Shipping Emission Inventory Preparation with AIS Data: A Stratified Random Sampling Method

Xianhua Wu ()
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Xianhua Wu: Shanghai Maritime University, School of Economics and Management

Chapter Chapter 2 in Environmental Disaster in China, 2026, pp 27-51 from Springer

Abstract: Abstract Shipping emission inventory is the basis of regional air pollution assessments and pollution prevention and control policies. The accuracy depends to a large extent on the calculation results of every single ship based on AIS. This paper establishes a regional stratified sampling emission model based on the emission calculation of every single ship to improve the efficiency and precision of regional shipping emission inventory preparation. It performs calculations according to waterway characteristics, ship types and main engine power. The key findings of this paper include (1) the fast algorithm calculates exhaust emissions using complete ship information, helping reduce the uncertainty caused by the absence of single ship parameters during estimation, (2) when the ship sampling ratio is not lower than 1/3, the relative error of emission results is less than 3% and (3) the preparation of shipping emission inventory using the fast algorithm significantly improves the calculation efficiency and accuracy.

Keywords: Shipping emissions; Emission inventory; Stratified sampling; AIS big data; STEAM model; Efficiency and accuracy (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-92-0910-1_2

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DOI: 10.1007/978-981-92-0910-1_2

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