Seasonal variation and size distribution of biogenic secondary organic aerosols at urban and continental background sites of China

Size-resolved biogenic secondary organic aerosols(BSOA) derived from isoprene and monoterpene photooxidation in Qinghai Lake, Tibetan Plateau(a continental background site) and five cities of China were measured using gas chromatography/mass spectrometry(GC/MS). Concentrations of the determined BSOA are higher in the cities than in the background and are also higher in summer than in winter. Moreover, strong positive correlations(R2= 0.44–0.90) between BSOA and sulfate were found at the six sites,suggesting that anthropogenic pollution(i.e., sulfate) could enhance SOA formation,because sulfate provides a surface favorable for acid-catalyzed formation of BSOA. Size distribution measurements showed that most of the determined SOA tracers are enriched in the fine mode( 3.3 μm) except for cis-pinic and cis-pinonic acids, both presented a comparable mass in the fine and coarse( 3.3 μm) modes, respectively. Mass ratio of oxidation products derived from isoprene to those from monoterpene in the five urban regions during summer are much less than those in Qinghai Lake region. In addition, in the five urban regions relative abundances of monoterpene oxidation products to SOA are much higher than those of isoprene. Such phenomena suggest that BSOA derived from monoterpenes are more abundant than those from isoprene in Chinese urban areas.     

运用生物循环理论建立多元生物污水处理新工艺

以活性污泥法为主流工艺的现代污水处理技术,存在着工程投资大，运行费用高，管理复杂等缺点，按照生物循环基本理论要示是不完善的。多元生物污水处理是按照食物链代谢规律,运有生物循环理论，设计成微生物－植物－水生动物3个处理单元。污水中的有机物作为微生物人良料在第1单元被套氧微生物消化降解成CO2，H2O，NH^ 4,CH^-4等，除CH4作为生物能源可回收利用外，其它物质是植物的营养物质，在第2单元藻类等多种植物吸收，通过光合作用合成植物细胞，并释放氧气，在第1单元和第2单元增殖的细胞和藻类成为水生动物的食料，在第3单元被浮游动物和鱼类捕食，转化成动物蛋白，污水中的有机物在3个单元组成的生态净化系统中，被多样生物逐级利用，最终转化成植物细胞和动物蛋白，使污水得到净化，达到三级处理水平，不产生二次污 ，是一种安全的，对环境友好的污水处理新技术，在国外被誉为21世纪的新科技。该污水净化系统，按照生物循环基本理论进行工艺设计，通过生态平衡自我调控，具有工艺流程简单，投资省，运行费用低，管理简便等优点，适合我国国情，有广阔的应用前景，尤其适有于小城镇污水处理。     

新疆老山口金矿岩浆隐爆角砾岩地质地球化学

新疆东准噶尔老山口金矿区发育有与金矿化密切有关的次火山闪长玢岩及与之密切伴生的闪长玢岩质隐爆角砾岩和闪斜煌斑岩质隐爆角砾岩 ,它们是在陆相火山作用下由同源岩浆分异演化而形成的产物。角砾岩具有浅成—超浅成环境及热塑、高压释放状态下的成岩特征。角砾岩的角砾、胶结物和次火山岩三者的岩石类型、岩相学特征和地球化学特征基本一致 ,具有稀土总量较低 ,轻稀土相对富集 ,重稀土相对亏损 ,铕异常不明显 ,大离子亲石元素相对富集 ,高场强元素相对亏损等特征。结合其构造背景、地质产状、岩石学和地球化学特征分析 ,这套岩石来源于受俯冲洋壳释放富含大离子亲石元素或强不相容元素流体交代过的亏损地幔楔。     

On the effect of Fe(III) on proliferation of Microcystis aeruginosa at high nitrate and low chlorophyll condition

The impact of Fe concentrations on the growth of Microcystisaeruginosa in aquatic systems under high nitrate and low chlorophyll conditions was studied. The responses of cell density, total and cell chlorophyll-a intracellular Fe content and organic elemental composition of M. aeruginosa to different concentration gradients of Fe(III) in the solutions were analysed. The results showed that the proliferation speeds of M. aeruginosa were: (1) decelerated when the Fe(III) concentration was lower than 50 μg/L in the solutions, (2) promoted and positively related to the increase of Fe(III) concentration from 100 to 500 μg/L in the solutions over the experimental period, and (3) promoted in the early stage but decelerated in later stages by excess adsorption of Fe by cells when the Fe(III) concentration was higher than 500 μg/L in the solutions. The maximum cell density, total and cell chlorophyll-a were all observed at 500 μg Fe(III)/L concentration. The organic elemental composition of M. aeruginosa was also affected by the concentration of Fe(III) in the solutions, and the molecular formula of M. aeruginosa should be expressed as C_7–7.5H₁₄O_0.8–1.3N_3.5–5 according to the functions for different Fe(III) concentrations. Cell carbon and oxygen content appeared to increase slightly, while cell nitrogen content appeared to decrease as Fe(III) concentrations increased from 100 to 500 μg/L in the solutions. This was attributed to the competition of photosynthesis and nitrogen adsorption under varying cell Fe content.     

