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Global atmospheric transport and source-receptor relationships for arsenic Ka-Ming Wai, Shiliang Wu, Xueling Li, Daniel A. Jaffe, and Kevin Perry Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.5b05549 • Publication Date (Web): 24 Feb 2016 Downloaded from http://pubs.acs.org on February 29, 2016
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Environmental Science & Technology
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Global atmospheric transport and source-receptor
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relationships for arsenic
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Ka-Ming Wai1,3, Shiliang Wu1,2*, Xueling Li2, Daniel A. Jaffe4, Kevin D. Perry5
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1
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Houghton, Michigan, USA
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2
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Michigan, USA
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now in Institute of Future Cities, Chinese University of Hong Kong, Hong Kong SAR, China.
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Physical Sciences Div., School of Science, Technology, Engineering and Mathematics,
Dept. of Geological and Mining Engineering and Sciences, Michigan Technological University,
Dept. of Civil and Environmental Engineering, Michigan Technological University, Houghton,
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University of Washington Bothell, Bothell, Washington, USA
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Dept. of Atmospheric Sciences, University of Utah, Salt Lake City, Utah, USA
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*
Contact information for corresponding author: 1-906-487-2590 (phone); 1-906-487-3371 (fax);
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[email protected]
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ABSTRACT: Arsenic and many of its compounds are toxic pollutants in the global environment.
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They can be transported long distances in the atmosphere before depositing to the surface, but
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the global source-receptor relationships between various regions have not yet been assessed. We
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develop the first global model for atmospheric arsenic to better understand and quantify its inter-
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continental transport. Our model reproduces the observed arsenic concentrations in surface air
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over various sites around the world. Arsenic emissions from Asia and South America are found
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to be the dominant sources for atmospheric arsenic in the Northern and Southern Hemispheres,
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respectively. Asian emissions are found to contribute 39% and 38% of the total arsenic
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deposition over the Arctic and Northern America, respectively. Another 14% of the arsenic
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deposition to the Arctic region is attributed to European emissions. Our results indicate that the
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reduction of anthropogenic arsenic emissions in Asia and South America can significantly reduce
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arsenic pollution not only locally but also globally.
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TOC Art
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INTRODUCTION
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Arsenic is a ubiquitous metalloid in the global environment. Elemental arsenic and many of its
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compounds have high toxicity and have been listed by the International Agency for Research on
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Cancer (IARC) as Group 1 carcinogens1. There have been many studies showing increased lung
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cancer risk for people living or working near arsenic-emitting industrial plants such as smelting
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facilities2-6. These arsenic compounds, even at relatively low exposure levels, can also cause
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many other adverse health effects related to the brain and nervous system, digestive system, and
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skin7-9.
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There have been increasing concerns about arsenic pollution in the environment. In 2012,
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Consumer Reports10 conducted tests on more than 200 samples of rice products in the United
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States and found that many of them (including some organic products and infant rice cereals)
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contain arsenic at “worrisome levels”. Since 2013, the European Union Directive has set an air
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quality standard for arsenic concentration in ambient air, which is 6 ng m-3 for annual mean
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concentrations. Besides direct inhalation, the arsenic concentration in ambient air can also affect
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the human exposure to arsenic through atmospheric deposition, which can enhance the arsenic
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levels in food (through arsenic uptake by crops/vegetation) or drinking water. Direct atmospheric
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deposition of arsenic was found to be the dominant transport pathway for arsenic from a factory
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to the leafy vegetables grown nearby, while arsenic in the root crops originated from both the
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soil and the atmosphere11. Therefore, the atmospheric concentrations and deposition of arsenic
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need to be accounted for to fully understand and evaluate the human exposure risk to arsenic in
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the environment12, 13.
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There are both anthropogenic and natural sources for atmospheric arsenic. Metal (copper, zinc,
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and lead) smelting and coal combustion are the major anthropogenic arsenic sources14-16, with
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copper smelting being the most important single source based on arsenic emissions15-17.
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Additional minor anthropogenic sources include application of herbicide, wood preservation, and
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waste incineration16. Natural sources for arsenic in the atmosphere include volcanic emissions,
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wind erosion of soil, and biological activities, with volcanic emissions being the most important
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source14, 17, 18. There are large uncertainties associated with the estimation of arsenic emissions to
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the atmosphere, but according to available global-scale estimates of emissions, the global
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anthropogenic sources are much larger than natural sources14, 17, 19, 20.
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There are large spatial variations for the atmospheric concentrations of arsenic, which can vary
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by several orders of magnitude from less than 0.1 ng m-3 in remote sites to more than 10 ng m-3
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in urban/industrial areas, presumably reflecting the impacts from anthropogenic activities. The
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surface arsenic concentrations were reported to be less than 0.041 ng m-3 in the south polar
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atmosphere21. In China and Chile the surface arsenic concentrations were found to reach 15 ng
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m-3 or higher22, 23. The typical residence time of arsenic in the atmosphere is several days17, 24, 25,
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making long-range transport of it possible. This implies that arsenic emissions from one region
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can significantly affect other regions downwind. However, the global source-receptor
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relationship between various regions has not been quantified so far, in contrast to the extensively
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studied source-receptor relationship for other anthropogenic pollutants and dust26.
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Some previous studies have shown that the regional transport of atmospheric arsenic is evident.
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Using a trajectory model, Pacyna et al.27 studied the atmospheric transport of arsenic and several
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other trace elements from European source regions to Norway and reported that the performance
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of the model is most sensitive to changes in emissions and deposition velocities of these
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elements. Akeredolu et al.28 investigated the long-range transport of arsenic and other
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anthropogenic heavy metals into the Arctic region for the period of July 1979-June 1980 and
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found that the model results agreed with observations within a factor of 2 – 3. Gidhagen et al.23
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studied the regional effects from smelter emissions of arsenic in Chile and demonstrated that
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anthropogenic emissions are the dominant sources for arsenic in the ambient air. A more recent
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study29 simulating the atmospheric concentrations of some heavy metals over Europe pointed out
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that the limited data in emissions is an important factor affecting the model performance.
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Another recent study30 reported that the model results significantly underestimate the measured
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atmospheric concentrations of arsenic and other heavy metals in the United Kingdom, but it did
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not include any sources outside of the European region. Based on the significant arsenic
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enrichment in snowpack samples from the Antarctic Plateau, Hong et al.31 proposed that the
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emissions of trace elements (including arsenic) from nonferrous metal smelting and fossil fuel
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combustion processes in South America, especially in Chile, are the most likely sources. The
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seemingly pristine polar regions are particularly vulnerable to global change and the long-range
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transport of air pollutants including arsenic can have very important implications for the polar
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environment32.
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In this study, we develop the first-ever global gridded emission inventory for arsenic and
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implement it in a global atmospheric chemical transport model (GEOS-Chem) to examine the
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global transport and source-receptor relationships for arsenic.
