These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


PUBMED FOR HANDHELDS

Search MEDLINE/PubMed


  • Title: Characterization of ammonia emissions from light-duty gasoline vehicles based on real-world driving and dynamometer measurements.
    Author: Wu L, Yu F, Luo H, Zhu M, Liao S, Liu J, Wu C, Horchler EJ, Ristovski Z, Zheng J.
    Journal: Sci Total Environ; 2024 Jun 15; 929():172644. PubMed ID: 38649054.
    Abstract:
    Ammonia (NH3) contributes significantly to the formation of particulate matter, and vehicles represent a major source of NH3 in urban areas. However, there remains a lack of comprehensive understanding regarding the emission characteristics of NH3 from vehicles. This study conducted real-world driving emission (RDE) measurements and dynamometer measurements on 33 light-duty gasoline vehicles (LDGVs) to investigate their emission characteristics and impact factors. The tested vehicles include China 3 to China 6 emission standards. The results show that the average NH3 emission factors of LDGVs decreased by >80 % from China 3 to China 6 emission standards. The results obtained from dynamometer measurements reveal that independent from other conventional pollutants (such as HCHO and NOx), NH3 emissions do not exhibit significant emission peaks during the hot- or cold-start phase. The RDE measurement covers a more comprehensive range of the vehicle's real-world driving conditions, resulting in higher NH3 emission factors compared with dynamometer measurements. The analysis of RDE measurements revealed that NH3 emissions are influenced by vehicle speeds and accelerations. Acceleration processes contribute approximately 50 % of total NH3 emissions over a driving period. Finally, using real driving speed, acceleration, and road gradient as input parameters, an NH3 emission rate model based on vehicle specific power was developed. This emission rate model enables a more precise reflection of LDGVs' NH3 emissions of LDGVs across diverse driving conditions and provides valuable data support for high-resolution inventories of vehicle NH3 emissions.
    [Abstract] [Full Text] [Related] [New Search]