燃煤电厂大气污染物排放考核时间间隔的建议

新的《火电厂大气污染物排放标准》和新《环境保护法》实施后，燃煤火电企业的依法治企自觉性不断提高，但由于不同的环保管理文件对超标处罚依据和处罚手段不同，造成政府对企业处罚的自由裁量权加大，对企业造成一定的压力与困惑。结合企业实际运行情况对燃煤电厂大气污染物排放考核时间间隔提出建议。     

A new baseline model for estimating willingness to pay from discrete choice models

We show a substantive problem exists with the widely-used ratio of coefficients approach to calculating willingness to pay (WTP) from discrete choice models. The correctly calculated standard error for WTP using this approach is shown to be undefined. This occurs because the cost parameter's standard error implies some possibility the true parameter value is arbitrarily close to zero. We propose a simple yet elegant way to overcome this problem by reparameterizing the (negative) cost variable's coefficient using an exponential transformation to enforce the theoretically correct positive coefficient. With it the confidence interval for WTP is now finite and well behaved.     

淠河灌区集中式饮用水源地水质健康风险等级研究

为了解淠河灌区集中式饮用水源地水质健康风险状况,选取Cr6+、As、Cd、Pb、Mn、Cu、Zn、Fe、F、NH+4-N等10项污染因子作为健康风险指标,运用三角模糊集理论和α-截集技术,确立置信度为0.8,得到各污染指标的健康风险区间值;同时建立模糊化特征的风险等级判别标准和判别方法.结果表明,该水源地水质总健康风险值为4,风险等级为Ⅳ级(一般).3种化学致癌物Cr6+、As、Cd合计风险区间值介于5.586×10-5~9.365×10-5之间,风险由高到低的顺序依次为:Cr6+AsCd,浓度在空间上变化不大,具有一定的负面效应,但均未超过美国环保署推荐的最大可接受水平1.0×10-4;Cr6+风险区间值较大,风险等级较高,应将Cr6+作为首要的健康风险管理控制指标.其余7种非致癌化学有毒物没有风险,不存在负面效应,非致癌健康风险明显低于致癌风险.     

Parental phenols exposure and spontaneous abortion in Chinese population residing in the middle and lower reaches of the Yangtze River

Widespread use of phenols has led to ubiquitous exposure to phenols. In experimental animals, phenols increased resorptions, reduced live litter size and fetal body weights. However, there are limited epidemiological evidences of the relationships between exposure to phenols and pregnancy outcomes. We evaluated the associations between parental urinary levels of various phenols and spontaneous abortion in a Chinese population residing in the middle and lower reaches of the Yangtze River. A case-control study was conducted that included 70 case couples with medically unexplained spontaneous abortion and 180 control couples who did not have a history of spontaneous abortion and had at least one living child. Both parental urinary phenols were measured by ultra-high performance liquid chromatography-tandem mass spectrometry including bisphenol A (BPA), benzophenone-3 (BP-3), 2,3,4-trichlorophenol (2,3,4-TCP), pentachlorophenol (PCP), 4-n-octylphenol (4-n-OP) and 4-n-nonylphenol (4-n-NP). Compared with the low exposure group, there was an increased risk of spontaneous abortion with high paternal urinary PCP concentration [odds ratio (OR) = 2.09, 95% Confidence Interval (CI), 1.05–4.14], and maternal exposure to 4-n-OP and alkylphenol(s) also significantly increased the risk of spontaneous abortion (OR = 2.21, 95% CI, 1.02–4.80; OR = 2.81, 95% CI, 1.39–5.65, respectively). Our study firstly provides the evidence that paternal PCP exposure, maternal 4-n-OP and alkylphenol(s) exposure are associated with spontaneous abortion in humans.     

Use of Approximate Inference in an Index of Completeness of Biological Inventories

Abstract:  To assess the completeness of a floristic or faunal inventory, one may use the ratio of the observed number of species to the "true number" of species ( C ). If the inventory is complete , C = 1. The estimate of the true number can be obtained from accumulation curves, nonparametric methods, or other techniques. We devised a simple method for computing confidence intervals (CI) for C and for evaluating the null hypothesis that the inventory is complete. The method is based on the assumptions that an estimate of the variance of the true number of species is known and that the distribution of the estimator of the true number of species is approximately normal. We applied our method to bird inventories in the Balsas Basin of Mexico. The completeness index for subtransects were lower (84.0, 85.4, and 89.9%) than for the whole transect (91.6%) (all significantly different from 100%). Thus, these particular inventories were incomplete at 2 spatial resolutions. Our method of estimating CI for C can be used to estimate species richness obtained from databases of different sites or to test the null hypothesis that an inventory derived from a database is complete.     

