Green analytical chemistry metrics

Размещено на http://www.allbest.ru/

MINISTRY OF EDUCATION OF THE REPUBLIC OF BELARUS

BELARUSIAN STATE UNIVERSITY

FACULTY OF CHEMISTRY

Department of Physical Chemistry

Green analytical chemistry metrics

ESAEV MIKHAIL ANATOLYEVICH

MIKHALEV ARTYOM KONSTANTINOVYCH



Table of Contents

• green environment metric index
• List of abbreviations
• Introduction
• 1. Principles of Green Analytical Metrics
• 1.1 National Environment Method Index
• 1.2 Analytical GREEnness Metric Approach and Software
• 1.3 Green Analytical Procedure Index
• 1.4 Complementary green analytical procedure index (ComplexGAPI)
• 1.5 RGB Additive Color Model to Analytical Method Evaluation
• 1.6 Eco-scale
• 2. Application of GAC metrics
• 2.1 AGREE
• 2.2 GAPI
• 2.3 NEMI
• 2.4 Complementary green analytical procedure index (ComplexGAPI)
• 2.5 RGB Additive Color Model to Analytical Method Evaluation
• 2.6 Examples of analytical Eco-Scale calculation
• 3. Problems and solutions
• 3.1 Qualitative problems
• 3.2 Quantitative problems
• Conclusion
• Bibliography
• 

List of abbreviations

EPA - Environmental Protection Agency

GAC - Green Analytical Chemistry

GAPI - Green Analytical Procedure Index

GC-MS - Gas Chromatography Mass Spectrometry

HPLC - High Performance Liquid Chromatography

NEMI - National Environmental Method Index

NFPA - National Fire Protection Association

RGB - Red, Green, Blue

TRI - Toxic Release Inventory



Introduction

The concept of green chemistry was introduced at the beginning of the 1990s and can be can be perceived as a contribution of chemists to sustainable development [1, 2]. The principal aim of green chemistry is reduction and elimination of the use and he generation of hazardous substances. In turn, organic chemistry makes a significant contribution to the use and the generation of hazardous substances. For that very reason, the direction of the development of green organic synthesis dominated for a decade. In 1999, the term “Green Analytical Chemistry” (GAC) was proposed [3] and, at the same year, Paul Anastas drew attention to the need of the development of green analytical methodology. While green chemistry metric systems, mainly applied in chemical synthesis, usually refer to the mass of the product, this is not a viable approach in the case of analytical chemistry, where there is no obvious product with a particular mass. Thus, it is obvious that GAC requires dedicated to evaluate the degree of greenness of analytical methods. At the same time, finding the appropriate way to assess the greenness of an analytical procedure is an arduous task since a great variety of different parameters must be taken into consideration.

Several different approaches to GAC metrics have been developed so far, such as National Environmental Index (NEMI) [4], Eco-Scale [5], Analytical GREEnness Metric Approach and software [6], Green Analytical Procedure Index [7] and so on. Diversity of methods leads to the issue of choosing an appropriate metric to assess greenness of analytical procedure. Hence, the main objective of the study - to examine different approaches to assess the greenness of an analytical procedure. To accomplish this objective several tasks were set:

1. Consider different methods that can be applied in GAS

2. Highlight pros and cons of each method

3. Explore possibilities of using approaches to analytical procedures



1. Principles of Green Analytical Metrics

1.1 National Environment Method Index

One of the earliest tools for the assessment of the greenness of analytical methods is the National Environmental Method Index (NEMI) [4]. According to NEMI a method is “less green” if

1. PBT - a chemical used in the method is listed as a PBT, as defined by the EPA's TRI [8].

2. Hazardous - a chemical used in the method is listed on the TRI or on one of the RCRA's D, F, P or U hazardous waste lists [8]

3. Corrosive - the pH during the analysis is <2 or >12

4. Waste - amount of waste generated is >50 g

A greenness profile symbol was introduced to provide an easily recognized summary of greenness profile of the method. The NEMI profile symbol (Figure 1) is a circle that is divided into four fields and this fields are labeled as PBT, Hazardous, Corrosive and Waste. Each field reflects a different criterion and these criteria are considered in a binary way: if a value of a criterion is met, the respective part of the pictogram is filled in with green color; otherwise, it remains uncolored.

Figure 1 The example of NEMI pictogram. The field is green if the requirements of criterion are fulfilled

Even though NEMI as a greenness assessment tool has its advantages (e.g., it is easy to read by potential users), it also has some drawbacks. The NEMI symbol presents each threat as being below or above a certain value, and therefore it cannot be considered quantitative. Furthermore, this tool does not take into consideration such issues as energy, chemical and reagent consumption, and the amount of waste generated. In addition, searching for each chemical used in the procedure in official lists (EPA TRI list, Resource Conservation and Recovery Act list, etc.) is time-consuming.

1.2 Analytical GREEnness Metric Approach and Software

An interesting green metric tool, entitled AGREE (analytical greenness) software appeared in recent research [6]. It focuses on the 12 principles of green analytical chemistry GAC, shown in Table 1. In the AGREE metric, a scale of 0-1 employed the result is offered by a pictogram, where the scale values are designated by the user. It is important to note that all 12 principles of GAC have been assigned a scale, from sample treatment (direct input is preferred), the size of the sample, the use of energy(minimized), to the safety of the operator. To assess the greenness of the procedure all 12 principles should be converted scores. A summary of transformations applied to every principle is presented in graphical form in Figure 2.

