scholarly journals Global modeling of heterogeneous hydroxymethanesulfonate chemistry

2020 ◽  
Author(s):  
Shaojie Song ◽  
Tao Ma ◽  
Yuzhong Zhang ◽  
Lu Shen ◽  
Pengfei Liu ◽  
...  
Keyword(s):  
Transport Model ◽  
Seasonal Pattern ◽  
Field Measurements ◽  
Organosulfur Compound ◽  
Northern China ◽  
Molar Ratio ◽  
Chemical Transport Model ◽  
Global Modeling ◽  
Sulfur Chemistry ◽  
Key Factor

Abstract. Hydroxymethanesulfonate (HMS) has recently been identified as an abundant organosulfur compound in aerosols during winter haze episodes in northern China. It has also been detected in other regions, although the concentrations are low. Because of the sparse field measurements, the global significance of HMS and its spatial and seasonal patterns remain unclear. Here, we implement HMS chemistry into the GEOS-Chem chemical transport model and conduct multiple global simulations. The developed model accounts for cloud entrainment and gas–aqueous mass transfer within the rate expressions for heterogeneous sulfur chemistry. Our simulations can generally reproduce the available HMS observations, and show that East Asia has the highest HMS concentration, followed by Europe and North America. The simulated HMS shows a seasonal pattern with higher values in the colder period. Photochemical oxidizing capacity affects the competition of formaldehyde with oxidants (such as ozone and hydrogen peroxide) for sulfur dioxide and is a key factor influencing the seasonality of HMS. The highest average HMS concentration (1–3 μg m−3) and HMS/sulfate molar ratio (0.1–0.2) are found in northern China winter. The simulations suggest that aqueous clouds act as the major medium for HMS chemistry while aerosol liquid water may play a role if its rate constant for HMS formation is greatly enhanced compared to cloud water.

scholarly journals Global modeling of heterogeneous hydroxymethanesulfonate chemistry

2021 ◽  
Vol 21 (1) ◽  
pp. 457-481
Author(s):  
Shaojie Song ◽  
Tao Ma ◽  
Yuzhong Zhang ◽  
Lu Shen ◽  
Pengfei Liu ◽  
...  
Keyword(s):  
Transport Model ◽  
Seasonal Pattern ◽  
Field Measurements ◽  
Organosulfur Compound ◽  
Northern China ◽  
Molar Ratio ◽  
Chemical Transport Model ◽  
Global Modeling ◽  
Sulfur Chemistry ◽  
Key Factor

Abstract. Hydroxymethanesulfonate (HMS) has recently been identified as an abundant organosulfur compound in aerosols during winter haze episodes in northern China. It has also been detected in other regions although the concentrations are low. Because of the sparse field measurements, the global significance of HMS and its spatial and seasonal patterns remain unclear. Here, we modify and add to the implementation of HMS chemistry in the GEOS-Chem chemical transport model and conduct multiple global simulations. The model accounts for cloud entrainment and gas–aqueous mass transfer within the rate expressions for heterogeneous sulfur chemistry. Our simulations can generally reproduce quantitative HMS observations from Beijing and show that East Asia has the highest HMS concentration, followed by Europe and North America. The simulated HMS shows a seasonal pattern with higher values in the colder period. Photochemical oxidizing capacity affects the competition of formaldehyde with oxidants (such as ozone and hydrogen peroxide) for sulfur dioxide and is a key factor influencing the seasonality of HMS. The highest average HMS concentration (1–3 µg m−3) and HMS ∕ sulfate molar ratio (0.1–0.2) are found in northern China in winter. The simulations suggest that aqueous clouds act as the major medium for HMS chemistry while aerosol liquid water may play a role if its rate constant for HMS formation is greatly enhanced compared to cloud water.

scholarly journals Aerosol concentrations variability over China: two distinct leading modes

