The GREENPEG Project Toolset to Explore for Buried Pegmatites Hosting Lithium, High-Purity Quartz, and Other Critical Raw Materials

The GREENPEG toolset provided below (steps 1–3; Apps. 1–26) is an integrated, multimethod package tailored to small- and medium-scale companies exploring for pegmatites aiming to maximize the success of subsequent and generally more costly techniques such as drilling. Its importance lies in the urgent need to identify new deposits of green energy transition and high-tech commodities such as Li for electric vehicle batteries and high-purity quartz for the Si metal needed to produce photovoltaics. GREENPEG is a European Commission research and innovation project funded in the context that exploration and production of critical and strategic raw materials in Europe is generally low (e.g., Raw Materials Information System, 2024). This makes Europe heavily reliant on imports from other countries, especially China. The European Union’s dependency on imports has raised concerns about supply disruptions and vulnerabilities in the event of trade disputes, geopolitical tensions, or other events. To mitigate these risks, the European Commission has launched initiatives like the Raw Materials Initiative (2008), the European Battery Alliance (2017), and the Critical Raw Materials Act (2023). It takes part in the Minerals Security Partnership international initiative (U.S. Department of State, 2024) and finances research and innovation programs to promote domestic exploration, mining, and recycling of critical and strategic raw materials. In this context, GREENPEG has established a toolset for exploration of pegmatite-type deposits to stimulate and promote technological innovation and competitiveness of exploration services and mining companies and geological surveys. The project was carried out in Europe, mainly with European partners, but results are applicable worldwide.

The toolset consists of a complementary suite of tailored conventional and newly developed methods, novel data-processing approaches, three new geophysical exploration systems, and two specialist databases designed and optimized from knowledge, experience, and innovations developed during the GREENPEG project (2020–2024). The individual tools are optimized for the relatively small size, varying depths, geologic settings, physicochemical properties, and different European surface environments of pegmatite deposits—from coastal Arctic to temperate forest, alpine, and Mediterranean settings. They are particularly suited to the targeting of Li, high-purity quartz and Ta deposits. The toolset can be tailored to the geologic and broader characteristics and challenges of an exploration area and to specific customer needs in terms of goals, level of experience, and budget.

Individual tools were tested in four active European pegmatite exploration areas (GREENPEG demonstration sites): Wolfsberg in Austria (alpine), Leinster in Ireland (temperate forest), Tysfjord in Norway (coastal Arctic), and the Central Iberian pegmatite province (Fregeneda-Almendra, Gonçalo, Barroso-Alvão) in Portugal and Spain (hot dry-summer Mediterranean). The toolset can be used at province (500–10,000 km²), district (25–500 km²), and/or prospect scale (<25 km²) and is underpinned by a modified genetic model based on appraisal of European pegmatite-type ore deposits (Müller et al., 2022).

When entering the toolset workflow (Table 1; Fig. 1), the users are asked whether they are familiar with the physical and chemical characteristics of pegmatites and best practice in environmental, social, and governance (ESG) factors in pegmatite exploration. If the answer is no, they are directed to step 1, which provides an introduction to both the nature and genesis (processes of formation) of pegmatites and their related ores and relevant ESG considerations and suggested further reading. If the answer is yes, they can proceed to step 2 to perform a target area desk study (Fig. 1).

In step 2, the user can choose which of the four types/genetic classes of pegmatite deposits best fits their exploration scenario. The next step is to decide on the appropriate scale(s) to work at (province, district, and/or prospect), which will depend on their objectives, the types and quality of a priori information available, and the level of site development (exploration brownfield vs. greenfield). At each scale of exploration, the user can work through a GREENPEG flowchart to decide on the most appropriate methodologies to apply and in which order (step 3; Table 2). The Appendix contains detailed explanations of how the methods are applied and gives examples of results obtained by GREENPEG and their interpretation.

This section reviews how to differentiate between various chemical and genetic types of granitic pegmatites and introduces ESG considerations relevant to pegmatite exploration. Exploration for mineralized pegmatites is extremely challenging, as they are found in a large variety of different settings, and because of their small size, lack of petrophysical contrast with most host rocks, and mineralogical variability, they are commonly difficult to detect using standard geochemical and geophysical methods (Trueman and Černý, 1982; Selway et al., 2005; Galeschuk and Vanstone, 2005, 2007; Bradley et al., 2017; Steiner, 2019). Exploration success in a particular area requires a comprehensive understanding of local geology, geochemistry, mineralogy, and petrophysics, as well as ESG factors. It is necessary to understand not only the nature of the pegmatites themselves but also their alteration halos (which can provide a larger target in exploration than the pegmatite itself), and the wall rocks, which may have the same or strongly contrasting physicochemical characteristics as the pegmatites. A detailed understanding of these aspects is provided in the following sections.

Granitic pegmatites, hereafter referred to as “pegmatites” for brevity, are very coarse grained (usually >3 cm) igneous rocks of granitic or near-granitic composition that can be divided into two major chemical groups based on their mineralogy and chemistry, according to the classifications of Černý (1991a) and Wise et al. (2022) (Table 3):

1. LCT pegmatites according to Černý (1991a) or group-1 pegmatites according to Wise et al. (2022): The term LCT comes from the initial letters of the relatively rare elements lithium (Li), cesium (Cs), and tantalum (Ta), which are characteristically abundant this group of pegmatites, sometimes to grades that may be economic to mine. Other elements of potential economic interest include tin (Sn), beryllium (Be), rubidium (Rb), and sometimes phosphorus (P). LCT pegmatites crystallize from melts produced, directly or indirectly, by partial melting of metasediments and are therefore referred to as S-type (see Černý et al., 2012). Host-rock types of LCT pegmatites are commonly greenschist to amphibolite facies metamorphic rocks or S-type granites.

2. NYF pegmatites according to Černý (1991a) or group-2 pegmatites according to Wise et al. (2022): The term NYF comes from the initial letters of the relatively rare elements niobium (Nb), yttrium (Y), and fluorine (F), which are characteristically abundant in these pegmatites, sometimes to grades which may be economic to mine. They may also contain economic concentrations of rare earth elements (REEs), also called lanthanides, which show similar geochemical behavior to yttrium. Thorium (Th) is commonly abundant too, although this may be more of a problem than an opportunity, as it has few uses and rocks containing it may constitute low-level radioactive waste. NYF pegmatites crystallize from melts produced by partial melting of metaigneous rocks either in anorogenic A-type settings (and are generally alkaline) or in I-type settings (see Černý et al., 2012). The melts are commonly emplaced in greenschist to amphibolite facies metamorphic rocks or in A- or I-type granite plutons.

