scholarly journals Future prediction of surface ozone over east Asia using Models-3 Community Multiscale Air Quality Modeling System and Regional Emission Inventory in Asia

2008 ◽  
Vol 113 (D8) ◽  
Author(s):  
Kazuyo Yamaji ◽  
Toshimasa Ohara ◽  
Itsushi Uno ◽  
Jun-ichi Kurokawa ◽  
Pakpong Pochanart ◽  
...  
Keyword(s):  
Air Quality ◽  
East Asia ◽  
Emission Inventory ◽  
Surface Ozone ◽  
Air Quality Modeling ◽  
Quality Modeling ◽  
Future Prediction

scholarly journals Emission Inventory Processing of Biomass Burning from A Global Dataset for Air Quality Modeling

2020 ◽  
Author(s):  
Ernesto Pino-Cortés ◽  
Samuel Carrasco ◽  
Luis A. Díaz-Robles ◽  
Francisco Cubillos ◽  
Fidel Vallejo ◽  
...  
Keyword(s):  
Air Quality ◽  
Biomass Burning ◽  
Emission Inventory ◽  
Sparse Matrix ◽  
Local Level ◽  
Air Quality Modeling ◽  
Simulation Software ◽  
Atmospheric Pollutants ◽  
Fire Emissions ◽  
Quality Modeling

Wildfires generate large amounts of atmospheric pollutants yearly. The development of an emissions inventory for this activity is a challenge today, mainly to perform modeling of air quality. There are free available databases with historical information about this source. The main goal of this study was to process the results of biomass burning emissions for the year 2014 from the Global Fire Assimilation System (GFAS). The pollutants studied were the black carbon, the organic carbon, fine and coarse particulate matter, respectively. The inputs were pre-formatted to enter to the simulation software of the emission inventory. In this case, the Sparse Matrix Operator Kernel Emissions (SMOKE) was used and the values obtained in various cities were analyzed. As a result, the spatial distribution of the forest fire emissions in the Southern Hemisphere was achieved, with the polar stereographic projection. The highest emissions were located in the African continent, followed by the northern region of Australia. Future air quality modeling at a local level could apply the results and the methodology of this study. The biomass burning emissions could add a better performance of the results and more knowledge on the effect of this source.

Air pollution emission inventory and air quality modeling for Can Tho City, Mekong Delta, Vietnam

2017 ◽  
Vol 11 (1) ◽  
pp. 35-47 ◽  
Author(s):  
Ho Quoc Bang ◽  
Vu Hoang Ngoc Khue ◽  
Nguyen Thoai Tam ◽  
Kristofer Lasko
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Emission Inventory ◽  
Mekong Delta ◽  
Air Quality Modeling ◽  
Pollution Emission ◽  
Quality Modeling ◽  
Can Tho City

Regional Air Quality Modeling System (RAQMS) predictions of the tropospheric ozone budget over east Asia

2003 ◽  
Vol 108 (D21) ◽  
Author(s):  
R. B. Pierce ◽  
J. A. Al-Saadi ◽  
T. Schaack ◽  
A. Lenzen ◽  
T. Zapotocny ◽  
...  
Keyword(s):  
Air Quality ◽  
East Asia ◽  
Tropospheric Ozone ◽  
Air Quality Modeling ◽  
Quality Modeling ◽  
Regional Air Quality

scholarly journals Climate forced air-quality modeling at urban scale: sensitivity to model resolution, emissions and meteorology

2015 ◽  
Vol 15 (4) ◽  
pp. 4767-4821
Author(s):  
K. Markakis ◽  
M. Valari ◽  
O. Perrussel ◽  
O. Sanchez ◽  
C. Honore
Keyword(s):  
Air Quality ◽  
Emission Inventory ◽  
Scale Effects ◽  
Air Quality Modeling ◽  
Anthropogenic Emissions ◽  
Vertical Resolution ◽  
Model Resolution ◽  
Post Processing ◽  
Quality Modeling ◽  
Forced Air

