焚烧飞灰重金属含量及浸出长期变化规律研究

通过对24个飞灰样品的重金属全量消解和高精度X射线荧光光谱法（HDXRF）快速检测结果进行线性回归分析,发现HDXRF法可较准确测定飞灰中Cu、Pb、Zn、Ni和Cd含量（线性回归决定系数R²³0.90）.采用HDXRF法对某焚烧厂飞灰重金属含量6个月快速检测及浸出毒性测定数据统计分析发现：飞灰重金属月均含量较稳定（变异系数CV<0.14）但日均含量波动较大（CV>2.54）;飞灰中Pb、Cu和Zn含量呈正相关（相关系数r>0.78）;金属浸出浓度受浸出液终点pH值影响显著,超标频率依次为Pb（68.9%）、Cd（66.1%）、Ni（24.0%）、Cu（14.2%）和Zn（1.6%）.短期飞灰金属含量和浸出毒性数据受焚烧工况,烟气处理工况和垃圾组分等多种因素共同影响,不具有代表性.为评估垃圾分类源头削减重金属效果,建议采用快速检测方法对焚烧飞灰重金属含量进行长期监测.     

电化学原位产生H2O2的影响因素分析及数学建模

以Pt为阳极,石墨碳棒为阴极,Na2SO4为支持电解质,实验探讨了电化学原位产生H2O2的规律.通过正交试验,确定阴极溶液初始pH值、电流密度CD、通氧流量Q和支持电解质浓度CNa2SO4等主要参数对H2O2产生量的影响,并提出最佳参数组合:pH=2.00,CD=1.02mA·cm-2,Q=0.4L·min-1,CNa2SO4=0.1 mol·L-1,极间距D=6cm.采用二次多项式逐步回归和BP神经元网络2种方法,建立了这些参数对于H2O2产生量的预测模型,并对模型进行检验.结果表明,2种方法在一定参数条件下都可预测阴极区溶液中H2O2浓度,BP神经元网络法预测的准确度好于二次多项式逐步回归方法,且更适合于在线控制.     

企业职业伤害严重度系数研究

在对不同企业之间的职业伤害风险进行量化和比较时，不同程度职业伤害的统一量化是关键难题。本文使用损失工作日的方法，通过对调研所得有效数据的统计学分析，计算得出企业职业伤害的重伤严重度系数α和轻伤严重度系数β的值，α和β值与国外相关研究结果有较好的可比性。本文所得到的α和β值是对不同企业职业伤害风险量化计算和比较的重要基础。     

应用自动识别和定量系统评价两种污水再生工艺对微量有机污染物的去除效果

采用气质联用分析,并结合自动识别与定量系统(AIQS-DB)考察2种再生水厂采用的深度处理工艺对微量有机污染物的去除效果。结果表明,以污水为原水的膜生物反应器(MBR)+臭氧氧化+生物活性炭滤池(BAC)工艺用于再生水生产,MBR工艺对有机污染物的去除起主要作用;城市污水厂二级出水为原水的混凝沉降+浸没式超滤(SMF)/连续微滤(CMF)+部分反渗透(RO)+臭氧氧化工艺用于再生水生产,其SMF和CMF工艺段的膜截留作用均可有效消减有机污染物含量,SMF的效果优于CMF;2种工艺中采用的臭氧技术都能进一步加强部分物质的去除效果。气质联用结合AIQS-DB可用于再生水中污染物的筛查和不同污水再生工艺对微污染物消减效果的评价。     

航空维修人为差错影响因素分析中的模糊层次分析法

航空维修中的人为差错影响因素分析对于预防事故发生至关重要,如何定量分析及辨识出主要影响因素是亟待解决的问题。为此,结合航空维修实际,提出运用群组模糊层次分析法对人为差错影响因素进行量化排序和分类,归纳细化了影响因素层次体系,并给出了分析计算流程。以一起由维修人为差错所引发的航空事故为例进行了实证分析,结果表明:该方法能够辨识出航空维修中人为差错产生的主要影响因素,进而对制订最优事故预防方案,控制和减少该类事故的发生有积极意义。同时该方法对其他行业中的人为差错主要影响因素辨识有着一定的参考价值。     

Quantification and valuation of ecosystem services in diverse production systems for informed decision-making