Wise et al. (2022) distinguish an additional, rarer, chemical group of I-type pegmatites, formed by partial melting of metaigneous source rocks, which either have a B-Be-REE-Nb-Ti-Li-Ca (groups 1 and 2) or Al-Be-B (group 3) chemical enrichment signature and occur in granulite to amphibolite facies metamorphic rocks. As these groups are relatively uncommon, and for the sake of brevity, they are not discussed further in this contribution.

Another group of pegmatites, variously called simple, barren, ceramic, or abyssal pegmatites, has been distinguished. Here, it is important to understand that the term “barren” may only apply to a single or group of target commodities. In Li exploration, for example, an LCT/group 1 pegmatite containing no spodumene or petalite may be considered barren of Li but may contain large, sometimes economic, amounts of high-quality feldspar. A second consideration is that, when using the classification of Wise et al. (2022), every pegmatite should be allocated to one of the above-named mineralogical-chemical groups (Table 3), because the mineralogical approach covers every type of pegmatite. This should take into account the geologic setting and occurrence of other types of pegmatites nearby, or in the same belt, since pegmatites commonly occur in clusters sharing similar mineralogical and geochemical features (Černý, 1991b). The term “mixed NYF-LCT” pegmatites should be avoided, as the mineralogy of the wall zone (second outermost zone of the pegmatite, Fig. 2), thought to be at least approximately representative of the primary mineral assemblage and melt signature, always allows NYF/group 2, LCT/group 1, group 1 and 2, and group 3 pegmatites to be distinguished (Wise et al., 2022).

The modern pegmatite classification of Wise et al. (2022) is principally based on the mechanism of melt production (granite-derived versus anatectic) and the type of chemical enrichment (e.g., Müller et al., 2022; Wise et al., 2022). Magmas may be direct products of anatexis (DPA) or residual melts of granitic magmatism (RMG); chemical enrichments may give signatures of either group 1-LCT or group 2-NYF pegmatites. These two factors allow classification into four pegmatite types: DPA group 1-LCT (simplified as DPA-LCT), RMG group 1-LCT (simplified as RMG-LCT), DPA group 2-NYF (simplified as DPA-NYF) and RMG group 2-NYF (simplified as RMG-NYF). RMG pegmatites crystallize from the residual, most fractionated melts released during the final crystallization of large-volume granitic intrusions (Černý, 1991b). DPA pegmatites are derived by partial melting of igneous, metaigneous, or metasedimentary rocks, probably often followed by magma fractionation that increases rare elements.

LCT pegmatites (group 1 pegmatites)—mineralogy: Constituent minerals of LCT (group-1) pegmatites are listed in Table 3. All usually contain quartz, K-feldspar, sodic plagioclase, and muscovite, plus a range of minor minerals that may be of economic interest, including spodumene (Li), tantalite-columbite group minerals (Ta), cassiterite (Sn), beryl (Be), feldspars, and pollucite (Cs). High B may be reflected in an abundance of tourmaline, with potential for economic gemstone tourmaline, and high P in a variety of phosphate minerals. Sulfide minerals are almost always at trace levels. Currently, the major commodity mined from LCT pegmatites is Li. Pegmatites with >1 wt % Li₂O are typically considered economic; economic considerations (size and grade of deposit) for the different target commodities are provided in Table 4. Their Li, however, can be hosted by a variety of minerals, most commonly spodumene (LiAlSi₂O₆ containing stoichiometrically 8.0 wt % Li₂O), which is the principal economic host of Li in pegmatites, and petalite (LiAlSi₄O₁₀ containing stoichiometrically 4.5 wt % Li₂O); spodumene is favored because of its higher Li content. Whether spodumene or petalite occurs depends mainly on the pressure (and to a lesser degree the temperature) of magma emplacement and crystallization (London, 1984). At typical geothermal gradients, spodumene is expected at depths >10 km and petalite at shallower levels. In many LCT pegmatites, both are present, even in the same sample. This is conventionally interpreted as indicating that the pegmatite magma and/or rock crossed the phase boundary between the stability fields of the two minerals (London, 1984), although crystallization of one mineral outside its predicted stability field cannot be ruled out. In addition to these minerals, certain micas also contain appreciable concentrations of Li, most notably lepidolite and zinnwaldite, although they are rarely present in economic concentrations (Dittrich et al., 2023).

LCT pegmatites (group 1 pegmatites)—internal zoning: Some LCT pegmatites have a distinct mineral-chemical zoning (e.g., Jahns, 1955). This is most often characterized by an increase in crystal size toward the center, with varying proportions and types of minerals, which develops as the body undergoes progressive inward crystallization. If well developed, there is usually a medium-grained border zone, granophyric wall zone, megacrystic (blocky) intermediate zone, quartz core, and late-stage replacement zones (Fig. 2A). However, economic albite-spodumene pegmatites, e.g., in Leinster and Wolfsberg, are usually unzoned or poorly zoned mineralogically, for reasons that are not understood (Fig. 2B). Other varieties, e.g., some dike-like pegmatites on the Iberian Peninsula, show layered structures that are attributed to rapid disequilibrium crystallization as a result of injection into open fractures and strong melt undercooling (Garate-Olave et al., 2017; Roda-Robles et al., 2023). Examples of possible pegmatite anatomical types are shown in Figure 3. Shallowly emplaced pegmatites (<2.5 kbar) may also exhibit open miarolitic cavities, which may contain gem-quality spodumene, tourmaline, beryl, and topaz.

The orientation of crystals in pegmatites varies between intrusions. In most, crystals are aligned (semi)-perpendicular to wall rocks as a result of inward crystallization of the melt (Černý and Ercit, 2005). However, many pegmatites, in particular those that are unzoned, have partially or largely random crystal orientations, perhaps resulting from their intrusion syntectonically into deformation zones or relatively low degrees of undercooling (Keyser et al., 2023a).

LCT pegmatites (group 1 pegmatites)—intrinsic magmatic-hydrothermal alteration: Many spodumene pegmatites have a bimodal crystal size distribution. Early formed pegmatitic (>1 cm) crystals of spodumene, quartz, feldspars, and sometimes muscovite may have been partially altered to finer-grained secondary quartz-muscovite and/or albite-rich assemblages. Apart from replacing the early minerals, it is possible that the finer-grained albite (in some cases called cleavelandite where it has a platy crystal habit) crystallizes directly from the melt and grows interstitially between early coarse crystals. The destruction of spodumene during these alteration processes results in a reduction in pegmatite Li potential (Kaeter et al., 2018, 2021). Albitization may, however, increase economic Sn and Ta potential because secondary albitite may contain cassiterite and tantalite-columbite group minerals (Kaeter et al., 2021). Tantalite-columbite group minerals in albite zones have a higher Ta tenor than those that formed in the primary assemblage (Kaeter et al., 2018).

