丙烯腈、醋酸乙烯酯罐区火险分析及对策

对丙烯腈、醋酸乙酯罐系统危险性及罐区泄漏潜在危险性进行了系统分析。并对丙烯腈、醋酸乙烯酯罐区的防火防爆提出了相应的对策,对泡沫消防设备及可燃气体检测器灭火系统的可行性和实用性进行了重点介绍和探讨。     

化学吸收法回收工业废气中CO的研究

通过实验优选出一种ＣｕＣｌ－ＭｇＣｌ２水溶系统高选择性ＣＯ吸收剂,确定了吸收剂对ＣＯ的最大吸收量与温度的关系,探讨了气体组成变化对ＣＯ回收率的影响,由实验数据求出吸收过程中ＣＯ的回收率为９３％。采用气相色谱分析法测出产物ＣＯ的纯度为９８％,给出吸收液的解吸温度范围为１２０－１４０℃。初步探讨了ＣｕＣｌ－ＭｇＣｌ２水溶系吸收剂对ＣＯ的吸收反应机理,为转炉烟气等工业废气中ＣＯ的分离回收提供了新途径。     

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.     

基于我国物种毒性数据的多溴联苯醚预测无效应浓度分析

采用多溴联苯醚(PBDEs)对我国广泛分布生物物种的生态毒性数据,根据欧盟现有化学物质风险评价技术指导文件,对不同环境介质中PBDEs预测无效应浓度(PNEC)进行了推导。结果表明:我国淡水环境PBDEs(四溴、五溴、八溴)的PNEC水分别为50μg·L~(-1)、0.53μg·L~(-1)、0.017μg·L~(-1)。沉积物环境PBDEs(四溴、五溴、八溴和十溴)的PNEC沉积物分别为823.35 mg·kg~(-1)wt、1.55 mg·kg~(-1)dw、12.72 mg·kg~(-1)dw、38.41 mg·kg~(-1)dw。土壤环境PBDEs(四溴、五溴、八溴和十溴)的PNEC土壤分别为668.3mg·kg~(-1)wt、0.38 mg·kg~(-1)dw、147 mg·kg~(-1)dw、98 mg·kg~(-1)dw。次生毒性PBDEs(五溴、八溴和十溴)的PNEC经口分别为0.3~0.7 mg·kg~(-1)、0.56 mg·kg~(-1)、2 500 mg·kg~(-1)。该数值期为我国PBDEs的环境风险评价提供科学基础。     

上海城市绿地景观异质性分析

选取贯穿上海外环线内绿地景观的8条样线，借助数学的方法，研究绿地景观要素的构成、线性分布等特征，从而找出了上海城市绿地景观的异质性状况，并对今后的规划建设提出了建议。     

长江口南支重金属分布研究

对长江口南支采集的水样、悬沙和表层沉积物中的重金属含量进行了分析。结果表明，悬浮物中重金属含量高于表层沉积物，且2者远高于水相中重金属含量。大多数重金属元素间都有良好的相关性。水相中重金属含量由内向外呈轻微的浓度变化；悬浮物中重金属含量逐渐降低；表层沉积物中重金属含量向长江口外有降低趋势，介在长江口门处出现高浓度。河口重金属的分布受到离子交换、吸附、解吸、释释以及水动力等诸多因素的影响。     

日光辐射对大气真菌粒子的影响

大气中真菌粒子的衰亡和净化，除与真菌自身的因素有关外，与日光辐射也有密切关系。此文现场观测了日光辐射对大气真菌粒子的影响。结果表明，一天内大气真菌粒子浓度与日光辐射强度呈反比：大气真菌粒数直径中值与日光辐射强度呈正比：随着日光辐射强度的增大，＜３．０μｍ的大气真菌粒子，其浓度减小的速度比＞３．０μｍ的快。     

北京市2005年夏季大气颗粒物污染特征及影响因素

对2005年7～8月北京市不同功能区8个采样点PM10和PM2.5的浓度水平、空间分布、PM10/PM2.5比值进行了分析,并讨论了PM10和PM2.5的日变化特征及影响因素.结果表明,北京市夏季PM10和PM2.5日均浓度为155.37 μg/m3和87.70 μg/m3,分别为国家二级标准和美国PM2.5标准的1.04倍和1.35倍;PM2.5、PM10浓度在不同功能区存在一定差异;PM2.5和PM10的日变化以白天高,夜间低为主,且不同功能区的最高值对应于城市居民活动的不同高峰期;在湿度较高的情况下,PM2.5、PM10与湿度呈一定正相关性,且湿度对PM2.5的影响更大;降水前后PM2.5、PM10浓度变化情况表明降水的主要作用是清除粗粒子,对PM2.5的影响则较小.     

Heavy metals in soils and crops in Southeast Asia

In a reconnaisance soil geochemical and plant survey undertaken to study the heavy metal uptake by major food crops in Malaysia, 241 soils were analysed for cation exchange capacity (CEC), organic carbon (C), pH, electrical conductivity (EC) and available phosphorus (P) using appropriate procedures. These soils were also analysed for arsenic (As), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb) and zinc (Zn) using aqua regia digestion, together with 180 plant samples using nitric acid digestion. Regression analysis between the edible plant part and aqua regia soluble soil As, Cd, Cr, Cu, Hg, Ni, Pb and Zn concentrations sampled throughout Peninsular Malaysia, indicated a positive relationship for Pb in all the plants sampled in the survey (R2 = 0.195, p < 0.001), for Ni in corn (R2 = 0.649, p < 0.005), for Cu in chili (R2 = 0.344, p < 0.010) and for Zn in chili (R2 = 0.501, p < 0.001). Principal component analysis of the soil data suggested that concentrations of Co, Ni, Pb and Zn were strongly correlated with concentrations of Al and Fe, which is suggestive of evidence of background variations due to changes in soil mineralogy. Thus the evidence for widespread contamination of soils by these elements through agricultural activities is not strong. Chromium was correlated with soil pH and EC, Na, S, and Ca while Hg was not correlated with any of these components, suggesting diffuse pollution by aerial deposition. However As, Cd, Cu were strongly associated with organic matter and available and aqua regia soluble soil P, which we attribute to inputs in agricultural fertilisers and soil organic amendments (e.g. manures, composts).