淮南小学校园不同活动场所灰尘重金属区域分异及生物可给性

利用PBET(Physiologically Based Extraction Test)体外胃肠模拟方法研究淮南市小学校园不同活动场所灰尘中8种典型重金属(Cd、Co、Cr、Cu、Ni、Pb、V和Zn)在胃肠阶段的生物可给量,并计算其生物可给性,采用US EPA人体健康风险评价方法,评估研究区灰尘重金属经手-口暴露途径摄入对儿童产生的健康风险.结果表明;与淮南市土壤环境背景值相比,淮南市小学校园不同活动场所灰尘重金属总量普遍偏高,累积量较大的是Cd、Zn、Pb和Cu,富集程度较高.对比分析不同活动场所灰尘重金属含量发现,楼道灰尘重金属在3种活动场所中富集程度较高,其中Cd富集水平最高,主要因为楼道灰尘重金属不仅来源于楼道内部金属栏杆扶手生锈老化和防腐防锈油漆使用,同时受到室外污染源的影响.相关分析和主成分分析表明,灰尘重金属主要来自室外交通活动、工业活动、自然源以及室内污染源,Cd主要来自燃煤活动.PBET法提取重金属可给量在胃和小肠阶段差异较大,Cd、Pb、V和Zn在胃阶段生物可给量高于肠阶段.对比不同活动场所灰尘重金属生物可给量发现,在胃肠阶段均表现为楼道灰尘重金属可给量高于操场灰尘和校门口灰尘.健康风险评估表明,Zn在不同活动场所灰尘中重金属日平均暴露量最高,非致癌风险商(HQ)小于1,在安全阈值之内,对儿童不存在非致癌风险.Cd、Co、Cr和Ni的致癌风险商(CR)大小顺序为楼道灰尘操场灰尘校门口灰尘,在人体可承受范围内.楼道灰尘重金属的总非致癌风险指数(HI)最大,达0.118,因暴露时间较长,对儿童的潜在危害不容忽视.     

5—(4—磺酸基苯偶氮)8—(2,4—二硝基苯氨基)喹啉测定食品中铜的研究应用

在弱碱性介质中 ,5— (4—磺酸基苯偶氮 ) 8— (2 ,4—二硝基苯氨基 )喹啉 (SPDNPAQ)与铜反应生成 2∶ 1紫红色络合物 ,体系 λmax=56 0 nm,ε=1.2 3× 10 5L· mol-1· cm-1。铜含量在 0～ 0 .4 mg/ L内符合比耳定律 ,方法用于一些生物样品和水样中铜的测定。     

高铝粉煤灰提取氧化铝后硅钙渣用作水泥混合材

为了使高铝粉煤灰提取氧化铝后所产生的硅钙渣被大量的用作水泥混合材,通过水泥强度、水化放热和干缩性实验研究了原状硅钙渣和脱碱硅钙渣对水泥强度和稳定性的影响。结果表明,当硅钙渣掺量达30%时,硅钙渣水泥强度仍可满足P·C 32.5水泥要求。且随硅钙渣掺入量的增加,水泥早期水化放热速率增加的同时水泥累计水化放热量和干缩率还会显著降低。与原状硅钙渣相比,在同等掺量的情况下,脱碱硅钙渣更有利于保持水泥强度,降低其水化热和改善干缩性。     

响应曲面法优化絮凝处理木薯淀粉废水

采用中心复合实验设计和响应面分析法研究复合絮凝剂聚合氯化铝锌(PAZC)和聚合氯化铝(PAC)混凝处理木薯淀粉废水,进行设计和分析,以溶液pH值和絮凝剂用量为考察因素,分别以COD、浊度去除率为考察指标,选用最佳优化数学模型描述考察指标和考察因素之间的数学关系,并以设定PAZC和PAC对COD去除率(65%),浊度去除率(90%)和SS去除率(90%)的目标值,通过等高线叠加图预测最优实验条件,得到PAZC投量为6.5 mg/L,pH为7.7时,COD去除率和浊度去除率分别达到最大为76.6%和99.9%;PAC投量为19.2 mg/L,pH为7.8时,COD去除率和浊度去除率最大值分别为64.4%和97.1%。经对最优条件进行验证,预测值与验证实验平均值接近。     

燃煤电厂重金属排放与周边土壤重金属污染评价

为研究燃煤电厂重金属排放对周边土壤重金属污染的影响,测定了某燃煤电厂烟囱入口烟气中Cd、Cr、Hg、Ni、Pb、As含量,同时根据当地气象及地形条件,在燃煤电厂周边采集19个土壤样品,分析了土壤中重金属含量及分布情况,并对其污染程度进行评价.结果表明,燃煤电厂烟气中6种重金属元素的质量浓度为0.02～2.00μg/m3...     

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.