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Huang H, Wan Y. Formation of an unprecedented yellow snow episode in Xinjiang on December 1, 2018. Heliyon 2023; 9:e18857. [PMID: 37593622 PMCID: PMC10428044 DOI: 10.1016/j.heliyon.2023.e18857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 07/27/2023] [Accepted: 07/31/2023] [Indexed: 08/19/2023] Open
Abstract
On 1 December 2018, a heavy yellow snow fell in Urumqi (87°37'E, 43°47'N) - the largest city of northwest China's Xinjiang province, which was the first case that the yellow snow has been observed in winter. The air parcel trajectories obtained from Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model and the dust surface mass concentration from Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) were adopted to identify the potential sources and transport paths of pollutants responsible for this yellow snow episode. The meteorological situation and the European Center for Medium-Range Weather Forecasts (ECMWF) forecast products have been utilized to analyze the supportive meteorological conditions. The results showed that the heavy snow in Urumqi was contaminated by the yellow dust originated in Karamay of Xinjiang province. The strong surface winds in Karamay lifted large amounts of dust into the atmosphere. Then the airborne dusts were transported to Urumqi rapidly by strong low-level winds, where precipitation in connection with the upper trough and the cold front lead to the yellow snow episode. This study can provide important scientific significance for predicting this kind of event (yellow snow).
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Affiliation(s)
- Haibo Huang
- Meteorological Center of Xinjiang Air Traffic Management Bureau, Urumqi, Xinjiang, China
| | - Yu Wan
- Xinjiang Meteorological Observatory, Urumqi, Xinjiang, China
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Attiya AA, Jones BG. An extensive dust storm impact on air quality on 22 November 2018 in Sydney, Australia, using satellite remote sensing and ground data. ENVIRONMENTAL MONITORING AND ASSESSMENT 2022; 194:432. [PMID: 35568770 PMCID: PMC9107411 DOI: 10.1007/s10661-022-10080-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 04/21/2022] [Indexed: 05/05/2023]
Abstract
Recurrent dust storms represent a significant concern in Australia because of their related hazards and damages since particulate matter (PM) has harmful impacts on the environmental, health and economic sectors. The particulate matter may be released from natural sources and human activities. The major part of natural particulate matter is emitted into the air by wind erosion processes from desert and semi-desert areas at the world scale. A huge dust storm crossed over several areas of New South Wales (NSW), Australia, including the Sydney region on 21-22 November 2018 and decreased the horizontal visibility to less than 1 km for 22 h. This study examined the synoptic weather conditions, and assessed the air quality and identified the source and transport trajectory of the dust storm over Sydney using ground and satellite remote sensing data. PM10 (< 10 μm) concentrations were obtained from selected air quality monitoring sites operated by the Environmental Protection Agency in NSW. The highest hourly concentration of PM10 (578.7 μg/m3) was recorded at Singleton in the Hunter Valley, while concentrations in Sydney ranged from 480 to 385 μg/m3, well above the standard air quality level in Australia (50 μg/m3 per 24 h). The HYSPLIT back trajectories of air parcels suggest that the potential sources of the dust episode originated from the Lake Eyre Basin and northeast South Australia, the Mundi Mundi plains west of Broken Hill, Cobar and the grazing lands and the red sandplains in northwestern NSW. It then travelled towards the east coast. These long-range airflows transported suspended dust particles, raising air quality to hazardous levels (elevated PM10 levels) over most areas of NSW. The results from the HYSPLIT model for dust movement are confirmed by MODIS satellite images. Many areas of NSW experienced this intense dust storm due to northwest wind generated by the low-pressure systems and cold fronts over South Australia and many parts of western NSW as it moved eastward.
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Affiliation(s)
- Ali A Attiya
- Atmospheric Science Department, Science Faculty, Mustansiriyah University, Baghdad, Iraq.
