從空汙排放致生之福利成本探討國際海運減排效益

The Benefits of Reducing Emissions in International Shipping: A Perspective of Welfare Costs Attributable to Air Pollution

吳疆泠(Chiang Lead Woo)

指導教授 ： 林子倫

國立臺灣大學/理學院/氣候變遷與永續發展國際學位學程/碩士(2022年)

https://doi.org/10.6342/NTU202203663

摘要

因應2050年的全球淨零排放（Net-Zero）目標，英國勞氏海運去碳中心在2022年7月更新之《零碳石油監測報告》中，將精煉油轉型的可及應用列為最優先項目，著重三個面向的討論：技術可及的量產技術（9等級）、獎勵投資的投資可及（6等級），和確保永續溝通的溝通可及（6等級）。
此外，挪威驗船協會2022年報告指出：相對海運重油（Heavy fuel oil）空氣污染物排放，當前三種更少污染的近潔淨海運燃料，有甲醇（Methanol）、氨（Ammonia）和液化天然氣甲烷（Liquefied natural gas, LNG）；其中，可再生甲醇（Bio-methanol）之應用發展最易優先普及亦最為安全。以天然氣或氨氣作為燃料的技術，仍要3-8年才能達到量產規模。因此，本研究在海運用油轉型之際，提供3種以成本效益為主軸的空汙減排順序情境建議：相同減排量模式、人均減排量模式，和國家總減排量模式，用以降低決策偏誤，並累積碳交易或碳稅機制的論據基礎。
本研究在「共同但有差異原則」和「比較利益法則」的立論基礎下，將所有樣本國（丹麥、波蘭、瑞典、英國）視為一整體的減排單位，納入肩負不同歷史碳排的排放數據，期能為減排資金點出符合成本效益考量的減排順序。研究方法採用開放 STIRPAT 模型與嶺迴歸模型（Ridge Regression）解決空氣污染物排放之間的前驅（Precursor）效果和共線性（Multicollinearity）。資料取自國際認可之開放資料庫遴選空氣污染排放量，以R軟體分析空汙邊際治理收益，以得出最適空汙邊際治理成本（Marginal costs, MC），進行氣候變遷立法及碳交易市場之論述基礎，盼碳定價能如實反應可歸因空汙的福利成本。
因應2050年的全球淨零排放（Net-Zero）目標，英國勞氏海運去碳中心在2022年7月更新之《零碳石油監測報告》中，將精煉油轉型的可及應用列為最優先項目，著重三個面向的討論：技術可及的量產技術（9等級）、獎勵投資的投資可及（6等級），和確保永續溝通的溝通可及（6等級）。
此外，挪威驗船協會2022年報告指出：相對海運重油（Heavy fuel oil）空氣污染物排放，當前三種更少污染的近潔淨海運燃料，有甲醇（Methanol）、氨（Ammonia）和液化天然氣甲烷（Liquefied natural gas, LNG）；其中，可再生甲醇（Bio-methanol）之應用發展最易優先普及亦最為安全。以天然氣或氨氣作為燃料的技術，仍要3-8年才能達到量產規模。因此，本研究在海運用油轉型之際，提供3種以成本效益為主軸的空汙減排順序情境建議：相同減排量模式、人均減排量模式，和國家總減排量模式，用以降低決策偏誤，並累積碳交易或碳稅機制的論據基礎。
本研究在「共同但有差異原則」和「比較利益法則」的立論基礎下，將所有樣本國（丹麥、波蘭、瑞典、英國）視為一整體的減排單位，納入肩負不同歷史碳排的排放數據，期能為減排資金點出符合成本效益考量的減排順序。研究方法採用開放 STIRPAT 模型與嶺迴歸模型（Ridge Regression）解決空氣污染物排放之間的前驅（Precursor）效果和共線性（Multicollinearity）。資料取自國際認可之開放資料庫遴選空氣污染排放量，以R軟體分析空汙邊際治理收益，以得出最適空汙邊際治理成本（Marginal costs, MC），進行氣候變遷立法及碳交易市場之論述基礎，盼碳定價能如實反應可歸因空汙的福利成本。

關鍵字

防止船舶污染國際公約附錄六防止船舶空氣污染規則 ； 細懸浮微粒暴露 ； 福利成本 ； 開放STIRPAT模型 ； 政府空汙部門治理支出 ； 成本效益分析 ； 決策順序

