Effect of ammonia load on efficiency of nitrogen removal in an SBBR with liquid-phase circulation

Abstract

-The removal of biological nitrogen from a synthetic wastewater with different ammonium nitrogen concentrations (50 and 100 mgN-NH 4 + /L) by a nitrification and denitrification process using a sequencing batch biofilm reactor (SBBR) with liquid-phase circulation was studied. The system with a total working volume of 4.6 L (3.7 L in the reactor and 0.9 L in the reservoir) treated 2.1 L of synthetic wastewater in 12-h cycles. As inoculum two types of biomass were used: an anaerobic/anoxic one from an up-flow anaerobic sludge blanket reactor (UASB) and an aerobic one from a prolonged aeration activated sludge system. The system, maintained at 30 ± 1 o C, operated in batch mode followed by fed-batch mode and was aerated intermittently. During fed-batch operation the reactor was fed with an external carbon source as electron donor in the denitrifying step and with no aeration. When the reactor was fed with 50 mgN-NH 4 + /L, efficiencies of removal of ammonium nitrogen and total nitrogen from the effluent were 93.8 and 72.2%, respectively, and nitrite, nitrate and organic nitrogen concentrations were 0.07, 6.4 and 0.5 mg/L, respectively. On the other hand, when the influent ammonium nitrogen concentration was 100 mgN-NH 4 + /L, residual nitrite and nitrate were 0.17 and 20.4, respectively, and no N-Org was found in the effluent. It should be mentioned that residual nitrate remained unaltered at the different C/N ratios used. Consequently, efficiency of total nitrogen removal was reduced to 66.7%, despite efficiency of ammonium nitrogen removal exceeding 90%. These results show the potential of the proposed system in removing ammonium nitrogen from liquid effluents with a moderate ammonium nitrogen concentration.

Hybrid gradient particle swarm optimization for dynamic optimization problems of chemical processes

“…For case (1), control variables are discretized into10, 20 stages; for case (2), control variables are discretized into 11, 20 stages. Our experiment results are listed in Table 4, along with those results obtained by Luus with IDP, [7] Balsa-Canto et al with restricted secondorder information (RSOI), [3] Shelokar et al with multicanonical jump walk annealing assisted by tabu list (MJWAT). [18] Figures 7 and 8 plot control trajectories u and fractional difference graphs for both cases.…”

“…[12,34] [35] problem 4 consists of determination of four control variables of a chemical reactor, which aims to maximize the economic benefit. The problem has been studied by Luus, [7] Balsa-Canto et al, [3] and Shelokar et al [18] The system is described as follows: and the following bounds on the control variables: 0≤u 1 ≤20; 0≤u 2 ≤6; 0≤u 3 ≤4; 0≤u 4 ≤20:…”

“…[1,2] During the last two decades, a number of algorithms have been proposed for handling DOPs due to their profound importance in industrial and engineering practices. These algorithms can be generally divided into two categories: gradient-based algorithms (GBA) [3][4][5][6] and gradient free algorithms (GFA). [7][8][9][10][11][12][13][14][15][16][17][18][19] Most of traditional algorithms, including Newton method, [3] sequential quadratic programming (SQP), [4] and interior-point algorithm, [5,6] belong to GBAs.…”

“…[14] This problem is very challenging because the performance index is of low sensitivity to the control policy. [34] The mathematical model is described as follows: ASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING HYBRID GRADIENT PARTICLE SWARM OPTIMIZATION 715 42594 262 Luus and Hennessy [34] Direct search 31 / 32.61339 / / / / 45 / 32.686867 / / / / Upreti [10] GA 45 / 32.59277 / / / / Angira and Santosh [14] TDE 45 30 32.684338 / / / / [7] IDP 10 / 20.0895 / / / / / Eva Balsa-Canto [3] RSOI 10 / 20.0895 / / / / / P.S. Shelokar [18] MJWAT [7] IDP 11 / 21.757 / / / / / Eva Balsa-Canto [3] RSOI 11 / 21.757 / / / / / P.S.…”

Evaluation of the microbial diversity of denitrifying bacteria in batch reactor

“…Many inocula from domestic and industrial sewage treatment plants may contain denitrifying bacteria, mainly in activated sludge systems (Liu et al, 2006;Daniel et al, 2009), where the biological nitrogen removal occurs to promote denitrification, i.e., under heterotrophic anoxic conditions, the organic carbon sources act as electron donors and reduce nitrate to nitrogen gas (Canto et al, 2008).…”