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Global Change
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The photolysis of atmospheric nitrous acid (HONO) is a significant source of OH radicals in remote and Polar Regions. HONO is produced in/on snow surfaces in a photochemical reaction from nitrate ions. In an attempt to quantify the production of HONO at a snow covered mid-latitude location we made measurements of HONO fluxes for a 10-day period at the Mt. Cimone (MTC) research station in the Italian northern Apennines (2165 m asl) during March 2004. Production fluxes under normal background conditions were small, and reached maximum values of 20 nmol m-2 h-1 on only two occasions. However, during a transport event of Saharan dust to MTC we observed deposition fluxes of up to -120 nmol m-2 h-1 of HONO on to the snow surface. The deposited Sahara dust had rendered the surface snow alkaline, so that large amounts of acids could be absorbed from the atmosphere.
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This work introduces an index to identify deep stratospheric intrusions (SI) from measurement data alone, without requiring additional model-based information. This stratospheric intrusion index (SI2) provides a qualitative description of SI event behaviour by summarizing the information from different tracer variations. Moreover, being independent from any model constraint, the SI2 can also represent a valid tool to help in evaluating the capacity of chemistry-transport and chemistry-climate models in simulating deep stratosphere to troposphere transport. The in situ variations of ozone, beryllium-7 and relative humidity were used to calculate the index. The SI2 was applied on 8-year data recorded at the regional GAW station of Mt. Cimone (2165 m asl; 44.10N, 10.70E: Italy). The comparison of the SI2 behaviour with a pre-existing database obtained by also using model products, permitted us to tune a SI2-threshold value capable of identifying SI events efficiently. In good agreement with previous climatological studies across Europe, at Mt. Cimone, the averaged monthly SI frequency obtained by the SI2 analysis showed a clear seasonal cycle with a winter maximum and a spring-summer minimum. These results suggest that the presented methodology is efficient for both identifying SI events and evaluating their annual frequency at the considered baseline measurement site.