From Carbon Inventory to Carbon Governance: 
A Comparative Case Study of Carbon Hotspots and Reduction Strategies in Taiwanese Schools

Yu Tsai Cheng; Wei-Hung Chen

doi:doi:10.11648/j.sr.20261406.19

Research Article |

| Peer-Reviewed

From Carbon Inventory to Carbon Governance: A Comparative Case Study of Carbon Hotspots and Reduction Strategies in Taiwanese Schools

Yu Tsai Cheng^*, Wei-Hung Chen

Published in Science Research (Volume 14, Issue 6)

Received: 30 September 2026 Accepted: 26 October 2026 Published: 10 November 2026

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Abstract

This study adopts one junior high school and one elementary school in Kaohsiung City, Taiwan, as comparative cases to establish organizational greenhouse gas (GHG) inventories in accordance with ISO 14064-1: 2018. By analyzing emission structures, standardized carbon emission intensities, carbon hotspots, and data quality, the study explores feasible pathways for transitioning from “carbon inventory” to “carbon governance.” The total GHG emissions of the two schools were 536.981 and 692.726 tCO₂e/year, respectively, with purchased electricity accounting for more than half of total emissions in both schools (54.75% and 53.31%). In the junior high school, secondary emission hotspots included upstream emissions associated with electricity generation, commuting by faculty and staff, and fugitive emissions from R-410A refrigerant. In contrast, methane emissions from septic tanks represented a distinctive hotspot in the elementary school, accounting for 20.05% of total emissions, primarily because wastewater was not collected and conveyed to the municipal wastewater treatment system. The annual GHG emission intensities per student were 306.496 and 342.425 kgCO₂e/student-year, while the emission intensities per unit of floor area were 13.296 and 19.364 kgCO₂e/m²-year, respectively. The findings indicate that inter-school comparisons should not rely solely on total emissions; rather, they should integrate emission intensity indicators, hotspot distribution, data quality, and managerial controllability. Based on these findings, this study proposes a carbon governance cycle consisting of “inventory–hotspot identification–prioritization–carbon reduction actions–monitoring and improvement–environmental education.” This framework provides a practical reference for future carbon reduction decision-making and carbon governance in primary and secondary education settings.

Published in	Science Research (Volume 14, Issue 6)
DOI	10.11648/j.sr.20261406.19
Page(s)	449-456
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2026. Published by Science Publishing Group

Keywords

Campus Carbon Inventory, Carbon Governance, Carbon Emission Hotspots, ISO 14064-1, Carbon Reduction Strategies, Sustainable Campus

1．引言

巴黎協定確立了全球氣候變化治理的長期目標，並通過國家自主貢獻、定期報告與全球盤點等安排，推動各方持續檢視減排進展、提升後續行動力度

[11]

。這項國際政策框架凸顯了排放信息透明化、持續追蹤與逐步改善的重要性，但並未直接規定個別學校的盤查程序。從校園管理角度延伸思考，國民中小學同時具備公共建築及環境教育場域的雙重屬性，日常運行涉及用電、燃料、冷媒、交通及廢棄物等排放相關活動，亦承擔培養學生永續素養的教育任務。因此，本研究將國際氣候治理所強調的長期性與透明度，作為理解校園碳治理必要性的背景，而非據此推論任何單一學校的減排績效。ISO 14064-1 可建立排放清冊，但「完成盤查」並不等同「形成治理」。臺灣基層學校常面臨專業人力不足、活動數據分散、部分排放源缺乏長期紀錄，以及盤查後缺少持續改善機制等問題

[1, 2, 7]

。

本研究提出四項問題：RQ1不同教育階段校園的排放結構有何差異？RQ2兩校主要碳排熱點為何？RQ3 經學生人數與樓地板面積標準化後，排放強度有何差異？RQ4 如何結合碳盤查、熱點與資料缺口建立可操作的校園碳治理模式？研究貢獻在於以K-12真實盤查資料補充實證研究，並建立「總量—強度—熱點—資料品質—治理優先」分析鏈，將Whole-school／Whole Institution Approach所強調的治理、參與與持續改善連結至校園碳盤查結果

[3, 6, 9, 10]

