scholarly journals Improvement and further development in CESM/CAM5: gas-phase chemistry and inorganic aerosol treatments

2014 ◽  
Vol 14 (17) ◽  
pp. 9171-9200 ◽  
Author(s):  
J. He ◽  
Y. Zhang
Keyword(s):  
Air Quality ◽  
Gas Phase ◽  
Power Law ◽  
Global Scale ◽  
Particle Formation ◽  
New Particle Formation ◽  
Gas Phase Chemistry ◽  
Model Version ◽  
Inorganic Aerosol ◽  
Phase Chemistry

Abstract. Gas-phase chemistry and subsequent gas-to-particle conversion processes such as new particle formation, condensation, and thermodynamic partitioning have large impacts on air quality, climate, and public health through influencing the amounts and distributions of gaseous precursors and secondary aerosols. Their roles in global air quality and climate are examined in this work using the Community Earth System Model version 1.0.5 (CESM1.0.5) with the Community Atmosphere Model version 5.1 (CAM5.1) (referred to as CESM1.0.5/CAM5.1). CAM5.1 includes a simple chemistry that is coupled with a 7-mode prognostic Modal Aerosol Model (MAM7). MAM7 includes classical homogenous nucleation (binary and ternary) and activation nucleation (empirical first-order power law) parameterizations, and a highly simplified inorganic aerosol thermodynamics treatment that only simulates particulate-phase sulfate and ammonium. In this work, a new gas-phase chemistry mechanism based on the 2005 Carbon Bond Mechanism for Global Extension (CB05_GE) and several advanced inorganic aerosol treatments for condensation of volatile species, ion-mediated nucleation (IMN), and explicit inorganic aerosol thermodynamics for sulfate, ammonium, nitrate, sodium, and chloride have been incorporated into CESM/CAM5.1-MAM7. Compared to the simple gas-phase chemistry, CB05_GE can predict many more gaseous species, and thus could improve model performance for PM2.5, PM10, PM components, and some PM gaseous precursors such as SO2 and NH3 in several regions as well as aerosol optical depth (AOD) and cloud properties (e.g., cloud fraction (CF), cloud droplet number concentration (CDNC), and shortwave cloud forcing, SWCF) on the global scale. The modified condensation and aqueous-phase chemistry could further improve the prediction of additional variables such as HNO3, NO2, and O3 in some regions, and new particle formation rate (J) and AOD on the global scale. IMN can improve the prediction of secondary PM2.5 components, PM2.5, and PM10 over Europe as well as AOD and CDNC on the global scale. The explicit inorganic aerosol thermodynamics using the ISORROPIA II model improves the prediction of all major PM2.5 components and their gaseous precursors in some regions as well as downwelling shortwave radiation, SWCF, and cloud condensation nuclei at a supersaturation of 0.5% on the global scale. For simulations of 2001–2005 with all the modified and new treatments, the improved model predicts that on global average, SWCF increases by 2.7 W m−2, reducing the normalized mean bias (NMB) of SWCF from −5.4 to 1.2%. Uncertainties in emissions can largely explain the inaccurate prediction of precursor gases (e.g., SO2, NH3, and NO) and primary aerosols (e.g., black carbon and primary organic matter). Additional factors leading to the discrepancies between model predictions and observations include assumptions associated with equilibrium partitioning for fine particles assumed in ISORROPIA II, irreversible gas/particle mass transfer treatment for coarse particles, uncertainties in model treatments such as dust emissions, secondary organic aerosol formation, multi-phase chemistry, cloud microphysics, aerosol–cloud interaction, dry and wet deposition, and model parameters (e.g., accommodation coefficients and prefactors of the nucleation power law) as well as uncertainties in model configuration such as the use of a coarse-grid resolution.

scholarly journals Improvement and further development in CESM/CAM5: gas-phase chemistry and inorganic aerosol treatments

2013 ◽  
Vol 13 (10) ◽  
pp. 27717-27777 ◽  
Author(s):  
J. He ◽  
Y. Zhang
Keyword(s):  
Air Quality ◽  
Gas Phase ◽  
Particle Formation ◽  
Cloud Microphysics ◽  
Specific Humidity ◽  
New Particle Formation ◽  
Gas Phase Chemistry ◽  
Model Version ◽  
Inorganic Aerosol ◽  
Phase Chemistry

