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Sci Total Environ ; 526: 187-95, 2015 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-25933290

RESUMO

Many household batteries worldwide still end up in landfills or are incinerated due to inefficient collection and recycling schemes. Toxic heavy metals from improperly discarded button cells pose a serious risk to human health and the environment, as they can pollute air, soil and water. This paper analyses a series of button cells selected from batteries available on the retail market, and compares their polluting potential. A total of 64 batteries were subjected to chemical analyses of 19 elements - including metals and metalloids - , and energy density measurements. The samples were from four different brands of each of the four most common button cell technologies (alkaline, zinc-air, silver oxide and lithium). An energy-normalized index - the Weighted Potential Pollution Index (WPPI) - was proposed to compare the polluting potential of the different batteries. The higher the battery WPPI score, the greater the content in toxic elements and the lower the energy output. The results of the chemical composition and energy density varied depending on the construction technology of the button cells. However, significant differences in both variables were also found when comparing different brands within the same technology. The differences in WPPI values confirmed the existence of a significant margin to reduce the environmental impact of discarded button cells simply by avoiding the most polluting options. The choice of the battery with the most favourable WPPI produced a reduction in potential pollution of 3-53% for silver oxide batteries, 4-39% for alkaline, 20-28% for zinc-air and 12-26% for lithium. Comparative potential pollution could be assessed when selecting batteries using an energy-normalized index such as WPPI to reduce the environmental impact of improperly disposed button cells.


Assuntos
Fontes de Energia Elétrica , Metais Pesados/análise , Eliminação de Resíduos , Poluição Ambiental/estatística & dados numéricos , Medição de Risco
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