基于单颗粒气溶胶质谱仪的香河采暖季前后含铅颗粒物的组成特征研究

为了研究粒径在0.2?—?2.0μm的含铅颗粒物的化学组分和粒径分布特征,运用单颗粒气溶胶质谱仪(SPAMS)于2017年10月至2018年1月在河北省香河县开展观测活动.通过自适应神经网络算法(ART-2a)对含铅颗粒物进行命名、合并后,主要分为六类:富钾(Pb-K)、元素碳(Pb-EC)、有机碳元素碳(Pb-OCE...     

北京地区气溶胶水溶性组分粒径分布特征

2016~2017年,分别在夏季和冬季在北京城区利用微孔均匀分级采样器(MOUDI-122),采集环境气溶胶,并对其中水溶性离子和水溶性有机物开展了定量分析,对主要水溶性组分质量浓度粒径分布特征,以及季节和不同污染状态下的差异进行了讨论。结果表明,NH4+、NO3-、SO42-、K+和冬季Cl-主要分布在积聚模态,Mg2+和Ca2+主要分布在粗粒子模态,NH4+、NO3-、SO42-在积聚模态的质量浓度最高,二次离子仍是北京地区PM2.5污染的主要组分。SO42-在夏季浓度较高,而NO3-、K+、Cl-在冬季明显高于夏季,Mg2+和Ca2+来源较为独立,与气溶胶其他主要组分的相关性较低。夏季NO3-和SO42-浓度昼夜差异显著,白天SO42-浓度水平明显高于夜晚,夜晚NO3-浓度明显高于白天,且主要表现在积聚模态。污染状况下,二次离子在积聚模态和粗模态浓度增加明显,但在爱根模态中浓度降低。冬季随着污染加重,二次离子液滴模态质量中值粒径明显增大。夏季积聚模态WSOC浓度粒径分布峰值粒径明显大于冬季,0.056~0.32μm粒径段WSOC在不同污染状态下浓度水平基本一致,在0.32μm以上区间,污染状态下WSOC平均浓度明显高于清洁时段。     

长江中下游铜铁多金属矿床铅同位素特征

本文通过对长江中下游地区侵入岩长石铅、矿石硫化物铅同位素组成对比研究。说明长江中下游铜铁多金属成矿带可划分为东区（宁芜以东宁镇和苏锡地区）和西区（宁芜及其以西至鄂东南地区）．东、西两区的侵入岩长石铅和矿石硫化物铅同位素组成具有明显差异，在207Pb／204Pb-206Pb／204Pb图上它们的投影点明显地分为两个分布区。据铅同位素资料计算，长江中下游地壳形成时间主要是26－38亿年；据亮幔混合铅模式计算的μMix值表明，本区侵入岩和接确交代型矿石铅为壳幔混合源，以地幔源为主，前者幔源铅约占63-74％．后者幔源铅约占51－74％，层状含铜黄铁矿型矿体矿石铅主要来自上地壳。     

亚硝化颗粒污泥中EPS提取方法与组成特性的比较研究

以异养型好氧颗粒污泥(AGS)、普通活性污泥(AS)和厌氧颗粒污泥(An GS)为参照,考察了5种方法对亚硝化颗粒污泥(GNS)中胞外聚合物(EPS)的提取效果,以选出最佳方法,并通过测定蛋白质(PN)/多糖(PS)含量、三维荧光(3D-EEMs)与傅里叶红外(FT-IR)图谱,比较分析了GNS中EPS的组成特性.结果表明,甲醛-Na OH法能在有效保护细胞结构的同时,获得较高的EPS提取效率,而耗时更短的甲醛-热碱法对GNS也同样适用.尽管亚硝化颗粒污泥的EPS总量低于其他污泥样品,但高比例的PS成分有利于自养型微生物的固着生长.从可溶性微生物代谢产物(λEx/λEm=250~310 nm/320~380 nm)和芳香类蛋白质(λEx/λEm=200~250 nm/280~380 nm)所对应的荧光峰强度及红外图谱可知,GNS具有比AS更高的微生物活性和更丰富的结构性蛋白,且EPS组成更为简单.     

浙江沿海无居民海岛植物群落物种组成及多样性

无居民海岛是自然资源的宝库,人类活动对无居民海岛的影响日益剧烈,掌握它们的植物群落物种组成和多样性现状有利于进行海岛植被多样性的监测和保护。本文运用植物群落生态学方法,对浙江沿海5个无居民海岛的植被物种组成及多样性进行了研究。结果如下:(1)调查区域共记录到高等植物77科,166属,226种,其中草本151种,木本植物75种。基于双向指示种分析方法(TWINSPAN)分析,将该区域植物群落分为17个类型。(2)17个群落的物种Shannon指数均在1.91?—?2.60,Pielou指数(均匀度指数)值在0.80附近浮动,Margalef指数(丰富度指数)在1.86?—?3.80,各个群落的丰富度指数与多样性指数变化趋势大体一致,与群落均匀度无明显关系。植物区系成分多样,主要为泛热带成分和北温带成分。本研究可为我国沿海无居民海岛的资源保护及其开发利用提供科学数据。     

Size and elemental composition of dry-deposited particles during a severe dust storm at a coastal site of Eastern China

