Hard market: consumption and production of cement

Pavel Prikhodko, Ph.D. Machine Learning

Cement is one of the world’s key building materials, both in the residential and non-residential sectors. This material is also used in the production of concrete. Thus, over 70 percent of cement sales in the United States were made to producers of ready-mixed concrete, and about 12 percent of sales went to concrete product manufacturers. According to information published at Statista.com, around 4,100 million metric tons of cement were produced globally in 2015. The U.S. accounted for about 83.4 million metric tons of this production. The year before, 4,180 million metric tons of material were produced worldwide, and 83.2 million metric tons were produced in the U.S. In 2013, these numbers decreased: 4,080 million metric tons globally and about 77.4 million metric tons in the U.S.

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In 2012, around 74.9 million metric tons of cement were produced in the country compared to 3,800 million metric tons around the world. In 2011 and 2010, the global production numbers amounted to 3,600 million metric tons and 3,310 million metric tons respectively. In the U.S., the production of cement amounted to approximately 68.6 million metric tons and 67.2 million metric tons of cement.

Let’s have a look at the statistics representing the apparent cement consumption in the United States. We can see that in 2015, the consumption of cement, which is mainly used in the construction industry, approximated to 93 million metric tons. In 2014, the country consumed about 89.2 million metric tons of this building material. In 2013 and 2012, the numbers amounted to 81.7 million metric tons and 77.9 million metric tons respectively.

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In 2015, the cost of cement came to $105.50 per metric ton, the highest price in recent years. In 2014, one metric ton of cement cost $100.50. In 2013, cement was valued at $95 per metric ton. The price stayed the same in 2012 and 2011: $89.50 per metric ton of building material.

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About Pavel Prikhodko

Pavel Prikhodko, Ph.D. Machine Learning

Pavel has worked for many years as a researcher and developer on a wide range of applications (varying from mechanics and manufacturing to social data, finance and advertising), building predictive systems and trying to find stories that data can tell.

In his free time, he enjoys being with his family.

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