2020 ◽  
Author(s):  
Juan Feng ◽  
Jianlei Zhu ◽  
Jianping Li ◽  
Hong Liao
Keyword(s):  
Transport Model ◽  
Eastern China ◽  
Practical Importance ◽  
Negative Temperature ◽  
Northern China ◽  
Dipole Mode ◽  
Chemical Transport Model ◽  
Boundary Layer Height ◽  
The North ◽  
The North Atlantic Oscillation

Abstract. Understanding the variability in aerosol concentrations (AC) over China is a scientific challenge and is of practical importance. The present study explored the month-to-month variability in AC over China based on simulations of an atmospheric chemical transport model with a fixed emissions level. The month-to-month variability in AC over China is dominated by two principal modes: the first leading mono-pole mode and the second meridional dipole mode. The mono-pole mode mainly indicates enhanced AC over eastern China, and the dipole mode displays a south–north out-of-phase pattern. The two leading modes are associated with different climatic systems. The mono-pole mode relates to the 3-month leading El Niño–South Oscillation (ENSO), while the dipole mode connects with the simultaneous variation in the North Atlantic Oscillation (NAO) or the Northern Hemisphere Annular Mode (NAM). The associated anomalous dynamic and thermal impacts of the two climatic variabilities are examined to explain their contributions to the formation of the two modes. For the mono-pole mode, the preceding ENSO is associated with anomalous convergence, decreased planetary boundary layer height (PBLH), and negative temperature anomalies, which are unfavorable for emissions. For the dipole mode, the positive NAO is accompanied by opposite anomalies in the convergence, PBLH, and temperature over southern and northern China, paralleling the spatial formation of the mode. This result suggests that the variations originating from the tropical Pacific and extratropical atmospheric systems contribute to the dominant variabilities of AC over China.

scholarly journals Aerosol concentrations variability over China: two distinct leading modes

2020 ◽  
Vol 20 (16) ◽  
pp. 9883-9893 ◽  
Author(s):  
Juan Feng ◽  
Jianlei Zhu ◽  
Jianping Li ◽  
Hong Liao
Keyword(s):  
Transport Model ◽  
Southern Oscillation ◽  
Eastern China ◽  
Practical Importance ◽  
Negative Temperature ◽  
Northern China ◽  
Dipole Mode ◽  
Chemical Transport Model ◽  
Boundary Layer Height ◽  
The North

Abstract. Understanding the variability in aerosol concentrations (ACs) over China is a scientific challenge and is of practical importance. The present study explored the month-to-month variability in ACs over China based on simulations of an atmospheric chemical transport model with a fixed emissions level. The month-to-month variability in ACs over China is dominated by two principal modes: the first leading monopole mode and the second meridional dipole mode. The monopole mode mainly indicates enhanced ACs over eastern China, and the dipole mode displays a south–north out-of-phase pattern. The two leading modes are associated with different climatic systems. The monopole mode relates to the 3 months leading the El Niño–Southern Oscillation (ENSO), while the dipole mode connects with the simultaneous variation in the North Atlantic Oscillation (NAO) or the Northern Hemisphere Annular Mode (NAM). The associated anomalous dynamic and thermal impacts of the two climatic variabilities are examined to explain their contributions to the formation of the two modes. For the monopole mode, the preceding ENSO is associated with anomalous convergence, decreased planetary boundary layer height (PBLH), and negative temperature anomalies over eastern China, which are unfavorable for emissions. For the dipole mode, the positive NAO is accompanied by opposite anomalies in the convergence, PBLH, and temperature over southern and northern China, paralleling the spatial formation of the mode. This result suggests that the variations originating from the tropical Pacific and extratropical atmospheric systems contribute to the dominant variabilities of ACs over China.

scholarly journals Current estimates of biogenic emissions from Eucalypts uncertain for Southeast Australia

