scholarly journals CAMS-REG-v4: a state-of-the-art high-resolution European emission inventory for air quality modelling

2021 ◽  
Author(s):  
Jeroen Kuenen ◽  
Stijn Dellaert ◽  
Antoon Visschedijk ◽  
Jukka-Pekka Jalkanen ◽  
Ingrid Super ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Point Source ◽  
Power Plants ◽  
Emission Inventory ◽  
State Of The Art ◽  
Agricultural Waste ◽  
Emission Model ◽  
Air Quality Modelling ◽  
Emission Data

Abstract. This paper presents a state-of-the-art anthropogenic emission inventory developed for the European domain for a 18-year time series (2000–2017) at a 0.1° × 0.05° grid, specifically designed to support air quality modelling. The main air pollutants are included: NOx, SO2, NMVOC, NH3, CO, PM10 and PM2.5 and also CH4. To stay as close as possible to the emissions as officially reported and used in policy assessment, the inventory uses where possible the officially reported emission data by European countries to the UN Framework Convention on Climate Change and the Convention on Long-Range Transboundary Air Pollution as the basis. Where deemed necessary because of errors, incompleteness of inconsistencies, these are replaced with or complemented by other emission data, most notably the estimates included in the Greenhouse gas Air pollution Interaction and Synergies (GAINS) model. Emissions are collected at the high sectoral level, distinguishing around 250 different sector-fuel combinations, whereafter a consistent spatial distribution is applied for Europe. A specific proxy is selected for each of the sector-fuel combinations, pollutants and years. Point source emissions are largely based on reported facility level emissions, complemented by other sources of point source data for power plants. For specific sources, the resulting emission data were replaced with other datasets. Emissions from shipping (both inland and at sea) are based on the results from the a separate shipping emission model where emissions are based on actual ship movement data, and agricultural waste burning emissions are based on satellite observations. The resulting spatially distributed emissions are evaluated against earlier versions of the dataset as well as to alternative emission estimates, which reveals specific discrepancies in some cases. Along with the resulting annual emission maps, profiles for splitting PM and NMVOC into individual component are provided, as well as information on the height profile by sector and temporal disaggregation down to hourly level to support modelling activities. Annual grid maps are available in csv and NetCDF format (Kuenen et al., 2021).

scholarly journals TNO-MACC_II emission inventory; a multi-year (2003–2009) consistent high-resolution European emission inventory for air quality modelling

2014 ◽  
Vol 14 (20) ◽  
pp. 10963-10976 ◽  
Author(s):  
J. J. P. Kuenen ◽  
A. J. H. Visschedijk ◽  
M. Jozwicka ◽  
H. A. C. Denier van der Gon
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
High Resolution ◽  
Emission Inventory ◽  
Point Sources ◽  
Air Quality Modelling ◽  
Emission Data ◽  
Data Set ◽  
Spatially Distributed ◽  
Reported Data

Abstract. Emissions to air are reported by countries to EMEP. The emissions data are used for country compliance checking with EU emission ceilings and associated emission reductions. The emissions data are also necessary as input for air quality modelling. The quality of these "official" emissions varies across Europe. As alternative to these official emissions, a spatially explicit high-resolution emission inventory (7 × 7 km) for UNECE-Europe for all years between 2003 and 2009 for the main air pollutants was made. The primary goal was to supply air quality modellers with the input they need. The inventory was constructed by using the reported emission national totals by sector where the quality is sufficient. The reported data were analysed by sector in detail, and completed with alternative emission estimates as needed. This resulted in a complete emission inventory for all countries. For particulate matter, for each source emissions have been split in coarse and fine particulate matter, and further disaggregated to EC, OC, SO4, Na and other minerals using fractions based on the literature. Doing this at the most detailed sectoral level in the database implies that a consistent set was obtained across Europe. This allows better comparisons with observational data which can, through feedback, help to further identify uncertain sources and/or support emission inventory improvements for this highly uncertain pollutant. The resulting emission data set was spatially distributed consistently across all countries by using proxy parameters. Point sources were spatially distributed using the specific location of the point source. The spatial distribution for the point sources was made year-specific. The TNO-MACC_II is an update of the TNO-MACC emission data set. Major updates included the time extension towards 2009, use of the latest available reported data (including updates and corrections made until early 2012) and updates in distribution maps.

