中国蔬菜硝酸盐和亚硝酸盐污染因素及控制研究

本文综述了近十几年来我国城市蔬菜中硝酸盐和亚硝酸盐污染的研究结果,表明随着氮肥使用量的增大,蔬菜中硝酸盐污染较为严重而亚硝酸盐污染也不容忽视。探讨了蔬菜受硝酸盐和亚硝酸盐污染的影响因素及控制对策     

从委托代理理论谈中国的环境影响评价制度

根据委托代理理论,分析了中国环境影响评价制度中存在的问题,立足于绿色招商的理念,理顺建设项目环评委托代理关系,明确了建设单位、环评单位、招商部门、环保部门等相互之间的关系和职责,以使中国的环境影响评价制度更适应新型工业化道路发展的要求。     

城市规划的环境影响评价研究初探

环境影响评价法的颁布是中国环境影响评价的一个新阶段。中国至今尚无明确的、系统的规划环境影响评价的技术导则和规范,其评价理论仍在探索之中。分析了国内外规划环境影响评价的历史和现状。从区域环境影响评价的实践经验总结出了城市规划环境影响评价应强调城市发展的可持续性。探讨了该层次评价的介入时间、评价原则、环境影响因素识别及评价内容,提出从生态合理性、绿色化程度等方面考虑城市规划的生态环境影响。     

智能型防碰天车装置的安全可靠性分析

针对目前油田钻井现场使用的智能型防碰天车装置存在一些安全问题，分析了问题的实质是设计测量精度和安全可靠性不高。提出了具体改进设计的方案与意见。     

Mechanism and characterization of microplastic aging process: A review

● Methods for estimating the aging of environmental micro-plastics were highlighted. ● Aging pathways & characterization methods of microplastics were related and reviewed. ● Possible approaches to reduce the contamination of microplastics were proposed. ● The prospect and deficiency of degradable plastics were analyzed. With the increasing production of petroleum-based plastics, the problem of environmental pollution caused by plastics has aroused widespread concern. Microplastics, which are formed by the fragmentation of macro plastics, are bio-accumulate easily due to their small size and slow degradation under natural conditions. The aging of plastics is an inevitable process for their degradation and enhancement of adsorption performance toward pollutants due to a series of changes in their physiochemical properties, which significantly increase the toxicity and harm of plastics. Therefore, studies should focus on the aging process of microplastics through reasonable characterization methods to promote the aging process and prevent white pollution. This review summarizes the latest progress in natural aging process and characterization methods to determine the natural aging mechanism of microplastics. In addition, recent advances in the artificial aging of microplastic pollutants are reviewed. The degradation status and by-products of biodegradable plastics in the natural environment and whether they can truly solve the plastic pollution problem have been discussed. Findings from the literature pointed out that the aging process of microplastics lacks professional and exclusive characterization methods, which include qualitative and quantitative analyses. To lessen the toxicity of microplastics in the environment, future research directions have been suggested based on existing problems in the current research. This review could provide a systematic reference for in-depth exploration of the aging mechanism and behavior of microplastics in natural and artificial systems.     

MSWNet: A visual deep machine learning method adopting transfer learning based upon ResNet 50 for municipal solid waste sorting

● MSWNet was proposed to classify municipal solid waste. ● Transfer learning could promote the performance of MSWNet. ● Cyclical learning rate was adopted to quickly tune hyperparameters. An intelligent and efficient methodology is needed owning to the continuous increase of global municipal solid waste (MSW). This is because the common methods of manual and semi-mechanical screenings not only consume large amount of manpower and material resources but also accelerate virus community transmission. As the categories of MSW are diverse considering their compositions, chemical reactions, and processing procedures, etc., resulting in low efficiencies in MSW sorting using the traditional methods. Deep machine learning can help MSW sorting becoming into a smarter and more efficient mode. This study for the first time applied MSWNet in MSW sorting, a ResNet-50 with transfer learning. The method of cyclical learning rate was taken to avoid blind finding, and tests were repeated until accidentally encountering a good value. Measures of visualization were also considered to make the MSWNet model more transparent and accountable. Results showed transfer learning enhanced the efficiency of training time (from 741 s to 598.5 s), and improved the accuracy of recognition performance (from 88.50% to 93.50%); MSWNet showed a better performance in MSW classsification in terms of sensitivity (93.50%), precision (93.40%), F1-score (93.40%), accuracy (93.50%) and AUC (92.00%). The findings of this study can be taken as a reference for building the model MSW classification by deep learning, quantifying a suitable learning rate, and changing the data from high dimensions to two dimensions.     

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.     

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.     

锌在不同磷源条件下对铜绿微囊藻生长与产毒的影响

针对磷和微量元素对藻类生长的共同作用,研究不同磷源条件下锌对藻细胞生长与产毒的影响。实验选用铜绿微囊藻为藻种,分别以无机磷磷酸氢二钾(K_2HPO_4)、小分子有机磷甘油磷酸钠(NaGly)和大分子有机磷卵磷脂(LEC)为磷源,研究不同锌(Zn~(2+))含量对藻细胞的藻密度、碱性磷酸酶活性(alkaline phosphatase activity,APA)以及胞内藻毒素(MC-LR)的影响。研究发现:以NaGly为磷源时微量元素锌对藻细胞生长的促进效果显著,而以K_2HPO_4或LEC为磷源时,锌含量的变化对藻细胞生长无显著影响。APA不仅与磷源有关而且与锌含量相关,以LEC为磷源时的APA显著高于以K_2HPO_4或NaGly为磷源时的APA,且锌含量越低APA越低,以K_2HPO_4为磷源时锌含量越低APA越高,而锌对以NaGly为磷源时的APA几乎没有影响。磷源与微量元素锌对藻细胞的产毒均产生影响,NaGly有利于藻毒素的产生; LEC不利于藻细胞的产毒,但锌含量越低藻细胞的产毒量越多。综上所述,磷源与微量元素锌共同作用对藻细胞的生长与产毒产生影响,小分子有机磷NaGly与锌的效果显著。