DOI: 10.3303/CET24111112
Paper Received: 17 June 2024; Revised: 03 July 2024; Accepted: 01 August 2024
Please cite this article as: Prasara-A J., Bridhikitti A., Srinon M., Thuayjan T., Ragsasilp A., Silalertruksa T., 2024, Carbon Footprint Reduction
Measures for a Higher Educational Institution: Lessons Learned from COVID-19 Pandemic, Chemical Engineering Transactions, 111, 667-672
DOI:10.3303/CET24111112
CHEMICAL ENGINEERING TRANSACTIONS
VOL. 111, 2024
A publication of
The Italian Association
of Chemical Engineering
Online at www.cetjournal.it
Guest Editors: Valerio Cozzani, Bruno Fabiano, Genserik Reniers
Copyright © 2024, AIDIC Servizi S.r.l.
ISBN 979-12-81206-11-3; ISSN 2283-9216
Carbon Footprint Reduction Measures for a Higher
Educational Institution: Lessons Learned from COVID-19
Pandemic
Jittima Prasara-Aa,*, Arika Bridhikittib, Methawee Srinona, Thiwaporn Thuayjana,
Areerat Ragsasilpa, Thapat Silalertruksac
aFaculty of Environment and Resource Studies, Mahasarakham University, Mahasarakham, 44150, Thailand
bEnvironmental Engineering and Disaster Management Program, School of Interdisciplinary Studies, Mahidol University
Kanchanaburi Campus, Lumsum Sub-District, Saiyok District, Kanchanaburi, 71150, Thailand
cDepartment of Environmental Engineering, King Mongkut's University of Technology Thonburi, Bangkok, 10140, Thailand
jittima.p@msu.ac.th
Carbon Footprint of Organization (CFO) is a vital tool for helping promote higher education institutions towards
green university and carbon neutrality. This study assessed the carbon footprint of a faculty at a large university
located in north-eastern Thailand. The goal of this study was to estimate carbon footprints from 2015 to 2021
and to see how the COVID-19 pandemic affects carbon footprints in order to find greenhouse gas (GHG)
emission reduction measures for the post-COVID-19 period. It was found that, before the pandemic, electricity
use was the most significant GHG emissions-contributing activity. During the COVID-19 period, students’
commute reduction causes a substantial decrease in carbon footprint. After the pandemic, the institutions should
prioritize measures to reduce electricity consumption, further expand online learning opportunities, encourage
telecommuting for staff, and optimize transportation logistics to minimize GHGs.
1. Introduction
Climate change is a vast global problem that has received significant attention internationally. The Thai
government has set a goal to achieve carbon neutrality by 2050 and net-zero GHG emissions by 2065 (ONEP,
2023). Therefore, all sectors need to work together to achieve this goal. The higher education sector is one of
the critical sectors in the country, educating students and providing academic services to the community. This
sector can potentially participate in reducing greenhouse gas (GHG) emissions, helping achieve Thailand's
carbon neutrality goal. Mahasarakham University (MSU) is a large university located in the north-eastern region
of Thailand. It hosts more than 40,000 students. This university has a green university policy where the carbon
footprint is one of the indicators to be implemented for a green university (MSU, 2024).
Carbon Footprint of Organization (CFO) is the amount of greenhouse gas (GHG) emissions and removals along
the life cycles caused by an organization's operations and is measured in terms of tons or kilograms of carbon
dioxide equivalent (TGO, 2018). Carbon footprint is a complementary tool to Life Cycle Assessment (LCA),
which is a tool to assess potential environmental impacts along the life cycle of a product/service or organization.
Carbon footprint evaluates a single impact category, i.e. GHG emissions, while LCA assesses several impact
categories. CFO can be used to help identify measures to reduce GHG emissions, leading to the Thai
government's goal of carbon neutrality. In the higher education sector, the CFO has been widely used in
Thailand and international universities (Li et al., 2021). This study assessed the carbon footprint of the Faculty
of Environment and Resource Studies, MSU, as a case study. The results of the study can provide
recommendations to reduce GHG emissions for other departments with similar activities. The tools used for this
study can also guide other departments to assess their carbon footprints.
