Song Xinshan

Influences of seasons, N/P ratios and chemical compounds on phosphorus removal performance in algal pond combined with constructed wetlands

Nitrogen (N) and phosphorous (P) are main contaminants and P removal was restrained by several factors: season, N/P, and chemical compounds (CCs) in water ecosystems. In this paper, two algal ponds combined with constructed wetlands were built to increase the removal performance. Different hydraulic retention time (HRT), different N/P and chemical compounds were chosen to investigate the influences of the above factors on the contaminant removal performance. The optimum phosphorus removal rate was 69.74% under the nitrogen removal of 92.85% in influent containing PO43- after 3-day HRT in algal pond combined with constructed wetlands. The investigation results indicated that these factors improved the nutrient removal efficiencies. Seasonal influence on the removal performance can be avoided by choosing the optimal HRT length of 3days. The higher N/P at 60 can improve the phosphorus removal and the lower N/P at 15 showed the stronger synergistic effect between phosphorus and nitrogen removals. Compared with PO3- and P2O74- in influent, PO43- affected phosphorus removal more significantly. The better linear fitting between organic phosphorus removal and nitrogen removal in influent contained P2O74- was found. Algae can absorb nutrients for growth, and oxygen release, microbial activity intensification and microbial carbon replenishment induced by algae will improve the performance. The study suggested that the control of HRTs, N/Ps, CCs, and algae might be an effective way to improve wastewater treatment performance.

Effects of iron and calcium carbonate on the variation and cycling of carbon source in integrated wastewater treatments

Iron and calcium carbonate were added in wastewater treatments as the adjusting agents to improve the contaminant removal performance and regulate the variation of carbon source in integrated treatments. At different temperatures, the addition of the adjusting agents obviously improved the nitrogen and phosphorous removals. TN and TP removals were respectively increased by 29.41% and 23.83% in AC-100 treatment under 1-day HRT. Carbon source from dead algae was supplied as green microbial carbon source and Fe2+ was supplied as carbon source surrogate. COD concentration was increased to 30mg/L and above, so the problem of the shortage of carbon source was solved. Dead algae and Fe2+ as carbon source supplement or surrogate played significant role, which was proved by microbial community analysis. According to the denitrification performance in the treatments, dead algae as green microbial carbon source combined with iron and calcium carbonate was the optimal supplement carbon source in wastewater treatment.

海藻酸钠/蒙脱石联合负载型纳米Fe 0 对Cu (II)的去除研究

由于蒙脱石负载型纳米Fe0（Mt-nZVI）在使用中易随水迁移，造成出水水质混浊和Fe0流失.因此，本研究制备了海藻酸钠（SA）和蒙脱石（Mt）联合负载型纳米零价铁（SA/Mt-nZVI），探究其对水中Cu（Ⅱ）的去除效果，并考察了Cu（Ⅱ）初始浓度、pH值对去除率的影响.结果表明：以2%（质量分数）SA和6%（质量分数）Mt-nZVI条件制备的SA/Mt-nZVI小球对Cu（Ⅱ）处理效果好，反应24 h后，SA/Mt-nZVI小球对初始浓度为40 mg·L-1 Cu（Ⅱ）的去除率达到92.11%，与游离的Mt-nZVI颗粒相比，其活性并未降低；Cu（Ⅱ）的去除率随其初始浓度升高而降低；在pH为2~6之间，Cu（Ⅱ）去除率随pH升高而升高.SA/Mt-nZVI小球可有效净化污水中的Cu（Ⅱ），将其重复使用3次后，对Cu（Ⅱ）的去除率仍维持在59.52%.

Parallelization and Performance Test to Multiple Objective Particle Swarm Optimization Algorithm

In recent years, Model calibration and parameter estimation with high complexity is a common problem in many areas of researches, especially in environmental modeling. This paper proposes a comparatively simple technique on the parallel implement of Multi-objective Particle Swarm Optimization algorithm (MOPSO). The transformation of the sequential objective evaluation in the MOPSO is based on the Matlab parallel computing tool box. Two study cases of different complexity demonstrate that the parallel implementation resulted in a considerable time saving. The deviation of computational time indicates that MOPSO has the characteristic of randomness because of the crowding distance and the dominant ranking. The proposed parallel MOPSO therefore, provides an ideal means to solve global optimization problems that are comparatively with high complexity.