牛粪-化肥配施对水稻田氮磷迁移转化的影响

在控制外源N输入量相同的前提下,通过田间小区实验,探讨有机肥与化肥不同施用量（牛粪施用量：5,10,20t/hm²）对稻田田间土-水界面氮磷迁移转化特征的影响.结果表明：控制稻田水中NH₄⁺-N、NO₃^--N、TN和TP输出的最佳时期分别为施肥后的第5,30,7,20d,且TN和TP浓度随时间变化符合单指数衰减方程（0.7444≤R²≤0.9724;1.1×10^-6≤F≤0.0055）.采用牛粪部分代替化肥的施肥方式,在一定范围内能降低稻田退水中TN、TP输出负荷（41.8%、36.0%、64.3%;20.3%、39.1%、48.9%）,还可以降低稻田水中N/P,降低水体富营养化风险.同时,牛粪的施用可提高土壤中脲酶和磷酸酶的含量,促进氮磷向植物可吸收形态转化.综合经济成本和生态效益核算,采用10t有机肥代替无机肥的处理是相对经济环保的施肥方法,该施肥方式下,氮磷年输出负荷分别为17.70,1.26kg/hm².     

马莲河流域河水化学特征和化学风化过程分析

采用Gibbs图解和端元分析方法研究了马莲河水化学特征、离子来源和化学风化作用,利用质量平衡正演模型评价了各风化作用对水化学组分的贡献率。结果表明,马莲河水为高TDS咸水,阳离子以Na~+、Mg~(2+)为主,阴离子以Cl~-、SO_4~(2-)为主;沿河水流向TDS降低,水化学类型由Cl-Na型演变为HCO_3·SO_4-Na·Mg型;河水化学组分的主要形成作用为化学风化,蒸发盐主导了流域风化过程,对离子组分平均贡献率高达76.5%,硅酸盐和碳酸盐风化较弱;化学风化具空间变异,从上游到下游,硫酸盐和碳酸盐贡献率增加,岩盐贡献率降低。岩性是控制流域化学风化作用的首要因素,降雨量和径流量可能也有一定影响。     

DZ125合金HY3包覆型涂层退除研究

目的 研究化学法退除DZ125合金HY3包覆型涂层。方法 采用真空电弧镀技术（AIP）在定向凝固镍基高温合金DZ125上制备包覆型涂层HY3,利用化学方法完全退除基体上的涂层,通过失重法研究对比1#和2#退除溶液退除HY3涂层和DZ125合金的退除速率,采用扫描电镜（SEM）对退除后的HY3涂层和DZ125基体的微观组织进行观察。结果 经过100 min,2#溶液可以将20 ?m左右的HY3涂层完全退除,采用1#溶液需要超过100 min才能完全退除涂层。两种对DZ125合金的腐蚀性很小,对于同一种合金而言,1#溶液和2#溶液对合金的腐蚀速率比值为1︰13。在1#溶液中,合金与涂层腐蚀速率的比值为1︰87.65;在2#退除溶液中,合金与涂层腐蚀速率的比值为1︰6.81。结论 1#溶液更加适合退除DZ125合金上的HY3涂层。     

A study on the interactions among several plant secondary compounds and aphids

The research, focused on the specific interactions among seven plant secondary compounds and aphids, was carried out and the preliminary results showed: (1) "T-typed tube method" was regarded as the best method compared with others designed to observe the interactions. (2) Cabbage aphid was able to be attracted by laurolene while it was not susceptible to α-pinene, β-pinene and diamylene. (3) Gossypol, a major secondary substance in cotton, was able to be implicated as feeding attractant to cotton aphid. (4) Rutin might be implicated repellent to cotton aphid.     

在线自动监测仪与实验室国标方法测定地表水中总氮的比对分析

随着监测技术的发展,地表水中越来越多的污染物可采用自动监测仪器实现实时监测。采用自动监测与实验室国标方法测定地表水中总氮的结果是否可比以及造成差异的原因,文章根据实际样品比对实验对此进行了探讨。     

水中氮类污染物的联系与区别

叙述了水体中含氮类污染物的来源，种类，相互转化方式和条件，表征意义等，以便对水中氮类污染物有一个全面，系统的认识。     

氨氮测定过程中有关问题的探讨

针对纳氏比色法测定氨氮过程中存在的问题，提出了相应的解决办法。消除了混浊和泡沫干扰问题，降低了空白吸光度，提高了测定的准确度。     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

城市大气中颗粒物的研究现状及健康效应

综述了大气尘(TSP、PM10、PM2.5)的研究现状,重点围绕TSP、PM10、PM2.5的物理特征、化学组成(有机组成、重金属元素的总含量及其各化学形态分布)及其源解析进行描述,也提及了大气颗粒物与健康的关系.     

同时分解法测定水中总氮和总磷

通过实验找到了同时测定水中总氮和总磷的条件,实现了总氮和总磷的同时测定。