In the past few years, we have faced the epidemic of COVID-19, which has caused universities to change
activities drastically. In early 2020, MSU was closed and offered online teaching. In the later stage, employees
switched working days to reduce social distancing. In 2021, staff were allowed to work full-time while the
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university still provided online teaching. Most students did not travel to the university during that period, except
those who needed to work in a laboratory. The situation changed as a result of the outbreak of COVID-19 should
affect the amount of carbon footprint of the organization to some extent. The Faculty of Environment and
Resource Studies, MSU, started to assess the organization's carbon footprint in 2015. Therefore, this research
examines the carbon footprint from 2015 to 2021. The study identifies the primary sources of GHGs caused by
the organization in different years. It also assesses the impact of the COVID-19 epidemic on the organization's
carbon footprint. Finally, it provides measures to reduce GHG for the organization after the pandemic.
2. Methodology
This research assesses CFO following the guidelines of TGO (2018), covering the years 2015 to 2021. The
number of students enrolled in each academic year is shown in Figure 1.
2.1 Organizational boundary
This study sets organizational boundary using the control approach. This means a corporation is responsible
for all GHG emissions released from operations it controls. This control approach was chosen because the
study's results will better reflect the faculty's management. The organization's carbon footprint is expressed in
tons of carbon dioxide equivalent per fiscal year (covering September to October of the following year). For
example, fiscal year 2015 covers September 2014 to October 2015). Since the organization under study is a
governmental agency, its data are recorded every fiscal year.
2.2 Operational boundary
This step defines the scope of direct and indirect emissions within the organizational boundary. The operational
boundary is classified into three scopes, which are scope 1: direct GHG emissions, scope 2: indirect GHG
emissions, and scope 3: other GHG emissions. A list of activities contributing to GHG emissions for different
scopes is presented in Table 1. Activities in scopes 1 and 2 are compulsory to be implemented as suggested in
the guidelines, while data for scope 3 is optional. In this study, the activity data included in scope 3 were those
recorded by the organization. Note that the faculty does not own the plantation area. Hence, GHG absorption
by trees is excluded from the organizational boundary.
Table 1: List of activities along the value chain by scope
Scope Item Activity data Unit Type of data Source of data
Scope 1: Direct GHG
emissions
1.1 On-road vehicular
fuel consumption
L/year Annual report Facilities division of the faculty
1.2 Refrigerant kg/year Annual report Building division of the university
1.3 CH4 from
wastewater
treatment (Septic
tank)
kg/year Statistics Estimated using IPCC guidelines and the
number of staff and students
Scope 2: Indirect GHG
emissions
2.1 Electricity
consumption
kWh/year Annual report Building division of the university
Scope 3: Other indirect
GHG emissions
3.1 Water use m3/year Annual report Building division of the university
3.2 Paper use kg/year Annual report Facilities division of the faculty
3.3 Commute for staff km/year Survey Staff
Gasoline used in
passenger cars
L/year Estimated using average distance, number
of staff, and rate of fuel consumption
Diesel used in
pick-up trucks
L/year Estimated using average distance, number
of staff, and rate of fuel consumption
Gasoline used in
motorcycles
L/year Estimated using average distance, number
of staff, and rate of fuel consumption
3.4 Commute for
students
km/year Survey Students
Gasoline used in
passenger cars
L/year Estimated using average distance, number
of students, and rate of fuel consumption
Diesel used in
pick-up trucks
L/year Estimated using average distance, number
of students, and rate of fuel consumption
Gasoline used in
motorcycles
L/year Estimated using average distance, number
of students, and rate of fuel consumption
2.3 Inventory analysis
The activity data in Table 1 includes information that can be collected from annual reports and estimates. Data
such as fuel, refrigerant, electricity, water and paper consumption were obtained directly from the annual reports.
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Methane emissions from wastewater treatment (Septic tank) were estimated following IPCC guidelines
(Equation 6.1) (IPCC, 2006), using the number of staff and students per year. The commute of staff and students
was calculated using surveys and the number of staff and students per year. The travel distances of
students/staff in the unit of km/year were estimated using surveys. The average round-trip distance for each
type of vehicle was calculated using the formula below:
Avg D =
∑ 𝐷𝑖𝑛
𝑖=0
𝑛
(1)
where; Avg D = Average distance for each vehicle type (km); Di = distance for round-trip to work for staff/student
i (km); n = number of staff/students interviewed (persons).
After getting the average distance traveled for each type of vehicle, the total distance traveled by each type of
vehicle is calculated each year using the formula below:
Dty = Avg D × N × d (2)
where; Dty = total distance for each vehicle type per year (km); Avg D = average distance for each vehicle type
(km); N = number of total staff/students registered in a year (persons); d = number of working days in a year
(days).
