GlobalData: Global iron ore consumption to drop by 2.8%
Published by John Williams,
Editorial Assistant
Global Mining Review,
The impact of COVID-19 on the mining industry has been strained by the struggling global automotive industry, which consumes approximately 17% of iron ore globally. Global light vehicle sales fell by 24% in 1Q20, then 47.5% in April and 33.8% in May. Although sales were boosted by improvements in China in May, where light vehicle sales rose by 8.1% y/y, over the second quarter global sales are expected to drop by 34%. Slow demand in the automotive space will have a knock-on effect and reduce demand for iron ore, says GlobalData, a leading data and analytics company.
Vinneth Bajaj, Senior Mining Analyst at GlobalData, comments: “COVID-19 is expected to significantly impact global iron ore consumption, which is projected to drop by 2.8% to reach 2034.6 million t in 2020. This drop reflects how the market has been directly affected by COVID-19, with workers unable to get to sites and severe disruption to the delivery of key materials and equipment, as well as the impact of widespread disruption to economic activity.
Due to the likely drop in investment, with planned projects in commercial and industrial buildings sectors potentially being put on hold or cancelled, GlobalData expects the global construction output to contract by 2.8% in 2020.
Bajaj concluded: “Only once the virus is under control can the industry rebound and global demand return. In the long-term, it is expected that global iron ore consumption will grow at a compound annual growth rate (CAGR) of 1.3% over the forecast-period (2021 - 2024), to reach 2193.8 million t in 2024 – supported by a strong demand for growth in India and China, alongside continuous development across Russia, Japan, South Korea and Brazil.
Read the article online at: https://www.globalminingreview.com/finance-business/02072020/globaldata-global-iron-ore-consumption-to-drop-by-28/
You might also like
Taking Control With Artificial Intelligence
Jürgen Kern, Mario Gerards, and Michael Panholzer, ANDRITZ, examine how adopting AI-based control systems in the filtration process can result in higher reliability and lower operating costs.