- School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, NSW, 2522, Australia.
| | - Brian G Jones
- School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, NSW, 2522, Australia
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Abstract
Northern China was hit by a severe dust storm on 15 March 2021, covering a large area and bring devastating impact to a degree that was unprecedented in more than a decade. In the study, we carried out a day-and-night continuous monitoring to the path of the moving dust, using multi-spectral data from the Chinese FY-4A satellite combined with the Japanese Himawary-8 from visible to near-infrared, mid-infrared and far-infrared bands. We monitored the whole process of the dust weather from the occurrence, development, transportation and extinction. The HYSPLIT(Hybrid Single Particle Lagrangian Integrated Trajectory) backward tracking results showed the following two main sources of dust affecting Beijing during the north China dust storm: one is from western Mongolia; the other is from arid and semi-arid regions of northwest of China. Along with the dust storm, the upper air mass, mainly from Siberia, brought a significant decrease in temperature. The transport path of the dust shown by the HYSPLIT backward tracking is consistent with that revealed by the satellite monitoring. The dust weather, which originated in western Mongolia, developed into the “3.15 dust storm” in north China, lasting more than 40 h, with a transport distance of 3900 km, and caused severe decline in air quality in northern China, the Korean peninsula and other regions. It is the most severe dust weather in the past 20 years in east Asia.
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SCHWANCK FRANCIÉLE, SIMÕES JEFFERSONC, HANDLEY MICHAEL, MAYEWSKI PAULA, BERNARDO RONALDO. Anthropogenic trace elements (Bi, Cd, Cr, Pb) concentrations in a West Antarctic ice core. AN ACAD BRAS CIENC 2022; 94:e20210351. [DOI: 10.1590/0001-3765202220210351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Accepted: 01/13/2022] [Indexed: 11/22/2022] Open
Affiliation(s)
| | - JEFFERSON C. SIMÕES
- Universidade Federal do Rio Grande do Sul/UFRGS, Brazil; University of Maine, USA
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Kaviani F, Memarian MH, Eslami-Kalantari M. Radioactive impact on Iran and the world from a postulated accident at Bushehr Nuclear Power Plant. PROGRESS IN NUCLEAR ENERGY 2021. [DOI: 10.1016/j.pnucene.2021.103991] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Jafari Hombari F, Pazhoh F. Synoptic analysis of the most durable pollution and clean waves during 2009-2019 in Tehran City (capital of Iran). NATURAL HAZARDS (DORDRECHT, NETHERLANDS) 2021; 110:1247-1272. [PMID: 34429567 PMCID: PMC8377706 DOI: 10.1007/s11069-021-04990-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Accepted: 08/11/2021] [Indexed: 06/13/2023]
Abstract
The present study was done to analyze and compare synoptic conditions during the most durable pollution and clean waves (MDPW and MDCW) in Tehran City (capital of Iran). For this purpose, air quality index (AQI) data were first obtained during 2009-2019 from the Tehran Air Quality Control Company in Tehran Province. Then, a threshold of (AQI ≤ 101) representing a polluted and unhealthy atmosphere was considered as MDPW, and a threshold of (AQI ≤ 50) representing a clean (good) air was selected as MDCW in Tehran City by identifying the polluted days. The results showed the presence of MDPW during 43 polluted days from November 21, 2010 to January 2, 2011. Intensity and frequency of the polluted days during statistical period showed a decreasing trend that coincided with an increasing trend of precipitation. Analysis of synoptic conditions occurred during 43 days of MDPW indicated penetration of Siberian high-pressure from the east at sea level and extension of sub-tropical anticyclone in mid-level from the west that led to development of an anticyclone circulation with descending and converging flow in Iran and surrounding region. As a result, a calm and sustainable climate and stable concentration of pollutants were observed throughout Tehran City. Backward trajectory of sources and entry route of the polluted air to Tehran City during peak days of pollution showed that desert regions of southern Iraq and central Iran along the southern and southwestern parts played a major role in increasing concentration of pollutants during occurrence of durable wave. Different routes were observed in entry of dusty and the polluted air to Tehran City according to hybrid single-particle Lagrangian integrated trajectory (HY SPLIT) model, but in most of peak days, the areas that were near and adjacent to Tehran City with height of less than 1000 m played a greater role in particle transport. Investigation of instability indices during MDPW showed that in most days of pollution, values of instability intensity were classified into weak class and lower troposphere (1000-850 hPa) compared to higher levels, and degree of stability and calmness of the atmosphere was more. So that, the highest frequency of temperature inversions occurred near the earth's surface.
