Chemistry Reference
In-Depth Information
With the ever-increasing information in databases of analytical methods, users have the data they need to
support more informed selections of methods and to improve the greenness of analytical laboratory operations.
The most common parameter - the E-factor [71] - is in principle very simple and well suited to
characterizing chemical processes. Although it does not consider material life cycle stages apart from
production, the E-factor is a measure of environmental impact and sustainability that is often employed by
chemists. The E-factor consists of the ratio of product to the total inputs (or all materials used in the production
process) and is expressed by the following equation:
input material kg
[
E
=
.
product kg
[]
The E-factor takes into account all the chemicals involved in production. Energy and water inputs are
generally not included in E-factor calculations, nor are products of combustion, such as water vapour or
carbon dioxide. Because of its simplicity and despite the challenges of including recycled compounds in
formulas, this parameter is attracting attention and is even being used to analyse complex processes [72].
However, the E-factor is not directly applicable to analytical chemistry because the 'product' of an analytical
laboratory is not quantifiable in kilograms, so the equation cannot be used to calculate its E-factor. All
chemicals and solvents could in principle become waste, even after careful recycling. However, the ratio of
the requisite amount of chemicals and solvents to the amount of sample required to obtain a measurable
analytical signal can be used to compare different analytical methods.
Atom economy is another important metric of material efficiency in green chemistry [73]. Atom economy
calculates the efficiency with which atoms that are used as feedstocks in chemical transformations are
incorporated into the final product. Unlike the E-factor, which is based on the specific conditions and
circumstances of a process, atom economy is an intrinsic metric that measures the theoretical efficiency of a
process under perfect conditions. This metric is most frequently applied to chemical transformations in which
substances of discrete molecular structure are transformed into new, homogeneous target products.
In analytical chemistry, an efficiency parameter could be developed based on analytical signals. To apply
this approach to analytical measurements, it must be possible to assess how many molecules of analyte will
give a measurable analytical signal where the theoretical limits of one molecule are known. Optical
spectroscopy, especially fluorescence, electrochemistry and bioanalysis are areas of analytical chemistry
with highly sensitive methods, due to the extremely selective nature of the reactions. According to this
approach, the sensitivity of the method correlates with its greenness.
Unfortunately, it is rare that a single analyte can be analysed without an interfering matrix; the sample
preparation is usually complex, and the calculations are therefore more complicated.
Energy metrics are usually similar to those for mass; one can take into account all forms of energy, such as
that used for heating or cooling per kg of product.
Some potential metrics might include [74]:
Total process energy MJ
[
]
,
Energy Intensity
=
product kg
[]
and
Life Cycle energy requirements MJ
[
]
Life Cycle Energy
=
product kg
[]
in which all energy requirements for every step are included into the life cycle (process, material manufacturing,
recovery, treatment).
