Greenness evaluation metric for analytical methods and software

Abstract

The focus of green analytical chemistry (GAC) is to minimize the negative impacts of analytical procedures on human safety, human health, and the environment. Several factors, such as the reagents used, sample collection, sample processing, instruments, energy consumed, and the quantities of hazardous materials and waste generated during analytical procedures, need to be considered in the evaluation of the greenness of analytical assays. In this study, we propose a greenness evaluation metric for analytical methods (GEMAM). The new greenness metric is simple, flexible, and comprehensive. The evaluation criteria are based on both the 12 principles of GAC (SIGNIFICANCE) and the 10 factors of sample preparation, and the results are presented on a 0–10 scale. The GEMAM calculation process is easy to perform, and its results are easy to interpret. The output of GEMAM is a pictogram that can provide both qualitative and quantitative information based on color and number.

Graphical abstract

Highlights

• •A comprehensive GAC metric was proposed.
• •GEMAM is based on 12 principles of GAC and 10 factors of GSP.
• •GEMAM could provide qualitative and quantitative information.

1. Introduction

Green analytical chemistry (GAC), which originated from green chemistry, is a relatively new concept [1]. The concept of GAC was introduced in 2000, and its purpose was to reduce or eliminate the negative impacts of analytical procedures on human safety, human health, and the environment [[2], [3], [4]]. To achieve this, some measures, such as the use of solventless extraction techniques, the employment of less toxic solvents, and the miniaturization of devices for sample preparation and detection, need to be implemented [5]. Furthermore, proper guidelines and GAC metrics need to be established to assess the greenness of analytical methods.

Jacek Namieśnik proposed the 12 principles of GAC, which provide a road map and guidance for analysts to implement GAC [6]. However, owing to the various characteristics and requirements of different analytical assays, the 12 GAC principles are only applicable to some analytical procedures [7] (Fig. S1). López-Lorente et al. [8] proposed 10 principles of green sample preparation (GSP), which expand the scope of GAC in assessing the greenness of sample preparation (Fig. S1). Furthermore, numerous GAC metrics such as national environmental methods index (NEMI) [9], high performance liquid chromatography environmental assessment tools (HPLC-EAT) [10], analytical method volume intensity (AMVI) [11], Analytical Eco-scale [12], Spider diagram [13], green analytical procedure index (GAPI) [14], red-green-blue (RGB) additive color model [15], HEXAGON [16], analytical method greenness score (AMGS) [17], analytical greenness calculator (AGREE) [18], Complex GAPI [19], ComplexMoGAPI [20], AGREEprep [21], and blue applicability grade index (BAGI) [22] have been developed to assess the greenness of analytical assays.

These metrics are valuable for evaluating the greenness of analytical methods [23]. However, some of these GAC metrics are proposed for particular analytical assays. For instance, HPLC-EAT can only be used to assess the greenness of analytical methods based on HPLC-related techniques. Some of these GAC metrics are universal and applicable to most analytical methods, but they still have some limitations [18]. For instance, NEMI, GAPI, and Complex GAPI can only be used for qualitative analysis. Others such as Analytical Eco-scale, AMGS, and AMVI do not have pictograms to display the greenness of analytical methods. Moreover, the calculation process for metrics such as Analytical Eco-scale, AMGS, AMVI, HEXAGON, and ComplexMoGAPI is complex. In addition, the comprehensiveness of AGREE, AGREEprep and BAGI needs further improvement. Therefore, the aim of this study is to develop a novel simple, flexible, practical, and comprehensive GAC metric for evaluating the greenness of analytical assays. The new metric is an additional GAC metric to the currently existing tools for green assessment. This tool can provide a more detailed and thorough assessment, offering both qualitative and quantitative insights into the greenness of analytical assays. The GEMAM software used for greenness assessing is freely available at https://gitee.com/xtDLUT/Gemam/releases/tag/Gemam-v1.

2. Material and methods

Quantifying the greenness of an analytical assay is challenging owing to the various procedures involved, including sample collection, sample preparation, chromatographic separation, and instrument detection [6] (Fig. 1). According to the principles of GAC and GSP, six aspects, namely the sample, reagent, instrumentation, method, waste generated, and the operator, are considered in the greenness evaluation metric for analytical methods (GEMAM) [6].

Fig. 1.

The procedures included in an analytical method.

