Abstract
Abstract Iron emissions from human activities, such as oil combustion and smelting, affect the Earth's climate and marine ecosystems. These emissions are difficult to quantify accurately due to a lack of observations, particularly in remote ocean regions. In this study, we used long‐term, near‐source observations in areas with a dominance of anthropogenic iron emissions in various parts of the world to better estimate the total amount of anthropogenic iron emissions. We also used a statistical source apportionment method to identify the anthropogenic components and their sub‐sources from bulk aerosol observations in the United States. We find that the estimates of anthropogenic iron emissions are within a factor of 3 in most regions compared to previous inventory estimates. Under‐ or overestimation varied by region and depended on the number of sites, interannual variability, and the statistical filter choice. Smelting‐related iron emissions are overestimated by a factor of 1.5 in East Asia compared to previous estimates. More long‐term iron observations and the consideration of the influence of dust and wildfires could help reduce the uncertainty in anthropogenic iron emissions estimates.
Plain Language Summary Human activities, such as smelting and oil combustion, release smoke and particles into the atmosphere. These particles often contain iron, which not only absorbs sunlight, contributing to atmospheric warming, but also serves as a nutrient for phytoplankton in various ocean regions. However, the precise extent of human‐induced iron emissions remains uncertain due to a lack of comprehensive monitoring data. In this study, we leverage a global data set of iron observations to refine our estimates of iron emissions attributed to human activities. Additionally, we examine other co‐released substances, such as carbon and nickel, to identify specific emission sources of iron. We employ statistical techniques to distinguish human‐caused iron emissions from those originating from natural sources like dust and wildfires. Moreover, we utilize iron oxide observations to constrain emissions originating from East Asia and Norway, which are estimated to originate largely from smelting emissions. Through the analysis of long‐term data sets, we provide lower and upper bounds to human‐caused iron emissions. Furthermore, we investigate the impact of reduced observation numbers and a sparse network on the range of estimated iron emissions. Our findings highlight the critical role of observation quality in accurately assessing iron emissions from human activities.
Key Points Anthropogenic total iron emissions are constrained to a factor of 3 in most global regions using long‐term aerosol observations The number of sites, interannual variability, and site selection filter can affect the model‐observation comparison uncertainty by 15%–50% Smelting‐related emissions are constrained to a factor of 1.5 using iron oxide observations from East Asia