The temporal variability of microphysical parameters of pyrolysis smoke, retrieved by inverting the characteristics of aerosol scattering and extinction, has been studied. The polarization scattering phase functions and spectral extinction coefficients were measured for 65 hours in smoke aerosols produced from thermal decomposition of pine wood during low-temperature pyrolysis in the Big Aerosol Chamber (BAC) of Institute of Atmospheric Optics, Siberian Branch, Russian Academy of Sciences. The microstructure parameters (volume concentration and mean radius of particles with division into fine and coarse fractions) and the complex refractive index of pyrolysis smoke are retrieved following the developed algorithm for inverting optical measurements. The real part of the refractive index is found to be in the vicinity of n = 1.55, and the imaginary part is in the range 0.007 < kappa < 0.009; the mean radius of fine particles varies in the narrow range 0.137-0.146 mu m. During smoke aging, the particle ensemble-mean radius monotonically increased from 0.19 to 0.6 mu m mainly due to a relative increase in the content of coarse aerosol. Results of this work are important for estimation of the radiative forcing of aerosol and improvement of climate models and algorithms of remote optical sounding.

This paper takes the representative buried structure in permafrost regions, a transmission line tower foundation, as the research object. An inverse prediction is conducted in a scaled-down experimental system mimicking actual heat conduction of the frozen ground in a tower foundation. In permafrost regions, global warming and the heat transfer through the buried structures bring significantly adverse thermal effects on the stability of the infrastructures. In modeling the thermal effects, it has been a challenge to determine the ground surface boundary condition and heat source strength from the buried structures due to the complex climate and environmental conditions. In this work, based on the improved model predictive inverse method with an adaptive strategy, an inverse scheme is successfully implemented to simultaneously identify the time-varying surface temperature and the time-space-dependent heat source representing the buried structures. In this scheme, an adaptive time-varying predictive model is established by the rolling update of the sensitivity response coefficients according to the predicted temperature field to overcome the influence of nonlinear characteristics in the heat transfer process. The inverse method is verified by simulation and experimental data. According to the experimental inversion results, the reconstructed temperature distribution efficiently predicts the thermal state evolution of the permafrost foundation under seasonal freezing and thawing. It is found that, under the experimental conditions, the intensified thawing and freezing are significantly severe, e.g., the increased area ratio of active layer thickness is as high as 28% after building a tower, and the depth of permafrost table ranges from about 14 mm to about 38 mm, which could be detrimental to the stability and safety of the tower foundation. This study will provide valuable guidance for risk assessments or optimizing the design and maintenance of the real tower foundation and similar buried structures.