LCT pegmatites (group 1 pegmatites)—halos: Geochemical halos commonly form around LCT pegmatites because of expulsion of fluid during pegmatite melt intrusion and/or crystallization. Halos may show enrichments in B, Li, Rb, Cs, Be, Sn, Ta, and Nb that gradually decline over distances of meters to tens of meters or more away from the pegmatite margin (Barros et al., 2022; Errandonea-Martin et al., 2022) or much more abruptly within centimeters (Geiger et al., 2024). Halos are often visible to the naked eye within ~10 cm of pegmatite contacts, and sometimes in veins, but otherwise are generally invisible. They nevertheless tend to be detectable in small volumes of rock, e.g., in 20-cm-long pieces of drill core, implying that halo signatures are often not restricted to major veins but are present throughout the host rock. The minerals hosting the halo signature can include micas, tourmaline, amphiboles, and oxides such as Nb-Ta–rich rutile, and depend in part on host-rock mineralogy and geochemistry (Barros et al., 2022; Errandonea-Martin et al., 2022).

The mineralogy and physical properties of the host rocks exert major controls on the spatial extent and intensity of halo development. The expulsion of hydrothermal fluids to form the halo is likely to be triggered by the exsolution of hydrothermal fluids from pegmatite melts, probably at the time of emplacement (Errandonea-Martin et al., 2022), and probably triggers pegmatite crystallization. Alternatively, later loss of the fluid during pegmatite crystallization, taking with it substantial Li and most B, may reduce the rate of crystal growth and increase nucleation of new crystals leading to a switch to finer-grained crystallization of quartz-muscovite assemblages and especially albite in the pegmatite intrusion (Barros et al., 2022).

Halos are a useful geochemical exploration feature but also indicate that certain elements have been carried away from the pegmatite melt by magmatic-hydrothermal fluids, often including a large proportion of the original rare element inventory (see App. 20). Factors determining the width of the halo may include the volume of pegmatite melt (and therefore the volume of fluid released), the orientation of intrusions relative to country-rock structures (influencing fluid pathways), pegmatite melt chemistry (especially fluid content and types and concentrations of ligands), depth of emplacement (which exerts an influence on mineralogy, fluid release, and temperature of fluids), and the rheology of the host rock, itself dependent on both rock structures, such as cleavage, and on mineral properties (which affects the nature of deformation and therefore fluid flow). Examples of halo widths in the GREENPEG demonstration sites are 0.1 to 2 times the thickness of the Tysfjord pegmatites in Norway, 0.5 to 1 times the thickness of the Wolfsberg pegmatite dikes in Austria, ≤0.1 times the thickness of the Moylisha pegmatite dikes in Ireland, and 4 to 5 times the thickness of the Fregeneda-Almendra pegmatites in Spain (see App. 20). The width and volume of the halo adds to the exploration footprint (potential anomaly) shown by a pegmatite, and, if detected on surface, could indicate the presence of a pegmatite below (Galeschuk and Vanstone, 2005).

NYF pegmatites (group 2 pegmatites)—mineralogy: The enrichment in Nb, Y, and/or F in NYF (group 2) pegmatites may lead to the crystallization of indicative accessory minerals such as allanite, gadolinite, fluorite, topaz, aeschynite, euxenite, fergusonite, and samarskite (Table 3). Locally, microcline occurs as the green variety amazonite, the most characteristic mineral fingerprint of NYF pegmatites (Martin et al., 2008). NYF pegmatite melts contain higher concentrations of Fe compared with LCT equivalents, which often leads to the crystallization of biotite and other Fe-rich minerals such as magnetite and hornblende. Besides Nb, Y, F, and Fe, these pegmatites may be enriched in REEs, Be, U, and Th to the extent that some people refer to them as REE pegmatites. Elevated U and Th concentrations in addition to high K in the pegmatites may produce relatively high gamma radiation relative to their host rocks (App. 12).

NYF pegmatites (group 2 pegmatites)—internal zoning: In general, NYF pegmatites show less pronounced internal mineral, chemical, and structural zoning than LCT pegmatites. The zoning is characterized by a general increase in crystal size from pegmatite margin to core, an increase of Li, Rb, Ta, and Cs in mica (e.g., Rosing-Schow et al., 2018) and of Rb in feldspar (e.g., Müller et al., 2008), and a change in accessory mineral assemblages—for example, magnetite-euxenite-(Y) in the wall zone, to almandine-allanite-(Ce)-columbite-(Fe) in the intermediate zone, to spessartine-tourmaline-beryltopaz-microlite in the core and albite zones (Solås pegmatite in Iveland, Norway; Müller et al., 2018). Chemically evolved NYF pegmatites, however, can exhibit complex zoning with a granitic-textured border zone, a coarse wall zone with graphic quartz-feldspar intergrowths, a megacrystic intermediate zone, predominantly made up of blocky microcline, and a massive quartz core. Monomineralic quartz cores can reach dimensions of >100,000 m³. Shallowly emplaced NYF pegmatites (<2.5 kbar) may develop open cavities containing gem-quality topaz, beryl, and/or spessartine (Müller et al., 2018).

NYF pegmatites (group 2 pegmatites)—intrinsic magmatic-hydrothermal alteration: Some chemically evolved NYF pegmatites may develop finer-grained albite (cleavelandite) replacement zones. These superimpose and replace preexisting parts of the pegmatite. In some cases, such alteration zones are enriched in Li, Rb, Cs, Ta, and Sn, which has led to certain NYF pegmatites containing them being misinterpreted as mixed NYF-LCT types (Müller et al., 2018).

NYF pegmatites (group 2 pegmatites)—halos: Similar to LCT pegmatites, geochemical halos are common around NYF pegmatites because of expulsion of fluids into the wall rocks during pegmatite melt emplacement and/or crystallization. Halos can show enrichment in Rb, Tl, Li, Cs, Ta, F, Sn, Nb, U, and Th, gradually declining over distances of meters to tens of meters from the pegmatite margin. The widest halos proven so far occur around Proterozoic NYF pegmatites in the Tysfjord area of northern Norway, which have a width of up to 15 m but are highly irregular. Because the halos have elevated U and Th, they emit higher gamma radiation than the wall rocks outside the halo, and so they can be easily detected using a handheld scintillometer or by air- and drone-borne high-resolution radiometry surveys (Apps. 6, 8, 12).

