食物转化视角下我国家庭食物浪费程度与影响因素——基于CHNS数据的实证分析

长期以来,我国食物供应充足稳定,但是人口、环境等因素不断对此提出挑战,并且我国每年的食物损失和浪费数量十分惊人。从食物转化视角将食物浪费率定义为家庭食物消费中未能正常转化为家庭成员身体质量指数的比例,采用随机前沿模型并基于CHNS数据估算我国家庭食物浪费率,并探讨家庭异质性特征的影响。结果显示：家庭平均浪费率为11.28%;家庭规模越小、孩子或老年人的数量越多、收入水平越高、南方地区、户主的受教育程度越低、主要女性成员的受教育程度越高或者有工作、对膳食知识掌握程度越低的家庭浪费率越高。因此,要鼓励生产小包装食物和小型厨具,指导家庭根据实际需求购买食物,加强推广食育运动,开展节粮活动并教授减损措施。     

浏阳河长沙段CODMn、NH3-N和TP综合降解系数研究

采用现场水团追踪法,研究了浏阳河长沙段COD_Mn、NH₃-N和TP的综合降解系数与河段水流流速之间的相关关系,并通过河段历史水文和水质监测数据对所建立的相关方程进行了验证.结果表明,浏阳河长沙段COD_Mn、NH₃-N和TP的综合降解系数与流速之间呈明显的线性相关关系,相关方程形式分别为K（COD_Mn）=0.037+0.635v、K（NH₃-N）=0.059+0.315v和K（TP）=0.004+0.140v.所建立的线性相关方程对研究河段COD_Mn、NH₃-N和TP浓度预测结果的决定系数均大于0.90、相对均方根误差均小于0.10.受风浪作用、紊动水流和弯道环流的影响,当流速小于0.35m/s时,顺直河段的污染物综合降解系数均大于弯曲河段的污染物综合降解系数;当流速大于0.46m/s时,弯曲河段污染物综合降解系数均大于顺直河段的污染物综合降解系数.研究成果对浏阳河长沙段水质管理与水环境保护具有重要的参考价值.     

新烟碱类农药呋虫胺对映体选择性研究进展

农业生产中,呋虫胺以外消旋体的形式销售和使用,在进入生态环境后出现对映体选择性降解、吸收、代谢、排泄等.不区分对映体间差异的传统风险评估给呋虫胺的合理使用与生态安全带来了诸多隐患.研究指出S-呋虫胺既是高毒体也是高活体,其生态毒性为R-呋虫胺的13.9~145.9倍,但R-呋虫胺也表现出较高的杀虫活性,且作物中优先降解,开发高比例的R体农药有利于维持杀虫活性的同时降低对非靶生物和生态环境的负效应.本文旨在综述呋虫胺对映体选择性生物活性、生态毒性及环境行为研究进展,为其科学难题的解决提供新思路,也为其科学有效管理提供理论依据.     

Impact of meteorological condition changes on air quality and particulate chemical composition during the COVID-19 lockdown

Stringent quarantine measures during the Coronavirus Disease 2019 (COVID-19) lockdown period (January 23, 2020 to March 15, 2020) have resulted in a distinct decrease in anthropogenic source emissions in North China Plain compared to the paralleled period of 2019. Particularly, 22.7% decrease in NO₂ and 3.0% increase of O₃ was observed in Tianjin, nonlinear relationship between O₃ generation and NO₂ implied that synergetic control of NO_x and VOCs is needed. Deteriorating meteorological condition during the COVID-19 lockdown obscured the actual PM_2.5 reduction. Fireworks transport in 2020 Spring Festival (SF) triggered regional haze pollution. PM_2.5 during the COVID-19 lockdown only reduced by 5.6% in Tianjin. Here we used the dispersion coefficient to normalize the measured PM_2.5 (DN-PM_2.5), aiming to eliminate the adverse meteorological impact and roughly estimate the actual PM_2.5 reduction, which reduced by 17.7% during the COVID-19 lockdown. In terms of PM_2.5 chemical composition, significant NO₃^? increase was observed during the COVID-19 lockdown. However, as a tracer of atmospheric oxidation capacity, odd oxygen (O_x = NO₂ + O₃) was observed to reduce during the COVID-19 lockdown, whereas relative humidity (RH), specific humidity and aerosol liquid water content (ALWC) were observed with noticeable enhancement. Nitrogen oxidation rate (NOR) was observed to increase at higher specific humidity and ALWC, especially in the haze episode occurred during 2020SF, high air humidity and obvious nitrate generation was observed. Anomalously enhanced air humidity may response for the nitrate increase during the COVID-19 lockdown period.     

