The paper presents the evaluation of the relation between meteorological elements and air pollutants’ concentrations. The analysis includes daily concentrations of pollutants and variation of meteorological elements such as wind speed, air temperature and relative humidity, precipitation and total radiation at four monitoring stations located in the province of Lower Silesia in individual months of the winter half-year (November–April, according to hydrological year classification) of 2005–2009. Data on air quality and meteorological elements came from the results of research conducted in the automatic net of air pollution monitoring conducted in the range of the State Environment Monitoring. The effect of meteorological elements on analysed pollutant concentration was determined using the correlation and regression analysis at significance level α < 0.05. The occurrence of maximum concentration of NO, NO2, NOX, SO2 and PM10 occurred in the coldest months during winter season (January, February and December) confirmed the strong influence of “low emission” on air quality. Among the meteorological factors assessed wind speed was most often selected component in step wise regression procedure, then air temperature, less air relative humidity and solar radiation. In the case of a larger number of variables describing the pollution in the atmosphere, in all analyzed winter seasons the most common set of meteorological elements were wind speed and air temperature.
Giant miscanthus is a vigorously growing energy plant, popularly used for biofuels production. It is a grass with low soil and water requirements, although its productivity largely depends on complementary irrigation, especially in the first year of cultivation. The aim of the study was to assess the impact of the forecast climate changes, mainly air temperature increase, on the water needs of giant miscanthus during the growing season in 2021–2050 in the Kuyavia region (central Poland). The years 1981–2010 as the reference period were applied. The meteorological data was based on the regional climate change model RM5.1 with boundary conditions from the global ARPEGE model for the SRES A1B emission scenario. Crop evapotranspiration, calculated using the Penman-Monteith method and crop coefficients, was assumed as a measure of water needs. The study results showed that in view of the expected temperature changes, in the forecast period 2021–2050, the giant miscanthus water needs will increase by 10%. The highest monthly increase may occur in August (16%) and in September (23%). In the near future, the increase in water needs of giant miscanthus will necessitate the use of supplementary irrigation. Hence the results of this study may contribute to increasing the efficiency of water use, and thus to the rational management of irrigation treatments and plant energy resources in the Kuyavia region.
The objective of this study was the development and verification of a model of soil moisture decrease during dry spells—SMDS. The analyses were based on diurnal information of the occurrence of atmospheric precipitation and diurnal values of soil moisture under a bare soil surface, covering the period of 2003–2019, from May until October. A decreasing exponential trend was used for the description of the rate of moisture decrease in six layers of the soil profile during dry spells. The least squares method was used to determine, for each dry spell and soil depth, the value of exponent α , which described the rate of soil moisture decrease. Data from the years 2003–2015 were used for the identification of parameter α of the model for each of the layers separately, while data from 2016–2019 were used for model verification. The mean relative error between moisture values measured in 2016–2019 and the calculated values was 3.8%, and accepted as sufficiently accurate. It was found that the error of model fitting decreased with soil layer depth, from 8.1% for the surface layer to 1.0% for the deepest layer, while increasing with the duration of the dry spell at the rate of 0.5%/day. The universality of the model was also confirmed by verification made with the use of the results of soil moisture measurements conducted in the years 2009–2019 at two other independent locations. However, it should be emphasized that in the case of the surface horizon of soil, for which the process of soil drying is a function of factors occurring in the atmosphere, the developed model may have limited application and the obtained results may be affected by greater errors. The adoption of calculated values of coefficient α as characteristic for the individual measurement depths allowed calculation of the predicted values of moisture as a function of the duration of a dry spell, relative to the initial moisture level adopted as 100%. The exponential form of the trend of soil moisture changes in time adopted for the analysis also allowed calculation of the duration of a hypothetical dry spell t, after which soil moisture at a given depth drops from the known initial moisture θ0 to the predicted moisture θ. This is an important finding from the perspective of land use.
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