scholarly journals Improvement of the satellite-derived NO<sub><i>x</i></sub> emissions on air quality modeling and its effect on ozone and secondary inorganic aerosol formation in the Yangtze River Delta, China

2021 ◽  
Vol 21 (2) ◽  
pp. 1191-1209
Author(s):  
Yang Yang ◽  
Yu Zhao ◽  
Lei Zhang ◽  
Jie Zhang ◽  
Xin Huang ◽  
...  
Keyword(s):  
Air Quality ◽  
Emission Inventory ◽  
Model Performance ◽  
Yangtze River Delta ◽  
Nox Emissions ◽  
Top Down ◽  
Bottom Up ◽  
Emission Estimation ◽  
Reduced Rate ◽  
The Yrd

Abstract. We developed a top-down methodology combining the inversed chemistry transport modeling and satellite-derived tropospheric vertical column of NO2 and estimated the NOx emissions of the Yangtze River Delta (YRD) region at a horizontal resolution of 9 km for January, April, July, and October 2016. The effect of the top-down emission estimation on air quality modeling and the response of ambient ozone (O3) and inorganic aerosols (SO42-, NO3-, and NH4+, SNA) to the changed precursor emissions were evaluated with the Community Multi-scale Air Quality (CMAQ) system. The top-down estimates of NOx emissions were smaller than those (i.e., the bottom-up estimates) in a national emission inventory, Multi-resolution Emission Inventory for China (MEIC), for all the 4 months, and the monthly mean was calculated to be 260.0 Gg/month, 24 % less than the bottom-up one. The NO2 concentrations simulated with the bottom-up estimate of NOx emissions were clearly higher than the ground observations, indicating the possible overestimation in the current emission inventory, attributed to its insufficient consideration of recent emission control in the region. The model performance based on top-down estimate was much better, and the biggest change was found for July, with the normalized mean bias (NMB) and normalized mean error (NME) reduced from 111 % to −0.4 % and from 111 % to 33 %, respectively. The results demonstrate the improvement of NOx emission estimation with the nonlinear inversed modeling and satellite observation constraint. With the smaller NOx emissions in the top-down estimate than the bottom-up one, the elevated concentrations of ambient O3 were simulated for most of the YRD, and they were closer to observations except for July, implying the VOC (volatile organic compound)-limited regime of O3 formation. With available ground observations of SNA in the YRD, moreover, better model performance of NO3- and NH4+ was achieved for most seasons, implying the effectiveness of precursor emission estimation on the simulation of secondary inorganic aerosols. Through the sensitivity analysis of O3 formation for April 2016, the decreased O3 concentrations were found for most of the YRD region when only VOC emissions were reduced or the reduced rate of VOC emissions was 2 times of that of NOx, implying the crucial role of VOC control in O3 pollution abatement. The SNA level for January 2016 was simulated to decline 12 % when 30 % of NH3 emissions were reduced, while the change was much smaller with the same reduced rate for SO2 or NOx. The result suggests that reducing NH3 emissions was the most effective way to alleviate SNA pollution of the YRD in winter.

scholarly journals Improvement from the satellite-derived NO<sub>x</sub> emissions on air quality modeling and its effect on ozone and secondary inorganic aerosol formation in Yangtze River Delta, China

2020 ◽  
Author(s):  
Yang Yang ◽  
Yu Zhao ◽  
Lei Zhang ◽  
Jie Zhang ◽  
Xin Huang ◽  
...  
Keyword(s):  
Air Quality ◽  
Model Performance ◽  
Yangtze River Delta ◽  
Nox Emissions ◽  
Top Down ◽  
Bottom Up ◽  
Inorganic Aerosols ◽  
Quality Modeling ◽  
Emission Estimation ◽  
Reduced Rate

