Investigation of emissions from passenger flights Denizli Çardak Airport, Türkiye

Author:

Çil Mehmet AliORCID,Tarhan CevahirORCID

Abstract

AbstractDue to developing aviation sector, number of aircraft in the world is increasing. Along with this development, problems such as the decrease in air quality in and around the airport also arise. In this study, it is tried to calculate pollutant emissions occurring in 2022 during the LTO cycles of Denizli Çardak Airport in Turkey. These calculations are based on the information obtained from ICAO Engine Emission Data Bank and flight information published by the General Directorate of State Airports Authority (GDSAA). As a result of the data obtained, 74.64 ton/year pollutants (NOx-37.148 t/y, CO-35.398 t/y and HC-2.094 t/y) were calculated for 2022 at Denizli Çardak Airport. Of all emissions, NOx accounted for 50%, CO 47% and HC 3%. In the LTO cycle, the most fuel is burned in taxi cycle and pollutant emissions produced in this cycle are greater. With a 2 min reduction in taxi time, there will be an approximate 6.8% reduction in the total emission rate in the LTO cycle. Similarly, with a 4 min reduction in taxi time, there will be a 13.72% reduction in the whole emission rate in the LTO cycle. Unlike other studies, in this study the emission rates of various engines were compared. It has been calculated that the amount of pollutant emissions produced by the new generation Boeing 737 MAX LEAP-1B powered aircraft in LTO cycle is 25% less than the amount of pollutant emissions produced by the Airbus A320 NEO LEAP-1 A powered aircraft. The biggest factor here is that the emission of CO pollutants is less. Considering the emission rates produced by these four different engines (B737-800 CFM56-7B, A320 V2500-A1, B737 MAX LEAP-1B, A320 NEO LEAP-1 A), the Airbus A320 V2500-A1 engine is a more environmentally friendly engine than the other engines.

Funder

Erciyes University

Publisher

Springer Science and Business Media LLC

Reference47 articles.

1. Aviation and the Global Atmosphere: A Special Report of the. (n.d.). Retrieved May 25, 2023, from https://books.google.com.tr/books?hl=tr&lr=&id=JgphajrWfOsC&oi=fnd&pg=PP9&ots=NdNeDQnlY8&sig=sSO_0u_g8Yd1_ob5E3fwF64-GK0&redir_esc=y#v=onepage&q&f=false

2. Barceló J, Montero L, Marqués L, Carmona C (2010) Https://Doi Org/ 217519–27. https://doi.org/10.3141/2175-03. Travel Time Forecasting and Dynamic Origin-Destination Estimation for Freeways Based on Bluetooth Traffic Monitoring

3. Boeing (2022) Annual Report. (n.d.). Retrieved April 10, 2023, from https://www.boeing.com/resources/boeingdotcom/company/annual-report/2022/Boeing-2022-Annual-Report.pdf

4. Boeing (2021) (n.d.). Retrieved May 21, 2023, from https://www.boeing.com/resources/boeingdotcom/market/assets/downloads/CMO%202021%20Report_13Sept21.pdf

5. Bombardier (2023) (2023). https://bombardier.com/sites/default/files/en/supporting_docs/BCA_2009_Market_Forecast.pdf

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3