Improvement of a Global High-Resolution Ammonia Emission Inventory for Combustion and Industrial Sources with New Data from the Residential and Transportation Sectors

2017 ◽  
Vol 51 (5) ◽  
pp. 2821-2829 ◽  
Author(s):  
Wenjun Meng ◽  
Qirui Zhong ◽  
Xiao Yun ◽  
Xi Zhu ◽  
Tianbo Huang ◽  
...  
Keyword(s):  
High Resolution ◽  
Emission Inventory ◽  
Ammonia Emission ◽  
Industrial Sources

A comprehensive ammonia emission inventory with high-resolution and its evaluation in the Beijing–Tianjin–Hebei (BTH) region, China

2015 ◽  
Vol 106 ◽  
pp. 305-317 ◽  
Author(s):  
Ying Zhou ◽  
Shuiyuan Cheng ◽  
Jianlei Lang ◽  
Dongsheng Chen ◽  
Beibei Zhao ◽  
...  
Keyword(s):  
High Resolution ◽  
Emission Inventory ◽  
Ammonia Emission ◽  
Bth Region

scholarly journals A high-resolution ammonia emission inventory in China

2012 ◽  
Vol 26 (1) ◽  
pp. n/a-n/a ◽  
Author(s):  
Xin Huang ◽  
Yu Song ◽  
Mengmeng Li ◽  
Jianfeng Li ◽  
Qing Huo ◽  
...  
Keyword(s):  
High Resolution ◽  
Emission Inventory ◽  
Ammonia Emission

High-resolution anthropogenic ammonia emission inventory for the Yangtze River Delta, China

Chemosphere ◽  
2020 ◽  
Vol 251 ◽  
pp. 126342 ◽  
Author(s):  
Xingna Yu ◽  
Li Shen ◽  
Xinhong Hou ◽  
Liang Yuan ◽  
Yuepeng Pan ◽  
...  
Keyword(s):  
High Resolution ◽  
Yangtze River ◽  
Emission Inventory ◽  
Yangtze River Delta ◽  
River Delta ◽  
Ammonia Emission ◽  
The Yangtze River ◽  
The Yangtze River Delta

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.

Modelling Seasonal Dynamics from Temporal Variation in Agricultural Practices in the UK Ammonia Emission Inventory

2007 ◽  
pp. 3-13 ◽  
Author(s):  
S. Hellsten ◽  
U. Dragosits ◽  
C. J. Place ◽  
T. H. Misselbrook ◽  
Y. S. Tang ◽  
...  
Keyword(s):  
Temporal Variation ◽  
Seasonal Dynamics ◽  
Emission Inventory ◽  
Agricultural Practices ◽  
Ammonia Emission ◽  
The Uk

scholarly journals Ammonia emission inventory for the state of Wyoming

2003 ◽  
Author(s):  
Thomas W. Kirchstetter ◽  
Colette R. Maser ◽  
Nancy J. Brown
Keyword(s):  
Emission Inventory ◽  
The State ◽  
Ammonia Emission

A high-resolution emission inventory of anthropogenic trace elements in Beijing-Tianjin-Hebei (BTH) region of China

2018 ◽  
Vol 191 ◽  
pp. 452-462 ◽  
Author(s):  
Chuanyong Zhu ◽  
Hezhong Tian ◽  
Yan Hao ◽  
Jiajia Gao ◽  
Jiming Hao ◽  
...  
Keyword(s):  
Trace Elements ◽  
High Resolution ◽  
Emission Inventory ◽  
Bth Region

Volatile organic compounds sources in Paris in spring 2007. Part II: source apportionment using positive matrix factorisation

2011 ◽  
Vol 8 (1) ◽  
pp. 91 ◽  
Author(s):  
Cécile Gaimoz ◽  
Stéphane Sauvage ◽  
Valérie Gros ◽  
Frank Herrmann ◽  
Jonathan Williams ◽  
...  
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compound ◽  
Organic Compounds ◽  
Emission Inventory ◽  
Positive Matrix ◽  
Air Mass ◽  
Volatile Organic ◽  
Industrial Sources ◽  
Fuel Evaporation ◽  
Matrix Factorisation

Environmental context Volatile organic compounds are key compounds in atmospheric chemistry as precursors of ozone and secondary organic aerosols. To determine their impact at a megacity scale, a first important step is to characterise their sources. We present an estimate of volatile organic compound sources in Paris based on a combination of measurements and model results. The data suggest that the current emission inventory strongly overestimates the volatile organic compounds emitted from solvent industries, and thus needs to be corrected. Abstract A positive matrix factorisation model has been used for the determination of volatile organic compound (VOC) source contributions in Paris during an intensive campaign (May–June 2007). The major sources were traffic-related emissions (vehicle exhaust, 22% of the total mixing ratio of the measured VOCs, and fuel evaporation, 17%), with the remaining emissions from remote industrial sources (35%), natural gas and background (13%), local sources (7%), biogenic and fuel evaporation (5%) and wood-burning (2%). It was noted that the remote industrial contribution was highly dependent on the air-mass origin. During the period of oceanic influences (when only local and regional pollution was observed), this source made a relatively low contribution (<15%), whereas the source contribution linked to traffic was high (54%). During the period of continental influences (when additional continental pollution was observed), remote industrial sources played a dominant role, contributing up to 50% of measured VOCs. Finally, the positive matrix factorisation results obtained during the oceanic air mass-influenced period were compared with the local emission inventory. This comparison suggests that the VOC emission from solvent industries might be overestimated in the inventory, consistent with findings in other European cities.

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