Contribution of Ship Emissions to Aerosol Number Concentrations: Parameterization of Plume‐Scale Nonlinear Microphysics and Application

羽流 气溶胶 环境科学 大气科学 气象学 比例(比率) 非线性系统 物理 量子力学
作者
Jingbo Mao,Yan Zhang,Fangqun Yu,Shujun Bie,Yu Qi,Weichun Ma,Jianmin Chen,Limin Chen
出处
期刊:Journal Of Geophysical Research: Atmospheres [Wiley]
卷期号:130 (4)
标识
DOI:10.1029/2024jd042867
摘要

Abstract Ships are an important source of tiny atmospheric particles over oceans capable of affecting clouds, and the change of ship fuel sulfur has been suggested to reduce particle cooling effects. Number concentrations and sizes of emitted particles are critical for assessing the climate and health impacts of shipping emissions. Here, we build the direct ship particle number (SPN) emission inventory and further propose a computationally efficient approach (look‐up table, EIPN) to estimate particle number emission by accounting for the subgrid process of ship plumes. In the Yangtze River Delta (YRD) coastal area along East China Sea, the total ship particle number emission estimated based on EIPN is 7.3 × 10 23 particles with the values of 5.9 × 10 24 particles predicted by the SPN, showing a notable overestimation by a factor of ∼8 (compared to EIPN). The particle number and cloud condensation nuclei (CCN) under 0.4% water supersaturation (CCN0.4) conducted utilizing the EIPN with normalized mean biases (NMB) of −13.1% and −28.6% exhibit higher concordance with observations than those using the conventional mass emission inventory (NMB = −37.7%, −44.9%) and SPN (NMB = −57.4%, −72.2%), demonstrating the significant improvement in 3‐D models. Ship‐related particles have large spatiotemporal variations, and their contribution to CCN is driven by secondary particles. Our results support the influence of ship emissions on coastal air aerosols and CCN and highlight the importance of accounting for ship plume subgrid processes.

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