GEMAM can be used to assess the greenness of the entire analytical assay, covering aspects such as sample collection site, sample storage, sample preparation, reagents, method type, method performance, instrumentation, waste generation, and the impacts of the analytical assay on operators. A pictogram consisting of seven hexagons is used to classify the greenness at different stages of the entire analytical assay (Fig. 2). The central hexagon represents the overall greenness score, while the six surrounding hexagons indicate the six key dimensions of GAC. These dimensions are assessed using 21 criteria, which were developed by summarizing, supplementing, and refining the 12 principles of GAC (SIGNIFICANCE) [6] and the 10 factors of GSP [8]. The specific relationship between the GEMAM principles and the 12 principles of green analytical chemistry, as well as the 10 factors of sample preparation, is shown in Table S1. The criteria of GEMAM are based on the 12 principles of GAC and the 10 factors of GSP, which are scored on a scale of 0–10. The GEMAM pictogram uses a color scale with different levels ranging from green to red color to indicate the greenness of different procedures of the analytical method (Table S2). Different weights (W) can be assigned to both the six sections and 21 criteria of GEMAM, depending on their relative impact on the overall greenness of the analytical method (Table 1). By default, the weights for the six sections, i.e., sample, reagent, instrument, method, waste, and operator, are assigned as 10 %, 25 %, 15 %, 15 %, 25 %, and 10 %, respectively. In addition, users can adjust the weights for the different sections and criteria based on the environmental and health impacts of different analytical procedures. The differences between the weights assigned to the six sections and 21 criteria of GEMAM are visually represented by the thickness of the hexagonal boundaries and the area of the corresponding graph (Fig. 2), respectively. Detailed greenness evaluation results of an analytical assay can be exported in PDF format.

Fig. 2.

The general result of the greenness evaluation metric of analytical methods (GEMAM) assessment (left) and the corresponding color scale for reference (right).

Table 1.

Weights for different sections and different criteria of greenness evaluation metric for analytical methods (GEMAM).

Weight (mSection) (%)	Sections	Criterion	Weight (mCriterion) (%)
10	Sample	1. Sample preparation site	20
		2. Whether the sample is damaged during sample preparation	20
		3. Range of extraction when sample preparation	20
		4. The size of sample	20
		5. Storage of sample	20
25	Reagent	6.Description of the ideal green derivatization	10
		7.The amounts of reagents	10
		8.The score of reagents	80
15	Method	9. Number of analytes determined in a single run (or analysis parameters)	20
		10. Sample throughput (per h)	30
		11. Number of main steps in the analysis process	20
		12. Ratio of the mass of sustainable and renewable materials to the total mass of materials used	20
		13. Economic benefits of the method	10
15	Instrument	14. The energy consumption per analysis should be minimized	40
		15. Automation of instruments	30
		16. Miniaturization of instruments	30
25	Waste	17. Waste treatment	10
		18. The amounts of wastes	10
		19. The score of wastes	80
10	Operator	20. Hermetic sealing of analytical process	50
		21. Noise generating of analytical process	50

Each section of GEMAM has multiple evaluation criteria. The score for each section is calculated by summing the individual scores assigned to each of the evaluation criteria. The overall GEMAM score is then calculated by summing the individual scores assigned to all of the six sections. Finally, the color and the numerical score of the GEMAM output result for evaluating the greenness of analytical procedures are displayed in the middle of the pictogram. The GEMAM score can be calculated using Eqs. Eq. 1, Eq. 2), as shown below:

$$\text{Score}\text{of}\text{each}\text{section}=\sum _{\mathrm{i}=1}^{\begin{array}{c}\mathrm{n}=\text{Number}\text{of}\text{criteria}\\ \text{in}\text{each}\text{section}\end{array}}10\times \text{weight}\text{of}\text{criterion}\mathrm{i}\times \text{the}\text{score}\text{of}\text{criterion}\mathrm{i}$$ Eq. 1

$$\text{Total}\text{score}=\sum _{\mathrm{i}=1}^{\mathrm{n}=6}\sum \text{Score}\text{of}\text{section}\mathrm{i}\times \text{Weight}\text{of}\text{Section}\mathrm{i}$$ Eq. 2

Each of the 21 criteria of GEMAM is converted into scores. Fig. 3 shows the summary of transformations applied to the 21 criteria of GEMAM.

Fig. 3.

Graphical representation of 21 criteria of greenness evaluation metric of analytical methods (GEMAM) applied to transform the greenness evaluation parameters into scores in the 0−1 scale. USD: United States dollar; SHED: safety, health, environment, and disposal.

