静态雾水采集器性能的评估

文章通过对日本神奈川县丹沢.大山中不同位置安装的静态雾水采集器采集样品的分析结果,分别与动态雾水采集器及同一地点采集的雨水样品的分析结果进行线性相关性的分析后得出:动态雾水采集器的性能虽然好于静态雾水采集器。但是,静态雾水采集器安置的环境如果适当,那么静态雾水采集器所采集的样品能够反映大气环境的状况,并且由于其价格低廉、不耗电特点,是一个很好的大气监测设备。     

西双版纳城、郊雾水化学组成分析

利用 1997年 11月西双版纳城、郊雾的外场试验观测资料 ,从该地区雾水化学组成与其他地区雾水化学组成的比较、雾水化学组成与环境的关系、雾水化学组成的来源、雾水化学成分的浓度与雾的微物理结构的关系等几个方面分析了该地区雾的化学特征 .结果表明 ,西双版纳城郊雾水明显呈碱性 ,F-浓度比我国其他地区高很多 ;由于生态环境的不同 ,西双版纳城郊雾的化学成分浓度有很大差异 ;与历史资料比较 ,西双版纳城区雾水总离子浓度明显增加 ;雾水的化学组成与当地的气溶胶、土壤的化学组成密切相关 ;雾水总离子浓度与雾滴粒径有关 .     

西双版纳城、郊雾水化学组成分析

利用１９９７年１１月西双版纳城、郊雾的外场试验观测资料，从该地区雾水化学组成与其他地区雾水化学组成的比较、雾水化学组成与环境的关系、雾水化学组成的来源、雾水化学成分的浓度与雾的微物理结构的关系等几个方面分析了地区雾的化学特征。结果表明，西双版纳城郊雾水明显呈碱性，Ｆ＾－浓度比我国其他地区高很多；由于生态环境的不同，西双版纳城郊雾的化学成分浓度有很大差异；与历史资料，西双版纳城区雾水总离子浓度明显增     

2006 年南京冬季浓雾雾水的化学组分

利用2006 年12 月24~27 日南京外场观测试验资料和采集到的雾水样品化学分析资料,从雾水的化学组成及同月采集的雨水的比较、雾水离子间的相关性、雾水离子浓度与污染气体的关系等几方面,分析了南京雾水的化学特征.结果表明,南京雾水pH 值介于4.24~7.27,多呈酸性;雾水离子浓度随时间有较大变化,这与雾的宏观和微物理结构有关;雾水中离子浓度与同时期(2006 年12 月上旬)雨水中的离子浓度以及污染气体的浓度变化趋势有一致性.如,雾水SO4₂^-和NO₃^-的浓度在25 日14:30~19:55 有1 个峰值,而污染气体的峰值则相对提前,大约在13:00~14:00,随后气体和离子的浓度都逐渐降低.     

舟山地区雾水酸度及其化学组成

1987年4～5月份在浙江舟山地区考察所获得的31份雾水样品的分析表明,其酸度与以前报道的雾水酸度相比较,显示很低的酸含量。海洋雾水中各成分的钠比值,与内陆雾水是很不相同的。故雾水成份的钠比值,可作为判别雾的性质和成因的参考依据。根据雾水样品所测得的主要离子组成和浓度,作了样品pH值的估计,并与实测值作了比较。     

南京2013年冬季三级分粒径雾水化学特征

为研究南京冬季不同粒径雾滴的化学成分的特征,利用three-stage CASCC主动式分档雾水采集器,于2013年12月7日~12月9日南京郊区发生浓雾期间,分时段采集三级分档雾水样本,分档粒径为4~16μm(三级)、16~22μm(二级)、>22μm(一级),共计23个分档雾水样本;用瑞士万通850professional IC型色谱仪器测定水溶性阴、阳离子浓度,分析探讨了三级分粒径雾水中阴、阳离子组分的分布特征,不同粒径雾滴中阴、阳离子浓度的相关性,雾水离子浓度与污染气体以及微物理之间的关系.结果表明,南京雾水的pH值多呈酸性,雾水中的各离子成分分布都与雾滴的大小存在着尺度依赖性关系,小雾滴与大雾滴相比,小雾滴中主要离子成分浓度(NH4+,NO3-,SO42-)高、pH值小且电导率(EC)值高.同时南京雾水中的各离子浓度呈现出夜间高白天低.统计分析显示,南京雾过程中雾水组分的变化,主要源于污染源的贡献差异.结合雾滴谱和污染气体资料分析得出,雾水化学组成的变化与微物理特征以及空气中污染气体有关.     