並列摘要

To achieve the 2050 Net Zero carbon emission goal, the Lloyd’s Register Maritime Decarbonisation Hub published the report ‘Zero Carbon Fuel Monitor – July 2022 Update’ to facilitate discussions of fuels transformation. The top priority of progression in scaling technology, stimulating investment and community of ensuring sustainability focuses on the technology readiness level (TRL, 9 levels), investment readiness level (IRL, 6 levels), and community readiness level (CRL, 6 levels).
Besides, according to the report published by Det Norske Veritas (DNV), updated cleaner marine energy include Methanol, Ammonia, and LNG; meanwhile, the safest bio-methanol is easily scaled-up rapidly to date. Otherwise, the scaling technology of LNG and ammonia will be available in 3 to 8 years. Hence, this study provides 3 diverse priorities of emissions reduction based on the cost-effectiveness analyses: the same reduction mode, the mean emissions per capita mode, and national total emissions mode to reduce biases of decision-making and accumulate fundamentals of carbon emission trade systems (ETS) and carbon tax schemes.
The fundamental of this study is based on the principle of common but differentiated responsibilities and respective capabilities (CBDRRC) and the principle of comparable advantage. Meanwhile, the selected parties are regarded as a whole reduction unit, and the historical emissions are adopted to do cost-effectiveness analyses for reduction priorities of funding.
This study selects the extended STIRPAT model with ridge regression to solve the precursor effects and multicollinearity between different emissions. The data is acquired from international recognised datasets and computed by R software version 4.2.0 to get suggestive marginal government spending from the equivalent welfare saving.
These analyses can strengthen driving forces of climate change legislation and nestle up actual marine carbon price with a perspective of welfare costs attributable to emissions exposure.
The observation period in this study is from 2005 to 2013 which the span of available continuous 9 years after the start of the EU Clean Air Programme for Europe (Café programme). Also, the selective criteria include the LSCI over 40, positions and territories. The selection includes the UK with high LSCI, and the others with middle LSCI: Denmark, Poland, Sweden.
The findings of this study contain the cost-effectiveness ratios of welfare costs attributable to marine emission exposure to land-based government spending in the air sectors. Such ratios are 12.50 times in Denmark, 20.67 times in Poland, and 75.88 times in the UK; however, only 0.18 times in Sweden. It can be inferred that (1) the effect of the equivalent government spending on marine reduction in nations with high LCSI was more cost-effective than those of nations with low LCSI; (2) the country with good air quality like Sweden had low welfare saving from emissions reduction under the comparable advantage principle.
Additionally, the spending effect in Sweden could significantly reduce welfare costs attributable to emissions exposure, and that in Denmark also had negative effect but insignificantly. In terms of national emissions, only Polish welfare costs attributable to emission exposure had decoupled from its emissions of SO2, PM2.5, N2O, CH4, and CO. Besides, Polish share of fuels use in total energy consumption could significantly decrease welfare loss attributable to emissions exposure.

Nonetheless, these OECD 4 suggestively needed to add their spending on tackling marine emissions from fuels combustion, and the most increase was in the UK (2,988 USD per capita), followed by Polish (148 USD per capita), Danish (114 USD per capita), and Swedish (5 USD per capita).
Eventually, the suggestive priority of pooling emissions reduction is compiled in Table 4-6 to facilitate global, regional, and national reduction tasks for reference.

並列關鍵字

MARPOL Annex VI ； PM2.5 exposure ； Welfare costs ； the Extended STIRPAT model ； Government spending in the air sector ； Cost-effectiveness analysis ； Priority of policy-making

參考文獻

IMO, Forth IMO GHG Study. IMO, London, UK, 2020. https://wwwcdn.imo.org/localresources/en/OurWork/Environment/Documents/Fourth%20IMO%20GHG%20Study%202020%20Executive-Summary.pdf. Last visited April 10, 2022.

Barrett, S. and Dannenberg A., 2012. Climate negotiations under scientific uncertainty. Proceedings of the National Academy of Sciences, 109(43):17372–17376.

Sarah R. Cooley, Brittany Bello, Daniel Bodansky, Anthony Mansell, Andreas Merkl, Nigel Purvis, Susan Ruffo, Gwynne Taraska, Anna Zivian, George H. Leonard, 2019. Overlooked ocean strategies to address climate change, Global Environmental Change, 59:101968. https://doi.org/10.1016/j.gloenvcha.2019.101968. https://doi.org/10.1016/j.gloenvcha.2019.101968.

Jeffrey Chow, Coco Dijia Du and Xun Wu, 2022. Uncertainty and collaborative governance: the role of science in combating shipping air pollution in Hong Kong and the Greater Bay Area, China, Journal of Environmental Policy and Planning, DOI:10.1080/1523908X.2022.2044297.

The International Chamber of Shipping, 2021. A Zero Emission Blueprint for Shipping. https://www.ics-shipping.org/publication/a-zero-emission-blueprint-for-shipping/ Last visited April 10, 2022.