New insights into submicron particles impact on visibility.

The aim of the study was to analyze the impact of very fine atmospheric particles (submicron particulate matter; PM1) on visibility deterioration. Taking into consideration not only their entirely different physio-chemical properties in comparison to a well-recognized PM10 but also the origin and a growing environmental awareness of PM1, the main research problem has been solved in few steps. At first, the chemical composition of PM1 was determined in two selected urban areas in Poland. Measurements of meteorological parameters, i.e., air temperature and humidity, precipitation, atmospheric pressure, wind speed, and visibility, were also conducted. The next step of the work was the analysis of (1) seasonal changes of the concentration of PM1 and its main components, (2) the influence of chemical components of PM1 on light extinction, and (3) the influence of PM1 and humidity on visibility. Hierarchical cluster analysis, correlation matrixes and a heat map, and classification and regression tree analysis were used. The light extinction coefficient is influenced mainly by coarse mass of PM, and PM1-bound ammonium nitrate, organic matter, and by Rayleigh scattering. The less important in the light extinction coefficient shaping has PM1-bound ammonium sulfate, elemental carbon, and soil. In this way, the secondary origin PM1 components were proved to most significantly influence the visibility. The obtained results confirmed the possibility of the use of statistical agglomeration techniques to identify ranges of variation of visibility, including independent variables adopted to analyses (meteorological conditions, chemical composition of PM1, etc.).

In Search of a Soil Moisture Content Simulation Model: Mechanistic and Data Mining Approach Based on TDR Method Results.

Soil moisture content simulation models have continuously been an important research objective. In particular, the comparisons of the performance of different model types deserve proper attention. Therefore, the quality of selected physically-based and statistical models was analyzed utilizing the data from the Time Domain Reflectometry technique. An E-Test measurement system was applied with the reflectogram interpreted into soil volumetric moisture content by proper calibration equations. The gathered data facilitated to calibrate the physical model of Deardorff and establish parameters of: support vector machines, multivariate adaptive regression spline, and boosted trees model. The general likelihood uncertainty estimation revealed the sensitivity of individual model parameters. As it was assumed, a simple structure of statistical models was achieved but no direct physical interpretation of their parameters, contrary to a physically-based method. The TDR technique proved useful for the calibration of different soil moisture models and a satisfactory quality for their future exploitation.

The influence of a green roof drainage layer on retention capacity and leakage quality.

The aim of the research was to determine the influence of the substrate and different drainage materials on retention capacity and runoff water quality from three green roof containers. Phosphates were chosen as the water quality indicator based on their potential adverse impact on water quality in urban rainwater collectors. The field experiment was conducted at the Warsaw University of Life Sciences Water Center meteorological station in years 2013-2015. In terms of precipitation, the monitoring period covered a wet (+147.1 mm), average (+42.7 mm) and dry (- 66.3 mm) year. Leakage from the containers was recorded when the substrate moisture exceeded 20% and precipitation exceeded 3.5 mm/d for washed gravel, or 5.0 mm/d for a polypropylene mat and expanded clay. Phosphates were observed in leachates from all containers, with higher values observed in the second year of monitoring. As the result of this study, it can be concluded that the polypropylene mat and aggregates create different conditions for the formation of the leachate, in both volumes and its chemistry. The drainage layer made from a polypropylene mat is the most effective in terms of rainwater retention capacity and the resulting leachate quality.