SBR法处理啤酒废水和味精废水进水方式的研究

采用SBR法处理啤酒废水和味精废水 ,研究了不同进水方式对SBR法处理效果的影响。试验结果表明 :啤酒废水采用限制曝气进水效果较好 ,瞬时进水和限制曝气进水效果相当 ;味精废水采用非限制曝气进水效果较好。通过动力学分析认为 :SBR反应器内的反应在限制曝气进水条件下以推流式进行 ,在非限制曝气进水条件下具有完全混合式的特点。     

乌鲁木齐市市民环境意识万人问卷调查报告

为贯彻全国和自治区第４次环保会议精神,了解和提高全市各族群众的环境意识,使环境保护基本国策深入人心,乌鲁木齐市环保局在１９９８年“六·五”世界环境日之际开展了以“关心环境保护,共建美丽首府”为主题的市民环境意识万人问卷活动。由全市７区１县及２个开发区环保局（站）协助,分别在政府机关、厂矿、学校、街头、摊点进行发放问卷活动。调查结果初步摸清了乌鲁木齐市在环境宣传教育中所取得的成效和存在的问题,为今后更好地加强环境宣传教育,普及环境科学知识,提高社会各界环境意识提供了参考信息。     

废催化剂浸出规律的静态实验方法

利用静态浸出实验方法对废催化剂中重金属在不同固水比和浸出次数条件下的浸出规律进行了系统研究。实验发现浸出次数大于３次后,重金属的浸出浓度和浸出速率趋于稳定,同时固水比的增加也没有明显改变废催化剂中重金属的浸出。认为在浸取次数大于３次以后,随着表面溶质的溶解,浸出过程主要为内扩散所控制。     

活性炭纤维吸附／热解吸／毛细管气相色谱法测定低浓度VOCs的方法

本文以活性炭纤维为吸附材料,建立了活性炭纤维吸附／二次热解吸 缩／毛细管气相色谱法测定空气中ＶＯＣＳ的方法,讨论了吸附剂的安全采样体积,湿度控制及分析方法的精密度,检出限和回收率。本法对苯,甲苯,四氯乙烯,对－二甲苯和苯乙类的最低可测浓度分别为０．１３,０．０２,０．１２,０．０５和０．０５μｇ．ｍ＾－３,适用于低浓度ＶＯＣＳ样品的测定。     

Mechanism of complexation of toxic arsenate,selenate, and molybdate with hydrotalcites

Environmental Chemistry Letters - Wastewater from the uranium mining industry contains toxic arsenate (AsO43–), selenate (SeO42–), and molybdate (MoO42–) that can be removed by...     

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.     

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.     

震后灾害链生机制及其对汶川地震城镇重建的影响

汶川8级大地震对地表产生强烈扰动,导致次生山地灾害极度发育,影响到震后灾害的活动特征及其相应的减灾对策。震后松散固体物质急剧增加、流域微地貌变化明显(沟道堵塞严重)、水文变化利于侵蚀和洪峰,使得灾害群发链生:崩塌、滑坡→泥石流→堰塞湖→溃决洪水(泥石流),8月中旬灾区各地因强降雨而大规模爆发泥石流堵塞河道,洪水冲毁掩埋重建城镇,给地震重灾区造成巨大损失。从以汶川县映秀镇为例,在阐述灾害链研究成果的基础上,分析震后灾害链的形成条件、成灾过程以及对城镇重建居民点的危害特点,进而提出灾害防治措施,为灾后城镇建设防灾减灾提供参考建议。     

基于合成孔径雷达的城市建筑地震受损分析

汶川地震灾区位于青藏高原东缘,该地区云雨天气较多,光学遥感受制约较大,而微波能够穿透云、雾、小雨等,且不受太阳光线的影响,雷达遥感具有全天时、全天候的特点,因而可以弥补光学遥感的不足。根据房屋受地震破坏后影响雷达回波强度,在雷达影像上表现为亮度及纹理不同的原理,本论文利用不同分辨率的COSMO-SkyMed和Radarsat等SAR数据,将其与震前的SPOT影像进行配准后,通过纹理分析等处理,对都江堰市区、北川县城曲山镇等受灾较为严重的城镇进行分析解译,利用雷达影像判读出倒塌房屋的信息,以及地震次生山地灾害对城镇的破坏。     

Cadmium uptake by different rice genotypes that produce white or dark grains

IntroductionCadmium(Cd)isanon essentialtracemetalthathasadverseeffectsonplants,animalsandhumans.EnvironmentalcontaminationwithCdduetoanthropogenicactivities,suchasmining,industry,agricultureandwastedisposalhasbeenincreasingsincethebeginningofthe 2 0thcentury (Alloway,1995) .ResearchoncontrollingCdpollutionassociatedwithassessingandmanagingacuteinjurytohumanhealththroughoccupationalexposureanddisposalofCdfromindustrialpointsourcestolocalpopulationsthroughseveralpathwayshasmadeconsiderableadva…