Abstract. Gas-phase chemistry and subsequent gas-to-particle conversion processes such as new particle formation, condensation, and thermodynamic partitioning have large impacts on air quality, climate, and public health through influencing the amounts and distributions of gaseous precursors and secondary aerosols. Their roles in global air quality and climate are examined in this work using the Community Earth System Model version 1.0.5 (CESM1.0.5) with the Community Atmosphere Model version 5.1 (CAM5.1) (referred to as CESM1.0.5/CAM5.1). CAM5.1 includes a simple chemistry that is coupled with a 7-mode prognostic Modal Aerosol Model (MAM7). MAM7 includes classical homogenous nucleation (binary and ternary) and activation nucleation (empirical first-order power law) parameterizations, and a highly-simplified inorganic aerosol thermodynamics treatment that only simulates sulfate (SO42−) and ammonium (NH4+). In this work, a new gas-phase chemistry mechanism based on the 2005 Carbon Bond Mechanism for Global Extension (CB05_GE) and several advanced inorganic aerosol treatments for condensation of volatile species, ion-mediated nucleation (IMN), and explicit inorganic aerosol thermodynamics have been incorporated into CESM/CAM5.1-MAM7. Comparing to the simple gas-phase chemistry, CB05_GE can predict many more gaseous species, and improve model performance for PM2.5, PM10, PM2.5 components, and some PM gaseous precursors such as SO2 and NH3 in several regions, as well as aerosol optical depth (AOD) and cloud properties (e.g., cloud fraction (CF), cloud droplet number concentration (CDNC), and shortwave cloud forcing (SWCF)) on globe. The modified condensation and aqueous-phase chemistry further improves the predictions of additional variables such as HNO3, NO2, and O3 in some regions, and new particle formation rate (J) and AOD over globe. IMN can improve the predictions of secondary PM2.5 components, PM2.5, and PM10 over Europe, as well as AOD and CDNC over globe. The explicit inorganic aerosol thermodynamics using ISORROPIA II improves the predictions of all major PM2.5 components and their gaseous precursors in some regions, as well as near-surface temperature and specific humidity, precipitation, downwelling shortwave radiation, SWCF, and cloud condensation nuclei at a supersaturation of 0.5% over globe. With all the modified and new treatments, the improved model predicts that on a global average, SWCF decreases by 2.9 W m−2, reducing the overprediction of SWCF from 7.9% to 0.9%. Uncertainties in emissions can explain largely the inaccurate predictions of precursor gases (e.g., SO2, NH3, and NO) and primary aerosols (e.g., black carbon and primary organic matter). Additional factors leading to discrepancies between model predictions and observations include uncertainties in model treatments such as dust emissions, secondary organic aerosol formation, multiple-phase chemistry, cloud microphysics, aerosol-cloud interaction, and dry and wet deposition.

scholarly journals Gas-phase chemistry in the online multiscale NMMB/BSC Chemical Transport Model: Description and evaluation at global scale

2016 ◽  
Author(s):  
Alba Badia ◽  
Oriol Jorba ◽  
Apostolos Voulgarakis ◽  
Donald Dabdub ◽  
Carlos Pérez García-Pando ◽  
...  
Keyword(s):  
Vertical Distribution ◽  
Gas Phase ◽  
Biomass Burning ◽  
Transport Model ◽  
State Of The Art ◽  
Chemical Transport ◽  
Global Scale ◽  
Chemical Transport Model ◽  
Gas Phase Chemistry ◽  
Phase Chemistry

