Aerosol Iron Solubility Specification in the Global Marine Atmosphere with Machine Learning
Aerosol Iron Solubility Specification in the Global Marine Atmosphere with Machine Learning
复制标题
通过机器学习确定全球海洋大气中气溶胶铁溶解度规范
DOI：
10.1021/acs.est.2c05266
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发表时间：
2022
影响因子：
11.4
通讯作者：
Daizhou Zhang
中科院分区：
文献类型：
--
作者：
Jinhui Shi;Yang Guan;Huiwang Gao;Xiaohong Yao;Renzheng Wang;Daizhou Zhang
气溶胶铁（Fe）溶解度是评估大气营养盐输入海洋的关键因素，但由于确定溶解度的机制尚不清楚，在模式中没有得到很好的描述。我们开发了一个深度学习模型，根据我们在中国沿海城市观察到的数据来预测溶解度。该模型有五个变量：气溶胶粒子的粒径范围、相对湿度以及硫酸盐、硝酸盐和草酸盐与总铁含量的比值。结果表明，与文献中的溶解度在世界上大多数海洋和边缘地区的皮尔逊相关系数（r）高达0.73-0.97的统计协议。例外的是大西洋，其中获得了良好的协议与使用本地数据训练的模型（r：0.34-0.66）。该模型进一步揭示了草酸盐/TFe的比例是影响溶解度的最重要的变量。这些结果表明，在经过仔细训练和验证的深度学习模型中，将溶解度视为六个因素的函数是可行的。我们的模型和预计的溶解度提供了创新的选择，更好地量化气溶胶可溶性铁在全球海洋大气中的观测和模型研究的空气到海洋的输入。
Aerosol iron (Fe) solubility is a key factor for the assessment of atmospheric nutrients input to the ocean but poorly specified in models because the mechanism of determining the solubility is unclear. We develop a deep learning model to project the solubility based on the data that we observed in a coastal city of China. The model has five variables: the size range of particles, relative humidity, and the ratios of sulfate, nitrate and oxalate to total Fe (TFe) contents in aerosol particles. Results show excellent statistical agreements with the solubility in the literature over most worldwide seas and margin areas with the Pearson correlation coefficients (r) as large as 0.73–0.97. The exception is the Atlantic Ocean, where good agreement is obtained with the model trained using local data (r: 0.34–0.66). The model further uncovers that the ratio of oxalate/TFe is the most important variable influencing the solubility. These results indicate the feasibility of treating the solubility as a function of the six factors in deep learning models with careful training and validation. Our model and projected solubility provide innovative options for better quantification of air-to-sea input of aerosol soluble Fe in observational and model studies in the global marine atmosphere.