Geophysical exploration for pegmatites is challenging, as they often show very little or no detectable geophysical contrast with their host rocks, being nonmagnetic and nonconductive and having a density similar to that of most common upper crustal rock types (Trueman and Černý, 1982; Galeschuk and Vanstone, 2005, 2007; Selway et al., 2005; Bradley et al., 2017). However, with a profound knowledge of the petrophysical contrasts in the area of interest, recent developments in exploration technologies and an improved understanding of pegmatite properties and genesis, numerous minor geophysical differences between pegmatites and their host rocks have been identified, especially given appropriate pegmatite body thickness/depth/physical properties contrast ratios. GREENPEG project activities have contributed to this knowledge. These mappable criteria are listed in Table 5, along with practicable exploration methods and method combinations, which provide the knowledge required to proceed with step 2 (target area desk study), where these mappable criteria are set into the context of the mineral systems exploration approach, as defined by Fraser et al. (2007).

An ESG assessment is needed at an early stage in any exploration project, ideally before proceeding to an in-depth ESG desk study (step 2.2). This should be repeated and evolved at regular intervals throughout the entire exploration process, particularly if there is a change in strategy or context (social, political, and/or environmental) or if a new exploration technique is added. In terms of social context, it is important to have a clear strategy for community participation, engagement, and communication from the earliest stages of the project, with sufficient resources to ensure strategy performance. Discussion and suggestions for ESG guidance, frameworks, and schemes are given in Appendix 26.

If a new exploration site is in a little-known or unexplored area, continue to step 2.1.1. If the target area occurs near an existing mining operation, with known ore potential, then move to step 2.1.2.

There are a number of criteria that can be used to determine if an exploration area has potential for pegmatite deposits. The best documented is the occurrence of pegmatite deposits in belts, either in magmatic belts or high-grade metamorphic domains. If the exploration area lies on a linear trend of similar age with known pegmatite occurrences, there is a potential of mineralized pegmatites. There is also a common, but by no means essential, association of pegmatite clusters and fields with predominantly late-orogenic and subordinate cases of postorogenic and anorogenic granite plutons (e.g., Černý, 1991b). These features can be assessed by studying maps of known European pegmatite occurrences (Fig. 4) and their age (Table 6). Figure 5 illustrates the age distribution of different pegmatite types worldwide according to McCauley and Bradley (2014). Tkachev (2011) is another suitable reference for worldwide pegmatite occurrences and their association with orogens throughout geologic time. If the exploration area formed outside a prospective province(s) or time period, and there is no reference to pegmatite or characteristic mineral occurrences in the Mindat.org database (www.mindat.org), its prospectivity should be questioned. If the target area lies in a recognized pegmatite province and includes rocks and/or structures of recognized prospective age, and there are suitable mineralogical occurrences (e.g., of Li minerals), it may be worth undertaking a chemical and genetic classification of the pegmatite field, applying criteria in Table 3. With this knowledge, move to step 2.2.

Brownfield exploration is where there is significant known mineralization or there are mined sites close to, or in, the target area. Historical mine sites can become mineable again if there are changes in commodity prices or in the nature and costs of mineral processing and mining technologies. If so, the next step is to evaluate the exploration environment—costs of licenses and surveys, etc.

There are numerous international and national data sets available with physical, ecological, and social data to enable characterization of the exploration environment prior to field visits and selection of exploration tools. The first data to assess are those that could end or pause project progress, such as particularly sensitive community concerns or environmental zones/issues; see Appendix 26. Examples of these desk-study data are given in Table 7.

Many European countries, through geological survey and exploration licensing organizations, provide access to geologic, geophysical, and geochemical databases and maps at a range of scales, including existing drill hole/core data, and even the drill core itself. Airborne geophysical data relevant to district-scale analysis, at line spacing of 200 to 400 m, may be freely accessible through national surveys. This will often include magnetic and radiometric data sets and, in some cases, electromagnetic data. Historinocal prospect-scale ground geophysics data may also be available, as well as province- and district-scale gridded geochemical data for soils and stream sediments. Examples of data providers include the Geological Survey of Norway (2023), Geological Survey of Finland (2023), and Geological Survey Ireland (2023).

Data are commonly offered, with corresponding reports, as raw, gridded, and sometimes even interpreted data. This allows the data to be reprocessed, remodeled, and reinterpreted. National core storage facilities should be contacted and, if possible, visited for on-site sample investigation and, potentially, subsampling. Reports containing geochemical and petrophysical data and relevant hand specimens and drill cores, for both the pegmatite and the country rock, must be sourced and evaluated to provide important background information for forthcoming analytical work and interpretation. Mineralogical information from known pegmatite occurrences in the target area can be extracted from the Mindat.org database (www.mindat.org). A freely accessible petrophysical database (Haase and Pohl, 2022; Haase et al., 2022; App. 25) and a spectral library (Cardoso-Fernandes et al., 2022a; App. 4) of European pegmatite ores and their wall rocks were produced in the GREENPEG project to support exploration methodologies. Remote sensing data, e.g., Landsat or Sentinel, are freely accessible and can be downloaded through the National Aeronautics and Space Administration (NASA, 2023) and European Space Agency (ESA) portals (European Space Agency, 2023). Other products, like WorldView-3 (2023) or the Italian PRISMA data (Italian Space Agency, 2023) can be purchased or requested via their web pages. Finally, there may be relevant data in academic publications, many of which can be found using online search engines. The user should check whether the data from all of these sources are free to use, have to be purchased, and/or are subject to a license agreement or acknowledgement in any publication, presentation, or report.

For the evaluation of the gathered data, a data metafile for the target area should be created. Already at this early stage, successful toolset application for pegmatite exploration can be achieved if the site and target relevant data sets are readily available and combined according to GREENPEG recommendations (see step 3). It should be obvious, at this stage, whether any data or data types are missing, and if so, these should be listed. To further the interpretation of the data, the current best-fit theoretical genetic model for the exploration area should be selected, as a model to test (step 2.4) and a mineral systems approach implemented (step 2.5), with the overarching aim of narrowing down the exploration area.

In the desk-study phase of pegmatite exploration, an important step is to decide whether the commodities sought are likely to occur in the chemical type of pegmatites present (group 1-LCT or group 2-NYF). A formation model (DPA or RMG) for the exploration area may help to narrow down the target area.

The chemical type of pegmatite is decided by compiling available mineralogical and chemical data for known pegmatite occurrences in the area, using the Mindat.org open database (www.mindat.org) and published papers and reports and then comparing with Table 3; this may allow some areas to be categorized as nonprospective.