。

2．文獻回顧與理論基礎

2.1．盤查、強度與熱點

ISO 14064-1:2018強調組織與報告邊界、排放源識別、活動數據、排放系數，以及相關性、完整性、一致性、準確性與透明度

[7]

。世界資源研究所與世界可持續發展工商理事會提出的《溫室氣體覈算體系：企業覈算與報告標準》（GHG Protocol Corporate Standard），以相關性、完整性、一致性、透明度及準確性為五項核心覈算與報告原則

[12]

。其中，相關性強調排放信息須符合使用者的決策需求；完整性要求說明既定邊界內的排放來源及排除事項；一致性有助於不同年度的可比性；透明度要求披露數據來源與估算假設；準確性則著重盡可能降低系統性偏差及不確定性。雖然該標準主要針對企業組織，相關覈算原則仍可作為本研究檢視學校活動數據與盤查文件質量的參考。因此，本研究在比較排放總量之外，亦重視數據來源、估算依據與跨年度追蹤所需的一致性。Chaer等人（2025）針對教育建築能源效率、智慧技術整合及建築使用者行為進行系統性文獻回顧，指出建築的能源使用不僅與設備技術有關，也受到佔用情境、環境條件及使用者行為影響

[4]

。研究同時討論智慧能源系統實施時的成本、維護、教育與訓練等障礙，說明節能改善不應僅限於設備汰換，而應綜合考慮使用管理與技術可行性。將此觀點應用於本研究的校園情境，可以解釋為何外購電力雖為兩校共同的最大碳排熱點，治理建議仍需進一步區分空調設定、用電行為、設備效率及監測管理等可控措施；但上述建議屬於本研究的治理推論，並非該綜述直接驗證兩所案例學校的結果。校園碳足跡及生命週期研究則顯示，僅觀察能源或總排放量，可能忽略交通、採購等間接排放；不同學生人數與建築規模亦使總量難以直接比較

[5, 8]

。因此，每生與每平方米排放強度可改善跨校比較，而熱點分析可把“排放量排序”進一步轉化為“治理優先排序”。

2.2．Whole-school 治理與資料品質

Whole-school／Whole Institution Approach強調治理、管理、課程、社區、能力建設、組織文化與學生參與

[6, 9, 10]

。聯合國教科文組織（UNESCO）於2024年發佈的《綠色學校質量標準》（Green School Quality Standard）將學校永續轉型歸納為四個彼此關聯的面向：學校治理、設施與運營、教學與學習，以及社區參與

[14]

。其中，設施與運營涵蓋能源與用水管理、廢棄物、交通、採購及建築運行等活動，強調環境行動不僅是一項課程主題，也應落實於學校日常制度與資源配置。在本研究中，這套標準提供了由碳排清冊走向治理的概念性依據：學校可將高排放來源、數據缺口及可控改善項目納入行政討論，並以跨部門合作推動持續改善。然而，該標準屬於學校永續管理指引，不能直接替代ISO 14064-1的排放覈算規則。UNESCO同年發佈的《綠色課程指引：為氣候行動而教與學》（Greening Curriculum Guidance）強調氣候教育應具行動導向、科學內容、整體性與公正性，並針對不同年齡層規劃認知、社會情意及行為層面的學習成果

[15]

。因此，校園碳盤查資料可進一步轉化為學生可理解的學習素材，例如比較校園用電熱區、討論交通行為與排放的關係，或參與節能成效的觀察與記錄。這些應用是本研究根據該指引提出的教育實踐建議，而非UNESCO對本研究兩所學校所作的實證評估。另一方面，活動數據的完整性與可追溯性會影響熱點識別、年度比較與減碳成效判讀；校園碳排覈算及不確定性研究也指出，應明確管理估算數據及相關不確定性

[13]

。據此，本研究將數據質量視為治理能力的一部分。

2.3．分析架構

本研究整合文獻形成六項治理構面：治理與領導、盤查與資料能力、熱點辨識與優先決策、減碳行動、監測與持續改善、全校參與與環境教育。實證分析聚焦於清冊、強度、熱點與資料品質；治理構面則用以說明如何把盤查資訊轉化為可持續決策。