Abstract. This paper presents a comprehensive description and benchmark evaluation of the tropospheric gas-phase chemistry component of the NMMB/BSC Chemical Transport Model (NMMB/BSC-CTM), an online chemical weather prediction system conceived for both the regional and the global scale. We provide an extensive evaluation of a global annual cycle simulation using a variety of background surface stations (EMEP, WDCGG and CASTNET), ozonesondes (WOUDC, CMD and SHADOZ), aircraft data (MOZAIC and several campaigns), and satellite observations (SCIAMACHY and MOPITT). We also include an extensive discussion of our results in comparison to other state-of-the-art models. The model shows a realistic oxidative capacity across the globe. The seasonal cycle for CO is fairly well represented at different locations (correlations around 0.3–0.7 in surface concentrations), although concentrations are underestimated in spring and winter in the Northern Hemisphere, and are overestimated throughout the year at 800 and 500 hPa in the Southern Hemisphere. Nitrogen species are well represented in almost all locations, particularly NO2 in Europe (RMSE below 9 μg m−3). The modeled vertical distribution of NOx and HNO3 are in excellent agreement with the observed values and the spatial and seasonal trends of tropospheric NO2 columns correspond well to observations from SCIAMACHY, capturing the highly polluted areas and the biomass burning cycle throughout the year. Over Asia, the model underestimates NOx from March to August probably due to an underestimation of NOx emissions in the region. Overall, the comparison of the modelled CO and NO2 with MOPITT and SCIAMACHY observations emphasizes the need for more accurate emission rates from anthropogenic and biomass burning sources (i.e., specification of temporal variability). The resulting ozone (O3) burden (348 Tg) lies within the range of other state-of-the-art global atmospheric chemistry models. The model generally captures the spatial and seasonal trends of background surface O3 and its vertical distribution. However, the model tends to overestimate O3 throughout the troposphere in several stations. This is attributed to an overestimation of CO concentration over the southern hemisphere leading to an excessive production of O3. Overall, O3 correlations range between 0.6 to 0.8 for daily mean values. The overall performance of the NMMB/BSC-CTM is comparable to that of other state-of-the-art global chemical transport models.

scholarly journals Technical Note: simulation of detailed aerosol chemistry on the global scale using MECCA-AERO

2007 ◽  
Vol 7 (2) ◽  
pp. 3301-3331
Author(s):  
A. Kerkweg ◽  
R. Sander ◽  
H. Tost ◽  
P. Jöckel ◽  
J. Lelieveld
Keyword(s):  
Gas Phase ◽  
Particle Number ◽  
Global Scale ◽  
Technical Note ◽  
Double Counting ◽  
Dynamical Models ◽  
Aerosol Chemistry ◽  
Gas Phase Chemistry ◽  
Phase Chemistry

Abstract. We present the MESSy submodel MECCA-AERO, which simulates both aerosol and gas phase chemistry with the same mechanism. Including the aerosol phase into the chemistry mechanism increases the stiffness of the resulting set of differential equations. The numerical aspects of the approach followed in MECCA-AERO are presented. MECCA-AERO requires input of an aerosol dynamical/microphysical model to provide the aerosol size and particle number information of the modes/bins for which the chemistry is explicitly calculated. Additional precautions are required to avoid the double counting of processes, especially for sulphate in the aerosol dynamical and the chemistry model. This coupling is explained in detail. To illustrate the capabilities of the new aerosol submodel, examples for species usually treated in aerosol dynamical models are shown. The aerosol chemistry as provided by MECCA-AERO is very sumptuous and not readily applicable for long-term simulations, though it provides a reference to evaluate simplified approaches.

scholarly journals Modelling the contribution of biogenic volatile organic compounds to new particle formation in the Jülich plant atmosphere chamber

2015 ◽  
Vol 15 (18) ◽  
pp. 10777-10798 ◽  
Author(s):  
P. Roldin ◽  
L. Liao ◽  
D. Mogensen ◽  
M. Dal Maso ◽  
A. Rusanen ◽  
...  
Keyword(s):  
Gas Phase ◽  
Organic Compounds ◽  
Particle Surface ◽  
Particle Formation ◽  
Heterogeneous Reactions ◽  
Chemical Mechanism ◽  
Particle Phase ◽  
New Particle Formation ◽  
Aerosol Dynamics ◽  
Phase Chemistry