Decision-making for the genetic type is more complex. Pegmatite magmas may be direct products of partial melting/anatexis (DPA) of metasedimentary, igneous, or metaigneous country rocks or residual melts of granitic magmatism (RMG) (e.g., Müller et al., 2022; Wise et al., 2022; Koopmans et al., 2024; Fig. 6). The RMG model implies that pegmatites crystallize from the residual, most fractionated melts released during the final crystallization of large-volume granitic intrusions (Černý, 1991b). According to this model, the LCT and NYF pegmatites that are most fractionated and are enriched in incompatible elements occur farthest from their parental granite pluton, which must be of the same age as the pegmatites (Fig. 7). This model fits a number of European pegmatite provinces—for example, the Variscan S-type granite-related pegmatite fields on the Iberian Peninsula (e.g., Roda-Robles et al., 2018) and others in Germany, Poland, and France, and the Paleoproterozoic A-type granite pegmatite fields of Ukraine, Finland, and north Norway (Table 6).

In Europe, the DPA model is most applicable to the Sveconorwegian South Scandinavian pegmatite province, the Permian Austroalpine Unit pegmatite province in Austria and north Italy, and the Caledonian Leinster province in Ireland (Table 6; Müller et al., 2015, 2017; Barros and Menuge, 2016; Knoll et al., 2023; Rosing-Schow et al., 2023). In these cases, the pegmatites are genetically, and often temporally, unrelated to any granite plutons in the area, as far as can be determined from field relationships and geochemical studies. The regional distribution and chemistry of these anatectic pegmatites is controlled by the chemistry, mineralogy, and degree of partial melting of their source rocks, which could be metasedimentary, igneous, or metaigneous, and by tectonic structures. Melts that formed these pegmatites may have travelled long distances (≥5 km; e.g., Černý, 1991a), and thus their current wall rocks are not necessarily the source of the melts. Characteristic of these pegmatite fields is a more heterogeneous or even erratic distribution of chemically evolved and less evolved pegmatites, making exploration more challenging (Fig. 8). In many cases, the presence of syngenetic tectonic structures control the district-scale emplacement patterns (Fig. 8B, C, E, F).

Assessing the genetic type (DPA or RMG) may require a range of information on the age, tectonic and structural setting, chemistry and mineralogy of the pegmatites and host rocks, nature of the wall rocks, how the melts/fluids evolved, any secondary enrichment/diminution processes, etc. In general, however, for the purposes of the initial stages of exploration, the following criteria can be used:

1. If your target area lies in one of the European pegmatite provinces, then determine its genetic type using Table 6. Some examples of genetic classification of non-European pegmatite fields are provided by Wise et al. (2022).

2. If some or all pegmatites in a particular field are within or in close proximity of a granite pluton of similar chemical affinity and similar age, then RMG genesis is probable, especially if the district-scale zoning of pegmatite composition is concentric to the pluton. In these cases, chemical primitive pegmatites are found within or near the pluton, whereas the most fractionated ones occur farthest from the granitic source (Černý, 1991b).

3. Use mineralogical information on the target area from the Mindat.org database (www.mindat.org) to inform the decision on the most appropriate genetic model (see Table 3).

Data and information from the first stages of the desk study should be assessed using the mineral systems approach, as defined by Fraser et al. (2007). This builds on the source-pathway-trap-modification concept and evaluates which of the stages/processes contribute to the mineralization and to what extent. It also considers how the stages/processes (manifested in mineralogy, chemistry, structures, etc.) can be identified using geologic, geophysical, and geochemical methods. For pegmatites, this means identifying the source of the melts, the route by which these were transported to their zone of final crystallization, and where and how the melts evolved and were trapped to produce mineralized pegmatites,and were then possibly affected by subsolidus processes or subsequent metamorphism and deformation (e.g., Duuring, 2020). The overall aim is to define mappable criteria and proxies for critical mineralizing processes leading to economic mineralization. Table 8 summarizes the characteristics of pegmatite genetic types and the application of the mineral systems approach, source-pathway-trap-modification scheme and the resulting mappable criteria, based on results from the GREENPEG demonstration sites. The first step in using the table is to decide on the pegmatite genetic type: DPA-NYF, RMG-NYF, DPA-LCT, or RMG-LCT (see step 2.4). For European pegmatite provinces, this genetic classification is known (see Table 6; Fig. 4). Also, for most pegmatite provinces worldwide, genetic pegmatite type has been established. Published examples are Shearer et al. (1992) and Webber et al. (2019) for the United States, Cerný (1991b) and Turlin et al. (2017) for Canada, Fuchsloch et al. (2018) and Shaw et al. (2022) for Africa, Kendall-Langley et al. (2020) for Australia, Li et al. (2023) for China, and Lima et al. (2019) for Brazil. The genetic classification of pegmatites at the target site is not essential for toolset application, but it can save costs in exploration by allowing methods to be applied more precisely and effectively.

Source: The source is the rocks that underwent partial melting to form melts (±fluids) and then either crystallized directly or underwent fractionation to form DPA melts or formed granite batholiths or plutons where there was extensive fractionation to produce RMG pegmatite melts. The composition of the source strongly controls pegmatite chemistry and mineralogy (LCT or NYF affinity; Table 8). The Li sources of LCT pegmatite melts are metasediments and metaigneous rocks with granitic S-type affinity that are enriched in Li > 100 ppm (Knoll et al., 2023; Koopmans et al., 2024) compared to the average upper crustal composition of 24 ppm (Rudnick and Gao, 2014). Fluorine and REE sources of NYF pegmatites are metaigneous rocks with A-type or I-type affinity (Černý et al., 2012).

Pathways: Pathway structures are the main control on the distribution of DPA pegmatites. They act as permeable zones through which melts and fluids may be focused and channelized until they reach the zone of pegmatite formation. Volatile-rich melts, which usually have a relatively low viscosity, can penetrate surrounding rocks along bedding or metamorphic foliation planes to form sills or via ductile or brittle structures to produce dikes or segregations. Pathways for melts do not need to be created at the time of magmatism or partial melting but are often structures that formed long before the mineralization event (Hagemann et al., 2016) and become reactivated as dilatant zones during the pegmatite intrusion event. Enhanced permeability within shear zones can be via dilatant grain boundaries and microcracks at a microscopic scale and fractures at a macroscopic scale (e.g., Simpson et al., 2001). Pathway structures for RMG pegmatites may include preexisting faults or those that form during emplacement of pegmatites and related granite plutons.

Traps: Structural traps for pegmatite melts are sites into which melts can be channeled and crystallize, provided that the required chemical and physical conditions are fulfilled. They are generally dilatational, occurring in open or lowpressure segments of faults and shear zones, in fold hinges, between rotating rigid blocks, and between rocks of different rheology. The size of the first-order trapping structures and corridors are of regional scale. In the case of the Leinster albite-spodumene pegmatite belt in Ireland, for example, the trapping corridor is at least 40 km long and 3 km wide (Barros et al., 2022; Fig. 8E). The trigger(s) for crystallization is/are uncertain but might be undercooling in most cases, or perhaps release of magmatic hydrothermal fluids.

