Soil organic carbon (SOC) and mineral nitrogen (Nmin), especially nitrates (NO3−) in agroecosystems have attracted much attention over the past few decades due to their crucial roles in soil ...fertility, crop productivity, environmental quality, and/or climate change mitigation and adaptation. The aim of the study was to evaluate the contents of organic carbon, ammonium, and nitrate in soils under differentiated pH, texture, and fertilization rates. A large-scale environmental study was conducted in Polish arable lands. The spatial distribution of the sampling points reflected agricultural production conditions, variability of soil properties, and representativeness of textures that are characteristic of Poland. Our results indicated that SOC content was significantly affected by the soil pH and texture as well as mineral and organic fertilization. The same factors, except organic amendments, significantly supported mineral nitrogen concentration in the present study. The most important factors controlling SOC in the study were ranked as follows: soil pH > pre-crop N fertilization > crop N fertilization > N applied with manure > soil texture. In the case of N-NH4 and N-NO3, mineral fertilization was the most critical variable. The carbon and nitrogen governance in agroecosystems should consider the ranks of factors controlling their contents.
Carbon Monoxide (CO) is an important urban pollutant with a relation to transition economies based on emission intensities. In this study, Sentinel-5, MODerate resolution Imaging Spectroradiometer ...(MODIS), and Landsat-8 images were used to investigate the variations of CO and urban environmental indices and the correlations between them. From the assessed correlations for 932 Iranian cities, it occurred that the assessed indices were all correlated. The highest CO levels were 0.031 in the spring of 2019 and 2020, whereas in 2021 it was equal to 0.030 in both the spring and winter, respectively. In 2019 and 2020 the maximum values of the Enhanced Vegetation Index (EVI) in the spring were 0.181 and 0.183. Exceptionally high Absorbing Aerosol Index (AAI) values of - 0.834 and - 1.0, along with Urban Index (UI) of 0.102 and 0.092, were correlated with recorded spikes in CO level, despite that these seasons' EVI values were not so abnormal. It was forecasted that in 2030 rises in the CO level by 13.2% in the winter and by 17.5% in the fall are expected, with the simultaneous increase of AAI by 204.5% and 980.2%, and Aerosol Optical Depth (AOD) by 27% and 5% in the winter and spring, respectively.
Wyniki uzyskano na podstawie badań środowiskowych przeprowadzonych w roku 2012 i 2016. Na badanym obszarze wyznaczono 318 punktów pobierania próbek glebowych, z czego 249 wyznaczono na gruntach ...ornych, 69 na użytkach zielonych (45 na glebach bardzo lekkich, 103 na lekkich, 101 na średnich i 69 na ciężkich). W pobranych próbkach glebowych oznaczono skład granulometryczny metodą laserową, pH w 1 mol KCl dm–3, fosfor i potas przyswajalny metodą Egnera-Riehma (DL), magnez przyswajalny po ekstrakcji z gleby 0,0125 mol CaCl2 dm–3. Uzyskane wyniki badań oceniono na podstawie liczb granicznych obowiązujących w Polsce. Stwierdzono, że w pięciu powiatach (biłgorajski, parczewski, rycki, świdnicki, tomaszowski) nastąpił wzrost udziału procentowego gleb kwaśnych i bardzo kwaśnych w roku 2016 w porównaniu z rokiem 2012. W pozostałych powiatach udział ten zmniejszył się lub pozostał niezmieniony. Pomimo odnotowanej poprawy odczynu gleby pomiędzy rokiem 2012 a 2016 udział gleb wymagających koniecznego lub potrzebnego wapnowania zmniejszył się o ponad 4 p.p., z 36% w roku 2012 do 31,9% w roku 2016. Jednocześnie udział gleb o ograniczonych potrzebach wapnowania lub braku jego konieczności był podobny w obu latach badań (50%). Zasobność gleby w przyswajalne formy badanych makroelementów (P, K, Mg) zmniejszyła się w roku 2016 w porównaniu z rokiem 2012. Wzrost udziału gleb o bardzo niskiej i niskiej zasobności w roku 2016 był różny w zależności od pierwiastka i wynosił: 1 p.p. dla fosforu (wzrost z 27% w roku 2012 do 28% w roku 2016), 4,3 p.p. dla potasu (46,1% – 2012, 50,4% – 2016), 6,4 p.p. dla magnezu (54,9% – 2012, 61,3% – 2016). Wzrost udziału gleb o niskiej i bardzo niskiej zasobności w makroelementy (P, K, Mg) w roku 2016, w porównaniu z rokiem 2012, świadczy o konieczności wprowadzenia zrównoważonego nawożenia tymi składnikami, uwzględniającego zasobność gleby oraz potrzeby pokarmowe uprawianych roślin.
W pracy przedstawiono wyniki badań zawartości azotanów(V) i fosforanów w wodach drenarskich pochodzących z rolniczych obszarów województwa lubelskiego. Badania wykonano w latach 2008–2010. Próbki wód ...pobierano ze studzienek lub z piezometrów w dwóch terminach: wiosną i jesienią. Wykazano, że istotne różnice w stężeniu azotanów(V) i fosforanów występowały w wodach pomiędzy niektórymi kategoriami agronomicznymi gleb. W terminie wiosennym najwięcej przypadków o istotnie najwyższym stężeniu azotanów(V) i fosforanów stwierdzono w próbkach wody pobranych z gleb lekkich, natomiast jesienią – w wodach z gleby organicznej (azotany(V)) oraz organicznej i ciężkiej (fosforany). W próbkach pobranych wiosną, niezależnie od roku badań, obserwowano większe stężenia azotanów(V) niż w wodach pobieranych w terminie jesiennym. W przypadku stężeń fosforanów podobny związek stwierdzono w 2008 r. Oznacza to, że następował ubytek azotanów(V) i fosforanów z badanych gleb, a jednym ze sposobów przemieszczania się tych składników poza profil glebowy mogło być ich wymywanie do wód gruntowych. Stwierdzono dodatnią i istotną statystycznie zależność pomiędzy stężeniami azotanów(V) i fosforanów w wodach pobranych wiosną 2008 r.
