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.     

Bi-national assessment of the Great Lakes: SOLEC partnerships

Many administrative jurisdictions have authority over parts of the Great Lakes, sometimes with competing purposes as well as governance at differing scales of time and space. As demand increases for high quality information that is relevant to environmental managers, environmental and natural resource agencies with limited budgets must look to interdisciplinary, collaborative approaches for the collection, analysis and reporting of data. The State of the Lakes Ecosystem Conferences (SOLEC) were begun in 1994 in response to reporting requirements of the Great Lakes Water Quality Agreement between Canada and the U.S. The biennial conferences provide independent, science-based reporting on the state of health of the Great Lakes ecosystem components. A suite of indicators necessary and sufficient to assess Great Lakes ecosystem status was introduced in 1998, and assessments based on a subset of the indicators were presented in 2000. Because SOLEC is a multi-agency, multi-jurisdictional reporting venue, the SOLEC indicators require acceptance by a broad spectrum of stakeholders in the Great Lakes basin. The SOLEC indicators list is expected to provide the basis for government agencies and other organizations to collaborate more effectively and to allocate resources to data collection, evaluation and reporting on the state of the Great Lakes basin ecosystem.     

Tree species in relation to soil moisture regime in northwestern Ontario,Canada

Selected data on site, vegetation cover, and soil, including soil moisture regime (SMR), were collected from 2 167 field plots in northwestern Ontario, Canada. SMR provides an estimate of an averaged, annualized soil moisture supply throughout a complete vegetation cycle. SMR is based upon a relative scale that subjectively ranks sites from , 0, and 1 through 9 along a soil moisture continuum which relates to a dry to wet gradient. SMR may be generally correlated to tree growth, stand composition, degree of competition, nutrient availability and overall site quality.This paper reports on relationships between SMR and major tree species. Results highlight relationships between SMR class and the broad ecological ranges of several tree species. In northwestern Ontario, the determination of SMR can help resource managers to better understand the ecology of boreal sites.     

Comparative rice seed toxicity tests using filter paper,growth pouch-tm,and seed tray methods

Paper substrate, especially circular filter paper placed inside a Petri dish, has long been used for the plant seed toxicity test (PSTT). Although this method is simple and inexpensive, recent evidence indicates that it gives results that are significantly different from those obtained using a method that does not involve paper, especially when testing metal cations. The study compared PSTT using three methods: filter paper, Growth Pouch-TM, and seed tray. The Growth Pouch-TM is a commercially available device. The seed tray is a newly designed plastic receptacle placed inside a Petri dish. The results of the Growth Pouch-TM method showed no toxic effects on rice for Ag up to 40 mg L^–1 and Cd up to 20 mg L^–1. Using the seed tray method, IC₅₀ (50% inhibitory effect concentration) values were 0.55 and 1.4 mg L^–1 for Ag and Cd, respectively. Although results of filter paper and seed tray methods were nearly identical for NaF, Cr(VI), and phenol, the toxicities of cations Ag and Cd were reduced by using the filter paper method; IC₅₀ values were 22 and 18 mg L^–1, respectively. The results clearly indicate that paper substrate is not advisable for PSTT.     

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.     

垃圾填埋场渗出液中有害成分的研究

研究垃圾填埋场渗出液中的有害成分。渗出液样品用适当的方法处理后 ,用气相色谱 -质谱联用方法和原子发射光谱法进行定性分析。然后用原子吸收分光光度法和反相高效液相色谱法定量测定样品中微量的 Cu、Zn、Pb、Cr、Cd、Hg、苯酚、对甲苯酚、萘、蒽     

工作场所空气中硫酸雾（SO3）的分析

采用碘量法测定工作场所空气中的三氧化硫及硫酸雾，三氧化硫及硫酸雾经中性水吸收后与碘化钾和碘酸钾反应，析出的碘与淀粉指示剂作用产生蓝色，进行比色测定。     

地面水环境质量评价的有时序多目标决策方法

将有时序多目标决策方法应用于地面水环境质量优势的比较，介绍了决策方法的原理和评价步骤。实例分析表明该方法计算过程简便，分辨率高，排序结果与实际环境质量状况相符合。