Elemental Composition of HULIS in the Pearl River Delta Region, China: Results Inferred from Positive and Negative Electrospray High Resolution Mass Spectrometric Data

2012 ◽  
Vol 46 (14) ◽  
pp. 7454-7462 ◽  
Author(s):  
Peng Lin ◽  
Angela G. Rincon ◽  
Markus Kalberer ◽  
Jian Zhen Yu
2011 ◽  
Vol 11 (12) ◽  
pp. 33733-33783 ◽  
Author(s):  
J. Y. Zheng ◽  
S. S. Yin ◽  
D. W. Kang ◽  
W. W. Che ◽  
L. J. Zhong

Abstract. Detailed NH3 emission inventories are important to understand various atmospheric processes, air quality modeling study, air pollution management, and related environmental and ecological issues. A high-resolution NH3 emission inventory is developed based on the state-of-the-science techniques, the up-to-date information, and the advanced expert knowledge for the Pearl River Delta region, China. To provide model-ready emissions input, this NH3 emissions inventory is spatially allocated to 3 km × 3 km grid cells using source-based spatial surrogates with Geographical Information System (GIS) technology. For NH3 emissions, 9 source categories and 45 sub-categories are identified in this region, and detailed spatial and temporal characteristics are investigated. Results show that livestock is by far the most important NH3 emission source that contributes about 61.7% of the total NH3 emissions in this region, followed by nitrogen fertilizer applications (~23.7%) and non-agricultural sources (~14.6%). Uncertainty analysis reveals that the uncertainties associated with different sources vary from source to source and the magnitude of the uncertainty associated with a specific source mainly depends on the degree of accuracy of the emission factors and activity data as well as the technique used to perform the estimate. The validity of the NH3 emissions inventory is justified by the trend analysis of local rainwater compositions, especially pH values, the Ca2+ + NH4+/SO42− + NO3− ratios, and NH4+ concentrations which are directly or indirectly related to NH3 emissions. Based on the analysis, recommendations for additional work to further improve the accuracy of the NH3 emissions inventory are also discussed and proposed.


2012 ◽  
Vol 12 (15) ◽  
pp. 7041-7058 ◽  
Author(s):  
J. Y. Zheng ◽  
S. S. Yin ◽  
D. W. Kang ◽  
W. W. Che ◽  
L. J. Zhong

Abstract. Detailed NH3 emission inventories are important to understand various atmospheric processes, air quality modeling studies, air pollution management, and related environmental and ecological issues. A high-resolution NH3 emission inventory was developed based on state-of-the-science techniques, up-to-date information, and advanced expert knowledge for the Pearl River Delta region, China. To provide model-ready emissions input, this NH3 emissions inventory was spatially allocated to 3 km × 3 km grid cells using source-based spatial surrogates with geographical information system (GIS) technology. For NH3 emissions, 9 source categories and 45 subcategories were identified in this region, and detailed spatial and temporal characteristics were investigated. Results show that livestock is by far the most important NH3 emission source by contributing about 61.7% of the total NH3 emissions in this region, followed by nitrogen fertilizer applications (~23.7%) and non-agricultural sources (~14.6%). Uncertainty analysis reveals that the uncertainties associated with different sources vary from source to source and the magnitude of the uncertainty associated with a specific source mainly depends on the degree of accuracy of the emission factors and activity data as well as the technique used to perform the estimate. Further studies should give priority to the hog, broiler, goose subsectors of the livestock source and N fertilizer application source in order to reduce uncertainties of ammonia emission estimates in this region. The validity of the NH3 emissions inventory is justified by the trend analysis of local precipitation compositions, such as pH values, the Ca2++NH4+/SO42−+ NO3− ratios, and NH4+ concentrations which are directly or indirectly related to NH3 emissions.


Geothermics ◽  
2021 ◽  
Vol 96 ◽  
pp. 102164
Author(s):  
Zheng-An Wei ◽  
Haibing Shao ◽  
Ling Tang ◽  
Bin Deng ◽  
Hailong Li ◽  
...  

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