Wednesday, November 23, 2016

2015 Volumes and Revenues for Several Rubbers

I searched the Internet extensively to find total global volumes and revenues for as many synthetic rubbers as I could.  Apparently more than two dozen commercially-available synthetic polymeric materials are generally considered to be similar enough in properties and uses to natural rubber as to generically be referred to as a rubber.  (Click here for a list of these at a Wikipedia site.)  Of these synthetic rubbers, I was only able to find sufficient volume and revenue data on seven from which I could construct the following table:

synthetic rubber
2015 volume metric ton (mt)
 2015 revenue (usd)
average price(usd)/ mt
styrene butadiene (sbr)
 $ 10,000,000,000
 $        1,429
silicon elastomers
 $    6,000,000,000
 $        3,000
polybutadiene (br)
 $    5,000,000,000
 $        1,429
ethylene propylene diene monomer (epdm)
 $    2,800,000,000
 $        2,154
polychloroprene (cr)
 $    1,200,000,000
 $        3,000
 $       700,000,000
 $      20,000
acrylonitrile butadiene (nbr)
 $       325,000,000
 $        2,097
 $ 26,025,000,000

I suspect one reason I could find only data for these seven “rubber-like materials” is that they represent the vast majority of total volume produced and revenue generated for the commercially-available synthetic polymers in the rubber category (those listed at the Wikipedia site).

The totals shown in the table agree well with what can be found on the Internet for total synthetic rubber produced globally in 2015 and the global revenues generated by that total.

I could find no single Internet site (source) that provides comprehensive data such as shown in the above table.    Searching and analysis is needed of a variety of sites to find the necessary data from which I believe a reasonably good determination can be made of volumes and revenues. The data in the table may not be exact but likely falls within a "smallish" range that is.

One conclusion I have is that very likely much volume and/or revenue data on the Internet implies more accuracy than is warranted because such data represent estimates.   And such estimates cannot be as accurate as the data often implies. 

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