Determination of Q1, an unknown organochlorine contaminant, in human milk, Antarctic air, and further environmental samples

Q1, an organochlorine component with the molecular formula C(9)H(3)Cl(7)N(2) and of unknown origin was recently identified in seal blubber samples from the Namibian coast (southwest of Africa) and the Antarctic. In these samples, Q1 was more abundant than PCBs and on the level of DDT residues. Furthermore, Q1 was more abundant in seals from the Antarctic than the Arctic. To prove this assumption, gas chromatography-electron-capture negative ion mass spectrometry (GC/ECNI-MS), which is sensitive and selective for Q1, allowed for screening of traces of Q1 even in samples with particularly high levels of other organochlorine contaminants. Q1 was isolated by high-performance liquid chromatography (HPLC) from a skua liver sample. A 1:1 mixture with trans-nonachlor in electron-capture detectors (ECDs) was used to determine the relative response factor with ECNI-MS. The ECNI-MS response of Q1 turned out to be 4.5 times higher than that of trans-nonachlor in an ECD. With GC/ECNI-MS in the selected ion-monitoring mode, four Antarctic and four Arctic air samples were investigated for the presence of Q1. In the Antarctic air samples, Q1 levels ranged from 0.7 to 0.9 fg/m(3). In Arctic air samples, however, Q1 was below the detection limit (<0.06 fg/m(3) or 60 ag/m(3)). We also report on high Q1 levels in selected human milk samples (12-230 microg/kg lipid) and, therefore, suggested that the unknown Q1 is an environmental compound whose origin and distribution should be investigated in detail. Our data confirm that Q1 is a bioaccumulative natural organochlorine product. Detection of a highly chlorinated natural organochlorine compound in air and human milk is novel.     

切圆燃烧煤粉炉的空气分级燃烧改造

阐述了分级燃烧抑制NOx形成的基本原理,介绍了切圆燃烧煤粉炉的空气分级燃烧改造的基本特点,考察了轴向和径向空气分级、炉内空气浓度等因素对NOx排放量的影响;控制适当条件,使脱氮效率达到30％－50％,对煤粉炉的空气分级燃烧改造进行了费用效益分析。     

Progress in developing an ANN model for air pollution index forecast

An air pollution index (API) reporting system is introduced to selected cities of China for public communication on air quality data. Shanghai is the first city in China providing daily average API reports and forecasts. This paper describes the development of an artificial neural network (ANN) model for the API forecasting in Shanghai. It is a multiple layer perceptron (MLP) network, with meteorological forecasting data as the main input, to output the next day average API values. However, the initial version of the MLP model did not work well. To improve the model, a series of tests were conducted with respect to the training method and structure optimization. Based on the test results, the training algorithm was modified and a new model was built. The new model is now being used in Shanghai for API forecasting. Its performance is shown reasonably well in comparison with observation. The application of the old model was only weakly correlated with observation. In 1-year application, the correlation coefficients were 0.2314, 0.1022 and 0.1710 for TSP, SO₂ and NO_x, respectively. But for the new model, for over 8 months application, the correlation coefficients are raised to 0.6056, 0.6993 and 0.6300 for PM₁₀, SO₂, and NO₂. Further, the new algorithm does not rely on manpower intervention so that it is now being applied in several other Chinese cities with quite different meteorological conditions. The structure of the model and the application results are presented in this paper and also the problems to be further studied.     

Environmental forensic investigation of the air pollution from a cement manufacturing unit

Abstract

Cement manufacturing is a process that results in the emission of significant quantities of suspended particulate matter (SPM) to the ambient air. An environmental forensic investigation was carried out in the surroundings of a major cement manufacturing unit at a place called Coimbatore in the southern Indian state of Tamil Nadu. The investigation was carried out to identify the contribution of the cement manufacturing unit to the SPM concentration of the surrounding air environment. The sampling points’ selection and sample collection were done following the principles outlined in the INTERPOL Manual for Pollution Crime Forensic Investigation. On-site monitoring of the air samples was carried out using Mini Laser Aerosol Spectrometer (GRIMM, Mini-LAS Model 11R). The instrument was capable of measuring particles ranging from 0.25 to 32 µm and classifying them into 31 size channels. The test results at majority of the monitoring locations were well above the limits specified in the National Ambient Air Quality Standards of India. Microscopic studies of the dust samples were carried out for surface texture and particle shape. The spatial distribution of particles was analysed using geographic information system (GIS) for the visual identification of the extent of the pollution by keeping the cement factory as the focal point. The results from the GIS and microscopic analysis established the role of the cement factory in the particulate matter pollution of its surroundings, specifically in the areas North-West of the factory. The successfully adopted procedure can serve as a guideline for the environmental forensic investigation of similar pollution incidences.     