闽南地区酸性雾水特征初探

1993年3～4月,在闽南地区进行了一次综合性酸雨集中观测,探讨其雾水特征如下:闽南地区雾水已严重酸化,其最低pH值达到2.91,是该地区酸性湿沉降的重要组成部分;雾水中有机酸根的贡献占总阴离子量9%;雾水含较多四价硫,并与甲醛反应形成络合物;雾水受到周围海洋的影响,Cl-有严重的亏损      

2009年夏季黄山云雾水化学特征及来源分析

利用09年夏季在黄山光明顶气象站采集的25个云雾水样本及气象站常规资料,分析了云雾过程雾水的化学特征、污染来源与微物理特性.结果表明,观测期间云雾水呈弱酸性,平均值pH值为6.4,主要的离子浓度由大到小排列为:SO42->NH4+>Ca2+>NO3->Na+>Cl-,表明二次污染物对黄山云雾水的贡献较大.统计分析显示,各云雾过程中雾水组分变化,主要缘于不同云雾过程中污染源与海洋源的贡献率不同.结合后向轨迹进一步分析显示,影响气团主要来源于海洋和周边地区,不同气团影响下雾水离子组分及云雾微物理特征差别明显.     

南京冬季雾水金属元素及水溶性阴离子浓度特征

2007-11-15～2007-12-31期间在南京北郊南京信息工程大学设立采样点,对出现的6次浓雾过程进行了分时段雾水样品采集,并使用ICS-2000离子色谱仪和IRISIntrepidⅡ等离子体发射光谱仪测定了雾水中5种水溶性阴离子和14种金属元素浓度.结果表明,南京6次浓雾过程雾水pH值在4.64～6.88之间;;水溶性阴离子平均浓度以SO24-最高(2864.9μmol·L-1),其次是Cl-(1584.4μmol·L-1)和NO3-(736·0μmol·L-1);;含量较高的金属元素有Ca、K、Na、Mg、Al和Zn;;雾水重金属元素Cu、Ni、Pb、Cd和Cr的平均浓度分别为2.30、1.46、0.42、0·41和0.37μmo·lL-1;;雾水金属元素浓度在雾的初始时段表现较高,随着雾的持续发展出现不同程度降低,但日出后的上班早高峰时段又出现很明显的升高;;雾水NO2-浓度值表现为夜间浓度较高而日出后浓度很低或消失,夜、昼变化非常大;;通过对比雾水和雨水pH平均值发现,雾水pH平均值是6.20,雨水pH平均值为4.91,小于酸雨指标值5.6,酸度较强;;雾水电导率是雨水的10.5倍,雾水的重金属...     

泰山云雾水中多环芳烃的特征与来源分析

于2008年10月18日~11月26日在泰山采集云雾水样品,分析了泰山云雾水中PAHs的含量特征及其与气象条件和pH值、电导的相互关系.结果表明,泰山云雾水中菲含量最多,芴和苊的含量次之;云雾水样品中PAHs浓度与气温有很好的相关性.应用特征分子比值法和因子分析法对云雾水中PAHs的来源进行解析,得出泰山云雾水中PAHs的主要来源为煤炭燃烧源,石油源的贡献相对较小.     

重庆雾水对体外肺泡巨噬细胞酸性磷酸酶活性的影响

本文采集了重庆市三个污染轻重不同地区的雾水,并探讨了它们对体外PAM胞内ACP活性的影响。结果显示:污染严重的雾水对ACP活性呈现早期短暂抑制,中期明显激活,后期缓慢下降的峰形改变,在酶活性上升同时伴随酶染色区域在细胞内的扩散;污染轻的雾水仅有早期抑制作用而无刺激酶活性升高的表现。     

重庆雾的酸化机理及物态的特征

本文对重庆雾滴谱及含水量进行了对比分析.重庆大气污染严重,使雾的物化性质有雾滴平均直径下降、数密度增加、含水量偏低的特点.文中用主成分分析、相关分析及相图等方法对雾水酸度来源、形成机理进行了探讨.     

A preliminary study on the characteristics of fogwater in the masson pine forest in Chongqing, China

The masson pine (Pinns massoniana Lamb.) forest of 2000 ha situated on Nanshan, the south bank of the Yangtze River near Chongqing, China. From 1982, some trees began to die. Since then, half of the trees have died and the whole forest is in danger. Prom November 1986 to January 1987, a study dealt with the characteristics of fogwater in that area was carried out, in order to explain the relationship between acid fog and masson pine decline. The results of our study showed that the acid fog might be responsible in part for the decline of the masson pine forest.     

