THE USE OF BIOLOGICAL CRITERIA IN ENVIRONMENTAL POLICY1

ABSTRACT: The hypothesis of this paper is that regulatory systems for the control of effluent released to the environment can be, if improperly designed, inadequate for both the establishment of effective pollution control policy and the assessment of the biological significance of violations. This inadequacy may stem from several factors: first, the use of single point standards which delineate the boundary between legally acceptable and unacceptable pollutant discharges; and second, the existence of significant weaknesses in the frequency and design of monitoring programs. In order to be effective, pollution standards must reflect the impact of pollutants on the ecosystem. To achieve this goal, three critical pieces of information are required: measurement of ambient levels of released pollutants, frequency distributions derived from these data, and estimates of biological damage functions. Illustrating the above three requirements with data drawn from research in British Columbia, the authors recommended a restructuring of environmental policy to provide regulatory agencies with an effective mechanism for the analysis and control of environmental degradation.     

A reliability evaluation method based on the weakest failure modes for side-by-side offloading mooring system of FPSO

Offshore structures are complex systems, and numerous failure modes must be taken into consideration when reliability analysis in different loads and environment conditions are conducted on them. It is difficult to obtain structural system reliability with respect to complicated systems with numerous failure modes and dependency consideration among them. This paper applies the combination of the weakest failure modes theory with structural reliability theory to conduct reliability analysis on of side-by-side offloading mooring system of FPSO. Firstly, the numerical simulation of the system in different conditions is addressed to acquire the statistical data of time-history stress of components including hawsers, fenders and yoke, based on which, the reliability indexes of all the failure modes and correlation coefficient matrix are derived. Then the weakest failure modes, i.e. the representative failure modes that have significant impact on the system, are located through Probability Network Evaluation Technique. The probability of structural system is estimated through the weakest failure modes by considering the system as series. The analysis results indicate that two environment conditions (0°&0°&0° and 0°&30°&45° in combinations of wave, wind and current) are relative dangerous, which is in good correspondence with the practical expertise. The method is verified to be an effective and convenient evaluation approach for structural reliability analysis in terms of complex systems. It is beneficial for the identification of structure indicators from the weakest failure mode group and conduct optimum of structural system configurations in the design stage.     

九龙江流域大气氮湿沉降研究

通过2004～2005年对位于我国东南沿海的九龙江流域及周边共17个站点的实地观测,运用GIS技术定量揭示了大气氮湿沉降强度和时空分布特征,并利用氮稳定同位素分析雨水硝态氮的主要来源.结果表明,①17个站点雨水总氮平均浓度为(2.20±1.69)～(3.26±1.37) mg·L-1(以N计,下同),铵态氮、硝态氮和有机氮分别占39%、25%和36%;②雨水氮浓度随降雨强度的增大呈降低趋势,旱季浓度明显大于雨季,降水对大气具有清洗作用;③低δ15N值表明雨水硝态氮主要来源于汽车尾气排放、化石燃料燃烧和化肥施用;④九龙江流域大气氮湿沉降量平均9.9 kg·hm-2,春夏2季约占全年的91%,大气氮湿沉降占沉降总量的66%,揭示了该地区1∶2的大气氮干湿沉降结构.大气氮湿沉降时空差异与降雨量和氮的排放直接相关.     

Quantifying Rarity, Losses, and Risks for Native Fishes of the Lower Colorado River Basin: Implications for Conservation Listing

Abstract:  We examined spatial distributions of fishes native to the lower basin of the Colorado River (25 species) at three scales to determine percent decline from historical distributions based on a regional biodiversity database. We cumulated records from 1843 to 1980 to develop a "historical distribution" for each species and used those occurrences recorded from 1981 to 1998 as "modern" records. We then contrasted historical and modern distributions to (1) quantify losses in spatial distribution; (2) determine how strongly these losses and fragmentation patterns corresponded to the perceived risk of extinction of each species, as represented by its status under the IUCN Red List of Endangered Species; and (3) update extinction risk rankings for 15 fishes endemic to the lower Colorado Basin according to the IUCN criteria. Based on presence and absence data, fish fauna of the lower Colorado Basin have suffered massive distributional losses. On average, ranges of extant species have diminished more than 45% relative to their historical distribution, and 35% of species have lost 50% or more of their occurrences. We provide nine new IUCN rankings and six updates to reflect more accurately the heightened imperilment of these species. Based on our new rankings, 7 of the 15 lower Colorado Basin endemics are critically endangered, 1 is endangered, 2 are vulnerable, and 1 is already extinct. We categorize the remaining 2 endemics as lower risk. This work demonstrates the utility of matching quantitative spatial metrics such as the scale-area slope statistic to extinction risk criteria for species whose persistence is strongly influenced by spatial distribution.     

Contributions to composite sampling

The initial use of composite sampling involved the analysis of many negative samples with relatively high laboratory cost (Dorfman sampling). We propose a method of double compositing and compare its efficiency with Dorfman sampling. The variability of composite measurement samples has environmental interest (hot spots). The precision of these estimates depends on the kurtosis of the distribution; leptokurtic distributions (₂ > 0) have increased precision as the number of field samples is increased. The opposite effect is obtained for platykurtic distributions. In the lognormal case, coverage probabilities are reasonable for < 0.5. The Poisson distribution can be associated with temporal compositing, of particular interest where radioactive measurements are taken. Sample size considerations indicate that the total sampling effort is directly proportional to the length of time sampled. If there is background radiation then increasing levels of this radiation require larger sample sizes to detect the same difference in radiation.     

