Microalgae cultivation could contribute to the achievement of several sustainable development goals (SDGs). However, cultivating Chlorella vulgaris, like any other microalgae, is challenging due to various biotic, abiotic and process related factors that can affect its growth and biomass productivity. Nutrient availability, particularly N and P, and their ratio play a crucial role in building cellular structures and maintaining metabolic processes, determining basically the maximum achievable biomass productivity under given circumstances. The present article aims to improve the N and P ratio to enhance the biomass productivity of Chlorella vulgaris microalgae as well as to characterize the biomass growth kinetics that can be used for prediction purposes. The results showed that the nutrient solutions prepared with increased nitrate concentration (T1 – N:P = 55:1 and T3 – N:P = 28:1) promoted chlorophyll formation and significantly outperformed the control sample (BG-11 – N:P = 35:1) with 192% and 183%, leading to higher biomass productivity with 1160 μg L⁻¹ and 1103 μg L⁻¹, respectively. Moreover, a strong positive correlation was revealed (0.81) between phosphate concentration and microalgae activity rate, indicating the role of phosphorous in energy transfer, resulted in stimulated microalgae activity rates with 71.2% and 70.66% in the phosphate-increased nutrient solutions (T2 – N:P = 14:1 and T3 – N:P = 28:1). In addition, an exponential equation was introduced to characterize the biomass growth kinetics, of which the theoretically achievable maximum chlorophyll concentration (C_TAM) and the theoretical cultivation time (t_cultivation) were determined for the tested nutrient solutions with variable N:P ratio. It was concluded, that the higher the N:P ratio, the higher the C_TAM is, nevertheless the absolute concentration of these nutrients need to be considered as well. The introduced two key parameters could provide valuable information for decision makers regarding the optimization of growth conditions, nutrient supplementation, and harvesting, additionally decreasing the production costs and making the cultivation cycles more effective and sustainable.

The estimation of crop evapotranspiration (ETc) is crucial for irrigation water management, especially in arid regions. This can be particularly relevant in the Po Valley (Italy), where arable lands suffer from drought damages on an annual basis, causing drastic crop yield losses. This study presents a novel approach for vegetation-based estimation of crop evapotranspiration (ETc) for maize. Three years of high-resolution multispectral satellite (Sentinel-2)-based Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Normalized Difference Red Edge Index (NDRE), and Leaf Area Index (LAI) time series data were used to derive crop coefficients of maize in nine plots at the Acqua Campus experimental farm of Irrigation Consortium for the Emilia Romagna Canal (CER), Italy. Since certain vegetation indices (VIs) (such as NDVI) have an exponential nature compared to the other indices, both linear and power regression models were evaluated to estimate the crop coefficient (K_c). In the context of linear regression, the correlations between Food and Agriculture Organization (FAO)-based K_c and NDWI, NDRE, NDVI, and LAI-based K_c were 0.833, 0.870, 0.886, and 0.771, respectively. Strong correlation values in the case of power regression (NDWI: 0.876, NDRE: 0.872, NDVI: 0.888, LAI: 0.746) indicated an alternative approach to provide crop coefficients for the vegetation period. The VI-based ETc values were calculated using reference evapotranspiration (ET₀) and VI-based K_c. The weather station data of CER were used to calculate ET₀ based on Penman-Monteith estimation. Out of the Vis, NDWI and NDVI-based ETc performed the best both in the cases of linear (NDWI RMSE: 0.43 ± 0.12; NDVI RMSE: 0.43 ± 0.095) and power (NDWI RMSE: 0.44 ± 0.116; NDVI RMSE: 0.44 ± 0.103) approaches. The findings affirm the efficacy of the developed methodology in accurately assessing the evapotranspiration rate. Consequently, it offers a more refined temporal estimation of water requirements for maize cultivation in the region.

In light of climate change and limited water resources, optimizing water usage in agriculture is crucial. This study models water productivity to help regional planners address these challenges. We integrate CROPWAT-based reference evapotranspiration (ET_o) with Sentinel 2 data to calculate daily evapotranspiration and water needs for maize using soil and climate data from 2021 to 2023. The HYDRUS model predicted volumetric soil moisture content, validated against observed data. A 2D hydrodynamic model within HYDRUS simulated temporal and spatial variations in soil water distribution for maize at a non-irrigated site in Hungary. The model used soil physical properties and crop evapotranspiration rates as inputs, covering crop development stages from planting to harvest. The model showed good performance, with R² values of 0.65 (10 cm) and 0.81 (60 cm) in 2021, 0.51 (10 cm) and 0.50 (60 cm) in 2022, and 0.38 (10 cm) and 0.72 (60 cm) in 2023. RMSE and NRMSE values indicated reliability. The model revealed water deficits and proposed optimal irrigation schedules to maintain soil moisture between 32.2 and 17.51 V/V%. This integrated approach offers a reliable tool for monitoring soil moisture and developing efficient irrigation systems, aiding maize production’s adaptation to climate change.