2.1. The criteria about sample preparation considered in greenness evaluation by GEMAM

The first hexagon of the GEMAM pictogram is divided into five parts, and it is associated with sample preparation. The greenness score for this first hexagon is based on the first, second, and third principles of GAC and the first principle of GSP (Table S3). Specifically, the first part, marked with number 1, is associated with the sample preparation site. In-line sample preparation is recommended as the preferred choice because it could minimize the consumption of reagents and energy during the sample preparation process [24]. Furthermore, it also mitigates sample degradation owing to inadequate storage conditions during transport. This part is assigned scores of 1, 0.75, 0.5, and 0.25, corresponding with the sample preparation site at in-line, on-line, on site, and ex situ, respectively. The second part, marked with number 2, is associated with the integrity of the sample during sample preparation. This part is assigned a score of 1 if there is no sample destruction during sample preparation. Otherwise, this part is assigned a score of 0.5. The third part, marked with number 3, is associated with the range of the extraction during sample preparation. According to GSP principles, a significant shift toward miniaturization exists during the sample preparation process [25]. This transition includes adopting microextraction techniques such as solid-phase microextraction, micro-electro-membrane extraction, and liquid-phase microextraction [26]. This trend aims to reduce the size of the samples while minimizing the generation of waste, lowering time costs, increasing the portability of the analytical system, and reducing energy consumption and environmental pollution. This part is assigned scores of 1, 0.75, 0.5, and 0.25 based on the extraction mode used: ultra-microextraction, microextraction, semi-microextraction, and macroextraction, respectively. Ultra-microextraction techniques employ sample volumes below 100 μL and acceptor phases below 10 μL or 1 mg as a tentative threshold. Microextraction techniques are defined according to International Union of Pure and Applied Chemistry (IUPAC) standards [27]. Compared with traditional sample extraction assays, microextraction procedures, such as liquid-phase microextraction and solid-phase microextraction, typically require only 1–10 mL of sample. Liquid-phase microextraction typically consumes only 0.5–400 μL of extraction solvent, while solid-phase microextraction commonly requires a small quantity of solid adsorbent at milligram level [28]; Semi-microextraction technology is a scaled-down version of traditional liquid-liquid extraction (LLE) or solid-phase extraction (SPE) methods, typically based on smaller sample volumes and reduced amounts of extraction reagents. For a 10 mL sample, the typical organic solvent dosage ranges from 0.5 to 1.0 mL, or 10–100 mg of the sorbent for semi-microextraction [26]. In contrast, macroextraction techniques involve the use of relatively larger volumes of solvents or sorbents to extract and concentrate analytes. SPE and LLE are the known conventional macroextraction techniques.

The goal of GAC is to reduce the amounts of samples used [29]. The fourth part, marked with number 4, is associated with the sample size. A score of 1 is assigned if the sample size is less than 10 g (mL); a score of 0 is assigned if the sample size exceeds 100 g (mL). For sample sizes between 10 and 100 g (mL), the score can be calculated using Eq. (3):

$$\{\begin{array}{l}1\\ {\text{Score}}_{4\text{th}}=\left(-1.068\right)\times {\mathrm{e}}^{-0.9}\times \ln \left(\begin{array}{c}\text{sample}\text{mass}\text{or}\\ \text{volume}\text{in}\mathrm{g}\text{or}\text{mL}\end{array}\right)+2\\ 0\end{array}\begin{array}{l}\le 10\mathrm{g}\left(\text{mL}\right)\\ 10-100\mathrm{g}\left(\text{mL}\right)\\ \ge 100\mathrm{g}\left(\text{mL}\right)\end{array}$$ Eq. 3

The fifth part, marked with number 5, is associated with the storage conditions of the tested samples. Scores are assigned based on the storage conditions as follows: 1 for room temperature storage, 0.85 for protection from light, 0.7 for dry conditions, 0.55 for refrigeration (2−8 °C), 0.4 for freezer storage (−80 to −20 °C), 0.25 for cryogenic storage (<−150 °C), and 0 for storage with special additives. The detailed calculation rules for the sample section are summarized and shown in Table S3. The principles of GEMAM for assessing the greenness of analytical assays based on dried blood spots (DBS) and biofluid sampler (BFC) (Table S4).

2.2. The criteria about reagents considered in greenness evaluation by GEMAM

The key objective of GAC is to reduce the use of reagents during analytical procedures, especially solvents that pose significant occupational and environmental hazards, and replace highly toxic reagents with more innocuous solvents [30]. The second hexagon of the GEMAM pictogram is divided into three parts and is associated with the reagents used during the analytical procedures. The greenness score calculation for this hexagon is based on the 6th, 10th, and 11th principles of GAC, as well as the second principle of GSP (Table S5). The first part, marked with number 6, addresses whether derivatization is used during sample preparation. In some cases, derivatization is necessary to modify the chemical structure of the analyte and consequently improve the sensitivity, selectivity, or adaptability of the analytical method [31,32]. The use of derivative reagents adds extra steps to the analytical process and increases the consumption of chemicals and corresponding waste production. However, with the rapid development of GAC in sample preparation, several green derivatization approaches have been developed [32,33]. Reddy Mudiam et al. [34] developed a method combining ultrasound-assisted dispersive liquid-liquid microextraction (UA-DLLME) with automated in-port sialylation (auto-IPS) for simultaneous determination of 10 phenolic endocrine disruptor chemicals (PEDCs). Through the incorporation of liquid-liquid microextraction, the sialylation reaction occurred rapidly at the gas chromatography-mass spectrometry (GC-MS) port, reducing the reaction time and minimizing the consumption of derivatization reagents. Jain et al. [35] employed alkyl chloroformate as a greener alternative to conventional salivating agents for non-steroidal anti-inflammatory drugs (NSAIDs) detection in urine samples. This derivatization was performed at room temperature in a short time (30 s), significantly lowering both reaction time and energy consumption. Wang et al. [36] used subcritical water extraction combined with DLLME and derivatization to determine hydroxylated polycyclic aromatic hydrocarbons (OH-PAHs) in sediment samples. This method was more sensitive and stable than conventional SPE. In the development of green derivatization, the scoring for the sixth criterion is as follows: if no derivatization is required, the method receives a score of 1; if derivatization is needed, the method is compared with an ideal green derivatization process [37]. The greenness of the derivatization step can be evaluated as follows:

