Maritime sector contributions on NO2 surface concentrations in major ports of the Mediterranean Basin

IF 3.9 3区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES Atmospheric Pollution Research Pub Date : 2024-06-19 DOI:10.1016/j.apr.2024.102228
Andreas Pseftogkas , Maria-Elissavet Koukouli , Astrid Manders , Arjo Segers , Trissevgeni Stavrakou , Janot Tokaya , Charikleia Meleti , Dimitris Balis
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Abstract

The aim of this study is to estimate the contribution of the maritime sector on the air quality of major Mediterranean ports with the Long Term Ozone Simulation-European Operational Smog (LOTOS-EUROS) chemical transport model, using two source apportionment methods: the brute-force emission scenario methodology and the labelling approach. With the brute-force method NO2 shipping concentrations are estimated by the ratio of the difference between two model runs - with original and reduced emissions - and the equivalent emission reduction factor. In the labelling, emitted species are explicitly labelled per sector and tracked through all model processes. Simulations are performed for a one-year period, from May 2018 to May 2019 and the two methodologies are intercompared. The methods show strong agreement between NO2 shipping contributions (R > 0.95) and differences of ∼14%. A sensitivity analysis carried out using the brute-force method indicates that a linear regime between NOX emissions and NO2 concentrations holds, when adopting a low to moderate emission reduction (<50%). We applied the brute-force method with an assumed 20% emission reduction and found that the NO2 surface concentrations attributed to maritime sector activities in selected ports were between 5% and 70% of the total NO2 surface concentrations, with a mean value of 27%. Comparisons between measurements from the European Environment Agency (EEA) ground-based monitoring stations and LOTOS-EUROS NO2 surface concentrations show a strong correlation (R∼0.8) with an underestimation of the model (∼-32%) for the whole period. The bias is reduced to −20% when air quality monitoring stations affected by traffic and industrial activities are excluded from the analysis. Moreover, observed Sentinel-5 Precursor TroPospheric MOnitoring Instrument (S5P/TROPOMI) and modelled NO2 vertical column densities (VCDs) show a significant spatial agreement (R∼0.86) for both summer and winter with biases of −25% and −1%, respectively, over the selected ports. These comparisons were carried out as an indirect way of validating the applied methodology and the performance of the model in coastal areas. The present study provides a solid background which will enable the assimilation of the satellite observations to the CTM to infer NOX shipping emissions in the Mediterranean Basin in view of the upcoming designation of the Mediterranean Sea as an Emission Control Area in 2025.

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海事部门对地中海盆地主要港口二氧化氮表面浓度的影响
本研究的目的是利用长期臭氧模拟-欧洲烟雾(LOTOS-EUROS)化学运输模型,采用两种源分配方法:强制排放情景法和标签法,估算海运业对地中海主要港口空气质量的影响。在 "强制 "方法中,二氧化氮的运输浓度是通过两个模型运行(原始排放量和减少的排放量)之间的差值与等效减排系数的比值来估算的。在标记法中,每个部门的排放物种都被明确标记,并通过所有模型过程进行跟踪。模拟时间为 2018 年 5 月至 2019 年 5 月,为期一年,并对两种方法进行了相互比较。这两种方法在二氧化氮航运贡献之间显示出很强的一致性(R > 0.95),差异为 14%。使用蛮力法进行的敏感性分析表明,在采用中低减排量(50%)时,氮氧化物排放量与二氧化氮浓度之间的线性关系成立。我们在假定减排量为 20% 的情况下采用了 "蛮力法",结果发现,在选定的港口,海洋部门活动造成的二氧化氮表面浓度占二氧化氮表面总浓度的 5% 到 70%,平均值为 27%。欧洲环境署(EEA)地面监测站的测量结果与 LOTOS-EUROS 的二氧化氮表面浓度之间的比较显示出很强的相关性(R∼0.8),整个时期的模型估计值偏低(∼-32%)。如果将受交通和工业活动影响的空气质量监测站排除在分析之外,偏差将减小到-20%。此外,观测到的哨兵-5前体大气监测仪器(S5P/TROPOMI)和模拟的二氧化氮垂直柱密度(VCDs)在选定港口的夏季和冬季显示出显著的空间一致性(R∼0.86),偏差分别为-25%和-1%。进行这些比较是为了间接验证所应用的方法和模式在沿海地区的性能。鉴于地中海即将在 2025 年被指定为排放控制区,本研究为将卫星观测数据同化到 CTM 中以推断地中海盆地的 NOX 航运排放提供了坚实的背景。
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来源期刊
Atmospheric Pollution Research
Atmospheric Pollution Research ENVIRONMENTAL SCIENCES-
CiteScore
8.30
自引率
6.70%
发文量
256
审稿时长
36 days
期刊介绍: Atmospheric Pollution Research (APR) is an international journal designed for the publication of articles on air pollution. Papers should present novel experimental results, theory and modeling of air pollution on local, regional, or global scales. Areas covered are research on inorganic, organic, and persistent organic air pollutants, air quality monitoring, air quality management, atmospheric dispersion and transport, air-surface (soil, water, and vegetation) exchange of pollutants, dry and wet deposition, indoor air quality, exposure assessment, health effects, satellite measurements, natural emissions, atmospheric chemistry, greenhouse gases, and effects on climate change.
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