Effect and its time lags of water level fluctuations in Three Gorges Reservoir on the macroinvertebrates in a tributary bay北大核心CSCD

In order to study how water level fluctuations (WLF) of reservoir influence the macroinvertebrate in tributary bay, we studied the effect of WLF of the Three Gorges Reservior on macroinvertebrate communities in Xiangxi Bay, and the time lags of such effect, based on the surveys in spring and summer from 2005 to 2010. In this research, WLF was represented by water level drawdown (WLD) and the sum of absolute values of rate of water level fluctuations (RWlf). Pearson correlation analysis was used to analyze the relationship between WLF and macroinvertebrates. No significant correlation was found between macroinvertebrates and sum of absolute values of RWLF, while WLD showed significant influence on some biotic parameters. In spring, WLD did not cause significant effect to macroinvertebrates (P > 0.05). In summer, however, the influence was significant, especially in the area of the downstream (XX01 - XX02) of the Xiangxi Bay (P < 0.05). The middle reach of the bay (XX05), located in the conjunction area between Xiangxi Bay and a secondary tributary of the TGR, was also affected significantly (P < 0.05). The relative abundance of Tubificidae declined with the increase of the WLF, while abundance of Chironomidae increased. The time lags of the influence to macroinvertebrates were about 15 days. This analysis indicated that WLF in the mainstream of the reservoir mainly influences the downstream of the tributary bay, and also affects the conjunction area of the secondary tributary. Chironomidae are more tolerant than Tubificidae in water-body with dramatic disturbance, therefore can be considered as the indicator of the effect of summer WLF on macroinvertebrates.     

An alternative work measurement method and its application to a manufacturing industry

Difficulties in determining the standard time justify the need to develop alternative methods to direct measurement procedures. The indirect methods which are comparison and prediction, standard data and formulation, predefined movement-time systems have several deficiencies in time measurement procedures. In this study, an alternative indirect work measurement method based on artificial neural networks (ANNs) is presented which is simple and inexpensive. For the application of the proposed method, the products that have similar production processes are selected among the whole product family produced in a manufacturing company. The standard times of the sampled products that are previously measured are used and the standard times of the remaining several products and semi-products are predicted by the proposed method. The model results show that the proposed method can be applied accurately in companies which produce similar products.     

The application of artificial neural networks to flow and phosphorus dynamics in small streams on the Boreal Plain,with emphasis on the role of wetlands

Historically, management strategies in Canada's boreal forest have focused on forest polygons and terrestrial biodiversity to address ecological considerations in forest management. The Forest Watershed and Riparian Disturbance (FORWARD) project examines the problem from a watershed perspective rather than a forest polygon viewpoint. The main objective of this study was to devise an artificial neural network (ANN) modeling tool that can predict flow and total phosphorus (TP) concentration for ungauged watersheds (where daily flow is not monitored). This dictates that all inputs should be easily accessed via a public domain database, like the Environment Canada weather database, without the need to install flow gauges in each modeled watershed. Daily flow and TP concentration for two of the project watersheds were modeled using ANNs. The two watersheds (1A Creek, 5.1 km² and Willow Creek, 15.6 km²) were chosen to reflect variations in wetland area and composition in the study area. Flow was modeled with a feed-forward multilayer perceptron ANN trained with the error back-propagation algorithm. Simulated values for flow were then used, as inputs, to model TP concentration using the same neural networks algorithm. One hidden layer with three slabs; each operating with a different activation function was utilized to simulate the conceptual differences between base flow, snowmelt, and storm events. Time domain analysis was conducted to identify possible model time-lagged inputs reflecting the time dependency of the modeled variables. Spectral analysis was used to address data hystereses. Our results highlight the capabilities of ANN in modeling complex ecosystems and highly correlated variables. Results also indicated that more research towards the phosphorus dynamics in wetlands is required to better represent the impact of wetland area and composition on the water-phase phosphorus in ANN modeling.     

Environmental degradation and remediation: is economics part of the problem?

It is argued that standard environmental economic and 'ecological economics', have the same fundamentals of valuation in terms of money, based on a demand curve derived from utilitymaximization. But this approach leads to three different measuresof value. An invariant measure of value exists only if the consumer has 'homothetic preferences'. In order to obtain a numerical estimate of value, specific functional forms are necessary, but typically these estimates do not converge. This is due to the fact that the underlying economic model is not structurally stable.According to neoclassical economics, any environmental remediation can be justified only in terms of increases in consumer satisfaction, balancing marginal gains against marginal costs. It is not surprising that the optimal policy obtained fromthis approach suggests only small reductions in greenhouse gases.We show that a unidimensional metric of consumer's utility measured in dollar terms can only trivialize the problem of global climate change.     

