The concentrations, distribution and sources of PAHs in agricultural soils and vegetables from Shunde, Guangdong, China

The concentrations, distribution and sources of 16 polycyclic aromatic hydrocarbons (PAHs) were determined in 30 agricultural soil and 16 vegetable samples collected from subtropical Shunde area, an important manufacturing center in China. The total PAHs ranged from 33.7 to 350 μg/kg in soils, and 82 to 1,258 μg/kg in vegetables. The most abundant individual PAHs are phenanthrene, fluoranthene, chrysene, pyrene and benzo(b)fluoranthene for soil samples, and anthracene, naphthalene, phenanthrene, pyrene and chrysene for vegetable samples. Average vegetable–soil ratios of total PAHs were 2.20 for leafy vegetables and 1.27 for fruity vegetables. Total PAHs in vegetable samples are not significantly correlated to those in corresponding soil samples. Principal component analyses were conducted to distinguish samples on basis of their distribution in each town, soil type and vegetable specie. Relatively abundant soil PAHs were found in town Jun’an, Beijiao, Chencun, Lecong and Ronggui, while abundant vegetable PAHs were observed in town Jun’an, Lecong, Xingtan, Daliang and Chenchun. The highest level of total PAHs were found in vegetable soil, followed by pond sediment and “stacked soil” on pond banks. The PAHs contents in leafy vegetables are higher than those in fruity vegetables. Some PAH compound ratios suggest the PAHs derived from incomplete combustion of petroleum, coal and refuse from power generation and ceramic manufacturing, and paint spraying on furniture, as well as sewage irrigation from textile industries. Soil PAHs contents have significant logarithmic correlation with total organic carbon, which demonstrates the importance of soil organic matter as sorbent to prevent losses of PAHs.     

Polycyclic aromatic hydrocarbons and organochlorine pesticides in surface soils from the Qinghai-Tibetan plateau

Eighty eight surface soil samples were collected from the Qinghai-Tibetan Plateau (QTP) for determination of polycyclic aromatic hydrocarbons (PAHs) and organochlorine pesticides (OCPs), including dichlorodiphenyltrichloroethane and metabolites (DDXs) and hexachlorocyclohexane isomers (HCHs). The measured concentrations were 51.8 ± 38.5 ng g(-1), 0.329 ± 0.818 ng g(-1), and 0.467 ± 0.741 ng g(-1) as means and standard deviations of PAHs, DDXs, and HCHs, respectively, which were 1-2 orders of magnitude lower than those reported for eastern China. Significant differences were also revealed among four sub-areas within QTP. PAHs detected in the samples from the remote sub-areas of T'ang-ku-la/Hoh Xil Mountains and along the Qinghai-Tibet highway in the west and northwest of QTP were 1 order of magnitude lower than those from Lhasa and east Qinghai. The differences in soil OCPs among the sub-areas were 2-7 times. Soil PAHs were significantly correlated with emission density and soil organic carbon content (SOC), while OCPs were correlated significantly with the population density and SOC. Based on the calculated backward air mass trajectories and geographical distributions of emission and population, it was revealed that PAHs and OCPs accumulated in the soils in the west and northwest QTP were primarily from long-range transport and may represent the background levels of East Asia. This part of QTP can also serve as an important receptor area for regional or even global long-range transport study. The elevated concentrations of PAHs and OCPs in Lhasa and east Qinghai were mainly from local sources, while PAHs from adjacent Lanzhou area also contributed considerably to the accumulation of PAHs in east Qinghai.     

沙尘天气强度特征指数研究——以北京地区为例

利用1970—2000年北京及其周边地区以及影响北京沙尘天气的上风向共14个基准气象站的沙尘天气与相关气象因子资料,分析了沙尘天气与各因子之间的相关性。研究发现,风速、相对湿度与沙尘天气的相关关系最显著;同时,对能见度与沙尘浓度观测值的分析得出,二者存在非线性关系。在上述分析的基础上,用能见度、风速、相对湿度构建了沙尘强度特征指数,该指数与这3个因子均呈非线性关系,指数值越大表示沙尘天气强度越大,反之,指数值越小表示沙尘天气强度越小。经验说明,沙尘强度特征指数与相应沙尘浓度观测值有着较一致的变化趋势,该指数从气象和环境两个方面反映了沙尘天气的强度特征。     

高海拔排土场边坡安全稳定性的PS⁃InSAR监测

为了解决高海拔排土场边坡灾害监测难度大以及安全稳定性预警等问题,提出利用 PS-InSAR 技术对高海拔排土场边坡进行安全稳定性监测分析。通过对西藏山南桑日县某排土场边坡进行监测分析研究,采用 2018 年 11 月 04 日至 2020 年 12 月 23 日的 25 景 Sentinel-1A 数据,利用时序差分干涉相位的时空分析方法,进行差分干涉、模型迭代计算和地理编码等解算,解算得到平均形变速率分布,基于平均形变速率结果分析该排土场边坡的安全稳定性。结果表明：利用 PS-InSAR 技术能够获取排土场边坡区域的地表形变信息;该研究区域坡体 2018 年 11 月至 2020 年 12 月的平均形变速率最大值为 -20.00 mm/a,最大形变速率区域出现在排土场边坡的下部 ;通过 PS-InSAR 技术能够对其安全稳定状态进行准确评价,并进行预警预报,为排土场边坡的安全稳定服役提供有效技术保证。     

