青年群体对传统绿色生态文化回归的影响研究

传统方法对青年群体绿色生态文化回归的影响分析中,存在青年群体分析影响片面,影响分析计算准确率较低的问题。为此提出青年群体对传统绿色生态文化回归的影响与思考。通过勒布朗斯回归数学影响方程确定影响因子,建立青年群体主观因子与客观因子之间的动态关联;采用大数据分析,构建大数据影响因子数据分析模型;依托绿色生态文化回归影响算法,从而完成青年群体对传统绿色生态文化回归的影响分析。该影响分析方法比传统方法平均准确度提升3.55倍,且能够实现青年群体对传统绿色生态文化回归的影响分析。     

废水中硝基苯类化合物测定方法的探讨及新方法研究

探讨了废水中硝基苯类化合物的气相色谱法测定方法中的水样预处理操作繁琐,实验耗时长,且萃取时使用易挥发有毒有害的有机物二氯甲烷。另一种常见的测定方法还原-偶氮分光光度法,而染料、印染制革等工业废水的颜色较深,对测定造成干扰,通常通过蒸馏预处理消除水样颜色带来的干扰,而在蒸馏过程中因硝基苯类沸点较高不能将水样中的硝基苯类化合物全部蒸出,导致检测结果偏低。提出了一种经聚己内酰胺脱色,简单又快捷地消除水样中颜色的干扰,又避免了硝基苯类化合物蒸馏不完全的问题,再利用还原-偶氮分光光度法准确测定废水中硝基苯类化合物的方法。     

湿地植被对污水净化效果分析研究

人工湿地植被种植对污水净化具有显著性的改善作用,分析人工湿地植被种植与污水净化的量化关系,分析人工湿地植被种植对污水改善的原理,建立生态植被污水净化处理模式,采用多元回归分析方法人工湿地植被对水质控制和小型富营养水体生态恢复的效益因素,以营养物的去除率、重金属的去除率以及有机物去除率为指标,分析人工湿地植被种植对污水净化的生态学改善模型。研究表明,人工湿地植被种植能增加水体透明度,降低水体中的富营养物和重金属等物质,对污水具有显著性的改善作用。     

环保宣教影视作品制作中生态环保意识分析研究

传统环保宣教影视作品内容过于空泛,难以引起人们共鸣,近年来环境问题逐渐严重,带来一系列自然灾害,为人民生命财产带来巨大损失。影视作品能够起到传播观念和导向舆论的作用,将生态环保意识引入影视作品可以引发人们的思考。对环保宣教影视作品中生态环保意识进行分析,探讨了生态环保意识的建立过程以及融入过程,通过实验研究了环保宣教影视作品中引入生态环保意识对环境保护起到的作用。实验结果表明,引入生态环保意识的环保宣教影视作品能够更好地向社会大众宣传环保好处,更好地促进环境保护工程的实施。     

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.     

青铜峡铝厂氟污染对广武乡玉米影响的调查分析

监测了青铜峡铝厂东南方向４．５ｋｍ的广武乡玉米叶，得知含氟量为４３．９４－１６６．１ｍｇ／ｋｇ，对照样品树新林场玉米叶的含氟均值为１３．１５ｍｇ／ｋｇ，广武乡的玉米受到了严重的氟污染，农作物减产严重。     

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.     

Determination of PAHs by On-Line Polarization Synchronous Fluorescence with HPLC

A novel analytical method has been established for on-line simultaneous determination of fluorene and acenaphthene,chrysene and benzo[a]anthracene (B[a]A) by polarization synchronous fluoromet.y (PSF) coupled to high performance liquid chromatography (HPLC). The detection limits were: 0.039, 0.046, 0.016 and 0.042 mgL-1 for fluorene, acenaphthene, chrysene and B[a]A, respectively. The proposed method has been successfisily applied to simultaneous determination of these PAHs in environmental air and marine sediment samples.     

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.