2016 ◽  
Author(s):  
K. M. Emmerson ◽  
I. E. Galbally ◽  
A. B. Guenther ◽  
C. Paton-Walsh ◽  
E.-A. Guerette ◽  
...  
Keyword(s):  
Transport Model ◽  
Chemical Species ◽  
Field Measurements ◽  
Oxidation Products ◽  
Biogenic Emissions ◽  
Emission Rates ◽  
Chemical Transport Model ◽  
Southeast Australia ◽  
Unusual Position ◽  
Adult Trees

Abstract. The biogenic emissions of isoprene and monoterpenes are one of the main drivers of atmospheric photochemistry, including oxidant and secondary organic aerosol production. In this paper, the emission rates of isoprene and monoterpenes from Australian vegetation are investigated for the first time using the Model of Emissions of Gases and Aerosols from Nature version 2.1 (MEGANv2.1), the CSIRO chemical transport model, and atmospheric observations of isoprene, monoterpenes and isoprene oxidation products (methacrolein and methyl-vinyl-ketone). Observations from four field campaigns during three different seasons are used, covering urban, coastal suburban and inland forest areas. The observed concentrations of isoprene and monoterpenes were of a broadly similar magnitude, which may indicate that southeast Australia holds an unusual position where neither chemical species dominates. The model results overestimate the observed atmospheric concentrations of isoprene (up to a factor of 6) and underestimate the monoterpene concentrations (up to a factor of 4). This may occur because the emission rates currently used in MEGANv2.1 for Australia are drawn mainly from young Eucalypt trees (< 7 years), which may emit more isoprene than adult trees. There is no single increase/decrease factor for the emissions which suits all seasons and conditions studied. There is a need for further field measurements of in-situ isoprene and monoterpene emission fluxes in Australia.

scholarly journals Adjoint sensitivity of global cloud droplet number to aerosol and dynamical parameters

2012 ◽  
Vol 12 (5) ◽  
pp. 12081-12117 ◽  
Author(s):  
V. A. Karydis ◽  
S. L. Capps ◽  
A. G. Russell ◽  
A. Nenes
Keyword(s):  
Transport Model ◽  
Circulation Model ◽  
Cloud Droplet ◽  
Sea Salt ◽  
Global Circulation Model ◽  
Uptake Coefficient ◽  
Chemical Transport Model ◽  
Adjoint Sensitivity ◽  
Global Modeling ◽  
Aerosol Modeling

Abstract. We present the development of the adjoint of a comprehensive cloud droplet formation parameterization for use in aerosol-cloud-climate interaction studies. The adjoint efficiently and accurately calculates the sensitivity of cloud droplet number concentration (CDNC) to all parameterization inputs (e.g., updraft velocity, water uptake coefficient, aerosol number and hygroscopicity) with a single execution. The droplet adjoint is then integrated within three dimensional (3-D) aerosol modeling frameworks to quantify the sensitivity of CDNC formation globally to each parameter. Sensitivities are computed for year-long executions of the NASA Global Modeling Initiative (GMI) Chemical Transport Model (CTM), using wind fields computed with the Goddard Institute for Space Studies (GISS) Global Circulation Model (GCM) II', and the GEOS-Chem CTM, driven by meteorological input from the Goddard Earth Observing System (GEOS) of the NASA Global Modeling and Assimilation Office (GMAO). We find that over polluted (pristine) areas, CDNC is more sensitive to updraft velocity and uptake coefficient (aerosol number and hygroscopicity). Over the oceans of the Northern Hemisphere, addition of anthropogenic or biomass burning aerosol increases predicted CDNC in contrast to coarse-mode sea salt which tends to decrease CDNC. Over the Southern Oceans, CDNC is most sensitive to sea salt, which is the main aerosol component in the area. Globally, CDNC is predicted to be less sensitive to changes in the hygroscopicity of the aerosols than in their concentration with the exception of dust where CDNC is very sensitive to particle hydrophilicity over arid areas. Regionally, the sensitivities differ considerably between the two frameworks and quantitatively reveal why the models differ considerably in their indirect forcing estimates.

