Understanding and addressing the environmental risk of microplastics

Over the past decades, the plastic production has been dramatically increased. Indeed, a category of small plastic particles mainly with the shapes of fragments, fibers, or spheres, called microplastics (particles smaller than 5 mm) and nanoplastics (particles smaller than 1 μm) have attracted particular attention. Because of its wide distribution in the environment and potential adverse effects to animal and human, microplastic pollution has been reported as a serious environment problem receiving increased attention in recent years. As one of the commonly detected emerging contaminants in the environment, recent evidence indicates that the concentration of microplastics show an increasing trend, for the reason that up to 12.7 million metric tons of plastic litter is released into aquatic environment from land-based sources each year. Furthermore, microplastic exposure levels of model organisms in laboratory studies are usually several orders of magnitude higher than those found in environment, and the microplastics exposure conditions are also different with those observed in the environment. Additionally, the detection of microplastics in feces indicates that they can be excreted out of the bodies of animal and human. Hence, great uncertainties might exist in microplastics exposure and health risk assessment based on current studies, which might be exaggerated. Policies reduce microplastic emission sources and hence minimize their environmental risks are determined. To promote the above policies, we must first overcome the technical obstacles of detecting microplastics in various samples.     

Approaching the upper boundary of driver-response relationships: identifying factors using a novel framework integrating quantile regression with interpretable machine learning

● A novel framework integrating quantile regression with machine learning is proposed. ● It aims to identify factors driving observations to upper boundary of relationship. ● Increasing N:P and TN concentration help fulfill the effect of TP on CHL. ● Wetter and warmer decrease potential and increase eutrophication control difficulty. ● The framework advances applications of quantile regression and machine learning. The identification of factors that may be forcing ecological observations to approach the upper boundary provides insight into potential mechanisms affecting driver-response relationships, and can help inform ecosystem management, but has rarely been explored. In this study, we propose a novel framework integrating quantile regression with interpretable machine learning. In the first stage of the framework, we estimate the upper boundary of a driver-response relationship using quantile regression. Next, we calculate “potentials” of the response variable depending on the driver, which are defined as vertical distances from the estimated upper boundary of the relationship to observations in the driver-response variable scatter plot. Finally, we identify key factors impacting the potential using a machine learning model. We illustrate the necessary steps to implement the framework using the total phosphorus (TP)-Chlorophyll a (CHL) relationship in lakes across the continental US. We found that the nitrogen to phosphorus ratio (N׃P), annual average precipitation, total nitrogen (TN), and summer average air temperature were key factors impacting the potential of CHL depending on TP. We further revealed important implications of our findings for lake eutrophication management. The important role of N׃P and TN on the potential highlights the co-limitation of phosphorus and nitrogen and indicates the need for dual nutrient criteria. Future wetter and/or warmer climate scenarios can decrease the potential which may reduce the efficacy of lake eutrophication management. The novel framework advances the application of quantile regression to identify factors driving observations to approach the upper boundary of driver-response relationships.     

Influence of H2S and NH3 on biogas dry reforming using Ni catalyst: a study on single and synergetic effect

● NH₃ in biogas had a slight inhibitory effect on dry reforming. ● Coexistence of H₂S and NH₃ led to faster decline of biogas conversion. ● Regeneration was effective for catalysts deactivated under synergetic effect. Biogas is a renewable biomass energy source mainly composed of CH₄ and CO₂. Dry reforming is a promising technology for the high-value utilization of biogas. Some impurity gases in biogas can not be completely removed after pretreatment, which may affect the performance of dry reforming. In this study, the influence of typical impurities H₂S and NH₃ on dry reforming was studied using Ni/MgO catalyst. The results showed that low concentration of H₂S in biogas could cause serious deactivation of catalyst. Characterization results including EDS, XPS and TOF-SIMS confirmed the adsorption of sulfur on the catalyst surface, which was the cause of catalyst poisoning. We used air calcination method to regenerate the sulfur-poisoned catalysts and found that the regeneration temperature higher than 500 °C could help catalyst recover the original activity. NH₃ in the concentration range of 50–10000 ppm showed a slight inhibitory effect on biogas dry reforming. The decline rate of biogas conversion efficiency increased with the increase of NH₃ concentration. This was related to the reduction of oxygen activity on catalyst surface caused by NH₃. The synergetic effect of H₂S and NH₃ in biogas was investigated. The results showed that biogas conversion decreased faster under the coexistence of H₂S and NH₃ than under the effect of H₂S alone, so as the surface oxygen activity of catalyst. Air calcination regeneration could also recover the activity of the deactivated catalyst under the synergetic effect of H₂S and NH₃.     