The main point of this research is to assess the applicability of condensed molasses soluble (CMS), which is an organic by-product of lysine fermentation, as an environmentally friendly complexing agent in rhizofiltration of heavy metal contaminated acid mine drainage (AMD). First, the ecotoxicological properties (growth inhibition, seed germination) of CMS were examined with often applied indicator plant species such as duckweed (Lemna minor) and lettuce (Lactuca sativa) so as to define the possible applicable CMS concentration. Then the heavy metal accumulation and translocation properties of root accumulator plant species, i.e. common reed (Phragmites australis) and sedge (Carex flacca), were studied to optimize CMS concentration for rhizofiltration. Due to the CMS application, significant increase in bioaccumulation was detected in the case of every examined heavy metal (As, Cd, Cu, Pb and Zn) at the end of the experiment. Results also showed that CMS increased the heavy metal concentration in shoots, but did not affect the root accumulation characteristics of the plants. Furthermore, CMS treated plants accumulated heavy metals at higher rates in their roots compared to control. The results suggest that CMS is a viable additive and a complexing agent to aid rhizofiltration of heavy metal contaminated AMD.

Monitoring the concentration of heavy metals in urban soils is of a paramount importance for several reasons. These inorganic pollutants can pose a significant health risk to living organisms, as they are toxic even at low concentrations and can be present in the soil for a long period of time. This study assesses the spatial distribution, concentration levels, and potential anthropogenic and natural sources of eight typical heavy metals (As, Cd, Co, Cr, Cu, Ni, Pb and Zn) occurring in urban surface soils across Debrecen, Hungary. A total of 295 topsoil samples were collected; heavy metal concentrations were determined by energy-dispersive X-ray fluorescence (EDXRF) spectrometry. The results were interpreted using descriptive statistics, correlation analysis, hierarchical clustering, factor analysis, ordinary kriging interpolation, and spatial-discriminant analysis. The dual origin of the metal contaminants was revealed: As, Co, Pb, and Zn showed strong anthropogenic signatures associated with traffic, urban waste, and construction materials, whereas Cr and Ni were associated with natural geogenic sources. Cd reflected both lithogenic and point-source urban pollution. The current evaluation incorporated Hungarian and Dutch regulatory benchmarks to identify exceedances of environmental quality thresholds. It was found that only Cd and Cr exceeded the Hungarian target values, on average. Linear discriminant analysis based on pollution maps highlighted contamination hotspots around traffic corridors and newly industrialized zones. The importance of high-resolution soil monitoring in the rapidly urbanizing city is highlighted. Given its anticipated industrial and transportation developments, accumulations of heavy metals are probably going to be further exacerbated; therefore, the results provide a critical baseline for future environmental assessments and long-term monitoring.

In phytostabilization, heavy metal-tolerant plants (e.g.,grasses) can be used to reduce the mobility of heavy metals in soils. The most important step in phytostabilization is the selection of the suitable plant species, in which growth and development can be supported by soil amendments. Sewage sludge compost could be a suitable additive, which provides nutrients for the plant species used for phytostabilization and contributes to an alternative solution for sewage sludge utilization. The aim of the study was to examine the potential of sewage sludge compost in phytostabilization for heavy metal contaminated matrices: identify the optimal ratio of sewage sludge compost to decrease phytotoxicity of the matrices, and assessment of feasible plant species for phytostabilization based on its bioaccumulation properties. In this research, perennial ryegrass (Lolium perenne), broad-leaved sorrel sorrel (Rumex acetosa), lettuce (Lactuca sativa) and cabbage (Brassica oleracea var. capitata) were used for phytotoxicity experiments as well as for testing sewage sludge compost amended phytostabilization of polluted flotation sludge and mine tailings. Sewage sludge compost increased the pH and electric conductivity of the matrices. High salt content and low acidity, altogether with heavy metals caused harmful physiological effects on plant species grown without any compost addition. In the root development test, as in the germination test, the application of 5% sewage sludge compost proved to be optimal. The lower translocation factors of broad-leaved sorrel and perennial ryegrass showed a higher rate of heavy metal accumulation in the roots. Perennial ryegrass, cabbage, and lettuce plant species reached their maximum biomass by adding 5% of sewage sludge compost. Based on the bioaccumulation, translocation and biomass properties, application of perennial ryegrass is recommended for phytostabilization of heavy metal contaminated sites. Furthermore, composted sewage sludge also had a significant effect on the reduction of heavy metal uptake by cabbage and lettuce, which highlights their role as indicator plants in ecotoxicological measurements. The effects of sewage sludge compost added to the heavy metals contaminated flotation sludge and mine tailings (pH = 4.8) were examined. The applicability of broad-leaved sorrel and perennial ryegrass that can be found under natural conditions in the study area was assessed as a function of sewage sludge compost ratio for phytostabilization purposes. Moreover, ecotoxicological tests had been performed with cabbage and lettuce on sewage sludge compost + flotation sludge and mine tailings mixtures. Based on the results, it was proved that the phytostabilization is feasible with the investigated plant species by adding 5% of sewage sludge compost to the flotation sludge and mine tailings.