Double Green Process: a low environmental impact method for recycling of CdTe,a-Si and CIS/CIGS thin-film photovoltaic modules

On the basis of the method for managing the end of life of CdTe photovoltaic panels previously proposed by the authors, a new method for the recycling of all types of thin-film panels (CdTe, a-Si and CIS/CIGS) has been developed and optimised under a research project founded by Enel Foundation and CRUI Foundation. The DGP process has been developed through a feasibility study carried out from three points of view: technical, environmental and economic. The process is composed by two sub-processes matched to each other, one suitable for CdTe panels (named DGPa) and the other one for a-Si and CIS/CIGS panels (DGPb). The Double Green Panel process is based mainly on mechanical treatments with a minimum use of chemicals and it is characterised by a greater level of automation and a high flexibility in production capacity. The potential environmental impacts of various configurations of the DGP process have been extensively analysed with LCA tool in order to develop an environmentally friendly process. The economic feasibility has been assessed through the Discounted Cash Flow Analysis (DCFA) method. The revenues associated to the recovery of valuable and common materials and the recycling costs have been taken into account.     

Comparative analysis of data reduction techniques for questionnaire validation using self-reported driver behaviors

Introduction: Exploratory data reduction techniques, such as Factor Analysis (FA) and Principal Component Analysis (PCA), are widely used in questionnaire validation with ordinal data, such as Likert Scale data, even though both techniques are indicated to metric measures. In this context, this study presents an e-survey, conducted to obtain self-reported behaviors between Brazilian drivers (N = 1,354, 55.2% of males) and Portuguese drivers (N = 348, 46.6% of males) based on 20 items from the Driver Behavior Questionnaire (DBQ) on a five-point Likert Scale. This paper aimed to examine DBQ validation using FA and PCA compared to Categorical Principal Component Analysis (CATPCA) which is more indicative to use with Likert Scale data. Results: The results from all techniques confirmed the most replicated factor structure of DBQ, distinguishing behaviors as errors, ordinary violations, and aggressive violation. However, after Varimax rotation, CATPCA explained 11% more variance compared to FA and 2% more than PCA. We identified cross-loadings among the component of the techniques. An item changed its dimension in the CATPCA results but did not change the structural interpretability. Individual scores from dimension 1 of CATPCA were significantly different from FA and PCA. Individual scores from factor 1 of CATPCA were significantly different from FA and PCA. Practical applications: The CATPCA seems to be more advantageous in order to represent the original data and considering data constrains. In addition to finding an interpretable factorial structure, the representation of the original data is regarded as relevant since the factor scores could be used for crash prediction in future analyses.     

基于SPA模型的煤矿瓦斯危险源风险评价

根据危险源理论和三类危险源的观点,采用集对分析(SPA)方法,进行了安全一事故集对的同异反分析,指出应采取措施控制不确定项,尤其要控制其中的第二类、第三类危险源才能使系统趋于安全状态;同时建立了煤矿瓦斯危险源风险评价模型,通过联系度的计算得出煤矿瓦斯的安全等级.研究表明,将集对分析方法应用于某煤矿瓦斯危险源风险评价,计算简单,结果较为精确、可靠,为不确定系统的评价提供了一条新思路.     

松花江佳木斯江段水环境质量变化状况及趋势(水生生物指标)分析

根据近十年来的松花江佳木斯江段水环境质量监测数据,从水生生物指标对松花江佳木斯江段水环境质量变化趋势进行了评价分析,水生生物指标分析结果表明:近十年来佳木斯江段水环境质量得到显著持续改善,规律性的由轻-中污染变化为轻污染状况。标志着近十年水污染治理取得了一定成效。     

电厂燃煤锅炉颗粒物分段去除效率及成因分析

选取某大型发电企业进行实测,根据测试数据计算颗粒物去除装置对颗粒物的分段去除效率。结果表明:静电除尘器除尘效率为99.91%、湿法脱硫装置除尘效率为60.51%、湿法脱硫装置出口相对静电除尘器进口的颗粒物去除效率为99.61%、湿法脱硫装置出口颗粒物浓度是静电除尘器出口颗粒物浓度的4.18倍。此外,也依据计算结果并结合实际情况分析了影响各除尘段颗粒物去除效率的主要成因,这些成因主要包括各除尘段功能、脱硫剂与脱硫副产品的颗粒物、脱硫装置运行平稳性等,期望本研究成果能对电厂燃煤锅炉大气污染控制设施关系调整、重新设计及大气环境污染治理思路调整提供重要科学依据与指导。     