scholarly journals Trans-Pacific transport of Asian dust and CO: accumulation of biomass burning CO in the subtropics and dipole structure of transport

2009 ◽  
Vol 9 (3) ◽  
pp. 12899-12926 ◽  
Author(s):  
J. Nam ◽  
Y. Wang ◽  
C. Luo ◽  
D. A. Chu
Keyword(s):  
Biomass Burning ◽  
Transport Model ◽  
High Sensitivity ◽  
Chemical Transport Model ◽  
Pressure System ◽  
Transport Pathways ◽  
Dust Transport ◽  
Dipole Structure ◽  
Modis Aod ◽  
Key Factor

Abstract. In May 2003, both MODIS aerosol optical depth (AOD) and carbon monoxide (CO) measurements from MOPITT show significant trans-Pacific transport to North America. We apply the global chemical transport model, GEOS-Chem, to analyze the main features of the long-range transport events. Enhancements of MOPITT CO over the tropical Pacific are much broader than MODIS AOD enhancements. We find in model simulations that a substantial fraction of the CO enhancements in the subtropics in May is due to biomass burning in Southeast Asia in April. Biomass burning CO was recirculated into the subtropical high-pressure system and lingered for a much longer period than aerosols transported at higher latitudes. Simulated AOD enhancements are due to a combination of dust, sulfate, and organic and elemental carbons. Dust contribution dominates the AOD enhancements in early May. Model results indicate that dust transport takes place at higher altitude than the other aerosols. MODIS observations indicate a bias in model simulated pathway of dust AOD transport. Sensitivities of dust transport pathways are analyzed in the model. The dipole structure of transport over the Pacific is found to be the key factor leading to the high sensitivity of simulated transport pathways to source location and wind field.

scholarly journals Simulating secondary organic aerosol from missing diesel-related intermediate-volatility organic compound emissions during the Clean Air for London (ClearfLo) campaign

2016 ◽  
Vol 16 (10) ◽  
pp. 6453-6473 ◽  
Author(s):  
Riinu Ots ◽  
Dominique E. Young ◽  
Massimo Vieno ◽  
Lu Xu ◽  
Rachel E. Dunmore ◽  
...  
Keyword(s):  
Organic Compound ◽  
Secondary Organic Aerosol ◽  
Transport Model ◽  
Field Measurements ◽  
Organic Aerosol ◽  
Chemical Transport Model ◽  
Total Particulate Matter ◽  
Clean Air ◽  
The Uk ◽  
The Impact

Abstract. We present high-resolution (5 km  ×  5 km) atmospheric chemical transport model (ACTM) simulations of the impact of newly estimated traffic-related emissions on secondary organic aerosol (SOA) formation over the UK for 2012. Our simulations include additional diesel-related intermediate-volatility organic compound (IVOC) emissions derived directly from comprehensive field measurements at an urban background site in London during the 2012 Clean Air for London (ClearfLo) campaign. Our IVOC emissions are added proportionally to VOC emissions, as opposed to proportionally to primary organic aerosol (POA) as has been done by previous ACTM studies seeking to simulate the effects of these missing emissions. Modelled concentrations are evaluated against hourly and daily measurements of organic aerosol (OA) components derived from aerosol mass spectrometer (AMS) measurements also made during the ClearfLo campaign at three sites in the London area. According to the model simulations, diesel-related IVOCs can explain on average  ∼  30 % of the annual SOA in and around London. Furthermore, the 90th percentile of modelled daily SOA concentrations for the whole year is 3.8 µg m−3, constituting a notable addition to total particulate matter. More measurements of these precursors (currently not included in official emissions inventories) is recommended. During the period of concurrent measurements, SOA concentrations at the Detling rural background location east of London were greater than at the central London location. The model shows that this was caused by an intense pollution plume with a strong gradient of imported SOA passing over the rural location. This demonstrates the value of modelling for supporting the interpretation of measurements taken at different sites or for short durations.

scholarly journals Correlations between PM2.5 and Ozone over China and Associated Underlying Reasons