室内空气中污染物的检测技术

室内环境空气污染对人体健康影响很大,文中指出了影响人体健康的致病因子,分析了单个微粒的光通量和粒径之间的关系。鉴于单下颗粒的散射光信号很弱,本文提出一种方法,把激光器的内腔作为颗粒注入区,利用激光器的内腔功率谱密度远大于腔外功率密度的特点,结合先进的激光散控制理论,对空气中的颗粒进行检测。     

混凝沉淀—气浮—生化处理洗毛废水

采用混凝沉淀－气浮－生化处理洗毛废水。混凝沉淀－气浮在进水ＣＯＤ１４５００ｍｇ／Ｌ,处理水量２０００ｍ＾３／ｄ,ＣＯＤ去除率９０％;ＨＲＴ ３２ｈ生化处理时,出水ＣＯＤ为１８７ｍｇ／ｌ,可达到污水综合排放二级标准（洗毛行业）。     

Progress in quantitative research on the relationship between atmospheric oxidation and air quality

Atmospheric oxidizing capacity (AOC) is an essential driving force of troposphere chemistry and self-cleaning, but the definition of AOC and its quantitative representation remain uncertain. Driven by national demand for air pollution control in recent years, Chinese scholars have carried out studies on theories of atmospheric chemistry and have made considerable progress in AOC research. This paper will give a brief review of these developments. First, AOC indexes were established that represent apparent atmospheric oxidizing ability (AOIe) and potential atmospheric oxidizing ability (AOIp) based on aspects of macrothermodynamics and microdynamics, respectively. A closed study refined the quantitative contributions of heterogeneous chemistry to AOC in Beijing, and these AOC methods were further applied in Beijing-Tianjin-Hebei and key areas across the country. In addition, the detection of ground or vertical profiles for atmospheric OH·, HO₂·, NO₃· radicals and reservoir molecules can now be obtained with domestic instruments in diverse environments. Moreover, laboratory smoke chamber simulations revealed heterogeneous processes involving reactions of O₃ and NO₂, which are typical oxidants in the surface/interface atmosphere, and the evolutionary and budgetary implications of atmospheric oxidants reacting under multispecies, multiphase and multi-interface conditions were obtained. Finally, based on the GRAPES-CUACE adjoint model improved by Chinese scholars, simulations of key substances affecting atmospheric oxidation and secondary organic and inorganic aerosol formation have been optimized. Normalized numerical simulations of AOIe and AOIp were performed, and regional coordination of AOC was adjusted. An optimized plan for controlling O₃ and PM_2.5 was analyzed by scenario simulation.     

VOC emission caps constrained by air quality targets based on response surface model: A case study in the Pearl River Delta Region, China

Because of the recent growth in ground-level ozone and increased emission of volatile organic compounds (VOCs), VOC emission control has become a major concern in China. In response, emission caps to control VOC have been stipulated in recent policies, but few of them were constrained by the co-control target of PM_2.5 and ozone, and discussed the factor that influence the emission cap formulation. Herein, we proposed a framework for quantification of VOC emission caps constrained by targets for PM_2.5 and ozone via a new response surface modeling (RSM) technique, achieving 50% computational cost savings of the quantification. In the Pearl River Delta (PRD) region, the VOC emission caps constrained by air quality targets varied greatly with the NO_x emission reduction level. If control measures in the surrounding areas of the PRD region were not considered, there could be two feasible strategies for VOC emission caps to meet air quality targets (160 µg/m³ for the maximum 8-hr-average 90th-percentile (MDA8-90%) ozone and 25 µg/m³ for the annual average of PM_2.5): a moderate VOC emission cap with <20% NOx emission reductions or a notable VOC emission cap with >60% NO_x emission reductions. If the ozone concentration target were reduced to 155 µg/m³, deep NO_x emission reductions is the only feasible ozone control measure in PRD. Optimization of seasonal VOC emission caps based on the Monte Carlo simulation could allow us to gain higher ozone benefits or greater VOC emission reductions. If VOC emissions were further reduced in autumn, MDA8-90% ozone could be lowered by 0.3-1.5 µg/m³, equaling the ozone benefits of 10% VOC emission reduction measures. The method for VOC emission cap quantification and optimization proposed in this study could provide scientific guidance for coordinated control of regional PM_2.5 and O₃ pollution in China.     

吹扫捕集与色谱质谱联用测定水中挥发性有机物

采用吹扫描集与色谱质谱联用的对水中１９种挥发性有机物同时进行富集分离，定性和定量检测，结果表明，不同化合物的平均回收率大于９０％相对偏差小于５％，该方法的检测限约为０．１－０．４μ／Ｌ。实验证明吹扫描集与色谱质谱联用技术是快速测定水中挥发性有要峨的有效手段。