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METHODS
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We developed a global arsenic model based on the GEOS-Chem chemical transport model
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(http://geos-chem.org) v9-01-01. The GEOS-Chem model has been applied to a wide range of
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research related to atmospheric trace gases, aerosols and mercury33-35. It is driven by assimilated
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meteorological fields from the NASA Global Modeling and Assimilation Office (GMAO). The
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GEOS-4 meteorological data were used for all the model simulations except for the 2011
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simulation (specifically for comparison to measurement data from the MBO site), which was
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driven by GEOS-5 data (since GEOS-4 data is not available).
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Available data on arsenic emissions for various regions around the world were compiled,
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processed and gridded to 4o latitude by 5o longitude for the model with a base year of 2005
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(unless otherwise specified). For Chile, the major arsenic source region in the Southern
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Hemisphere, we followed Gidhagen et al.23. The Australian emissions were based on Australia’s
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National Pollutant Inventory (NPI) (http://www.npi.gov.au/resource/arsenic-and-compounds-0).
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Arsenic emissions in the United States followed the U.S. EPA NATA (National-Scale Air Toxics
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Assessment) inventory for 1999 (http://archive.epa.gov/airtoxics/nata1999/web/html/index.html).
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The Canadian emissions were based on Environment Canada’s National Pollutant Release
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Inventory for 2000 (NPRI) (http://www.ec.gc.ca/inrp-npri). The European emissions of arsenic
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followed the ESPREME inventory (http://espreme.ier.uni-stuttgart.de).
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There is no national emission inventory for arsenic emissions from metal smelting available for
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China, so we developed a new inventory for China in this study. It was derived using the
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production data of non-ferrous metals from the Yearbook of Nonferrous Metals Industry of China
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200536 and the corresponding arsenic emission factors from Chilvers and Peterson16. Arsenic
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emissions from coal-fired power plants in China followed Tian et al.37. Initial model evaluation
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with our a priori arsenic emission inventory developed for China showed a systematic low bias
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for model-simulated arsenic concentrations over China. A likely reason for this low bias is that
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the arsenic emission factors16 from metal smelting used in this study might be too low for China.
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So we scaled up the arsenic emissions due to metal smelting in China by a factor of 1.5 and then
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found very good agreement between model results and observational data (Figure 1, Table 2).
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Anthropogenic arsenic emissions from other countries around the world were estimated by
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taking advantage of the available SO2 emission inventories from the Emissions Database for
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Global Atmospheric Research (EDGAR; http://edgar.jrc.ec.europa.eu). We followed EDGAR
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version 338 for SO2 emissions in 2005 and applied a constant value for the As/S emission ratio39-
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40
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emission ratio assumed the median value of 5.63 x 10-4 (standard deviation 3.92 x 10-4) g As/g S
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from literature studies39-40. Due to the limited data available on the correlations of As/S
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emissions there is significant uncertainty associated with the emission ratio we used.
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We also estimated arsenic emissions from volcanic activities based on the As/S correlations. We
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followed the global volcanic SO2 emission inventory from Andres and Kasgnoc41 and the
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volcanic arsenic emissions were calculated using the ratio of 1.59 x 10-4 g As/g S, which is the
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median value of As/S flux ratios found for volcanic emissions around the world (standard
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deviation=1.0 x 10-3 g As/g S)42-45.
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Because most (90% or more) atmospheric arsenic sorbs onto aerosols46, in particular fine mode
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(i.e. PM2.5) aerosols47-48, we treated the deposition processes of arsenic similarly as PM2.5
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aerosols. The wet deposition of arsenic followed the scheme used by Liu et al.49, which considers
to derive the arsenic emissions from other countries not previously mentioned. The As/S
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the scavenging from convective updrafts, rainout from convective anvils and rainout and
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washout from large-scale precipitation. The dry deposition followed a resistance-in-series
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scheme50, with the surface resistances following the work of Zhang et al.51. The wet deposition in
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GEOS-Chem with both GEOS-4 and GEOS-5 meteorological fields has been previously
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evaluated52-53.
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For model evaluation, we focused on atmospheric arsenic measurement data from nonurban sites
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given the coarse spatial resolution (4o latitude x 5o longitude) of the global model. We collected
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available measurement data from various regions around the world in the literature and compiled
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them in Table 2. Except for the time series data from the Mt. Bachelor Observatory, data for sites
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in the United States and Europe were from the Interagency Monitoring of Protected Visual
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Environments (IMPROVE)54 and the European Monitoring and Evaluation Programme (EMEP)
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transport of aerosol and gas phase pollutants in baseline air arriving to North America56-57. Data
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from the MBO were obtained using a rotating drum impactor with 3-hour time resolution and
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with synchrotron X-ray fluorescence analysis57. It appears that the measurement data for
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atmospheric arsenic deposition are extremely limited, so we are not able to evaluate the model
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performance on arsenic deposition in this study.
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RESULTS AND DISCUSSION
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The global arsenic emissions are calculated to be 30.7 Gg yr-1 with the breakdown for major
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source regions (15.8 and 4.4 Gg yr-1 in East Asia and South America, respectively) summarized
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in Table 1. Our global total arsenic emission is comparable to previous studies by Walsh et al.17
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and Nriagu18 who both estimated the global total arsenic emissions to be 31 Gg yr-1. In contrast,
network, respectively. The MBO site has been used for over a decade to examine long-range
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Chilvers and Peterson16 estimated a very large natural source for arsenic leading to a much
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higher global total arsenic emission of 73.5 Gg yr-1. The model-simulated annual mean
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concentrations of atmospheric arsenic are compared with available measurement data in Figure 1
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and Table 2. We find very good agreement between model results and observations with a high
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correlation (r2 = 0.98, slope of regression line = modelled results / observed results = 1.0, mean
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normalized bias = 89%). However, significant biases are identified for a few stations located in
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remote areas, such as Alaska and Hawaii, where the model strongly overestimates the
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atmospheric arsenic concentrations (Table 2). This likely reflects the uncertainties associated
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with the natural emissions of arsenic as well as the deposition parameters used in the model.
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The global total wet and dry deposition of arsenic was calculated to be 25.4 Gg yr-1 and 5.3 Gg
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yr-1, respectively. The global total atmospheric burden of arsenic is calculated to be 377 Mg
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leading to a global average atmospheric lifetime for arsenic of 4.5 days. The calculated
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atmospheric arsenic lifetimes against deposition range from 4.1 to 5.4 days for different regions
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around the world (Table 1), which are within the range (2.5 – 9 days) reported in the literature17,
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24, 25
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atmospheric deposition (in particular wet deposition) rates. Additional factors such as
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atmospheric transport can also affect the regional lifetime of atmospheric arsenic.
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Figure 1 shows the annual average arsenic concentrations in ambient air driven by synoptic
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transport events. High arsenic concentrations (10 ng m-3 or higher) are found over large areas in
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eastern China and northern Chile, which are at least one order of magnitude higher than those in
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the United States and Europe. Figure 1 also illustrates the outflow of arsenic plumes from Asia,
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which are transported over the North Pacific and North America following the Westerlies.