Abstract. While previous research helped to identify and prioritize the sources of error in air-quality modeling due to anthropogenic emissions and spatial scale effects our knowledge is limited on how these uncertainties affect climate forced air-quality assessments. Using as reference a 10 yr model simulation over the greater Paris (France) area at 4 km resolution and anthropogenic emissions from a 1 km resolution bottom-up inventory, through several tests we estimate the sensitivity of modeled ozone and PM2.5 concentrations to different potentially influential factors with a particular interest over the urban areas. These factors include the model horizontal and vertical resolution, the meteorological input from a climate model and its resolution, the use of a top-down emission inventory, the resolution of the emissions input and the post-processing coefficients used to derive the temporal, vertical and chemical split of emissions. We show that urban ozone displays moderate sensitivity to the resolution of emissions (~8%), the post-processing method (6.5%) and model resolution (~5) while annual PM2.5 levels are particularly sensitive to changes in their primary emissions (~32%) and the resolution of the emission inventory (~24%) while model horizontal and vertical resolution are of little effect. In addition we use the results of these sensitivities to explain and quantify the discrepancy between a coarse (~50 km) and a fine (4 km) resolution simulation over the urban area. We show that the ozone bias of the coarse run (+9 ppb) is reduced by ~40% by adopting a higher resolution emission inventory, by 25% by using a post-processing technique based on the local inventory (same improvement is obtained by increasing model horizontal resolution) and by 10% by adopting the annual emission totals of the local inventory. The bias on PM2.5 follows a more complex pattern with the positive bias associated to the coarse run (+3.6 μg m3) increasing or decreasing depending on the type of the refinement. We conclude that in the case of fine particles the coarse simulation cannot selectively incorporate local scale features in order to reduce model error.

scholarly journals Multi-year Downscaling Application of Online Coupled WRFCMAQ over East Asia for Regional Climate and Air Quality Modeling: Model Evaluation and Aerosol Direct Effects

2016 ◽  
Author(s):  
Chaopeng Hong ◽  
Qiang Zhang ◽  
Yang Zhang ◽  
Youhua Tang ◽  
Daniel Tong ◽  
...  
Keyword(s):  
Air Quality ◽  
East Asia ◽  
Model Evaluation ◽  
Dynamical Downscaling ◽  
Regional Climate ◽  
Air Quality Modeling ◽  
Meteorological Variables ◽  
Direct Effects ◽  
Modeling Framework ◽  
Quality Modeling

Abstract. In this study, a regional coupled climate-chemistry modeling system using the dynamical downscaling technique was established by linking the global Community Earth System Model (CESM) and the regional online coupled Weather Research and Forecasting – Community Multiscale Air Quality (WRF-CMAQ) model for the purpose of comprehensive assessments of regional climate change and air quality and their interactions within one modeling framework. The modeling system was applied over East Asia for a multiyear climatological application during 2006–2010 driven with CESM downscaling data under Representative Concentration Pathway 4.5 (RCP 4.5) as well as a short-term air quality application in representative months in 2013 driven with a reanalysis dataset. A comprehensive model evaluation was conducted against observations from surface networks and satellite observations to assess the model's performance. This study presents the first application and evaluation of the online coupled WRF-CMAQ model for climatological simulations using the dynamical downscaling technique. The model was able to satisfactorily predict major meteorological variables. The improved statistical performance for the 2-m temperature (T2) in this study compared with the Coupled Model Inter-comparison Project Phase 5 (CMIP5) multi-models might be related to the use of the regional model WRF and the bias-correction technique applied for CESM downscaling. The model showed good ability to predict PM2.5 in winter and O3 in summer in terms of statistical performance and spatial distributions. Compared with global models that tend to underpredict PM2.5 concentrations in China, WRF-CMAQ was able to capture the high PM2.5 concentrations in urban areas. In general, the online coupled WRF-CMAQ model performed well for both climatological and air quality applications. The coupled modeling system with direct aerosol feedbacks predicted aerosol optical depth relatively well and significantly reduced the overprediction in downward shortwave radiation at the surface (SWDOWN) over polluted regions in China. The performance of cloud variables was not as good as other meteorological variables, and underpredictions of cloud fraction resulted in overpredictions of SWDOWN and underpredictions of shortwave and longwave cloud forcing. The importance of climate-chemistry interactions was demonstrated via the impacts of aerosol direct effects on climate and air quality. The aerosol effects on climate and air quality in East Asia were more significant than in other regions because of higher aerosol loadings that resulted from severe regional pollution, which indicates the need for applying online-coupled models over East Asia for regional climate and air quality modeling and to study the important climate-chemistry interactions.