After the total travel distance of each type of vehicle per year is calculated, it is used to estimate the amount of
fuel consumption of each vehicle type using the formula below:
Fq = Dty / Fcr (3)
where; Fq = total quantity of fuel consumption for each vehicle type per year (L); Dty = total distance for each
vehicle type per year (km); Fcr = Fuel consumption rate for each vehicle type per year (km/L). The fuel
consumption rate is obtained from TGO (2022).
2.4 Carbon footprint assessment
After obtaining the activity data in Table 1, the carbon footprint can be calculated using the formula below (TGO
2018):
GHG emissions = Activity data × Emission factor (4)
Emission factors were obtained from TGO (2022).
2.5 GHG reduction measurement plan
After getting the carbon footprint from the previous step, the sources contributing to GHG emissions in each
scope were considered to identify measures to reduce GHG emissions for the organization after the COVID-19
period.
3. Results and Discussion
The first part of this section presents the amounts of GHGs from the organization's activities for the years 2015-
2021. The second part discusses the impacts of the COVID-19 outbreak on carbon footprints.
3.1 Organizational carbon footprint per capita
The estimated annual carbon footprints, encompassing both direct and indirect emissions, prior to the first
confirmed death from COVID-19 in 2020 (years 2015 to 2019), ranged from 0.35 to 0.37 t CO2eq per capita
(see Figure 1). This value is comparable to the carbon footprint of Huachiew Chalermprakiet University, Thailand
(0.42 t CO2eq per capita) (Rodtusana, 2013). However, the average carbon footprint per capita of other Thai
universities appears to be higher than that reported in this study. For instance, Aroonsrimorakota (2019)
reported it as 1.85 t CO2eq per capita, and Janangkakan et al. (2019) reported it as 1.08 t CO2eq per capita.
Scope 3 GHGs significantly influence these variations. Since scope 3 indirect GHG emissions consist of 15
categories, which are complex and so far have not yet been mandatory for CFO certification by TGO (2018),
the inclusion of activity data within scope 3 may vary across different organizations. The incorporation of more
activity data will result in higher carbon footprint values. Nevertheless, organizations stand to benefit from
including additional activity data in their assessments, as it provides valuable information for devising effective
GHG reduction plans.
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Figure 1: Number of students registered and staff and carbon footprint per capita in different academic years
Electricity consumption stands out as the primary contributor to greenhouse gas emissions. As depicted in
Figure 2, scope 2, representing electricity consumption, accounted for the largest proportion (39 % to 41 %) of
the total carbon footprint emissions during normal years (2015 to 2019). This finding aligns with results from
carbon footprint studies conducted at other universities both within and outside Thailand. These studies
consistently identified electricity consumption as the predominant source of GHGs for their respective
organizations. For instance, Clemson University, USA (Clabeaux et al., 2020), University of the Punjab,
Pakistan (Haseeb et al., 2022) and Sakarya University, Turkey (Yigit and Şeneren, 2023). Similar findings were
reported for other Thai universities, such as Mahidol University (Aroonsrimorakota, 2019) and Chulalongkorn
University (Janangkakan et al., 2019).
Figure 2: Carbon footprints (CF) of the faculty categorized into different GHG emission scopes for 2015-2021
3.2 Effects of the COVID-19 pandemic on the carbon footprints of the faculty
In early 2020, MSU closed its campus, allowing staff and students to work remotely for three months, followed
by a transition to online teaching for the rest of the year. Concurrently, support staff adjusted their schedules to
facilitate social distancing measures for the remainder of 2020. In 2021, the university sustained online teaching
throughout the year, while support staff returned to full-time on-site work. Lecturers had the option to teach
online either from their workplace or home between 2020 and 2021. Throughout this period, laboratory services
continued operating to facilitate on-site practices for both students and staff. Despite the persistent COVID-19
outbreak in 2021, the carbon footprint decreased to 0.29 t CO2eq per capita (Figure 1), reflecting a reduction of
approximately 17% to 22%. This decline was slightly less pronounced than that reported for a UK University,
which saw a nearly 30% decrease during the COVID-19 lockdown (Filimonau et al., 2021).
