scholarly journals Evaluation of global EMEP MSC-W (rv4.34) WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurements

2021 ◽  
Vol 14 (11) ◽  
pp. 7021-7046
Author(s):  
Yao Ge ◽  
Mathew R. Heal ◽  
David S. Stevenson ◽  
Peter Wind ◽  
Massimo Vieno
Keyword(s):  
North America ◽  
Southeast Asia ◽  
East Asia ◽  
Atmospheric Chemistry ◽  
Wet Deposition ◽  
Global Analysis ◽  
Monitoring Networks ◽  
Model Framework ◽  
Annual Total ◽  
Model Measurement

Abstract. Atmospheric pollution has many profound effects on human health, ecosystems, and the climate. Of concern are high concentrations and deposition of reactive nitrogen (Nr) species, especially of reduced N (gaseous NH3, particulate NH4+). Atmospheric chemistry and transport models (ACTMs) are crucial to understanding sources and impacts of Nr chemistry and its potential mitigation. Here we undertake the first evaluation of the global version of the EMEP MSC-W ACTM driven by WRF meteorology (1∘×1∘ resolution), with a focus on surface concentrations and wet deposition of N and S species relevant to investigation of atmospheric Nr and secondary inorganic aerosol (SIA). The model–measurement comparison is conducted both spatially and temporally, covering 10 monitoring networks worldwide. Model simulations for 2010 compared use of both HTAP and ECLIPSEE (ECLIPSE annual total with EDGAR monthly profile) emissions inventories; those for 2015 used ECLIPSEE only. Simulations of primary pollutants are somewhat sensitive to the choice of inventory in places where regional differences in primary emissions between the two inventories are apparent (e.g. China) but are much less sensitive for secondary components. For example, the difference in modelled global annual mean surface NH3 concentration using the two 2010 inventories is 18 % (HTAP: 0.26 µg m−3; ECLIPSEE: 0.31 µg m−3) but is only 3.5 % for NH4+ (HTAP: 0.316 µg m−3; ECLIPSEE: 0.305 µg m−3). Comparisons of 2010 and 2015 surface concentrations between the model and measurements demonstrate that the model captures the overall spatial and seasonal variations well for the major inorganic pollutants NH3, NO2, SO2, HNO3, NH4+, NO3-, and SO42- and their wet deposition in East Asia, Southeast Asia, Europe, and North America. The model shows better correlations with annual average measurements for networks in Southeast Asia (mean R for seven species: R7‾=0.73), Europe (R7‾=0.67), and North America (R7‾=0.63) than in East Asia (R5‾=0.35) (data for 2015), which suggests potential issues with the measurements in the latter network. Temporally, both model and measurements agree on higher NH3 concentrations in spring and summer and lower concentrations in winter. The model slightly underestimates annual total precipitation measurements (by 13 %–45 %) but agrees well with the spatial variations in precipitation in all four world regions (0.65–0.94 R range). High correlations between measured and modelled NH4+ precipitation concentrations are also observed in all regions except East Asia. For annual total wet deposition of reduced N, the greatest consistency is in North America (0.75–0.82 R range), followed by Southeast Asia (R=0.68) and Europe (R=0.61). Model–measurement bias varies between species in different networks; for example, bias for NH4+ and NO3- is largest in Europe and North America and smallest in East Asia and Southeast Asia. The greater uniformity in spatial correlations than in biases suggests that the major driver of model–measurement discrepancies (aside from differing spatial representativeness and uncertainties and biases in measurements) are shortcomings in absolute emissions rather than in modelling the atmospheric processes. The comprehensive evaluations presented in this study support the application of this model framework for global analysis of current and potential future budgets and deposition of Nr and SIA.

scholarly journals Evaluation of global EMEP MSC-W (rv4.34)-WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurements

2021 ◽  
Author(s):  
Yao Ge ◽  
Mathew R. Heal ◽  
David S. Stevenson ◽  
Peter Wind ◽  
Massimo Vieno
Keyword(s):  
North America ◽  
Southeast Asia ◽  
East Asia ◽  
Atmospheric Chemistry ◽  
Wet Deposition ◽  
Global Analysis ◽  
Monitoring Networks ◽  
Model Framework ◽  
Annual Total ◽  
Model Measurement