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Similarly the arsenic plumes from North America are transported across the North Atlantic
. The variations in arsenic lifetimes across various regions mainly reflect the differences in
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towards Europe (Figure 1 and Figure 3c). In the Southern Hemisphere, the major arsenic source
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region is Chile. The arsenic plumes at lower latitudes are transported towards the tropical Pacific
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following the trade winds, and those at higher latitudes are transported towards the Southern
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Atlantic following the Westerlies. We further evaluate the model performance in simulating the
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daily time series of measured atmospheric arsenic concentrations at the Mt. Bachelor
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Observatory (MBO, 44.0° N, 121.7° W), located on the west coast of the United States (Figure
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2). The model reproduces the temporal variations in arsenic concentrations reasonably well (r2 =
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0.35, slope of regression line = modelled results / observed results = 1.15, mean normalized bias
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= 36%).
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In order to better examine the source-receptor relationships between various regions in terms of
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arsenic concentration and deposition, we carried out a suite of sensitivity simulations where
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anthropogenic arsenic emissions from a certain region were turned off in the model. For
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example, we shut off emissions from Asia in the sensitivity model run and then compared the
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calculated atmospheric arsenic deposition (Dno_Asia) with those from the base run (Dbase) to derive
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the percentage contribution of Asian emissions to atmospheric arsenic in the receptor region:
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ContributionAsia= (Dbase – Dno_Asia) / Dbase x 100%. Figure 3 shows the contribution to total (wet +
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dry) deposition from each continental-scale source region.
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Anthropogenic arsenic emissions from Asia are found to make the largest contributions to
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atmospheric arsenic deposition over the North Pacific Ocean and western North America (Figure
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3a). Up to 70% of total atmospheric arsenic concentration and 80% of total arsenic deposition
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over the western part of North America are attributed to anthropogenic Asian emissions.
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Significant contributions to the Arctic region (up to 60% for atmospheric concentration and 70%
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for total arsenic deposition, see footnote in Table 3 for the definition of the Arctic) are calculated
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for Asian emissions (Figure 3a).
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Figure 3b shows the contribution from European anthropogenic arsenic emissions. The European
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contributions mainly extend northward to the Arctic and eastward over part of Russia. The
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European emissions are also found to contribute to arsenic deposition over the Mediterranean
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Sea by up to 60%. Figure 3c shows the contribution from North American anthropogenic arsenic
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emissions. The eastward transport of the arsenic-laden plumes from North America leads to its
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large contribution to the arsenic deposition over the North Atlantic Ocean (up to 80% right off
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the eastern coast of the US).
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The contribution of anthropogenic arsenic emissions from South America is found to dominate
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over the Southern Hemisphere except for Southern Africa and Australia (Figure 3d). Up to 90%
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of arsenic deposition over the Antarctic is attributed to emissions from South America, which
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confirms the hypothesis by Hong et al.31.
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The source-receptor relationships for atmospheric arsenic concentration and deposition between
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major regions in the Northern Hemisphere are summarized in Table 3. On average, about 39% of
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the total arsenic deposition over the Arctic region is attributed to Asian anthropogenic emissions,
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reflecting the strong arsenic emissions from Asia. The European anthropogenic emissions are
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calculated to contribute almost 14% of the total arsenic deposition to the Arctic. The North
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American contribution to arsenic in the Arctic (about 4%) is found to be much less than those
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from Asia or Europe, reflecting both the lower anthropogenic emission strengths and the lower
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latitudes of the sources. The Asian anthropogenic emissions are found to contribute to the total
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arsenic deposition in North America by 38%.
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The inter-continental transport of arsenic, especially the significant global impacts associated
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with arsenic emissions from certain source regions as shown by our results, highlights the
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benefits of international cooperation to reduce arsenic pollution around the world. These source-
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receptor relationships should be considered by researchers and policymakers in designing
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mitigation strategies for arsenic pollution.
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ACKNOWLEDGMENT
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The authors thank the EMEP data providers for making the arsenic data available. This
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publication was made possible by a U.S. EPA grant (grant 83518901). Its contents are solely the
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responsibility of the grantee and do not necessarily represent the official views of the U.S. EPA.
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Further, the U.S. EPA does not endorse the purchase of any commercial products or services
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mentioned in the publication. S.W. acknowledges support from the NSF (grant 1313755). The
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Mt. Bachelor Observatory is supported by the NSF (grant 1447832). We thank four anonymous
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reviewers and the Associate Editor for very helpful comments.
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Supporting Information Available
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Figure S1 indicating the source regions used in Figure 3.
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AUTHOR INFORMATION
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Author Contributions
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K.M.W. and S.W. designed the entire study and wrote the manuscript. K.M.W. developed the
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arsenic model based on the standard GEOS-Chem model and did all model experiments and
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analysis of outputs. X.L. assisted the project with literature review and database preparation at
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the early stage of the project. D.A.J. and K.D.P. provided data of atmospheric arsenic
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measurements from Mt. Bachelor Observatory, USA.
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31. Hong, S.; et al. Evidence of Global-Scale As, Mo, Sb, and Tl Atmospheric Pollution in the Antarctic Snow. Environ. Sci. Tech. 2012, 46, 11550–11557. 32. Wolff, E. W.; Peel, D. A. The record of global pollution in polar snow and ice. Nature, 1985, 313, 535-540. 33. Bey, I.; et al. Global modeling of tropospheric chemistry with assimilated meteorology: Model description and evaluation. J. Geophys. Res. 2001, 106, 23,073–23,095. 34. Martin, R.V.; et al. Interpretation of TOMS observations of tropical tropospheric ozone with a global model and in-situ observations. J. Geophys. Res. 2002, 107, 4351.
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35. Huang, Y.; Wu, S.; Dubey, M. K.; French, N. H. F. Impact of aging mechanism on model simulated carbonaceous aerosols. Atmos. Chem. Phys. 2013, 13, 6329–6343. 36. China Non-ferrous Metals Industry Association. The Yearbook of Nonferrous Metals Industry of China 2005; China Nonferrous Metals Industry Press: Beijing, China, 2006. 37. Tian, H.; et al. Atmospheric emissions estimation of Hg, As, and Se from coal-fired power plants in China. Sci. Total Environ. 2011, 409, 3078–3081. 38. Olivier, J. G. J.; Berdowski, J. J. M. In The Climate System; Berdowski, J., Guicherit, R., Heij, B. J., Eds.; A. A. Balkema Publishers/Swets & Zeitlinger Publishers: Lisse, The Netherlands 2001. 39. Pollution Probe. Sulphur dioxide and toxic metal emissions from smelters in Ontario; Pollution Probe: Toronto, Canada, 2003. 40. Tumati, P. R.; Bilonick, R. A. Estimating Trace Element Emissions Using USGS Coal Data. J. Air Waste Manage. Assoc. 1996, 46, 58–65. 41. Andres, R. J.; Kasgnoc, A. D. A time-averaged inventory of subaerial volcanic sulfur emissions. J. Geophys. Res. 1998, 103, 25251–25261. 42. Symonds, R. B.; Rose, W. L.; Reed, M. H.; Lichte, F. E.; Finnegan, D. L. Volatilization, transport, and
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sublimation of metallic and non-metallic elements in high temperature gases at Merapi Volcano,
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Indonesia. Geochim. Cosmochim. Acta 1987, 51, 2083–2101.