As shown in Figure 2, direct GHGs in scope 1 accounted for 28% to 31% of the total carbon footprint during
normal years. However, during the COVID-19 pandemic, scope 1 GHGs notably increased to 38% of the total
in 2020 and 46% in 2021. In contrast, indirect GHGs in scope 3—including water consumption, paper usage,
and transportation of staff and students—experienced a significant reduction from 83 to 97 t CO2eq per year
during normal years to 35 t CO2eq in 2020 and 17 t CO2eq in 2021.
Figure 3 illustrates that from 2019 to 2020, student transportation was the largest GHG contributor for scope 3.
While, in 2021 when online teaching was practiced for the entire year, staff transportation accounted for the
largest fraction of scope 3 GHGs. Online teaching, eliminating the need for student travel to campus, significantly
contributes to GHG reduction. Similarly, El Geneidy et al. (2021) observed that travel-related emissions are the
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primary GHG sources for knowledge organizations. This is similar to an onsite conference setting; Polgar and
Elekné Fodor (2023) reported that participant transportation is the largest GHG source for the conference,
accounting for almost 70 percent of the total carbon footprint of the national scientific student conference in
Hungary. Online teaching during the pandemic also reduces electricity, paper, and water usage at the faculty,
although electricity consumption has shifted to home use. However, this is excluded from our study's
calculations as it falls outside the organizational boundary. It is crucial to carefully consider the carbon footprint
of online learning at home when devising policies (Filimonau et al., 2021).
The decline in GHGs from 2020 to 2021 could be attributed to demographic shifts towards an aging society and
the COVID-19 outbreak. The decrease in student numbers from 2017 to 2019, is not directly linked to the
pandemic, but is likely due to a low birth rate (Prasartkul et al., 2019). Based on the coefficient of determination,
R², for linear regression models between student and staff numbers and carbon footprint emissions for normal
years (2015 to 2019) in Figure 4, the decline in students and staff could explain approximately 75.5%, 98.5%,
and 99.9% of the variations in scope 1, 2, and 3 GHG emissions, respectively. Assuming student enrollment
remained unaffected by the pandemic, the impact of organizational behavior changes attributed to COVID-19
on GHG emissions could account for small fractions, as implied from the linear model in Figure 4. Notably, GHG
per capita per year during normal years tended to increase with decreasing student and staff numbers, indicating
poorer energy efficiency. These findings underscore the significant role of students and staff in GHG emissions
reduction and advocate for adopting energy-efficient approaches after COVID-19 to enhance institutional low-
carbon plans.
Figure 3: Breakdown of scope 3 carbon footprints for 2019-2021
Figure 4: Linear regressions models and corresponding coefficients of determination (R2) between the number
of students and staff for the pre-epidemic period (2015 to 2019) and carbon footprints (CF) for different scopes
4. Conclusions
This study assessed the carbon footprint of the Faculty of Environment and Resource Studies, Mahasarakham
University, Thailand, to identify measures to reduce GHG emissions for teaching units in the university after the
pandemic. This research examined the carbon footprints from the fiscal years 2015-2021. During 2020-2021,
universities were affected by the COVID-19 outbreak, causing changes in teaching modes. The results found
that between 2015 and 2019, the total carbon footprints tended to decline over the years. However, in 2020 and
2021 (during the pandemic), the total carbon footprint has significantly decreased. During 2015-2019, the
leading cause of GHGs is electricity use. During the course of online teaching throughout 2021, electricity
consumption was reduced by more than 25 percent of the pre-epidemic period. This is due to the shift to home
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electricity usage. In 2021, the scope 3 carbon footprint decreased from 2019 by almost 80 percent, mainly due
to the reduction of students' commutes. The university has returned to work on-site since 2022. Therefore, the
most critical GHG reduction measure that the university should take is to reduce electricity consumption, such
as implementing energy-efficient technologies, optimizing building energy management systems, promoting
energy conservation behaviors among staff and students, and investing in renewable energy sources like solar
or wind power. Educational institutions can consider integrating pandemic-induced changes, such as online
teaching and remote work arrangements, to minimize GHGs from commuting. This could support the green
university and lead to carbon neutrality.
Acknowledgments
This work was supported by Mahasarakham University (Contract No. 5905042). The authors also thank the staff
and students of the Faculty of Environment and Resource Studies, and the staff of the Building Division of
Mahasarakham University for providing useful information for this research work.
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Carbon Footprint Reduction Measures for a Higher Educational Institution: Lessons Learned from COVID-19 Pandemic