Abstract. We developed a top-down methodology combining the inversed chemistry transport modeling and satellite-derived tropospheric vertical column of NO2, and estimated the NOx emissions of Yangtze River Delta (YRD) region at a horizontal resolution of 9 km for January, April, July and October 2016. The effect of the top-down emission estimation on air quality modeling, and the response of ambient ozone (O3) and secondary inorganic aerosols (SO42−, NO3−, and NH4+, SNA) to the changed precursor emissions were evaluated with the Community Multi-scale Air Quality (CMAQ) system. The top-down estimates of NOx emissions were smaller than those in a national emission inventory, MEIC (i.e., the bottom-up estimates), for all the four months, and the monthly mean was calculated at 260.0 Gg/month, 24 % less than the bottom-up one. The NO2 concentrations simulated with the bottom-up estimate of NOx emissions were clearly higher than the ground observation, indicating the possible overestimation in current emission inventory attributed to its insufficient consideration of recent emission control in the region. The model performance based on top-down estimate was much better, and the biggest change was found for July with the normalized mean bias (NMB) and normalized mean error (NME) reduced from 111 % to −0.4 % and from 111 % to 33 %, respectively. The results demonstrate the improvement of NOx emission estimation with the nonlinear inversed modeling and satellite observation constraint. With the smaller NOx emissions in the top-down estimate than the bottom-up one, the elevated concentrations of ambient O3 were simulated for most YRD and they were closer to observation except for July, implying the VOC (volatile organic compound)-limit regime of O3 formation. With available ground observations of SNA in the YRD, moreover, better model performance of NO3− and NH4+ were achieved for most seasons, implying the effectiveness of precursor emission estimation on the simulation of secondary inorganic aerosols. Through the sensitivity analysis of O3 formation for April 2016, the decreased O3 concentrations were found for most YRD region when only VOCs emissions were reduced or the reduced rate of VOCs emissions was two times of that of NOx, implying the crucial role of VOCs control on O3 pollution abatement. The SNA level for January 2016 was simulated to decline 12 % when 30 % of NH3 emissions were reduced, while the change was much smaller with the same reduced rate for SO2 or NOx. The result suggests that reducing NH3 emissions was the most effective way to alleviate SNA pollution for YRD in winter.

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.

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

2016 ◽  
Author(s):  
Yaduan Zhou ◽  
Yu Zhao ◽  
Pan Mao ◽  
Qiang Zhang ◽  
Jie Zhang ◽  
...  
Keyword(s):  
Air Quality ◽  
High Resolution ◽  
Emission Inventory ◽  
Spatial Scales ◽  
Air Quality Modeling ◽  
Capital City ◽  
Nox Emissions ◽  
Quality Modeling ◽  
Emission Estimation ◽  
Southern Jiangsu

Abstract. Improved emission inventories combining detailed source information are crucial for better understanding 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 model (CTM) might not be able to well reproduce the evolution of atmospheric pollution process 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 survey. 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, 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 for pollution transport, in particular, much higher SO2 concentrations than observation were simulated for downtown Nanjing (the capital city of Jiangsu) using the regional or national inventories, implying the overestimation in urban emissions when the locations of large emitters were not fully considered, and the densities of economy or population were simply 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 &amp; steel and cement plants were identified as important contributors to the PM2.5 concentrations in Nanjing (the capital city of Jiangsu). The O3 formation was VOCs-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.

scholarly journals Comparison and evaluation of anthropogenic emissions of SO<sub>2</sub> and NO<sub>x over China

2017 ◽  
Author(s):  
Meng Li ◽  
Zbigniew Klimont ◽  
Qiang Zhang ◽  
Randall V. Martin ◽  
Bo Zheng ◽  
...  
Keyword(s):  
Comprehensive Evaluation ◽  
Model Performance ◽  
Chemical Transport ◽  
Nox Emissions ◽  
Emission Inventories ◽  
Ozone Monitoring Instrument ◽  
Top Down ◽  
Bottom Up ◽  
Essential Input ◽  
Inventory Development

