Observing network effect of shipping emissions from space: A natural experiment in the world’s busiest port

Author:

Liu Song1ORCID,Li Xicheng1,Li Juan1,Shu Lei2,Fu Tzung-May134,Yang Xin134ORCID,Zhu Lei134ORCID

Affiliation:

1. School of Environmental Science and Engineering, Southern University of Science and Technology , Shenzhen 518055 , China

2. School of Geographical Sciences, Fujian Normal University , Fuzhou 350007 , China

3. Guangdong Provincial Observation and Research Station for Coastal Atmosphere and Climate of the Greater Bay Area , Shenzhen 518055 , China

4. Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology , Shenzhen 518055 , China

Abstract

AbstractMaritime trade and associated emissions are dynamic in nature. Although shipping emissions contribute significantly to air quality and climate change, their trade-governed dynamics remain less explored due to the lack of observational evidence. Here, we use satellite measurements to capture the redistribution of shipping nitrogen oxides (NOx) emissions from Shanghai port, the world’s busiest port, during a natural experiment posted by the localized COVID-19 lockdown in 2022. Viewing the ports as nodes in a network linked by ship journeys, we quantify a lockdown-induced −42% reduction in shipping NOx emissions for Shanghai port. We further identify an emission transfer to its neighboring connected ports, confirmed by comprehensive vessel activity observations. Our study highlights the socioeconomic drivers of shipping emissions, which may add additional layers of complexity to air quality management.

Funder

National Natural Science Foundation for Young Scientists of China

Key-Area Research and Development Program of Guangdong Province

Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks

Guangdong Basic and Applied Basic Research Foundation

Guangdong Basic and Applied Basic Research Fund

Guangdong University Research Project Science Team

Shenzhen Science and Technology Program

Center for Computational Science and Engineering at Southern University of Science and Technology

Publisher

Oxford University Press (OUP)

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