Abstract. We used the Aerosol Dynamics gas- and particle-phase chemistry model for laboratory CHAMber studies (ADCHAM) to simulate the contribution of BVOC plant emissions to the observed new particle formation during photooxidation experiments performed in the Jülich Plant-Atmosphere Chamber and to evaluate how well smog chamber experiments can mimic the atmospheric conditions during new particle formation events. ADCHAM couples the detailed gas-phase chemistry from Master Chemical Mechanism with a novel aerosol dynamics and particle phase chemistry module. Our model simulations reveal that the observed particle growth may have either been controlled by the formation rate of semi- and low-volatility organic compounds in the gas phase or by acid catalysed heterogeneous reactions between semi-volatility organic compounds in the particle surface layer (e.g. peroxyhemiacetal dimer formation). The contribution of extremely low-volatility organic gas-phase compounds to the particle formation and growth was suppressed because of their rapid and irreversible wall losses, which decreased their contribution to the nano-CN formation and growth compared to the atmospheric situation. The best agreement between the modelled and measured total particle number concentration (R2 > 0.95) was achieved if the nano-CN was formed by kinetic nucleation involving both sulphuric acid and organic compounds formed from OH oxidation of BVOCs.

scholarly journals Technical Note: Simulation of detailed aerosol chemistry on the global scale using MECCA-AERO

2007 ◽  
Vol 7 (11) ◽  
pp. 2973-2985 ◽  
Author(s):  
A. Kerkweg ◽  
R. Sander ◽  
H. Tost ◽  
P. Jöckel ◽  
J. Lelieveld
Keyword(s):  
Gas Phase ◽  
Particle Number ◽  
Global Scale ◽  
Technical Note ◽  
Double Counting ◽  
Dynamical Models ◽  
Aerosol Chemistry ◽  
Gas Phase Chemistry ◽  
Phase Chemistry

Abstract. We present the MESSy submodel MECCA-AERO, which simulates both aerosol and gas phase chemistry within one comprehensive mechanism. Including the aerosol phase into the chemistry mechanism increases the stiffness of the resulting set of differential equations. The numerical aspects of the approach followed in MECCA-AERO are presented. MECCA-AERO requires input of an aerosol dynamical/microphysical model to provide the aerosol size and particle number information of the modes/bins for which the chemistry is explicitly calculated. Additional precautions are required to avoid the double counting of processes, especially for sulphate in the aerosol dynamical and the chemistry model. This coupling is explained in detail. To illustrate the capabilities of the new aerosol submodel, examples for species usually treated in aerosol dynamical models are shown. The aerosol chemistry as provided by MECCA-AERO is very sumptuous and not readily applicable for long-term simulations, though it provides a reference to evaluate simplified approaches.

scholarly journals GNAQPMS v1.1: accelerating the Global Nested Air Quality Prediction Modeling System (GNAQPMS) on Intel Xeon Phi processors

2017 ◽  
Vol 10 (8) ◽  
pp. 2891-2904 ◽  
Author(s):  
Hui Wang ◽  
Huansheng Chen ◽  
Qizhong Wu ◽  
Junmin Lin ◽  
Xueshun Chen ◽  
...  
Keyword(s):  
Air Quality ◽  
Gas Phase ◽  
Quality Prediction ◽  
Xeon Phi ◽  
Prediction Modeling ◽  
Gas Phase Chemistry ◽  
Air Quality Prediction ◽  
Parallel Mode ◽  
Phase Chemistry ◽  
Intel Xeon