Fogwater chemistry at Riverside,California

Fog, aerosol, and gas samples were collected during the winter of 1986 at Riverside, California. The dominant components of the aerosol were NH₄⁺, NO₃⁻, and SO₄₂₋. Gaseous NH₃ was frequently present at levels equal to or exceeding the aerosol NH₄⁺. Maximum level were 3800, 3100, 690 and 4540 neq m⁻³ for NH₄⁺, NO₃²⁻ and NH_3(g), respectively. The fogwater collected at Riverside had very high concentrations, particularly of the major aerosol components. Maximum concentrations were 26,000 29,000 and 6200 μM for NH₄⁺, NO₃⁻ and SO₄²⁻, respectively. pH values in fogwater ranged from 2.3 to 5.7. Formate and acetate concentrations as high as 1500 and 580 μM, respectively, were measured. The maximum CH₂O concentration was 380 μM. Glyoxal and methylglyoxal were found in all the samples; their maximum concentrations were 280 and 120 μM, respectively. Comparison of fogwater and aerosol concentrations indicates that scavenging of precursor aerosol by fog droplets under the conditions at Riverside is less than 100% efficient.The chemistry at Riverside is controlled by the balance between HNO₃ production from NO_x emitted throughout the Los Angeles basin and NH₃ emitted from dairy cattle feedlots just west of Riverside. The balance is controlled by local mixing. Acid fogs result at Riverside when drainage flows from the surrounding mountains isolate the site from the NH₃ source. Continued formation of HNO_3(g) in this air mass eventually depletes the residual NH_3(g). A simple box model that includes deposition, fog scavenging, and dilution is used to assess the effect of curtailing the dairy cattle feedlot operations. The calculations suggest that the resulting reduction of NH₃ levels would decrease the total NO₃⁻ in the atmosphere, but nearly all remaining NO₃⁻ would exist as HNO₃. Fogwater in the basin would be uniformly acidic.     

Multiphase chemistry in a microphysical radiation fog model—A numerical study

A microphysical radiation fog model is coupled with a detailed chemistry module to simulate chemical reactions in the gas phase and in fog water during a radiation fog event. In the chemical part of the model the microphysical particle spectrum is subdivided into three size classes corresponding to non-activated aerosol particles, small and large fog droplets. Chemical reactions in the liquid phase are separately calculated in the small and in the large droplet size class. The impact of the chemical constitution of activated aerosols on fogwater chemistry is considered in the model simulations. The mass transfer of chemical species between the gas phase and the two liquid phases is treated in detail by solving the corresponding coupled differential equation system. The model also accounts for concentration changes of gas-phase and aqueous-phase chemical species which are induced by turbulence, gravitational settling and by evaporation/condensation processes.Numerical results demonstrate that fogwater chemistry is strongly controlled by dynamic processes, i.e. the vertical growth of the fog, turbulent mixing processes and the gravitational settling of the particles. The concentrations of aqueous-phase chemical species are different in the two droplet size classes. Reactands with lower water solubility are mainly found in the large droplet size class because the characteristic time for their mass transfer from the gas phase into the liquid phase is essentially longer than the characteristic time for the formation of large fog droplets. Species with high water solubility are rapidly transferred into the small fog droplets and are then washed out by wet deposition before these particles grow further to form large droplets. Thus, the concentrations of the major ions (NO₃⁻, NH₄⁺) are much higher in small than in large droplets, yielding distinctly lower pH values of the small particles. In the present study the reaction of sulfur with H₂O₂ and the Fe(III)-catalysed autoxidation of S(IV) are the major S(VI) producing mechanisms in fog water. Most of the time the sulfur oxidation rates are higher in the large than in the small droplets. Fogwater deposition by gravitational settling occurs mainly in the large droplet size class. However, since in the small droplets the concentrations of chemical species with very good water solubility are relatively high, in both droplet size classes the total wet deposition of these reactands is of the same order of magnitude.     

Evolution of chemical composition of fogwater in winter in Chengdu, China

Two sampling sites representing the urban and suburban area of Chengdu, China were sampled and analyzed for selected chemicals to characterize the evolution of the chemical composition of fogwater. A trend of total organic carbon (TOC) > total nitrogen (TN) > total inorganic carbon (TIC) was observed for both sites. Variation of inorganic ions indicated that inorganic pollutants were not accumulated in the fog. Concentrations of n-alkanes (C11-C37) at the urban site ranged from 7.58 to 27.75 ng/mL while at the suburban site concentrations were 2.57-21.55 ng/mL. The highest concentration of n-alkanes was observed in the mature period of fog (393.12 ng/mL) which was more than ten times that in the fog formation period (27.83 ng/mL) and the fog dissipation period (14.87 ng/mL). Concentrations of Σ15PAHs were in the range of 7.27-38.52 ng/mL at the urban site and 2.59-22.69 ng/mL at the suburban site. Contents of PAHs in the mature period of fog (27.15 ng/mL) > fog dissipation period (11.59 ng/mL) > fog formation period (6.42 ng/mL). Concentrations of dicarboxylic acids (C5-C9) ranged from 10.92 to 40.78 ng/mL, with glutaric acid (C5) as the dominant dicarboxylic acid. These data provide strong indications of the accumulation of certain organic chemicals of environmental concern in fog and fog water, and provide additional insights about processes in urban and suburban air acting on organic chemicals with similar physical chemical properties.     