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Affiliation(s)
| | - Farshad Pazhoh
- Department of Physical Geography, Kharazmi University, Tehran, Iran
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Guan Q, Luo H, Pan N, Zhao R, Yang L, Yang Y, Tian J. Contribution of dust in northern China to PM 10 concentrations over the Hexi corridor. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 660:947-958. [PMID: 30743979 DOI: 10.1016/j.scitotenv.2018.12.412] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Revised: 12/25/2018] [Accepted: 12/27/2018] [Indexed: 06/09/2023]
Abstract
Four main dust sources and dust events that affected the Hexi Corridor were defined, and the HYSPLIT model was used to trace the dust that originated during the dust episodes of 2015-2017 and to quantify the contributions of dust sources to PM10. On this basis, an algorithm that quantified the contribution of dust sources to PM10 was proposed in this study. The results showed that the main dust sources affecting the Hexi Corridor are generally located in the northern part of Xinjiang, which is mainly dominated by the Gurbantunggut Desert (source A); the Taklimakan and Kumtag Deserts and their surrounding areas (source B); both Qaidam Basins (source C); and the Badain Jaran Desert, Tengger Desert, Hobq Desert, Ulan Buh Desert, and Mu Us Sandy Land and their surrounding areas (source D). The occurrence time of dust and the frequency of PM10 exceeded the daily concentration standards and showed significant characteristics of being high in the spring and low in the autumn. The higher concentration of PM10 in the winter was mainly due to anthropogenic sources from heating process. The contribution of source area D to PM10 concentration was the greatest (42%). Source area B was one of the main dust sources (with a contribution rate of 23%); however, approximately 63% of the dust in this area originates from the Kumtag Desert. The contribution of source area A is lower than that of the study area due to greater precipitation and higher vegetation coverage (22% contribution rate). Source area C has the lowest contribution to the research area due to obstruction by the Qilian Mountain (13% contribution rate).
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Affiliation(s)
- Qingyu Guan
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China; Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China.
| | - Haiping Luo
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China; Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
| | - Ninghui Pan
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China; Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
| | - Rui Zhao
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China; Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
| | - Liqin Yang
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China; Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
| | - Yanyan Yang
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China; Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
| | - Jing Tian
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China; Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
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Duc HN, Chang LTC, Azzi M, Jiang N. Smoke aerosols dispersion and transport from the 2013 New South Wales (Australia) bushfires. ENVIRONMENTAL MONITORING AND ASSESSMENT 2018; 190:428. [PMID: 29946831 DOI: 10.1007/s10661-018-6810-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/17/2017] [Accepted: 06/18/2018] [Indexed: 06/08/2023]
Abstract
Environmental monitoring and modelling, especially in the regional context, has seen significant progress with the widely usage of satellite measurement in conjunction with local meteorological and air quality monitoring to understand the atmospheric dispersion and transport of air pollutants. This paper studies the application of these data and modelling tools to understand the environment effects of a major bushfire period in the state of New South Wales (NSW), Australia, in 2013. The bushfires have caused high pollution episodes at many sites in the greater Sydney metropolitan areas. The potential long-range transport of aerosols produced by bushfires to other region and states has been seen by regulators as a major concern. Using data and images collected from satellites, in addition to the results obtained from different simulations carried out using HYSPLIT trajectory model and a regional meteorological model called Conformal Cubic Atmospheric Model (CCAM), we were able to identify at least 2 days on which the smoke aerosols from bush fires in NSW has been transported at high altitude to the northern state of Queensland and the Coral Sea. As a result, widespread high particle concentration in South East Queensland including the Brisbane area, as measured by nearly all the air quality monitoring stations in this region, occurred on the day when the smoke aerosols intruded to lower altitude as indicated by the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) Lidar measurements on the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) satellite. The use of meteorological or air quality modelling to connect the ground-based measurements with satellite observations as shown in this study is useful to understand the pollutant transport due to bushfires and its impact on regional air quality.