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43. Goff, F.; et al. Geochemical surveillance of magmatic volatiles at Popocatepetl volcano, Mexico. Bull. Geol. Soc. Am. 1998, 110, 695–710. 44. Wardell, L. J.; Kyle, P. R.; Counce, D. Volcanic emissions of metals and halogens from White Island
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(New Zealand) and Erebus volcano (Antarctica) determined with chemical traps. J. Volcanol.
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Geotherm. Res. 2008, 177, 734–742.
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45. Calabrese, S.; et al. Atmospheric sources and sinks of volcanogenic elements in a basaltic volcano (Etna, Italy). Geochim. Cosmochim. Acta 2011, 75, 7401–7425. 46. Matschullat, J., 2000. Arsenic in the geosphere—a review. Science of the Total Environment 249, 297–312. 47. De La Campa, A. M. S., J. De La Rosa, Y. González-Castanedo, R. Fernández-Camacho, A. Alastuey,
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X. Querol, A. Stein, J. Ramos, S. Rodríguez, and I. G. Orellana (2011), Levels and chemical
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composition of PM in a city near a large Cu-smelter in Spain, Journal of Environmental Monitoring,
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13(5), 1276-1287.
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48. Sakata, M., and K. Asakura (2011), Atmospheric dry deposition of trace elements at a site on Asiancontinent side of Japan, Atmospheric Environment, 45(5), 1075-1083.
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49. Liu, H.; Jacob, D. J.; Bey, I.; Yantosca, R. M. Constraints from 210Pb and 7Be on wet deposition and
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transport in a global three-dimensional chemical tracer model driven by assimilated meteorological
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fields. J. Geophys. Res. 2001, 106, 12109–12128.
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50. Wesely, M. L. Parameterization of surface resistances to gaseous dry deposition in regional-scale numerical-models. Atmos. Environ. 1989, 23, 1293–1304. 51. Zhang, L. M.; Gong, S. L.; Padro, J.; Barrie, L. A size-segregated particle dry deposition scheme for an atmospheric aerosol module. Atmos. Environ. 2001, 35, 549–560. 52. Selin, N.E.; Jacob, D. J. Seasonal and spatial patterns of mercury wet deposition in the United States:
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Constraints on the contribution from North American anthropogenic sources. Atmos Environ., 2008,
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42, 5193-5204.
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53. Zhang, L.; et al. Nitrogen deposition to the United States: distribution, sources, and processes. Atmos. Chem. Phys., 2012, 12, 4539-4554. 54. IMPROVE Data Guide from University of California Davis, 1995 (available at: http://vista.cira.colostate.edu/improve/Publications/OtherDocs/IMPROVEDataGuide/IMPROVEData
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Guide.htm)
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55. Tørseth, K., Aas, W., Breivik, K., Fjæraa, A. M., Fiebig, M., Hjellbrekke, A. G., Lund Myhre, C.,
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Solberg, S., and Yttri, K. E.: Introduction to the European Monitoring and Evaluation Programme
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(EMEP) and observed atmospheric composition change during 1972–2009, Atmos. Chem. Phys., 12,
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5447-5481, doi:10.5194/acp-12-5447-2012, 2012.
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56. Jaffe, D. A.; et al. Export of Atmospheric Mercury from Asia. Atmos. Environ. 2005, 39, 3029-3038.
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57. Fischer, E.V.; Perry, K. D.; Jaffe, D. A. Optical and chemical properties of aerosols transported to
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Mount Bachelor during spring 2010. J. Geophys. Res. 2011, 116, D18202. 58. Chen, J.; et al. Characteristics of trace elements and lead isotope ratios in PM2.5 from four sites in Shanghai. J. Hazard. Mat. 2008, 156, 36–43. 59. Yang, Y.; et al. Elemental composition of PM2.5 and PM10 at Mount Gongga in China during 2006. Atmos. Res. 2009, 93, 801–810. 60. Kang, J.; et al. A five-year observation of atmospheric metals on Ulleung Island in the East/Japan Sea: Temporal variability and source identification. Atmos. Environ. 2011, 45, 4252–4262.
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TABLES. Table 1. Sources and average atmospheric lifetimes of arsenic for various regions*.
Global
East Asia
Europe
North America
South America
Other regions
Anthropogenic sources (Gg yr-1)
28.6
15.5
0.7
0.6
4.3
7.5
Natural (Gg yr-1)
2.1
0.3
0.2
0.04
0.1
1.5
4.1
5.4
4.5
Not estimated
sources
Life-time (days) †
4.5
4.1
396 397 398 399
*The geographical regions are defined as: East Asia (20–56°N, 92.5–152.5°E); Europe (36– 72°N, 12.5°W–62.5°E); North America (24–60°N, 132.5– 57.5°W); South America (40–4°S, 82.5–57.5°W).
400 401
†
Atmospheric life-time of arsenic against deposition (dry deposition plus wet deposition).