Validation and improvement of Taiwan Emission inventory for air quality modeling

2020 ◽  
Author(s):  
Ming-Tung Chuang ◽  
Charles C.-K Chou ◽  
Chuan-Yao Lin
Keyword(s):  
Air Quality ◽  
Point Source ◽  
Emission Inventory ◽  
Sparse Matrix ◽  
Air Quality Modeling ◽  
Emission Data ◽  
Modeling And Analysis ◽  
Quality Modeling ◽  
System Data ◽  
Analysis System

<p>The performance of air quality modeling (AQM) depends largely on the uncertainty of emission inventory. Since the emission data is an important input for AQM, this study tried to validate the controversial emission inventory. The Taiwan EPA (TEPA) has released the latest TEDS10.0 (Taiwan Emission Database System, version 10.0) based on 2016. This emission has attracted high arguments among governments and academics. This study applied the SMOKE v4.6 (Sparse Matrix Operator Kerner Emissions) to process the TEDS. The study used the CEMS (Continuous Emission Monitoring System) data and replaced temporalized large point source which accounts for 70% of all point source emissions, updated the biogenic emission calculation, improved the temporal profile of NH3, several area sources, and all mobile sources. Then we utilized the CMAQ (Community Modeling and Analysis System) model to simulate a PM2.5 event. However, the performance of the abovementioned improvement for emission processing is still not satisfactory. Therefore, this study tried to adjust the emission inventory according to the comparison of simulations and observations. The performance of air quality modeling has been improved after adjustment.  Meanwhile, this study provided suggestions of several aspects to be improved to the TEPA.</p>

scholarly journals Application of an Adaptive Nudging Scheme in Air Quality Forecasting in China

2008 ◽  
Vol 47 (8) ◽  
pp. 2105-2114 ◽  
Author(s):  
Xiangde Xu ◽  
Lian Xie ◽  
Xinghong Cheng ◽  
Jianming Xu ◽  
Xiuji Zhou ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Weather Forecasting ◽  
Initial Conditions ◽  
Primary Source ◽  
Emission Data ◽  
Weather Observations ◽  
Pollution Emissions ◽  
Air Pollution Emissions ◽  
Source Of Error

Abstract A major challenge for air quality forecasters is to reduce the uncertainty of air pollution emission inventory. Error in the emission data is a primary source of error in air quality forecasts, much like the effect of error in the initial conditions on the accuracy of weather forecasting. Data assimilation has been widely used to improve weather forecasting by correcting the initial conditions with weather observations. In a similar way, observed concentrations of air pollutants can be used to correct the errors in the emission data. In this study, a new method is developed for estimating air pollution emissions based on a Newtonian relaxation and nudging technique. Case studies for the period of 1–25 August 2006 in 47 cities in China indicate that the nudging technique resulted in improved estimations of sulfur dioxide (SO2) and nitrogen dioxide (NO2) emissions in the majority of these cities. Predictions of SO2 and NO2 concentrations in January, April, August, and October using the emission estimations derived from the nudging technique showed remarkable improvements over those based on the original emission data.

scholarly journals Enhanced atmospheric oxidizing capacity in simulating air quality with updated emission inventories for power plants especially for haze periods over East China

2017 ◽  
Author(s):  
Lei Zhang ◽  
Tianliang Zhao ◽  
Sunling Gong ◽  
Shaofei Kong ◽  
Lili Tang ◽  
...  
Keyword(s):  
Air Quality ◽  
Power Plants ◽  
Emission Inventory ◽  
Environmental Changes ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Atmospheric Environment ◽  
Pollutant Emission ◽  
East China ◽  
Emission Inventories

