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Featured researches published by Weixi Gong.


Tellus B | 2011

Effects of black carbon aging on air quality predictions and direct radiative forcing estimation

Sung Hoon Park; S. L. Gong; V. S. Bouchet; Weixi Gong; P. A. Makar; M. D. Moran; Craig Stroud; J. Zhang

An aging scheme for black carbon (BC) aerosol was implemented into a regional air-quality forecast model to study the impact of BC aging on air quality predictions. Three different assumptions for the mixing state of BC—external mixture, internal mixture and gradual aging—were used to simulate the distribution of BC particles over North America in April 2002. Cloud –condensation nuclei number and BC wet deposition rate increased significantly and BC mass column loading decreased as a result of BC aging. With the gradual aging process incorporated into the model, the comparison of ground level BC concentration predictions with surface observations was slightly improved. Estimation of the average direct radiative forcing of BC over the spatial domain of this study showed that the factor of direct forcing enhancement by BC aging was much smaller than the mixing state effect factor. The effect of increased wet deposition due to aging compensated partially for the effect of increased absorbance suggesting that the change in the hygroscopic properties of BC due to aging must be taken into account to quantify accurately the effect of BC aging on climate.


Archive | 2008

Comprehensive Surface-Based Performance Evaluation of a Size- and Composition-Resolved Regional Particulate-Matter Model for a One-Year Simulation

M. D. Moran; Qiong Zheng; M. Samaali; J. Narayan; R. Pavlovic; Sophie Cousineau; V. S. Bouchet; Mourad Sassi; P. A. Makar; Weixi Gong; S. L. Gong; Craig Stroud; Annie Duhamel

A comprehensive performance evaluation has been carried out for the first annual simulation made with AURAMS, a size- and composition-resolved, off-line, regional particulate-matter (PM) modelling system. The year simulated was 2002, the modelling domain covered most of North America, and the horizontal grid size was 42 km. The large evaluation data set consisted of filter-based and con- tinuous surface air-chemistry measurements made by five Canadian and U.S. net- works and precipitation-chemistry measurements made by seven Canadian and U.S. networks. Completeness criteria were used to exclude stations with incomplete records, and units conversions were performed to maximize uniformity and com- parability. Quantities used in the performance evaluation included annual air con- centrations of SO2, NO2, O3, HNO3, PM2.5, PM10, PM2.5-SO4, PM2.5-NO3, PM2.5-NH4, PM2.5-CM, PM2.5-EC, and PM2.5-TOM, and annual concentrations in precipitation of SO4 = , NO3 - , and NH4 + . The extensive evaluation has allowed inferences about factors contributing to some model weaknesses.


Archive | 2014

Current and Future Developments in Numerical Air Quality Forecasting in Canada

S. Ménard; Sylvie Gravel; M. D. Moran; H. Landry; A. Kallaur; R. Pavlovic; P. A. Makar; Craig Stroud; Weixi Gong; Jack Chen; David Anselmo; Sophie Cousineau

Environment Canada produces twice-daily, 48-h operational air quality (AQ) forecasts for a domain covering North America. At the core of the forecast system is the GEM-MACH model, an on-line coupled meteorology and chemistry model that includes a representation of gas-phase, aqueous-phase, and heterogeneous chemistry and a number of particulate matter (PM) processes. In this paper, a brief description of the recent changes to the Canadian National AQ Forecasting System is given, followed by a discussion of future development plans. The objective for the next version of the system is to deliver improved AQ forecasts by improving initial and boundary conditions and representations of emissions and processes.


Archive | 2016

High Resolution Model Simulations of the Canadian Oil Sands with Comparisons to Field Study Observations

P. A. Makar; Craig Stroud; J. Zhang; M. D. Moran; A. Akingunola; Weixi Gong; Sylvie Gravel; B. Pabla; Philip Cheung; Qiong Zheng; G. Marson; S.-M. Li; J. R. Brook; K. Hayden; John Liggio; Ralf M. Staebler; Andrea Darlington