• 1)Satisfaction level ≥5: the method receives a score of 0.8, indicating that it is close to the ideal green derivatization process.
• 2)Satisfaction level ≥3: the method receives a score of 0.5, indicating a reasonably green derivatization process that demonstrates progress toward greener practices but still has room for improvement.
• 3)Satisfaction level <3: the method receives a score of 0, indicating an insufficiently green derivatization process.

The description of ideal green derivatization is shown in Table S6.

The second part, marked with number 7, addresses the impacts of reagents on safety, health, and the environment, and their recyclability. The safety-health-environment-recyclability (SHER) framework is used in this part for score calculation. The safety of reagents (S) is assessed through the evaluation of reagent flammability/explosivity, corrosiveness, and instability, as explained in the relevant safety data sheets (Table S7). For health (H), assessment is based on two critical factors, also described in Table S7. Acute toxicity of reagents is the first factor of H, which includes immediate effects such as irritation and corrosiveness to the eyes, skin, and respiratory tract. The chronic toxicity of reagents is the second factor of H, which covers the long-term effects of reagents on human health, such as carcinogenicity, neurotoxicity, teratogenicity, and reproductive toxicity. The impact of reagents on the environment (E) refers to the persistence, bioconcentration, and mobility of the corresponding reagents in soil. Furthermore, R refers to the recyclability of the reagents used during analytical procedures. The scoring system for this part, based on the “SHER” framework, differs from the previous standards. In earlier standards, scores were assigned based on specific criteria or were calculated using specific formulas. In the “SHER” framework, the final score is determined through the subtraction of the reagent’s score from the total score for the seventh criterion. The calculation is performed using Eqs. Eq. 4, Eq. 5), as shown below:

$${\text{Score}}_{\text{SHER}}=10\times \text{Weight}\text{of}7\text{th}\text{criterion}-\left({\mathrm{S}}_{\text{safety}}+{\mathrm{S}}_{\text{health}}+{\mathrm{S}}_{\text{environment}}+{\mathrm{S}}_{\text{recyclability}}\right)$$ Eq. 4

$${\text{Score}}_{7\text{th}}={\text{Score}}_{\text{SHER}}\times {\text{Score}}_{8\text{th}}\times {\text{RFactor}}_{\text{num}}\times {\text{RFactor}}_{\text{type}}$$ Eq. 5

The third part, marked with number 8, is related to the amounts of reagents used during analytical procedures. The score of this part can be calculated using Eq. (6), as shown below:

$${\text{Score}}_{8\text{th}}=1-\text{normalize}\left({\text{amounts}\text{of}\text{reagents}}^2\right)$$ Eq. 6

2.3. The criteria about method considered in greenness evaluation by GEMAM

The third hexagon of the GEMAM pictogram consists of five parts and is associated with the method performance. The greenness score calculation for this third hexagon is based on the 4th and 8th principles of GAC, as well as the 3rd, 6th, 7th, and 10th principles of GSP (Table S8). The first part, marked with number 9, pertains to the number of analytes detected in a single run. A multi-analyte or multi-parameter assay is the preferred option. Scores are assigned as follows: a score of 1 is given if the number of analytes is greater than 10; a score of 0.8 is given if the number of analytes is greater than 5 and less than or equal to 10; a score of 0.6 is given if the number of analytes is greater than 3 and less than or equal to 5; a score of 0.4 is given if the number of analytes is greater than 1 and less than or equal to 3; and a score of 0.2 is given if only one analyte is detected. The second part, marked with number 10, is related to the assay’s throughput (the number of samples analyzed per h). The score for this part can be calculated using Eq. (7), as shown below:

$${\text{Score}}_{10\text{th}}=1.575\times {\mathrm{e}}^{-2}\times \ln \left(\text{number}\text{of}\text{prepared}\text{samples}\text{per}\mathrm{h}\right)+0.0333$$ Eq. 7