An environmental study, which was conducted at 45 agricultural farms located in south-eastern Poland (Lubelskie Voivodeship) over the period of 2015-2016, evaluated the effect of some soil ...physicochemical properties and nitrogen fertilisation on winter wheat yield. Soil physicochemical analysis was performed using conventional methods at the accredited laboratory of the Regional Chemical and Agricultural Station in Lublin. Factorial analysis was carried out after classifying the soil according to soil textural classes, pH classes, and phosphorus, potassium and magnesium abundance classes, as well as after determining three nitrogen rates applied for wheat and its previous crop: I – 0-30; II – 31-60; III – 61-90 kg N ha–1. The study found a positive, but not always significant, effect of soil textural class (in particular, the content of silt and clay particles) and soil pH class (from acidic to alkaline) on winter wheat grain yield. Soil phosphorus, potassium and magnesium abundance was not found to have any significant effect on grain yield. However, these nutrients were observed to positively affect wheat grain yield. Nitrogen fertilisation applied for the evaluated crop and the previous crop was found to significantly affect winter wheat grain yield.
•Retrospective meteorological time series from MERRA-2 exhibit multifractality.•Highest variability of multifractal spectra parameters was observed for the air temperature.•Maps of the multifractal ...parameters can be used to analyse differences in climate dynamics.•Correlation of the multifractal parameters with a number of statistical parameters describing the series was observed.•Geo-statistical analysis delivered important information about the range of influence, sill and nugget variance of singularity spectra parameters.
Spatial variability of the multifractal properties of a 36-year-long meteorological time series for Poland coming from the MERRA-2 database was analysed. It constitute a very valuable source of meteorological data, as high similarity with ground data recorded at meteorological stations in the region of interest was stated by the analysis of similarity measures. The highest variability of multifractal spectra parameters was observed for the air temperature, whereas the lowest was for the air pressure. Spatial analysis of multifractal spectra parameters enabled to select the regions vulnerable to the occurrence of extreme events, correlated or uncorrelated processes, etc. Obtained maps of multifractal parameters give a new insight into climate dynamics in the region and are a valuable source of information for comparative analyses. The spatial variation of the parameters of multifractal spectra was also confirmed by geo-statistical analysis, which delivered important information about the range of influence, sill and nugget variance. The paper is the first attempt to use geo-statistical analysis in regard to multifractal properties of meteorological quantities.
Mineral nitrogen occurring at the depth of 60-90 cm of the soil profile, which is unavailable to the main root mass of grassland plants and arable land crops and which is located in this layer due to ...leaching to deeper soil layers, can pose a serious threat to water quality. This study attempted to evaluate Nmin content in grassland soils depending on soil type, land use, and farming intensity (i.e. livestock density). Regardless of observation period and natural factors evaluated, both land use and grassland use had a significant effect on mineral nitrogen content in the 60-90 cm soil layer. The lowest nitrogen content was shown in grassland mineral soils, whereas the cultivation of both maize and mixed cereals promoted greater accumulation of this nutrient in the soil profile at the depth of 60-90 cm. Mineral nitrogen content also depended on the use of grassland ecosystems. In mineral soils, the highest amounts of Nmin were found in hay grasslands, whereas in organic soils - in hay and pasture grasslands. The lowest amounts of nitrogen in the investigated soil layer were observed in alternate grasslands. It was also revealed that strong significant correlations exist between livestock density and the content of mineral nitrogen in the 60-90 cm soil layer. Calculated regression equation describing those relationships can help the farmer to plan sustainable fertilisation depending on livestock density of his farm.
The variations in vegetation coverage (defined as the area with Normalised Difference Vegetation Index (NDVI) > 0.2) and atmospheric patterns occurring during various vegetation seasons in the Kabul ...River Basin (KRB) in Afghanistan during 2001–2019 were analyzed. The analysis was done based on the NDVI, land surface temperature (LST), precipitation images from the remote sensing data, and geopotential height and temperature at 500 hPa from the retrospective datasets. The results revealed that the vegetation dynamics in KRB are impacted by both precipitation and LST. In the winter season, the LST has a more substantial role in shaping the vegetation dynamics than precipitation, while it is on contrary during the summer season. Cluster analysis showed that the four atmospheric patterns (e.g., Sub-Tropical High Pressure (STHP), Western European ridge-the Eastern Mediterranean and the Black Sea trough, Caspian Sea ridge (CSR), and the Mediterranean Sea trough-Central to Eastern Iran trough) can be identified and connected with the periods with the highest and the lowest vegetation coverage (VC) anomalies in the study area. The CSR and the Mediterranean Sea trough-the Central to Eastern Iran trough are the patterns responsible for the most positive VC anomalies. At the same time, the STHP and Western Europe ridge-the Eastern Mediterranean and the Black Sea trough are responsible for the most negative VC anomalies. As the atmospheric patterns have a significant role in shaping the vegetation status, a quick alert system to prevent agricultural areas from water or temperature stresses can be developed based on observations of them.
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