环境规制的蓝色红利效应研究

利用中国工业企业数据库2004~2009年制造业企业数据,以清洁生产目录标准的政策实施为外生冲击事件,基于倍差估计法（DID）实证检验了环境规制对企业盈利能力、盈利质量、波特效应和管理创新成本等蓝色红利的影响.结果发现：环境规制显著提升了制造企业的利润率和企业的现金流充裕性,改善了企业的盈利能力和盈利质量;环境规制显著降低了企业管理创新成本,但波特效应不显著.环境规制的蓝色红利效应存在地方策略互动、企业规模和所有制的异质性：地方政府之间的策略性不合作抑制了环境规制蓝色红利效应.企业规模的扩大提高了管理创新成本,但强化其他相关的蓝色红利效应.环境规制对国有企业的利润率、现金流以及全要素生产率的改善作用强于非国有企业,但更有助于降低非国有企业的管理创新成本.     

典型肥料生产场地氨氮分布特征及风险控制目标确定

为探究肥料生产场地的NH₃-N（氨氮）分布特征及环境风险,以我国某肥料生产场地为研究对象,在场地调查基础上,对场地土壤和地下水NH₃-N的空间分布进行分析,并以人体健康和场地地下水为保护对象分别讨论了土壤NH₃-N风险控制目标值的计算方法.结果表明:①目标场地土壤中w（NH₃-N）为0.03~15 000 mg/kg,水平方向上高值区集中分布于核心生产区及原辅料堆场,垂向上总体表现为由上至下随深度增加呈先逐步升高后降低的趋势,并且富集于人工填土与原状粉质黏土交界处,粉质黏土阻碍NH₃-N向下迁移,并随地层结构变化其迁移深度不同.②场地上层滞水和潜水中ρ（NH₃-N）分别为19.10~3 320和0.03~219 mg/L,超标率分别为100%和57.89%,并且地下水与土壤的NH₃-N在水平空间分布上具有重叠特征.③因NH₃-N主要通过呼吸吸入挥发性气体产生暴露,并且仅有经呼吸暴露的毒性参数,故采用《污染场地风险评估技术导则》中经呼吸暴露途径的非致癌效应风险控制值计算模型来计算土壤NH₃-N的控制目标,通过代入场地实测土壤K_d（土-水分配系数）,得到居住用地下的土壤NH₃-N控制目标值为9 195 mg/kg;若考虑保护地下水水质安全,据三相或两相平衡模型耦合NH₃-N在包气带衰减和地下水稀释作用,当目标场地地表无积水的入渗条件下得到的控制目标值为6 203 mg/kg;当地层从上至下呈饱和含水条件时,土壤NH₃-N控制目标为811 mg/kg.计算值可用作不同场地进行土壤NH₃-N风险管控的参考目标,实际应用中可结合不同地块环境条件、不同受体和保护目标,选择相应的风险控制值对场地进行风险管控.此外,土壤和地下水的NH₃-N污染控制均可考虑采用工程措施和制度控制来进行.      

农业灌溉用水经济价值及其影响因素——基于剩余价值法和陕西关中地区农户调研数据

灌溉水经济价值是农业用水定价的重要基础。根据陕西关中地区农户调研数据,采用剩余价值法计算得到小麦、玉米和苹果灌溉水经济价值均值分别为0.66 元/m³、0.84 元/m³、3.17 元/m³。以该结果作为水价调整上限与现状水价比较,小麦和玉米的水价上调空间介于0.24~0.71元/m³,苹果的水价调整空间介于2.72~3.04 元/m³之间。使用分位数模型对影响因素的研究发现：（1）仅在灌溉水经济价值较低时,农户和家庭特征以及土地分散程度有显著影响;（2）在灌溉水经济价值较高时,增强农户节水意识以及加入用水者协会将能有效提升灌溉用水经济价值;（3）粮食转为经济作物、进行农业水价综合改革在所有分位点上均呈显著正向影响。本文可为研究区域农业用水分类定价及改善用水效率提供参考。     

海洋工程用新型牺牲阳极设计与性能研究(Ⅴ)——导管架平台阴极保护设计探讨

目的 针对不同设计使用年限的导管架平台,通过对比新型阳极和常规阳极用量来评价新型阳极的优势和不足。方法 针对设计寿命15年和30年的导管架平台,计算满足不同阶段保护电流需求的新型阳极和常规阳极的需求量。结果 当导管架平台设计年限较短,比如15年,牺牲阳极用量由初期保护电流需求量决定,新型阳极的使用可以达到节约阳极用量的目的。当设计年限较长,比如30年,牺牲阳极用量则由维持电流需求量决定,采用新型阳极并不能节约阳极用量。结论 并非所有设计年限的导管架平台使用新型阳极都能达到节约用量的目的,具体要根据实际计算结果而定。     