Modification: Emplaced and crystallizing or crystallized pegmatites can be modified by autometasomatism (e.g., albitization or quartz-muscovite greisenization causing replacement of spodumene and, thus, lowering the Li ore grade). Most pegmatites are either late- to post-tectonic with respect to regional orogenic episodes, or they are emplaced under anorogenic conditions. However, some are recrystallized during subsequent metamorphic episodes, e.g., at Wolfsberg in Austria and Tysfjord in Norway. The effects on pegmatites are relatively little studied but are mentioned briefly in Table 8—for example, the increase in the quality of high-purity quartz seen in Tysfjord pegmatites owing to quartz recrystallization and related crystal purification (Zhou et al., 2023).

In conclusion, the correct choice of the genetic model is crucial to the subsequent development of the correct (1) mineral systems approach, (2) exploration strategy, and (3) toolset for the following reasons:

1. RMG pegmatites of the chemical LCT type may be effectively explored by identifying and characterizing the parental (“fertile”) granite pluton. Best prospects are late- to post-tectonic, S-type muscovite and two-mica granites emplaced at moderate to shallow crustal levels. These granites have high initial ⁸⁷Sr/⁸⁶Sr isotope ratios and low K/Rb, K/Cs, and K/Li ratios and are typically texturally inhomogeneous and highly silicic, leucocratic, and meta- to peraluminous, often with accessory cordierite, andalusite, or garnet (Groat and Ercit, 1996).

2. A field or district assessment of DPA pegmatites requires generally a denser sampling grid than for RMG pegmatites to reveal any regional chemical or mineralogical zoning of the field because of their relatively irregular distribution and size/shape and orientation, especially in complexly deformed zones.

3. The focus on revealing and interpreting province- or district-scale tectonic structures should be much stronger for DPA than for RMG fields because structural control is much stronger for anatectic pegmatites. Thus, it is suggested that the application of airborne magnetic (+ radiometric) studies is essential for anatectic pegmatite exploration.

This step provides the site-specific exploration workflow These are based on deposit characteristics, project stage and objective, and method selection and is therefore scale dependent. The GREENPEG toolset divides the exploration workflow into three major scales: province scale (500–10,000 km²), district scale (25–500 km²), and prospect scale (<25km²).

Table 2 lists exploration methods for the three scales verified through GREENPEG application. Some methods applications are not exclusively limited to one single scale but can be utilized across scales (see step 3.3). Accordingly, exploration work requires moving upand downscale during the whole exploration process, particularly between district and prospect scale, to constantly add data and increase the knowledge. The desk study and exploration environment assessment define on what scale exploration should commence to develop the most suitable exploration strategy for pegmatite deposits. The choice of exploration methods should start at the largest scale necessary and then move through to prospect scale. Information from all the scales should be integrated to define a conceptual model for the target area.

The first step is to identify the locations of greatest potential interest and any critical red flags prior to undertaking any exploration activity, either remotely or on the ground:

1. A risk assessment for the activities, to cover health and safety aspects of the work involved, legal aspects (third-party liability, inadvertent contravention of legal restrictions, etc.), and financial liability (specialist advice is recommended);

2. Community stakeholder analysis and desk-based baseline social context studies;

3. Environmental context and desk-based baseline studies, including an appropriate environmental and social impact scoping assessment, including checking that all regulatory requirements are met;

4. Development of a preliminary exploration schedule;

5. Planning a program of community relationship building and engagement and, initially, identifying and making contacts with community leaders;

6. Seeking relevant permissions for access to sites, to sample and to fly with remote sensing devices, etc.

Basic geologic field mapping and/or verification of outcropping rock types and structures at district and prospect scales is always required, even if maps already exist (Apps. 16, 17). Petrophysical studies (Apps. 24, 25) determining the physical properties of the different rock types present should be carried out prior to any geophysical field campaign. The gained knowledge will help understanding the airborne data and identify the most efficient airborne and ground-borne geophysical techniques to plan and sustain a cost-effective geophysical exploration. If not possible because of lack of rock samples, time, and/or financial restrictions, the GREENPEG petrophysical database (Haase and Pohl, 2022) should be consulted as a first step (App. 25).

For province-scale pegmatite exploration, three methods were developed and verified (Apps. 1–3):

1. Spectral identification of outcropping pegmatites from satellite images: Satellite images are evaluated together with outcrop identification using remote sensing data (Landsat, ASTER, and Sentinel-2) and different image processing algorithms.

2. Morphological identification of pegmatites using laser imaging, detection and ranging (LiDAR) on a variety of platforms (satellite, aircraft, drone): Various products can be acquired that allow coverage over province to prospect scales.

3. Identification of large-scale faults and shear zones through study of radar images: The identification of regional structures can be achieved using automatic lineament detection on Sentinel-1 data or a digital elevation model (DEM; ALOS data). In areas with soil and vegetation cover, province-scale airborne magnetic data sets add value to the radar image procedure as they also provide lithological information.

Each method description is divided into three levels, with one decision sequence for each level, as summarized below (see also Table 9). The corresponding flowchart is provided in Figure 9.

1. Spectral band selection for satellite images: NYF and LCT pegmatites show contrasting spectral signatures, and therefore their discrimination requires the use of different spectral bands and satellite image sets (ASTER, Landsat-8/9, Sentinel-2). Band selection is done by superimposing each satellite band over representative spectra of typical minerals of respective NYF and LCT pegmatite types available in spectral databases (Cardoso-Fernandes et al., 2021a, b, 2022a; App. 4).

2. Application of image processing methods: Several criteria should be considered in the selection of appropriate optical images to download, the necessary preprocessing workflow, and image processing methods to be tested. The processing steps and parameters provided are based on published studies (Table 9; App. 1).

3. Creation of province-scale maps of outcropping pegmatites: The results obtained through image processing and masking indices (such as those for snow, water, and vegetation) are combined to generate a surface map of outcropping pegmatites. This can be overlain on existing geologic maps and other relevant geologic data (structures, for example), using geographic information system (GIS) software, to identify and delineate specific areas of interest, which can be further examined at district scale using the appropriate methodology.

1. Obtaining a LiDAR-derived DEM: The resolution of LiDAR data varies depending on the carrier platform, i.e., whether satellite, aircraft, or drone. Airborne LiDAR allows the mapping of pegmatite bodies/mines at province scale. However, acquisition of high-resolution LiDAR data using drones enables a more detailed analysis down to prospect scale.