Dry-deposited particles were collected during the passage of an extremely strong dust storm in March, 2010 at a coastal site in Qingdao(36.15°N, 120.49°E), a city located in Eastern China. The size, morphology, and elemental composition of the particles were quantified with a scanning electron microscope equipped with an energy dispersive X-ray instrument(SEM–EDX). The particles appeared in various shapes, and their size mainly varied from 0.4to 10 μm, with the mean diameters of 0.5, 1.5, and 1.0 μm before, during, and after the dust storm, respectively. The critical size of the mineral particles settling on the surface in the current case was about 0.3–0.4 μm before the dust storm and about 0.5–0.7 μm during the dust storm. Particles that appeared in high concentration but were smaller than the critical size deposited onto the surface at a small number flux. The elements Al, Si and Mg were frequently detected in all samples, indicating the dominance of mineral particles. The frequency of Al in particles collected before the dust storm was significantly lower than for those collected during and after the dust storm. The frequencies of Cl and Fe did not show obvious changes, while those of S, K and Ca decreased after the dust arrival. These results indicate that the dust particles deposited onto the surface were less influenced by anthropogenic pollutants in terms of particle number.     

Sources and characteristics of fine particles over the Yellow Sea and Bohai Sea using online single particle aerosol mass spectrometer

Marine aerosols over the East China Seas are heavily polluted by continental sources. During the Chinese Comprehensive Ocean Experiment in November 2012, size and mass spectra of individual atmospheric particles in the size range from 0.2 to 2.0 μm were measured on board by a single particle aerosol mass spectrometer(SPAMS). The average hourly particle number(PN)was around 4560 ± 3240 in the South Yellow Sea(SYS), 2900 ± 3970 in the North Yellow Sea(NYS), and 1700 ± 2220 in the Bohai Sea(BS). PN in NYS and BS varied greatly over 3 orders of magnitude, while that in SYS varied slightly. The size distributions were fitted with two log-normal modes. Accumulation mode dominated in NYS and BS, especially during episodic periods. Coarse mode particles played an important role in SYS. Particles were classified using an adaptive resonance theory based neural network algorithm(ART-2a). Six particle types were identified with secondary-containing, aged sea-salt, soot-like, biomass burning, fresh sea-salt,and lead-containing particles accounting for 32%, 21%, 18%, 16%, 4%, and 3% of total PN,respectively. Aerosols in BS were relatively enriched in particles from anthropogenic sources compared to SYS, probably due to emissions from more developed upwind regions and indicating stronger influence of continental outflow on marine environment. Variation of source types depended mainly on origins of transported air masses. This study examined rapid changes in PN, size distribution and source types of fine particles in marine atmospheres. It also demonstrated the effectiveness of high-time-resolution source apportionment by ART-2a.     

石笋有机质碳同位素组成研究的进展与挑战

洞穴石笋因其精准的定年和蕴含的多种代用指标,已成为古气候和古环境变化研究的重要载体之一。在石笋研究的多种代用指标中,碳酸盐碳同位素由于受到多重因素的影响,应用其重建过去环境变化历史一直局限在少数几个研究地点。洞穴上覆土壤有机质是洞穴石笋中有机质的重要来源,除此之外,洞穴原位产生的微生物及基岩中的有机质也有贡献。由于主要继承了地表植被和土壤有机质的同位素组成,石笋有机质碳同位素组成的时间序列能够很好地指示地表植被的演变及土壤过程的变化。本文对石笋有机质碳同位素组成的研究现状进行了综述,介绍了最新建立的石笋有机质碳同位素组成分析方法,并指出应用这一指标研究环境变化需要解决的关键问题和未来面临的挑战。     

2021年青岛市一次PM_(2.5)和沙尘混合空气污染过程分析

以2021年3月青岛市空气自动站监测数据为依据,借助环境气象激光雷达、气溶胶激光雷达、在线离子色谱仪等技术手段,并利用后向轨迹模式(HYSPLIT)对青岛市一次PM_(2.5)和沙尘混合空气污染过程、气象条件、颗粒物组成以及传输路径等进行了综合分析。结果表明:静小风、湿度大、垂直方向逆温以及高空多次向近地面的污染物输送是第1阶段PM_(2.5)污染的主要原因,NO^(-)_(3)、SO^(2-)_(4)、NH^(+)_(4)浓度分别占水溶性离子浓度总和的51.7%,24.8%,22.4%,三者之和占ρ(PM_(2.5))的52.3%,机动车源、工业源和燃烧源贡献较大,其中尤以机动车源影响最显著;第2阶段各子站颗粒物浓度变化呈现明显的传输特征,PM_(2.5)中Ca^(2+)浓度升至第1阶段的6倍,沙尘源影响显著,污染气团主要来自蒙古国和我国内蒙古,前期由西北地区直接到达青岛,后期是经渤海湾、烟台到达青岛东南海域,最后回流至青岛;冷高压强度较弱导致近地面水平扩散条件不利,ρ(PM_(10))长时间维持在较高水平。     

广州市灰霾期PM10的化学组成对能见度的影响

采集广州市大气可吸入颗粒物(PM10)样品,并分别对冬、夏两季灰霾和非灰霾期PM10中有机碳(OC)、元素碳(EC)和水溶性离子进行分析。广州市灰霾期大气PM10中的主要化学成分按质量浓度大小排序为OC>NO3->SO24->NH4+>EC(非灰霾期则依次为OC>SO24->EC>NH4+>NO3-),其质量浓度分别为非灰霾期的4.7、12.5、3.7、3.2和2.3倍。相关性分析表明,灰霾期总碳[TC(OC+EC)]及NO3-的质量浓度对大气能见度的降低起主要作用,而非灰霾期则主要是TC和SO24-。