A novel objective function for optimal DG allocation in distribution systems using meta-heuristic algorithms

Meta heuristic algorithms have been introduced as a powerful method to solve the nonlinear optimization problems. These algorithms have been employed in many complex engineering problems due to their high capability in finding the solutions and reaching the optimal results within a short period of time. Optimization of distributed generation units in distribution systems, which have profoundly impacted on the system losses and voltage profile, is one of these nonlinear problems. In this study, a novel objective function was proposed for optimization procedure by meta-heuristic algorithms. The related objective function consists of the total cost of distributed generation units, cost of the purchased natural gas, cost of distribution system power losses, and penalty for greenhouse gas emissions. The electrical, cooling, and heating loads were considered in this study. In the distribution system, the waste and fuel cell were used to supply the required heating and cooling loads. The meta-heuristic algorithms including Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Imperialist Competitive Algorithm (ICA) were employed to find the optimal location and size of distributed generation units in a distribution system. A detailed performance analysis was done on 13 bus radial distribution system. The performances of three algorithms were compared with each other and results showed that the PSO was the fastest; and had the best solution and optimum results. Furthermore, the PSO reached the optimum solution in a fewer number of iterations than the GA and ICA algorithms.     

Post-tsunami changes in the littoral environment along the southeast coast of India

The 26th December 2004 Indian Ocean tsunami devastated coastal regions of the Indian subcontinent. Andaman and Nicobar Islands, coastal stretches of Tamil Nadu, Andhra Pradesh and Kerala were the most affected regions of India. Changes in the beach profiles, long shore currents, breaking wave characteristics in the surf zone at selected locations along the Tamil Nadu coast were studied during January, April, October 2005 and January 2006. Long shore sediment transport rates were estimated from the observed parameters. Studies were carried out earlier (1995-1996 and 1998) to understand the coastal environment over a one-year cycle in the study region. The post-tsunami observations were compared with the earlier studies to establish the variations in the littoral environment and to ascertain the normalcy of the littoral environment in the post-tsunami scenario. From the changes in the beach profiles, the shoreline was observed to recede by about 20m and built-up of backshore by about 0.5m at most locations. Observations from the field investigations and comparisons with earlier studies along this stretch of the coastline indicate that the coastline is yet to return completely to normalcy.     

浅层地下水升降对菜地土壤剖面硝化/反硝化微生物丰度的影响

为揭示湖泊近岸浅层地下水升降对菜地土壤剖面硝化与反硝化功能微生物基因丰度的影响,以洱海湖滨带菜地土壤剖面为研究对象,通过模拟地下水升降过程,分析了水位升高(S1)、水位降低(S2)及落干(S3)过程中土壤剖面AOA-amoA、AOB-amoA、nirK、nirS、nosZ基因丰度的变化特征,探讨了功能基因与土壤环境因子的耦合关系.结果表明:S3阶段的土壤剖面AOA-amoA和AOB-amoA基因丰度显著高于S1和S2;S1阶段的土壤剖面nirK、nirS、nosZ基因丰度均显著高于S2和S3.AOA-amoA基因丰度显著高于AOB-amoA基因丰度,nirS基因丰度显著高于nirK、nosZ基因丰度;不同取样时期的土壤剖面AOA-amoA、AOB-amoA、nirK、nirS、nosZ基因丰度均表现为A层B层C层D层.水位升降对土壤剖面AOA-amoA、AOB-amoA、nirK、nirS、nosZ基因丰度有显著影响,且AOA-amoA和nirS基因对水位升降更敏感,分别在硝化与反硝化作用中占主导地位;pH、有机碳(SOC)、全氮(TN)为功能基因AOA-amoA、AOB-amoA的环境驱动因子,而功能基因nirK、nirS、nosZ的环境驱动因子为土壤含水量(W)、铵态氮(NH~+_4-N)、硝态氮(NO~-_3-N)、TN、SOC、pH.该研究结果可为揭示浅层地下水升降过程中菜地土壤剖面氮素循环的微生物学机制提供科学依据.     