Table 1

The twelve green analytical principles [9]

Principle	Meaning
1	Direct analytical techniques should be applied to avoid sample treatment
2	Minimal sample size and minimal number of samples are goals
3	In situ measurements should be performed
4	Integration of analytical processes and operations saves energy and reduces the use of reagents
5	Automated and miniaturized methods should be selected
6	Derivatization should be avoided
7	Generation of a large volume of analytical waste should be avoided and proper management of analytical waste should be provided
8	Multianalyte or multiparameter methods are preferred versus methods using one analyte at a time
9	The use of energy should be minimized
10	Reagents obtained from renewable sources are preferred
11	Toxic reagents should be eliminated or replaced
12	The safety of the operator should be increased

Figure 2 Graphical representation of the functions applied to convert the variables to scores in the 0?1 scale [6]

The first principle of GAC states that direct analytical techniques should be applied to avoid sample treatment. In fact, avoiding sample treatment and sample preparation steps can drastically reduce the environmental, health, and safety issues associated with a given methodology. Direct analysis is, however, not always possible, since the samples should be in an appropriate state of matter and higher sensitivity and/or selectivity may be required. Different greenness levels can be differentiated according to this principle, as shown in Table 2.



Table 2

Sample Pretreatment Activities and Their Respective Scores [6]

Sample pretreatment activities	Score
Remote sensing without sample damage	1.00
Remote sensing with little physical damage	0.95
Nonivasive analysis	0.90
In-field sampling and direct analysis	0.85
In-field sampling and on-line analysis	0.78
on-line analysis	0.70
at-line analysis	0.60
off-line analysis	0.48
external sample pre- and treatment and batch analysis (reduced number of steps)	0.30
external sample pre- and treatment and batch analysis (large number of steps)	0.00

In order to convert the second principle into a metric, the above aspects and the classification of (bio)chemical analyses according to initial sample size are considered [10]. The equation to transform the mass (in grams) or volume (in milliliters) of sample to score is as follows:

Score = - 0.142 Ч ln (amount of sample in g or mL) + 0.65 (1)

As a result, as is shown in Table 3, ultramicroanalysis, microanalysis, and semimicroanalysis are scored as ideal analyses, while macroanalysis is assessed according to eq 1. A sample amount of 100 mg (or мL) is, in the authors' opinion, small enough to be assessed as green.

The third principle of GAC aims at the determination of target analytes as direct as possible. From the GAC point of view, it is important to locate the device close to the measurement location, since in such a case the time between two analyses is short and the time delay between sample collection and obtaining relevant analytical information is also short. In this sense, field-portable instruments and miniaturized analytical systems show high promise for greening chemical analyses [9, 10]. Therefore, the location of the analytical device with respect to the object of investigation is considered within this principle, as shown in Table 3. Concretely, four possibilities, namely, off-line, at-line, on-line, and in-line, have been considered as input data to assess the third principle of GAC

Table 3

Transformation of the Location of the Analytical Device toward the Investigated Object to Numerical Scores [6]

Input data	Score
In-line	1.00
On-line	0.66
At-line	0.33
Off-line	0.00

In order to assess the greenness of an analytical method according to the fourth principle of GAC, a score of 1.0 was set for procedures involving three or fewer steps, while, for four, five, six, seven, and eight or more steps, the scores were set at 0.8, 0.6, 0.4, 0.2, and 0, respectively.

According to the fifth principle of GAC both automation and miniaturization of analytical methods bring beneficial consequences for GAC, as miniaturized methods require less reagents, solvents, and energy. Automation of analytical procedures results in lower occupational exposure, especially toward vapors of solvents, and the risk of accidents is also reduced. The transformation of miniaturization and automation levels into scores is shown in Table 4.

Table 4

Transformation of the Level of Automation and Miniaturization of the Sample Preparation Step into Numerical Values [6]

Level of automation and miniaturization	Score
automatic, miniaturized	1.00
semi-automatic, miniaturized	0.75
manual, miniaturized	0.5
automatic, not miniaturized	0.5
semi-automatic, not miniaturized	0.25
manual, not miniaturized	0.00

The application of derivatization agents is problematic from the GAC point of view, since it implies additional steps and further use of chemicals with subsequent waste generation and it usually negatively affects the sample throughput. Depending on the derivatization agent's nature, the level of hazard can be highly variable. Each derivatization agent has a score between 0 to 1. The assessment criteria refer to the safety of application, environmental fate, environmental persistence, and biological effects. If no derivatization is applied, the score equal to 1 is given; otherwise, it is calculated according to the formula, where DA_i is the score corresponding to the particular derivatization agent.

Score = DA₁ Ч DA₂ Ч... Ч DA_n - 0.2 (2)

According to the seventh principal prevention of analytical waste generation would be ideal from an environmental and economic point of view. Unfortunately, analytical waste is produced in the vast majority of cases. To convert 7^th principle into score the equation was proposed:

Score = - 0.134 Ч ln (amount of waste in g or ml) + 0.6946 (3)

In this approach, it is suggested to include the mass or volume of

· liquid or solid reagents added to the sample

· solvents, acids, or bases applied

· all consumables and single-use devices, such as sorbents, cartridges, Pasteur pipettes, filters, etc.

