Contemporary Anthropogenic Silver Cycle:  A Multilevel Analysis

Abstract

Anthropogenic cycling of silver in 1997 is presented using three discrete governmental units: 64 countries encompassing what we believe to be over 90% of global silver flows, 9 world regions, and the entire planet. Using material flow analysis (MFA) techniques, the country level cycles are aggregated to produce the regional cycles, which are used to form a "best estimate" global cycle. Interesting findings include the following: (1) several silver-mining countries export ore and concentrate but also import silver-containing semiproducts and products; (2) the level of development for a country, as indicated by the gross domestic product, is a fair indicator of silver use, but several significant outliers exist; (3) the countries with the greatest mine production include Mexico, the United States, Peru, and China, whereas the United States, Japan, India, Germany, and Italy lead in the fabrication and manufacture of products; (4) North America and Europe's use of silver products exceed that of other regions on a per capita basis; (5) global silver discards, including tailings and separation waste, totaled approximately 57% of the silver mined; (6) approximately 57% of the silver entering waste management globally is recycled; and (7) the amount of silver entering landfills globally is comparable to the amount found in tailings. The results of this MFA lay the basis for further analysis, which in turn can offer insight into natural resource policy, the characterization of environmental impact, and better resource management.

Global Substance Flow Analysis of Indium

“…It is likely that the lost indium is in the mining tailings and the sludge from smelters. The yield rates for other metals were estimated as follows: 86% for copper, 26) 73% for silver, 27) 73% for chromium, 28) 82% for zinc 7) and 87% for nickel. 29) These figures demonstrate that the yield rate for indium is significantly lower than those for other metals, which may be attributed to the difficulty of extracting indium compared with other metals.…”

Density Functional Theory Studies of Structural Properties and Natural Bond Orbital for a New Silver Halo Compound

“…Silver compounds are used for the coating of photographic and X-ray film. Photography materials are the major source of discarded silver [13]. Silver can enter your body through your skin, such as photographers touching powders with silver in them.…”

Analysis of Aluminum Resource Supply Structure and Guarantee Degree in China Based on Sustainable Perspective

“…Consequently, the information provide a base and support to design and make resource policies; many research fields are involved in the following: (1) analysis of quantities in the entire system-Chen researched the whole life cycle of aluminum including production, trade, consumption, stocks, and losses using the SFA method [8][9][10]15,29]; Buchner analyzed Austrian aluminum flows in 2010 using a static SFA model and conducted extensive research on aluminum production, consumption, trade, and waste management [30]; (2) recycling and sustainability-Melo developed several models (statistical approaches) for estimating the potential scrap arising from discard metal-containing products to predict the amount of aluminum old scrap in the waste management stage in Germany [31]; Boin and Bertram carried out mass balance analysis in the aluminum recycling industry for the EU-15 in 2002 [32]; Hatayama et al reported a dynamic SFA of aluminum and its alloying elements in Japan to estimate future quantities of discarded aluminum in each of the eight categories using a population balance model [33]; (3) combining with other aspects such as value chain and environment; Dhalström analyzed aluminum flows in the United Kingdom in 2001 combining SFA with economic and environmental dimensions to create a value chain analysis [34]; Gang developed a dynamic SFA model to simulate the stocks and flows of the U.S. aluminum cycle and analyze the corresponding greenhouse gas (GHG) emissions [13]. Of course, this wonderful methodology was also conducted to research other metals, such as copper [35][36][37][38][39][40], nickel [41], zinc [39,42,43], iron [26], lead [44,45], silver [46], phosphorus [47,48], and so on. In recent years, this method has been applied at a more micro level, and used to measure the recovery rate, recovery amount, and recovery potential of a certain kind of product within a region or a small area [49][50]…”