混沌理论在事故分析及预测中的应用

在对江苏常州市某公司安全事故资料进行大量调查与统计的基础上,应用混沌理论分析了该公司安全事故的混沌特征,指出了事故对初始条件的敏感依赖性和事故的长期不可预测性。应用重构相空间理论对安全事故次数的时间序列进行了分析和预测。同时,还对安全事故统计资料进行了R/S分析,得出该时间序列以2 0 0 1年6月为界限,存在两个Hurst指数,H1=1.6 82 8和H2 =0 .2 936 ,表明在以3个月为时间统计尺度的条件下,事故发生次数在前一时间段整体表现为持久相关性,而在后一时间段表现为反持久相关性。预测与分析结果与实际情况符合较好,表明应用混沌理论进行事故分析与预测是可行的,反映了事故的发展趋势。     

自回归模型在井水埋深预测中的应用及改进

用时间序列分析方法建立井水埋深的预测模型时,首先采用差分的方法把季节性时间序列变成平稳时间序列,在此基础上,再用动态数据系统方法的传统F检验定阶法进行分析。由于样本的随机性可能过早地退出对模型的循环检验,从而不能找到合适的预测模型。笔者在用自回归模型建立井水预测模型的基础上,采用了一种改进的建模方法,提高了预测精度,并用实例进行了验证。     

木粉尘职业接触极限值的研究

木头作为原材料得到广泛应用 ,但硬木粉尘 (如橡木和山毛榉粉尘 )可导致人患鼻癌。不同国家的木粉尘的职业接触极限值 (或极限值 )却不尽相同。虽然关于木粉尘的极限值的国际讨论持续已久 ,但仍缺乏更好支持其极限值推导的健康相关数据。为保护木材加工工人的身体健康以及给木粉尘的职业接触极限值的制定机构提供可靠数据和科学决策方面的建议 ,笔者针对怎样为木粉尘 ,特别是致癌木粉尘制定一个合理极限值的问题 ,在“比较”和“设定”两方面对国际范围内的木粉尘的极限值进行了研究 ,其结果表明 ,大部分国家给予软木粉尘和硬木粉尘的极限值分别为 5mg/m3 和 1mg/m3 ;提出利用剂量 -影响 -关系和“线性多阶段”方法也可以给致癌硬木粉尘建立一个健康基础极限值或者一个可接受极限值 ,其极限值应该不仅根据木材类型而且还需根据工作岗位而分别综合设定。     

Estimating the total exposure to air pollutants for different population age groups in Hong Kong

Given that Hong Kong is one of the most densely populated cities in the world, the exposure of the Hong Kong people is one of the interesting research areas. In this study, an indirect approach was used to estimate the exposure to nitrogen dioxide (NO2), respiratory dust (PM10) and carbon monoxide (CO) pollutants experienced by different age groups of people in Hong Kong. The average concentrations of the 20 major microenvironments obtained from our measurement survey data, together with the people activity pattern data obtained from 7-day recall questionnaires, were used to predict frequency distributions to exposure assessment. Our results showed that Hong Kong people spent more than 86% of their time indoors. Homes were shown to be the one of the major exposure sites to NO2, CO and PM10 for all age groups. Our results also indicate that the 24-h NO2 exposure for individuals, irrespective of age, spending more than 2 h in commuting daily, was observed to be exceeding the 24-h NO2 exposure standards. This study was one of the pioneering studies with valuable contribution for modeling the estimates of exposures to NO2, PM10 and CO of different age groups in Hong Kong.     

北京平原区地下水污染源识别与危害性分级

地下水污染源的有效识别与分级对地下水污染风险源识别和地下水污染防控区划具有重要意义.本研究通过对北京市平原区主要污染源进行解析,构建了以特征污染物属性与污染物排放量计算污染源危害性的量化计算方法.运用ARCGIS 9.3软件实现了北京市平原区的污染负荷空间分布和污染物属性的叠加分析,得到地下水污染源识别与危害性分级.结果表明,该方法能够较为细致准确地反映出污染源的危害性分级,识别结果表明工业污染源对北京平原区地下水污染贡献最大,其次是城镇居民区和垃圾场.     

增城市典型行业化学品使用调查

化学品的使用会对周边环境,特别是水环境,带来一定的潜在污染风险。增城市是一个经济较发达,水系较复杂的城市,为保护其水环境,特对其工业、农业和生活源等典型行业所使用的化学品进行调查,希望由此提出一些保护水环境的建议。