To assess the impact of atmospheric aerosols on health, climate, and air traffic, aerosol properties must be measured with fine spatial and temporal sampling. This can be achieved by actively involving citizens and the technology they own to form an atmospheric measurement network. We establish this new measurement strategy by developing and deploying iSPEX, a low-cost, mass-producible optical add-on for smartphones with a corresponding app. The aerosol optical thickness (AOT) maps derived from iSPEX spectropolarimetric measurements of the daytime cloud-free sky by thousands of citizen scientists throughout the Netherlands are in good agreement with the spatial AOT structure derived from satellite imagery and temporal AOT variations derived from ground-based precision photometry. These maps show structures at scales of kilometers that are typical for urban air pollution, indicating the potential of iSPEX to provide information about aerosol properties at locations and at times that are not covered by current monitoring efforts.

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Abstract. In this paper, the use of a neural network algorithm for the retrieval of the aerosol properties from groundbased spectropolarimetric measurements is discussed. The neural network is able to retrieve the aerosol properties with an accuracy that is almost comparable to that of an iterative retrieval. By using the outcome of the neural network as first guess in the iterative retrieval scheme, the accuracy of the retrieved fine-and coarse-mode optical thickness is further improved, while for the other parameters the improvement is small or absent. The resulting scheme (neural network + iterative retrieval) is compared to the original one (look-up table + iterative retrieval) on a set of simulated ground-based measurements, and on a small set of real observations carried out by an accurate ground-based spectropolarimeter. The results show that the use of a neural-networkbased first guess leads to an increase in the number of converging retrievals, and possibly to more accurate estimates of the aerosol effective radius and complex refractive index.

Matrix metalloproteinase (MMP) activation is an essential feature of pathological and physiological arterial enlargement or shrinkage. Recently, furin-activated membrane type-1 MMP (MT1-MMP) was identified as the in vivo activator of MMP2 in mice. Although arterial enlargement and shrinkage are important in several pathological processes, this proprotein convertase^MT1-MMP axis has not been described during arterial remodeling. In rabbit femoral and carotid arteries, we report an increase in furin and MT1-MMP mRNA levels before and at the onset of arterial remodeling followed by an increase in activated MMP2. This reveals the presence of the proprotein convertase^MT1-MMP axis in flowinduced arterial remodeling and identifies furin as a possible target for local intervention in pathological arterial remodeling. ß