2. Visual inspection of LiDAR-derived DEM to verify exploration relevant features: By visually examining the DEM and conducting overlay analysis in GIS, we can identify ancient or ongoing pegmatite mining works. Furthermore, this analysis can aid in directly identifying structural controls that influence the emplacement and evolution of pegmatites, as well as other significant morphological structures, namely ice direction in regions highly affected by glacial weathering allowing better determination of sample provenance in soil/till geochemical surveys, or the direct identification of pegmatites due to differential weathering.

3. Analysis of LiDAR-derived DEM to identify regional structures that may control pegmatite emplacement: Structural analysis of the patterns associated with ancient/ongoing pegmatite mining works may help to identify pegmatiterelated structural controls. Ultimately, the combination of all interpreted structures will lead to the production of target maps showing favorable areas for pegmatites for further studies at other scales.

Remote-sensing-supported analysis of regional structures: Downloaded remote-sensing data can be subject to the following data processing steps for regional structural analysis:

1. Automatic lineament extraction: Geomatics algorithms can be applied for the automatic extraction of lineaments, but to achieve acceptable results, it is necessary to optimize several parameters through trial and error. Some parameters may influence the quality of the results more than others. Once the lineaments are automatically extracted, it is important to conduct a visual inspection to manually remove any potential anthropogenic structures, e.g., roads and pipelines. Ideally, the map containing the extracted data should be compared with existing structural geologic maps.

2. Trend analysis and structural interpretation: This step is conducted through overlay analysis in GIS, allowing for the identification of large-scale faults and shear zones that may influence pegmatite emplacement, as well as the delineation of younger faults that cut and displace the dikes. For each lineament data set, a rose diagram is presented as well as information on the number of extracted lineaments, the mean vector direction, and the azimuth class (10° intervals) with the highest frequency (presented as a percentage).

3. Alternative processing: The results should be evaluated in accordance with the predetermined objectives, and if deemed unsatisfactory, additional measures can be implemented. For instance, replacing the input radar data with a DEM, generating shaded relief models, and repeating the lineament extraction and analysis.

To identify pegmatites, key indicators can be utilized and represented on a map, ranked based on their expected contributions. These indicators include pegmatite outcrops, ancient and ongoing pegmatite mine works and proximity or density of geologic structures. Combining the key indicators, we can create a map with the probability of pegmatite occurrence, where interesting areas are delineated for further studies at the district scale. New evidence at the district or prospect scale may justify revised approaches at the province scale to refine the exploration models.

The objective of district-scale work is to reduce the exploration area to one or more prospect-scale targets. Therefore, an across-scale application of the methodologies is necessary that brings together all available data. The district-scale area can be selected in two ways.

The first approach to downscale from province to district scale, often used by large companies, is to use historical and accessible data such as geologic maps, remote sensing, airborne geophysical maps, geochemical Li, Ta, Be, and/or Sn showings, the mineral occurrence database Mindat.org (www.mindat.org), and scientific publications. Ideally, the systematic mineral systems approach is applied (Table 8), and mappable criteria are ranked and overlain to find a potential district. Geochemical data may be available from state geological surveys, as previous exploration results lodged with state bodies, and in some cases from academic research. This may include geochemical data for pegmatite and host-rock samples, from outcrop and previous drilling, and soil and stream sediment samples. In addition, larger companies and geological surveys commonly start a greenfield or grassroots survey by carrying out conventional province-scale geochemical whole-rock sampling or by using minor and trace elements of pathfinder minerals of outcropping pegmatites and wall rocks (App. 18) to establish a regional geochemical map to define districts for more focused exploration. In addition, GREENPEG has introduced the use of quartz chemistry for geochemical pegmatite exploration (Müller et al., 2015, 2021; Keyser et al., 2023b; Zhou et al., 2023; App. 21), soil and stream sediment sampling (Apps. 22, 23), and/or laser-induced breakdown spectroscopy (LIBS) mapping (Dias et al., 2023; App. 19) to create geochemical district-scale maps (e.g., Cardoso-Fernandes et al., 2022c; Apps. 21, 22). The integration of these methods in the exploration flowchart is described in more detail in the following prospect-scale section. This data set, in conjunction with, e.g., remote-sensing and airborne geophysical data, can be used to rank and select possible district-scale targets.

The second approach, which is more commonly used by junior exploration companies, is to use historical and accessible data to upscale from prospect to district scale. The exploration company selects pegmatite outcrops with high Li, Ta, Sn, and/or Be or containing high-purity quartz, often on sites where exploration and/or drilling has already been performed. Initial holes are drilled to confirm the mineralization, if possible, to a depth of ~350 m or as required to align with the feasible depth of an open pit or underground mining. This step can create data for positive press releases to attract funding for the search of new prospects.

The next step is to increase knowledge of the existing mineralized zone both along and perpendicular to strike. Therefore, if not yet available, additional ground (licenses) on a district scale must be staked. Where pegmatites are related to structures, the shape of a district-scale area can be five times, or more, longer than wide. The lesser the knowledge, the larger the area will be. For example, the district-scale area of the GREENPEG Leinster demonstration site was chosen to be 20 km long by 2 km wide along the structural contact (shear zone) between the Tullow Lowlands granite and metasediments. This choice corresponds to the historical knowledge of the area, where spodumene pegmatites have only been found within this corridor.

For upscaling and downscaling, one should start with existing data supported by field visits to evaluate mappable criteria. All gathered data should be organized in GIS layers with the most prospective areas in each marked with polygons and ranked. Basic layers like topography (including digital terrain model; DTM) and district license polygon are not described further. Spatial ESG data collected during the desk-study stage (such as conservation sites, land use, settlements, and infrastructure) and throughout the project (for example, locations of particular stakeholders or issues) can also be added as GIS layers.

Based on the GIS layer approach, the selection and ranking of prospective areas can be discussed and decided within the exploration team. If new data are obtained or interpretations made, the map layers must be adjusted and updated. The GIS project is a baseline document for the exploration work, which should be available to all levels of the project in order to gather the most information possible from the different stakeholders. The flow chart provided in Figure 10 gives an overview of how the different layers are linked to each other. Table 10 gives an overview of the district-scale airborne geophysical methods. Detailed descriptions and performance of these methods with examples from the GREENPEG demonstration sites are provided in Appendices 5, 6, and 7. The main components of the GIS layers are described in Table 11. When performing airborne geophysical studies, low-altitude flights may be noisy and, thus, an information and public awareness campaign (in advance) may be required.

