scholarly journals A plume-in-grid approach to characterize air quality impacts of aircraft emissions at the Hartsfield-Jackson Atlanta International Airport

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.

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.


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

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

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ilkay Orhan

Purpose The purpose of this study is to present the pollutant gas produced by hydrocarbons (HC), carbon monoxide (CO) and nitrogen oxides (NOx) and the quantity of fuel burned from commercial aircraft at Ordu-Giresun International Airport, Turkey during the landing and take-off (LTO) cycles in 2017. Design/methodology/approach The flight data recorded by the General Directorate of State Airports Authority and the aircraft engine emission data from International Civil Aviation Organization (ICAO) Engine Exhaust Emission Databank were used for calculation. The aircraft and engine types used by the airlines for flight at Ordu-Giresun International Airport were determined. To evaluate the effect of taxi time on emission amounts, analysis and evaluations were made by taking different taxi times into consideration. Findings As a result of the emission analysis, the amount of fuel consumed by the aircraft were calculated as 6,551.52 t/y, and the emission amounts for CO, HC and NOx were estimated as 66.81, 4.20 and 79.97 t/y, respectively. Practical implications This study is aimed to reveal the effect and contribution of taxi time on the emitted emission at the airport during the LTO phase of the aircraft. Originality/value This study helps aviation authorities explain the importance of developing procedures that ensure the delivery of aircraft to flights in minimum time by raising awareness of the impact of taxi time on emitted emissions, and contributes to the determination of an aircraft emission inventory at Ordu-Giresun International Airport.


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

2013 ◽  
Vol 120 ◽  
pp. 234-247 ◽  
Author(s):  
Jeffrey Rissman ◽  
Saravanan Arunachalam ◽  
Todd BenDor ◽  
J. Jason West

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.


2020 ◽  
Vol 20 (13) ◽  
pp. 7843-7873 ◽  
Author(s):  
Mariano Mertens ◽  
Astrid Kerkweg ◽  
Volker Grewe ◽  
Patrick Jöckel ◽  
Robert Sausen

Abstract. Land transport is an important emission source of nitrogen oxides, carbon monoxide, and volatile organic compounds. The emissions of nitrogen oxides affect air quality directly. Further, all of these emissions serve as a precursor for the formation of tropospheric ozone, thus leading to an indirect influence on air quality. In addition, ozone is radiatively active and its increase leads to a positive radiative forcing. Due to the strong non-linearity of the ozone chemistry, the contribution of emission sources to ozone cannot be calculated or measured directly. Instead, atmospheric chemistry models equipped with specific source attribution methods (e.g. tagging methods) are required. In this study we investigate the contribution of land transport emissions to ozone and ozone precursors using the MECO(n) model system (MESSy-fied ECHAM and COSMO models nested n times). This model system couples a global and a regional chemistry climate model and is equipped with a tagging diagnostic. We investigate the combined effect of long-range-transported ozone and ozone which is produced by European emissions by applying the tagging diagnostic simultaneously and consistently on the global and regional scale. We performed two simulations each covering 3 years with different anthropogenic emission inventories for Europe. We applied two regional refinements, i.e. one refinement covering Europe (50 km resolution) and one covering Germany (12 km resolution). The diagnosed absolute contributions of land transport emissions to reactive nitrogen (NOy) near ground level are in the range of 5 to 10 nmol mol−1. This corresponds to relative contributions of 50 % to 70 %. The largest absolute contributions appear around Paris, southern England, Moscow, the Po Valley, and western Germany. The absolute contributions to carbon monoxide range from 30 nmol mol−1 to more than 75 nmol mol−1 near emission hot-spots such as Paris or Moscow. The ozone which is attributed to land transport emissions shows a strong seasonal cycle with absolute contributions of 3 nmol mol−1 during winter and 5 to 10 nmol mol−1 during summer. This corresponds to relative contributions of 8 % to 10 % during winter and up to 16 % during summer. The largest values during summer are confined to the Po Valley, while the contributions in western Europe range from 12 % to 14 %. Only during summer are the ozone contributions slightly influenced by the anthropogenic emission inventory, but these differences are smaller than the range of the seasonal cycle of the contribution to land transport emissions. This cycle is caused by a complex interplay of seasonal cycles of other emissions (e.g. biogenic) and seasonal variations of the ozone regimes. In addition, our results suggest that during events with large ozone values the ozone contributions of land transport and biogenic emissions increase strongly. Here, the contribution of land transport emissions peaks up to 28 %. Hence, our model results suggest that land transport emissions are an important contributor during periods with large ozone values.


Sign in / Sign up

Export Citation Format

Share Document