Abstract. Atmospheric pollution has many profound effects on human health, ecosystems, and the climate. Of concern are high concentrations and deposition of reactive nitrogen (Nr) species, especially of reduced N (gaseous NH3, particulate NH4+). Atmospheric chemistry and transport models (ACTMs) are crucial to understanding sources and impacts of Nr chemistry and its potential mitigation. Here we undertake the first evaluation of the global version of the EMEP MSC-W ACTM driven by WRF meteorology (1° × 1° resolution), with a focus on surface concentrations and wet deposition of N and S species relevant to investigation of atmospheric Nr and secondary inorganic aerosol (SIA). The model-measurement comparison is conducted both spatially and temporally, covering 9 monitoring networks worldwide. Model simulations for 2010 compared use of both HTAP and ECLIPSEE (ECLIPSE annual total with EDGAR monthly profile) emissions inventories; those for 2015 used ECLIPSEE only. Simulations of primary pollutants are somewhat sensitive to the choice of inventory in places where regional differences in primary emissions between the two inventories are apparent (e.g. China), but much less so for secondary components. For example, the difference in modelled global annual mean surface NH3 concentration using the two 2010 inventories is 18 % (HTAP: 0.26 μg m−3; ECLIPSEE: 0.31 μg m−3) but only 3.5 % for NH4+ (HTAP: 0.316 μg m−3; ECLIPSEE: 0.305 μg m−3). Comparisons of 2010 and 2015 surface concentrations between model and measurement demonstrate that the model captures well the overall spatial and seasonal variations of the major inorganic pollutants NH3, NO2, SO2, HNO3, NH4+, NO3−, SO42−, and their wet deposition in East Asia, Southeast Asia, Europe and North America. The model shows better correlations with annual average measurements for networks in Southeast Asia (Mean R for 7 species:  = 0.73), Europe ( = 0.67) and North America ( = 0.63) than in East Asia ( = 0.35) (data for 2015), which suggests potential issues with the measurements in the latter network. Temporally, both model and measurement agree on higher NH3 concentrations in spring and summer, and lower concentrations in winter. The model slightly underestimates annual total precipitation measurements (by 13–34 %) but agrees well with the spatial variations in precipitation in all four world regions (0.65–0.78 R range). High correlations between measured and modelled NH4+ precipitation concentrations are also observed in all regions except East Asia. For annual total wet deposition of reduced N, the greatest consistency is in North America (R = 0.75), followed by Southeast Asia (R = 0.68) and Europe (R = 0.61). Model-measurement bias varies between species in different networks; for example, bias for NH4+ and NO3− is most in Europe and North America and least in East and Southeast Asia. The greater uniformity in spatial correlations than in biases suggests that the major driver of model-measurement discrepancies (aside from differing spatial representativeness and uncertainties and biases in measurements) are shortcomings in absolute emissions rather than in modelling the atmospheric processes. The comprehensive evaluations presented in this study support the application of this model framework for global analysis of current and potential future budgets and deposition of Nr and SIA.

scholarly journals Multi-model study of HTAP II on sulphur and nitrogen deposition

2018 ◽  
Author(s):  
Jiani Tan ◽  
Joshua S. Fu ◽  
Frank Dentener ◽  
Jian Sun ◽  
Louisa Emmons ◽  
...  
Keyword(s):  
North America ◽  
East Asia ◽  
South Asia ◽  
Wet Deposition ◽  
Task Force ◽  
East Asian ◽  
Control Policy ◽  
N Deposition ◽  
Eastern United States ◽  
S Deposition