3．研究方法

3.1．案例、邊界與資料

本研究採比較案例研究法，以高雄市同區域一所國中（Case A）與一所國小（Case B）為案例，以降低區域氣候、政策與基礎設施差異。Case A有學生1,752人、樓地板面積40,387.04 m²；Case B有學生2,023人、樓地板面積35,773 m²。盤查年度為民國114年，依ISO 14064-1 Category 1-6分類。活動數據來源包含電費與水費帳單、設備與冷媒紀錄、燃料與廢棄物資料、採購與運輸資料，以及必要之現場訪談與合理推估。

資料處理優先使用正式帳單、原始紀錄或直接量測；無完整紀錄之來源，保留推估依據與計算假設，並以Data Quality Gap Matrix檢視是否直接量測、是否具正式帳單、是否需推估及資料完整性。

3.2．排放量、強度與治理指標

學校i之排放源j及年度總排放量計算如下：

E_{ij} = {AD}_{ij} \times {EF}_{j} \times {GWP}_{j}

(1)

E_{i} = \sum_{j = 1}^{n} E_{ij}

(2)

其中AD為活動數據、EF為排放係數、GWP為全球暖化潛勢。為降低規模差異，建立以下標準化指標：

{CI}_{student, i} = \frac{E_{i} \times 1000}{N_{i}}

(3)

{CI}_{area, i} = \frac{E_{i} \times 1000}{A_{i}}

(4)

{EI}_{i} = \frac{{EC}_{i}}{N_{i}}

(5)

熱點貢獻率、減碳潛力與邊際減碳成本（MAC）為：

Contribution (%) = \frac{E_{ij}}{E_{i}} \times 100 %

(6)

{RP}_{ij} = E_{ij} \times r_{ij}

(7)

{MAC}_{ij} = \frac{(C_{ij} - S_{ij})}{{RP}_{ij}}

(8)

進一步以概念性CGPI 整合排放貢獻（HC）、減碳潛力（RP）、管理可控性（MC）、資料品質（DQI）與成本效益（CE）：

{CGPI}_{ij} = w_{1} {HC}_{ij} + w_{2} {RP}_{ij} + w_{3} {MC}_{ij} + w_{4} {DQI}_{ij} + w_{5} {CE}_{ij}

(9)

其中 Σwₖ=1、wₖ≥0。因本研究尚未取得所有措施的完整投資成本、效益與權重，MAC 與 CGPI 用於決策框架而非最終量化排名。

4．研究結果

4.1．兩校基本資料、排放結構與標準化強度

為避免濃縮稿僅呈現結論而缺乏實證主體，本節將兩校基本條件、排放結構與標準化指標併列比較。

表1 兩校基本資料與標準化排放指標。

比較指標	OO 國中	△△國小
學生人數	1,752 人	2,023 人
教職員人數	165 人	136 人
樓地板面積	40,387.04 m²	35,773 m²
總排放量	536.981 tCO₂e	692.726 tCO₂e
每生年排放強度	306.496 kgCO₂e/人·年	342.425 kgCO₂e/人·年
每m² 年排放強度	13.296 kgCO₂e/m²·年	19.364 kgCO₂e/m²·年
每生年用電強度	359.299 kWh/人·年	390.856 kWh/人·年

表2 兩校溫室氣體排放結構比較。

排放類別	OO 國中/tCO₂e	占比	△△國小/tCO₂e	占比
Category 1	57.77	10.76%	160.50	23.17%
Category 2	293.97	54.75%	369.26	53.31%
Category 3–6	185.24	34.50%	162.96	23.53%
總計	536.981	100%	692.726	100%

OO國中年度總排放量為536.981 tCO₂e，△△國小為692.726 tCO₂e，國小高約29%。兩校均以Category 2外購電力為主要來源（54.75%、53.31%），但Category 1分別為10.76%與23.17%，顯示△△國小具有較高比例的直接排放。經學生人數與樓地板面積標準化後，△△國小的排放強度仍較高，因此差異不能單純歸因於校園規模。