Abstract. The Global Nested Air Quality Prediction Modeling System (GNAQPMS) is the global version of the Nested Air Quality Prediction Modeling System (NAQPMS), which is a multi-scale chemical transport model used for air quality forecast and atmospheric environmental research. In this study, we present the porting and optimisation of GNAQPMS on a second-generation Intel Xeon Phi processor, codenamed Knights Landing (KNL). Compared with the first-generation Xeon Phi coprocessor (codenamed Knights Corner, KNC), KNL has many new hardware features such as a bootable processor, high-performance in-package memory and ISA compatibility with Intel Xeon processors. In particular, we describe the five optimisations we applied to the key modules of GNAQPMS, including the CBM-Z gas-phase chemistry, advection, convection and wet deposition modules. These optimisations work well on both the KNL 7250 processor and the Intel Xeon E5-2697 V4 processor. They include (1) updating the pure Message Passing Interface (MPI) parallel mode to the hybrid parallel mode with MPI and OpenMP in the emission, advection, convection and gas-phase chemistry modules; (2) fully employing the 512 bit wide vector processing units (VPUs) on the KNL platform; (3) reducing unnecessary memory access to improve cache efficiency; (4) reducing the thread local storage (TLS) in the CBM-Z gas-phase chemistry module to improve its OpenMP performance; and (5) changing the global communication from writing/reading interface files to MPI functions to improve the performance and the parallel scalability. These optimisations greatly improved the GNAQPMS performance. The same optimisations also work well for the Intel Xeon Broadwell processor, specifically E5-2697 v4. Compared with the baseline version of GNAQPMS, the optimised version was 3.51 × faster on KNL and 2.77 × faster on the CPU. Moreover, the optimised version ran at 26 % lower average power on KNL than on the CPU. With the combined performance and energy improvement, the KNL platform was 37.5 % more efficient on power consumption compared with the CPU platform. The optimisations also enabled much further parallel scalability on both the CPU cluster and the KNL cluster scaled to 40 CPU nodes and 30 KNL nodes, with a parallel efficiency of 70.4 and 42.2 %, respectively.

scholarly journals MP CBM-Z V1.0: design for a new Carbon Bond Mechanism Z (CBM-Z) gas-phase chemical mechanism architecture for next-generation processors

2019 ◽  
Vol 12 (2) ◽  
pp. 749-764
Author(s):  
Hui Wang ◽  
Junmin Lin ◽  
Qizhong Wu ◽  
Huansheng Chen ◽  
Xiao Tang ◽  
...  
Keyword(s):  
Air Quality ◽  
Gas Phase ◽  
Air Quality Model ◽  
Quality Model ◽  
Gas Phase Chemistry ◽  
Phase Chemistry ◽  
Bond Mechanism ◽  
Chemistry Module ◽  
Phase Chemical ◽  
Intel Xeon

Abstract. Precise and rapid air quality simulations and forecasting are limited by the computational performance of the air quality model used, and the gas-phase chemistry module is the most time-consuming function in the air quality model. In this study, we designed a new framework for the widely used the Carbon Bond Mechanism Z (CBM-Z) gas-phase chemical kinetics kernel to adapt the single-instruction, multiple-data (SIMD) technology in next-generation processors to improve its calculation performance. The optimization implements the fine-grain level parallelization of CBM-Z by improving its vectorization ability. Through constructing loops and integrating the main branches, e.g., diverse chemistry sub-schemes, multiple spatial points in the model can be operated simultaneously on vector processing units (VPUs). Two generation CPUs – Intel Xeon E5-2680 V4 CPU and Intel Xeon Gold 6132 – and Intel Xeon Phi 7250 Knights Landing (KNL) are used as the benchmark processors. The validation of the CBM-Z module outputs indicates that the relative bias reaches a maximum of 0.025 % after 10 h integration with -fp-model fast =1 compile flag. The results of the module test show that the Multiple-Points CBM-Z (MP CBM-Z) resulted in 5.16× and 8.97× speedup on a single core of Intel Xeon E5-2680 V4 and Intel Xeon Gold 6132 CPUs, respectively, and KNL had a speedup of 3.69× compared with the performance of CBM-Z on the Intel Xeon E5-2680 V4 platform. For the single-node tests, the speedup on the two generation CPUs can reach 104.63× and 198.50× using message passing interface (MPI) and 101.02× and 194.60× using OpenMP, and the speedup on the KNL node can reach 175.23× using MPI and 167.45× using OpenMP. The speedup of the optimized CBM-Z is approximately 40 % higher on a one-socket KNL platform than on a two-socket Broadwell platform and about 13 %–16 % lower than on a two-socket Skylake platform. We also tested a three-dimensional chemistry transport model (CTM) named Nested Air Quality Prediction Model System (NAQPMS) equipped with the MP CBM-Z. The tests illustrate an obvious improvement on the performance for the CTM after adopting the MP CBM-Z. The results show that the MP CBM-Z leads to a speedup of 3.32 and 1.96 for the gas-phase chemistry module and the CTM on the Intel Xeon E5-2680 platform. Moreover, on the new Intel Xeon Gold 6132 platform, the MP CBM-Z gains 4.90× and 2.22× speedups for the gas-phase chemistry module and the whole CTM. For the KNL, the MP CBM-Z enables a 3.52× speedup for the gas-phase chemistry module, but the whole model lost 24.10 % performance compared to the CPU platform due to the poor performance of other modules. In addition, since this optimization seeks to improve the utilization of the VPU, the model is more suitable for the new generation processors adopting the more advanced SIMD technology. The results of our tests already show that the benefit of updating CPU improved by about 47 % by using the MP CBM-Z since the optimized code has better adaptability for the new hardware. This work improves the performance of the CBM-Z chemical kinetics kernel as well as the calculation efficiency of the air quality model, which can directly improve the practical value of the air quality model in scientific simulations and routine forecasting.