华南某市生活垃圾组成特征分析

依据城市生活垃圾采样分析方法对华南某市20个街镇生活垃圾的物理性质和物理组成进行历时一年的研究.结果表明,研究区域垃圾平均容重为0.22×103kg·m-3,垃圾三组分(水分、灰分和可燃物)所占比例分别为55.0%~66.9%、18.6%~30.3%、69.7%~81.4%,有机质含量比例为50.1%~58.0%,各研究区镇垃圾热值范围为6 570~9 652 k J·kg-1,平均热值为8 272 k J·kg-1,高于世界银行推荐的垃圾焚烧所需最低热值(7 000 k J·kg-1).其它物理组分所占比例分别如下:厨余类为39.8%~53.3%,橡塑类为16.5%~33.4%,纸类为5.61%~7.95%,纺织类为1.14%~5.16%,竹类为2.49%~5.12%,玻璃类为1.10%~1.47%,混合类5.86%~7.57%,灰土类2.46%~6.73%,金属0.1%~0.32%,陶瓷0.4%~0.69%.相关分析和主成分分析结果表明纺织类、橡塑类、纸类、可燃物比重对焚烧有促进作用,厨余类、玻璃类、容重、灰分、含水率、灰土等则对焚烧有一定的负影响.     

Denaturing high-performance liquid chromatography (DHPLC)-based prenatal diagnosis for tuberous sclerosis

Tuberous sclerosis (TSC) is a frequent autosomal-dominant condition (affecting 1 in 6000 individuals) caused by various mutations in either the hamartin (TSC1) or the tuberin gene (TSC2). This allelic and non-allelic heterogeneity makes genetic counseling and prenatal diagnosis difficult, especially as a significant proportion of TSC cases are due to de novo mutations. For this reason the identification of the disease causing mutation is mandatory for accurate counseling, yet current mutation detection methods such as single-strand conformation polymorphism (SSCP) or denaturing gradient gel electrophoresis (DGGE) are labor intensive with limited detection efficiency. Denaturing high-performance liquid chromatography (DHPLC) is a high-throughput, semi-automated mutation detection system with a reported mutation detection rate close to 100% for PCR fragments of up to 800 bp. We used a recently described DHPLC assay allowing the efficient detection of mutations in TSC1 to analyze the DNA extracted from a chorion villus sample in order to perform a prenatal diagnosis for TSC. The fetus was found not to have inherited the deleterious mutation and the DHPLC diagnosis was confirmed by haplotype analysis. This represents the first DHPLC-based prenatal diagnosis of a genetic disease. Copyright © 2001 John Wiley & Sons, Ltd.     

The interrelationships between resource-holding potential,resource-value and reproductive success in territorial males: How much variation can we explain?

A long-standing hypothesis in behavioural ecology posits that males with greater resource-holding potential (RHP) control resource sites deemed more valuable by sexually-receptive females and, thereby, males controlling such sites accrue greater reproductive success (RS). This hypothesis has historically been investigated using three separate but non-mutually exclusive relationships (male RHP vs. resource value, resource value vs. male RS and male RHP vs. RS). The relationships between these three variables are predicted to be strongly positive, however, due to measurement error and biological noise, perfect correlations (r = 1.0) are rare in biology even for well-established relationships. Moreover, the inaccurate identification of either the male trait(s) important to RHP or the resource characteristic sought by females will weaken the observed strength of the relationships. Here, I use meta-analysis to quantitatively describe the general pattern of these relationships in animals. I predict that the relationships between male RHP, resource-value and RS should be significantly positive (male RHP and resource-value should explain a large amount of the variation in male RS). My meta-analysis supports this hypothesis; however, in the best case scenario only ca. 20% of the variation in the response variable was explained. I conclude by identifying areas in which we need to improve our investigations of resource-defence animals and recommending approaches to meet these needs. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

The spatiotemporal structure of population in the Muskrat (Ondatra zibethicus)

The spatiotemporal structure of the muskrat population has been studied by means of the prenatal radioactive marking of juveniles with 45 Ca and their subsequent recapture in the test area. The muskrat population is characterized by a cyclic type of spatial structure, with seasonal transition from a mosaic type of settling to a diffuse type and, after the breeding season, vice versa.     

获取日均值的大气监测时段选择

利用数理统计方法，以污染物瞬时监测数据为基础数据，选用控制在一定置信度下最大允许误差的统计公式确定出样本容量，并采用模糊集合运算—优化组合选择法，确定出获取日均值的最佳监测时段．