鄱阳湖典型湿地沉水植物的分布格局及其水环境影响因子

沉水植物是湖泊湿地生态系统中关键组分,调查研究沉水植物分布格局及其水环境影响因子,对于沉水植被的恢复与重建具有重要的指导意义。2013年5月初期分别对鄱阳湖典型湿地区域中有沉水植物的25个样地进行群落结构调查,采用系统取样方法对沉水植物进行调查采样并监测水环境因子,在野外调查的基础上运用GIS软件制作鄱阳湖典型区域沉水植物的生物量分布图,并采用主成分分析(PCA)和典范对应分析(CCA)方法分析其主要影响因子。结果表明:鄱阳湖湿地沉水植物以苦草(Vallisneria natans)为广布种,其中蚌湖及白沙湖以黑藻(Hydrilla verticillata)为优势种,白沙洲及乐安河龙口段以苦草为优势种,伴生种主要有金鱼藻(Ceratophyllum demersum)、马来眼子菜(Potamogeton malaianus)、菹草(P.crispus)、小茨藻(Najas minor)、大茨藻(N.marina)、刺苦草(V.spinulosa)和水车前(Ottelia alismoides)等。采用双向指示种分析法将研究区沉水植物分为6个群落;5月初大部分沉水植物尚处于生长季初期,生物量相对较低,仅菹草的生物量较大;沉水植物与浮叶植物共存现象明显。主成分分析(PCA)结果显示,第一主成分中水深、总磷和溶解氧等因子的系数值较大,第二主成分中pH值、化学需氧量和水体透明度等因子的系数值较大,是影响沉水植物分布的关键因子;典范对应分析(CCA)结果显示,水深、总磷和总氮对苦草和黑藻的影响显著,水体透明度是马来眼子菜的主要影响因子。     

水库抗旱调度分期特征确定方法研究

为在一定程度上减轻流域干旱损失,国家防汛抗旱总指挥部提出旱限水位的概念,并开展水库抗旱调度,降低干旱影响程度。旱限水位是水库低水位运行的控制性水位,其合理设置对提高区域水资源利用率意义重大,而水文气象特征在年内的阶段性变化要求基于旱限水位的水库管理应适应其变化特征。此次研究提出水库抗旱调度分期的确定方法,采用核主成分分析法提取指标的非线性特征,结合熵权法赋予指标权重后利用Fisher最优分割法对干旱的年内阶段性变化进行划分。以黄河流域刘家峡和小浪底水库为例,分期结果刘家峡水库分3期为:7月至9月,10月至3月,4月至6月;小浪底水库分3期为:7月至10月,11月至3月,4月至6月。     

A methodology for identifying and addressing dead-legs and corrosion issues in a Process Hazard Analysis (PHA)

Identifying dead-legs and related corrosion issues continues to be a challenge in the process industry. Pipeline corrosion has been a factor in several recent incidents involving releases and fires. A review of incident reports and citations over the past ten years indicates that Process Hazard Analysis (PHA) revalidations have been noted for not addressing the hazards of a process including corrosion mechanisms and dead-legs. In order for the hazards to be addressed, they must first be accurately identified in a PHA and documented along with any recommended actions for preventive maintenance. This paper describes a methodology for identifying and addressing dead-legs and related corrosion issues in a PHA that can be used to update corporate PHA procedures to be more robust in preventing corrosion related incidents.     

基于主成分分析-多元线性回归的松花江水体中多环芳烃源解析

对松花江全流域14个监测断面的16种美国环保局优先控制的多环芳烃(PAHs)的主要来源及其贡献率应用主成分因子分析-多元线性回归模型(PCA-MLR)进行了来源解析。结果表明:松花江全流域为化石和石油燃料的复合PAHs污染,水体环境中PAHs首要污染源为化石燃料燃烧和交通污染,合计贡献率为63.1%,第二大污染源为工业和民用燃煤污染,合计贡献率为36.9%,沿江的石化、石油基地、大型焦化厂、电厂都是PAHs的主要来源。     

某钢铁企业颗粒物无组织排放核算与监测对比分析

以济南东部老工业区一家大型钢铁企业为例,通过前期调研和排放系数核算出颗粒物(TSP)排放总量,再运用公式计算出厂区周边不同距离颗粒物(TSP)的落地浓度。将该落地浓度与厂区周边颗粒物(TSP)的监测值进行对比分析,充分印证了连续点源扩散的高斯模式的准确性和可行性。随着气流经过该厂区,对比上下风向监测点位颗粒物(TSP)浓度迅速升高(增大1.04倍),下风向颗粒物(TSP)浓度超出二级标准1.32倍;颗粒物(TSP)的落地浓度在厂区不同距离上的浓度变化明显,从0.1到10 km其落地浓度稀释了约3 500倍,距离>4 km时,无组织排放的颗粒物(TSP)对周围空气质量直接影响有限。