2016—2017年武汉市城区大气PM2.5污染特征及来源解析

利用2016年1月至2017年9月湖北省环境监测中心站大气复合污染自动监测站的在线监测数据，对武汉市城区PM_2.5的污染特征及主要来源进行解析。结果表明，武汉市城区PM_2.5质量浓度呈现出明显的季节差异，季节变化规律为冬季>春季>秋季>夏季。水溶性离子的主要成分SO₄^2-、NO₃^-和NH₄⁺占总离子质量浓度的82.0%。PM_2.5中阴离子相对阳离子较为亏损，颗粒整体呈碱性。夏季气态污染物的氧化程度较高且SO₂较NO₂氧化程度高。后向轨迹分析结果表明，区域传输是武汉市PM_2.5的一个重要来源，在4个典型重污染阶段，武汉市分别受到局地、东北、西北及西南方向气团传输的影响。PMF模型解析出武汉市PM_2.5五大主要来源及平均贡献率：扬尘22.0%、机动车排放27.7%、二次气溶胶21.6%、重油燃烧14.9%和生物质燃烧13.8%。     

郑州市土壤与绿色植物中汞的分布特征

汞污染具有生物积累性,因而得到社会广泛关注。研究监测和评估了郑州市城区土壤和绿色植物叶片中汞浓度、分布、污染水平等。研究发现郑州市主城区土壤总汞浓度为0. 150～0. 958 mg/kg,平均浓度为0. 448 mg/kg;郑州市主城区绿色植物叶片总汞浓度为0. 017～0. 249 mg/kg,平均浓度为0. 107 mg/kg;土壤和叶片中汞浓度按功能区排序为交通枢纽区工业区商业区行政区高教区住宅区。采用地累积指数法对郑州市80个土壤样品的汞污染水平进行评估,结果显示60%受到轻度污染,35%受到偏中度污染,5%受到中度污染。研究较为全面地分析了土壤汞污染的现状及浓度,为郑州市土壤汞污染防治提供参考。     

石家庄市春季大气颗粒物的铅污染特征

为了解石家庄市2016年春季大气颗粒物的铅污染特征及来源,利用单颗粒气溶胶质谱仪(SPAMS),分析了大气中含铅颗粒的化学成分。结果表明: 研究期间大气环境中含铅颗粒数浓度共出现11次跳跃式升高,跳跃时间段内石家庄均处于轻度污染过程。从成分分析来看,含铅颗粒分为纯铅颗粒、Pb与K(Pb-K)、OC(Pb-OC)、Cl(Pb-Cl)、混合颗粒等八大类。观测结果表明:Pb-K颗粒最多,占到含铅颗粒的84.4%；其次为纯铅颗粒,占比为13.0%。与石家庄市污染源谱库比对进行来源解析,得到Pb-K颗粒主要来自生活垃圾焚烧源, 纯铅颗粒主要来自工业源。结合石家庄市大气污染源排放清单和后向气流轨迹分析,推测含铅颗粒可能来自市区西南方向某区县的生活垃圾焚烧企业。     

Effect of ambient polycyclic aromatic hydrocarbons and nicotine on the structure of Aβ42 protein

● B[a]P, nicotine and phenanthrene molecules altered the secondary structure of Aβ₄₂. ● β-content of the peptide was significantly enhanced in the presence of the PAHs. ● Nicotine made stable cluster with Aβ₄₂ peptide via hydrogen bonds. ● Phenanthrene due to its small size, interfered with the Aβ₄₂ monomer more strongly. Recent studies have correlated the chronic impact of ambient environmental pollutants like polycyclic aromatic hydrocarbons (PAHs) with the progression of neurodegenerative disorders, either by using statistical data from various cities, or via tracking biomarkers during in-vivo experiments. Among different neurodegenerative disorders, PAHs are known to cause increased risk for Alzheimer’s disease, related to the development of amyloid beta (Aβ) peptide oligomers. However, the complex molecular interactions between peptide monomers and organic pollutants remains obscured. In this work, we performed an atomistic molecular dynamics study via GROMACS to investigate the structure of Aβ₄₂ peptide monomer in the presence of benzo[a]pyrene, nicotine, and phenanthrene. Interestingly the results revealed strong hydrophobic, and hydrogen-bond based interactions between Aβ peptides and these environmental pollutants that resulted in the formation of stable intermolecular clusters. The strong interactions affected the secondary structure of the Aβ₄₂ peptide in the presence of the organic pollutants, with almost 50 % decrease in the α-helix and 2 %–10 % increase in the β-sheets of the peptide. Overall, the undergoing changes in the secondary structure of the peptide monomer in the presence of the pollutants under the study indicates an enhanced formation of Aβ peptide oligomers, and consequent progression of Alzheimer’s disease.     

Emerging applications of green coconut: A promising lignocellulosic biomass

Waste accumulation is a grave concern and becoming a transboundary challenge for environment. During Covid-19 pandemic, diverse type of waste were collected due to different practices employed in order to fight back the transmission rate of the virus. Covid-19 was proved to be capricious catastrophe of this 20th century and even not completely eradicated from the world. The havoc created by this imperceptible quick witted, pleomorphic deadly virus can't be ignored. Though a number of vaccines have been developed by the scientists but there is a fear of getting this virus again in our life. Medical studies prove that immunity drinks will help to reduce its reoccurrences. Coconut water is widely used among all drinks available globally. Its massive consumption created an incalculable pile of green coconut shells around the different corners of the world. This practice generating enormous problem of space acquisition for the environment. Both the environment and public health will benefit from an evaluation of quantity of coconut waste that is being thrown and its potential to generate value added products. With this context, present article has been planned to study different aspects like, coconut waste generation, its biological properties and environmental hazards associated with its accumulation. Additionally, this review illustrates, green technologies for production of different value added products from coconut waste.     

