全氟化合物对水生植物的生态效应研究Ⅱ——金鱼藻对水中PFOS的生物富集及生理响应

为探究全氟化合物对水生植物的生态效应,选择金鱼藻(Ceratophyllum demersum L.)为受试生物,设定5、100、1 000、10 000、50 000、100 000μg·L-1以及对照共7个PFOS浓度梯度进行水培,分析包括超氧化物歧化酶(SOD)、过氧化氢酶(CAT)、过氧化物酶(POD)在内的抗氧化系统酶和细胞色素含量等生理响应特征,并研究金鱼藻对PFOS的生物有效性及富集能力。结果表明:金鱼藻对PFOS的富集量最高可达3 180 mg·kg-1dw,最大富集系数高达40.7倍,可作为PFOS污染水体植物修复的遴选物种。随PFOS浓度升高,SOD活力总体上没有明显变化,但POD活力表现为双重效用,即低浓度促进酶活力积累,而高浓度抑制酶活力积累。CAT活力在低浓度组(0、5、100、1 000μg·L-1),未表现出明显异常,在高浓度组(10 000、50 000、100 000μg·L-1),出现先升高后降低的趋势。色素含量也反应较为敏感,低浓度处理后色素含量升高,高浓度处理则导致色素含量先升高后降低,最高浓度处理下一直处于较低水平,可作为评价PFOS污染水体的生理敏感性指标。     

全氟化合物对水生植物的生态效应研究Ⅰ——典型城市河道全氟化合物的暴露水平及植物富集特征

全氟化合物(perfluorinated compounds,PFCs)近年来得到国内外广泛关注,针对工业源排放区域的环境暴露、来源解析以及动物层面的生态效应有较多研究,但对于普遍存在于非工业源(生活源)的城市河道PFCs暴露及水生植物富集等研究较为缺乏。本研究选择位于北京北部东西贯通的城市河道——清河水体为对象,分析结果表明,清河水体中12种目标PFCs均有检出(总量最高为65.45 ng·L-1),并以全氟丁烷磺酸盐(perfluorobutane sulfonate,PFBS)为主(最高达45.63 ng·L-1);6种水生植物(篦齿眼子菜、黑藻、金鱼藻、芦苇、菖蒲及水葱)的富集物质均以全氟辛烷磺酸盐(perfluorooctane sulfonate,PFOS)和全氟辛酸(perfluorooctanoic acid,PFOA)为主,沉水植物中金鱼藻对于PFOS的蓄积效果优于黑藻及篦齿眼子菜,挺水植物中根部PFCs含量高于茎叶,根部PFOA及PFOS含量高于茎叶,但全氟丁酸(perfluorobutanoic acid,PFBA)含量茎叶则高于根部。整体来看,尽管芦苇、菖蒲和水葱3种挺水植物尚不能作为PFCs的超富集植物,但其根部对PFCs均有显著的吸收效果,具有一定的生态修复潜质;沉水植物中金鱼藻是北方自然河道的优势物种,且对PFOS具有显著的富集效应,因此有必要进一步探索其PFCs生物指示和生态修复功能。     

办公室地面灰尘中PAHs污染的时间变化规律及人体健康风险

为探究室内地面灰尘中15种多环芳烃(PAHs)污染的时间变化规律,于2012年3—7月对北京市一座办公楼内的某办公室进行了每周一次的连续高密度灰尘样品采集。利用高效液相色谱-荧光检测器检测15种PAHs含量。结果表明,该办公室内灰尘样品中∑PAHs浓度范围为1 180~24 300 ng·g~(-1),平均浓度为8 960 ng·g~(-1)。总体上,检出的PAHs以3环PAHs为主,其中菲占PAHs总量的59%以上,其次是4环和5环PAHs,4环PAHs中占的比重最高,约占4环PAHs总量的34%。该办公室内灰尘中∑PAHs的浓度存在显著的时间变化差异,总体表现为∑PAHs浓度随气温升高而降低的趋势。源解析结果显示,机动车排放源、石油源、木材与煤燃烧是北京市室内灰尘中PAHs的主要来源。健康风险评估结果显示,ILCR皮肤接触ILCR手口摄入,且CR均值大于10-6,说明该采样点的PAHs污染存在"潜在致癌风险"。     

太原市城市化发展对城市气温变化影响的定量化研究

采用位于同一纬度的太原气象站与远郊区农村气象站获取的1957年-2014年的气象数据,用皮尔卡森相关系数、一元线性回归、城市化影响分析等方法研究了在全球气候变暖背景下城市地区气温变化趋势以及城市化影响.结果表明:城市年平均气温升高趋势明显高于农村;城市年极端高温与农村极端高温升高趋势差异不明显;城市年极端低温升高趋势显著高于农村.就城市化影响而言,城市化对年平均气温、年极端低温趋势影响明显,但对年极端高温趋势影响微弱.     

Environmental friendly leaching reagent for cobalt and lithium recovery from spent lithium-ion batteries

We investigated an environmentally friendly leaching process for the recovery of cobalt and lithium from the cathode active materials of spent lithium-ion batteries. The easily degradable organic acid DL-malic acid (C₄H₅O₆) was used as a leaching reagent. The structural, morphology of the cathode materials before and after leaching were characterized by X-ray diffraction (XRD) and scanning electronic microscopy (SEM). The amount of Co and Li present in the leachate was determined by atomic absorption spectrophotometry (AAS). Conditions for achieving a recovery of more than 90 wt.% Co and nearly 100 wt.% Li were determined experimentally by varying the concentrations of leachant, time and temperature of the reaction as well as the initial solid-to-liquid ratio. We found that hydrogen peroxide in a DL-malic acid solution is an effective reducing agent because it enhances the leaching efficiency. Leaching with 1.5 M DL-malic acid, 2.0 vol.% hydrogen peroxide and a S:L of 20 g L^?1 in a batch extractor results in a highly efficient recovery of the metals within 40 min at 90 °C.     

