scholarly journals Spatial Disaggregation of Particulate Matter Emission Inventory in the Metropolitan Area of Aburr\'a Valley for Air Quality Modelling

2020 ◽  
Author(s):  
Santiago Lopez Restrepo ◽  
Andres Yarce ◽  
Nicolas Pinel ◽  
O. Lucia Quintero ◽  
Arjo Segers ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Metropolitan Area ◽  
Emission Inventory ◽  
Air Quality Modelling ◽  
Particulate Matter Emission ◽  
Spatial Disaggregation

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.

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 (5) ◽  
pp. 5837-5869 ◽  
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 ◽  
Fine Particulate Matter ◽  
Point Sources ◽  
Air Quality Modelling ◽  
Distribution Maps ◽  
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 km × 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 others using fractions based on 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 dataset 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 dataset. 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.

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 Regional-scale modelling for the assessment of atmospheric particulate matter concentrations at rural background locations in Europe

2020 ◽  
Vol 20 (11) ◽  
pp. 6395-6415
Author(s):  
Goran Gašparac ◽  
Amela Jeričević ◽  
Prashant Kumar ◽  
Branko Grisogono
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Regional Scale ◽  
Atmospheric Particulate Matter ◽  
Spatial And Temporal Variability ◽  
Pollution Transport ◽  
Air Quality Modelling ◽  
Rural Background ◽  
Stable Conditions ◽  
Regional Air Quality

Abstract. The application of regional-scale air quality models is an important tool in air quality assessment and management. For this reason, the understanding of model abilities and performances is mandatory. The main objective of this research was to investigate the spatial and temporal variability of background particulate matter (PM) concentrations, to evaluate the regional air quality modelling performance in simulating PM concentrations during statically stable conditions and to investigate processes that contribute to regionally increased PM concentrations with a focus on eastern and central Europe. The temporal and spatial variability of observed PM was analysed at 310 rural background stations in Europe during 2011. Two different regional air quality modelling systems (offline coupled European Monitoring and Evaluation Programme, EMEP, and online coupled Weather Research and Forecasting with Chemistry) were applied to simulate the transport of pollutants and to further investigate the processes that contributed to increased concentrations during high-pollution episodes. Background PM measurements from rural background stations, wind speed, surface pressure and ambient temperature data from 920 meteorological stations across Europe, classified according to the elevation, were used for the evaluation of individual model performance. Among the sea-level stations (up to 200 m), the best modelling performance, in terms of meteorology and chemistry, was found for both models. The underestimated modelled PM concentrations in some cases indicated the importance of the accurate assessment of regional air pollution transport under statically stable atmospheric conditions and the necessity of further model improvements.

scholarly journals Regional contributions to particulate matter concentration in the Seoul metropolitan area, South Korea: seasonal variation and sensitivity to meteorology and emissions inventory

2017 ◽  
Vol 17 (17) ◽  
pp. 10315-10332 ◽  
Author(s):  
Hyun Cheol Kim ◽  
Eunhye Kim ◽  
Changhan Bae ◽  
Jeong Hoon Cho ◽  
Byeong-Uk Kim ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Seasonal Variation ◽  
Air Quality ◽  
South Korea ◽  
Metropolitan Area ◽  
Policy Support ◽  
Seoul Metropolitan Area ◽  
Regional Air Quality ◽  
Emissions Inventories ◽  
The Impact

Abstract. The impact of regional emissions (e.g., domestic and international) on surface particulate matter (PM) concentrations in the Seoul metropolitan area (SMA), South Korea, and its sensitivities to meteorology and emissions inventories are quantitatively estimated for 2014 using regional air quality modeling systems. Located on the downwind side of strong sources of anthropogenic emissions, South Korea bears the full impact of the regional transport of pollutants and their precursors. However, the impact of foreign emissions sources has not yet been fully documented. We utilized two regional air quality simulation systems: (1) a Weather Research and Forecasting and Community Multi-Scale Air Quality (CMAQ) system and (2) a United Kingdom Met Office Unified Model and CMAQ system. The following combinations of emissions inventories are used: the Intercontinental Chemical Transport Experiment-Phase B, the Inter-comparison Study for Asia 2010, and the National Institute of Environment Research Clean Air Policy Support System. Partial contributions of domestic and foreign emissions are estimated using a brute force approach, adjusting South Korean emissions to 50 %. Results show that foreign emissions contributed  ∼  60 % of SMA surface PM concentration in 2014. Estimated contributions display clear seasonal variation, with foreign emissions having a higher impact during the cold season (fall to spring), reaching  ∼  70 % in March, and making lower contributions in the summer,  ∼  45 % in September. We also found that simulated surface PM concentration is sensitive to meteorology, but estimated contributions are mostly consistent. Regional contributions are also found to be sensitive to the choice of emissions inventories.

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 Diesel particulate matter emission factors and air quality implications from in–service rail in Washington State, USA

2014 ◽  
Vol 5 (2) ◽  
pp. 344-351 ◽  
Author(s):  
Daniel A. Jaffe ◽  
Greg Hof ◽  
Sofya Malashanka ◽  
Justin Putz ◽  
Jeffrey Thayer ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Emission Factors ◽  
Washington State ◽  
Diesel Particulate Matter ◽  
Diesel Particulate ◽  
Particulate Matter Emission
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