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Affiliation(s)
- Hiep Nguyen Duc
- Environment Quality, Atmospheric Science and Climate Change Research Group, Ton Duc Thang University, Ho Chi Minh, Vietnam.
- Faculty of Environment and Labour Safety, Ton Duc Thang University, Ho Chi Minh, Vietnam.
| | | | - Merched Azzi
- CSIRO Energy Flagship, 11 Julius Avenue, North Ryde, NSW, 2113, Australia
| | - Ningbo Jiang
- New South Wales Office of Environment and Heritage, Sydney, Australia
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Bucher EH, Stein AF. Large Salt Dust Storms Follow a 30-Year Rainfall Cycle in the Mar Chiquita Lake (Córdoba, Argentina). PLoS One 2016; 11:e0156672. [PMID: 27258088 PMCID: PMC4892511 DOI: 10.1371/journal.pone.0156672] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2016] [Accepted: 05/18/2016] [Indexed: 11/18/2022] Open
Abstract
Starting in 2006, a new source of intense salt dust storms developed in Mar Chiquita (Córdoba, Argentina), the largest saline lake in South America. Storms originate from vast mudflats left by a 30-year expansion-retreat cycle of the lake due to changes in the regional rainfall regime. The annual frequency of salt dust storms correlated with the size of the salt mudflats. Events were restricted to the coldest months, and reached up to 800 km from the source. Occurrence of dust storms was associated with specific surface colors and textures easily identifiable in satellite images. High-emission surfaces were characterized by the presence of sodium sulfate hydrous/anhydrous crystals (mirabilite and thenardite), and a superficial and variable water table, which may result in the periodic development of a characteristic “fluffy” surface derived from salt precipitation-dissolution processes. HYSPLIT model simulation estimates a deposition maximum near the sources (of about 2.5 kg/ha/yr), and a decreasing trend from the emission area outwards, except for the relative secondary maximum modeled over the mountain ranges in southern Bolivia and northern Argentina due to an orographic effect. The 2009 total deposition of salt dust generated in Mar Chiquita was estimated at 6.5 million tons.
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Affiliation(s)
- Enrique H. Bucher
- Instituto de Diversidad y Ecología Animal (CONICET-UNC) and Centro de Zoología Aplicada, Facultad de Ciencias Exactas Físicas y Naturales, Universidad Nacional de Córdoba, Rondeau 798, 5000 Córdoba, Argentina
- * E-mail:
| | - Ariel F. Stein
- NOAA / Air Resources Laboratory, R/ARL—NCWCP—Room 4205, 5830 University Research Court, College Park, Maryland 20740, United States of America
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Xi X, Sokolik IN. Seasonal dynamics of threshold friction velocity and dust emission in Central Asia. JOURNAL OF GEOPHYSICAL RESEARCH. ATMOSPHERES : JGR 2015; 120:1536-1564. [PMID: 26690836 PMCID: PMC4672962 DOI: 10.1002/2014jd022471] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2014] [Revised: 01/09/2015] [Accepted: 01/17/2015] [Indexed: 05/19/2023]
Abstract
UNLABELLED An improved model representation of mineral dust cycle is critical to reducing the uncertainty of dust-induced environmental and climatic impact. Here we present a mesoscale model study of the seasonal dust activity in the semiarid drylands of Central Asia, focusing on the effects of wind speed, soil moisture, surface roughness heterogeneity, and vegetation phenology on the threshold friction velocity (u*t ) and dust emission during the dust season of 1 March to 31 October 2001. The dust model WRF-Chem-DuMo allows us to examine the uncertainties in seasonal dust emissions due to the selection of dust emission scheme and soil grain size distribution data. To account for the vegetation effects on the u*t , we use the Moderate Resolution Imaging Spectroradiometer monthly normalized difference vegetation index to derive the dynamic surface roughness parameters required by the physically based dust schemes of Marticorena and Bergametti (1995, hereinafter MB) and Shao et al. (1996, hereinafter Shao). We find the springtime u*t is strongly enhanced by the roughness effects of temperate steppe and desert ephemeral plants and, to less extent, the binding effects of increased