4.2．碳排熱點與跨案例比較

表3 兩校主要碳排熱點比較。

排名	OO 國中排放源	tCO₂e	占比	△△國小排放源	tCO₂e	占比
1	外購電力	293.9728	54.75%	外購電力	369.2578	53.31%
2	電上游	87.3735	16.27%	化糞池	138.8723	20.05%
3	員工通勤	58.7316	10.94%	電力上游	109.7494	15.84%
4	R-410A 冷媒	54.8208	10.21%	R-32 冷媒	20.7399	2.99%
5	教科書生產	29.4032	5.48%	員工通勤-汽車	14.1667	2.05%
6	一般廢棄物	6.7170	1.25%	員工通勤-機車	12.5542	1.81%

OO國中前四大熱點為外購電力、電力上游、員工通勤及R-410A 冷媒逸散，合計超過九成；△△國小則為外購電力、化糞池、電力上游及R-32 冷媒，其中化糞池甲烷占20.05%，形成與OO國中顯著不同的直接排放特徵。

表4 兩校排放特徵與治理重點之跨案例比較。

比較面向	OO國中	△△國小
排放型態	Category 2 主導；其他間接排放較高	Category 2 主導，但 Category 1 明顯偏高
主要次要熱點	電力上游、通勤、冷媒	化糞池、電力上游、冷媒
治理可控項目	用電管理、空調/冷媒、通勤	用電管理、污水/化糞池、冷媒
資料管理重點	通勤、冷媒、機具燃料	化糞池/污水、通勤、廢棄物
優先治理方向	能源效率＋冷媒/交通管理	能源效率＋污水設施改善

比較結果顯示，同樣以外購電力為第一大熱點，並不代表兩校可採相同治理策略。OO國中的通勤與冷媒逸散可由交通管理、設備維護與冷媒管理介入；△△國小的化糞池則涉及污水處理與基礎設施，治理工具與一般節能措施不同。

4.3．資料品質與治理優先性

表5 Data Quality Gap Matrix（資料品質缺口矩陣）。

排放源	主要資料來源	資料品質	主要缺口	改善方式
電力	正式帳單	高	缺口小	年度彙整／持續追蹤
用水	正式帳單	高	缺口小	年度彙整／持續追蹤
食材運輸	推估／紀錄	中	距離與重量紀錄不足	每日/批次登錄
廢棄物	推估	待改善	缺乏實際秤重	定期秤重
機具燃料	推估／單據	中	使用紀錄不足	建立油料紀錄
冷媒	設備清冊／維修紀錄	中	補充量與逸散紀錄不足	建立設備履歷
部分通勤	訪談／推估	中	距離與運具變動	定期更新調查

表6 兩校主要治理優先項目之實證判讀（未進行MAC／CGPI數值排名）。

治理項目	OO 國中實證依據	△△國小實證依據	可控性判讀	建議優先行動
外購電力	54.75%（最大熱點）	53.31%（最大熱點）	高（校內用電）／低（電力結構）	節電、空調設定、設備效率
冷媒管理	R-410A 10.21%	R-32 2.99%	高	設備履歷、維護與洩漏管理
通勤	員工通勤 10.94%	汽 2.05%＋機車 1.81%	中	通勤調查、低碳運具與共乘
污水／化糞池	非主要熱點	化糞池20.05%	中至高（視納管條件）	評估納管、設施改善與操作管理
資料治理	部分來源需推估	部分來源需推估	高	建立常態紀錄與年度追蹤

資料品質分析顯示，電力與用水因具有正式帳單與明確使用期間，完整性與可追溯性最高；冷媒補充、機具燃料、廢棄物、食材運輸及部分通勤資料較依賴行政紀錄、訪談或推估，年度一致性較弱。這類缺口即使不影響當年度完成清冊，仍會降低後續年度比較與減碳成效判讀的可信度。

結果亦顯示，「排放量最高」不必然等同「治理優先」。外購電力雖為共同最大來源，但電力上游受整體電力結構影響，學校直接可控性有限；相較之下，用電管理、空調設定、冷媒維護與設備汰換較具直接可控性。△△國小之化糞池兼具高排放貢獻與設施特定性，若具污水納管或設施改善條件，應與能源管理並列優先。

因此，治理排序至少應同時考量排放貢獻、減碳潛力、管理可控性、資料品質與成本效益。這也是本研究提CGPI概念架構的目的：把熱點由「看見排放」進一步轉為「選擇行動」。

