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 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 Quantification and evaluation of atmospheric ammonia emissions with different methods: a case study for the Yangtze River Delta region, China

2020 ◽  
Vol 20 (7) ◽  
pp. 4275-4294 ◽  
Author(s):  
Yu Zhao ◽  
Mengchen Yuan ◽  
Xin Huang ◽  
Feng Chen ◽  
Jie Zhang
Keyword(s):  
Air Quality ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
Emission Factors ◽  
River Delta ◽  
The Yangtze River ◽  
Nh3 Volatilization ◽  
Inorganic Aerosols ◽  
Emission Estimation ◽  
The Yangtze River Delta

Abstract. To explore the effects of data and method on emission estimation, two inventories of NH3 emissions of the Yangtze River Delta (YRD) region in eastern China were developed for 2014 based on constant emission factors (E1) and those characterizing agricultural processes (E2). The latter derived the monthly emission factors and activity data integrating the local information of soil, meteorology, and agricultural processes. The total emissions were calculated to be 1765 and 1067 Gg with E1 and E2, respectively, and clear differences existed in seasonal and spatial distributions. Elevated emissions were found in March and September in E2, attributed largely to the increased top dressing fertilization and to the enhanced NH3 volatilization under high temperature, respectively. A relatively large discrepancy between the inventories existed in the northern YRD with abundant croplands. With the estimated emissions 38 % smaller in E2, the average of simulated NH3 concentrations with an air quality model using E2 was 27 % smaller than that using E1 at two ground sites in the YRD. At the suburban site in Pudong, Shanghai (SHPD), the simulated NH3 concentrations with E1 were generally larger than observations, and the modeling performance was improved, indicated by the smaller normalized mean errors (NMEs) when E2 was applied. In contrast, very limited improvement was found at the urban site JSPAES, as E2 failed to improve the emission estimation of transportation and residential activities. Compared to NH3, the modeling performance for inorganic aerosols was better for most cases, and the differences between the simulated concentrations with E1 and E2 were clearly smaller, at 7 %, 3 %, and 12 % (relative to E1) for NH4+, SO42-, and NO3-, respectively. Compared to the satellite-derived NH3 column, application of E2 significantly corrected the overestimation in vertical column density for January and October with E1, but it did not improve the model performance for July. The NH3 emissions might be underestimated with the assumption of linear correlation between NH3 volatilization and soil pH for acidic soil, particularly in warm seasons. Three additional cases, i.e., 40 % abatement of SO2, 40 % abatement of NOx, and 40 % abatement of both species, were applied to test the sensitivity of NH3 and inorganic aerosol concentrations to precursor emissions. Under an NH3-rich condition, estimation of SO2 emissions was detected to be more effective on simulation of secondary inorganic aerosols compared to NH3. Reduced SO2 would restrain the formation of (NH4)2SO4 and thereby enhance the NH3 concentrations. To improve the air quality more effectively and efficiently, NH3 emissions should be substantially controlled along with SO2 and NOx in the future.

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 Quantification and evaluation of atmospheric ammonia emissions with different methods: A case study for the Yangtze River Delta region, China

2019 ◽  
Author(s):  
Yu Zhao ◽  
Mengchen Yuan ◽  
Xin Huang ◽  
Feng Chen ◽  
Jie Zhang
Keyword(s):  
Air Quality ◽  
Yangtze River ◽  
Satellite Observation ◽  
Yangtze River Delta ◽  
River Delta ◽  
The Yangtze River ◽  
Nh3 Volatilization ◽  
Inorganic Aerosols ◽  
Emission Estimation ◽  
The Yangtze River Delta

Abstract. To explore the effects of data and method on emission estimation, two inventories of NH3 emissions of the Yangtze River Delta (YRD) region in eastern China were developed for 2014 based on the constant emission factors (E1) and those characterizing the agricultural processes (E2), respectively. The latter integrated the detailed information of soil, meteorology and agricultural processes, and derived the monthly information of emission factors and activity data. The total emissions were calculated at 1765 and 1067 Gg, respectively, and agricultural activities (livestock farming and fertilizer use) were estimated to contribute 74–84 % to total emissions in the two inventories. Clear differences existed in seasonal and spatial distributions of NH3 emissions. Elevated emissions were found in March and September in E2, attributed largely to the increased top dressing fertilization and to the enhanced NH3 volatilization under high temperature, respectively. Relatively large discrepancy between the methods existed in northern Yangtze River Delta areas with abundant croplands. The two inventories were evaluated through air quality modeling and available ground and satellite observation. With the estimated emissions 38 % smaller in E2, the average of simulated NH3 concentrations using E2 was 27 % smaller than that using E1 at two ground observation sites in the YRD region. At the suburban SHPD site, the simulated NH3 concentrations with E1 were generally larger than observation, and the modeling performance was largely improved indicated by the smaller NMEs when E2 was applied. In contrast, very limited improvement was found at the urban site JSPAES, as E2 failed to improve the emission estimation of local sources including transportation and residential activities. Compared to NH3, the modeling performance for inorganic aerosols was better for most cases, and the differences between the simulated concentrations with E1 and E2 were clearly smaller, at 7 %, 3 % and 12 % (relative to E1) for NH4+, SO42−, and NO3−, respectively. Regarding the satellite-derived NH3 column, application of E2 significantly corrected the overestimation in vertical column density simulation for January and October with E1, but did not improve the model performance for July. The NH3 emissions might be underestimated with the assumption of linear correlation between NH3 volatilization and soil pH for acidic soil, particularly in warm seasons. Three additional cases, i.e., 40 % abatement of SO2, 40 % abatement of NOX, and 40 % abatement of both species were applied to test the sensitivity of NH3 and inorganic aerosol concentrations to precursor emissions. Under an NH3-rich condition for most of YRD, estimation of SO2 emissions was detected to be more effective on simulation of secondary inorganic aerosols compared to NH3. Reduced SO2 would restrain the formation of (NH4)2SO4, and thereby enhance the NH3 concentrations. Besides the emissions, uncertainties existed as well in the limitations of ground and satellite observation and incomplete mechanism of gas to particle conversion applied in the model. To improve the air quality more effectively and efficiently, NH3 emissions should be substantially controlled along with SO2 and NOX in the future.

