Metrics for quantifying how much different threats contribute to red lists of species and ecosystems

Red lists are a crucial tool for the management of threatened species and ecosystems. Among the information red lists provide, the threats affecting the listed species or ecosystem, such as pollution or hunting, are of special relevance. This information can be used to quantify the relative contribution of different threat factors to biodiversity loss by disaggregating the cumulative extinction risk across species into components that can be attributed to certain threats. We devised and compared 3 metrics that accomplish this and may be used as indicators. The first metric calculates the portion of the temporal change in red list index (RLI) values that is caused by each threat. The second metric attributes the deviation of an RLI value from its reference value to different threats. The third metric uses extinction probabilities that are inferred from red list categories to estimate the contribution of a threat to the expected loss of species or ecosystems within 50 years. We used data from Norwegian Red Lists to test and evaluate these metrics. The first metric captured only a minor portion of the biodiversity loss caused by threats because it ignores species whose red list category does not change. Management authorities will often be interested in the contribution of a given threat to the total deviation from the optimal state. This was measured by the remaining metrics. The second metric was best suited for comparisons across countries or taxonomic groups. The third metric conveyed the same information but uses numbers of species or ecosystem as its unit, which is likely more intuitive to lay people and may be preferred when communicating with stakeholders or the general public.     

基于BML生产率指数的中国旅游业能源效率评价与影响因素研究

为减少旅游业能源消耗,实现旅游低碳绿色发展,探讨如何提高旅游业能源效率,基于包含非期望产出的方向性距离函数,首先构建了适应旅游业的Biennial Malmquist-Luenberger(BML)效率指数,以中国30个省市2005~2013年旅游业为实证对象,测度了其能源效率,9 a来旅游业能源效率变化源泉可被分解为全要素生产率、资本对能源替代效应、劳动对能源替代效应、能源结构效应和产出结构效应5项影响因素。研究发现:(1)中国旅游业能源效率整体上处于较低水平,旅游业能源效率可以扩张提升的比例较大。(2)整体上全要素生产率、资本对能源替代效应、劳动对能源替代效应和能源结构效应的提升能促进旅游业能源效率提高。(3)近3 a来劳动和资本投入的能源替代效应对旅游业能源效率变化的作用超过了全要素生产率。(4)区域层面上,东部地区旅游业能源效率高于中西部地区,主要由地区间旅游业对资本投入使用和能源消耗结构的差异造成。(5)整个样本期间,中国17个省市旅游业能源效率呈现下降趋势,背后的因素各有不同,旅游业资本替代效应是湖北省、福建省和浙江省等多数省市旅游业能源效率下降的主要因素,全要素生产率是安徽省、海南省、贵州省和甘肃省旅游业能源效率下降的主要原因。因此,合理利用投入的资源要素对旅游业低能耗发展至关重要,尤其是要发挥好资本对能源的替代效应,高效的资本配置能极大提高旅游能源效率。     

南宁市可持续发展评价指标体系及可持续发展度研究

本文在对南宁市社会、经济和环境三个子系统研究的基础上，采用层次分析、专家咨询等方法，建立了城市可持续发展指标体系，运用指标体系和分析方法，对南宁市可持续发展水平进行了综合评价分析。     

基于微震监测的岩体失稳智能预报

岩体稳定性预报是微震监测工作的重要组成部分。探讨微震活动性参数变化作为岩体稳定性预测的可行性,结合用沙坝矿实际生产过程中观测到的现象,提出微震监测岩体失稳预报的一般模式。根据b值在岩体失稳前先增大后减小的趋势作为危险预警初始条件;并将能量指数、施密特数急剧下降以及累积视体积增加的时间段作为岩体失稳的预警期,将事件数的急剧下降作为危险的临界状态。用沙坝矿根据这一原理建立的岩体失稳预报模式可以达到采场失稳的智能预报,解决了人工判别预警期过程中效率低的难题,保障矿山的生产工作。     