The empirical evidence of decline in ecosystem services (ES) over the last century has reinforced the call for ES quantification, monitoring and valuation. Usually, only provisioning ES are marketable and accounted for, whereas regulating, supporting and cultural ES are typically non-marketable and overlooked in connection with land-use or management decisions. The objective of this study was to quantify and value total ES (marketable and non-marketable) of diverse production systems and management intensities in Denmark to provide a basis for decisions based on economic values. The production systems were conventional wheat (Cwheat), a combined food and energy (CFE) production system and beech forest. Marketable (provisioning ES) and non-marketable ES (supporting, regulating and cultural) ES were quantified by dedicated on-site field measurements supplemented by literature data. The value of total ES was highest in CFE (US$ 3142 ha⁻¹ yr⁻¹) followed by Cwheat (US$ 2767 ha⁻¹ yr⁻¹) and beech forest (US$ 2328 ha⁻¹ yr⁻¹). As the production system shifted from Cwheat - CFE–beech, the marketable ES share decreased from 88% to 75% in CFE and 55% in beech whereas the non-marketable ES share increased to 12%, 25% and 45% of total ES in Cwheat, CFE and beech respectively, demonstrating production system and management effects on ES values. Total ES valuation, disintegrated into marketable and non-marketable share is a potential way forward to value ES and ‘tune’ our production systems for enhanced ES provision. Such monetary valuation can be used by policy makers and land managers as a tool to assess ES value and monitor the sustained flow of ES. The application of ES-based valuation for land management can enhance ES provision for maintaining the productive capacity of the land without depending on the external fossil-based fertilizer and chemical input.     

聚乙烯微塑料的微生物降解研究进展

现代工业的发展使得塑料制品的使用量急剧增加,由此产生的大量废旧塑料垃圾在环境中裂解形成粒径更小的微塑料（<5 mm）.由于微塑料结构稳定,分布广泛且生物可利用性低,在环境中长期存在,已经逐渐成为对海洋生态和环境造成巨大影响的重要污染物.近年的研究表明,自然环境中存在一些能降解这些难降解微塑料的微生物,微生物降解无二次污染且对环境扰动少,在微塑料的去除中具有很好地应用潜力,但亦有一些局限性.综述了环境中数量最多的聚乙烯微塑料的微生物降解研究现状,着重探讨了降解效果和量化方法.基于微塑料生物分解效率普遍较低的现状,开展进一步的研究还非常有必要.     

Matrix effect on the performance of headspace solid phase microextraction method for the analysis of target volatile organic compounds (VOCs) in environmental samples

Solid phase microextraction (SPME) is a fast, cheap and solvent free methodology widely used for environmental analysis. A SPME methodology has been optimized for the analysis of VOCs in a range of matrices covering different soils of varying textures, organic matrices from manures and composts from different origins, and biochars. The performance of the technique was compared for the different matrices spiked with a multicomponent VOC mixture, selected to cover different VOC groups of environmental relevance (ketone, terpene, alcohol, aliphatic hydrocarbons and alkylbenzenes). VOC recovery was dependent on the nature itself of the VOC and the matrix characteristics. The SPME analysis of non-polar compounds, such as alkylbenzenes, terpenes and aliphatic hydrocarbons, was markedly affected by the type of matrix as a consequence of the competition for the adsorption sites in the SPME fiber. These non-polar compounds were strongly retained in the biochar surfaces limiting the use of SPME for this type of matrices. However, this adsorption capacity was not evident when biochar had undergone a weathering/aging process through composting. Polar compounds (alcohol and ketone) showed a similar behavior in all matrices, as a consequence of the hydrophilic characteristics, affected by water content in the matrix. SPME showed a good performance for soils and organic matrices especially for non-polar compounds, achieving a limit of detection (LD) and limit of quantification (LQ) of 0.02 and 0.03 ng g⁻¹ for non-polar compounds and poor extraction for more hydrophilic and polar compounds (LD and LQ higher 310 and 490 ng g⁻¹). The characteristics of the matrix, especially pH and organic matter, had a marked impact on SPME, due to the competition of the analytes for active sites in the fiber, but VOC biodegradation should not be discarded in matrices with active microbial biomass.     

Development and application of LC–APCI–MS method for biomonitoring of animal and human exposure to imidacloprid

Imidacloprid (IMI) is a relatively new neuro-active neonicotinoid insecticide and nowadays one of the largest selling insecticides worldwide. In the present study a LC–APCI–MS based method was developed and validated for the quantification of imidacloprid and its main metabolite 6-chloronicotinic acid (6-CINA) in urine and hair specimens. The method was tested in biomonitoring of intentionally exposed animals and subsequently applied for biomonitoring of Cretan urban and rural population.