表7 兩校主要碳排熱點之累積集中程度。

累積熱點範圍	OO國中	△△國小	比較意義
最大單一來源	54.75%	53.31%	兩校皆由外購電力主導
前三大來源	81.96%	89.20%	國小排放更集中於少數來源
前四大來源	92.17%	92.19%	兩校前四大來源均逾九成
前六大來源	98.90%	96.05%	治理資源可聚焦於少數關鍵熱點

表8 依兩校實證熱點形成之分期治理策略。

治理期間	OO國中重點	△△國小重點	共同治理原則
短期	用電行為、空調設定、冷媒紀錄、通勤資料	用電行為、化糞池操作管理、冷媒紀錄	優先採低成本且高可控措施
中期	高耗能設備汰換、冷媒洩漏管理、通勤方案	污水/化糞池改善、空調設備效率提升	依熱點與設備年限配置資源
長期	年度盤查與強度KPI、交通與設備制度化	污水納管可行性、年度盤查與強度KPI	形成「盤查—行動—監測」閉環

5．討論

5.1．排放特徵與熱點形成

研究結果顯示，教育階段本身不足以完全解釋排放差異；基礎設施、設備條件與營運型態才是形成熱點的重要因素。兩校皆以外購電力為核心，但OO國中次要熱點集中於電力上游、通勤與冷媒，△△國小則出現化糞池甲烷的顯著直接排放。此結果支持校園減碳採差異化治理，而非以單一節能方案覆蓋所有學校。從治理角度看，學校應先確認高排放項目是否屬於自身可直接控制；若屬上游電力結構等低可控來源，應改以降低實際用電需求作為間接策略；若屬冷媒、通勤或污水設施等高可控來源，則可設計具體管理措施。

5.2．「總量—強度—熱點」之方法意義

總排放量適合描述整體規模，但無法公平比較不同學生人數與建築面積的學校；標準化強度改善可比性，但仍不能回答有限資源應先投入何處；熱點分析則補足治理排序功能。因此三者應交互使用，而非以單一指標評判校園減碳績效。

5.3．資料品質與治理能力

資料品質並非盤查後端的技術細節，而是治理能力的一部分。當高排放來源同時高度依賴推估，學校必須同時改善「排放」與「數據」。建立冷媒履歷、機具燃料紀錄、廢棄物秤重、食材運輸登錄與通勤定期更新，可使一次性盤查轉化為可持續的治理資訊。換言之，校園碳治理除了回答「哪些來源應優先減量」，也必須回答「哪些來源的資料應優先改善」；沒有穩定的基準資料，減碳成效即難以被可信地證明。

5.4．從盤查走向治理

綜合實證與Whole-school／Whole Institution Approach，本研究將校園碳治理界定為「盤查—資料品質確認—熱點辨識—優先排序—減碳行動—持續監測—環境教育」之循環。其核心不是追求單一最低排放數字，而是把排放資訊嵌入行政決策、設備管理、師生參與與年度改善。

6．結論與建議

6.1．主要結論

本研究獲得四項主要結論：（1）外購電力是兩校共同核心熱點，但次要熱點具有高度校園特定性；（2）經學生人數與樓地板面積標準化後，△△國小排放強度仍較高，證明跨校比較不宜僅依總量；（3）資料品質決定盤查結果能否支援年度追蹤與治理；（4）治理優先性應整合排放貢獻、減碳潛力、管理可控性、資料品質與成本效益。整體而言，碳盤查的價值不在於完成一份清冊，而在於能否把清冊轉化為資源配置與持續改善的決策依據。

6.2．實務與政策意涵

學校應建立活動數據常態管理、依熱點配置有限資源、以排放強度輔助績效追蹤，並把盤查結果轉化為可供師生參與的環境教育。教育主管機關可建立國中小標準化盤查模板、最低資料要求與年度追蹤格式，並依各校熱點差異設計節能、冷媒管理、污水處理或設備改善等差異化補助機制。

在績效管理上，不宜以年度總排放量直接進行校際排名；較適宜的作法是同時呈現每生、每平方米排放強度與主要熱點結構，使規模差異與設施差異能被分開解讀。對學校而言，短期可優先推動空調設定、非使用時段關機、冷媒維護與資料紀錄等低成本措施；中長期則依設備年限、污水設施條件與成本效益決定資本改善順序。