soil moisture. The u*t decreases as the aboveground biomass dies back and soil moisture depletes during summer. The u*t dynamics determines the dust seasonality by causing more summer dust emission, despite a higher frequency of strong winds during spring. Due to the presence of more erodible materials in the saltation diameter range of 60-200 µm, the dry-sieved soil size distribution data lead to eight times more season-total dust emission than the soil texture data, but with minor differences in the temporal distribution. On the other hand, the Shao scheme produces almost the same amount of season-total dust emission as the MB scheme, but with a strong shift toward summer due to the strong sensitivity of the u*t to vegetation. By simply averaging the MB and Shao model experiments, we obtain a mean estimate (Exp_mean) of season-total dust emission of 255.6 Mt (megaton), of which 26.8%, 50.4%, and 22.8% are produced in spring (March-April-May), summer (June-July-August), and autumn (September-October), respectively. The Exp_mean estimate identifies the Ustyurt Plateau, dried seabed of Aral Sea (called Aralkum), Caspian Sea coast, and loess deserts as the strongest dust source areas in Central Asia. The spatial distribution and seasonality of the Exp_mean estimate are in general agreement with ground station dusty weather observations and satellite aerosol optical depth and absorbing aerosol index products. Compared to Cakmur et al. (2006), the Exp_mean estimate suggests Central Asia contributes 10-17% to the global dust emission in 2001. KEY POINTS The WRF-Chem-DuMo model is used to study dust seasonality in Central Asia An accurate representation of u*t is critical for dust seasonality Multiexperiment mean dust emission estimate agrees with observations.
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Affiliation(s)
- Xin Xi
- School of Earth and Atmospheric Sciences, Georgia Institute of TechnologyAtlanta, Georgia, USA
- Correspondence to: X. Xi,,
| | - Irina N Sokolik
- School of Earth and Atmospheric Sciences, Georgia Institute of TechnologyAtlanta, Georgia, USA
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Rolph GD, Ngan F, Draxler RR. Modeling the fallout from stabilized nuclear clouds using the HYSPLIT atmospheric dispersion model. JOURNAL OF ENVIRONMENTAL RADIOACTIVITY 2014; 136:41-55. [PMID: 24878719 DOI: 10.1016/j.jenvrad.2014.05.006] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/21/2014] [Revised: 05/06/2014] [Accepted: 05/07/2014] [Indexed: 06/03/2023]
Abstract
The Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model, developed by the National Oceanic and Atmospheric Administration's Air Resources Laboratory, has been configured to simulate the dispersion and deposition of nuclear materials from a surface-based nuclear detonation using publicly available information on nuclear explosions. Much of the information was obtained from "The Effects of Nuclear Weapons" by Glasstone and Dolan (1977). The model was evaluated against the measurements of nuclear fallout from six nuclear tests conducted between 1951 and 1957 at the Nevada Test Site using the global NCEP/NCAR Reanalysis Project (NNRP) and the Weather Research and Forecasting (WRF) meteorological data as input. The model was able to reproduce the general direction and deposition patterns using the coarse NNRP data with Figure of Merit in Space (FMS - the percent overlap between predicted and measured deposition patterns) scores in excess of 50% for four of six simulations for the smallest dose rate contour, with FMS scores declining for higher dose rate contours. When WRF meteorological data were used the FMS scores were 5-20% higher in five of the six simulations, especially at the higher dose rate contours. The one WRF simulation where the scores declined slightly (10-30%) was also the best scoring simulation when using the NNRP data. When compared with measurements of dose rate and time of arrival from the Town Data Base (Thompson et al., 1994), similar results were found with the WRF simulations providing better results for four of six simulations. The overall result was that the different plume simulations using WRF data had more consistent performance than the plume simulations using NNRP data fields.