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.

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.

Preview of the future application of the environmental geo-satellites data using aircraft platform: Estimation of anthropogenic VOC emissions from formaldehyde columns

2020 ◽  
Author(s):  
Rokjin Park ◽  
Hyeong-Ahn Kwon ◽  
Yujin Oak
Keyword(s):  
Air Quality ◽  
South Korea ◽  
Future Application ◽  
Air Quality Model ◽  
Quality Model ◽  
Top Down ◽  
Vertical Column ◽  
Bottom Up ◽  
Ozone Sensitivity ◽  
Emission Changes

&lt;p&gt;The Geostationary Environment Monitoring Spectrometer (GEMS) will be launched in February 2020 and will provide hourly observations of atmospheric compositions in the daytime. Prior to the GEMS launch, we explore an application of GEMS data as constraints for estimating anthropogenic volatile organic compound (AVOC) emissions in South Korea using formaldehyde (HCHO) vertical column densities observations from the Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) onboard the B200 aircraft during the KORUS-AQ campaign. Our top-down estimates of total AVOC emissions are higher by a factor of four over the petrochemical industries compared to the bottom-up emissions. However, the national AVOC emissions from the top-down estimates are by 37% lower than those of the bottom-up emission inventory in South Korea. We also show that hourly column observations of HCHO can improve not only the total magnitude of AVOC emissions but also their diurnal variation, which is poorly constrained and used in air quality models. Our hourly estimates of AVOC emissions may, thus, improve air quality model simulations in which the simulated ozone sensitivity to AVOC emission changes are also investigated.&lt;/p&gt;

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

2018 ◽  
Vol 18 (5) ◽  
pp. 3433-3456 ◽  
Author(s):  
Meng Li ◽  
Zbigniew Klimont ◽  
Qiang Zhang ◽  
Randall V. Martin ◽  
Bo Zheng ◽  
...  
Keyword(s):  
Power Plants ◽  
Comprehensive Evaluation ◽  
National Level ◽  
Model Performance ◽  
Chemical Transport ◽  
Emission Factors ◽  
Emission Inventories ◽  
Ozone Monitoring Instrument ◽  
Top Down ◽  
Bottom Up

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 clues to improve 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. The FGD (flue-gas desulfurization) device penetration rate and removal efficiency, LNB (low-NOx burner) application rate and abatement efficiency in power plants, emission factors of industrial boilers and various vehicle types, and vehicle fleet need further verification. Diesel consumptions are quite uncertain in current inventories. Discrepancies at the sectorial and provincial levels are much higher than those of the national total. We then examined the impacts of different inventories on model performance by using the nested GEOS-Chem model. We finally derived top-down emissions by using the retrieved columns from the Ozone Monitoring Instrument (OMI) compared with the bottom-up estimates. High correlations were observed for SO2 between model results and OMI columns. For NOx, negative biases in bottom-up gridded emission inventories (−21 % for MIX, −39 % for ECLIPSE) were found compared to the satellite-based emissions. The emission trends from 2005 to 2010 estimated by two inventories were both consistent with satellite observations. The inventories appear to be fit for evaluation of the policies at an aggregated or national level; more work is needed in specific areas in order to improve the accuracy and robustness of outcomes at finer spatial and also technological levels. To our knowledge, this is the first work in which source comparisons detailed to technology-level parameters 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 identified potential directions for further improvement in inventory development.

scholarly journals Comparison of Top-Down and Bottom-Up Road Transport Emissions through High-Resolution Air Quality Modeling in a City of Complex Orography

Atmosphere ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1372
Author(s):  
Felipe Cifuentes ◽  
Carlos M. González ◽  
Erika M. Trejos ◽  
Luis D. López ◽  
Francisco J. Sandoval ◽  
...  
Keyword(s):  
Specific Activity ◽  
Road Transport ◽  
Urban Environments ◽  
Top Down ◽  
Activity Data ◽  
Bottom Up ◽  
Quality Modeling ◽  
Traffic Volumes ◽  
Vehicular Speed ◽  
Transport Emissions

Vehicular emissions are a predominant source of pollution in urban environments. However, inherent complexities of vehicular behavior are sources of uncertainties in emission inventories (EIs). We compare bottom-up and top-down approaches for estimating road transport EIs in Manizales, Colombia. The EIs were estimated using a COPERT model, and results from both approaches were also compared with the official top-down EI (estimated from IVE methodology). The transportation model PTV-VISUM was used for obtaining specific activity information (traffic volumes, vehicular speed) in bottom-up estimation. Results from COPERT showed lower emissions from the top-down approach than from the bottom-up approach, mainly for NMVOC (−28%), PM10 (−26%), and CO (−23%). Comparisons showed that COPERT estimated lower emissions than IVE, with higher differences than 40% for species such as PM10, NOX, and CH4. Furthermore, the WRF–Chem model was used to test the sensitivity of CO, O3, PM10, and PM2.5 predictions to the different EIs evaluated. All studied pollutants exhibited a strong sensitivity to the emission factors implemented in EIs. The COPERT/top-down was the EI that produced more significant errors. This work shows the importance of performing bottom-up EI to reduce the uncertainty regarding top-down activity data.

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