1. Ny-Ålesund Seminars, 25-26 October 2011

2. Black carbon (BC) belongs to what is generally termed Short Lived Climate Forcers (SLCF). This means that the compound influence the climate in one or more ways, while having a relatively short turn-over time in the atmosphere. It is therefore of interest to better understand the life- cycle of BC as it is transported from a source region to more remote locations such as the Arctic.

3. As almost all anthropogenic pollutants in the Arctic, black carbon is produced at lower latitudes where human activities take place. Since the pollutant is travelling away from the source region it is successively diluted with air that contains lower concentrations. SN For compounds such as black carbon the only mechanisms to remove it from the atmosphere is through dry and wet deposition. Surface

4. Whereas dry deposition can be formulated based on the physical characteristics of the particle (e.g. size) and ambient conditions such as surface properties and turbulence… …wet deposition involves the chemical state of the particle (i.e., affinity to water). It also depends on the actual mechanisms for the generation of precipitation, freezing, riming etc. In order to gain more insight into the wet deposition we have combined the long-term observations of particle light absorption at the Zeppelin station and combined these with model derived precipitation amounts based on the HYSPLIT trajectory model.

5. Note The primary observation at the Zeppelin is not BC per se, but rather the light absorbing coefficient (m -1 ). To convert from this property to a mass concentration a so called specific absorption coefficient is used (g m -2 ). This latter parameter is often not well characterized, however for our purposes in this study we can omit this conversion step.

6. For each observation at the Zeppelin station (starting in 2002) a 240 h back trajectory was calculated. The precipitation for each trajectory was accumulated over the 10 day transport to Zeppelin. Data was grouped by month and binned in 10 classes with the respect to the accumulated precipitation. Each month had typically 1500 trajectory- observation data points. For each precipitation class the median light absorption coefficient and median precipitation amount was calculated. For the month of March the data looks like this:

7. Abs is absorption coefficient, A the amplitude at P=0 P is the precipitation amount in mm and b is a “scavenging efficiency parameter” Abs=A*1/(1+P) b Abs (m -1 ) vs. precip.

8. Same type of fitting performed for each individual month Amplitude coefficient (i.e. abs at zero precip) Scav. efficiency coefficient: -Properties of the aerosol? -Temperature effect?

9. Is it possible to reproduce also the observed values if we introduces the seasonal variation in precipitation? At least on seasonal basis we can mimic the observed values and we can see why the second transport enhancement in fall does not show up at Zeppelin due to wet removal en route to Svalbard.

10. The data can be taken further to calculate the so called Washout Ratio (WR). This quantity is simply the ratio of BC in kg of air to the BC in a kg of precipitate. By using our derived relationships and assuming a boundary layer height of 1500 m, it is possible to calculate the WR for each our trajectories when there is precipitation. This was done for a period in spring 2007, when concurrent measurements of BC in snow and air were used to calculate observed WR. Although our calculated values fits generally well with those of Noone and Clarke (1989), there is a factor of two difference to those reported by Hegg et al. (2011) which is a one-on-one comparison.

11. Noone & Clarke (1988) Hegg et al. (2011) Zeppelin NYA 24 h moving average (grey line) WR based on fitted curve and history of precipitation WR of initial precipitation assuming 0 precipitation until arrival

12. +54000 trajectory transport cases associated with observation of mass Tunved et al., MS in preparation

13. Acknowledgment to the Swedish funding agenesis VR and Formas for support, and thanks to Norwegian Polar Inst. and Stockholm Uni. staff that help out on the measurement side. The method of combining in-situ observations and meteorological output parameters from trajectory models is very promising. Understanding the seasonal variation in the scavenging efficiency will be key for pertinent parameterizations in transport models.

14. Dark period Sunlit period Dp, m