Interactions of aerosols (ammonium sulfate,ammonium nitrate and ammonium chloride) and of gases (HCl,HNO3) with fogwater

The concentrations of aerosols (NH₄NO₃, (NH₄)₂SO₄ and NH₄Cl) and of gases (HCl_(g), HNO_3(g), NH_3(g) were determined by denuder methods under different conditions (in the absence of fog, before, during and after fog events). At this site situated in an urban region, high concentrations of the gaseous strong acids HCl_(g) and HNO_3(g) are observed. NH₄Cl and NH₄NO₃ aerosols represent a major fraction of the Cl⁻ and NO₃⁻ aerosols (<2.4 μm)collected by denuders. During a fog event, very high concentrations of SO₄²⁻ were found in small aerosols, which are attributed to the aqueous phase oxidation of SO₂ under the influence of high pH due to the presence of NH₃. Differences in SO₄²⁻ concentrations measured in aerosols (<2.4 μm) and in fog droplets were probably due to mass-transport limitations of the SO₂ oxidation. Ammonium sulfate aerosols represent in some cases a significant fraction of the total S present (SO_2(g) + SO₄²⁻. Soluble aerosols and gases contribute to the composition of fogwater and are released again after fog dissipation.     

The role of copper and oxalate in the redox cycling of iron in atmospheric waters

During daytime, the redox cycling of dissolved iron compounds in atmospheric waters, and the related in-cloud transformations of photooxidants, are affected by reactions of Fe and Cu with hydroperoxy (HO₂) and superoxide (O₂⁻) radicals and the photoreduction of Fe(III)-oxalato complexes. We have investigated several of the important chemical reactions in this redox cycle, through laboratory simulation of the system, using γ-radiation to produce HO₂/O₂⁻. At concentrations comparable to those measured in atmospheric waters, the redox cycling of Fe was dramatically affected by the presence of oxalate and trace concentrations of Cu. At concentrations more than a hundred times lower than Fe, Cu consumed most of the HO₂/O₂⁻, and cycled between the Cu(II) and Cu(I) forms. Cu⁺ reacted with FeOH²⁺ to produce Fe(II) and Cu(II), with a second order rate constant of approximately 3 × 10⁷ M⁻¹s⁻¹. The presence of oxalate resulted in the formation of Fe(III)-oxalato complexes that were essentially unreactive with HO₂/O₂⁻. Only at high oxalate concentrations was the Fe(II)C₂O₄ complex also formed, and it reacted relatively rapidly with hydrogen peroxide (k = (3.1 ± 0.6) × 10⁴ M⁻¹s⁻¹). Simulations incorporating measurements for other redox mechanisms, including oxidation by ozone, indicate that, during daytime, Fe should be found mostly in the ferrous oxidation state, and that reactions of FeOH²⁺ with Cu(I) and HO₂/O₂⁻, and to a lesser degree, the photolysis of Fe(III)-oxalato complexes, are important mechanisms of Fe reduction in atmospheric waters. The catalytic effect of Cu(II)/Cu(I) and Fe(III)/Fe(II) should also significantly increase the sink function of the atmospheric liquid phase for HO₂ present in a cloud. A simple kinetic model for the reactions of Fe, Cu and HO₂/O₂⁻, accurately predicted the changes in Fe oxidation states that occurred when authentic fogwater samples were exposed to HO₂/O₂⁻.     

A regional environmental management information system for Chinese EPA—the system analysis and design

REMIS is one of key research projects sponsored by the central government. It is recommended to regional EPAs as a main tool of the environmental management. REMIS simulates the functions of the regional EPAs and aimed to improve their management level. The national environmental management information system will base on REMIS.Functional analysis is the kernel of the REMIS system analysis. Data and data flow analysis are used to support the functional analysis.Investigations on the functions of the local EPAs of eight provinces and 12 cities have been taken. The functions were carefully sorted. Modular design method was used in system analysis and system design.The system analysis included functional analysis, data analysis and data flow analysis. The system design is based on the system analysis. HIPO diagram of each modular, data base structure, menu design, selection of hardware and software environment were the main items of the system design.     

机助地图叠置分析及其在自然资源研究中的应用

机助地图叠置分析包括多边形叠置分析和网格叠置分析两种方法。本文论述了多边形叠置分析的原理和方法,以及多边形叠置分析软件设计的基本思想,探讨了机助地图叠置分析在自然资源研究中的应用领域,并以实例说明了机助地图叠置分析应用于实践的方法和过程。机助地图叠置分析可应用于自然资源数据的统计计算、自然资源的分类和评价,以及动态、变化分析等方面。它对于自然资源尤其是农业自然资源的研究有着一定的意义。