北京上空气溶胶浓度垂直廓线特征

利用2008—2010年北京地区3.5 km高空内飞机探测的气溶胶(粒径范围为0.10～3.00 μm)数据,分析了该地区气溶胶的时空分布特征. 结果表明:①气溶胶浓度(以数浓度计,下同)均随高度增加而减小,在1.5 km以上高空的气溶胶浓度垂直梯度变化明显低于1.5 km以下的垂直梯度变化. 4—11月气溶胶浓度季节变化表现为夏季最高、秋季次之、春季最低. ②气溶胶浓度廓线逐时(09:00—19:00)变化较清晰地反映出其受大气边界层演变的影响. 在0～1.5 km高空,白天气溶胶浓度高值出现在09:00—11:00,低值出现在13:00—14:00;而在1.5～3.5 km高空的气溶胶浓度时段分布与其相反. ③人为活动是影响气溶胶浓度区域水平分布的重要因子. ④将气溶胶浓度廓线垂直分布分为a、b、c 3类. 类型a的近地面气溶胶浓度(0～4 000 cm-3)低,垂直方向上变化很小;类型b的近地面气溶胶浓度(4 000～9 000 cm-3)较高,垂直递减明显;类型c的近地面气溶胶浓度特别高,量级达到104 cm-3,并在大气边界层顶(约1.5 km)附近迅速递减. 北京地区气溶胶浓度廓线以类型b居多.      

湖南攸县典型煤矿和工厂区水稻田土壤镉污染特征及污染途径分析

为了解湖南攸县水稻田土壤镉污染特征及污染途径,选择煤矿区、煤矿工厂区和工厂区三类典型样地进行农田土壤、灌溉水渠底泥及典型含Cd工业产品和副产品如煤、煤矸石和水泥等介质中Cd含量的分析研究.结果表明:1三类样地农田和表层自然土壤以及灌溉渠底泥中的平均Cd含量都超过了土壤环境质量标准0.3 mg·kg-1,煤矿区和煤矿工厂区的煤矸石Cd含量以及工厂区的水泥Cd含量都与相应自然土壤中含量相似,工厂区Cd的大气沉降通量较高;2三类样地土壤Cd剖面垂直分布差异明显,煤矿区和煤矿工厂区0~40 cm剖面的农田土壤Cd较自然土壤高,煤矿区农田和自然土壤中的Cd垂直向下迁移的潜力较高;3煤矿工厂区和工厂区点源下风向农田表土Cd含量明显比上风向低;4攸县煤矿区和煤矿工厂区农田土壤Cd的灌溉水输入途径较为重要,而煤矿工厂区和工厂区农田土壤Cd的大气输入途径也较为明显.     

厦门马銮湾养殖海区多环芳烃的污染特征

通过两个航次对厦门马銮湾养殖区及厦门西海域非养殖区的表层海水及沉积物中的多环芳烃的含量，组成进行调查。结果发现：马銮湾养殖区表层海水中多环芳烃的含量已达到生态毒理评价标准，马銮湾养殖海区的表层海水中多环芳烃的含量及组成存在明显的时间差异；马銮湾养殖海区沉积物中的多环芳烃含量明显高于非养殖区，并且在养殖海区的沉积物中检测到苯并（b)荧蒽，吲哚芘和苯并（ghi)Bei等没有最低安全值的高分子量多环芳烃的存在，直接威胁养殖水体的安全。此外，还对马銮湾养殖海区中多环芳烃污染的来源进行了分析。     

三江源地区高寒草地土壤功能的水平分异特征及其沿发生层的垂直变化

三江源地区是研究土壤生态系统功能响应气候变化的热点区域.为了研究三江源地区高寒草地土壤剖面功能特征和驱动机制沿发生层的差异,分析了高寒草地土壤剖面不同发生层的土壤功能指标(包括呼吸、氮转化速率和酶活等)以及与环境因子之间的相关关系.结果表明,土壤功能特征在高寒草甸和高寒草原之间不存在显著差异,表层土相比于深层土具有更高的呼吸、氮转化速率和酶活.土壤理化性质中全氮含量是不同发生层土壤功能特征的关键驱动因子,分别解释了土壤功能特征18.3%、21.4%和27.5%的水平分异.气候和植被因子主要在表层土中通过改变土壤理化性质间接影响土壤功能,但是大气氮沉降在深层土中对土壤功能仍存在影响.结果显示,三江源地区高寒草地土壤表现出显著的氮受限特征,为全球气候变化背景下土壤功能多样性的维持和对气候变化的响应提供了新的见解.     