The third part, marked with number 11, is related to the number of steps in the analytical method. Scores are assigned as follows: a score of 1 is given if the method has three or fewer steps; 0.8 for four steps; 0.6 for five steps; 0.4 for six steps; 0.2 for seven steps; and 0 for eight or more steps. The fourth part, marked with number 12, is related to the ratio of the mass of sustainable and renewable materials to the total mass of materials used [38]. In alignment with the third principle of GSP, this part is assigned scores as follows:

• 1)Score 1: only sustainable and renewable materials are used several times.
• 2)Score 0.75: 75 % or more of the materials are sustainable or renewable.
• 3)Score 0.5: 45 %–75 % of materials are sustainable or renewable.
• 4)Score 0.25: 15 %–45 % of materials are sustainable or renewable, or materials are not sustainable or renewable and are used several times.
• 5)Score 0: 15 % or less of the materials are sustainable or renewable and can only be used once.

The fifth part, marked with number 13, is related to the economic consumption of the analytical method. A score of 1 is assigned if the average cost of analyzing a single sample is less than 1 (United States dollar (USD)), and a score of 0 is assigned if the average cost of analyzing a single sample exceeds 100 (USD). Moreover, if the average cost of analyzing a single sample fall between 1 and 100 (USD), the score can be calculated using Eq. (8), as shown below:

$${\text{Score}}_{13\text{th}}=\{-\begin{array}{l}1\\ {\left(\mathrm{e}-0.4215\right)}^{-1}\times \ln \left(\begin{array}{c}\text{average}\text{cost}\text{to}\text{analysis}\\ \mathrm{a}\text{single}\text{sample}\end{array}\right)+2.006\\ 0\end{array}\begin{array}{l}\le 10\text{USD}\\ 10-100\text{USD}\\ \ge 100\text{USD}\end{array}$$ Eq. 8

2.4. The criteria about instrument considered in greenness evaluation by GEMAM

The choice of instrument is highly dependent on the specific application of the analytical method. Optimal instrument selection can streamline the analytical procedure, expedite the process, increase the sensitivity and accuracy of the assay, and minimize both the required sample size and reagent volume [39]. The fourth hexagon of the GEMAM pictogram has three parts, and it is associated with the instrument used during analytical procedures. The greenness score calculation for this fourth hexagon is based on the fifth, and ninth principles of GAC, as well as the eighth principle of GSP (Table S9). Minimizing the energy consumption of instruments is a key factor in assessing the instrument’s life cycle. The first part, marked with number 14, is related to the energy consumption of the instrument. This section is divided into two sub-sections, and the total score of this section is the sum of the scores of the two sub-sections. The detailed calculation rules for the first part are summarized and shown in Table S10. In the first sub-section, the instrument that consumes the most energy during the analytical procedures should be evaluated to assign a score:

• 1)Score 1: simple instruments with minimal energy requirements, such as flasks, reflux condensers, and stirrers.
• 2)Score 0.75: instruments that use lower amounts of energy, such as spectrophotometry, surface analytical techniques, voltammetry, and potentiometric methods.
• 3)Score 0.5: instruments such as gas chromatographs with non-mass spectrometric detection, atomic absorption spectroscopes, and instruments used for capillary electrophoresis.
• 4)Score 0.25: LC, GC-quadrupole detection, etc.
• 5)Score 0: Advanced MS instruments with high energy and/or inert gas consumption, such as inductively coupled plasma-optical emission spectrometer (ICP-OES), ICP-MS, etc.

In the second sub-section, the energy required per sample should be evaluated to assign a score:

• 1)Score 1: assigned when the energy consumption for analyzing a single sample is less than 0.1 kWh.
• 2)Score 0: assigned when the energy consumption for analyzing a single sample exceeds 1.5 kWh.

For energy consumption between 0.1 and 1.5 kWh, the score is calculated using Eq. (9), as shown below:

$${\text{Score}}_{14\text{th}-2}=\{\begin{array}{l}1\\ -0.7142\times \text{kWh}/\text{sample}+1.0714\\ 0\end{array}\begin{array}{l}\le 0.1\text{kWh}\\ 0.1-1.5\text{kWh}\\ \ge 1.5\text{kWh}\end{array}$$ Eq. 9

According to the fifth principle of GAC, the use of automated and miniaturized instruments can help reduce reagent consumption and waste generation [40,41]. The second part, marked with number 15, is related to the automation of the instrument. Scores are assigned as follows: a score of 1 is given for fully automatic instruments, 0.66 for semi-automatic instruments, and 0.33 for manual instruments. The third part, marked with number 16, is related to the miniaturization of the instrument. A score of 1 is given for miniaturized instruments and 0.5 for non-miniaturized instruments.