基于PMF模型解析典型化工园区VOCs污染来源应用研究

选取某小型化工园区为研究对象,在不同日期进行样品采集并使用气相色谱-质谱联用仪(GC-MS)定性定量分析,评估该区域VOCs污染水平及特征,同时研究P MF模型解析小尺度区域VOCs污染来源的可行性.结果表明,该研究区域VOCs浓度明显高于城市环境空气及其他化工园区,存在较重污染;该区域VOCs的主要成分为丙烯、苯、甲苯、萘、间-乙基甲苯、丙酮、丙烷、1,2,4-三甲苯、异丁烷等物质,各排放源污染特征显著,差异性明显;使用PMF模型对观测期间VOCs源解析,共获得4个因子,各因子与该区域不同排放源工艺及污染特征能够高度对应,并依此计算了各点位VOCs污染来源,结果与污染物扩散规律相符,PMF模型应用于小尺度污染物溯源分析具有可行性,能够很好地解析VOCs污染来源.     

Speciation characterization and coagulation of poly-silica-ferric-chloride：The role of hydrolyzed Fe（Ⅲ） and silica interaction

The highly e cient inorganic polymer flocculants (IPFs) of the ferric-silica system is a new and promising coagulant. Interactions between ferric species and silica play a large part in the coagulation of suspensions. These e ects are quite distinct from those associated with polymeric or colloid silica. However, although these species are key to coagulation e ciency, they have not been comprehensively discussed. A new type of coagulant, poly-silica-ferric-chloride (PFSC), was synthesized by co-polymerization and characterized by time complexation spectroscopy and photon correlation spectroscopy. Compared with traditional ferric salt, the results indicated that PFSC had a higher molecular weight, lesser positive charge, lower Feb and higher Fec. The higher the Si/Fe ratio, the higher the silica and lower the silicac found. The PFSC with appropriate polysilica acid not only obtained better coagulation/flocculation e ciency in turbidity removal, enhanced the flocculation index (FI) and provided less residual ferric, it also lowered water treatment costs compared to traditional ferric salt. Results showed that PFSC could remove colloid particles in water by charge neutralization and sweeping, adsorption bridging mechanism.     

时延神经网络对宝兴树蛙异质种群鸣叫的聚类分析

对瓦屋山宝兴树蛙3个不同海拔分布(A:山下;B:山腰;C:山上)的异质种群鸣叫的时频参数进行分析,发现三地鸣叫各参数互相重叠,无明显界线.常规统计分析不能使三地的鸣叫聚类为各自的组.使用时延神经网络对三地宝兴树蛙鸣叫的时频参数进行有指导聚类,发现三种群鸣叫有地区性差异,并表现出由个体交流引起的山腰种群群体特征的不显著.推测差异可能是因为长期地理隔离所导致.基于神经网络的分析结果,对各种群间的个体交流情况进行了初步估计.图6表1参20     

Photoelectrochemical technology for solar fuel generation,from single photoelectrodes to unassisted cells: a review

Environmental Chemistry Letters - Photoelectrochemical solar fuel generation requires a highly integrated technology for converting solar energy into chemical fuels. Dihydrogen (H2) and...     

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.     

Functional flax fiber with UV-induced switchable wettability for multipurpose oil-water separation

● A PAA-ZnO-HDTMS flax fiber with UV-induced switchable wettability was developed. ● The property of flax fiber could be switched from hydrophobicity to hydrophilicity. ● The mechanism of the acquired UV-induced switchable wettability was discussed. ● The developed flax fiber was successfully used for multipurpose oil-water separation. The large number of oily wastewater discharges and oil spills are bringing about severe threats to environment and human health. Corresponding to this challenge, a functional PAA-ZnO-HDTMS flax fiber with UV-induced switchable wettability was developed for efficient oil-water separation in this study. The developed flax fiber was obtained through PAA grafted polymerization and then ZnO-HDTMS nanocomposite immobilization. The as-prepared PAA-ZnO-HDTMS flax fiber was hydrophobic initially and could be switched to hydrophilic through UV irradiation. Its hydrophobicity could be easily recovered through being stored in dark environment for several days. To optimize the performance of the PAA-ZnO-HDTMS flax fiber, the effects of ZnO and HDTMS concentrations on its switchable wettability were investigated. The optimized PAA-ZnO-HDTMS flax fiber had a large water contact angle (~130°) in air and an extremely small oil contact angle (~0°) underwater initially. After UV treatment, the water contact angle was decreased to 30°, while the underwater oil contact angle was increased to more than 150°. Based on this UV-induced switchable wettability, the developed PAA-ZnO-HDTMS flax fiber was applied to remove oil from immiscible oil-water mixtures and oil-in-water emulsion with great reusability for multiple cycles. Thus, the developed flax fiber could be further fabricated into oil barrier or oil sorbent for oil-water separation, which could be an environmentally-friendly alternative in oil spill response and oily wastewater treatment.