Abstract. Bottom-up emission inventories provide primary understanding of sources of air pollution and essential input of chemical transport models. Focusing on SO2 and NOx, we conducted a comprehensive evaluation of two widely-used anthropogenic emission inventories over China, ECLIPSE and MIX, to explore the potential sources of uncertainties and find the clues in improving emission inventories. We first compared the activity rates and emission factors used in two inventories, and investigated the reasons of differences and the impacts on emission estimates. We found that SO2 emission estimates are consistent between two inventories (with 1 % differences), while NOx emissions in ECLIPSE's estimates are 16 % lower than those of MIX. Discrepancies at sectorial and provincial level are much higher. We then examined the impacts of different inventories on model performance, by using the nested GEOS-Chem model. We finally derived top-down NOx emissions by using the NO2 columns from the Ozone Monitoring Instrument (OMI) and compared with the bottom-up estimates. To our knowledge, this is the first work where source-sector comparisons are made along with the remote sensing retrievals and chemical transport modeling. Through the comparison between bottom-up emission inventories and evaluation with top-down information, we summarized the potential directions for further improvement in inventory development.

Evaluation of Air Pollutant Emission Inventories in East Asia

2020 ◽  
Author(s):  
Younha Kim ◽  
Jung-hun Woo ◽  
Youjung Jang ◽  
Minwoo Park ◽  
Bomi Kim ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Air Quality ◽  
East Asia ◽  
Emission Inventory ◽  
Air Pollutant ◽  
Emission Inventories ◽  
Top Down ◽  
Bottom Up ◽  
Emissions Inventory ◽  
Quality Study

&lt;p&gt;Concentration of air pollutants such as tropospheric ozone and aerosols are mainly affected by meteorological variables and emissions. East Asia has large amount of anthropogenic and natural air pollutant emissions and has been putting lots of efforts to improve air quality. In order to seek effective ways to mitigate future air pollution, it is essential to understand the current emissions and their impacts on air quality. Emission inventory is one of the key datasets required to understand air quality and find ways to improve it. Amounts and spatial-temporal distributions of emissions are, however, not easy to estimate due to their complicate nature, therefore introduce significant uncertainties.&lt;/p&gt;&lt;p&gt;In this study, we had developed an updated version of our Asian emissions inventory, named NIER/KU-CREATE (Comprehensive Regional Emissions inventory for Atmospheric Transport Experiment) in support of climate-air quality study. We first inter-compare multiple bottom-up inventories to understand discrepancies among the dataset(sectoral, spatial). We then inter-compare those bottom-up emissions to the satellite-based top-down emission estimates to understand uncertainties of the databases. The bottom-up emission inventories used for this study are: CREATE, MEIC(Multiresolution Emission Inventory for China), REAS (Regional Emission inventory in ASia), and ECLIPSE(Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants). The satellite-derived top-down emission inventory had been acquired from the DECSO (Daily Emission derived Constrained by Satellite Observations) algorithm data from the GlobEmissions website.&lt;/p&gt;&lt;p&gt;The analysis showed that some discrepancies, in terms of emission amounts, sectoral shares and spatial distribution patterns, exist among the datasets. We analyzed further to find out which parameters could affect more on those discrepancies. Co-analysis of top-down and bottom-up emissions inventory help us to evaluate emissions amount and spatial distribution. These analysis are helpful for the development of more consistent and reliable inventories with the aim of reducing the uncertainties in air quality study. More results of evaluation of emissions will be presented on site.&amp;#160; &amp;#160;&amp;#160;&amp;#160;&lt;/p&gt;&lt;p&gt;Acknowledgements : This work was supported by National Institute of Environment Research (NIER-2019-03-02-005), Korea Environment Industry &amp; Technology Institute(KEITI) through Public Technology Program based on Environmental Policy Program, funded by Korea Ministry of Environment(MOE)(2019000160007). This research was supported by the National Strategic Project-Fine particle of the National Research Foundation of Korea(NRF) funded by the Ministry of Science and ICT(MSIT), the Ministry of Environment(ME), and the Ministry of Health and Welfare(MOHW) (NRF-2017M3D8A1092022).&lt;/p&gt;

scholarly journals Bottom-Up Emission Inventory and Its Spatio-Temporal Distribution from Paved Road Dust Based on Field Investigation: A Case Study of Harbin, Northeast China