scholarly journals The impact of different nitrous acid sources in the air quality levels of the Iberian Peninsula

2010 ◽  
Vol 10 (11) ◽  
pp. 28183-28230 ◽  
Author(s):  
M. Gonçalves ◽  
D. Dabdub ◽  
W. L. Chang ◽  
F. Saiz ◽  
O. Jorba ◽  
...  
Keyword(s):  
Air Quality ◽  
Iberian Peninsula ◽  
Gas Phase ◽  
Urban Areas ◽  
Nitrous Acid ◽  
Quality Models ◽  
Chemical Mechanisms ◽  
Gas Phase Chemistry ◽  
Secondary Pollutants ◽  
Phase Chemistry

Abstract. Hydroxyl radical (OH) is a primary oxidant in the atmosphere and affects both gas-phase pollutants and particulate matter levels. Nitrous acid (HONO) acts as an important source of OH in the urban atmosphere. Therefore it is important to account accurately for HONO sources within air quality models in order to predict air pollution dynamics. HONO observations in urban areas are characterized by high concentrations at night and low concentrations around midday. Existing gas-phase chemical mechanisms do not reproduce the observed HONO levels, suggesting a lack of sources, such as direct emissions or heterogeneous reactions. Specific HONO emission rates, heterogeneous chemical mechanisms leading to its formation and related kinetics are still unclear. Therefore, most air quality models consider exclusively gas-phase chemistry related to HONO. This work applies the WRF-ARW/HERMES/CMAQ modeling system to quantify the effect of the addition of HONO sources in the predictability of HONO profiles, and its subsequent effect on secondary pollutants formation (mainly O3 and PM2.5). The modeling episode is based on a 2004 severe summertime pollution event in the Iberian Peninsula, using high resolution of 4 × 4 km2. Two different parameterizations for emissions and the hydrolysis of NO2 on wet surfaces are added as HONO sources in the atmosphere. Emissions have the largest impact on HONO levels, especially in urban areas, where they can contribute from 66% to 94% to the HONO peak concentration. Additionally, in urban environments, NO2 hydrolysis on building and vegetation surfaces contributes up to 30% to the HONO peak. Both, the available surface area and the relative humidity must be included as parameters affecting the NO2 hydrolysis kinetics. As a result, NO2 hydrolysis is negligible on aerosol surfaces, due to the small surface area available for reaction, and it is more effective in producing HONO below high relative humidity conditions. The addition of HONO sources affects the concentration of secondary pollutants. In particular, major changes are produced in the early morning, due to the higher OH release via HONO photolysis. Significant changes in PM2.5 concentrations are predicted, that can be 16% (2.6 μg m−3) higher in the new scenarios. When accounting for HONO sources, nitrate levels increase especially in urban areas and sulfates in areas downwind from conventional power plants in the Iberian Peninsula. Also, O3 peak concentrations are slightly affected (from 0.7 to 4 ppb, 1% to 4.5%). The improvement of the HONO sources representation within air quality models produces changes in O3 peak predictions and significantly affects the reaction pathways leading to aerosols formation. Therefore, HONO sources other than gas-phase chemistry should be accurately included within modeling frameworks.

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