· the mass or volume of the sample itself, if it is considered to be problematic - in contact with toxic, corrosive substances or the sample itself is of such nature

· When on-line decontamination, reuse, or recycling of wastes is performed, the amount of waste generated per sample is corrected accordingly.

In the eighth principle, the number of analytes that are determined in 1 h is considered. This is the result of multiplying the number of analytes determined in a single run by the analytical throughput, i.e., the number of consecutive samples that can be analyzed in 1 h. In order to recalculate this principle into score the following equation is used:

Score = 0.2429 Ч ln (number of analytes determined in 1 h) - 0.0517 (4)

The transformation results in scores equal to 0.0, 0.5, 0.9, and 1.0 for 1, 10, 50, and 70 analytes determined during 1 h, respectively.

Principle 9 claims that the use of energy should be minimized but the evaluation of the energy consumed in sample preparation, analytical separation, and detection steps can be challenging and demanding. In this approach, a traffic light energy score calculation dependent on the total kWh per sample was proposed [6]:

· Score of 1.0 is given to analytical systems that consume <0.1 kWh per sample: Hot plate solvent evaporation (<10 min), rotary evaporation, needle evaporation, ultrasound-assisted extraction, solid-phase extraction, and microextraction techniques; ultraperformance liquid chromatography; titrations, immunoassays, microbiological assays, UV?vis spectrophotometry, Fourier transform infrared spectroscopy, energy dispersive X-ray fluorescence, potentiometry, and non-instrumental detection (e.g., smartphone-based analysis).

· Score of 0.5 is given to analytical systems that consume 0.1?1.5 kWh per sample: Hot plate solvent evaporation (10?150 min), accelerated solvent extraction, supercritical fluid extraction, microwave-assisted extraction, gas chromatography and liquid chromatography (with detectors different than mass spectrometry), flame atomic absorption spectrometry, electrothermal atomic absorption spectrometry, inductively coupled plasmaoptical emission spectrometry, and mass spectrometry.

· Score of 0.0 is given to analytical systems that consume >1.5 kWh per sample: Hot plate solvent evaporation (>150 min), Soxhlet extraction, gas chromatography?mass spectrometry, liquid chromatography?mass spectrometry; X-ray diffraction, and nuclear magnetic resonance.

The 10th GAC principle is treated in a straightforward way. If no reagents are applied or all are from bio-based sources, the score is 1. If some of them are derived from bio-based sources, while others are not, the score is 0.5. In case none of the reagents originates from bio-based sources, the score equals 0 [6].

The 11th GAC principle aims at the removal or replacement of toxic reagents by greener alternatives whenever possible. Apart from the type of chemicals used, the number of toxic reagents or solvents used is also a critical issue. The first step to assess a given analytical methodology according to the 11th GAC principle is to indicate whether the assessed analytical procedure involves the application of any toxic reagents. If no toxic reagents are used, the score is equal to 1. Otherwise, the mass or volume of the reagent is transformed into the score according to eq 5.

Score = - 0.156 Ч ln (amount of reagent or solvent in g or mL) + 0.5898 (5)

To include the safety of the operator and environmental hazards, the number of threats that are not avoided is considered and they should be selected from the following list:

· Toxic to aquatic life

· Bioacummulative

· Persistent

· Highly flammable

· Highly oxidized

· Explosive

· Corrosive

If no threats are selected, the score equals 1. If one, two, three, or four threats are present, the score is 0.8, 0.6, 0.4, and 0.2, respectively. If five or more threats are identified, then the score is equal to zero.

The result of the assessment is a clock-like graph, with the overall score and color representation in the middle (Figure 3).

Figure 3 Generic result of assessment (left) and the corresponding color scale for reference (right)

The assessment can be easily performed using user-friendly software, with an automatically generated graph and an assessment report.

As a result, AGREE is a comprehensive, flexible, and straightforward evaluation approach that produces an easily interpretable and informative result. One of the advantages of this metric is the availability of freeware software which makes its applications more straightforward.

1.3 Green Analytical Procedure Index

In 2018, a paper was published in the analytical area that used the green analytical procedure index (GAPI) to evaluate the green character of an entire analytical methodology, from sample collection to final determination, focusing on the 12 green analytical principles [7]. In this methodology, five pentagrams were proposed to evaluate and quantify the environmental impact for each step of any analytical methodology, shown in Figure 4.

Figure 4 Green Analytical Procedure Index pictogram with description

The GAPI tool is a pictogram determining the greenness of each stage in the analytical procedure, employing both a color scale and three levels of evaluation for each stage. The color scale is from green through yellow to red to quantify low, medium, and high environmental impact, respectively, for each step, remarking that this tool is more efficient comparing different procedures. Additionally, the circle in middle GAPI is related to a procedure for qualification and quantification; thus, the GAPI does not show the circle where a procedure is only for qualification. The visual presentation of the assessment tool allows individual researchers to make their own value judgments about conflicting green criteria. Hence, this assessment tool is most valuable in comparing procedures. Green Analytical Procedure Index parameters description is presented in Table 5.