Employees' surface acting in interactions with leaders and peers

Surface acting has been widely studied in organizational research owing to its impact on organizational behaviors and outcomes. Past research almost exclusively has focused on employees' interactions with external parties such as customers, clients, and patients. This study sought to extend this literature by examining the effects of employees' surface acting in interactions with parties internal to the organization (i.e., leaders and peers). Data were collected from 40 work groups (129 focal participants, 40 leaders, and 40 peers) from a large real estate agency company located in Beijing, China. Results showed that employees' surface acting influenced various emotional, relational, and behavioral outcomes. In addition, the present findings revealed that the consequences of employees' surface acting differed across leaders versus peers. Copyright © 2015 John Wiley & Sons, Ltd.     

Optimal regulation of N/P in horizontal sub-surface flow constructed wetland through quantitative phosphorus removal by steel slag fed

High concentration of nitrogen and phosphorus and imbalance of N/P can lead to the formation of water and the malignant proliferation of toxic microalgae. This study put forward the advanced nutrient removal with the regulation of effluent N/P as the core in order to restrain the eutrophication and growth of poisonous algae. According to the preliminary study and review, the optimal N/P for non-toxic green algae was 50:1. The horizontal sub-surface flow constructed wetland was filled with steel slag and ceramsite to achieve the regulation of effluent N/P. The results showed that steel slag had the stable P removal capacity when treating synthetic solution with low P concentration and the average removal rate for 1.5, 1.0, and 0.5 mg/L synthetic P solution was 2.98 ± 0.20 mg kg−1/h, 2.26 ± 0.15 mg kg−1/h, and 1.11 ± 0.10 mg kg−1/h, respectively. Combined with P removal rate and P removal task, the filling amount of steel slag along the SSFCW (sub-surface flow constructed wetland) was 3.22 kg, 4.24 kg, and 4.31 kg. In order to ensure the stability of dephosphorization of steel slag, the regeneration of P removal capacity was investigated by switching operation of two parallel SSFCW in 20 days for cycle. The N removal was limited for the deficiency of carbon source (COD (chemical oxygen demand)/TN = 3–4), and was stable at 18.5–31.9% which was less affected by temperature. Therefore, by controlling the process of quantitative P removal of steel slag, the effluent N/P in SSFCW can be stable at 40–60:1 in the whole year, so as to inhibit the malignant proliferation of toxic algae.     

Monitoring gas- and particulate-phase short-chain polychlorinated paraffins in the urban air of Dalian by a self-developed passive sampler

The concentration of short-chain polychlorinated paraffins(SCCPs) in the urban air of Dalian,China was monitored from September 2016 to August 2017 with a self-developed passive sampler(PAS1) and an active high-volume sampler, simultaneously. PAS1 successfully collected the entire target SCCPs in the ambient air. Air SCCPs sampled by PAS1 were found be in the linear uptake stage during 181 days of sampling. Passive and active samples showed comparable congener profiles, and the dominant contributors of SCCPs in the two kinds of samples were similar. A significant linear correlation was observed between the total concentration of SCCPs sampled by PAS1 and active sampler in the four seasons. The passive sampling rates of the PAS1 for the gas and particulate phases of SCCPs were measured. The quantitative structure–property relationship of the sampling rate of PAS1(Rair) for gas-phase SCCPs was studied. From the molecular point of view, Rairwas mainly affected by the molecular weight and sub-cooled liquid vapor pressure of SCCPs. In general, SCCPs in the urban air of Dalian mainly existed in gas phase,lower molecular weight SCCPs primarily occurred in the gas phase, whereas higher molecular weight SCCPs were predominately adsorbed or absorbed on airborne particles. The air concentration of SCCPs in the four seasons were different, the correlation of the concentration of SCCPs in the air with the meteorology parameters was conducted. The exposure risk by intake air SCCPs of the residents around the sampling sites was evaluated according to the European risk assessment standards.     

Prediction of high-density polyethylene pyrolysis using kinetic parameters based on thermogravimetric and artificial neural networks

● Reducting the sampling frequency can enhance the modelling process. ● The pyrolysis of HDPE was investigated at three different heating rates. ● The average E_a and k₀ were calculated by Friedman, KAS, FWO, and CR methods. ● ANN was employed to predict the HDPE weight loss with the optimal MSE and R². Pyrolysis is considered an attractive option and a promising way to dispose waste plastics. The thermogravimetric experiments of high-density polyethylene (HDPE) were conducted from 105 °C to 900 °C at different heating rates (10 °C/min, 20 °C/min, and 30 °C/min) to investigate their thermal pyrolysis behavior. We investigated four methods including three model-free methods and one model-fitting method to estimate dynamic parameters. Additionally, an artificial neural network model was developed by providing the heating rates and temperatures to predict the weight loss (wt.%) of HDPE, and optimized via assessing mean squared error and determination coefficient on the test set. The optimal MSE (2.6297 × 10⁻²) and R² value (R² > 0.999) were obtained. Activation energy and pre-exponential factor obtained from four different models achieves the acceptable value between experimental and predicted results. The relative error of the model increased from 2.4 % to 6.8 % when the sampling frequency changed from 50 s to 60 s, but showed no significant difference when the sampling frequency was below 50 s. This result provides a promising approach to simplify the further modelling work and to reduce the required data storage space. This study revealed the possibility of simulating the HDPE pyrolysis process via machine learning with no significant accuracy loss of the kinetic parameters. It is hoped that this work could potentially benefit to the development of pyrolysis process modelling of HDPE and the other plastics.