402
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Table 2. Model-simulated annual average surface atmospheric arsenic concentrations compared with observations. Model result
Site
(ng m-3)
Observations (ng m-3)
Source/Reference Year of for observational observations data
Storhofdi, Iceland (63.4oN, 20.3oW)
0.07
0.18
2005
EMEP
Peyrusse Vieille, France (43.6oN, 0.2oE)
0.14
0.20
2005
EMEP
0.47
0.86
2005
EMEP
0.84
0.44
2005
EMEP
0.20
0.29
2005
EMEP
0.09
0.10
2002
EMEP
Neuglobsow, 13.0oE)
Germany
(53.1oN,
Topoliniky, 17.8oE)
Slovakia
(48.0oN,
Montseny, Spain (41.8oN, 2.4oE) o
o
Bredkalen, Sweden (63.8 N, 15.3 E) o
o
0.27
0.15
2005
EMEP
Rucava, Latvia (56.2 N, 21.1 E)
o
o
0.27
0.38
2005
EMEP
Florida, US (30.1oN, 84.2oW)
0.48
0.46
2005
IMPROVE
Virginia, US (37.6 N, 79.5 W)
0.63
0.44
2005
IMPROVE
Maine, US (46.7oN, 68.0oW)
0.25
0.16
2005
IMPROVE
Michigan, US (47.5oN, 88.1oW)
0.19
0.15
2004
IMPROVE
0.14
0.05
2005
IMPROVE
Texas, US (31.8oN, 104.8oW)
0.23
0.23
2005
IMPROVE
Washington, US (46.6oN, 121.4oW)
0.18
0.12
2005
IMPROVE
California, US (34.2oN, 116.9oW)
0.18
0.07
2005
IMPROVE
Idaho, US (44.2oN, 114.9oW)
0.19
0.03
2005
IMPROVE
Hawaii, US (19.4oN, 155.3oW)
0.10
0.01
2005
IMPROVE
Pallas, Finland (61.0 N, 24.2 E)
o
South Dakota, o 101.9 W)
o
US
(43.7oN,
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o
o
0.07
0.02
2005
IMPROVE
Alaska2, US (55.3 N, 160.5 W)
o
o
0.08
0.04
2005
IMPROVE
Beijing, China (39.8oN, 117.0oE)
22
18
2005
22
Shanghai, China (31.4 N, 121.3 E)
26
27
2004-2005
58
Sichuan, China (29.6oN, 102.0oE)
4.2
6.1
2006
59
Ulleung Island, S. Korea (37.5 N, 130.9oE)
3.6
3.0
2003-2008
60
Quillota, Chile (32.9oS, 71.2oW)
30
31
1999-2000
23
4.4
6.5
1999-2000
23
Alaska1, US (56.5 N, 132.8 W)
o
o
o
o
o
Quillagua, Chile (21.6 S, 69.5 W)
403 404
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Table 3. Source-receptor relationships for atmospheric arsenic concentration (deposition) between various regions*. Source regions Asia
Europe
North America
24.9
14.2
3.9
(39.2)
(13.8)
(4.3)
56.3
4.3
0.1
(58.0)
(4.9)
(0.2)
6.4
68.6
1.3
(10.0)
(60.1)
(2.0)
25.7
2.0
55.1
(38.2)
(1.1)
(41.4)
36.0
0.4
45.9
(48.3)
(0.4)
(30.0)
8.9
0.2
85.0
(16.3)
(0.2)
(67.7)
Arctic
Receptor regions
Asia
Europe
North America
Western US
Eastern US
*Shown as the percentage contribution to total atmospheric arsenic concentration (deposition) in the receptor region attributable to emissions from the source region. The geographical regions are defined as: Arctic (64 – 90°N, 180°W – 180°E); Asia (8 – 72°N, 57.5 –147.5°E); Europe (32 – 72°N, 7.5°W – 62.5°E); North America (28–72°N, 127.5– 62.5°W); Western US (28 – 48°N, 127.5 – 97.5°W); Eastern US (28–48°N, 97.5–67.5°W). 405 406 407 408 409 410
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FIGURES
Figure 1. Arsenic concentrations in surface air. Model-simulated annual (for year 2005) mean arsenic concentrations in ambient air (background) compared with measurement data at various stations (circles) around the world. Refer to Table 2 for specific values.
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0.5
ng/m3
0.4 0.3 0.2 0.1 0
Time measurement
modelling averaged
Figure 2. Daily arsenic concentrations in spring 2011. Measured daily average arsenic concentrations at the Mt. Bachelor Observatory (MBO, 44.0° N, 121.7° W) compared with model results.
(a)
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(b)
(c)
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(d)
Figure 3. Source attribution for arsenic deposition. Shown as percentage of total atmospheric arsenic deposition attributable to emissions from: (a) Asia; (b) Europe; (c) North America; and (d) South America. Source regions are indicated as rectangular boxes in Figure. S1 in the Supplementary Material. 412
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Article
Global atmospheric transport and source-receptor relationships for arsenic Ka-Ming Wai, Shiliang Wu, Xueling Li, Daniel A. Jaffe, and Kevin Perry Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.5b05549 • Publication Date (Web): 24 Feb 2016 Downloaded from http://pubs.acs.org on February 29, 2016
Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.
Environmental Science & Technology is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.
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Global atmospheric transport and source-receptor
2
relationships for arsenic
3
Ka-Ming Wai1,3, Shiliang Wu1,2*, Xueling Li2, Daniel A. Jaffe4, Kevin D. Perry5
4
1
5
Houghton, Michigan, USA
6
2
7
Michigan, USA
8
3
now in Institute of Future Cities, Chinese University of Hong Kong, Hong Kong SAR, China.
9
4
Physical Sciences Div., School of Science, Technology, Engineering and Mathematics,
Dept. of Geological and Mining Engineering and Sciences, Michigan Technological University,
Dept. of Civil and Environmental Engineering, Michigan Technological University, Houghton,
10
University of Washington Bothell, Bothell, Washington, USA
11
5
Dept. of Atmospheric Sciences, University of Utah, Salt Lake City, Utah, USA
12
*
Contact information for corresponding author: 1-906-487-2590 (phone); 1-906-487-3371 (fax);
13
[email protected]
14
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ABSTRACT: Arsenic and many of its compounds are toxic pollutants in the global environment.
16
They can be transported long distances in the atmosphere before depositing to the surface, but
17
the global source-receptor relationships between various regions have not yet been assessed. We
18
develop the first global model for atmospheric arsenic to better understand and quantify its inter-
19
continental transport. Our model reproduces the observed arsenic concentrations in surface air
20
over various sites around the world. Arsenic emissions from Asia and South America are found
21
to be the dominant sources for atmospheric arsenic in the Northern and Southern Hemispheres,
22
respectively. Asian emissions are found to contribute 39% and 38% of the total arsenic
23
deposition over the Arctic and Northern America, respectively. Another 14% of the arsenic
24
deposition to the Arctic region is attributed to European emissions. Our results indicate that the
25
reduction of anthropogenic arsenic emissions in Asia and South America can significantly reduce
26
arsenic pollution not only locally but also globally.
27 28
TOC Art
29 30
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31 32 33
INTRODUCTION
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Arsenic is a ubiquitous metalloid in the global environment. Elemental arsenic and many of its
35
compounds have high toxicity and have been listed by the International Agency for Research on
36
Cancer (IARC) as Group 1 carcinogens1. There have been many studies showing increased lung
37
cancer risk for people living or working near arsenic-emitting industrial plants such as smelting
38
facilities2-6. These arsenic compounds, even at relatively low exposure levels, can also cause
39
many other adverse health effects related to the brain and nervous system, digestive system, and
40
skin7-9.
41 42
There have been increasing concerns about arsenic pollution in the environment. In 2012,
43
Consumer Reports10 conducted tests on more than 200 samples of rice products in the United
44
States and found that many of them (including some organic products and infant rice cereals)
45
contain arsenic at “worrisome levels”. Since 2013, the European Union Directive has set an air
46
quality standard for arsenic concentration in ambient air, which is 6 ng m-3 for annual mean
47
concentrations. Besides direct inhalation, the arsenic concentration in ambient air can also affect
48
the human exposure to arsenic through atmospheric deposition, which can enhance the arsenic
49
levels in food (through arsenic uptake by crops/vegetation) or drinking water. Direct atmospheric
50
deposition of arsenic was found to be the dominant transport pathway for arsenic from a factory
51
to the leafy vegetables grown nearby, while arsenic in the root crops originated from both the
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soil and the atmosphere11. Therefore, the atmospheric concentrations and deposition of arsenic
53
need to be accounted for to fully understand and evaluate the human exposure risk to arsenic in
54
the environment12, 13.
55
There are both anthropogenic and natural sources for atmospheric arsenic. Metal (copper, zinc,
56
and lead) smelting and coal combustion are the major anthropogenic arsenic sources14-16, with
57
copper smelting being the most important single source based on arsenic emissions15-17.