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 449
Author(s):  
Lili Li ◽  
Kun Wang ◽  
Zhijian Sun ◽  
Weiye Wang ◽  
Qingliang Zhao ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Emission Inventory ◽  
Road Dust ◽  
Field Investigation ◽  
Pollutant Emissions ◽  
County Level ◽  
Bottom Up ◽  
Spatial Allocation ◽  
Paved Road

Road dust is one of the primary sources of particulate matter which has implications for air quality, climate and health. With the aim of characterizing the emissions, in this study, a bottom-up approach of county level emission inventory from paved road dust based on field investigation was developed. An inventory of high-resolution paved road dust (PRD) emissions by monthly and spatial allocation at 1 km × 1 km resolution in Harbin in 2016 was compiled using accessible county level, seasonal data and local parameters based on field investigation to increase temporal-spatial resolution. The results demonstrated the total PRD emissions of TSP, PM10, and PM2.5 in Harbin were 270,207 t, 54,597 t, 14,059 t, respectively. The temporal variation trends of pollutant emissions from PRD was consistent with the characteristics of precipitation, with lower emissions in winter and summer, and higher emissions in spring and autumn. The spatial allocation of emissions has a strong association with Harbin’s road network, mainly concentrating in the central urban area compared to the surrounding counties. Through scenario analysis, positive control measures were essential and effective for PRD pollution. The inventory developed in this study reflected the level of fugitive dust on paved road in Harbin, and it could reduce particulate matter pollution with the development of mitigation strategies and could comply with air quality modelling requirements, especially in the frigid region of northeastern China.

scholarly journals Ensemble Predictions of Air Pollutants in China in 2013 for Health Effects Studies Using WRF/CMAQ Modeling System with Four Emission Inventories

2017 ◽  
Author(s):  
Jianlin Hu ◽  
Xun Li ◽  
Lin Huang ◽  
Qi Ying ◽  
Qiang Zhang ◽  
...  
Keyword(s):  
Air Quality ◽  
Health Effects ◽  
Air Pollutants ◽  
Emission Inventory ◽  
Model Performance ◽  
Observation Data ◽  
Emission Inventories ◽  
Air Quality Model ◽  
Quality Model ◽  
Future Health

Abstract. Accurate exposure estimates are required for health effects analyses of severe air pollution in China. Chemical transport models (CTMs) are widely used tools to provide detailed information of spatial distribution, chemical composition, particle size fractions, and source origins of pollutants. The accuracy of CTMs' predictions in China is largely affected by the uncertainties of public available emission inventories. The Community Multi-scale Air Quality model (CMAQ) with meteorological inputs from the Weather Research and Forecasting model (WRF) were used in this study to simulate air quality in China in 2013. Four sets of simulations were conducted with four different anthropogenic emission inventories, including the Multi-resolution Emission Inventory for China (MEIC), the Emission Inventory for China by School of Environment at Tsinghua University (SOE), the Emissions Database for Global Atmospheric Research (EDGAR), and the Regional Emission inventory in Asia version 2 (REAS2). Model performance was evaluated against available observation data from 422 sites in 60 cities across China. Model predictions of O3 and PM2.5 with the four inventories generally meet the criteria of model performance, but difference exists in different pollutants and different regions among the inventories. Ensemble predictions were calculated by linearly combining the results from different inventories under the constraint that sum of the squared errors between the ensemble results and the observations from all the cities was minimized. The ensemble annual concentrations show improved agreement with observations in most cities. The mean fractional bias (MFB) and mean fractional errors (MFE) of the ensemble predicted annual PM2.5 at the 60 cities are −0.11 and 0.24, respectively, which are better than the MFB (−0.25–−0.16) and MFE (0.26–0.31) of individual simulations. The ensemble annual 1-hour peak O3 (O3-1 h) concentrations are also improved, with mean normalized bias (MNB) of 0.03 and mean normalized errors (MNE) of 0.14, compared to MNB of 0.06–0.19 and MNE of 0.16–0.22 of the individual predictions. The ensemble predictions agree better with observations with daily, monthly, and annual averaging times in all regions of China for both PM2.5 and O3-1 h. The study demonstrates that ensemble predictions by combining predictions from individual emission inventories can improve the accuracy of predicted temporal and spatial distributions of air pollutants. This study is the first ensemble model study in China using multiple emission inventories and the results are publicly available for future health effects studies.