2.5. The criteria about waste considered in greenness evaluation by GEMAM

Hazardous waste generated during analytical procedures can significantly pollute the environment. Preventing the production of waste is an ideal goal, but in practice, waste is inevitably generated during the analytical process [42]. The fifth hexagon of the GEMAM pictogram consists of three parts, and it is associated with the waste generated during analytical procedures. The greenness score calculation for this hexagon is based on the seventh principle of GAC and the fourth principle of GSP (Table S11). The waste generated during analytical procedures should be minimized and appropriate waste treatment measures should be implemented [43]. The first part, marked with number 17, is related to waste treatment. If the waste is recycled, this part is assigned a score of 1. If the waste is degraded/passivated, the score is 0.5. If the waste is not treated at all, the score of this part is 0.

The second part, marked with number 18, addresses the impacts of waste on safety, health, the environment, and disposal considerations. The safety, health, environment, and disposal (SHED) framework is also applied to assess waste in this section, similar to its application in the reagent module. The scores for SHED and the corresponding assessment for the part marked with number 18 are calculated using Eqs. Eq. 10, Eq. 11), as shown below:

$${\text{Score}}_{\text{SHED}}=10\times \text{weight}\text{of}18\mathrm{t}\mathrm{h}\text{criterion}-\left({\mathrm{S}}_{\text{safety}}+{\mathrm{S}}_{\text{health}}+{\mathrm{S}}_{\text{environment}}+{\mathrm{S}}_{\text{disposal}}\right)$$ Eq. 10

$${\text{Score}}_{18\text{th}}={\text{Score}}_{\text{SHED}}\times {\text{Score}}_{19\text{th}}\times {\text{WFactor}}_{\text{num}}\times {\text{WFactor}}_{\text{type}}$$ Eq. 11

Two penalty factors are used in the calculation of Score_18th. WFactor_num serves as a penalty factor for the amounts of waste generated. WFactortype acts as a penalty factor based on the type of waste. Details regarding the determination of WFactor_num and WFactor_type are summarized and presented in the supplementary materials.

The third part, marked with number 19, is related to the amount of waste generated. The score for this part can be calculated using the following formula:

$${\text{Score}}_{19\text{th}}=1-\text{normalize}\left({\text{amount}\text{of}\text{waste}}^2\right)$$ Eq. 12

The amount of waste generated during analytical procedures is closely linked to its impact on human safety, human health, and the environment. In GEMAM, both the “SHED” factor and the amount of waste generated are considered in the assessment of the greenness of analytical assays.

2.6. The criteria about the impacts of analytical assay on operators considered in greenness evaluation by GEMAM

Operator safety should be considered during analytical procedures. The greenness score calculation in the sixth hexagon is based on the 12th principle of GAC and the 10th principle of GSP (Table S12). The sixth hexagon of the GEMAM pictogram consists of two parts that assess the impacts of analytical assays on operators. The first part, marked with number 20, is related to the hermetic sealing conditions of the analytical procedures. If no harmful gas emissions occur during the analytical procedures, this part is assigned a score of 1; otherwise, it receives a score of 0. The second part, marked with number 21, is related to the noise generated during analytical procedures. The score for this part can be calculated using the following formula:

$${\text{Score}}_{21\text{th}}={\mathrm{e}}^{0.68}\times \ln \begin{array}{c}(\text{The}\text{decibels}\left(\text{dB}\right)\text{of}\text{the}\\ \text{noise}\text{generated}\text{during}\\ \text{analytical}\text{procedure}\end{array}/100)+0.0083$$ Eq. 13

3. Results

GEMAM was used to evaluate the greenness of three analytical methods in this study, highlighting the applicability and convenience of this new GAC metric. Default weights have been set for all criteria within the GEMAM framework. The greenness evaluation results of the three analytical assays are shown in Fig. 4.

Fig. 4.

The greenness results of three different analytical assays evaluated by greenness evaluation metric of analytical methods (GEMAM) and other nine green analytical chemistry (GAC) metrics. Method 1: a high-performance liquid chromatography photo-diode array (HPLC-PDA) assay coupled with liquid–liquid extraction (LLE) as sample processing procedure for detection of sotolon; Method 2: an ultra-high performance liquid chromatography photo-diode array (UHPLC-PDA) assay coupled with micro-extraction with packed sorbent (MEPS) as sample processing procedure for detection of sotolon; Method 3: a gas chromatography-mass spectrometry (GC-MS) assay coupled with liquid–liquid extraction (LLE) as sample processing procedure for detection of sotolon. NEMI: national environmental methods index; Eco-Scale: Analytical Eco-Scale; GAPI: green analytical procedure index; ComplexGAPI: complex green analytical procedure index; AGREE: analytical greenness calculator; AGREEpre: analytical greenness calculator preparation; RGB: red-green-blue; BAGI: blue applicability grade index; ComplexMoGAPI: complex modified green analytical procedure index.