Table 5

Green Analytical Procedure Index parameters description [7]

Category	Green	Yellow	Red
Sample preparation
Collection (1)	In-line	On-line or At-line	Off-line
Preservation (2)	None	Chemical or Physical	Physico-chemical
Transport (3)	None	Required	-
Storage (4)	None	Under normal conditions	Under special conditions
Type of method: Direct or indirect (5)	No sample preparation	Simple procedures, e.g., filtration, decantation	Extraction required
Scale of extraction (6)	Nano-extraction	Micro-extraction	Macro-extraction
Solvents/reagents used (7)	Solvent-free methods	Green solvents/reagents used	Non-green solvents/reagents used
Additional treatments (8)	None	Simple treatments (clean up, solvent removal, etc.)	Advanced treatments (derivatization, mineralization, etc.)
Reagents and solvents
Amount (9)	<10 mL (<10 g)	10-100 mL (10-100 g)	>100 mL (>100 g)
Health Hazard (10)	Slightly toxic, slight irritant; NFPA health hazard score = 0 or 1	Moderately toxic; could cause temporary incapacitation; NFPA = 2 or 3	Serious injury on short-term exposure; known or suspected small animal carcinogen; NFPA = 4.
Safety hazard (11)	Highest NFPA flammability or instability score of 0 or 1. No special hazards.	Highest NFPA flammability or instability score of 2 or 3, or a special hazard is used.	Highest NFPA flammability or instability score of 4.
Instrumentation
Energy (12)	?0.1 kWh per sample	?1.5 kWh per sample	>1.5 kWh per sample
Occupational hazard (13)	Hermetic sealing of analytical process	-	Emission of vapours to the atmosphere
Waste (14)	<1 mL (<1 g)	1-10 mL (1-10 g)	>10 mL (<10 g)
Waste treatment (15)	Recycling	Degradation, passivation	No treatment
Additional mark: Quantification
Circle in the middle of GAPI: Procedure for qualification and quantification	No circle in the middle of GAPI: Procedure only for qualification
NFPA: National Fire Protection Association

The visual presentation of GAPI allows for an at-a-glance comparison of several methods and easy selection of the greenest method for a particular study. The proposed GAPI assessment can be a good semiquantitative tool for laboratory practice and educational purposes. The GAPI tool not only provides an immediately perceptible perspective to the user/reader, but also gives exhaustive information on evaluated procedures.

1.4 Complementary green analytical procedure index (ComplexGAPI)

In 2021 was proposed a new metric for the evaluation of analytical procedures based on the GAC attributes. The proposed solution expands on the well-known green analytical procedure index (GAPI) by adding extra fields pertaining to the processes performed prior to the analytical procedure itself. The new metric was called complementary green analytical procedure index (ComplexGAPI).

Here, the developed tools for assessing the greenness of the given analytical procedures come to the rescue (Figure 5) [11].



Figure 5 Life cycle assessment (LCA) of an analytical methodology

The LCA of an analytical protocol includes quality-by-design (QbD) approaches in every step of the development of a new procedure, its validation and operational applications [12]. Moreover, LCA includes additional elements, such as the identification of an analytical target profile (ATP) - a set of criteria that define what will be measured (e.g., analyte content and impurity content) and the performance criteria to be achieved by the measurement (e.g., validation parameters), but without specifying the method [13]. With these features in mind, the LCA of an analytical procedure can be broken down into three stages: method design, method qualification, and continued method verification (Figure 5).

In 2018, the green analytical procedure index (GAPI) tool was reported and has since been used by many scientists to evaluate the green nature of the developed procedures, making it relatively successful and already established at the time of writing. The GAPI metric is discussed in section 1.3.

ComplexGAPI was created based on the same principles which guided the development of GAPI: the analytical eco-scale [7] and the eco-scale [14]. In addition, some requirements taken from the CHEM21 [15] tool were also taken into consideration in ComplexGAPI development. This makes the new metric easy to use for those who are already familiar with these tools and have used them to assess the green nature of the analytical procedures. They will in fact find the assessment process much more straightforward and less time-consuming thanks to the availability of the software for ComplexGAPI. The ComplexGAPI metric expands the pictogram created for GAPI by adding an additional hexagonal field at its bottom. This field corresponds to the `green' character of pre-analysis processes. It covers such aspects as yield and conditions, reagents and solvents, instrumentation, work up and purification of the end products (Figure 6).

Figure 6 The ComplexGAPI pictogram, with the original GAPI pictogram greyed out in the background, and particular fields of the added hexagonal glyph grouped and colour-coded for clarity

As in GAPI, the modified tool utilizes a colour scale, with two or three levels of evaluation for each stage. The created pictogram can be used to evaluate and quantify - from green to yellow to red - the low, medium and high environmental impacts associated with each stage of the pre-analysis process and the analytical methodology. Each field reflects a different feature of the described processes and analytical protocol and is filled green if certain requirements are met. The complex green analytical procedure index parameters are described in Table 6.



