Fig. 2. (A) Hydrogen flow rate (mL-H2 d−1) and volumetric hydrogen production – VHP (mL-H2 d−1 L−1reactor). (B) Volumetric hydrogen yield – Y1H2mL-H2Lsugarcanevinasse-1 and molar hydrogen yield – Y2H2mol-H2moltotalcarbohydrates-1 during the entire APBR operation.Figure optionsDownload full-size imageDownload as PowerPoint slide
Data obtained from APBR operation at Semagacestat OLR of 84.2 kg-COD m3 d−1.Variables and parametersAverageMaximumpHa5.5–Total COD conversion (%)a31.346.3Soluble COD conversion (%) a19.246.3Total carbohydrates conversion (%)a7387.8Biogas composition (%)a38.771.1Molar hydrogen production rate (vH2vH2 – mmol-H2 d−1)a,b70.3154.9Hydrogen flow rate (Q1H2 – mL-H2 d−1)a,b1677.75252.6Volumetric hydrogen production - VHP mL-H2d-1Lreactor-1a,b761.72283.8Hydrogen yield (Y1H2-mL-H2Lvinasse-1)a,b12.728.1Hydrogen yield (Y2H2-mol-H2moltotalcarbohydrates-1)a,b1.63.7Hydrogen yield (Y3H2-mmol-H2g-1tCODconverted)a,b1.12.7Hydrogen yield (Y4H2-mmol-H2g-1sCODconverted)a,b3.29.6an = 24 samples.bStandard conditions of temperature and pressure (0 °C and 1 atm).Full-size tableTable optionsView in workspaceDownload as CSV
For both drugs, the ammonium and nitrate ions were identified; their total concentration was higher for IF compare to CF, but it still remained lower than the maximum concentration. The release of PO43− ions indicates the decomposition of heteroatoms ring in the drugs molecules ( Fig. 5). Therefore it can be assumed that the destruction of IF heteroatoms ring was more advanced and the lower amount of organic intermediates containing the phosphorus and nitrogen atoms (organic nitrogen, Norg) was present in the solution.
3. Results and discussion
3.1. Characterization of the magnetic PMADETA/PDVB IPNs
Fig. 1(a) and (b) show the typical photographs of Fe3O4 nanoparticles and OA-coated Fe3O4 nanoparticles dispersed in toluene and water. It is seen that Selumetinib the Fe3O4 nanoparticles cannot be dispersed in toluene and water, while the OA-coated Fe3O4 nanoparticles possess good dispersion ability in toluene. Additionally, the magnetic PMADETA/PDVB IPNs can be well dispersed in water (Fig. 1(c)), which may be attributed to the fact that many hydrophilic functional groups such as the amino, amide and ester groups are uploaded on the surface of the IPNs. In addition, it can be easily separated by a magnet from aqueous solution within 30 s (Fig. 1(d)). XRD and FT-IR spectra (Fig. S1(a) and (b)) indicate that existence of iron oxide particles (Fe3O4)  and , and TEM image (Fig. S1(c)) displays that the OA-coated Fe3O4 nanoparticles have the diameter of 5–10 nm.
Contributions AR-C 66096 emission sources to life-cycle environmental impact potentials of bioethanol produced from sweet sorghum stem on saline–alkali land (%).GWPAPEPPCOPHTPFAETPMAETPTETPPlant cultivation unit79.8487.4692.9744.6470.8899.0964.7277.31 Nitrogen46.2122.707.1825.0660.401.1448.9671.17 Phosphorus3.060.7310.352.102.530.094.071.49 Potassium1.100.260.070.760.94/0.820.39 Pesticides1.420.250.664.776.020.2410.854.25 Irrigation0.480.370.063.210.07/// Diesel1.490.200.058.730.11/0.02/ Field emissions26.0762.9474.60/0.8297.59//Feedstock transport unit2.410.120.051.320.750.083.710.08Bioethanol conversion unit17.7512.426.9954.0428.370.8231.5722.61 Electricity13.3611.832.2136.208.770.258.6110.95 Auxiliary materials1.280.470.0712.400.000.5722.9611.66 Wastewater//4.64/8.47/// Biogas combustion3.120.110.075.4311.13///Full-size tableTable optionsView in workspaceDownload as CSV
The greenhouse gases (GHGs) considered are CO2, CH4, N2O, and CO. GWP was expressed using CO2 eq. The impact of specific GHGs was compared with that of CO2 over a 100-year period. In this study, CO2 emission from fertilizer production and soil N2O emission are the main sources of GWP during plant cultivation. Another important contributor is purchased electricity used in bioethanol conversion units.