Hidden Markov models for circular and linear-circular time series

We introduce a new class of circular time series based on hidden Markov models. These are compared with existing models, their properties are outlined and issues relating to parameter estimation are discussed. The new models conveniently describe multi-modal circular time series as dependent mixtures of circular distributions. Two examples from biology and meteorology are used to illustrate the theory. Finally, we introduce a hidden Markov model for bivariate linear-circular time series and use it to describe larval movement of the fly Drosophila. Received: September 2003 / Revised: March 2004     

Multiple indicators, partially ordered sets, and linear extensions: Multi-criterion ranking and prioritization

This paper is concerned with the question of ranking a finite collection of objects when a suite of indicator values is available for each member of the collection. The objects can be represented as a cloud of points in indicator space, but the different indicators (coordinate axes) typically convey different comparative messages and there is no unique way to rank the objects while taking all indicators into account. A conventional solution is to assign a composite numerical score to each object by combining the indicator information in some fashion. Consciously or otherwise, every such composite involves judgments (often arbitrary or controversial) about tradeoffs or substitutability among indicators. Rather than trying to combine indicators, we take the view that the relative positions in indicator space determine only a partial ordering and that a given pair of objects may not be inherently comparable. Working with Hasse diagrams of the partial order, we study the collection of all rankings that are compatible with the partial order (linear extensions). In this way, an interval of possible ranks is assigned to each object. The intervals can be very wide, however. Noting that ranks near the ends of each interval are usually infrequent under linear extensions, a probability distribution is obtained over the interval of possible ranks. This distribution, called the rank-frequency distribution, turns out to be unimodal (in fact, log-concave) and represents the degree of ambiguity involved in attempting to assign a rank to the corresponding object. Stochastic ordering of probability distributions imposes a partial order on the collection of rank-frequency distributions. This collection of distributions is in one-to-one correspondence with the original collection of objects and the induced ordering on these objects is called the cumulative rank-frequency (CRF) ordering; it extends the original partial order. Although the CRF ordering need not be linear, it can be iterated to yield a fixed point of the CRF operator. We hypothesize that the fixed points of the CRF operator are exactly the linear orderings. The CRF operator treats each linear extension as an equal voter in determining the CRF ranking. It is possible to generalize to a weighted CRF operator by giving linear extensions differential weights either on mathematical grounds (e.g., number of jumps) or empirical grounds (e.g., indicator concordance). Explicit enumeration of all possible linear extensions is computationally impractical unless the number of objects is quite small. In such cases, the rank-frequencies can be estimated using discrete Markov chain Monte Carlo (MCMC) methods.     

基于数理统计理论的超标概率在环境质量评价中的应用

目前经常使用的评价环境质量超标情况的主要指标为超标率,但它将环境监测抽样样本和样本总体相混淆,从而导致其不能客观评价环境质量的超标情况。基于概率统计论提出了一种新的指标——超标概率来评价环境质量的超标情况。利用抽样样本的特性,求出超标概率。由于环境监测样本抽样方式的不同,超标概率的计算公式也略有不同。为了说明该方法如何运用,以京杭大运河宿迁段水质为例,分析了每种污染物和整个京杭大运河宿迁段的超标情况。     

南京市可吸入颗粒物数浓度变化及尺度分布

采用南京市近期颗粒物粒子数浓度的观测资料，对颗粒物中可吸人颗粒物(PM10)进行了分析。结果表明：近10年来南京地区可吸人颗粒物的数浓度显著增加，平均增加近4倍；PM10数浓度主要受生产活动和大气层结变化影响，日变化呈现两高两低变化趋势。观测期间，可吸人颗粒物中主要成分是细粒子，PM25数量平均占PM10总数量的99％以上。     

应用淡水生物毒性数据推导海水水质基准的可行性及适用性初探

在海洋环境风险评价及环境标准与基准的制定中,由于海水生物毒性数据的欠缺,通常引入淡水数据加以补充,以此推导海水的预测无效应浓度(PNEC),但该方法所推导PNEC的"失真"程度目前尚未完全清晰。本研究选取了Pb、Cd、马拉硫磷和狄氏剂四种典型化合物,应用SSD模型方法比较分析了分别基于淡水生物和海水生物以及二者一并使用推导的PNEC值之间的差异性和相关性。结果发现:淡水生物与海水生物对各化合物响应的敏感性具有一定的差异。对于重金属,淡水物种可能对其胁迫更具敏感性,将淡水数据与海水数据一并使用所获得PNEC可有效的保护海洋生物;对于有机磷和有机氯农药,海水生物通常更具敏感性,淡水数据的介入和应用可能会对部分海洋生物造成部分"欠保护"现象,但总体上,淡水HC5与海水HC5二者相差不大,可通过适当的安全因子加以校正。