近场地震作用下库区深水钢筋混凝土高墩地震易损性分析∗

为研究近场地震作用下库区深水钢筋混凝土高墩的概率损伤特性,以90 m高的矩形空心薄壁钢筋混凝土深水高墩为研究对象,综合考虑桥墩设计参数和近场地震动的随机性,基于OpenSees软件建立深水高墩有限元模型,开展不同水深的7种工况(水深:0、15、30、45、60、75、90 m)下,顺桥向和横桥向近场地震激励的增量动力非线性分析。以截面临界曲率值为损伤指标,研究深水高墩的易损性。结果表明:各工况下,轻微损伤、中等损伤和严重损伤阶段的损伤概率均随地震波峰值加速度的增加而增大,并且当峰值加速度达到1.0g时损伤概率达到最大,而完全损伤阶段的损伤概率则在峰值加速度为0.5g时出现峰值点;近场地震顺桥向激励时,墩身中上部和墩底区域均较容易损伤,而横桥向激励时仅墩底区域较容易损伤;当水深超过45 m后,高墩最大损伤概率变化不大且截面曲率概率需求基本一致,45 m水深为深水高墩显著水深。因此,应重点分析水深达到高墩高度一半时深水高墩的损伤情况。     

CAS工艺与AOE工艺曝气池水质信息场的测量与分析

为了研究曝气池空间内水质的分布及变化规律,采用了YSI6600 V2多参数水质检测仪对成都市三瓦窑污水处理厂的一期工程传统污泥法(CAS)、二期工程缺氧、好氧和内源呼吸(AOE)工艺中的曝气池分别进行了包括DO、NH3-N、NO3--N、pH、氯化物和温度等水质指标的场的检测,通过分析这些数据,揭示了曝气池内部水质变化的规律,并比较了CAS工艺与AOE工艺内水质处理效果的差别。结果表明,(1)溶解氧沿池深方向呈现出一定的分布规律,CAS工艺中随池深增加,溶解氧增加,AOE工艺中随着池深的增加,溶解氧降低;(2)AOE工艺对氨氮在O区的去除率可达97.64%,明显高于CAS工艺的41.76%;(3)沿曝气池长度测量溶解氧空间分布规律,参照理论曲线及依据水质处理要求,调整曝气量的方法具有长期运行经济、水质处理效果好的特点。     

超声波处理、热处理及酸碱调节对剩余污泥溶解效果的对比研究

以高含磷剩余污泥为对象,采用超声波处理、热处理和酸碱调节3种减量化技术,研究了细胞物质溶解过程中COD、氮、磷的释放规律.结果表明,在超声最大时间为1.0 h、声能密度为0.167～0.500 W/mL的实验条件下,超声波处理中污泥减量和细胞物质的释放效果随超声时间延长而提高,声能密度对释放效果的影响较小;在热处理中,污泥减量和细胞物质的释放效果随热处理温度的升高和热处理时间的延长而提高,但热处理温度的贡献大于热处理时间;在超声波处理和热处理(除热处理温度为50 ℃外)中,污泥上清液TN中均以有机氮为主,NH3-N次之;在酸碱调节处理中,只有在初始pH为12.0时,处理4.0 h后才会有一定的污泥减量和溶解效果,但污泥浓度下降不明显.3种减量化技术中,超声波处理最为经济、有效.     

TiO2光催化处理络合铜废水的实验研究

研究了以悬浮态TiO2为催化剂,在紫外光的作用下对络合铜废水进行光催化反应,分别考察了常温下TiO2投加量、反应时间、废水初始pH值、反应气氛等因素对处理效果的影响,并探讨了反应机理。结果表明:TiO2投加量为2 g/L,废水pH=4,300 W高压汞灯照射下,载入60 mL/min的空气反应40 min,120 mg/L EDTA络合铜废水的Cu(II)与COD的去除率达到最高,分别为96.56%和57.67%。     

人工湿地污水处理工艺及除污机理

对人工湿地污水处理工艺及其对水中污染物的去除机理进行了综述,并对人工湿地处理污水的技术进行了展望。     

利用SPAMS初探盘锦市冬季PM2.5污染特征及来源

利用SPAMS 0515于2015年1月在盘锦市兴隆台空气质量自动监测点位采集PM_(2.5)样品,并分析其污染特征和来源。研究结果表明,盘锦市冬季PM_(2.5)的颗粒类型主要以OC颗粒、富钾颗粒、EC颗粒组成。其中,OC颗粒占比最高,为52.5%;PM_(2.5)污染的主要贡献源为燃煤、生物质燃烧、机动车尾气排放,占比分别为33.2%、25.7%、17.5%,特别是在PM_(2.5)质量浓度较高时段,燃煤和机动车尾气排放对污染的贡献较大。