Table 6

Comprehensive green analytical procedure index parameter description

Category	Green	Yellow	Red
Pre-analysis processes
Yield/selectivity and conditions
Yield (I)	>89%	70-89%	<70%
Temperature/time (II)	Room temperature, <1h	Room temperature, >1h Heating, <1h Cooling to 0 _C	Heating, >1 h Cooling <0 _C
Relation to the green economy
Number of rules met	5-6	3-4	1-2
Reagents and solvents
Health hazard (IVa)	Slightly toxic, slightly irritant; NFPA health hazard score is 0 or 1	Moderately toxic; could cause temporary incapacitation; NFPA = 2 or 3	Serious injury on short-term exposure; known or suspected small animal carcinogen; NFPA = 4
Safety hazard (IVb)	Highest NFPA flammability, instability score of 0 or 1. No special hazards	Highest NFPA flammability or instability score is 2 or 3, or a special hazard is involved	Highest NFPA flammability or instability score is 4
Instrumentation
Technical setup (Va)	Common setup	Additional setups/semi-advanced instruments used	Pressure equipment >1 atm; glove box
Energy (Vb)	?0.1 kW h per sample	?1.5 kW h per sample	>1.5 kW h per sample
Occupational hazard (Vc)	Hermetization of the analytical process	--	Emission of vapours to the atmosphere
Workup and purification
Workup and purification of the end product (VI a)	None or simple processes	Application of standard purification techniques	Application of advanced purification techniques
Purity (VIb)	>98%	97-98%	<97%
ADDITIONAL FIELD:
E-factor
E-factor =
Sample preparation and analysis
Sample preparation
Collection (1)	In-line	On-line or at-line	Off-line
Preservation (2)	None	Chemical or physical	Physicochemical
Transport (3)	None	Required	--
Storage (4)	None	Under normal conditions	Under special conditions
Type of method: direct or indirect (5)	None sample preparation	Simple procedures, e.g., filtration and decantation	Extraction required
Scale of extraction (6)	Nanoextraction	Microextraction	Macroextraction
Solvents/reagents used (7)	Solvent-free methods	Green solvents/reagents used	Non-green solvents/reagents used
Additional treatments (8)	None	Simple treatments (extract clean up, solvent removal, etc.)	Advanced treatments (derivatization, mineralization, etc.)
Reagents and solvents
Amount (9)	<10 mL (<10 g)	10-100 mL (10-100 g)	>100 mL (>100 g)
Health hazard (10)	Slightly toxic, slightly irritant; NFPA health hazard score is 0 or 1	Moderately toxic; could cause temporary incapacitation; NFPA = 2 or 3	Serious injury on short-term exposure; known or suspected small animal carcinogen; NFPA = 4
Safety hazard (11)	Highest NFPA flammability, instability score of 0 or 1. No special hazards.	Highest NFPA flammability or instability score is 2 or 3, or a special hazard is used.	Highest NFPA flammability or instability score is 4
Instrumentation
Energy (12)	?0.1 kW h per sample	?1.5 kW h per sample	>1.5 kW h per sample
Occupational hazard (13)	Hermetization of the analytical process	--	Emission of vapours to the atmosphere
Waste (14)	<1 mL (<1 g)	1-10 mL (1-10 g)	>10 mL (10 g)
Waste treatment (15)	Recycling	Degradation, passivation	No treatment
ADDITIONAL MARK: QUANTIFICATION
Oval in the middle of GAPI: Procedure for qualification and quantification	No oval in the middle of GAPI: Procedure only for qualification
NFPA, National Fire Protection Association

The proposed tool is accompanied by a simple piece of software that facilitates the use of ComplexGAPI for assessing the greenness of analytical procedures. It was developed in Python using the default Tkinter library. The user chooses parameters corresponding to both the pre-analysis processes and the sample preparation and analysis stages from drop-down menus, and the corresponding ComplexGAPI pictogram is generated live for immediate reference. When ready, the pictogram can be saved either as a raster image (.png) or vector graphic (.svg). The software is available under the open-source MIT license and can be downloaded from mostwiedzy.pl/complexgapi. The code is made available in an open repository.

1.5 RGB Additive Color Model to Analytical Method Evaluation

Analogously, the name of a tool comes from the initials of the three primary colors (Red, Green, Blue) which in the model, correspond to the three primary attributes of any analytical method: analytical performance assessed typically by a classical validation process ? R; safety/ecofriendliness which includes the widely discussed aspects of GAC, e.g., hazards related to reagents and waste, occupational risks or energy consumption ? G; and productivity/practical effectiveness which includes such criteria like cost- and timeeffectiveness, the extent of sample destruction, methodological complexity, time and cost related to appropriate staff training, and some ordinary instrument operation-related aspects like service frequency or risk of random malfunction - B [16].

Like in electronic devices, mixing these three primary colors of light produces an impression of whiteness, so an analytical method becomes white if it has all the primary attributes to a satisfactory degree. Such a white method is thus complete and coherent. According to another analogy, mixing only two primary components gives one of the secondary colors. A yellow, magenta or cyan method is satisfactory in terms of two attributes but lacks the remaining primary color, thus being neither complete nor coherent. Logically, a method is red, green, or blue if it has only one attribute and lacks the other two.

Figure 7 Final colors of a method, required criteria expressed by the individual CS values, and general implications

Whether a method conforms with the idea of redness, greenness and blueness is quantitatively measured by a Colour Score (CS) ranging from 0% to 100%. It is assumed that the method gains one of these elementary colours if the corresponding CS is ?66.6%, a boundary value which is named the “satisfaction range”. Otherwise, the method loses this primary colour. If its particular CS is ?33.3%, named the “tolerance range”, the method is colourless with regard to this primary attribute and transparent/neutral for two other attributes. Hence, if one CS is tolerable and two other CS values are satisfactory, the method is magenta, yellow, or cyan. If two CS values are in the tolerance range and one in the satisfaction range, the method is red, green, or blue. If all three CS values are tolerable but not satisfactory, the method is colourless (this is represented by the gray colour). However, if at least one CS is <33.3%, the method becomes black and not transparent for other attributes. In other words, it is always finally black because any other primary colors are blocked. This approach is justified by the logical reasoning that if at least one primary attribute is unacceptable, any other positive features of the method are overshadowed in the final rating (Figure 7).