scholarly journals Air Quality Modeling for of a Strong Dust Event in East Asia in March 2010

2012 ◽  
Vol 12 (4) ◽  
pp. 615-628 ◽  
Author(s):  
Xiao Han ◽  
Cui Ge ◽  
Jinhua Tao ◽  
Meigen Zhang ◽  
Renjian Zhang
Keyword(s):  
Air Quality ◽  
East Asia ◽  
Air Quality Modeling ◽  
Dust Event ◽  
Quality Modeling

scholarly journals Development of a high-resolution emission inventory and its evaluation and application through air quality modeling for Jiangsu Province, China

2017 ◽  
Vol 17 (1) ◽  
pp. 211-233 ◽  
Author(s):  
Yaduan Zhou ◽  
Yu Zhao ◽  
Pan Mao ◽  
Qiang Zhang ◽  
Jie Zhang ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Air Quality ◽  
High Resolution ◽  
Emission Inventory ◽  
Spatial Scales ◽  
Air Quality Modeling ◽  
Nox Emissions ◽  
Quality Modeling ◽  
Emission Estimation ◽  
Southern Jiangsu

Abstract. Improved emission inventories combining detailed source information are crucial for better understanding of the atmospheric chemistry and effectively making emission control policies using air quality simulation, particularly at regional or local scales. With the downscaled inventories directly applied, chemical transport models might not be able to reproduce the authentic evolution of atmospheric pollution processes at small spatial scales. Using the bottom-up approach, a high-resolution emission inventory was developed for Jiangsu China, including SO2, NOx, CO, NH3, volatile organic compounds (VOCs), total suspended particulates (TSP), PM10, PM2.5, black carbon (BC), organic carbon (OC), and CO2. The key parameters relevant to emission estimation for over 6000 industrial sources were investigated, compiled, and revised at plant level based on various data sources and on-site surveys. As a result, the emission fractions of point sources were significantly elevated for most species. The improvement of this provincial inventory was evaluated through comparisons with other inventories at larger spatial scales, using satellite observation and air quality modeling. Compared to the downscaled Multi-resolution Emission Inventory for China (MEIC), the spatial distribution of NOx emissions in our provincial inventory was more consistent with summer tropospheric NO2 VCDs observed from OMI, particularly for the grids with moderate emission levels, implying the improved emission estimation for small and medium industrial plants by this work. Three inventories (national, regional, and provincial by this work) were applied in the Models-3 Community Multi-scale Air Quality (CMAQ) system for southern Jiangsu October 2012, to evaluate the model performances with different emission inputs. The best agreement between available ground observation and simulation was found when the provincial inventory was applied, indicated by the smallest normalized mean bias (NMB) and normalized mean errors (NME) for all the concerned species SO2, NO2, O3, and PM2.5. The result thus implied the advantage of improved emission inventory at local scale for high-resolution air quality modeling. Under the unfavorable meteorology in which horizontal and vertical movement of atmosphere was limited, the simulated SO2 concentrations at downtown Nanjing (the capital city of Jiangsu) using the regional or national inventories were much higher than those observed, implying that the urban emissions were overestimated when economy or population densities were applied to downscale or allocate the emissions. With more accurate spatial distribution of emissions at city level, the simulated concentrations using the provincial inventory were much closer to observation. Sensitivity analysis of PM2.5 and O3 formation was conducted using the improved provincial inventory through the brute force method. Iron and steel plants and cement plants were identified as important contributors to the PM2.5 concentrations in Nanjing. The O3 formation was VOC-limited in southern Jiangsu, and the concentrations were negatively correlated with NOx emissions in urban areas owing to the accumulated NOx from transportation. More evaluations are further suggested for the impacts of speciation and temporal and vertical distribution of emissions on air quality modeling at regional or local scales in China.

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