Detection of ship plumes from residual fuel operation in emission control areas using single-particle mass spectrometry

Abstract

Abstract. Ships are among the main contributors to global air pollution, with substantial impacts on climate and public health. To improve air quality in densely populated coastal areas and to protect sensitive ecosystems, sulfur emission control areas (SECAs) were established in many regions of the world. Ships in SECAs operate with low-sulfur fuels, typically distillate fractions such as marine gas oil (MGO). Alternatively, exhaust gas-cleaning devices (“scrubbers”) can be implemented to remove SO2 from the exhaust, thus allowing the use of cheap high-sulfur residual fuels. Compliance monitoring is established in harbors but is difficult in open water because of high costs and technical limitations. Here we present the first experiments to detect individual ship plumes from distances of several kilometers by single-particle mass spectrometry (SPMS). In contrast to most monitoring approaches that evaluate the gaseous emissions, such as manned or unmanned surveillance flights, sniffer technologies and remote sensing, we analyze the metal content of individual particles which is conserved during atmospheric transport. We optimized SPMS technology for the evaluation of residual fuel emissions and demonstrate their detection in a SECA. Our experiments show that ships with installed scrubbers can emit PM emissions with health-relevant metals in quantities high enough to be detected from more than 10 km distance, emphasizing the importance of novel exhaust-cleaning technologies and cleaner fuels. Because of the unique and stable signatures, the method is not affected by urban background. With this study, we establish a route towards a novel monitoring protocol for ship emissions. Therefore, we present and discuss mass spectral signatures that indicate the particle age and thus the distance to the source. By matching ship transponder data, measured wind data and air mass back trajectories, we show how real-time SPMS data can be evaluated to assign distant ship passages.