Abstract. This study uses multi-model ensemble results of 11 models from the 2nd phase of Task Force Hemispheric Transport of Air Pollution (HTAP II) to calculate the global sulfur (S) and nitrogen (N) deposition in 2010. Modelled wet deposition is evaluated with observation networks in North America, Europe and Asia. The modelled results agree well with observations, with 76–83 % of stations having predicted within ±50 % of observations. The results underestimate SO42−, NO3− and NH4+ wet depositions in some European and East Asian stations, but overestimate NO3− wet deposition in Eastern United States. Inter-comparison with previous projects (PhotoComp, ACCMIP and HTAP I) shows HTPA II has considerably improved the estimation of deposition at European and East Asian stations. Modelled dry deposition is generally higher than the “inferential” data calculated by observed concentration and modelled velocity in North America, but the inferential data has high uncertainty, too. The global S deposition is 84 Tg(S) in 2010, with 49 % of the deposits on continental regions and 51 % on ocean (19 % on coastal). The global N deposition consists of 59 Tg(N) oxidized nitrogen (NOy) deposition and 64 Tg(N) reduced nitrogen (NHx) deposition in 2010. 65 % of N is deposited on the continental regions and 35 % is on ocean (15 % on coastal). The estimated outflow of pollution from land to ocean is about 4 Tg(S) for S deposition and 18 Tg(N) for N deposition. Compared our results to the results in 2001 from HTAP I, we find that the global distributions of S and N depositions have changed considerably during the last 10 years. The global S deposition decreases 2 Tg(S) (3 %) from 2001 to 2010, with significant decreases in Europe (5 Tg(S) and 55 %), North America (3 Tg(S) and 29 %) and Russia (2 Tg(S) and 26 %), and increases in South Asia (2 Tg(S) and 42 %) and the Middle East (1 Tg(S) and 44% ). The global N deposition increases by 7 Tg(N) (6 %), mainly contributed by South Asia (5 Tg(N) and 39 %), East Asia (4 Tg(N) and 21 %) and Southeast Asia (2 Tg(N) and 21 %). The NHx deposition is increased with no control policy on NH3 emission in North America. On the other hand, NOy deposition starts to dominate in East Asia (especially China) due to boosted NOx emission in recent years.

scholarly journals Regional trend analysis of surface ozone observations from monitoring networks in eastern North America, Europe and East Asia

Elem Sci Anth ◽  
2017 ◽  
Vol 5 (0) ◽  
pp. 50 ◽  
Author(s):  
Kai-Lan Chang ◽  
Irina Petropavlovskikh ◽  
Owen R. Copper ◽  
Martin G. Schultz ◽  
Tao Wang
Keyword(s):  
North America ◽  
East Asia ◽  
Trend Analysis ◽  
Surface Ozone ◽  
Eastern North America ◽  
Monitoring Networks ◽  
Regional Trend

scholarly journals Global analysis of the participation of sovereign wealth funds in the stock market

2020 ◽  
Vol 6 (1) ◽  
pp. 51-67
Author(s):  
L. Gómez-Pavón Durán
Keyword(s):  
North America ◽  
Middle East ◽  
Southeast Asia ◽  
Global Analysis ◽  
Listed Companies ◽  
Theoretical Description ◽  
High Concentration ◽  
Sovereign Wealth Funds ◽  
Total Investment ◽  
The One

This paper provides an analysis of the overall investment in listed companies made by a sample of 30 sovereign wealth funds. The first part of this paper comprises a theoretical description of sovereign wealth funds, while the second part covers the analysis of the investment made at both the aggregate and individual levels. The results achieved from this analysis lead to the conclusion that Europe, Asia and North America attract more than two-thirds of total investment, with the financial sector being the one that attracts more funds. Another result indicates that more than 80% of total investment in listed companies comes from five sovereign wealth funds. Finally, the results also show that there is a group of sovereign wealth funds from Southeast Asia and the Middle East that have a high concentration and percentage of control over the investments they made, which could be an indicator of strategic positions.

scholarly journals Distributions and regional budgets of aerosols and their precursors simulated with the EMAC chemistry-climate model

2012 ◽  
Vol 12 (2) ◽  
pp. 961-987 ◽  
Author(s):  
A. Pozzer ◽  
A. de Meij ◽  
K. J. Pringle ◽  
H. Tost ◽  
U. M. Doering ◽  
...  
Keyword(s):  
North America ◽  
East Asia ◽  
Atmospheric Chemistry ◽  
General Circulation ◽  
Climate Model ◽  
Temporal Distribution ◽  
Circulation Model ◽  
Temporal Correlation ◽  
Horizontal Resolution ◽  
Nitrate Aerosol

