Multiple batch extraction test to estimate contaminant release parameters using a Bayesian approach

Industrial activities produce vast amounts of weakly contaminated materials which are commonly reused as filling materials on natural ground. There is a strong demand to define guidelines for the application of these materials, to estimate the leaching potential of contaminants from the materials, and to assess the potential hazard for groundwater pollution. We present a multiple batch experiment, where measurements of liquid-phase concentrations at varying liquid/solid ratios are used to estimate the total mass of contaminant that can be extracted from a contaminated material with a mild extractant like water. Furthermore, the experiment yields estimates of the isotherm describing the partitioning of the contaminant between the solid and liquid phases, and a concentration that might be expected under soil hydraulic conditions representative for the field situation. Model parameters are estimated from liquid-phase concentrations within a Bayesian framework by applying the Shuffled Complex Evolution Metropolis Algorithm (SCEM-UA), an efficient Markov Chain Monte Carlo sampler. A sensitivity analysis and inversions of synthetically generated data corrupted with noise show the general suitability of the proposed method. An uncertainty analysis for model parameters and model predictions shows the expected accuracy of the estimates. An application to concentration measurements obtained from a multiple batch extraction test illustrates the applicability of the approach for a real situation.     

Impact of neighbourhood land-cover in epiphytic lichen diversity: analysis of multiple factors working at different spatial scales

The objective of this work was to determine the impact of neighbourhood land-cover in epiphytic lichen diversity. We used geostatistics to analyse the spatial structure of lichen-indicators (number of lichen species and Lichen Diversity Value) and correlate them to land-cover considering different distances from the observed data. The results showed that lichen diversity was influenced by different environmental factors that act in the same territory but impact lichens at different distances from the source. The differences in the distance of influence of the several land-cover types seem to be related to the size of pollutants/particles that predominantly are dispersed by each land-cover type. We also showed that a local scale of analysis gives a deeper insight into the understanding of lichen richness and abundance in the region. This work highlighted the importance of a multiple spatial scale of analysis to deeply interpret the relation between lichen diversity and the underling environmental factors.     

Univariate Bayesian nonparametric binary regression with application in environmental management

In environmental management, we often have to deal with binary response variables whose outcome dictates the course of action. This paper introduces a nonparametric Bayesian binary regression model with a single predictor variable that is more flexible than the commonly used logistic or probit models. Due to the Bayesian feature, the model can be easily used to combine observed data with our knowledge of the subject to produce site-specific results. By using three examples, this paper shows the potential application of the model in the environmental management, and its advantages in terms of flexibility in model specification, robustness to outliers, and realistic interpretation of data.     

印刷线路板在复合环境下的腐蚀

印刷线路板几乎会出现在每一种电子设备当中,它是以绝缘材料辅以导体配线所形成的结构元件。印刷线路板的腐蚀形式符合大气腐蚀的基本规律,但又有自己的特点。本文概述了印刷线路板在气体污染物、灰尘、潮湿、高温等多因素复合环境条件下的失效形式及腐蚀机理,其主要的腐蚀形式是:电偶腐蚀、电解腐蚀和缝隙腐蚀;文中还简单总结了印刷线路板腐蚀的主要影响因素,其主要的影响因素是:湿度、温度、腐蚀性气体和固态污染物等。     

巢湖对合肥市的生态响应

巢湖位于合肥市的上风向,是该市的通风口。在东南风的帮助下,为合肥市输送了大量水汽,并与合肥市形成了一个热量循环系统,使该市的生态呈现出一定的局域特性。总结了巢湖对合肥市的生态调节作用,合肥市在其发展成长过程中对巢湖生态产生的巨大影响,提出合肥市在经济发展的同时兼顾巢湖的生态作用,以促进该市经济与生态和谐发展。     

Classifying environmentally significant urban land uses with satellite imagery

We investigated Bayesian networks to classify urban land use from satellite imagery. Landsat Enhanced Thematic Mapper Plus (ETM(+)) images were used for the classification in two study areas: (1) Marina del Rey and its vicinity in the Santa Monica Bay Watershed, CA and (2) drainage basins adjacent to the Sweetwater Reservoir in San Diego, CA. Bayesian networks provided 80-95% classification accuracy for urban land use using four different classification systems. The classifications were robust with small training data sets with normal and reduced radiometric resolution. The networks needed only 5% of the total data (i.e., 1500 pixels) for sample size and only 5- or 6-bit information for accurate classification. The network explicitly showed the relationship among variables from its structure and was also capable of utilizing information from non-spectral data. The classification can be used to provide timely and inexpensive land use information over large areas for environmental purposes such as estimating stormwater pollutant loads.     