1.6 Eco-scale

The basis for the concept of an analytical Eco-Scale is that the ideal green analysis has a value of 100. This approach is analogous to the Eco-Scale proposed by Van Aken et al. for evaluating the greenness of organic synthesis [14]. For each of analytical procedure parameters (amount of reagents, hazards, energy and waste), penalty points are assigned if it departs from ideal green analysis (Table 7). Because the influence of hazardous substances depends on their amount, it is proposed that the total penalty points should be calculated by multiplying the sub-total penalty points for a given amount and hazard.



Table 7

The penalty points (PPs) to calculate analytical Eco-Scale

Reagents
		Sub-total PP	Total PP
Amount	<10 mL (g)	1	Amount PP Ч Hazard PP
	10-100 mL (g)	2
	>100 mL (g)	3
Hazard (physical, environmental, health)	None	0
	Less severe hazard	1
	More severe hazard	2
Instruments
Energy	?60.1 kWh per sample		0
	?61.5 kWh per sample		1
	>1.5 kWh per sample		2
Occupational hazard	Analytical process hermetization	0
	Emission of vapors and gases to the air	3
Waste	None		0
	<1 mL (g)		1
	1-10 mL (g)		3
	>10 mL (g)		5
	Recycling		0
	Degradation		1
	Passivation		2
	No treatment		3
* PPs are assigned to each of hazard category posed by a reagent. Each reagent can have more than one hazard category, thus the sub-total PP value for a single reagent may be greater than 2.

The sum of penalty points for the whole procedure should be included in the Eco-Scale calculation, according to the following formula:

Analytical Eco-Scale = 100 - total penalty points

The result of calculation is ranked on a scale, where the score:

>75 represents excellent green analysis,

>50 represents acceptable green analysis,

<50 represents inadequate green analysis.

Assignment of penalty points to categories of hazard and energy needs a detailed explanation. For assessing the hazard of reagents used in analytical procedures, different classifications of hazardous substances can be applied. For example, the NEMI database uses EPA (Environmental Protection Agency) Toxic Release Inventory, Clean Water Act and Clean Air Act for environmental hazard assessment, and NFPA (National Fire Protection Association) classification for health and safety hazard assessment, respectively [17]. We propose to evaluate physical, environmental and health hazards on the basis of the Globally Harmonized System of Classification and Labeling of Chemicals (GHS), which is the most comprehensive, up-to-date classification of chemicals [18]. For convenience and simplicity, we propose that pictograms and signal words should be included in evaluation of the hazards posed by reagents used in an analytical procedure. Each reagent can be characterized by one or more of the nine pictograms (flame, flame over circle, corrosion, gas cylinder, skull and crossbones, exclamation mark, environment and health hazard). For each pictogram, penalty points are assigned. Two signal words are used in GHS: ``danger'' (more severe hazard, category 1 and/or 2) and ``warning'' (less hazard, other categories). It is proposed the following system of penalty point assignment to hazards: none (no pictogram) = 0 penalty points less severe hazard = 1 penalty points more severe hazard = 2 penalty points.

Penalty points for energy use will be assigned according to the values proposed by Raynie and Driver [19]. The least energy-consuming laboratory practices and instruments (2.5 h). Examples of penalty points assigned to reagents for hazards and to analytical techniques for energy use are given in Table 8.

Table 8

The examples of penalty points (PPs) for hazards

Reagent	Number of pictograms	Signal word	Penalty points
Acetic acid (glacial)	2	Danger	4
Acetic acid (30%)	1	Danger	2
Acetylene	2	Danger, Warning	3
Ammonia solution (25%)	3	Danger	6
Benzoic acid	1	Danger	1
Dichloromethane	1	Warning	1
Hydrochloric acid (30%)	2	Warning	4
Hydrogen peroxide (30%)	2	Danger	4
n-Hexane	4	Danger	8
Nitric acid (65%)	2	Danger	4
Potassium dichromate	5	Danger	10
Sodium hydroxide (30%)	1	Danger	2
Sulfuric acid (25%)	1	Danger	2



2. Application of GAC metrics

2.1 AGREE

AGREE metric was applied to the described procedure [20] based on stir-bar sorptive extraction followed by ultrasound-assisted extraction and high-performance liquid chromatographic separation of analytes with UV detection. The procedure involves external sample treatment with reduced number of steps (principle 1), and 0.3 g of soil sample is needed (p 2). The measurement is off-line (p 3), and the procedure involves seven distinct steps (p 4). The procedure is neither automated nor miniaturized (p 5). No derivatization agents are involved in the analysis (p 6). Analytical wastes include the sample itself (0.3 g), 2 mL of acetone and 2 mL of NaCl solution, 0.5 g of NaCl added during the SBSE stage, and 2.05 mL of EtOH as well as 18 mL of the LC mobile phase (p 7). Eight analytes are determined in a single run and the sample throughput is ?2.5 samples h?1, based on the SBSE desorption time of 20 min (p 8). LC is the most energy demanding analytical technique (p 9), and some of the reagents (alcohols) can be from bio-based sources (p 10). The procedure requires 21.55 mL of toxic solvents (p 11), and MeOH is considered highly flammable (p 12). The result of AGREE analysis is shown in Figure 8.