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Affiliation(s)
- G D Rolph
- NOAA Air Resources Laboratory (ARL), NCWCP R/ARL, 5830 University Research Court, College Park, MD 20740, USA.
| | - F Ngan
- NOAA Air Resources Laboratory (ARL), NCWCP R/ARL, 5830 University Research Court, College Park, MD 20740, USA; Cooperative Institute for Climate and Satellites, University of Maryland, College Park, MD, USA
| | - R R Draxler
- NOAA Air Resources Laboratory (ARL), NCWCP R/ARL, 5830 University Research Court, College Park, MD 20740, USA
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Liu XH, Wai KM, Wang Y, Zhou J, Li PH, Guo J, Xu PJ, Wang WX. Evaluation of trace elements contamination in cloud/fog water at an elevated mountain site in Northern China. CHEMOSPHERE 2012; 88:531-41. [PMID: 22503636 DOI: 10.1016/j.chemosphere.2012.02.015] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2011] [Revised: 02/03/2012] [Accepted: 02/03/2012] [Indexed: 05/12/2023]
Abstract
Totally 117 cloud/fog water samples were collected at the summit of Mt. Tai (1534m a.s.l.)-the highest mountain in the Northern China Plain. The results were investigated by a combination of techniques including back trajectory model, regional air quality and dust storm models, satellite observations and Principal Component Analysis. Elemental concentrations were determined by Inductively Coupled Plasma Mass Spectrometry, with stringent quality control measures. Higher elemental concentrations were found at Mt. Tai compared with those reported by other overseas studies. The larger proportions and higher concentrations of toxic elements such as Pb and As in cloud/fog water compared with those in rainwater at Mt. Tai suggests higher potential hazards of cloud/fog water as a source of contamination in polluted areas to the ecosystem. Peak concentrations of trace elements were frequently observed during the onset of cloud/fog events when liquid water contents of cloud/fog water were usually low and large amount of pollutants were accumulated in the ambient air. Inverse relationship between elemental concentrations and liquid water contents were only found in the samples with high electrical conductivities and liquid water contents lower than 0.3gm(-3). Affected mainly by the emissions of steel industries and mining activities, air masses transported from south/southwest of Mt. Tai were frequently associated with higher elemental concentrations. The element Mn is attributed to play an important role in the acidity of cloud/fog water. The composition of cloud/fog water influenced by an Asian dust storm event was reported, which was seldom found in the literature.
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Affiliation(s)
- Xiao-huan Liu
- College of Environmental Science and Engineering, Ocean University of China, Qingdao, China
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Leadbetter SJ, Hort MC, von Löwis S, Weber K, Witham CS. Modeling the resuspension of ash deposited during the eruption of Eyjafjallajökull in spring 2010. ACTA ACUST UNITED AC 2012. [DOI: 10.1029/2011jd016802] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Stajner I, Davidson P, Byun D, McQueen J, Draxler R, Dickerson P, Meagher J. US National Air Quality Forecast Capability: Expanding Coverage to Include Particulate Matter. AIR POLLUTION MODELING AND ITS APPLICATION XXI 2011. [DOI: 10.1007/978-94-007-1359-8_64] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
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