Community analysis of ammonia and nitrite oxidizers in start-up of aerobic granular sludge reactor

A lab-scale sequencing batch reactor (SBR) was setup and the aerobic granular sludge was successfully incubated by using anaerobic granular sludge as seed sludge. Nitrogen was partially removed by simultaneous nitrification and denitrification (SND) via nitrite with free ammonia (FA) of about 10 mg/L. The denaturing gradient gel electrophoresis (DGGE) method was used to investigate community structure of α-Proteobacteria, β-Proteobacteria, ammonia oxidizing bacteria (AOB), and Nitrospira populations during start-up. The population sizes of bacteria, AOB and Nitrospira were examined using real-time PCR method. The analysis of community structure and Shannon index showed that stable structure of AOB population was obtained at the day 35, while the communities of α-Proteobacteria, β-Proteobacteria, and Nitrospira became stable after day 45. At stable stage, the average cell densities were 1.1×1012, 2.2×1010 and 1.0×1010 cells/L for bacteria, AOB and Nitrospira, respectively. The relationship between characteristics of nitrifying bacteria community and nitrogenous substrate utilization constant was discussed by calculating Pearson correlation. Certain correlation seemed to exist between population size, biodiversity, and degradation constant. And the influence of population size might be greater than that of biodiversity.     

环渤海地区海洋经济发展进程中的生态环境响应及其影响因素

基于海洋经济发展进程的生态环境演化模型,建立了环渤海地区海洋经济与生态环境发展水平评价指标体系,通过构建响应度模型定量分析2004至2014年环渤海地区海洋经济发展的海洋生态环境响应变化及影响因素,得出以下结论:(1)通过构建海洋经济与生态环境发展水平评价指标体系及综合评价模型进行测算发现,环渤海地区海洋经济发展综合评价值由2004年的0.135提升至2014年的0.850,表明环渤海地区海洋经济发展水平不断提高,并呈现出良好的发展势头;海洋生态环境发展综合评价值先由2004年的0.647降至2012年的0.335,后又缓慢回升至2014年的0.374,表明环渤海地区海洋生态环境水平虽在2012至2014年间略有好转,但总体仍呈波动下降趋势。(2)通过构建海洋生态环境响应度模型进行测算发现,环渤海地区海洋经济发展的生态环境响应指数由2004年的-0.073下降至2012年的-0.576,而后又增大至2014年的-0.297,表明环渤海地区海洋经济发展对生态环境演变产生了"胁迫"影响,总体呈现出由"弱胁迫"向"强胁迫"变化的态势,但胁迫程度在2012至2014年间有所缓和。(3)通过多元回归分析发现,与海洋生态环境响应指数的偏回归系数较高的3个自变量分别为海洋科技课题成果应用数量、海域利用效率、单位面积工业废水排放达标量,且海域利用效率的回归系数最高为0.749。表明海域利用效率是影响环渤海地区海洋生态环境响应演变的主要因素,此外,海洋科技发展水平的提高以及海洋污染治理力度加强等因素也对胁迫程度的减小具有一定的推动作用。     

2001-2018年浙江省酸雨变化特征及影响因素分析

利用2001-2018年浙江省32个城市酸雨观测资料,结合数理统计和GIS空间插值,分析了全省降水酸度变化、化学组分特征及其影响因素.研究结果表明,以2009年为拐点,浙江省酸雨污染呈先加重后减轻的趋势,降水酸度和酸雨率均得到显著改善.2009年后,轻酸雨城市的比例不断上升.至2018年,全省大部分城市均处于轻酸雨区,...     

基于STPA和模糊BN的装配式建筑吊装施工安全风险分析

为有效评估装配式建筑吊装施工中的安全风险状态,识别关键风险因素,运用系统理论过程分析方法(STPA)构建吊装施工过程中的控制反馈结构,识别导致危险的不安全控制行为,确定不安全控制行为的致因因素;基于风险因素间的关联关系构建贝叶斯网络(BN)模型,推理计算装配式建筑吊装施工安全风险状态概率,并结合反向诊断推理分析影响安全事故的风险因素;通过敏感性分析,识别装配式建筑吊装施工安全中的关键风险因素。结果表明：装配式建筑吊装施工安全风险处于低风险状态;起重机械超负荷运行、现场安全管理不到位和吊索吊具存在缺陷等因素是影响装配式建筑吊装施工安全风险的关键风险因素。