6.3．理論與方法意涵

本研究在理論上區分「碳盤查」與「碳治理」：前者建立排放資訊，後者則要求把資訊納入優先排序、資源配置、行動與持續監測。方法上則將總量、標準化強度、熱點與資料品質串聯，避免僅以單一指標解讀校園碳績效。資料品質的納入亦說明，治理能力不只反映是否能減碳，也反映學校是否具備持續產生可信資訊的制度能力。

6.4．研究限制與未來方向

本研究限制包括僅有兩所同區域案例、部分間接排放需推估、僅有單一年度資料，以及MAC與CGPI尚未完成完整成本與權重驗證。兩校建築年代、設備效率、污水處理方式與使用行為亦可能同時影響排放結果，因此本研究不宜把差異單純歸因於教育階段。

未來可擴充不同縣市、規模與類型學校，建立多年度追蹤資料與基準值；進一步蒐集設備投資、維護成本、節能效益與減碳量，量化MAC；並透過專家法或多準則決策方法驗證CGPI權重與敏感度。另可發展校園碳治理成熟度與全校參與量表，檢驗治理能力、師生參與與實際排放績效之關聯。

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Cheng, Y. T., Chen, W. (2026). From Carbon Inventory to Carbon Governance: A Comparative Case Study of Carbon Hotspots and Reduction Strategies in Taiwanese Schools. Science Research, 14(6), 449-456. https://doi.org/10.11648/j.sr.20261406.19

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Cheng, Y. T.; Chen, W. From Carbon Inventory to Carbon Governance: A Comparative Case Study of Carbon Hotspots and Reduction Strategies in Taiwanese Schools. Sci. Res. 2026, 14(6), 449-456. doi: 10.11648/j.sr.20261406.19

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Cheng YT, Chen W. From Carbon Inventory to Carbon Governance: A Comparative Case Study of Carbon Hotspots and Reduction Strategies in Taiwanese Schools. Sci Res. 2026;14(6):449-456. doi: 10.11648/j.sr.20261406.19

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@article{10.11648/j.sr.20261406.19,
  author = {Yu Tsai Cheng and Wei-Hung Chen},
  title = {From Carbon Inventory to Carbon Governance: 
A Comparative Case Study of Carbon Hotspots and Reduction Strategies in Taiwanese Schools},
  journal = {Science Research},
  volume = {14},
  number = {6},
  pages = {449-456},
  doi = {10.11648/j.sr.20261406.19},
  url = {https://doi.org/10.11648/j.sr.20261406.19},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sr.20261406.19},
  abstract = {This study adopts one junior high school and one elementary school in Kaohsiung City, Taiwan, as comparative cases to establish organizational greenhouse gas (GHG) inventories in accordance with ISO 14064-1: 2018. By analyzing emission structures, standardized carbon emission intensities, carbon hotspots, and data quality, the study explores feasible pathways for transitioning from “carbon inventory” to “carbon governance.” The total GHG emissions of the two schools were 536.981 and 692.726 tCO₂e/year, respectively, with purchased electricity accounting for more than half of total emissions in both schools (54.75% and 53.31%). In the junior high school, secondary emission hotspots included upstream emissions associated with electricity generation, commuting by faculty and staff, and fugitive emissions from R-410A refrigerant. In contrast, methane emissions from septic tanks represented a distinctive hotspot in the elementary school, accounting for 20.05% of total emissions, primarily because wastewater was not collected and conveyed to the municipal wastewater treatment system. The annual GHG emission intensities per student were 306.496 and 342.425 kgCO2e/student-year, while the emission intensities per unit of floor area were 13.296 and 19.364 kgCO2e/m²-year, respectively. The findings indicate that inter-school comparisons should not rely solely on total emissions; rather, they should integrate emission intensity indicators, hotspot distribution, data quality, and managerial controllability. Based on these findings, this study proposes a carbon governance cycle consisting of “inventory–hotspot identification–prioritization–carbon reduction actions–monitoring and improvement–environmental education.” This framework provides a practical reference for future carbon reduction decision-making and carbon governance in primary and secondary education settings.},
 year = {2026}
}