基于改进AHP的地下矿突水风险评价

地下矿突水风险的有效评价是矿井水害防治与安全开采的基本前提与重要基础。为了科学有效地评价地下矿突水事故风险,在深入研究分析与归纳地下矿突水因素的基础上,构建了较为全面的矿井突水事故风险评价指标体系,体系包括7个一级指标,各一级指标有与之对应的二级指标。应用德尔菲法对各项指标进行统一打分并求平均值,对层次分析法进行改进并应用于确定各项指标的权重,然后根据风险评价模型计算出评价结果。最后,结合国内某典型矿山进行实际的应用,所得结果与实际情况一致性较好,说明该方法可以提高矿井突水风险评价的有效性与准确性,具有较好的可行性。     

基于过程方法的企业安全评价指标体系构建方法

针对安全评价技术的应用现状,分析现有安全评价体系在构建上的局限性,认为安全评价体系应基于现代安全管理体系的运作方式进行构建;回顾安全管理的发展过程,对代表现代安全管理的两种管理模式的起源及特点进行了分析,认为两种管理模式都应用了质量管理的过程方法;在该基础之上,结合过程方法的特点与企业的实际运作方式,提出基于过程方法的安全管理模型,并运用该模型,对安全评价体系的指标构成进行分析;以危险源识别、管理过程、安全教育与培训和应急准备与响应4个指标为基础,构建了安全评价体系的框架。     

衡水湖底泥重金属污染特征及生态风险评价

在衡水湖设置了11个采样点,分析底泥中重金属Cr、Ni、Cu、Zn、As、Cd、Pb、Mn、Co、Sb、Tl的浓度,运用地累积指数法、潜在生态风险指数法对重金属污染程度进行评价,采用SPSS软件进行Pearson相关性分析。结果表明:除Cd和Co外,衡水湖底泥中其他重金属浓度平均值均低于河北省A层土壤背景值,其中Cr、Ni、Cu、Zn、As和Pb浓度在各采样点均低于GB 15618—2018《土壤环境质量 农用地土壤污染风险管控标准(试行)》中农用地土壤风险筛选值,Sb、Co浓度在各采样点均低于GB 36600—2018《土壤环境质量 建设用地土壤污染风险管控标准(试行)》中建设用地土壤风险管制值,Cd浓度有8个采样点超过GB 15618—2018的农用地土壤风险筛选值,1个采样点高于GB 36600—2018的建设用地土壤风险管制值;地累积指数法评价结果表明,底泥中Cd总体为偏中度污染,Co总体为轻度污染,而Cr、Ni、Cu、Zn、As、Pb、Mn、Sb和Tl可视为无污染;潜在生态风险指数评价结果表明,衡水湖底泥中重金属RI平均值为270.79,属于中等生态危害,底泥中各重金属对衡水湖生态风险贡献率为Cd>>Co>As>Sb≈Pb>Cu>Ni>Cr>Mn≈Zn,其中Cd对RI的贡献率高达91%,是主要的污染因子,Cd污染可能是引黄河水入湖和人类活动等原因造成的。     

辽河保护区七星湿地生态系统健康评价

以辽河保护区七星湿地为研究对象,采用主成分分析法与相关性分析法筛选湿地生态系统健康评价指标,构建了由化学需氧量（COD_Mn）、总磷（TP）浓度、氨氮（NH₃-N）浓度、叶绿素a（Chl-a）浓度、溶解氧（DO）浓度5个指标构成的湿地生态系统健康综合评价指标体系,以表征湿地生态系统的水环境质量、水生生物和栖息地环境质量特征;运用综合指数法对七星湿地生态系统健康状况进行评价。结果表明：七星湿地13个采样点中,6个为亚健康等级,6个为一般病态等级,1个为疾病等级;七星湿地总体生态系统健康状况为亚健康等级。     

