A sampling method for calculating regional ship emission inventories
Xin Peng, Yuanqiao Wen, Lichuan Wu, Changshi Xiao, Chunhui Zhou, Dong Han
Abstract
In this study, we propose a sampling method for calculating ship exhaust emission inventories, which reduces the uncertainties induced by missing ship static data in traditional methods. The stratified random sampling method is utilized to take sample ships based on the ship density, ship type, and main engine power. The exhaust emissions from sample ship are calculated using an activity-based method with 1 s temporal resolution AIS (Automatic Identification System) data. Then the regional ship exhaust emissions are estimated based on the sampling relationship. Sensitivity experiments show that the relative error of the proposed method decreases quickly with the sampling ratio (the ratio between the number of sampled ships and total ships) and it is less than 3.5% when the sampling ratio is higher than 10%. The method is used to estimate the inventories of ship exhaust emissions in the Yangtze river, which can improve the computational accuracy of ship emissions.