The first evaluated analytical assay is based on liquid–liquid extraction (LLE) using glycerol as a keeper solvent and high-performance liquid chromatographic (HPLC) for the separation of sotolon via diode array detection (DAD) [44]. The detailed information for the greenness evaluation of this assay using GEMAM is presented as follows: for the first section (sample module), the sample preparation site is categorized as ex situ (criterion 1), and the samples are damaged during sample processing (criterion 2). The LLE employed in this study is classified as a microextraction assay (criterion 3). The sample size is 10 mL (criterion 4). The storage condition is refrigeration at 2−8 °C (criterion 5). The calculated score for the sample module is 5.1. For the second section (reagent module), no derivatization reagent is used during the analytical procedures (criterion 6). Five kinds of reagents are used: glycerol, dichloromethane, veratrin acid, formic acid, and acetonitrile (criterion 7), with consumptions of 10 μL, 6 mL, 300 μL, 23.58 μL, and 5.4 mL per sample (criterion 8), respectively. The “SHER” scores for these reagents are assigned according to Table S7. The final score for the reagent module is 5.24. For the third section (method module), only one analyte is quantified in a single run (criterion 9), and only one sample is analyzed per h (criterion 10). The analytical method involves nine steps (criterion 11). Furthermore, 15 %–45 % of the materials used in the analytical method are sustainable or reusable (criterion 12). The cost of analyzing a single sample is less than 10 USD (criterion 13). The final score for the method module is 1.9. For the fourth section (instrument module), the instrument that consumes the most energy during the analytical process is high-performance liquid chromatography - ultraviolet detector (HPLC-UV) (criterion 14−1), and its energy consumption for analyzing a sample is 126 Wh (criterion 14−2). The instrument used in this study is semi-automated and not miniaturized (criteria 15, 16). The final score for the instrument module is 5.96. For the fifth section (waste module), no treatment is conducted on the waste generated during analytical procedures (criterion 17). The waste mainly consists of five reagents: glycerol, methylene chloride, veratrin acid, formic acid, and acetonitrile (criteria 18, 19). The score for the waste module is 5.39. For the sixth section (operator module), the analytical procedure is hermetic (criterion 20), and the noise generated during the analytical procedure is less than 60 dB (criterion 21). The score for the operator module is 10. The final evaluation score calculated by GEMAM for this analytical assay is 5.347.

The second evaluated analytical assay is based on microextraction with packed sorbent (MEPS) and ultra-high-performance liquid chromatography (UHPLC) for the separation of sotolon in fortified wines, using photo-diode array (PDA) detection [45]. For the first section (sample module), the sample preparation site is ex situ (criterion 1), and the samples are damaged during sample processing (criterion 2). MEPS qualifies as a microextraction assay (criterion 3). The sample size is 1.75 mL (criterion 4), and the storage condition is refrigeration at 2 °C−8 °C (criterion 5). The score for the sample module is 6.1. For the second section (reagent module), no derivatization reagents are used during analytical procedures (criterion 6). Two kinds of reagents, formic acid and methanol, are used (criterion 7), with consumptions of 18 and 550 μL, respectively (criterion 8). The “SHER” scores of these reagents are assigned according to Table S7. The score for the reagent module is 5.46. For the third section (method module), only one analyte is quantified in a single run (criterion 9), and the assay processes 10 samples per h (criterion 10). The analytical assay involves eight steps (criterion 11). In addition, 45 %–75 % of the materials used in the analytical method are sustainable (criterion 12). The cost of analyzing a single sample is less than 10 USD (criterion 13). The final score for the method module is 3.97. For the fourth section (instrument module), the instrument that consumes the most energy is the UPLC-photodiode array detector (PDA) (criterion 14−1), and its energy consumption for analyzing a sample is less than 0.1 kWh (criterion 14−2). The instrument used in this study is semi-automated and not miniaturized (criteria 15 and 16). The final score for the instrument module is 7.5. For the fifth section (waste module), the waste generated during the analytical procedure is not treated (criterion 17). The waste mainly consists of two reagents: formic acid and methanol (criteria 18 and 19). The score for the waste module is 6.25. For the sixth section (operator module), the analytical procedure is hermetic (criterion 20), and the noise generated during the analytical procedure is less than 60 dB (criterion 21). The score for the operator module is 10. The final GEMAM evaluation score for this analytical assay is 6.257.