Abstract. The new global anthropogenic emission inventory (EDGAR-CIRCE) of gas and aerosol pollutants has been incorporated in the chemistry general circulation model EMAC (ECHAM5/MESSy Atmospheric Chemistry). A relatively high horizontal resolution simulation is performed for the years 2005–2008 to evaluate the capability of the model and the emissions to reproduce observed aerosol concentrations and aerosol optical depth (AOD) values. Model output is compared with observations from different measurement networks (CASTNET, EMEP and EANET) and AODs from remote sensing instruments (MODIS and MISR). A good spatial agreement of the distribution of sulfate and ammonium aerosol is found when compared to observations, while calculated nitrate aerosol concentrations show some discrepancies. The simulated temporal development of the inorganic aerosols is in line with measurements of sulfate and nitrate aerosol, while for ammonium aerosol some deviations from observations occur over the USA, due to the wrong temporal distribution of ammonia gas emissions. The calculated AODs agree well with the satellite observations in most regions, while negative biases are found for the equatorial area and in the dust outflow regions (i.e. Central Atlantic and Northern Indian Ocean), due to an underestimation of biomass burning and aeolian dust emissions, respectively. Aerosols and precursors budgets for five different regions (North America, Europe, East Asia, Central Africa and South America) are calculated. Over East-Asia most of the emitted aerosols (precursors) are also deposited within the region, while in North America and Europe transport plays a larger role. Further, it is shown that a simulation with monthly varying anthropogenic emissions typically improves the temporal correlation by 5–10% compared to one with constant annual emissions.

scholarly journals Global modeling of cloud water acidity, precipitation acidity, and acid inputs to ecosystems

2020 ◽  
Vol 20 (20) ◽  
pp. 12223-12245
Author(s):  
Viral Shah ◽  
Daniel J. Jacob ◽  
Jonathan M. Moch ◽  
Xuan Wang ◽  
Shixian Zhai
Keyword(s):  
East Asia ◽  
Carboxylic Acids ◽  
Atmospheric Chemistry ◽  
Wet Deposition ◽  
Cloud Water ◽  
Water Ph ◽  
Precipitation Ph ◽  
Water Acidity ◽  
Global Mean ◽  
Precipitation Acidity

Abstract. Cloud water acidity affects the atmospheric chemistry of sulfate and organic aerosol formation, halogen radical cycling, and trace metal speciation. Precipitation acidity including post-depositional inputs adversely affects soil and freshwater ecosystems. Here, we use the GEOS-Chem model of atmospheric chemistry to simulate the global distributions of cloud water and precipitation acidity as well as the total acid inputs to ecosystems from wet deposition. The model accounts for strong acids (H2SO4, HNO3, and HCl), weak acids (HCOOH, CH3COOH, CO2, and SO2), and weak bases (NH3 as well as dust and sea salt aerosol alkalinity). We compile a global data set of cloud water pH measurements for comparison with the model. The global mean observed cloud water pH is 5.2±0.9, compared to 5.0±0.8 in the model, with a range from 3 to 8 depending on the region. The lowest values are over East Asia, and the highest values are over deserts. Cloud water pH over East Asia is low because of large acid inputs (H2SO4 and HNO3), despite NH3 and dust neutralizing 70 % of these inputs. Cloud water pH is typically 4–5 over the US and Europe. Carboxylic acids account for less than 25 % of cloud water H+ in the Northern Hemisphere on an annual basis but 25 %–50 % in the Southern Hemisphere and over 50 % in the southern tropical continents, where they push the cloud water pH below 4.5. Anthropogenic emissions of SO2 and NOx (precursors of H2SO4 and HNO3) are decreasing at northern midlatitudes, but the effect on cloud water pH is strongly buffered by NH4+ and carboxylic acids. The global mean precipitation pH is 5.5 in GEOS-Chem, which is higher than the cloud water pH because of dilution and below-cloud scavenging of NH3 and dust. GEOS-Chem successfully reproduces the annual mean precipitation pH observations in North America, Europe, and eastern Asia. Carboxylic acids, which are undetected in routine observations due to biodegradation, lower the annual mean precipitation pH in these areas by 0.2 units. The acid wet deposition flux to terrestrial ecosystems taking into account the acidifying potential of NO3- and NH4+ in N-saturated ecosystems exceeds 50 meqm-2a-1 in East Asia and the Americas, which would affect sensitive ecosystems. NH4+ is the dominant acidifying species in wet deposition, contributing 41 % of the global acid flux to continents under N-saturated conditions.

scholarly journals Spatiotemporal evaluation of EMEP4UK-WRF v4.3 atmospheric chemistry transport simulations of health-related metrics for NO<sub>2</sub>, O<sub>3</sub>, PM<sub>10</sub>, and PM<sub>2. 5</sub> for 2001–2010

2017 ◽  
Vol 10 (4) ◽  
pp. 1767-1787 ◽  
Author(s):  
Chun Lin ◽  
Mathew R. Heal ◽  
Massimo Vieno ◽  
Ian A. MacKenzie ◽  
Ben G. Armstrong ◽  
...  
Keyword(s):  
Air Pollution ◽  
Atmospheric Chemistry ◽  
Measurement Data ◽  
Transport Processes ◽  
Daily Maximum ◽  
Model Bias ◽  
Model Framework ◽  
Urban Background ◽  
Air Pollution Epidemiology ◽  
Model Measurement

Abstract. This study was motivated by the use in air pollution epidemiology and health burden assessment of data simulated at 5 km  ×  5 km horizontal resolution by the EMEP4UK-WRF v4.3 atmospheric chemistry transport model. Thus the focus of the model–measurement comparison statistics presented here was on the health-relevant metrics of annual and daily means of NO2, O3, PM2. 5, and PM10 (daily maximum 8 h running mean for O3). The comparison was temporally and spatially comprehensive, covering a 10-year period (2 years for PM2. 5) and all non-roadside measurement data from the UK national reference monitor network, which applies consistent operational and QA/QC procedures for each pollutant (44, 47, 24, and 30 sites for NO2, O3, PM2. 5, and PM10, respectively). Two important statistics highlighted in the literature for evaluation of air quality model output against policy (and hence health)-relevant standards – correlation and bias – together with root mean square error, were evaluated by site type, year, month, and day-of-week. Model–measurement statistics were generally better than, or comparable to, values that allow for realistic magnitudes of measurement uncertainties. Temporal correlations of daily concentrations were good for O3, NO2, and PM2. 5 at both rural and urban background sites (median values of r across sites in the range 0.70–0.76 for O3 and NO2, and 0.65–0.69 for PM2. 5), but poorer for PM10 (0.47–0.50). Bias differed between environments, with generally less bias at rural background sites (median normalized mean bias (NMB) values for daily O3 and NO2 of 8 and 11 %, respectively). At urban background sites there was a negative model bias for NO2 (median NMB  =  −29 %) and PM2. 5 (−26 %) and a positive model bias for O3 (26 %). The directions of these biases are consistent with expectations of the effects of averaging primary emissions across the 5 km  ×  5 km model grid in urban areas, compared with monitor locations that are more influenced by these emissions (e.g. closer to traffic sources) than the grid average. The biases are also indicative of potential underestimations of primary NOx and PM emissions in the model, and, for PM, with known omissions in the model of some PM components, e.g. some components of wind-blown dust. There were instances of monthly and weekday/weekend variations in the extent of model–measurement bias. Overall, the greater uniformity in temporal correlation than in bias is strongly indicative that the main driver of model–measurement differences (aside from grid versus monitor spatial representivity) was inaccuracy of model emissions – both in annual totals and in the monthly and day-of-week temporal factors applied in the model to the totals – rather than simulation of atmospheric chemistry and transport processes. Since, in general for epidemiology, capturing correlation is more important than bias, the detailed analyses presented here support the use of data from this model framework in air pollution epidemiology.

scholarly journals Spatiotemporal evaluation of EMEP4UK-WRF v4.3 atmospheric chemistry transport simulations of health-related metrics for NO<sub>2</sub>, O<sub>3</sub>, PM<sub>10</sub> and PM<sub>2.5</sub> for 2001–2010

2016 ◽  
Author(s):  
C. Lin ◽  
M. R. Heal ◽  
M. Vieno ◽  
I. A. MacKenzie ◽  
B. G. Armstrong ◽  
...  
Keyword(s):  
Air Pollution ◽  
Atmospheric Chemistry ◽  
Transport Processes ◽  
Urban Traffic ◽  
Model Bias ◽  
Model Framework ◽  
Urban Background ◽  
Air Pollution Epidemiology ◽  
Pm2.5 And Pm10 ◽  
Model Measurement

Abstract. This study was motivated by the use in air pollution epidemiology and health burden assessment of data simulated at 5 km × 5 km horizontal resolution by the EMEP4UK-WRF v4.3 atmospheric chemistry transport model. Thus the focus of the model-measurement comparison statistics presented here was on the health-relevant metrics of annual and daily means of NO2, O3, PM2.5 and PM10 (daily maximum 8-hour running mean for O3). The comparison was temporally and spatially comprehensive covering a 10-year period (2 years for PM2.5) and all measurement data from the UK national reference monitor network, which applies consistent operational and QC/QA procedures for each pollutant (60, 49, 29 and 35 sites for NO2, O3, PM2.5 and PM10, respectively). The two most important statistics highlighted in the literature for evaluation of air quality model output against policy (and hence health)-relevant standards – correlation and bias – were evaluated by site type, year, month and day-of-week. Model-measurement correlation and bias were generally better than values found in past studies that allowed for measurement uncertainties. Temporal correlations of daily concentrations were good for O3, NO2 and PM2.5 at both rural and urban background sites (median values of r across sites in the range 0.70–0.76 for O3 and NO2, and 0.65–0.69 for PM2.5), but poorer for PM10 (0.47–0.50). Bias differed between environments, with generally less bias at the background sites and least bias at rural background sites (median normalised mean bias (NMB) values for daily O3 and NO2 of 8 % and 11 %, respectively). At urban background sites there was a negative model bias for NO2 (median NMB = −29 %) and PM2.5 (−26 %) and a positive model bias for O3 (26 %). The directions of these biases are consistent with expectations of the effects of averaging primary emissions across the 5 km × 5 km model grid in urban areas, compared with monitor locations that are more influenced by these emissions than the grid average. This effect was particularly pronounced for comparison against urban traffic monitors, which are deliberately located close to strong sources of NOx and PM. The biases are also indicative of potential underestimations of primary NOx and PM emissions in the model, and, for PM, with known omissions in the model of some PM components, e.g. wind-blown dust. There were instances of monthly and weekday/weekend variations in extent of model-measurement bias. Overall, the greater uniformity in temporal correlation than in bias is strongly indicative that the main driver of model-measurement differences (aside from grid vs monitor spatial representivity) was inaccuracy of model emissions (both in annual totals and in the monthly and day-of-week temporal factors applied in the model to the totals) rather than simulation of atmospheric chemistry and transport processes. Since, in general for epidemiology, capturing correlation is more important than bias, the detailed analyses presented here support the use of data from this model framework in air pollution epidemiology.

scholarly journals Intercontinental transport and deposition patterns of atmospheric mercury from anthropogenic emissions

2013 ◽  
Vol 13 (9) ◽  
pp. 25185-25218 ◽  
Author(s):  
L. Chen ◽  
H.-H. Wang ◽  
J.-F. Liu ◽  
W. Zhang ◽  
D. Hu ◽  
...  
Keyword(s):  
North America ◽  
Southeast Asia ◽  
East Asia ◽  
Indian Subcontinent ◽  
Seasonal Pattern ◽  
Atmospheric Mercury ◽  
Anthropogenic Emissions ◽  
Mercury Deposition ◽  
Mercury Emissions ◽  
Source Receptor Relationships

Abstract. Global policies that regulate anthropogenic mercury emissions to the environment require quantitative and comprehensive source–receptor relationships for mercury emissions, transport and deposition among major continental regions. In this study, we use the GEOS-Chem model to establish source–receptor relationships among eleven major continental regions worldwide. Source–receptor relationships for surface mercury concentrations (SMC) show that some regions (e.g. East Asia, the Indian subcontinent and Europe) should be responsible for their local surface Hg(II) and Hg(P) concentrations because of near-field transport and deposition contributions from their local anthropogenic emissions (up to 64% and 71% for Hg(II) and Hg(P), respectively, over East Asia). We define region of primary influence (RPI) and region of secondary influence (RSI) to establish intercontinental influence patterns. Results indicate that East Asia is SMC RPI for almost all other regions, while Europe, Russia and the Indian subcontinent also make some contributions to SMC over some receptor regions because they are dominant RSI source regions. Source–receptor relationships for mercury deposition show that approximately 16% and 17% of dry and wet deposition, respectively, over North America originate from East Asia, indicating that trans-pacific transport of East Asian emissions is the major foreign source of mercury deposition in North America. Europe, Southeast Asia and the Indian subcontinent are also important mercury deposition sources for some receptor regions because they are dominant RSI. We also quantify seasonal variation on mercury deposition contributions over other regions from East Asia. Results show that mercury deposition (including dry and wet) contributions from East Asia over the Northern Hemisphere receptor regions (e.g. North America, Europe, Russia, Middle East and Middle Asia) vary seasonally, with the maximum values in summer and minimum values in winter. The opposite seasonal pattern occurs on mercury dry deposition contributions over Southeast Asia and the Indian subcontinent.

scholarly journals GNAQPMS-Hg v1.0, a global nested atmospheric mercury transport model: model description, evaluation and application to trans-boundary transport of Chinese anthropogenic emissions

2015 ◽  
Vol 8 (9) ◽  
pp. 2857-2876 ◽  
Author(s):  
H. S. Chen ◽  
Z. F. Wang ◽  
J. Li ◽  
X. Tang ◽  
B. Z. Ge ◽  
...  
Keyword(s):  
North America ◽  
East Asia ◽  
Aqueous Phase ◽  
Wet Deposition ◽  
Transport Model ◽  
Atmospheric Mercury ◽  
Model Description ◽  
Anthropogenic Emissions ◽  
Comparison Results ◽  
Western Asia

Abstract. Atmospheric mercury (Hg) is a toxic pollutant and can be transported over the whole globe due to its long lifetime in the atmosphere. For the purpose of assessing Hg hemispheric transport and better characterizing regional Hg pollution, a global nested atmospheric Hg transport model (GNAQPMS-Hg – Global Nested Air Quality Prediction Modeling System for Hg) has been developed. In GNAQPMS-Hg, the gas- and aqueous-phase Hg chemistry representing the transformation among three forms of Hg: elemental mercury (Hg(0)), divalent mercury (Hg(II)), and primary particulate mercury (Hg(P)) are calculated. A detailed description of the model, including mercury emissions, gas- and aqueous-phase chemistry, and dry and wet deposition is given in this study. Worldwide observations including extensive data in China have been collected for model evaluation. Comparison results show that the model reasonably simulates the global mercury budget and the spatiotemporal variation of surface mercury concentrations and deposition. Overall, model predictions of annual total gaseous mercury (TGM) and wet deposition agree with observations within a factor of 2, and within a factor of 5 for oxidized mercury and dry deposition. The model performs significantly better in North America and Europe than in East Asia. This can probably be attributed to the large uncertainties in emission inventories, coarse model resolution and to the inconsistency between the simulation and observation periods in East Asia. Compared to the global simulation, the nested simulation shows improved skill at capturing the high spatial variability of surface Hg concentrations and deposition over East Asia. In particular, the root mean square error (RMSE) of simulated Hg wet deposition over East Asia is reduced by 24 % in the nested simulation. Model sensitivity studies indicate that Chinese primary anthropogenic emissions account for 30 and 62 % of surface mercury concentrations and deposition over China, respectively. Along the rim of the western Pacific, the contributions from Chinese sources are 11 and 15.2 % over the Korean Peninsula, 10.4 and 8.2 % over Southeast Asia, and 5.7 and 5.9 % over Japan. But for North America, Europe and western Asia, the contributions from China are all below 5 %.

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