不同有机肥中磷在土壤剖面中累积迁移特征与有效性差异

为明确连续施用不同有机肥后土壤剖面中磷的分布规律和迁移特征,探讨不同有机肥磷投入下农田磷负荷.通过4 a连续田间定位试验,定量化研究连续施用不同有机肥后土壤剖面中磷的累积迁移特征与有效性差异.结果表明:(1)连续4 a施用不同有机肥后,肥料中磷主要积累在0~15 cm表层土壤,土壤全磷、速效磷含量均随土壤深度增加逐渐降低;连续4 a施用高量有机肥后,其带入的磷可明显迁移到15~30 cm土层,施用高量猪粪速效磷可迁移到60~90 cm土层.(2)连续4 a施用不同有机肥后,土壤表层中速效磷占全磷比例增加,且高用量与低用量之间差异显著.土壤剖面中速效磷占全磷比例的大小顺序为:猪粪处理鸡粪处理污泥处理磷肥处理.(3)施用鸡粪、猪粪、污泥和磷肥后土壤表层中速效磷含量随磷投入量增加呈先增加后平缓的规律.(4)本试验条件下,不同有机肥相同磷投入下对表层土壤速效磷贡献存在较大差异,表现为:猪粪鸡粪污泥.猪粪带入磷的生物有效性和移动性明显高于鸡粪、污泥和磷肥.     

土地利用方式对土壤有机质及其碳库管理指数的影响

采用野外调查和室内分析的方式对子午岭不同土地利用方式下,土壤有机质、3种活性有机质及其碳库管理指数(CMI)进行了研究,结果表明,土壤有机质、3种活性土壤有机质含量均随土层的加深逐渐降低,在土壤剖面基本表现为林地、撂荒未翻耕地>撂荒翻耕地>农用地.同一土层,3种土壤活性有机质含量及其有效率表现为低活性有机质>中活性有机质>高活性有机质.不同利用方式下,活性有机质有效率随有机质活性增强,呈现撂荒未翻耕地>林地>撂荒翻耕地>农用地的趋势.不同利用方式之间的CMI的差异随有机质活性的增强而增大,且影响深度也逐渐加深.在0~30cm土层内,林地3种活性有机质的CMI高于撂荒翻耕地和农用地;而在30cm之下土层,3种利用方式低活性有机质的CMI相差不大,但中活性有机质和高活性有机质的CMI表现为林地>撂荒翻耕地>农用地.3种活性土壤有机质与其他生物化学性质之间均表现为显著或极显著相关关系,表明活性有机质可以指示土地利用方式对土壤有机质和CMI的影响.     

Leaf metabolic influence of glyphosate and nanotubes on the Arabidopsis thaliana phyllosphere

Chemical exposure can indirectly affect leaf microbiota communities, but the mechanism driving this phenomenon remains largely unknown. Results revealed that the co-exposure of glyphosate and multi-carbon nanotubes (CNTs) caused a synergistic inhibitory effect on the growth and metabolism of Arabidopsis thaliana shoots. However, only a slight inhibitory effect was induced by nanotubes or glyphosate alone at the tested concentrations. Several intermediate metabolites of nitrogen metabolism and fatty acid synthesis pathways were upregulated under the combined treatment, which increased the amount of energy required to alleviate the disruption caused by the combined treatment. Additionally, compared with the two individual treatments, the glyphosate/nanotube combination treatment induced greater fluctuations in the phyllosphere bacterial community members with low abundance (relative abundance (RA) <1%) at both the family and genus levels, and among these bacteria some plant growth promotion and nutrient supplement related bacteria were markable increased. Strikingly, strong correlations between phyllosphere bacterial diversity and metabolites suggested a potential role of leaf metabolism, particularly nitrogen and carbohydrate metabolism, in restricting the range of leaf microbial taxa. These correlations between phyllosphere bacterial diversity and leaf metabolism will improve our understanding of plant-microbe interactions and the extent of their drivers of variation and the underlying causes of variability in bacterial community composition.