Abstract. Air pollutant emissions play a determinant role in deteriorating air quality. However, an uncertainty in emission inventories is still the key problem for modeling air pollution. In this study, an updated emission inventory of coal-fired power plants (UEIPP) based on online monitoring data in Jiangsu province of East China for the year of 2012 was implemented in the widely used Multi-resolution Emission Inventory for China (MEIC). By employing the Weather Research and Forecasting Model with Chemistry (WRF-Chem), two simulations were executed to assess the atmospheric environmental change by using the original MEIC emission inventory and the MEIC inventory with the UEIPP. A synthetic analysis shows that (1) compared to the power emissions of MEIC, PM2.5, PM10, SO2 and NOx were lower, and CO, black carbon (BC), organic carbon (OC) and NMVOCs were higher in the UEIPP, reflecting a large discrepancy in the power emissions over East China; (2) In accordance with the changes of UEIPP, the modeled concentrations were reduced for SO2 and NO2, and increased for most areas of primary OC, BC and CO, whose concentrations in atmosphere are highly dependent on emission changes. (3) Interestingly, when the UEIPP was used, the atmospheric oxidizing capacity significantly reinforced, reflecting by increased oxidizing agents, e.g. O3 and OH, thus directly strengthened the chemical production from SO2 and NOx to sulfate and nitrate, which offset the reduction of primary PM2.5 emissions especially in the haze days. This study indicated the importance of updating air pollutant emission inventories in simulating the complex atmospheric environment changes with the implications on air quality and environmental changes.

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

scholarly journals Comparison of emissions inventories of anthropogenic air pollutants and greenhouse gases in China

2017 ◽  
Vol 17 (10) ◽  
pp. 6393-6421 ◽  
Author(s):  
Eri Saikawa ◽  
Hankyul Kim ◽  
Min Zhong ◽  
Alexander Avramov ◽  
Yu Zhao ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Emission Inventory ◽  
Air Pollutant ◽  
Central China ◽  
Pollutant Emissions ◽  
Mitigation Measures ◽  
Economic Activities ◽  
Temporal And Spatial Distribution ◽  
Emissions Inventories

Abstract. Anthropogenic air pollutant emissions have been increasing rapidly in China, leading to worsening air quality. Modelers use emissions inventories to represent the temporal and spatial distribution of these emissions needed to estimate their impacts on regional and global air quality. However, large uncertainties exist in emissions estimates. Thus, assessing differences in these inventories is essential for the better understanding of air pollution over China. We compare five different emissions inventories estimating emissions of carbon dioxide (CO2), carbon monoxide (CO), nitrogen oxides (NOx), sulfur dioxide (SO2), and particulate matter with an aerodynamic diameter of 10 µm or less (PM10) from China. The emissions inventories analyzed in this paper include the Regional Emission inventory in ASia v2.1 (REAS), the Multi-resolution Emission Inventory for China (MEIC), the Emission Database for Global Atmospheric Research v4.2 (EDGAR), the inventory by Yu Zhao (ZHAO), and the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS). We focus on the period between 2000 and 2008, during which Chinese economic activities more than doubled. In addition to national totals, we also analyzed emissions from four source sectors (industry, transport, power, and residential) and within seven regions in China (East, North, Northeast, Central, Southwest, Northwest, and South) and found that large disagreements exist among the five inventories at disaggregated levels. These disagreements lead to differences of 67 µg m−3, 15 ppbv, and 470 ppbv for monthly mean PM10, O3, and CO, respectively, in modeled regional concentrations in China. We also find that all the inventory emissions estimates create a volatile organic compound (VOC)-limited environment and MEIC emissions lead to much lower O3 mixing ratio in East and Central China compared to the simulations using REAS and EDGAR estimates, due to their low VOC emissions. Our results illustrate that a better understanding of Chinese emissions at more disaggregated levels is essential for finding effective mitigation measures for reducing national and regional air pollution in China.

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