58
Additional minor anthropogenic sources include application of herbicide, wood preservation, and
59
waste incineration16. Natural sources for arsenic in the atmosphere include volcanic emissions,
60
wind erosion of soil, and biological activities, with volcanic emissions being the most important
61
source14, 17, 18. There are large uncertainties associated with the estimation of arsenic emissions to
62
the atmosphere, but according to available global-scale estimates of emissions, the global
63
anthropogenic sources are much larger than natural sources14, 17, 19, 20.
64
There are large spatial variations for the atmospheric concentrations of arsenic, which can vary
65
by several orders of magnitude from less than 0.1 ng m-3 in remote sites to more than 10 ng m-3
66
in urban/industrial areas, presumably reflecting the impacts from anthropogenic activities. The
67
surface arsenic concentrations were reported to be less than 0.041 ng m-3 in the south polar
68
atmosphere21. In China and Chile the surface arsenic concentrations were found to reach 15 ng
69
m-3 or higher22, 23. The typical residence time of arsenic in the atmosphere is several days17, 24, 25,
70
making long-range transport of it possible. This implies that arsenic emissions from one region
71
can significantly affect other regions downwind. However, the global source-receptor
72
relationship between various regions has not been quantified so far, in contrast to the extensively
73
studied source-receptor relationship for other anthropogenic pollutants and dust26.
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Some previous studies have shown that the regional transport of atmospheric arsenic is evident.
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Using a trajectory model, Pacyna et al.27 studied the atmospheric transport of arsenic and several
76
other trace elements from European source regions to Norway and reported that the performance
77
of the model is most sensitive to changes in emissions and deposition velocities of these
78
elements. Akeredolu et al.28 investigated the long-range transport of arsenic and other
79
anthropogenic heavy metals into the Arctic region for the period of July 1979-June 1980 and
80
found that the model results agreed with observations within a factor of 2 – 3. Gidhagen et al.23
81
studied the regional effects from smelter emissions of arsenic in Chile and demonstrated that
82
anthropogenic emissions are the dominant sources for arsenic in the ambient air. A more recent
83
study29 simulating the atmospheric concentrations of some heavy metals over Europe pointed out
84
that the limited data in emissions is an important factor affecting the model performance.
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Another recent study30 reported that the model results significantly underestimate the measured
86
atmospheric concentrations of arsenic and other heavy metals in the United Kingdom, but it did
87
not include any sources outside of the European region. Based on the significant arsenic
88
enrichment in snowpack samples from the Antarctic Plateau, Hong et al.31 proposed that the
89
emissions of trace elements (including arsenic) from nonferrous metal smelting and fossil fuel
90
combustion processes in South America, especially in Chile, are the most likely sources. The
91
seemingly pristine polar regions are particularly vulnerable to global change and the long-range
92
transport of air pollutants including arsenic can have very important implications for the polar
93
environment32.
94
In this study, we develop the first-ever global gridded emission inventory for arsenic and
95
implement it in a global atmospheric chemical transport model (GEOS-Chem) to examine the
96
global transport and source-receptor relationships for arsenic.
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METHODS
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We developed a global arsenic model based on the GEOS-Chem chemical transport model
99
(http://geos-chem.org) v9-01-01. The GEOS-Chem model has been applied to a wide range of
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research related to atmospheric trace gases, aerosols and mercury33-35. It is driven by assimilated
101
meteorological fields from the NASA Global Modeling and Assimilation Office (GMAO). The
102
GEOS-4 meteorological data were used for all the model simulations except for the 2011
103
simulation (specifically for comparison to measurement data from the MBO site), which was
104
driven by GEOS-5 data (since GEOS-4 data is not available).
105
Available data on arsenic emissions for various regions around the world were compiled,
106
processed and gridded to 4o latitude by 5o longitude for the model with a base year of 2005
107
(unless otherwise specified). For Chile, the major arsenic source region in the Southern
108
Hemisphere, we followed Gidhagen et al.23. The Australian emissions were based on Australia’s
109
National Pollutant Inventory (NPI) (http://www.npi.gov.au/resource/arsenic-and-compounds-0).
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Arsenic emissions in the United States followed the U.S. EPA NATA (National-Scale Air Toxics
111
Assessment) inventory for 1999 (http://archive.epa.gov/airtoxics/nata1999/web/html/index.html).
112
The Canadian emissions were based on Environment Canada’s National Pollutant Release
113
Inventory for 2000 (NPRI) (http://www.ec.gc.ca/inrp-npri). The European emissions of arsenic
114
followed the ESPREME inventory (http://espreme.ier.uni-stuttgart.de).
115
There is no national emission inventory for arsenic emissions from metal smelting available for
116
China, so we developed a new inventory for China in this study. It was derived using the
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production data of non-ferrous metals from the Yearbook of Nonferrous Metals Industry of China
118
200536 and the corresponding arsenic emission factors from Chilvers and Peterson16. Arsenic
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emissions from coal-fired power plants in China followed Tian et al.37. Initial model evaluation
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with our a priori arsenic emission inventory developed for China showed a systematic low bias
121
for model-simulated arsenic concentrations over China. A likely reason for this low bias is that
122
the arsenic emission factors16 from metal smelting used in this study might be too low for China.
123
So we scaled up the arsenic emissions due to metal smelting in China by a factor of 1.5 and then
124
found very good agreement between model results and observational data (Figure 1, Table 2).
125
Anthropogenic arsenic emissions from other countries around the world were estimated by
126
taking advantage of the available SO2 emission inventories from the Emissions Database for
127
Global Atmospheric Research (EDGAR; http://edgar.jrc.ec.europa.eu). We followed EDGAR
128
version 338 for SO2 emissions in 2005 and applied a constant value for the As/S emission ratio39-
129
40
130
emission ratio assumed the median value of 5.63 x 10-4 (standard deviation 3.92 x 10-4) g As/g S
131
from literature studies39-40. Due to the limited data available on the correlations of As/S
132
emissions there is significant uncertainty associated with the emission ratio we used.
133
We also estimated arsenic emissions from volcanic activities based on the As/S correlations. We
134
followed the global volcanic SO2 emission inventory from Andres and Kasgnoc41 and the
135
volcanic arsenic emissions were calculated using the ratio of 1.59 x 10-4 g As/g S, which is the
136
median value of As/S flux ratios found for volcanic emissions around the world (standard
137
deviation=1.0 x 10-3 g As/g S)42-45.
138
Because most (90% or more) atmospheric arsenic sorbs onto aerosols46, in particular fine mode
139
(i.e. PM2.5) aerosols47-48, we treated the deposition processes of arsenic similarly as PM2.5
140
aerosols. The wet deposition of arsenic followed the scheme used by Liu et al.49, which considers
to derive the arsenic emissions from other countries not previously mentioned. The As/S
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the scavenging from convective updrafts, rainout from convective anvils and rainout and
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washout from large-scale precipitation. The dry deposition followed a resistance-in-series
143
scheme50, with the surface resistances following the work of Zhang et al.51. The wet deposition in
144
GEOS-Chem with both GEOS-4 and GEOS-5 meteorological fields has been previously
145
evaluated52-53.