Figure 8 The Result of AGREE analysis for the described procedure

The second procedure is based on solvent extraction (SE) followed by headspace solid-phase microextraction (HS-SPME) with GC-MS/MS determination [20]. The procedure involves sample preparation with a reduced number of steps (p 1), the mass of the soil sample is 2 g (p 2), and the analytical device is positioned in off-line mode (p 3). The number of distinctive analytical steps is six (p 4). The procedure is not automated but involves a miniaturized sample preparation technique (p 5). No derivatization agents are applied (p 6), the total amount of waste is 10.5 (g and mL combined), consisting of the sample itself, mixture of solvents used during solvent extraction step, syringe filter, and drying agent (p 7). The number of analytes determined is eight, and the analytical throughput is single sample h?1 as SPME extraction takes 60 min (p 8). The most energy demanding technique is GC-MS (p 9). None of the reagents is from bio-based sources (p 10), the volume of toxic reagents is 8 mL (p 11), and hexane is highly flammable and toxic to aquatic life (p 12). The result of AGREE assessment is shown in Figure 9.

Figure 9 The result of AGREE assessment for the described procedure

The third procedure is based on Soxhlet extraction and gas chromatography coupled with high resolution mass spectrometry [21]. The sample pretreatment is external with reduced number of steps (p 1). The mass of soil sample required for analysis is 3 g (p 2), and the measurement is performed in offline mode (p 3). The procedure consists of six steps (p 4), and it is neither automated nor miniaturized (p 5). Again, no derivatization agents are applied (p 6), the amount of waste generated is 219 mL or g of solvents, salts, and sorbents (p 7). The number of analytes determined is 13, and the analytical throughput is 0.042 samples h?1, as Soxhlet extraction takes 24 h (p 8), which is also the most energy demanding device (p 9). No reagents are from bio-based sources (p 10), while 200 mL of toxic solvents is needed (p 11). High flammability is not avoided (p 12). The result of assessment is presented in Figure 10.

Figure 10 The result of AGREE assessment for the described procedure

2.2 GAPI

In order to show how to conduct assessment by means of GAPI tool the procedure for determination clonazepam is considered [22]. Detailed step-by-step description is depicted in Table 9.



Table 9

Assessment of GAPI with Ab Eldin et al [22]

Category	Ab Eldin et al.	Value
Collection (1)	At-line	Yellow
Preservation (2)	None	Green
Transport (3)	None	Green
Storage (4)	Under normal conditions	Yellow
Type of method: Direct or indirect (5)	Simple procedures	Yellow
Scale of extraction (6)	Nano extraction	Green
Solvents/reagents used (7)	Green solvents	Yellow
Additional treatments (8)	Clean up is needed	Yellow
Amount (9)	25-30 mL	Yellow
Health Hazard (10)	1) sodium dodecyl sulfate- NA in NFPA list 2) sodium acetate 3) Isopropyl Alcohol-1	Green
Safety hazard (11)	1) sodium dodecyl sulfate- NA in NFPA list 2) sodium acetate-1 3) Isopropyl Alcohol-3	Yellow
Energy (12)	HPLC consumes ? 1.5 kWh per sample	Yellow
Occupational hazard (13)	HPLC analysis will be done in a closed environment, so the chance of occupational hazards is less	Green
Waste (14)	Waste generated by HPLC methods will be 1-10 mL	Yellow
Waste treatment (15)	No recycling treatment in the reported method	Red

2.3 NEMI

N. Haq et al. developed a method for estimating rosuvastatin using the RP-HPLC method, which entitles a green method, but it was not evaluated using any available green metric tools [23]. We took this literature as an example to assess the greenness of the method by applying NEMI with a step-by-step process; we got the pictogram for the proposed method as follows:

The chemicals used for the analytical method are MeOH and ethyl acetate as a mobile phase which has not been listed in the TRI list - so the pictogram is marked as green.

As per the hazardous waste list, the solvent used in the method is MeOH (U154), Ethyl Acetate (U112). Hence the pictogram portion -left blank.

The pH of solutions used in the method range from 2 to 12, so the pictogram is marked as green.

Analytical waste obtained by the method was less than 50 mL (based on the run time) - so the pictogram portion has been marked as green. Overall NEMI pictogram is presented in the Figure 11.

Figure 11 NEMI pictogram for estimating rosuvastatin using RP-HPLC method

2.4 Complementary green analytical procedure index (ComplexGAPI)

To showcase the utility and convenience of ComplexGAPI, the greenness of three reported analytical methodologies for the determination of pesticides in urine samples was assessed and juxtaposed and evaluated using the developed tool. The procedures are as follows: Procedure 1 (in situ IL-DLLME-HPLC): magnetic nanoparticle-assisted in situ ionic liquid dispersive liquid-liquid microextraction (in situIL-DLLME) coupled to high performance liquid chromatography (HPLC)[24]; Procedure 2 (SFO-DLLME-GC-MS): dispersive liquid-liquid microextraction (DLLME) based on solidification (SFO) of deep eutectic solvent (DES) droplets combined with gas chromatography-mass spectrometry (GC-MS)[25]; and Procedure 3 (SB-м-SPE-GC-MS): membrane-protected stir-bar supported micro-solid-phase extraction (SB-м-SPE) coupled to GC-MS[26].