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TY  - JOUR
T1  - From Carbon Inventory to Carbon Governance: 
A Comparative Case Study of Carbon Hotspots and Reduction Strategies in Taiwanese Schools
AU  - Yu Tsai Cheng
AU  - Wei-Hung Chen
Y1  - 2026/11/10
PY  - 2026
N1  - https://doi.org/10.11648/j.sr.20261406.19
DO  - 10.11648/j.sr.20261406.19
T2  - Science Research
JF  - Science Research
JO  - Science Research
SP  - 449
EP  - 456
PB  - Science Publishing Group
SN  - 2329-0927
UR  - https://doi.org/10.11648/j.sr.20261406.19
AB  - This study adopts one junior high school and one elementary school in Kaohsiung City, Taiwan, as comparative cases to establish organizational greenhouse gas (GHG) inventories in accordance with ISO 14064-1: 2018. By analyzing emission structures, standardized carbon emission intensities, carbon hotspots, and data quality, the study explores feasible pathways for transitioning from “carbon inventory” to “carbon governance.” The total GHG emissions of the two schools were 536.981 and 692.726 tCO₂e/year, respectively, with purchased electricity accounting for more than half of total emissions in both schools (54.75% and 53.31%). In the junior high school, secondary emission hotspots included upstream emissions associated with electricity generation, commuting by faculty and staff, and fugitive emissions from R-410A refrigerant. In contrast, methane emissions from septic tanks represented a distinctive hotspot in the elementary school, accounting for 20.05% of total emissions, primarily because wastewater was not collected and conveyed to the municipal wastewater treatment system. The annual GHG emission intensities per student were 306.496 and 342.425 kgCO2e/student-year, while the emission intensities per unit of floor area were 13.296 and 19.364 kgCO2e/m²-year, respectively. The findings indicate that inter-school comparisons should not rely solely on total emissions; rather, they should integrate emission intensity indicators, hotspot distribution, data quality, and managerial controllability. Based on these findings, this study proposes a carbon governance cycle consisting of “inventory–hotspot identification–prioritization–carbon reduction actions–monitoring and improvement–environmental education.” This framework provides a practical reference for future carbon reduction decision-making and carbon governance in primary and secondary education settings.
VL  - 14
IS  - 6
ER  -

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Author Information

Yu Tsai Cheng

Department of Environmental Engineering and Science, Fooyin University, Taiwan, China

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Wei-Hung Chen

Department of International Business, National Kaohsiung University of Science and Technology, Taiwan, China

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Table 1

表1 兩校基本資料與標準化排放指標。
Table 2

表2 兩校溫室氣體排放結構比較。
Table 3

表3 兩校主要碳排熱點比較。
Table 4

表4 兩校排放特徵與治理重點之跨案例比較。
Table 5

表5 Data Quality Gap Matrix（資料品質缺口矩陣）。
Table 6

表6 兩校主要治理優先項目之實證判讀（未進行MAC／CGPI數值排名）。
Table 7

表7 兩校主要碳排熱點之累積集中程度。
Table 8

表8 依兩校實證熱點形成之分期治理策略。

Plain Text BibTeX RIS

APA Style

Cheng, Y. T., Chen, W. (2026). From Carbon Inventory to Carbon Governance: A Comparative Case Study of Carbon Hotspots and Reduction Strategies in Taiwanese Schools. Science Research, 14(6), 449-456. https://doi.org/10.11648/j.sr.20261406.19

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ACS Style

Cheng, Y. T.; Chen, W. From Carbon Inventory to Carbon Governance: A Comparative Case Study of Carbon Hotspots and Reduction Strategies in Taiwanese Schools. Sci. Res. 2026, 14(6), 449-456. doi: 10.11648/j.sr.20261406.19

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AMA Style

Cheng YT, Chen W. From Carbon Inventory to Carbon Governance: A Comparative Case Study of Carbon Hotspots and Reduction Strategies in Taiwanese Schools. Sci Res. 2026;14(6):449-456. doi: 10.11648/j.sr.20261406.19