146
For model evaluation, we focused on atmospheric arsenic measurement data from nonurban sites
147
given the coarse spatial resolution (4o latitude x 5o longitude) of the global model. We collected
148
available measurement data from various regions around the world in the literature and compiled
149
them in Table 2. Except for the time series data from the Mt. Bachelor Observatory, data for sites
150
in the United States and Europe were from the Interagency Monitoring of Protected Visual
151
Environments (IMPROVE)54 and the European Monitoring and Evaluation Programme (EMEP)
152
55
153
transport of aerosol and gas phase pollutants in baseline air arriving to North America56-57. Data
154
from the MBO were obtained using a rotating drum impactor with 3-hour time resolution and
155
with synchrotron X-ray fluorescence analysis57. It appears that the measurement data for
156
atmospheric arsenic deposition are extremely limited, so we are not able to evaluate the model
157
performance on arsenic deposition in this study.
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RESULTS AND DISCUSSION
159
The global arsenic emissions are calculated to be 30.7 Gg yr-1 with the breakdown for major
160
source regions (15.8 and 4.4 Gg yr-1 in East Asia and South America, respectively) summarized
161
in Table 1. Our global total arsenic emission is comparable to previous studies by Walsh et al.17
162
and Nriagu18 who both estimated the global total arsenic emissions to be 31 Gg yr-1. In contrast,
network, respectively. The MBO site has been used for over a decade to examine long-range
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Chilvers and Peterson16 estimated a very large natural source for arsenic leading to a much
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higher global total arsenic emission of 73.5 Gg yr-1. The model-simulated annual mean
165
concentrations of atmospheric arsenic are compared with available measurement data in Figure 1
166
and Table 2. We find very good agreement between model results and observations with a high
167
correlation (r2 = 0.98, slope of regression line = modelled results / observed results = 1.0, mean
168
normalized bias = 89%). However, significant biases are identified for a few stations located in
169
remote areas, such as Alaska and Hawaii, where the model strongly overestimates the
170
atmospheric arsenic concentrations (Table 2). This likely reflects the uncertainties associated
171
with the natural emissions of arsenic as well as the deposition parameters used in the model.
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The global total wet and dry deposition of arsenic was calculated to be 25.4 Gg yr-1 and 5.3 Gg
173
yr-1, respectively. The global total atmospheric burden of arsenic is calculated to be 377 Mg
174
leading to a global average atmospheric lifetime for arsenic of 4.5 days. The calculated
175
atmospheric arsenic lifetimes against deposition range from 4.1 to 5.4 days for different regions
176
around the world (Table 1), which are within the range (2.5 – 9 days) reported in the literature17,
177
24, 25
178
atmospheric deposition (in particular wet deposition) rates. Additional factors such as
179
atmospheric transport can also affect the regional lifetime of atmospheric arsenic.
180
Figure 1 shows the annual average arsenic concentrations in ambient air driven by synoptic
181
transport events. High arsenic concentrations (10 ng m-3 or higher) are found over large areas in
182
eastern China and northern Chile, which are at least one order of magnitude higher than those in
183
the United States and Europe. Figure 1 also illustrates the outflow of arsenic plumes from Asia,
184
which are transported over the North Pacific and North America following the Westerlies.
185
Similarly the arsenic plumes from North America are transported across the North Atlantic
. The variations in arsenic lifetimes across various regions mainly reflect the differences in
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towards Europe (Figure 1 and Figure 3c). In the Southern Hemisphere, the major arsenic source
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region is Chile. The arsenic plumes at lower latitudes are transported towards the tropical Pacific
188
following the trade winds, and those at higher latitudes are transported towards the Southern
189
Atlantic following the Westerlies. We further evaluate the model performance in simulating the
190
daily time series of measured atmospheric arsenic concentrations at the Mt. Bachelor
191
Observatory (MBO, 44.0° N, 121.7° W), located on the west coast of the United States (Figure
192
2). The model reproduces the temporal variations in arsenic concentrations reasonably well (r2 =
193
0.35, slope of regression line = modelled results / observed results = 1.15, mean normalized bias
194
= 36%).
195
In order to better examine the source-receptor relationships between various regions in terms of
196
arsenic concentration and deposition, we carried out a suite of sensitivity simulations where
197
anthropogenic arsenic emissions from a certain region were turned off in the model. For
198
example, we shut off emissions from Asia in the sensitivity model run and then compared the
199
calculated atmospheric arsenic deposition (Dno_Asia) with those from the base run (Dbase) to derive
200
the percentage contribution of Asian emissions to atmospheric arsenic in the receptor region:
201
ContributionAsia= (Dbase – Dno_Asia) / Dbase x 100%. Figure 3 shows the contribution to total (wet +
202
dry) deposition from each continental-scale source region.
203
Anthropogenic arsenic emissions from Asia are found to make the largest contributions to
204
atmospheric arsenic deposition over the North Pacific Ocean and western North America (Figure
205
3a). Up to 70% of total atmospheric arsenic concentration and 80% of total arsenic deposition
206
over the western part of North America are attributed to anthropogenic Asian emissions.
207
Significant contributions to the Arctic region (up to 60% for atmospheric concentration and 70%
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for total arsenic deposition, see footnote in Table 3 for the definition of the Arctic) are calculated
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for Asian emissions (Figure 3a).
210
Figure 3b shows the contribution from European anthropogenic arsenic emissions. The European
211
contributions mainly extend northward to the Arctic and eastward over part of Russia. The
212
European emissions are also found to contribute to arsenic deposition over the Mediterranean
213
Sea by up to 60%. Figure 3c shows the contribution from North American anthropogenic arsenic
214
emissions. The eastward transport of the arsenic-laden plumes from North America leads to its
215
large contribution to the arsenic deposition over the North Atlantic Ocean (up to 80% right off
216
the eastern coast of the US).
217
The contribution of anthropogenic arsenic emissions from South America is found to dominate
218
over the Southern Hemisphere except for Southern Africa and Australia (Figure 3d). Up to 90%
219
of arsenic deposition over the Antarctic is attributed to emissions from South America, which
220
confirms the hypothesis by Hong et al.31.
221
The source-receptor relationships for atmospheric arsenic concentration and deposition between
222
major regions in the Northern Hemisphere are summarized in Table 3. On average, about 39% of
223
the total arsenic deposition over the Arctic region is attributed to Asian anthropogenic emissions,
224
reflecting the strong arsenic emissions from Asia. The European anthropogenic emissions are
225
calculated to contribute almost 14% of the total arsenic deposition to the Arctic. The North
226
American contribution to arsenic in the Arctic (about 4%) is found to be much less than those
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from Asia or Europe, reflecting both the lower anthropogenic emission strengths and the lower
228
latitudes of the sources. The Asian anthropogenic emissions are found to contribute to the total
229
arsenic deposition in North America by 38%.
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The inter-continental transport of arsenic, especially the significant global impacts associated
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with arsenic emissions from certain source regions as shown by our results, highlights the
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benefits of international cooperation to reduce arsenic pollution around the world. These source-
233
receptor relationships should be considered by researchers and policymakers in designing
234
mitigation strategies for arsenic pollution.
