Developing long-term strategies to reduce energy use and CO<Subscript>2</Subscript> emissions—analysis of three mitigation scenarios for iron and steel production in China

We perform a scenario analysis of three strategies for long-term energy savings and carbon dioxide (CO₂) emission reductions in iron and steel production in China, using a linear optimization modeling framework industry sector energy efficiency modeling (ISEEM). The modeling includes annual projections for one base scenario representing business-as-usual (BAU) and three additional scenarios representing different strategies to reduce annual energy use and CO₂ emissions from 2010 to 2050. Specifically, the three scenarios for cost-optimization modeling include changing the production share (PS), predefining emission reduction (ER) target, and stipulating carbon emission pricing (CP), respectively. While the three strategies are projected to result in similar annual energy savings by approximately 15 % compared to that of the BAU scenario in year 2050, the carbon emission pricing strategy brings about the highest annual energy savings in the medium term (e.g., 2025). In addition, adopting carbon emission pricing strategy will result in the highest emission reduction from BAU with much higher costs, i.e., by 20 % in 2025 and 41 % in 2050, while adopting either PS or ER strategies will result in a moderate level of emission reduction from BAU, i.e., by approximately 4 % in 2025 and 14 % in 2050. The analysis of China’s national strategies to reduce energy use and emissions provides important implications for global mitigation strategies.     

Functional regression on remote sensing data in oceanography

The aim of this study is to propose the use of a functional data analysis approach as an alternative to the classical statistical methods most commonly used in oceanography and water quality management. In particular we consider the prediction of total suspended solids (TSS) based on remote sensing (RS) data. For this purpose several functional linear regression models and classical non-functional regression models are applied to 10 years of RS data obtained from medium resolution imaging spectrometer sensor to predict the TSS concentration in the coastal zone of the Guadalquivir estuary. The results of functional and classical approaches are compared in terms of their mean square prediction error values and the superiority of the functional models is established. A simulation study has been designed in order to support these findings and to determine the best prediction model for the TSS parameter in more general contexts.     

A review of plastic pollution in aquatic ecosystems of Turkey

Environmental Science and Pollution Research - Turkey is one of the major plastic pollution sources in the Mediterranean and the Black Sea. This review summarizes present information, data, and...     

Biosorption characteristics of copper (II), chromium (III), nickel (II), and lead (II) from aqueous solutions by Chara sp. and Cladophora sp.

The aim of this research was to expose individual removals of copper, chromium, nickel, and lead from aqueous solutions via biosorption using nonliving algae species, Chara sp. and Cladophora sp. Optimum pH values for biosorption of copper (II), chromium (III), nickel (II), and lead (II) from aqueous solutions were determined to be 6, 7, 7, and 3 for Cladophora sp. and 5, 3, 5, and 4 for Chara sp. respectively. Maximum adsorption capacities of Chara sp. [10.54 for chromium (III) and 61.72 for lead (II)] and Cladophora sp. [6.59 for chromium (III) and 16.75 and 23.25 for lead (II)] for chromium (III) and lead (II) are similar. On the other hand, copper (II) and nickel (II) biosorption capacity of Cladophora sp. [14.28 for copper (II) and 16.75 for nickel (II)] is greater than Chara sp. [6.506 for copper (II) and 11.76 for nickel (II)]. Significantly high correlation coefficients indicated for the Langmuir adsorption isotherm models can be used to describe the equilibrium behavior of copper, chromium, nickel, and lead adsorption onto Cladophora sp. and Chara sp.     

Performance of duckweed (Lemna minor L.) on different types of wastewater treatment

Duckweed (Lemna minor L.) has a wide application in Turkey having suitable climatic conditions. In this study, the growth of duckweed was assessed in laboratory scale experiments. They were fed with municipal and industrial wastewater at constant temprature. COD, total nitrogen (TN), total phosphorus (TP) and ortho-phosphate (OP) removal efficiencies of the reactors were monitored by sampling influent and effluent of the system. Removal efficiency in this study reflects optimal results: 73-84% COD removal, 83-87% TN removal, 70-85% TP removal and 83-95% OP removal. The results show that the duckweed-based wastewater treatment is capable of treating the laboratory wastewater.     

Cost-effective approach to ethanol production and optimization by response surface methodology

Food wastes disposed from residential and industrial kitchens have gained attention as a substrate in microbial fermentations to reduce product costs. In this study, the potential of simultaneously hydrolyzing and subsequently fermenting the mixed carbohydrate components of kitchen wastes were assessed and the effects of solid load, inoculum volume of baker’s yeast, and fermentation time on ethanol production were evaluated by response surface methodology (RSM). The enzymatic hydrolysis process was complete within 6 h. Fermentation experiments were conducted at pH 4.5, a temperature of 30 °C, and agitated at 150 rpm without adding the traditional fermentation nutrients. The statistical analysis of the model developed by RSM suggested that linear effects of solid load, inoculum volume, and fermentation time and the quadratic effects of inoculum volume and fermentation time were significant (P < 0.05). The verification experiments indicated that the developed model could be successfully used to predict ethanol concentration at >90% accuracy. An optimum ethanol concentration of 32.2 g/l giving a yield of 0.40 g/g, comparable to yields reported to date, was suggested by the model with 20% solid load, 8.9% inoculum volume, and 58.8 h of fermentation. The results indicated that the production costs can be lowered to a large extent by using kitchen wastes having multiple carbohydrate components and eliminating the use of traditional fermentation nutrients from the recipe.     

Evaluation of physical, chemical and microbiological properties of lake Uluabat, Turkey

Lake Uluabat, known for its scenic beauty and richness of aquatic life, is situated in Marmara Region, Bursa (Turkey). On account of its importance, lake Uluabat was designated by the Ministry of Environment as a Ramsar site in 1998. Physical, chemical and microbiological parameters of the aquatic ecosystem in lake Uluabat were measured monthly at five stations from February 2003 to January 2004. The results showed that lake Uluabat can be classified as Class I with respect to temperature (16.36 +/- 7.47 degrees C), nitrate nitrogen (0.63 +/- 0.50 mgl(-1)), sodium (9.64 +/- 2.78 mgl(-1)), chloride (20.45 +/- 4.59 mgl(-1)), sulphate (54.80 +/- 29.97 mgl(-1)); as Class II with respect to dissolved oxygen (7.62 +/- 1.99 mgl(-1)), ammonium nitrogen (0.52 +/- 0.49 mgl(-1)), chemical oxygen demand (35.74 +/- 10.66 mgl(-1)), total coliform (2027 MPN100 ml(-1) (average value)); as Class III with respect to pH (8.69 +/- 0.16) and as Class IV with respect to total nitrogen (84.94 +/- 66.13 mgl(-1)), total phosphorus (1.11 +/- 3.01 mgl(-1)), biochemical oxygen demand (21.21 +/- 6.60 mgl(-1)) according to TWPCR (Turkey Water Pollution Control Regulation). The nutrient content of lake waterapparently indicated that lake had an eutrophic characteristic. Phosphorus was determined as a limiting factor in lake. The measured hardness values (140.94 +/- 14.61 CaCO3 mgl(-1)) indicated that lake water was classified as soft/hard during the study period. Eutrophic characteristic of the lake and contaminant accumulation in water will probably affect the future use of the lake. Therefore, pollution parameters must be regularly monitored and evaluated according to aquatic living and local regulations.