电子废弃物中持久性有机污染物分析检测方法的研究进展

针对目前电子废弃物中持久性有机污染物(POPs)尚未形成有效快速分析检测方法的问题,介绍了溶剂萃取、固相萃取、微波萃取和超临界流体萃取等POPs前处理技术的研究进展,总结了POPs的分析方法,如:气相色谱、液相色谱、气相色谱-质谱法、高分辨率气相色谱-高分辨质谱法等化学分析方法,以及生物传感器测定法、表面胞质团共振检测法、酶联免疫检测法等生物分析方法。分析了各方法的优劣,并提出了展望。     

矿化垃圾床反应器厌氧甲烷氧化协同生物脱氮的研究

垃圾卫生填埋过程中逸散的甲烷与渗滤液处理过程中反硝化段不够彻底产生的硝酸盐对周围环境具有严重的威胁,反硝化厌氧甲烷氧化技术可实现甲烷与硝酸盐的同步去除,极具应用前景.本研究通过模拟垃圾填埋过程,以矿化垃圾作为垃圾填埋的覆土层与反硝化厌氧甲烷氧化微生物的接种源,建立了矿化垃圾床系统.结果表明,反应系统在140d的运行期间...     

海湾深厚海床场地二维非线性远场强地震反应特征∗

人们早已认识到远距离强地震可能引起覆盖层深厚的沿海或盆地城市发生严重的地震灾害。以某杭州湾跨海通道为背景,建立跨海湾海床二维场地的精细化有限元模型,依据区域地震活动性,选取远场大地震井下记录作为海床基岩的输入地震动,考虑地震动特性、海床微地形特征、沉积土的空间异质性和非线性滞回特性,研究了远场强震引起的海床场地非线性地震效应特征。海床场地效应与海床微地形特征、沉积土的空间异质性和输入地震动特性密切相关。凹陷地表边缘、基岩隆起和凹陷部位及海床土软弱区域的场地放大效应显著,呈现出低频聚焦现象,且竖向地震反应更为明显。仅考虑水平向地震作用将显著低估海床非线性场地效应程度,水平向和竖向地震同时作用引起的竖向地震效应不应忽视。     

Volatilization of heavy metals during incineration of municipal solid wastes

Incineration experiments with MSW, which had been impregnated with heavy metals, were presented to obtain information on the volatilization behavior of the elements cadmium (Cd), lead (Pb), and zinc (Zn) under different conditions. Experiments were carried out in a bubbling fluid bed system connected to a customized inductively coupled plasma optical emission spectroscopy(ICP-OES) for analyzing metals in the flue gas. The results indicated that the combustion temperature, the gas atmosphere, and the chlorine content in the flue gas could affect the volatilization behavior of heavy metals. In the fluidized bed combustion, a large surface area was provided by the bed sand particles, and they may act as absorbents for the gaseous ash-forming compound. Comparer with the metals Cd and Pb, the vaporization of Zn was low. The formation of stable compounds such as ZnO.Al2O3 could greatly decrease the metals volatilization. The presence of chlorine would enhance the volatilization of heavy metals by increasing the formation of metal chlorides. However, when the oxygen content was high, the chlorinating reaction was kinetically hindered, which heavy metals release would be delayed.     

Surface microlayer enrichment of volatile organic compounds and semi-volatile organic compounds in drinking water source

Enrichment of volatile organic compounds(VOC) and semi-volatility organic compounds(SVOC) in surface microlayer(SM) of three ddnking water sources were studied. The enrichment factor(EFs) were 0.67 to 13.37 and 0.16 to 136, respectively. The results showed some VOC and most SVOC could enrich in SM. Some EFs of SVOC was quite high. Suspension and temperature could affect EFs of SVOC, slim wind and water movement do not destroy enrichment of organic in SM.     

Preparation and catalytic properties of ZrO2-Al2O3 composite oxide supported nickel catalysts for methane reforming with carbon dioxide

ZrO2-Al2O3 composite oxides and supported Ni catalysts were prepared, and characterized by N2 adsorption/desorption, X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) techniques. The catalytic performance and carbon deposition was also investigated. This mesoporous composite oxide is shown to be a promising catalyst support. An increase in the catalytic activity and stability of methane and carbon dioxide reforming reaction was resulted from the zirconia addition, especially at 5wt% ZrO2 content. The Ni catalyst supported ZrO2-Al2O3 has a strong resistance to sintering and the carbon deposition in a relatively long-term reaction.     

Stabilization effects of surplus soft clay with cement and GBF slag

Utilization of industrial waste and surplus construction soft clay as construction material was recommended, and many attempts at geotechnical waste utilization were undertaken. This study aimed at the application of cement and a kind of industrial wastes, i.e. granulated blast furnace slag, on stabilization of surplus soft clay. The results showed that the cement and slag can successfully stabilize Ariake clays even though this high organic clay fails to be stabilized by lime and cement. Addition of slag in cement for stabilization induces higher strength than cement alone for longer curing time. The application of the cement with slag is more suitable than cement alone for stabilization because of economical consideration.