The governments of Canada and Alberta are implementing a joint plan for oil sands monitoring that includes investigating emissions, transport and downwind chemistry associated with the Canadian oil sands region. As part of that effort, Environment Canada’s Global Environmental Multiscale—Modelling Air-quality And CHemistry (GEM-MACH) system was reconfigured for the first time to create nested forecasts of air quality at model grid resolutions down to 2.5 km, with the highest resolution domain including the Canadian provinces of Alberta and Saskatchewan. The forecasts were used to direct an airborne research platform during a summer 2013 monitoring intensive. Subsequent work with the modelling system has included an in-depth comparison of the model predictions to monitoring network observations, and to field intensive airborne and surface supersite observations. A year of model predictions and monitoring network observations were compared, as were model and aircraft flight track values. The relative impact of different model versions (including modified emissions and feedbacks between weather and air pollution) will be discussed. Model-based predictions of indicators of human-health (i.e., Air Quality Health Index) and ecosystem (i.e. deposition of pollutants) impacts for the region will also be described.


Archive | 2008

Modelling Regional Aerosols: Impact of Cloud Processing on Gases and Particles over Eastern North America and in Its Outflow During ICARTT 2004

Weixi Gong; J. Zhang; M. D. Moran; P. A. Makar; S. L. Gong; Craig Stroud; V. S. Bouchet; Sophie Cousineau; S. Ménard; M. Samaali; Mourad Sassi; B. Pabla; R. Leaitch; A. M. Macdonald; Kurt Anlauf; K. Hayden; Desiree Toom-Sauntry; Amy Leithead; J. W. Strapp

A regional aerosol model, AURAMS (A Unified Regional Air-quality Modelling System), is used to simulate gases and aerosols over eastern North America for the ICARTT field campaign period during summer 2004. The model performance is evaluated against both ground-based and airborne observations during the field campaign. A model sensitivity study is used to assess the impact of cloud processing on the aerosol characteristics in the air masses over eastern North America and its outflow to the North Atlantic during the study period.


Journal of Geophysical Research | 2008

Cloud processing of nitrate

K. L. Hayden; A. M. Macdonald; Weixi Gong; Desiree Toom-Sauntry; Kurt Anlauf; Amy Leithead; S.-M. Li; W. R. Leaitch; K. Noone


Atmospheric Chemistry and Physics | 2010

Impact of model grid spacing on regional- and urban- scale air quality predictions of organic aerosol

Craig Stroud; P. A. Makar; M. D. Moran; Weixi Gong; S. L. Gong; J. Zhang; K. Hayden; C. Mihele; J. R. Brook; J. P. D. Abbatt; Jay G. Slowik


Atmospheric Environment | 2010

Ensemble and bias-correction techniques for air quality model forecasts of surface O3 and PM2.5 during the TEXAQS-II experiment of 2006

I. Djalalova; James M. Wilczak; S. A. McKeen; Georg A. Grell; S. Peckham; Mariusz Pagowski; L. DelleMonache; J. McQueen; Youhua Tang; Pius Lee; John N. McHenry; Weixi Gong; V. S. Bouchet; Rohit Mathur


Journal of Geophysical Research | 2007

Comparison of Canadian air quality forecast models with tropospheric ozone profile measurements above midlatitude North America during the IONS/ICARTT campaign: Evidence for stratospheric input

David W. Tarasick; M. D. Moran; Anne M. Thompson; T. Carey-Smith; Yves J. Rochon; V. Bouchet; Weixi Gong; P. A. Makar; Craig Stroud; S. Ménard; L.-P. Crevier; S. Cousineau; J. A. Pudykiewicz; A. Kallaur; R. Moffet; Richard Ménard; A. Robichaud; O. R. Cooper; Samuel J. Oltmans; Jacquelyn C. Witte; G. Forbes; Bryan J. Johnson; John T. Merrill; Jennie L. Moody; Gary A. Morris; M. J. Newchurch; F. J. Schmidlin; Everette Joseph


Atmospheric Chemistry and Physics | 2010

Dynamic adjustment of climatological ozone boundary conditions for air-quality forecasts

P. A. Makar; Weixi Gong; C. Mooney; Junhua Zhang; Didier Davignon; M. Samaali; M. D. Moran; H. He; David W. Tarasick; David M. L. Sills; Jack Chen

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V. S. Bouchet

Meteorological Service of Canada

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Michael D. Moran

Meteorological Service of Canada

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