These procedures differ in many aspects, starting from the processes performed prior to the analysis, through the sample preparation step, ending at the final determination. In the first procedure, Fe₃O₄ magnetic nanoparticles and the ionic liquid ([N_4,4,4,4][N(CN)₂]) were synthesized and characterized before the analytical procedure. The DLLME extraction technique was used to isolate the analytes, while HPLC was applied for the final determination. In the second procedure, DES (menthol: phenylacetic acid) was synthesized and applied as an extractant. The extraction solvent was forced to pass through a glass filter under an N₂ stream and it was dispersed as fine droplets in the sample solution. Due to the low density of the synthesized extractant, it was collected on top of the sample solution without centrifugation. In the third procedure, the layered double hydroxide/graphene (LDH-G) hybrid was synthesized by co-precipitation and used as a sorbent in SB-м-SPE extraction. Furthermore, GC-MS was applied for the final determination of the analytes in urine samples. The result of the evaluation of these procedures for pesticide determination in urine ComplexGAPI is shown in Figure 12. By juxtaposing the results of the assessment of the selected procedures for the pesticide determination in urine samples, it is evident where these procedures differ and which aspects should be focused on to avoid certain issues. It should be noted that all methods require the transport of samples and their storage. The procedure based on DLLME, which in turn is based on the solidification of DES droplets and GC-MS (Procedure 2) seems to be greener than the other two methodologies. This is mainly because the processes related to the synthesis of DES as well as the micro-extraction procedure are based on nonhazardous reagents. In fact, DES synthesis is a very simple process. In this case, 4.68 g of menthol was mixed with 1.36 g of phenylacetic acid in a glass tube and the mixture was heated for 1 h at 60°C in a water bath. The synthesis occurs in 100% yield and no wastes are generated during this part (E-factor = 0). No further steps are required requires small amounts of reagents for the analytical separation, and thus, a few milliliters of wastes are generated. The critical point of Procedure I is the amount of waste generated that is not recycled. In fact, the synthesis of nanoparticles consists of several steps and requires a large aliquot of reagents. The resulting solution requires heating at 180°C for 20 h. The black magnetite microspheres were thoroughly washed with ethanol and deionized water several times and then dried under vacuum at 50°C for 24 h. Considering the analytical procedure, the protocol should be refined with respect to waste production and its regeneration. Procedure III fails in many aspects, including reagent consumption, waste generation, and conditions used in the synthesis processes. The synthesis part involves numerous steps, a large volume of reagents as well as their aliquots, and application of high temperature for long periods of time. The procedure does not support green economy and it is characterized by a higher E-factor. This is why, in comparison to all the evaluated procedures in terms of the green character, the last one is the lowest-scoring and future modifications are recommended.

Figure 12 Evaluation of three selected protocols using the ComplexGAPI tool



2.5 RGB Additive Color Model to Analytical Method Evaluation

To show the utility of the RGB model, we selected exemplary method devoted to the analytical problem - the determination of acetic acid in vinegar [16].

Overall, the table is divided into four horizontal parts, three being related to the evaluation of R, G, and B attributes, and the one, on the bottom, for presentation of the results obtained. The colored rectangles (consisting of merged cells) represent the criteria chosen for the three primary attributes. A rectangle's size in both directions (i.e., number of cells that were merged to form them) corresponds to the weights assigned to them: the vertical dimension represents W, reflecting the importance of a given primary attribute, and the horizontal dimension represents w, reflecting the importance of a particular criterion within the given attribute. A rectangle's color, in turn, indicates whether the corresponding aspect of the method may be deemed as satisfactory (red, green, and blue colors) if the corresponding score reached 66.6; tolerable (gray) ? if the score reached 33.3 but was below 66.6; or unacceptable (black) ? if the score was below 33.3. Below the colored cells presented are the crucial parameters used for evaluation: LAV and LSV for particular criteria (defined by user), the method's results subjected to the evaluation (e.g., RSD values representing precision), and the corresponding scores (appearing in all the columns referring to a given criterion).

Step 1. Rank the three primary attributes, i.e., R ? analytical performance, G ? safety/eco-friendliness, and B ? productivity/practical effectiveness, according to their subjective importance, by assigning individual W values.

Step 2. Select the criteria according to which the method will be evaluated for the three primary attributes. The choice of at least three key criteria is advised to keep the format simple and to include various method aspects.

Step 3. Rank the importance of the selected criteria by assigning them individual w values within each attribute. Their sum should be 10 (according to the format proposed in the template worksheet). Merge the appropriate rows and columns to represent every criterion by one cell. The size of the merged cells results from their W values (vertical dimension) and w values (horizontal dimension).

Step 4. Define the “lowest acceptable value ? LAV” and “lowest satisfactory value ? LSV” for each criterion, the stipulated thresholds helpful in a critical evaluation of your method.

Step 5. Write down the values reached by the method evaluated in each criterion in the cells denoted as “Result”. Preferably, all values should be determined experimentally or directly calculated with high accuracy; nevertheless, it is also acceptable to perform some approximations or predictions if accurate data are lacking. Such eventuality should be clearly indicated in a evaluation's description.

Step 6. Critically evaluate your method by assigning the value from the range 0?100 to each criterion. Use previously selected LAV and LSV as reference points. Write down the values in the cells denoted as “Score” in each column. For instance, if w for a given criterion is 3, write down the same score three times.

Step 7. Use the appropriate coloring of the individual rectangles: black for score <33.3; gray for score < 66.6 but ?33.3; and red, green, or blue for score ?66.6 (in the template worksheet published in the SI, the corresponding cells are conditionally formatted, so this step should not require any input from the user).