scholarly journals The influence of spatiality on shipping emissions, air quality and potential human exposure in Yangtze River Delta/Shanghai, China

2018 ◽  
Author(s):  
Junlan Feng ◽  
Yan Zhang ◽  
Shanshan Li ◽  
Jingbo Mao ◽  
Allison P. Patton ◽  
...  
Keyword(s):  
Air Quality ◽  
Yangtze River ◽  
Human Exposure ◽  
Regional Scale ◽  
Yangtze River Delta ◽  
River Delta ◽  
Population Exposure ◽  
Inland Water ◽  
The Yrd ◽  
The Impact

Abstract. The Yangtze River Delta (YRD) and the megacity of Shanghai are host to one of the busiest port clusters in the world, the region also suffers from high levels of air pollution. The goal of this study was to estimate the contributions of shipping to emissions, air quality, and population exposure and characterize their dependence on the geographic spatiality of ship lanes from the regional scale to city scale for 2015. The WRF-CMAQ model was used to simulate the influence of coastal and inland-water shipping, in port emissions, shipping-related cargo transport on air quality and, population-weighted concentrations, a measure of human exposure. Our results showed that the impact of shipping on air quality in the YRD was attributable primarily to shipping emissions within 12 NM of shore, but emissions coming from the coastal area of 24 to 96 NM still contributed substantially to ship-related PM2.5 concentrations in YRD. The overall contribution of ships to PM2.5 concentration in YRD could reach to 4.62 μg/m3 in summer when monsoon winds transport shipping emissions onshore. In Shanghai city, inland-water going ships were major contributors (40–80 %) to the shipping impact on urban air quality. Given the proximity of inland-water ships to urban populations of Shanghai, the emissions of inland-water ships contributed more to population-weighted concentrations. These research results provide scientific evidence to inform policies for controlling future shipping emissions; in particular, stricter standards could be considered for the ships on inland rivers and other waterways close to residential regions.

scholarly journals A top-down assessment using OMI NO2 suggests an underestimate in the NOx emissions inventory in Seoul, South Korea during KORUS-AQ

2018 ◽  
Author(s):  
Daniel L. Goldberg ◽  
Pablo E. Saide ◽  
Lok N. Lamsal ◽  
Benjamin de Foy ◽  
Zifeng Lu ◽  
...  
Keyword(s):  
South Korea ◽  
Emission Rate ◽  
Model Simulation ◽  
Nox Emission ◽  
Metropolitan Region ◽  
Nox Emissions ◽  
Top Down ◽  
Bottom Up ◽  
Field Campaign ◽  
Emissions Inventory

Abstract. In this work, we investigate the NOx emissions inventory in Seoul, South Korea using a regional NASA Ozone Monitoring Instrument (OMI) NO2 product. We first develop a regional OMI NO2 product by re-calculating the air mass factors using a high-resolution (4 × 4 km2) WRF-Chem model simulation, which better captures the NO2 shape profiles in urban regions. We then apply a model-derived spatial averaging kernel to further downscale the retrieval and account for the sub-pixel variability. These two modifications yield OMI NO2 values in the regional product that are 1.37 larger in the Seoul metropolitan region and > 2 times larger near large industrial sources. These two modifications also yield an OMI NO2 product that is in better agreement with the Pandora NO2 spectrometer measurements acquired during the Korea U.S.-Air Quality (KORUS-AQ) field campaign. NOx emissions are then derived for the Seoul metropolitan area during the KORUS-AQ field campaign using a top-down approach with the standard and regional NASA OMI NO2 products. We first apply the top-down approach to a model simulation to ensure that the method is appropriate: the WRF-Chem simulation utilizing the bottom-up emission inventory yields a NOx emission rate of 227 ± 94 kton/yr, while the bottom-up inventory itself yields a NOx emission rate of 198 kton/yr. Using the top-down approach on the regional OM NO2 product, we derive the NOx emissions rate from Seoul to be 484 ± 201 kton/yr, and a 353 ± 146 kton/yr NOx emissions rate using the standard NASA OMI NO2 product. This suggests an underestimate of 53 % and 36 % using the regional and standard NASA OMI NO2 products respectively. To supplement this finding, we compare the NO2 simulated by WRF-Chem to observations of the same quantity acquired by aircraft and find a model underestimate. When NOx emissions in the WRF-Chem model are doubled, there is better agreement with KORUS-AQ aircraft observations. Although the current work is focused on South Korea using OMI, the methodology developed in this work can be applied to other world regions using TROPOMI and future satellite datasets (e.g., GEMS and TEMPO) to produce high-quality region-specific top-down NOx emission estimates.

scholarly journals Modeling of the anthropogenic heat flux and its effect on regional meteorology and air quality over the Yangtze River Delta region, China

2016 ◽  
Vol 16 (10) ◽  
pp. 6071-6089 ◽  
Author(s):  
Min Xie ◽  
Jingbiao Liao ◽  
Tijian Wang ◽  
Kuanguang Zhu ◽  
Bingliang Zhuang ◽  
...  
Keyword(s):  
Air Quality ◽  
Urban Areas ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
Vertical Movement ◽  
Anthropogenic Heat ◽  
The Yangtze River ◽  
The Yrd ◽  
Surface O3 ◽  
The Yangtze River Delta

Abstract. Anthropogenic heat (AH) emissions from human activities caused by urbanization can affect the city environment. Based on the energy consumption and the gridded demographic data, the spatial distribution of AH emission over the Yangtze River Delta (YRD) region is estimated. Meanwhile, a new method for the AH parameterization is developed in the WRF/Chem model, which incorporates the gridded AH emission data with the seasonal and diurnal variations into the simulations. By running this upgraded WRF/Chem for 2 typical months in 2010, the impacts of AH on the meteorology and air quality over the YRD region are studied. The results show that the AH fluxes over the YRD have been growing in recent decades. In 2010, the annual-mean values of AH over Shanghai, Jiangsu and Zhejiang are 14.46, 2.61 and 1.63 W m−2, respectively, with the high value of 113.5 W m−2 occurring in the urban areas of Shanghai. These AH emissions can significantly change the urban heat island and urban-breeze circulations in the cities of the YRD region. In Shanghai, 2 m air temperature increases by 1.6 °C in January and 1.4 °C in July, the PBLH (planetary boundary layer height) rises up by 140 m in January and 160 m in July, and 10 m wind speed is enhanced by 0.7 m s−1 in January and 0.5 m s−1 in July, with a higher increment at night. The enhanced vertical movement can transport more moisture to higher levels, which causes the decrease in water vapor at ground level and the increase in the upper PBL (planetary boundary layer), and thereby induces the accumulative precipitation to increase by 15–30 % over the megacities in July. The adding of AH can impact the spatial and vertical distributions of the simulated pollutants as well. The concentrations of primary air pollutants decrease near the surface and increase at the upper levels, due mainly to the increases in PBLH, surface wind speed and upward air vertical movement. But surface O3 concentrations increase in the urban areas, with maximum changes of 2.5 ppb in January and 4 ppb in July. Chemical direct (the rising up of air temperature directly accelerates surface O3 formation) and indirect (the decrease in NOx at the ground results in the increase in surface O3) effects can play a significant role in O3 changes over this region. The meteorology and air pollution predictions in and around large urban areas are highly sensitive to the anthropogenic heat inputs, suggesting that AH should be considered in the climate and air quality assessments.

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