Copy | Download

@article{10.11648/j.sr.20261406.19,
  author = {Yu Tsai Cheng and Wei-Hung Chen},
  title = {From Carbon Inventory to Carbon Governance: 
A Comparative Case Study of Carbon Hotspots and Reduction Strategies in Taiwanese Schools},
  journal = {Science Research},
  volume = {14},
  number = {6},
  pages = {449-456},
  doi = {10.11648/j.sr.20261406.19},
  url = {https://doi.org/10.11648/j.sr.20261406.19},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sr.20261406.19},
  abstract = {This study adopts one junior high school and one elementary school in Kaohsiung City, Taiwan, as comparative cases to establish organizational greenhouse gas (GHG) inventories in accordance with ISO 14064-1: 2018. By analyzing emission structures, standardized carbon emission intensities, carbon hotspots, and data quality, the study explores feasible pathways for transitioning from “carbon inventory” to “carbon governance.” The total GHG emissions of the two schools were 536.981 and 692.726 tCO₂e/year, respectively, with purchased electricity accounting for more than half of total emissions in both schools (54.75% and 53.31%). In the junior high school, secondary emission hotspots included upstream emissions associated with electricity generation, commuting by faculty and staff, and fugitive emissions from R-410A refrigerant. In contrast, methane emissions from septic tanks represented a distinctive hotspot in the elementary school, accounting for 20.05% of total emissions, primarily because wastewater was not collected and conveyed to the municipal wastewater treatment system. The annual GHG emission intensities per student were 306.496 and 342.425 kgCO2e/student-year, while the emission intensities per unit of floor area were 13.296 and 19.364 kgCO2e/m²-year, respectively. The findings indicate that inter-school comparisons should not rely solely on total emissions; rather, they should integrate emission intensity indicators, hotspot distribution, data quality, and managerial controllability. Based on these findings, this study proposes a carbon governance cycle consisting of “inventory–hotspot identification–prioritization–carbon reduction actions–monitoring and improvement–environmental education.” This framework provides a practical reference for future carbon reduction decision-making and carbon governance in primary and secondary education settings.},
 year = {2026}
}

Copy | Download

TY  - JOUR
T1  - From Carbon Inventory to Carbon Governance: 
A Comparative Case Study of Carbon Hotspots and Reduction Strategies in Taiwanese Schools
AU  - Yu Tsai Cheng
AU  - Wei-Hung Chen
Y1  - 2026/11/10
PY  - 2026
N1  - https://doi.org/10.11648/j.sr.20261406.19
DO  - 10.11648/j.sr.20261406.19
T2  - Science Research
JF  - Science Research
JO  - Science Research
SP  - 449
EP  - 456
PB  - Science Publishing Group
SN  - 2329-0927
UR  - https://doi.org/10.11648/j.sr.20261406.19
AB  - This study adopts one junior high school and one elementary school in Kaohsiung City, Taiwan, as comparative cases to establish organizational greenhouse gas (GHG) inventories in accordance with ISO 14064-1: 2018. By analyzing emission structures, standardized carbon emission intensities, carbon hotspots, and data quality, the study explores feasible pathways for transitioning from “carbon inventory” to “carbon governance.” The total GHG emissions of the two schools were 536.981 and 692.726 tCO₂e/year, respectively, with purchased electricity accounting for more than half of total emissions in both schools (54.75% and 53.31%). In the junior high school, secondary emission hotspots included upstream emissions associated with electricity generation, commuting by faculty and staff, and fugitive emissions from R-410A refrigerant. In contrast, methane emissions from septic tanks represented a distinctive hotspot in the elementary school, accounting for 20.05% of total emissions, primarily because wastewater was not collected and conveyed to the municipal wastewater treatment system. The annual GHG emission intensities per student were 306.496 and 342.425 kgCO2e/student-year, while the emission intensities per unit of floor area were 13.296 and 19.364 kgCO2e/m²-year, respectively. The findings indicate that inter-school comparisons should not rely solely on total emissions; rather, they should integrate emission intensity indicators, hotspot distribution, data quality, and managerial controllability. Based on these findings, this study proposes a carbon governance cycle consisting of “inventory–hotspot identification–prioritization–carbon reduction actions–monitoring and improvement–environmental education.” This framework provides a practical reference for future carbon reduction decision-making and carbon governance in primary and secondary education settings.
VL  - 14
IS  - 6
ER  -

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