Potential of microalgae Bio-Coke as a sustainable solid fuel alternative to coal coke

Energy and environmental issues have triggered the search for new sources of green energy alternatives in recent years. Biofuel production from renewable sources is widely considered one of the most sustainable alternatives for environmental and economic sustainability. Microalgae are currently being promoted as one of the most promising liquid biofuel feedstocks due to their rapid growth, high lipid production capacity, and carbon–neutral cycle. In this study, whole microalgae cells were utilized as raw material to produce solid biofuel, i.e., Bio-Coke, and this study aimed to investigate the possibility of microalgae Bio-Coke as an alternative to coal coke. The results show that Bio-Coke can be produced from microalgae in the temperature range of 80–100 °C. The apparent density is between 1.253 and 1.261 g/cm³, comparable to the apparent density of lignocellulosic Bio-Coke. Additionally, the calorific value is higher than the calorific value of lignocellulosic Bio-Coke and within the range of the calorific value of subbituminous coal. Therefore, microalgae Bio-Coke can be utilized to replace coal coke usage in the future.

     

Size fraction of hazardous particulate matter governing the respiratory deposition and inhalation risk in the highly polluted city Delhi

Environmental Science and Pollution Research - Delhi has been identified as one of the highly polluted cities in the world and recently associated with the highest population weighted PM2.5...     

Modeling of energy and emissions from animal manure using machine learning methods: the case of the Western Mediterranean Region,Turkey

Environmental Science and Pollution Research - In Turkey, facilities for the use of biomass resources in energy production are increasing, and new conversion facilities are commissioned every year...     

Endocrine disrupting pesticides in soil and their health risk through ingestion of vegetables grown in Pakistan

Environmental Science and Pollution Research - A comprehensive study was conducted to appraise the concentrations of 30 endocrine disrupting pesticides (EDPs) in soil and vegetable samples...     

Amelioration of toxicopathological effects of cadmium with silymarin and milk thistle in male Japanese quail (Coturnix japonica)

Environmental Science and Pollution Research - Cadmium is an important widely distributed heavy metal in the environment due to its several industrial uses, while milk thistle is an important herb...     

Green sol–gel synthesis of novel nanoporous copper aluminosilicate for the eradication of pathogenic microbes in drinking water and wastewater treatment

Environmental Science and Pollution Research - We used a green sol–gel synthesis method to fabricate a novel nanoporous copper aluminosilicate (CAS) material. Nanoporous CAS was characterized...     

Effect of PM2.5 chemical constituents on atmospheric visibility impairment

PM_2.5 sampling was conducted at a curbside location in Delhi city for summer and winter seasons, to evaluate the effect of PM_2.5 and its chemical components on the visibility impairment. The PM_2.5 concentrations were observed to be higher than the National Ambient Air Quality Standards (NAAQS), indicating poor air quality. The chemical constituents of PM_2.5 (the water-soluble ionic species SO₄^2-, NO₃^?, Cl^?, and NH₄⁺, and carbonaceous species: organic carbon, elemental carbon) were analyzed to study their impact on visibility impairment by reconstructing the light extinction coefficient, b_ext. The visibility was found to be negatively correlated with PM_2.5 and its components. The reconstructed b_ext showed that organic matter was the largest contributor to b_ext in both the seasons which may be attributed to combustion sources. In summer season, it was followed by elemental carbon and ammonium sulfate; however, in winter, major contributions were from ammonium nitrate and elemental carbon. Higher elemental carbon in both seasons may be attributed to traffic sources, while lower concentrations of nitrate during summer, may be attributed to volatility because of higher atmospheric temperatures.

Implications: The chemical constituents of PM_2.5 that majorly effect the visibility impairment are organic matter and elemental carbon, both of which are products of combustion processes. Secondary formations that lead to ammonium sulfate and ammonium nitrate production also impair the visibility.     

Modeling seasonal variations of long-term soil CO<Subscript>2</Subscript> emissions in an orchard plantation in a semiarid area,SE Turkey

Emissions of soil CO₂ under different management systems have a significant effect on the carbon balance in the atmosphere. Soil CO₂ emissions were measured from an apricot orchard at two different locations: under the crown of trees (CO₂-UC) and between tree rows (CO₂-BR). For comparison, one other measurement was performed on bare soil (CO₂-BS) located next to the orchard field. Analytical data were obtained weekly during 8 years from April 2008 to December 2016. Various environmental parameters such as air temperature, soil temperature at different depths, soil moisture, rainfall, and relative humidity were used for modeling and estimating the long-term seasonal variations in soil CO₂ emissions using two different methods: generalized linear model (GLM) and artificial neural network (ANN). Before modeling, data were randomly split into two parts, one for calibration and the second for validation, with a varying number of samples in each part. Performances of the models were compared and evaluated using means absolute of estimations (MAE), square root of mean of prediction (RMSEP), and coefficient of determination (R²) values. CO₂-UC, CO₂-BR, and CO₂-BS values ranged from 11 to 3985, from 9 to 2365, and from 8 to 1722 kg ha^?1 week^?1, respectively. Soil CO₂ emissions were significantly correlated (p?<?0.05) with some environmental variables. The results showed that GLM and ANN models provided similar accuracies in modeling and estimating soil CO₂ emissions, as the number of samples in the validation data set increased. The ANN was more advantageous than GLM models by providing a better fit between actual observations and predictions and lower RMSEP and MAE values. The results suggested that the success of environmental variables for estimations of CO₂ emissions using the two methods was moderate.     

Performance evaluation of oil spill software systems in early fate and trajectory of oil spill: comparison analysis of OILMAP and PISCES 2 in Mersin bay spill

The aim of this study is to evaluate the performance level of two advanced oil spill software systems in early transport and fate of oil spill through algorithms accepted in oil spill literature. To do this, the performance level of software systems mostly used in real cases have been compared. OILMAP (the oil spill prediction modeling system) and PISCES 2 (potential incident simulation, control and evaluation system) have been used for spill trajectory in the light of four spill scenarios. The findings reveal that the OILMAP has predicted a relatively larger area of spill. In addition, OILMAP has achieved closer results to the calculations of approaches adopted in the literature for evaporation calculations. Besides, OILMAP software has provided highly reliable results in the evaporation rates of oil compared to the calculations of PISCES 2. On the other hand, as for the determination of the risky area, both software systems have yielded results with high reliability values, which could be used in taking precautions against oil spill in such areas.     

Managing Mediterranean soil resources under global change: expected trends and mitigation strategies

Regional Environmental Change - The soils of the Mediterranean Basin are the products of soil processes that have been governed by a unique convergence of highly differentiated natural and...