Peracetic Acid Sanitation on Arugula Microgreens Contaminated with Surface-Attached and Internalized Tulane Virus and Rotavirus

Food and Environmental Virology - Hydroponic production of vegetables is becoming more common, especially in regions with unfavorable climate for year-round crop production. However, if viruses are...     

长沙市医疗垃圾管理处置状况及特性研究

报道了对长沙市5所医院为期一个月的研究结果，内容包括：医疗垃圾管理处置现状；医疗垃圾类型及产量；门诊人数、住院人数及垃圾量的变化规律；住院病人和门诊病人的垃圾产率及中药渣产率；传染性垃圾与生活垃圾的比例及医疗垃圾的组成，指出了现行医疗垃圾管理处置需要改进和提高之处，为建立长沙市医疗垃圾集中处理示范工程提供了依据。     

草木樨在汞胁迫下的遗传分化研究

以草木樨(Melilotus officinalis)种子为研究对象,将其暴露于0、20、40和60 mg·L-1浓度的氯化汞中进行萌发,并对存活的幼苗利用水平淀粉凝胶电泳进行等位酶分析.结果表明,草木樨在Me和Pgi基因座具有多态性,其平均的等位基因数为3.0基因座-1,杂合性为0.332 - 0.342,草木樨符合...     

臭氧应用于烟气净化的研究进展

烟气中所含的二氧化硫(SO2),氮氧化物(NOx),重金属汞(Hg)等污染物都能对人体健康及周围环境产生危害.本文综述了臭氧法应用于烟气净化的研究进展、工业应用及反应机理,探讨了臭氧同时脱硫脱硝脱汞的主要影响因素,介绍了臭氧发生技术的研究现状,并对臭氧应用于烟气净化进行了经济性分析,认为臭氧法脱除烟气中的多种污染物具有广泛的应用前景.     

滇池外海北岸封闭水域控养水葫芦对水质的影响

在滇池外海北岸污染严重的0.25 km2封闭性蓝藻治理试验示范区内控养水葫芦,以削减富营养化水体内源氮(N)、磷(P)等污染物,探讨有效改善湖泊水质的生物治理措施.6月底按9.30 kg m-2投放水葫芦种苗,控养面积2.51hm2,示范区水面覆盖度为10%.结果显示:水葫芦放养后生长迅速,特别是在7-9月份,最大生长速率达37 2.7 g m-2 d-1;整个植株干物质平均N、P含量分别为23.22 g kg-1和5.03 g kg-1,每t鲜重水葫芦吸收1.63 kg N、0.35 kg P,通过水葫芦种养示范工程,直接由示范工程水域吸收带走N 1.15 t、P 0.25 t;水葫芦生长期间(7-12月),种养区较对照区水体DO、SD和p H均有下降;水葫芦根系具有较好的吸附拦截浮游藻类效果,致使种养区水体TN、TP和CODMn浓度显著高于对照区(P<0.05),并与水体Chl-a浓度显著正相关(P<0.05);水葫芦采收后并未引起二次污染,水质无恶化趋势.综上认为,规模化控养水葫芦可显著削减水体N、P等内源污染负荷,同时对浮游藻类吸附拦截效果明显,可将其滞留于特定水域,又能吸收利用藻类衰亡释放到水体的污染物,减轻外部空白水域水质恶化的压力.     

湖泊富营养化模型的研究进展

湖泊的富营养化是全球普遍关注的环境问题之一.湖泊的富营养化模型是防治、修复和治理湖泊富营养化的重要决策工具.按研究的侧重点不同,将湖泊富营养化模型分为简单回归模型、水质模型、生态模型和生态-水动力水质模型,并分别回顾了四类模型的研究进展.最后指出湖泊富营养化模型的发展趋势,强调不确定理论、3S技术、耦合模型是今后湖泊富营养化模型研究的重点,应在此基础上建立通用的模拟、预测、评价和优化模型,为湖泊富营养化管理提供科学依据.     

A fast antibiotic detection method for simplified pretreatment through spectra-based machine learning

• A spectral machine learning approach is proposed for predicting mixed antibiotic. • Pretreatment is far simpler than traditional detection methods. • Performance of the model is compared in different influencing factors. • Spectral machine learning is promising in the detection of complex substances. Antibiotics are widely used in medicine and animal husbandry. However, due to the resistance of antibiotics to degradation, large amounts of antibiotics enter the environment, posing a potential risk to the ecosystem and public health. Therefore, the detection of antibiotics in the environment is necessary. Nevertheless, conventional detection methods usually involve complex pretreatment techniques and expensive instrumentation, which impose considerable time and economic costs. In this paper, we proposed a method for the fast detection of mixed antibiotics based on simplified pretreatment using spectral machine learning. With the help of a modified spectrometer, a large number of characteristic images were generated to map antibiotic information. The relationship between characteristic images and antibiotic concentrations was established by machine learning model. The coefficient of determination and root mean squared error were used to evaluate the prediction performance of the machine learning model. The results show that a well-trained machine learning model can accurately predict multiple antibiotic concentrations simultaneously with almost no pretreatment. The results from this study have some referential value for promoting the development of environmental detection technologies and digital environmental management strategies.     

Semi-closed synthesis of nitrogen and oxygen Co-doped mesoporous carbon for selective aqueous oxidation

Heteroatom-doped meso/micro-porous carbon materials are conventionally produced by harsh carbonization under an inert atmosphere involving specific precursors, hard/soft templates, and heteroatom-containing agents. Herein, we report a facile synthesis of N and O co-doped meso/micro-porous carbon (NOMC) by template-free carbonization of a small-molecule precursor in a semi-closed system. The semi-closed carbonizaiton process yields hydrophilic NOMCs with large surface area in a high yield. The porous structure as well as the elemental composition of NOMCs can be modulated by changing the holding time at a particular temperature. NOMCs as metal-free heterogeneous catalysts can selectively oxidize benzyl alcohol and its derivatives into aldehydes/ketones with>85％conversion in aqueous solution, which is much higher than that of the control sample obtained in tube furnace (21％conversion), mainly due to their high N content, high percentage of pyridinic N, and large surface area. The presence of O-containing moieties also helps to improve the hydrophilicity and dispersion ability of catalysts and thus facilitates the mass transfer process during aqueous oxidation. The NOMC catalysts also dispayed excellent activity for a wide range of substrates with a selectivity of>99％.     

Degradation of the typical herbicide atrazine by UV/persulfate: kinetics and mechanisms

Environmental Science and Pollution Research - Atrazine (ATZ), a widely used herbicide, had received a significant amount of attention due to its widespread detection in aquatic environments as...     

Effects of ambient air pollution on glycosylated hemoglobin: a systematic review and meta-analysis

Environmental Science and Pollution Research - Air pollution is one of the biggest environmental health problems in the world; accumulative studies have shown that air pollution was closely related...