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 (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.

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.


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

2017 ◽  
Author(s):  
Mauro Masiol ◽  
Roy M. Harrison ◽  
Tuan V. Vu ◽  
David C. S. Beddows

Abstract. Major airports are often located within or close to large cities; their impacts on the deterioration of air quality at ground level are amply recognised. The international airport of Heathrow is a major source of nitrogen oxides in the Greater London area, but its contribution to the levels of submicrometre particles is unknown, and is the objective of this study. Two sampling campaigns were carried out during warm and cold seasons at a site close to the airfield (1.2 km). Size spectra were largely dominated by ultrafine particles: nucleation particles (


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

Environments ◽  
2021 ◽  
Vol 8 (1) ◽  
pp. 2
Author(s):  
Peter Brimblecombe ◽  
Yonghang Lai

The COVID-19 pandemic made it critical to limit the spread of the disease by enforcing human isolation, restricting travel and reducing social activities. Dramatic improvements to air quality, especially NO2, have often characterised places under COVID-19 restrictions. Air pollution measurements in Sydney in April 2019 and during the lockdown period in April 2020 show reduced daily averaged NO2 concentrations: 8.52 ± 1.92 and 7.85 ± 2.92 ppb, though not significantly so (p1~0.15) and PM2.5 8.91 ± 4.94 and 7.95 ± 2.64 µg m−3, again a non-significant difference (p1~0.18). Satellite imagery suggests changes that parallel those at ground level, but the column densities averaged over space and time, in false-colour, are more dramatic. Changed human mobility could be traced in increasing times spent at home, assessed from Google Mobility Reports and mirrored in decreased traffic flow on a major road, suggesting compliance with the restrictions. Electricity demand for the State of New South Wales was low under lockdown in early April 2020, but it recovered rapidly. Analysis of the uses of search terms: bushfires, air quality, haze and air pollution using Google Trends showed strong links between bushfires and pollution-related terms. The smoke from bushfires in late 2019 may well have added to the general impression of improved air quality during lockdown, despite only modest changes in the ground level measurements. This gives hints that successful regulation of air quality requires maintaining a delicate balance between our social perceptions and the physical reality.


Atmosphere ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 62
Author(s):  
Robert Cichowicz ◽  
Maciej Dobrzański

Spatial analysis of the distribution of particulate matter PM10, PM2.5, PM1.0, and hydrogen sulfide (H2S) gas pollution was performed in the area around a university library building. The reasons for the subject matter were reports related to the perceptible odor characteristic of hydrogen sulfide and a general poor assessment of air quality by employees and students. Due to the area of analysis, it was decided to perform measurements at two heights, 10 m and 20 m above ground level, using measuring equipment attached to a DJI Matrice 600 unmanned aerial vehicle (UAV). The aim of the measurements was air quality assessment and investigate the convergence of the theory of air flow around the building with the spatial distribution of air pollutants. Considerable differences of up to 63% were observed in the concentrations of pollutants measured around the building, especially between opposite sides, depending on the direction of the wind. To explain these differences, the theory of aerodynamics was applied to visualize the probable airflow in the direction of the wind. A strong convergence was observed between the aerodynamic model and the spatial distribution of pollutants. This was evidenced by the high concentrations of dust in the areas of strong turbulence at the edges of the building and on the leeward side. The accumulation of pollutants was also clearly noticeable in these locations. A high concentration of H2S was recorded around the library building on the side of the car park. On the other hand, the air turbulence around the building dispersed the gas pollution, causing the concentration of H2S to drop on the leeward side. It was confirmed that in some analyzed areas the permissible concentration of H2S was exceeded.


2004 ◽  
Vol 82 (1) ◽  
pp. 19-26 ◽  
Author(s):  
Xin Zhou ◽  
Ai-Min Ren ◽  
Ji-Kang Feng ◽  
Xiao-Juan Liu

The one-photon absorption (OPA) properties of tetrabenzoporphyrins (TBPs) and phthalocyanines (Pcs) were studied using the semiempirical ZINDO method and time-dependent density functional theory (TDDFT), respectively. The compared results confirmed that the semiempirical ZINDO method was reasonably reliable when calculating the OPA of tetrabenzoporphyrins and phthalocyanines. On the basis of the OPA properties obtained from the ZINDO method, two-photon absorption (TPA) properties of two series of molecules were investigated, using ZINDO and sum-over-states (SOS) methods. The results showed that the TPA cross-sections of all molecules were in the range of 220.6 × 10–50 – 345.9 × 10–50 cm4·s·photon–1, which were in the same order of magnitude as the values reported in the literature. The relatively larger δ(ω) value for Pcs with respect to that for corresponding TBPs originates from larger intramolecular charge transfer, which can be characterized by the difference of dipole moment between S0 and S1 and the transition dipole moment between S1 and S5.Key words: two-photon absorption, ZINDO, sum-over-states, tetrabenzoporphyrin, phthalocyanines.


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.


2021 ◽  
Author(s):  
Mubarak Ali

<p>A carbon atom keeps a non-preserved behavior because of converting into another state. This character makes it adjacently coincide with oxygen atom when it is in the gaseous state. A field variation develops for the day and night. On having the suitable interaction of photons with leaves in daytime, pieces of arc-shaped energy are made. To get the ground surface, the pieces of arc-shaped energy become empty due to the highest value of gravity at ground level. On sunset, empty pieces of arc-shaped energy fill with the force having the levitating nature, so they start flying to gather under the tree roof. Such filled force pieces develop the affinity in adjacently coinciding atoms of gaseous carbon and oxygen. At certain behavior of force, the downward ends of filled force pieces enter into the suitable unfilled states of gaseous atoms adhering the binding of C - O or O - C - O. So, a large number of CO and CO<sub>2</sub> molecules develops under the tree roof, which is not good for breathing during the night. In the morning, an arc-shaped energy breaks the affinity in CO and CO<sub>2</sub> molecules by giving back the filled force. As a result, the molecules dissociate into the atoms. To get the ground surface, the dissociated gaseous carbon atoms converted into graphitic carbon before noon. So, the oxygen concentration during sunshine increases under the tree roof thereby improving the breathing level of the one resting in the shadow. So, COVID-19 patients can take advantage of the raised level of oxygen. But, it is not useful to rest under the tree roofs at night. How the plantation of trees can be essential for a sustainable environment helps build remarkable procedures and is being discussed here. </p>


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