基于浮游细菌生物完整性指数的城市河流健康评价：以深圳河流域为例

河流中的细菌是生态系统中物质循环的重要参与者,能反映河流健康状况,其群落生物指标具有评估城市河流生态状况的潜力。通过调查深圳河流域内深圳河、布吉河和福田河3条河流中的浮游细菌群落,构建了生物完整性指数 (Ba-IBI) ,评估了该流域的健康状况。基于河水浮游细菌的Illumina高通量测序结果,通过差异性检验、箱线图筛选和相关性分析方法从163个候选指标中筛选出变形菌门、放线菌门和微丝藻菌目相对丰度及门水平Simpson多样性指数作为核心指标,构建Ba-IBI评价体系。结果表明,深圳河流域内的20个位点中处于健康状态、亚健康状态、一般状态和较差状态的位点数分别为7个、4个、5个和4个。其中,深圳河处于一般和较差状态的点位比例高达85.7%;健康状况从上游到下游逐渐恶化;整体健康状况较差。布吉河和福田河健康状况相对较好,处于亚健康状态。各采样点Ba-IBI得分与水质状况的相关性较高 (R=0.77,P<0.01) ,表明Ba-IBI能有效评价城市河流的健康状况。本研究结果可为深圳市河流的修复和管理工作提供参考。     

Characterization of primary precipitate composition formed during co-removal of Cr(VI) with Cu(II) in synthetic wastewater

BACKGROUND, AIMS AND SCOPE: Hexavalent chromium [Cr(VI)] cannot react with either carbonate or hydroxide to form chromium precipitates. However, by using a precipitation technology to treat plating wastewater containing Cr(VI), Cu(II), Ni(II) and Zn(II), approximately 78% of Cr(VI) (initial 60 mg/L) was co-removed with the precipitation of Cu(II), Ni(II) and Zn(II) (each 150 mg/L) by dosing with Na2CO3 (Sun 2003). Direct precipitation by forming Cu(II)-Cr(VI) precipitates followed by adsorption of Cr(VI) onto freshly formed Cu-precipitates was subsequently found to be the main mechanism(s) involved in Cr(VI) co-removal with Cu(II) precipitation by dosing Na2CO3 stepwise to various pH values (Sun et al. 2003). This study was. carried out to further characterize the formation of primary precipitates during the early stages of copper precipitation and simultaneous removal of Cr(VI) with Cu(II). METHODS: Test metal-solutions were prepared with industrial grade chemicals: CuCl2 x 2H2O, Na2SO4 and K2Cr2207. NaCO3 was added drop-wise to synthetic metal-solution to progressively increase pH. For each pH increment, removal of soluble metals was detected by atomic absorption spectrophotometer (AAS) and surface morphology of precipitates was analyzed by scanning electron microscope (SEM). To further characterize the formation of primary precipitates, a series of MINEQL+ thermodynamic calculations/analyses and equilibrium calculations/ analyses were conducted. RESULTS AND DISCUSSION: MINEQL+ thermodynamic calculation indicated that, for a system containing 150 mg/L Cu(II) and 60 mg/L Cr(VI) with gradual Na2CO3 dosing, if any precipitates can be formed at pH 5.0 or lower, it should be in the form of CuCrO4. Comparison tests using systems containing the same equivalent of Cu(II) plus Cr(VI) and Cu(II) plus SO4(2-) showed that the precipitation occurred at a pH of around 5.0 in the Cu(II)-Cr(VI) system and around 6.0 in the Cu(II)-SO4(2-) system. The discrepancy of the precipitation was indeed caused by the formation of Cu-Cr precipitates. The initiation of copper removal at pH around 5.0 for the Cu-Cr co-removal test was not attributable to the formation of Cu-CO3 precipitates, instead, it was most likely through the formation of insoluble Cu-Cr precipitates, such as CuCrO4 and CuCrO4 x 2Cu(OH)2. Experimental tests, equilibrium calculations, MINEQL+ thermodynamic calculations and surface morphologies for systems using higher concentrations of Cu(II) and Cr(VI) further verified the most probable composition of primary precipitates is copper-chromate. CONCLUSION: In the Cu-Cr co-removal test with Na2O3 dosing to increase pH and induce metal precipitation, copper-chromate precipitates are the primary precipitates produced and contribute to the initial simultaneous removal of copper and chromium.