minimizing root mean square error of the predictions using Bayesian optimization
•Forecast GHG emissions from 2021-2050 based on Shared Socioeconomic Pathways using the ensemble learning approach to
reduce the forecast variance and generalization errors
Step 3: ANN model
development,
optimization, and GHG
forecasting
Step 4: Cumulative
emissions budget
assessment based on
scenario analysis
Number of neurons Learning rate
Optimal hyperparameter
combination to forecast
with lowest error (4, 0.3)
Bayesian optimization model
1
2
3
4
5
0.1
0.2
0.3
0.4
0.5
Past Publications Sharing | Global MSW Emissions for Net-Zero Warming
Science, 382 (6672), 797-800 (2023)

37. | 37
Scenario analysis is conducted to determine the GHG emissions reduction potential of the
global MSW system in business-as-usual and mitigation case
•Assess the GHG emissions reduction potential of business-as-usual and mitigation scenarios based on the cumulative emissions
budget for the global MSW system (1.7% of the total GHG emissions)
Step 4: Cumulative
emissions budget
assessment based on
scenario analysis
Cumulative emissions budget from the beginning of 2020
Temperature limit,
warming relative to pre-
industrial levels (°C)
Global MSW system (Gt CO
2-we)
50
th
percentile of TCRE
relationship
67
th
percentile of TCRE
relationship
1.5 12 11
2 27 23
Past Publications Sharing | Global MSW Emissions for Net-Zero Warming
Science, 382 (6672), 797-800 (2023)
•Emissions budget is the amount of GHG that can be
emittedfor a given level of global warming (e.g., 1.5
and 2°C).
•Calculated by climate scientists based on the
relationship between Earth’s temperature and
carbon dioxide emissions (i.e., a bestestimate of
0.45°C per 1000 Gt CO
2)
•This relationship is the transient climate response to
cumulative CO
2emissions (TCRE)
To acknowledge emissions uncertainties

38. | 38
Individual mitigation strategies can reduce the cumulative GHG emissions in 2020–2050 by
27–70% relative to business-as-usual
Past Publications Sharing | Global MSW Emissions for Net-Zero Warming
Science, 382 (6672), 797-800 (2023)

39. | 39
~27%
~70%
Past Publications Sharing | Global MSW Emissions for Net-Zero Warming
Science, 382 (6672), 797-800 (2023)
Individual mitigation strategies can reduce the cumulative GHG emissions in 2020–2050 by
27–70% relative to business-as-usual

40. | 40
•Effectiveness of mitigation scenarios varies with
the income level of countries.
•Halving waste generation is the more effective
in high-income countries (HIC).
Past Publications Sharing | Global MSW Emissions for Net-Zero Warming
Science, 382 (6672), 797-800 (2023)
Individual mitigation strategies can reduce the cumulative GHG emissions in 2020–2050 by
27–70% relative to business-as-usual

41. | 41
•Effectiveness of mitigation scenarios varies with
the income level of countries.
•Halving waste generation is the more effective
in high-income countries (HIC).
•Diverting organic waste to biological treatment
is more effective in upper-middle-income
countries (UMIC), lower-middle-income
countries (LMIC), low-income countries (LIC)
due to their higher share of organic waste.
•GHG emissions reduction potentials are
intricately linked to income groups due to
differences in biodegradable and combustible
MSW composition.
Past Publications Sharing | Global MSW Emissions for Net-Zero Warming
Science, 382 (6672), 797-800 (2023)
Individual mitigation strategies can reduce the cumulative GHG emissions in 2020–2050 by
27–70% relative to business-as-usual

42. | 42
Staying within the 1.5°C limit requires adopting more than one strategy because individual
strategies alone are insufficient
•Retrofit landfill
-marginally stays within the 2°C limit until
2050
-might not achieve the Paris Agreement
goals






























(SSP2)
Past Publications Sharing | Global MSW Emissions for Net-Zero Warming
Science, 382 (6672), 797-800 (2023)

43. | 43
Staying within the 1.5°C limit requires adopting more than one strategy because individual
strategies alone are insufficient
•Retrofit landfill
-marginally stays within the 2°C limit until
2050
-might not achieve the Paris Agreement
goals
•Compost / Half waste
-plausible in meeting the 2°C target
-significant in reducing CH
4






























(SSP2)
Past Publications Sharing | Global MSW Emissions for Net-Zero Warming
Science, 382 (6672), 797-800 (2023)

44. | 44
Adopting all three strategies could prevent overshooting the temperature limits while
resulting in a global MSW system with net-zero warming relative to 2020
•Adopting all three mitigation strategies (by
2050) can:
–allow CO
2emissions reduction of
13 ±5 Gt under 1.5°C target
27 ±5 Gt under 2°C target
–achieve net zero warming
•Integrated waste treatment system is
needed to cater for waste heterogenicity
































13 Gt CO
2-we
27 Gt CO
2-we
(SSP2)
Past Publications Sharing | Global MSW Emissions for Net-Zero Warming
Science, 382 (6672), 797-800 (2023)

45. | 45
It is important to accelerate the complete adoption of mitigation strategies in waste sector to
achieve the Global Methane Pledge
~ 80%
Past Publications Sharing | Global MSW Emissions for Net-Zero Warming
•CH
4emissions can be reduced by
up to 80%compared with the
business-as-usual upon complete
adoption of mitigation strategies by
2050.
Science, 382 (6672), 797-800 (2023)

46. | 46
It is important to accelerate the complete adoption of mitigation strategies in waste sector to
achieve the Global Methane Pledge
Past Publications Sharing | Global MSW Emissions for Net-Zero Warming
•CH
4emissions can be reduced by
up to 80%compared with the
business-as-usual upon complete
adoption of mitigation strategies by
2050.
•The designed mitigation strategies
cannot timely reduce 30% of the
CH
4emissions by 2030 relative to
2020.
Science, 382 (6672), 797-800 (2023)

47. | 47
It is important to accelerate the complete adoption of mitigation strategies in waste sector to
achieve the Global Methane Pledge
•CH
4emissions can be reduced by
up to 80%compared with the
business-as-usual upon complete
adoption of mitigation strategies by
2050.
•The designed mitigation strategies
cannot timely reduce 30% of the
CH
4emissions by 2030 relative to
2020.
•Accelerate the complete adoption of
the mitigation strategies by at least
9–17 years (by 2033–2041).
•The existing technologies are there
–but we must act fast!
Accelerate by
9–17 years
Past Publications Sharing | Global MSW Emissions for Net-Zero Warming
Science, 382 (6672), 797-800 (2023)

48. | 48
Waste circularity is a key concept in MSW management.
01
04
02
03
Integrated MSW management is important to cater for the heterogenicity and
complexity of waste, including the environmental, economic, and social perspectives.
Waste is just a misplaced resource -not a waste if we give it a second life.
There is no such thing as ‘away.’ When we throw anything away, it must go somewhere
Annie Leonard, Co-Executive Director of Greenpeace USA
Sustainable process and systems analytical approaches are vital for MSW policy making.
Simulationslet us imagine a better world and discover how we can make it real –
John Sterman, Professor of MIT Sloan Management
Conclusion | Final Remark

49. | 49
AcknowledgementAcknowledgement
Prof Fengqi You
Dr Yee Van Fan
Prof Seung JickYoo
A/P Cheng Tung Chong
Prof David Laner
Prof Uzzal Hossain
Prof Aitazaz Farooque
Prof Haslenda Hashim
Prof Chew Tin Lee
Grant Funder
Industry Partner
Fellowship Sponsor

50. | 50
[email protected]