An intercomparative study of the effects of aircraft emissions on surface air quality

2017 ◽  
Vol 122 (15) ◽  
pp. 8325-8344 ◽  
Author(s):  
M. A. Cameron ◽  
M. Z. Jacobson ◽  
S. R. H. Barrett ◽  
H. Bian ◽  
C. C. Chen ◽  
...  
Author(s):  
Charles Gray ◽  
G. D. Kittredge

The Environmental Protection Agency has completed a study of the impact of aircraft emissions on air quality and a study of the technological feasibility of controlling aircraft emissions including an analysis of the cost and time requirements of the various control approaches. The air quality study has determined the need for aircraft emission standards, and the control technology study has determined that control is feasible and cost effective given adequate development time.


2013 ◽  
Vol 13 (18) ◽  
pp. 9285-9302 ◽  
Author(s):  
J. Rissman ◽  
S. Arunachalam ◽  
M. Woody ◽  
J. J. West ◽  
T. BenDor ◽  
...  

Abstract. This study examined the impacts of aircraft emissions during the landing and takeoff cycle on PM2.5 concentrations during the months of June and July 2002 at the Hartsfield–Jackson Atlanta International Airport. Primary and secondary pollutants were modeled using the Advanced Modeling System for Transport, Emissions, Reactions, and Deposition of Atmospheric Matter (AMSTERDAM). AMSTERDAM is a modified version of the Community Multiscale Air Quality (CMAQ) model that incorporates a plume-in-grid process to simulate emissions sources of interest at a finer scale than can be achieved using CMAQ's model grid. Three fundamental issues were investigated: the effects of aircraft on PM2.5 concentrations throughout northern Georgia, the differences resulting from use of AMSTERDAM's plume-in-grid process rather than a traditional CMAQ simulation, and the concentrations observed in aircraft plumes at subgrid scales. Comparison of model results with an air quality monitor located in the vicinity of the airport found that normalized mean bias ranges from −77.5% to 6.2% and normalized mean error ranges from 40.4% to 77.5%, varying by species. Aircraft influence average PM2.5 concentrations by up to 0.232 μg m−3 near the airport and by 0.001–0.007 μg m−3 throughout the Atlanta metro area. The plume-in-grid process increases concentrations of secondary PM pollutants by 0.005–0.020 μg m−3 (compared to the traditional grid-based treatment) but reduces the concentration of non-reactive primary PM pollutants by up to 0.010 μg m−3, with changes concentrated near the airport. Examination of subgrid-scale results indicates that median aircraft contribution to grid cells is higher than median puff concentration in the airport's grid cell and outside of a 20 km × 20 km square area centered on the airport, while in a 12 km × 12 km square ring centered on the airport, puffs have median concentrations over an order of magnitude higher than aircraft contribution to the grid cells. Maximum puff impacts are seen within the 12 km × 12 km ring, not in the airport's own grid cell, while maximum grid cell impacts occur within the airport's grid cell. Twenty-one (21)% of all aircraft-related puffs from the Atlanta airport have at least 0.1 μg m−3 PM2.5 concentrations. Near the airport, median daily puff concentrations vary between 0.017 and 0.134 μg m−3 (0.05 and 0.35 μg m−3 at ground level), while maximum daily puff concentrations vary between 6.1 and 42.1 μg m−3 (7.5 and 42.1 μg m−3 at ground level) during the 2-month period. In contrast, median daily aircraft contribution to grid concentrations varies between 0.015 and 0.091 μg m−3 (0.09 and 0.40 μg m−3 at ground level), while the maximum varies between 0.75 and 2.55 μg m−3 (0.75 and 2.0 μg m−3 at ground level). Future researchers may consider using a plume-in-grid process, such as the one used here, to understand the impacts of aircraft emissions at other airports, for proposed future airports, for airport expansion projects under various future scenarios, and for other national-scale studies specifically when the maximum impacts at fine scales are of interest.


Author(s):  
Claire Sarrat ◽  
Sébastien Aubry ◽  
Thomas Chaboud ◽  
Christine Lac

Local air quality is a major concern for the population regularly exposed to high levels of air pollution. The airport, mainly due to its aircraft engines activities during taxiing and take off, is often submitted to heterogeneous but important concentrations of NOx and PM. The study suggests an innovative approach to determine the air traffic impact on air quality at the scale of the airport, its runways and terminals, in order to be able to locate the persistent high concentrations spots. The pollutants concentrations at 10 m resolution and 1 s time step are calculated in order to identify the most affected areas of an airport platform. A real day of air traffic on a regional airport is simulated, using real data as aircraft trajectories (from radar streams). In order to estimate the aircraft emissions, the Air Transport Systems Evaluation Infrastructure (IESTA) is used. Regarding local air quality, IESTA relies on the non-hydrostatic meso-scale atmospheric model Meso-NH using grid-nesting capabilities with 3 domains, for this study. The detailed cartography of the airport distinguishes between grassland, parking and terminals, allowing to compute exchanges of heat, water and momentum between the different types of surfaces and the atmosphere as well as the interactions with the building using a drag force. The dynamic parameters like wind, temperature, turbulent kinetic energy and pollutants concentration are computed at 10 m resolution over the 2 × 4 km airport domain. The pollutants are considered in this preliminary study as passive tracers, without chemical reactions. This preliminary study aims at proving the feasibility of high scale modelling over an airport with state of the art physical models.