A new prediction method of industrial atmospheric pollutant emission intensity based on pollutant emission standard quantification

● Established a quantification method of pollutant emission standard. ● Predicted the SO₂ emission intensity of single coking enterprises in China. ● Evaluated the influence of pollutant discharge standard on prediction accuracy. ● Analyzed the SO₂ emissions of Chinese provincial and municipal coking enterprises. Industrial emissions are the main source of atmospheric pollutants in China. Accurate and reasonable prediction of the emission of atmospheric pollutants from single enterprise can determine the exact source of atmospheric pollutants and control atmospheric pollution precisely. Based on China’s coking enterprises in 2020, we proposed a quantitative method for pollutant emission standards and introduced the quantification results of pollutant emission standards (QRPES) into the construction of support vector regression (SVR) and random forest regression (RFR) prediction methods for SO₂ emission of coking enterprises in China. The results show that, affected by the types of coke ovens and regions, China’s current coking enterprises have implemented a total of 21 emission standards, with marked differences. After adding QRPES, it was found that the root mean squared error (RMSE) of SVR and RFR decreased from 0.055 kt/a and 0.059 kt/a to 0.045 kt/a and 0.039 kt/a, and theR² increased from 0.890 and 0.881 to 0.926 and 0.945, respectively. This shows that the QRPES can greatly improve the prediction accuracy, and the SO₂ emissions of each enterprise are highly correlated with the strictness of standards. The predicted result shows that 45% of SO₂ emissions from Chinese coking enterprises are concentrated in Shanxi, Shaanxi and Hebei provinces in central China. The method created in this paper fills in the blank of forecasting method of air pollutant emission intensity of single enterprise and is of great help to the accurate control of air pollutants.     

Five-wheel framework for system-based monitoring of heavy metal pollution in rivers

Sectorial approach for monitoring heavy metal pollution in rivers has failed to report realistic pollution status and associated ecological and human health risks. The increasing spread of heavy metals from different sources and emerging risks to human and environmental health call for reexamining heavy metal pollution monitoring frameworks. Also, the sources, spread, and load of heavy metals in the environment have changed significantly over time, requiring consequent modification in the monitoring frameworks. Therefore, studies on heavy metal monitoring in rivers conducted in the last decade were evaluated for experimental designs, research frameworks, and data presentations. Most studies (∼99%) (i) lacked inclusiveness of all environmental compartments; (ii) focused on “one pollutant – one/two compartment” or sometimes “one pollutant – one compartment – one effect” approach; and (iii) remained “data-rich but information poor.” An ecological approach with integrative system thinking is proposed to develop a holistic approach for monitoring river pollution. It is visualized that heavy metal monitoring, risk analyses, and water management must incorporate tracking pollutants in different environmental compartments of a river (water, sediment, and floodplain/bank soil) and consider correlating it with riverbank land use. The systems-based pollution monitoring and assessment studies will reveal the critical factors that drive heavy metals pollutant movement in ecosystems and associated potential risks to the environment, wildlife, and humans. Also, water quality and pollution indexing tools would help better communicate complex pollution data and associated risks among all stakeholders. Therefore, integrating systems approaches in scientific- and policy-based tools would help sustainably manage the health of rivers, wildlife, and humans.     

我国居住建筑室内PM_(2.5)研究现状及进展

分析了我国居住建筑室内PM_(2.5)污染水平,总结了现阶段PM_(2.5)的研究方法,主要包括理论分析法、数值模拟法和实验测试法。指出室外源是室内PM_(2.5)的主要污染来源,而室内烟草烟雾、烹饪及人员活动也会严重影响室内PM_(2.5)浓度。针对目前研究中存在的问题,提出了标定典型建筑在不同影响因素下的I/O比范围、研究家具和家电的颗粒物释放状况、加强农村室内外空气颗粒物污染调查等建议。     

工业废水毒性评估与致毒物质鉴别技术进展

综述了工业废水毒性的化学评估方法、生物毒性评估方法、毒性鉴定评估(TIE)程序以及效应引导的毒物鉴别分析(EDA)中污染物提取、分离、毒性测试、致毒物质识别等技术。指出,工业废水毒害风险评估方法正逐渐向化学分析与生物毒性测试相结合的关键致毒物质鉴别方法转变,便捷、高通量是致毒物质鉴别技术的发展方向,质谱技术及替代定性监测技术的发展将提供更为准确、便捷的致毒物质鉴别方法,为工业废水潜在风险防控提供依据。     

2013-2017年京津冀区域PM2.5浓度变化特征

利用2013-2017年京津冀区域13个城市PM_2.5监测数据，综合探讨了该区域PM_2.5浓度的时空变化特征。结果表明：京津冀区域PM_2.5污染整体较重，但治理成效显著，2013-2017年区域PM_2.5年均质量浓度分别为106、93、77、71、64 μg/m³，完成《大气污染防治行动计划》PM_2.5浓度下降25%左右的目标；13个城市PM_2.5浓度各百分位数总体呈现下降趋势，且随百分位数增大而下降速率加大，PM_2.5年均质量浓度平均每年下降10.6 μg/m³，污染严重的太行山沿线城市邢台、石家庄、邯郸3个城市平均每年分别下降20.3、16.1、13.9 μg/m³；京津冀区域PM_2.5重度污染天数比例分别为19.9%、16.6%、9.5%、9.0%、7.0%，呈下降趋势。2013-2017年京津冀区域PM_2.5平均质量浓度与非重度污染天相比升高19 μg/m³，PM_2.5重度污染天平均质量浓度较非重度污染天时高244.4%。