Evaluating long-term reductions in trace metal emissions from shipping in Shanghai.

J Hazard Mater

Function Hub, Thrust of Earth, Ocean and Atmospheric Sciences, The Hong Kong University of Science and Technology (Guangzhou), 511400 Guangzhou, China. Electronic address:

Published: December 2024

AI Article Synopsis

  • Shipping emissions significantly contribute to air pollution in coastal cities, prompting China to implement the Domestic Emission Control Area (DECA) policy in phases, which included stricter low-sulfur fuel mandates.
  • Long-term measurements at Dian Shan Lake showed a 63% decrease in vanadium (V) concentrations after DECA 2.0 was implemented, indicating improvements in air quality.
  • The study emphasizes the need for ongoing monitoring and suggests that nickel (Ni) emissions may come from sources beyond shipping, highlighting the complexity of managing air pollutants.

Article Abstract

Shipping emissions are a major contributor to air pollution in coastal cities, and Shanghai Port, the busiest port in the world, handles over 40 million TEU annually. To mitigate shipping emissions, China introduced the Domestic Emission Control Area (DECA) policy in phases: DECA 1.0 in 2016 and DECA 2.0 in 2019. DECA 1.0 mandated low-sulfur fuels (0.5 %) at berth and near major ports, down from 1.5 %, and this requirement was extended to a 12-nautical-mile emission control zone in DECA 2.0. In this study, we conducted long-term online measurements of shipping emission tracer of vanadium (V) and nickel (Ni), at the Dian Shan Lake (DSL) supersite, located approximately 50 km from Shanghai waters. The observed V concentration exhibited a strong dependence on wind direction, with higher levels from spring to summer due to more frequent marine winds compared to other seasons. The long-term measurement showed a significant decrease in V concentrations, dropping from an annual mean of 7.08 ng m³ during DECA 1.0 to 2.64 ng m³ during DECA 2.0. The represents a year-on-year reduction of 63 % based on measurement. To remove the meteorological impact on the measured concentration, a Random Forest (RF) machine learning model and the Community Multiscale Air Quality (CMAQ 5.4) model were applied under a business-as-usual (BAU) scenario. Both models produced consistent results, showing a reduction of up to 82 % in V concentrations in April with more frequent marine winds, confirming regional air quality improvements post-DECA 2.0. Additionally, we found that Ni has other sources that require further control beyond shipping. The study highlights the importance of long-term measurements for understanding the impact of air quality policies on emission patterns.

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Source
http://dx.doi.org/10.1016/j.jhazmat.2024.136367DOI Listing

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