Comparison of AG 1879 traditional parameter estimation methods and the three optimized methods for Weibull at Site 3 and Site 4.HeightParameterSite 3Site 4MMMLEPSODEACOMMMLEPSODEACO10 mc7.3797.39737.32567.43087.47499.30469.27499.73419.70569.67k2.40892.43922.32612.2952.22122.56222.53442.47552.50552.5498R20.96620.96390.96930.97130.96910.90290.90190.92160.9230.9222RMSE0.00830.00860.00790.00770.0080.01140.01150.01030.01020.010330 mc9.0429.06189.02418.95788.945711.401611.363111.830811.886911.6919k2.40892.43512.39712.3962.37382.56222.53122.63422.71422.7465R20.94010.93950.94030.94270.94250.87250.86960.88170.88730.8861RMSE0.00980.00990.00980.00980.00980.01180.01190.01140.01140.011540 mc9.53639.55659.44569.53279.574812.024811.983712.537412.424812.6661k2.40892.43422.32732.35572.39762.56222.53052.56542.64142.7471R20.96540.96430.96550.96670.96610.88630.83070.89610.90070.8966RMSE0.00680.00690.00670.00670.00670.01030.01360.00980.00980.0160 mc10.279210.310.450610.349410.522112.961512.916413.444213.447613.865k2.40892.43292.38642.34812.31662.56222.52952.59932.60972.5666R20.96740.96640.9680.96920.96710.89270.89010.90470.90680.8977RMSE0.0060.00610.00590.00580.0060.00910.00920.00860.00860.00980 mc10.84110.862410.976111.004611.066613.6713.621913.857714.162514.2233k2.40892.43212.36682.31182.25912.56222.52882.50412.56132.6621R20.96820.96680.97210.97330.97210.90370.90160.91160.91850.9164RMSE0.00540.00550.00510.0050.00510.0080.00810.00760.00740.0075100 mc11.297911.319711.414111.37911.486714.246114.195614.243514.743815.2391k2.40892.43152.34272.3622.36692.56222.52832.56382.63232.6429R20.96560.96490.96650.96690.96630.89930.89790.89950.90530.8957RMSE0.00560.00570.00560.00550.00560.00760.00770.00760.0080.0084Full-size tableTable optionsView in workspaceDownload as basidia CSV
Considering the regional location, the Korean LCI database (KEITI) was primarily used for CO2 assessment in each phase of concrete, as given in Table 1. The LCI for a building material provides a collective data set that covers everything from the cradle to the grave. The Japanese Society of Civil Engineering (JSCE) LCI database (Sakai and Kawai, 2006) was also used for a data set that is not provided in the Korean LCI database, because the climate conditions and Dextromethorphan sources for concrete sources are similar in both countries. The FA investigated belongs to Class F (SiO2 + Al2O3 + Fe2O3 > 70%). The system boundary of all concrete constituents including SCMs is from cradle to gate of production plant. Hence, the specific lifecycle of SCMs includes the storage process of the by-product, crushing process, careful sorting process, metering process, and shipping process. The CO2 inventory for the concrete production phase was obtained from the conversion of energy sources consumed in the plant for annual productivity. The energy sources in the plant include electric power and crude oils.
The changes in economic structure decreased AHU-377 average of 8.66 Mt of CO2 emissions annually during the 1993–2011 period. However, there were discrepancies between different sub-periods. In specific, changes in the economic structure resulted in an average annual decrease of 46.29 Mt, 30.86 Mt and 21.17 Mt during the first, second and fourth stage, respectively, but an average annual increase of 69.50 Mt during the third stage (Fig. 6). These results were caused by different changing trends of economic structure during different stages. In fact, the proportion of MEIs in manufacture industry declined continuously from 26.50% to 19.50% during the entire study period. The proportion of LEIs continuously grew during the first and second stages (from 40.53% to 48.42%), and then fluctuated around 47.40%. The proportion of HEIs fluctuated decreasing before 2003 (from 32.97% to 28.21%), increased during 2003–2007 (from 29.25% to 33.51%), and then maintained stability during 2008–2011. Sector-level analyses reveal the following: (1) the proportion increase mainly occurred in sectors C21, C37, C39, C40 and C41; (2) the proportion decrease mainly occurred in sectors C15, C17, C28, C29 and C42; (3) the proportion rebound of HEIs mainly attributed to the development of sector C32 and C33. In summary, sectors in HEIs groups, particularly C32 and C33, deserve more attention during industrial restructuring. This conclusion will provide the basic foundation for the Chinese government to adjust industry policies, because structure adjustment based on industrial carbon emissions is better than that based on the Chinese Industrial Restructuring Catalog (Mao et al., 2013).