基于人工神经网络和遗传算法研究锰过氧化酶脱色甲基橙

基于锰过氧化物酶(MnP)氧化脱色偶氮类染料的原理,实验研究MnP对甲基橙的脱色工艺,采用人工神经网络(ANN)和遗传算法(GA)建立脱色模型并优化工艺。建立的ANN模型的误差、相关系数、均方根误差和绝对平均偏差分别为0.0009、0.9971、1.21和6.82,模型有效且能够用于预测和工艺优化。采用GA对ANN模型进行数值寻优,得到的最佳工艺条件为酶液量0.6 mL,Mn2+浓度4 mmol/L,H2O2浓度0.49 mmol/L。该条件下脱色率达到(90.74±0.59)%。ANN耦合GA有效地建立了锰过氧化物酶脱色甲基橙的模型,并优化了工艺参数,为甲基橙脱色的研究提供一定参考。     

Trends in Chemical Composition of Wet-only Precipitation at Rural French Monitoring Stations Over the 1990–2003 Period

The long-term monitoring of precipitation and its chemical composition are important for identifying trends in rain quality and for assessing the effectiveness of pollution control strategies. A statistical test has been used to the atmospheric concentrations measured in the French rural monitoring network (MERA) in order to bring out spatio-temporal trends in precipitation quality in France over the period 1990–2003. The non-parametric Mann–Kendall test which has been developed for detecting and estimating monotonic trends in the time series was used and applied in our study at annual values of wet-only precipitation concentrations. The emission data suggest that SO₂ and NO _x emissions decreased (−3.3 and −2.0% year⁻¹, respectively) contrary to NH₃ emissions that increased slightly (+0.2% year⁻¹) over the period 1990–2002 in France. On the national scale, the pH values have a significant decreasing trend of −0.025 ± 0.02 unit pH year⁻¹. and concentrations in precipitation have a significant decreasing trend, −3.0 ± 1.6 and −3.3 ± 0.6% year⁻¹, respectively, corresponding with the downward trends in SO₂ emissions in France (−3.3% year⁻¹). A good correlation (R ² = 0.84) between SO₂ emissions and concentrations was obtained. The decreasing trend of was more significant (−5.4 ± 5.2% year⁻¹) than that of (−1.3 ± 2.4% year⁻¹). Globally, the concentration of the major ions showed a clear downward trend including marine and alkaline ions. In addition, the relative contribution of HNO₃ to acidity precipitation increased by 51% over the studied period.     

1998年长江流域暴雨洪水环流背景分析

１９９８年主汛期,由于西太平洋副热带持续偏南、偏强,中高纬度维持稳定的阻塞形势,６、７月雨带长期在鄱阳湖、没庭湖地区徘徊,造成长江中下游地区严重洪涝;８月随着副高北抬,长江上游出现多次强降水过程,长江干流受中下游洪水顶主上游洪峰下泻的影响,水位居高不下,多数水文站出现了超记录的历史最高水位。１９９８年的已成为一次少有的新的长江大洪水的典型。     

甘肃临夏地区人降雨气候背景分析

利用常规气象塑料,统计分析在作物生长的主要季节实施人工降雨的可能性及潜力,为开展人工降雨提供物理依据,分析结果表明：人工降雨的可能性及潜力分布存在明显的地域性和时间性,由此提出了为抗旱减灾面在临夏地区充分开发利用云水资源的具体对策和措施。     

秦皇岛地区气候干旱与人工增雨的探索

气候分析表明:随着气候变化及环境城市化,秦皇岛市区域年平均气温指数呈上升趋势,特别是近10年出现了连续偏高的异常变化;年降水指数呈明显减小趋势,出现了连年干旱,高温少雨不仅使生态环境不断恶化,而且使农田干旱、水库蓄水严重不足,因此人工增雨变得更加迫切。目前,秦皇岛市人工增雨工作已进入常态化、业务化轨道。总结1999—2008年火箭人工增雨经验,人工增雨操作的技术关键:一是分析局地降水气候规律;二是利用碘化银进行人工增雨需要适当的温度条件,即所谓进行冷云催化。在增雨时应充分考虑这一物理机制,选择好合适的发射高度,把催化剂送到可催化的温度环境中,以保证作业成功率。     

垂直流人工湿地处理农村污水的探讨

论述了人工湿地净化的机理以及垂直流人工湿地的设计方法,通过工程实践证明,采用该方法处理农村污水具有投资省、运行简便、处理效果稳定、操作简便、出水水质好能达标排放等诸多优点,可作为农村污水处理的优选方案。     

A hybrid model based on smooth transition periodic autoregressive and Elman artificial neural network for wind speed forecasting of the Hebei region in China

Wind energy, one of the most promising renewable and clean energy sources, is becoming increasingly significant for sustainable energy development and environmental protection. Given the relationship between wind power and wind speed, precise prediction of wind speed for wind energy estimation and wind power generation is important. For proper and efficient evaluation of wind speed, a smooth transition periodic autoregressive (STPAR) model is developed to predict the six-hourly wind speeds. In addition, the Elman artificial neural network (EANN)-based error correction technique has also been integrated into the new STPAR model to improve model performance. To verify the developed approach, the six-hourly wind speed series during the period of 2000–2009 in the Hebei region of China is used for model construction and model testing. The proposed EANN-STPAR hybrid model has demonstrated its powerful forecasting capacity for wind speed series with complicated characteristics of linearity, seasonality and nonlinearity, which indicates that the proposed hybrid model is notably efficient and practical for wind speed forecasting, especially for the Hebei wind farms of China.     

神经网络在空气污染预报中的应用研究

空气污染预报是一项复杂的系统工程,是当今环境科学研究的热点,国内外已有将神经网络法应用于大气污染预报的研究。本论文以PM2．5为例,采用伦敦市PM2．5的小时平均浓度数据,使用传统的BP神经网络建立预报模型,定量预测伦敦市PM2.5的小时平均浓度,探讨了大气污染预报网络的建模过程中,扩大样本集、去除样本集数据噪声和在输入向量中加入气象变量等因素对建模所产生的影响。最后得出结论,适当的选择样本集、气象变量,有利于提高所建立网络模型的预测精度。     

酸雨条件下城市农业土壤镉的释放研究

本文选取成都市典型农业土壤为研究对象,根据成都市降雨特征,模拟一定范围pH及主要阴、阳离子浓度配制成母液开展酸雨淋滤实验,以确定酸雨中影响土壤重金属元素镉溶解度的关键因素,探明其对镉释放的影响程度。研究结果表明,总体上酸雨加速了土壤镉的释放。不同类型土壤在同一酸雨条件下,镉的释放速度和最大释放量也不同。酸雨pH值和主要阴、阳离子浓度对镉释放的影响有明显的规律。     

STUDIES ON THE PURIFYING SPACE IN ARTIFICIAL WETLANDS WITH CATTAIL AND RUSH

调查了人工湿地水生植物根区理化特性,根系扩展的深度和位置,微生物和酶的分布状况;比较了不同深度人工湿地污水净化效果;探讨了人工湿地污水处理系统最佳净化空间位点。通过对香蒲、灯心草人工湿地的研究,发现植物的根系主要分布在基质上层２５ｃｍ区域内,在５到１０ｃｍ区域内,微生物数量最多,２５ｃｍ区域次之,３５ｃｍ以下较少。系统表层磷酸酶,葡聚糖脱水酶和蛋白酶的活性较２０ｃｍ区域内各酶活性强。对于废水的净化而言,系统２０ｃｍ和６０ｃｍ处的净化效果差别很小。结果表明,人工湿地废水处理系统上部区域为较佳净化空间。