The third evaluated analytical assay is based on LLE for the quantitative analysis of sotolon in various dry white wines via GC-MS [46]. For the first section (sample module), the sample preparation site is classified an ex situ (criterion 1), and the samples are damaged during sample processing (criterion 2). LLE is classified as a macroextraction assay (criterion 3). The sample size is 100 mL (criterion 4). The storage condition is refrigeration at 2−8 °C (criterion 5). The score for the sample module is 3.1. For the second section (reagent module), no derivatization reagent is used during the analytical procedures (criterion 6). Two kinds of reagents are utilized: 3-octanol and dichloromethane (criterion 7), with consumptions of 100 μL and 20 mL (criterion 8), respectively. The score for the reagent module is 4.08. For the third section (method module), only one analyte is quantified in a single run (criterion 9), and only one sample is analyzed per h (criterion 10). The analytical assay involves 10 steps (criterion 11). Furthermore, 15 %–45 % of the materials used in the analytical method are sustainable (criterion 12). The cost of analyzing a single sample is less than 10 USD (criterion 13). The final score for the method module is 1.9. For the fourth section (instrument module), the instrument that consumes the most energy is GC-MS (criterion 14−1), and its energy consumption for analyzing one sample is more than 1.5 kWh (criterion 14−2). The instrument used in this study is semi-automated and not miniaturized (criteria 15, 16). The final score for the instrument module is 3.5. For the fifth section (waste module), the waste generated during the analytical procedure is not treated (criterion 17). The waste mainly consists of two reagents: 3-octanol and dichloromethane (criteria 18, 19). The score for the waste module is 4.08. For the sixth section (operator module), the analytical procedure is hermetic (criterion 20). The noise generated during the analytical procedure is less than 60 dB (criterion 21). The score for the operator module is 10. The final evaluation score calculated by GEMAM for this analytical assay is 4.163.

4. Discussion

Sotolon, the compound responsible for the “nutty” and “spicy-like” aroma in old Port wines, also serves as a freshness indicator for dry white wines. High levels of sotolon indicate poor freshness in dry white wines. Owing to the different roles and influences of sotolon in different kinds of wines, an analytical assay should be developed to quantify it. However, the determination of sotolon in wines is a huge challenge, as it exists in very low amounts in complex wine matrices with high levels of volatile and non-volatile compounds. Therefore, appropriate sample processing, enrichment, and separation are necessary for the detection of ultra-low concentrations of wines. This is revealed in generally reflected by the low GEMAM score values of calculated for the three analytical assays. However, compared with the other two analytical methods, the second method stands out for using using MEPS, a microextraction technique known for its reusability and minimal sample volume requirements. In addition, the technique requires fewer reagents and demonstrates relative environmental friendliness during the analysis, resulting in reduced waste generation. These characteristics contribute to its superior evaluation across the method in sample, reagent, method, and waste modules, ultimately leading to a more favorable overall greenness assessment compared with the other methods.

For comparison, the greenness of the three analytical methods is also evaluated in terms of NEMI, Eco-scale, GAPI, ComplexGAPI, AGREE, AGREEpre, RGB, BAGI and ComplexMoGAPI. They have the similar results and the results are summarized in Fig. 4. The greenness of MEPS based procedure shows a superior greenness profile owing to several advantages such as a lower sample size requirement and higher sample throughput. The compiled version of the software and the associated codes are available at https://gitee.com/xtDLUT/Gemam/releases/tag/Gemam-v1. The detailed calculation procedures of GEMAM for evaluating the greenness of analytical methods are shown in Fig. S2-S6. The procedures for software installation of GEMAM are shown in Fig. S7A−H. Moreover, a video was recorded to help the analyst to use GEMAM to evaluate the greenness of analytical methods.

Supplementary video related to this article can be found at https://doi.org/10.1016/j.jpha.2025.101202

The following is/are the supplementary data related to this article:

5. Conclusion

GEMAM is a metric designed for evaluating the greenness of analytical methods. It integrates the 12 principles of GAC and the 10 factors of sample preparation. The associated calculation is easy for users to perform. The output results of GEMAM are presented through a pictogram that conveys both qualitative and quantitative information, utilizing color and numerical values that are easy to interpret. Generally, GEMAM is a simple, flexible, practical, and comprehensive GAC metric for evaluating the greenness of analytical assays. The case studies demonstrate the full applicability of GEMAM to different analytical procedures.

CRediT authorship contribution statement

Tong Xin: Writing – review & editing, Writing – original draft, Project administration, Investigation. Luyao Yu: Writing – review & editing, Writing – original draft, Investigation. Wenying Zhang: Investigation. Yingxia Guo: Investigation. Chuya Wang: Investigation. Zhong Li: Investigation. Jiansong You: Investigation. Hongyu Xue: Writing – review & editing, Writing – original draft, Project administration, Investigation. Meiyun Shi: Writing – review & editing, Writing – original draft, Project administration, Investigation. Lei Yin: Writing – review & editing, Writing – original draft, Project administration, Investigation.

Declaration of competing interest

The authors declare that there are no conflicts of interest.

Appendix A. Supplementary data

The following are the Supplementary data to this article: