Inland vessels emission inventory: distribution and emission characteristics in the Red River, Hanoi, Vietnam. Issue 2 (28th February 2022)

• Record Type: Journal Article
• Authors: Nguyen, Dat; Hoang, Anh Le; Nguyen Vu, Minh Anh; Nguyen, Viet Thanh; Pham, Tram Anh
• Is Part Of: Frontiers in engineering and built environment. Volume 2:Issue 2(2022)
• Page Start: 95
• Page End: 106
• Publication Date: 2022-02-28
• Subjects: Emission inventory -- Inland vessels -- Red River -- Vietnam; Engineering; Civil engineering; Environmental engineering; Geotechnical engineering; Periodicals; 620
• DOI: 10.1108/FEBE-11-2021-0052
• Languages: English
• ISSNs: 2634-2499

Abstract

Abstract : Purpose: Shipping is a major source of air pollution, causing severe impacts on the environment and human health, greatly contributing to the creation of greenhouse gases and influencing climate change. The research was investigated to provide a better insight into the emission inventories in the Red River in Hanoi (Vietnam) that is often heavily occupied as the primary route for inner-city waterway traffic. Design/methodology/approach: The total emissions of seven different pollutants (PM10, PM2.5, SOx, CO, CO2, NOx and HC) were estimated using the SPD-GIZ emission calculation model. Findings: The results show that CO2 has the most significant contribution to the gas volume emitted: 103.21 tons/day. Remarkably, bulk carriers are the largest emission vehicle, accounting for more than 97% of total emissions, due to their superior number and large capacity. Social implications: The result to have a roadmap for making efforts to fulfil its commitment so that it could achieve its net-zero climate target by 2050 in Vietnam as committed at COP26. Originality/value: In this research, the number of vehicles and types of vessels travelling on the Red River flowing within Hanoi territory and other activity data are reported. The tally data will be used to estimate emissions of seven different pollutants (PM10, PM2.5, SOx, CO, CO2, NOx and HC) using a method combining both top-down and bottom-up approaches.