Time allocation between work and recreation and the associated injury risks among young people

PROBLEM: The purpose of this study was to examine the relationship between overall risk of injury and time use patterns between work and active recreation among adolescents and young adults. METHODS: Using a representative sample of 9,795 Canadians aged 15-24 years, a multivariate logistic regression on the likelihood of any medically attended injury was conducted, including sociodemographic, individual, and time factors. RESULTS: Young people who engaged in a combination of high work and high activity hours were twice as likely to sustain a medically attended injury compared to those who worked low hours, but did not participate in any recreational activity. Those respondents who were not in school had a 43% increase in injury risk compared to full-time students. SUMMARY: Our findings suggest that injury risk was not a simple function of fatigue and cumulative exposure time. Our findings suggest the importance of considering time use and the associated injury risk tradeoffs. IMPACT ON INDUSTRY: Relevant to state and federal work safety policy makers, our findings suggest the importance of understanding where youth might otherwise spend their time if constraint were placed on their employment opportunities, and the associated injury risk tradeoffs must be taken into consideration.     

Methods of Assessing and Achieving Normality Applied to Environmental Data

2 and particle concentrations. Results show that the analyzed transformations work well and are very useful to achieve normal distributions.     

ANALYZING CORRELATIONS BETWEEN STREAM AND WATERSHED ATTRIBUTES1

ABSTRACT: Bivariate correlation analysis has been widely used to explore relationships between stream and watershed attributes that have all been measured on the same set of watersheds or sampling locations. Researchers routinely test H₀: ρ= 0 for each correlation in a large table and then go on to discuss only those that are declared “significant.” Such test results are inaccurate because no allowance is made for multiple testing, and also because the tests are not mutually independent. This paper reviews the Bonferroni approach to controlling the overall error rate in multiple testing and shows how the approach becomes impractical for large correlation tables. The Hotelling/Williams test is introduced for comparing two dependent correlations that share a variable, and numerical constraints for two such correlations are illustrated. References are also given for testing other hypothesized patterns among dependent correlations, and links to dependent correlation software are provided. The methods are illustrated for watershed and stream variables sampled in 23 small agricultural watersheds of the Willamette Valley, Oregon.     

CALCULATION OF NONLINEAR CONFIDENCE AND PREDICTION INTERVALS FOR GROUND-WATER FLOW MODELS1

ABSTRACT: A method is derived to efficiently compute nonlinear confidence and prediction intervals on any function of parameters derived as output from a mathematical model of a physical system. The method is applied to the problem of obtaining confidence and prediction intervals for manually-calibrated ground-water flow models. To obtain confidence and prediction intervals resulting from uncertainties in parameters, the calibrated model and information on extreme ranges and ordering of the model parameters within one or more independent groups are required. If random errors in the dependent variable are present in addition to uncertainties in parameters, then calculation of prediction intervals also requires information on the extreme range of error expected. A simple Monte Carlo method is used to compute the quantiles necessary to establish probability levels for the confidence and prediction intervals. Application of the method to a hypothetical example showed that includsion of random errors in the dependent variable in addition to uncertainties in parameters can considerably widen the prediction intervals.     

Estimating Trophic State Proportions of a Regional Lake Population: Are Larger Samples Always Better?

During the summers of 1991–1994, the Environmental Monitoringand Assessment Program (EMAP) sampled 344 lakes throughout thenortheastern United States using a proportional stratified sampling design based on lake size. Approximately one-quarter ofthe 344 lakes were sampled each year (4 years) for totalphosphorus to determine the proportion (and associated95% confidence intervals) of the northeast lake population 1ha (11,076 ± 1,699 lakes) that was in oligotrophic,mesotrophic, eutrophic, or heupereutropic (4 classes) conditionaccording to the total phosphorus criteria of the North AmericaLake Manegement Society. Estimates for the second, third, andfourth yr were developed as cumulative of the previous yrsamples and the current yr samples for the northeast as a wholeand for each of its three ecoregions (4 regions). New confidence intervals were computed for each cumulative yrcondition estimate. This produced a total (4 years × 4classes × 4 regions) of 64 cumulative yr tropic conditionestimates. Confidence intervals for 21% of these estimates didnot shorten with increased sample size. This phenomena raisedquestions about the accuracy of estimates based on cumulativesampling procedures. We explain why and how the phenomenon comesabout with both straight random and proportional randomsampling. Further, we present an example of the effects thisphenomenon has on lake tropic state condition estimates in thenortheastern United States.