Mitigating climate change by reducing particulate matter pollution from aircraft

通过减少飞机颗粒物污染来缓解气候变化

• 批准号: 576622-2022
• 负责人: Karatas, AhmetAE
• 金额: $ 1.82万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=743229
• 关键词: Mitigating; climate; change; reducing; particulate

Canada is aiming to be a leader in sustainable technologies. The aviation industry has fallen behind many other industries in terms of reducing its environmental footprint. Commercial aviation is responsible for 2-3% of global anthropogenic greenhouse gas emissions (GHG). Moreover, the contribution of aviation to climate change has been rapidly escalating as commercial air travel has been growing at an astounding rate. The total passenger traffic has more than tripled over the last 20 years and worldwide air cargo traffic has grown by about 50% in the last 15 years. Commercial aviation represents the fastest-growing source of GHG, soot, and NOX emissions. It is imperative for the health of our planet that engineers and researchers work to mitigate these effects.The proposed research collaboration between Toronto Metropolitan University (TMU) in Canada and Middle East Technical University (METU) in Turkey will explore emissions reduction strategies in gas turbine engines. Several detailed experiments to measure engine pollutants performed at TMU will generate experimental data which will be used to validate pollutant models developed at METU. The findings of this research will increase the robustness and technological readiness of pollutant models so they can be implemented into engine development programs.

加拿大的目标是成为可持续技术的领导者。 航空业在减少环境足迹方面落后于许多其他行业。商业航空占全球人为温室气体排放量的2-3%。此外，随着商业航空旅行以惊人的速度增长，航空业对气候变化的贡献正在迅速升级。在过去的20年里，总的客运量增加了两倍多，在过去的15年里，全球航空货运量增长了约50%。商用航空是增长最快的温室气体、烟尘和氮氧化物排放源。为了地球的健康，工程师和研究人员必须努力减轻这些影响。加拿大多伦多城市大学（TMU）和土耳其中东技术大学（METU）之间拟议的研究合作将探索燃气涡轮机发动机的减排策略。在TMU进行的测量发动机污染物的几个详细实验将产生实验数据，这些数据将用于验证METU开发的污染物模型。这项研究的结果将提高污染物模型的鲁棒性和技术准备程度，以便将其实施到发动机开发计划中。