THE ANTHROPOGENIC AIR POLLUTION SOURCE IDENTIFICATION IN URBAN AREAS USING SNOW SAMPLING

The anthropogenic sources of air pollution such as transport, energetics, household heating and industry generate different trace element footprint. The urban planning is one of tool to reduce air pollution with trace elements. The aim of this study is to identify air pollution sources in Jelgava city using trace elements. The snow sampling were collected during January and February 2017. The January snow samples characterise average Jelgava city air pollution. However, February characterises intensive tourism impact on total air quality of Jelgava city. The snow samples were analysed using inductively coupled plasma spectrometer (ICP-OES). The data analysis consists of three stages. First, data verification and development of waste burning; burning of oil and fossil materials; wastewater treatment and utilisation of sewage sludge; transport; metal industry and fireworks typical pollution trace element data sets. Second, the cluster analysis of each data set, by developing three groups of pollution level for each pollution source. Third the results of clusters were analysed using GIS, and the areas with different air pollution risks were identified. The results show strong evidence of transport and household impact on air quality.

Spatio-temporal influence of tundra snow properties on Ku-band (17.2 GHz) backscatter

During the 2010/11 boreal winter, a distributed set of backscatter measurements was collected using a ground-based Ku-band (17.2 GHz) scatterometer system at 26 open tundra sites. A standard snow-sampling procedure was completed after each scan to evaluate local variability in snow layering, depth, density and water equivalent (SWE) within the scatterometer field of view. The shallow depths and large basal depth hoar encountered presented an opportunity to evaluate backscatter under a set of previously untested conditions. Strong Ku-band response was found with increasing snow depth and snow water equivalent (SWE). In particular, co-polarized vertical backscatter increased by 0.82 dB for every 1 cm increase in SWE (R2 = 0.62). While the result indicated strong potential for Ku-band retrieval of shallow snow properties, it did not characterize the influence of sub-scan variability. An enhanced snow-sampling procedure was introduced to generate detailed characterizations of stratigraphy within the scatterometer field of view using near-infrared photography along the length of a 5 m trench. Changes in snow properties along the trench were used to discuss variations in the collocated backscatter response. A pair of contrasting observation sites was used to highlight uncertainties in backscatter response related to short length scale spatial variability in the observed tundra environment.