Atmosphere ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 352 ◽  
Author(s):  
Jia Zhu ◽  
Lei Chen ◽  
Hong Liao ◽  
Ruijun Dang
Keyword(s):  
Transport Model ◽  
Southern China ◽  
Correlation Coefficients ◽  
Northern China ◽  
Inhibitory Effect ◽  
Photochemical Activity ◽  
Chemical Transport Model ◽  
Promoting Effect ◽  
Interesting Phenomenon ◽  
Cold Environments

We investigated the spatial-temporal characteristics of the correlations between observed PM2.5 and O3 over China at a national-scale level, and examined the underlying reasons for the varying PM2.5–O3 correlations by using a chemical transport model. The PM2.5 concentrations were positively correlated with O3 concentrations for most regions and seasons over China, while negative correlations were mainly observed in northern China during winter. The strongest positive PM2.5–O3 correlations with correlation coefficients (r) larger than +0.7 existed in southern China during July, and the strongest negative correlations (r < −0.5) were observed in northern China during January. It was a very interesting phenomenon that the positive PM2.5–O3 correlations prevailed for high air temperature samples, while the negative correlations were generally found in cold environments. Together, the effective inhibitory effect of PM2.5 on O3 generation by reducing photolysis rates and the strong titration effect of freshly emitted NO with O3 contributed to the strongest negative PM2.5–O3 correlations in northern China during January (i.e., in cold environments). The strongest positive correlations in southern China during July (i.e., at high temperature), however, were mainly attributed to the promoting effect of high O3 concentration and active photochemical activity on secondary particle formation.

scholarly journals Adjoint sensitivity of global cloud droplet number to aerosol and dynamical parameters

2012 ◽  
Vol 12 (19) ◽  
pp. 9041-9055 ◽  
Author(s):  
V. A. Karydis ◽  
S. L. Capps ◽  
A. G. Russell ◽  
A. Nenes
Keyword(s):  
Transport Model ◽  
Circulation Model ◽  
Cloud Droplet ◽  
Sea Salt ◽  
Global Circulation Model ◽  
Uptake Coefficient ◽  
Chemical Transport Model ◽  
Adjoint Sensitivity ◽  
Global Modeling ◽  
Aerosol Modeling

Abstract. We present the development of the adjoint of a comprehensive cloud droplet formation parameterization for use in aerosol-cloud-climate interaction studies. The adjoint efficiently and accurately calculates the sensitivity of cloud droplet number concentration (CDNC) to all parameterization inputs (e.g., updraft velocity, water uptake coefficient, aerosol number and hygroscopicity) with a single execution. The adjoint is then integrated within three dimensional (3-D) aerosol modeling frameworks to quantify the sensitivity of CDNC formation globally to each parameter. Sensitivities are computed for year-long executions of the NASA Global Modeling Initiative (GMI) Chemical Transport Model (CTM), using wind fields computed with the Goddard Institute for Space Studies (GISS) Global Circulation Model (GCM) II', and the GEOS-Chem CTM, driven by meteorological input from the Goddard Earth Observing System (GEOS) of the NASA Global Modeling and Assimilation Office (GMAO). We find that over polluted (pristine) areas, CDNC is more sensitive to updraft velocity and uptake coefficient (aerosol number and hygroscopicity). Over the oceans of the Northern Hemisphere, addition of anthropogenic or biomass burning aerosol is predicted to increase CDNC in contrast to coarse-mode sea salt which tends to decrease CDNC. Over the Southern Oceans, CDNC is most sensitive to sea salt, which is the main aerosol component of the region. Globally, CDNC is predicted to be less sensitive to changes in the hygroscopicity of the aerosols than in their concentration with the exception of dust where CDNC is very sensitive to particle hydrophilicity over arid areas. Regionally, the sensitivities differ considerably between the two frameworks and quantitatively reveal why the models differ considerably in their indirect forcing estimates.

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