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ACKNOWLEDGMENT
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The authors thank the EMEP data providers for making the arsenic data available. This
238
publication was made possible by a U.S. EPA grant (grant 83518901). Its contents are solely the
239
responsibility of the grantee and do not necessarily represent the official views of the U.S. EPA.
240
Further, the U.S. EPA does not endorse the purchase of any commercial products or services
241
mentioned in the publication. S.W. acknowledges support from the NSF (grant 1313755). The
242
Mt. Bachelor Observatory is supported by the NSF (grant 1447832). We thank four anonymous
243
reviewers and the Associate Editor for very helpful comments.
244 245
Supporting Information Available
246
Figure S1 indicating the source regions used in Figure 3.
247 248 249
AUTHOR INFORMATION
250
Author Contributions
251
K.M.W. and S.W. designed the entire study and wrote the manuscript. K.M.W. developed the
252
arsenic model based on the standard GEOS-Chem model and did all model experiments and
253
analysis of outputs. X.L. assisted the project with literature review and database preparation at
254
the early stage of the project. D.A.J. and K.D.P. provided data of atmospheric arsenic
255
measurements from Mt. Bachelor Observatory, USA.
256 257 258
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TABLES. Table 1. Sources and average atmospheric lifetimes of arsenic for various regions*.
Global
East Asia
Europe
North America
South America
Other regions
Anthropogenic sources (Gg yr-1)
28.6
15.5
0.7
0.6
4.3
7.5
Natural (Gg yr-1)
2.1
0.3
0.2
0.04
0.1
1.5
4.1
5.4
4.5
Not estimated
sources
Life-time (days) †
4.5
4.1
396 397 398 399
*The geographical regions are defined as: East Asia (20–56°N, 92.5–152.5°E); Europe (36– 72°N, 12.5°W–62.5°E); North America (24–60°N, 132.5– 57.5°W); South America (40–4°S, 82.5–57.5°W).
400 401
†
Atmospheric life-time of arsenic against deposition (dry deposition plus wet deposition).
402
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Table 2. Model-simulated annual average surface atmospheric arsenic concentrations compared with observations. Model result
Site
(ng m-3)
Observations (ng m-3)
Source/Reference Year of for observational observations data
Storhofdi, Iceland (63.4oN, 20.3oW)
0.07
0.18
2005
EMEP
Peyrusse Vieille, France (43.6oN, 0.2oE)
0.14
0.20
2005
EMEP
0.47
0.86
2005
EMEP
0.84
0.44
2005
EMEP
0.20
0.29
2005
EMEP
0.09
0.10
2002
EMEP
Neuglobsow, 13.0oE)
Germany
(53.1oN,
Topoliniky, 17.8oE)
Slovakia
(48.0oN,
Montseny, Spain (41.8oN, 2.4oE) o
o
Bredkalen, Sweden (63.8 N, 15.3 E) o
o
0.27
0.15
2005
EMEP
Rucava, Latvia (56.2 N, 21.1 E)
o
o
0.27
0.38
2005
EMEP
Florida, US (30.1oN, 84.2oW)
0.48
0.46
2005
IMPROVE
Virginia, US (37.6 N, 79.5 W)
0.63
0.44
2005
IMPROVE
Maine, US (46.7oN, 68.0oW)
0.25
0.16
2005
IMPROVE
Michigan, US (47.5oN, 88.1oW)
0.19
0.15
2004
IMPROVE
0.14
0.05
2005
IMPROVE
Texas, US (31.8oN, 104.8oW)
0.23
0.23
2005
IMPROVE
Washington, US (46.6oN, 121.4oW)
0.18
0.12
2005
IMPROVE
California, US (34.2oN, 116.9oW)
0.18
0.07
2005
IMPROVE
Idaho, US (44.2oN, 114.9oW)
0.19
0.03
2005
IMPROVE
Hawaii, US (19.4oN, 155.3oW)
0.10
0.01
2005
IMPROVE
Pallas, Finland (61.0 N, 24.2 E)
o
South Dakota, o 101.9 W)
o
US
(43.7oN,
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o
o
0.07
0.02
2005
IMPROVE
Alaska2, US (55.3 N, 160.5 W)
o
o
0.08
0.04
2005
IMPROVE
Beijing, China (39.8oN, 117.0oE)
22
18
2005
22
Shanghai, China (31.4 N, 121.3 E)
26
27
2004-2005
58
Sichuan, China (29.6oN, 102.0oE)
4.2
6.1
2006
59
Ulleung Island, S. Korea (37.5 N, 130.9oE)
3.6
3.0
2003-2008
60
Quillota, Chile (32.9oS, 71.2oW)
30
31
1999-2000
23
4.4
6.5
1999-2000
23
Alaska1, US (56.5 N, 132.8 W)
o
o
o
o
o
Quillagua, Chile (21.6 S, 69.5 W)
403 404
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Table 3. Source-receptor relationships for atmospheric arsenic concentration (deposition) between various regions*. Source regions Asia
Europe
North America
24.9
14.2
3.9
(39.2)
(13.8)
(4.3)
56.3
4.3
0.1
(58.0)
(4.9)
(0.2)
6.4
68.6
1.3
(10.0)
(60.1)
(2.0)
25.7
2.0
55.1
(38.2)
(1.1)
(41.4)
36.0
0.4
45.9
(48.3)
(0.4)
(30.0)
8.9
0.2
85.0
(16.3)
(0.2)
(67.7)
Arctic
Receptor regions
Asia
Europe
North America
Western US
Eastern US
*Shown as the percentage contribution to total atmospheric arsenic concentration (deposition) in the receptor region attributable to emissions from the source region. The geographical regions are defined as: Arctic (64 – 90°N, 180°W – 180°E); Asia (8 – 72°N, 57.5 –147.5°E); Europe (32 – 72°N, 7.5°W – 62.5°E); North America (28–72°N, 127.5– 62.5°W); Western US (28 – 48°N, 127.5 – 97.5°W); Eastern US (28–48°N, 97.5–67.5°W). 405 406 407 408 409 410
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FIGURES
Figure 1. Arsenic concentrations in surface air. Model-simulated annual (for year 2005) mean arsenic concentrations in ambient air (background) compared with measurement data at various stations (circles) around the world. Refer to Table 2 for specific values.
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0.5
ng/m3
0.4 0.3 0.2 0.1 0
Time measurement
modelling averaged
Figure 2. Daily arsenic concentrations in spring 2011. Measured daily average arsenic concentrations at the Mt. Bachelor Observatory (MBO, 44.0° N, 121.7° W) compared with model results.
(a)
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(b)
(c)
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(d)
Figure 3. Source attribution for arsenic deposition. Shown as percentage of total atmospheric arsenic deposition attributable to emissions from: (a) Asia; (b) Europe; (c) North America; and (d) South America. Source regions are indicated as rectangular boxes in Figure. S1 in the Supplementary Material. 412
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