2011 ◽  
Vol 45 (36) ◽  
pp. 6526-6533 ◽  
Author(s):  
Yifang Zhu ◽  
Elinor Fanning ◽  
Rong Chun Yu ◽  
Qunfang Zhang ◽  
John R. Froines

2019 ◽  
Vol 304 ◽  
pp. 02023
Author(s):  
Víctor Archilla ◽  
Dévora Hormigo ◽  
María Sánchez-García ◽  
David Raper

Emissions from aircraft have adverse effects on the air quality in and around airports, contributing to public health concerns within neighbouring communities. AVIATOR will adopt a multi-level measurement, modelling and assessment approach to develop an improved description and quantification of the relevant aircraft engine emissions, and their impact on air quality under different climatic conditions. Particulate and gaseous emissions in a test cell and on-wing from an in-service aircraft will be measured to determine pollutant plume evolution from the engine and APU exhaust. This will provide an enhanced understanding of primary emitted pollutants, specifically the nvPM and vPM (down to 10nm), and the scalability between the regulatory test cell and real environments. AVIATOR will develop and deploy a proof-of-concept low cost sensor network for monitoring UFP, PM and gaseous species across multiple airports and surrounding communities. Campaigns will be complemented by high-fidelity modelling of aircraft exhaust dynamics, microphysical and chemical processes within the plume. CFD, box, and airport air quality models will be applied, providing validated parameterisations of the relevant processes, applicable to standard dispersion modelling on the local scale. Working with the regulatory community, AVIATOR will develop improved guidance on measuring and modelling the impact of aircraft emissions, and will provide airports and regulators with tools and guidance to improve the assessment of air quality in and around airports.


2013 ◽  
Vol 13 (1) ◽  
pp. 1089-1132 ◽  
Author(s):  
J. Rissman ◽  
S. Arunachalam ◽  
M. Woody ◽  
J. J. West ◽  
T. BenDor ◽  
...  

Abstract. This study examined the impacts of aircraft emissions during the landing and takeoff cycle on PM2.5 concentrations during the months of June 2002 and July 2002 at the Hartsfield-Jackson Atlanta International Airport. Primary and secondary pollutants were modeled using the Advanced Modeling System for Transport, Emissions, Reactions, and Deposition of Atmospheric Matter (AMSTERDAM). AMSTERDAM is a modified version of the Community Multiscale Air Quality (CMAQ) model that incorporates a plume-in-grid process to simulate emissions sources of interest at a finer scale than can be achieved using CMAQ's model grid. Three fundamental issues were investigated: the effects of aircraft on PM2.5 concentrations throughout northern Georgia, the differences resulting from use of AMSTERDAM's plume-in-grid process rather than a traditional CMAQ simulation, and the concentrations observed in aircraft plumes at sub-grid scales. Comparison of model results with an air quality monitor located in the vicinity of the airport found that normalized mean bias ranges from −77.5% to 6.2% and normalized mean error ranges from 40.4% to 77.5%, varying by species. Aircraft influence average PM2.5 concentrations by up to 0.232 μg m−3 near the airport and by 0.001–0.007 μg m−3 throughout the Atlanta metro area. The plume-in-grid process increases concentrations of secondary PM pollutants by 0.005–0.020 μg m−3 (compared to the traditional grid-based treatment) but reduces the concentration of non-reactive primary PM pollutants by up to 0.010 μg m−3, with changes concentrated near the airport. Examination of sub-grid scale results indicates that puffs within 20 km of the airport often have average PM2.5 concentrations one order of magnitude higher than aircraft contribution to the grid cells containing those puffs, and within 1–4 km of emitters, puffs may have PM2.5 concentrations 3 orders of magnitude greater than the aircraft contribution to their grid cells. 21% of all aircraft-related puffs from the Atlanta airport have at least 0.1 μg m−3 PM2.5 concentrations. Median daily puff concentrations vary between 0.017 and 0.134 μg m−3, while maximum daily puff concentrations vary between 6.1 and 42.1 μg m−3 during the 2-month period. In contrast, median daily grid concentrations vary between 0.015 and 0.091 μg m−3, while maximum daily grid concentrations vary between 0.751 and 2.55 μg m−3. Future researchers may consider using AMSTERDAM to understand the impacts of aircraft emissions at other airports, for proposed future airports, for airport expansion projects under various future scenarios, and for other national-scale studies specifically when the maximum impacts at fine scales are of interest.


2018 ◽  
Vol 72 ◽  
pp. 198-207 ◽  
Author(s):  
Xiaowen Yang ◽  
Shuiyuan Cheng ◽  
Jianlei Lang ◽  
Ran Xu ◽  
Zhe Lv

2017 ◽  
Vol 122 (24) ◽  
pp. 13,472-13,494 ◽  
Author(s):  
L. P. Vennam ◽  
W. Vizuete ◽  
K. Talgo ◽  
M. Omary ◽  
F. S. Binkowski ◽  
...  

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