Applicability of small-scale black carbon sensors to explore high resolution spatial variability of ambient black carbon

Abstract. Black Carbon (BC) is a particulate pollutant emitted as a by-product of combustion. BC has an emerging role in air quality monitoring with the current recommendations by the World Health Organization, that systematic measurements of BC should be conducted to capture the temporal and spatial variability of BC. To observe this variability, especially in urban areas, a large quantity of sensor-type measurements is required. In this study, four different types of small-scale filter-based BC sensors (AE51, MA200, MA350, Observair) were used to build a sensor network in Kumpula campus, Helsinki, Finland. Our aim was to test the applicability of the sensors to monitor ambient BC concentrations in field conditions and to study the variation of BC in high resolution. The results were compared to a reference level instrument (MAAP) for validation. During intercomparisons, the sensors had a good correlation with the reference and after a simple orthogonal regression calibration, were deemed suitable for deployment in the sensor network. During deployment, the sensor network proved to be able to capture small scale temporal and spatial differences in BC concentrations and showed potential for source-apportionment applications. The changes in temperature (T) and relative humidity (RH) were observed to induce error in the BC measurements. This error was amplified by the dualspot correction, which was worsening the measurement result under instable conditions of T and RH. This should be considered when using sensors that apply this correction automatically. The environmental compensation used by the Observair sensors reduced the error from the changing T and RH. To reduce the effect of changing T and RH, more robust environmentally controlled boxes should be developed or correction algorithms, such as environmental compensation, should be applied.