Prospect-scale exploration typically takes place within small (<25 km²) license areas where, very often, targets have already been identified. The range of available exploration methods is significantly greater than for district or province scale (Table 12). In addition to the larger-scale methods, drone- and ground-borne tools can be applied to add local geochemical and mineralogical data and understanding. Also, geophysical depth-imaging methods, e.g., electrical resistivity tomography (ERT), seismic, gravity, or groundpenetrating radar (GPR), may provide reliable geometries and depth information for pegmatites. However, to choose the right geophysical tool(s), the petrophysical contrast between pegmatites and wall rock must first be known. This also applies to geochemical tools that depend on recognizing contrast between pegmatites, host rocks, and potential geochemical halos (LIBS and whole-rock halo chemistry, soil and stream sediment chemical mapping).

With increasing geologic complexity and target spatial resolution, the concept of jointly interpreting various data sets, e.g., petrophysics, geophysics, lithology, tectonics, mineralogy, and geochemistry, is a well-known and usually very beneficial approach. Geophysical identification of buried pegmatites can be difficult because of small petrophysical contrasts, whereas geochemical data (e.g., soil and stream sediments) can have excellent 2-D locating potential but yield no geometrical or depth information. In addition, small changes in the geologic setting can have an important impact on pegmatite mineralization potential, crucial for exploration companies in their decision-making. However, the combination and integration of various data help to minimize or even overcome the uncertainty of an individual data set.

Community engagement becomes essential at prospect scale and should be initiated before work on the ground begins. Defining the community relevant to the prospect and devising an effective communication plan are key to initiating community engagement. Early engagement will minimize the risk of erroneous information circulating in the community as exploration proceeds.

The starting point of the prospect-scale toolset assumes that a prospect has been identified and that commodities sought have already been defined but allows for the possibility of by-product discovery, e.g., Ta in Li prospects. Prospect knowledge will vary from one area to another. By default, it is assumed in this document that a prospect has been identified from recent district-scale exploration or analysis of previous data sets, but it is recognized that this is not always the case. Ideally, there will be a district-scale understanding of the following basic pegmatite features before undertaking prospectscale exploration:

1. Where do pegmatites crop out (compiled information of steps 3.2 and 3.3)?

2. What are their approximate dimensions and shape?

3. What is their typical orientation, especially strike?

4. Do they occur in swarms or as widely separated bodies?

5. What rock types host pegmatites?

If the above pegmatite features are unknown, or are poorly known, then an early orientation survey should be undertaken.

The recommended GREENPEG prospect-scale exploration process is outlined in Figure 11; users should be aware of the following:

1. In any given prospect, some recommended methods will not be applicable for a variety of reasons specific to the commodities sought, geologic setting, practicalities on the ground, and ESG factors. Most prospect-scale methods are nondestructive, only requiring land access. However, emissions caused by transport to site and equipment operation should be considered, and activities of field workers and drones may disturb wildlife or farm animals. Avoid activities during nesting and hunting seasons. Soil and stream sediment sampling causes ground disturbance, which is minimized by protecting vegetation from excavated soil using plastic sheets and, for soils, infilling the sampling hole and replacing the turf after completed work. If excessively high radiation levels are observed, take preventative actions and consider whether this has economic implications.

2. In general, there should be continuous updating of data representation (maps, plots, etc.) and existing hypotheses as more data are acquired.

3. ESG data should be continuously updated to inform the technical planning and progress of the exploration campaign.

Deciding which methods to apply:

1. Eliminate methods that should not be applied, e.g., if petrophysical data indicate no physical property contrast, certain geophysical methods will not give a pegmatite-related signal; if soil cover is too thick, radiometric measurements might fail to detect the radioactive signal of pegmatites, and high vegetation might make drone-borne surveys redundant (Table 12).

2. Consider method utility for the commodity or type of pegmatite sought.

3. For selected methods, set provisional sequence of deployment defined by efficiency in respect to the geologic setting, cost-benefit analysis and social and/or environmental considerations, noting that some methods are more economical or less disruptive when carried out together.

4. Adjust for limitations on deployment of these methods (seasonal, acquisition of staff and equipment, permitting).

5. The planned sequence of method deployment should be reassessed as results are acquired and interpreted.

Data processing is very specific to the method and is outlined in the accompanying method appendices (Apps. 8–24). When data have gone through initial processing and been checked and filtered for quality, further processing may be through traditional, manual knowledge-based methods. Alternatively, to minimize bias, machine learning algorithms can be applied to analyze large data sets for features that can be linked directly or indirectly to pegmatites. For prospect-scale exploration, a combination of both approaches is recommended.

Data visualization as a series of GIS layers is recommended. In the exploration flowchart (Fig. 11), these are presented in groups for simplifications, but GIS layers for individual methods or small groups of closely related methods are required. The range of layers will depend on the mix of methods used, but it is recommended that district-scale maps should provide the starting point that can be adapted as necessary. If exploration proceeds successfully, then 3-D visualization software will be required to estimate initial ore grade and tonnage information. Although ESG and basic geologic mapping information should always be acquired first, the optimum sequence of the large number of potential geophysical and geochemical methods will vary from prospect to prospect and may not fully follow the sequence set out in Figure 11.

The end point of the prospect-scale toolset is to be able to define drilling targets for resource delineation, based on an adequate understanding of ESG issues and of the geology, mineralogy, geochemistry, and geophysical properties of the target pegmatites and surrounding rocks.

Until very recently, deliberate discovery of buried pegmatites has been almost nonexistent because of an apparent absence of viable detection techniques. The toolset presented is the first to set out a comprehensive guide to exploration for all types of granitic pegmatites, especially including cases where they are buried. It is based on four years of work by the GREENPEG team, which has been drawn from 13 academic, industry, and government organizations across Europe. The project has allowed mutual exchange of understanding by team members of the wide range of expertise represented in GREENPEG, ranging from remote sensing, geologic, and numerous geophysical and geochemical techniques. Combined with the wide range of methods and technologies developed, adapted and tested, it is this reciprocal understanding of expertise that has led to many new insights into pegmatite exploration methods. A priori knowledge gained from petrophysics and borehole logging has potential to perform geophysical exploration that is more targeted and cost-effective. The strengths of the multi-disciplinary consortium were the continuous accumulation of broad knowledge and experience at every project stage and the evaluation and reassessment of achieved data and applied methods, including those which have been underrepresented or simply ignored in pegmatite exploration approaches. The result is an exploration toolset equipping small- and medium-scale companies getting started or progressing in their activities for pegmatite exploration. The developed toolset is versatile by offering a range of options, from the design of a complete workflow to individual methods focusing only on special aspects during exploration. After the project finish in October 2024, the project consortium will continue to work as expert group ensuring the exploitation and dissemination of the toolset and providing advice to stakeholders if required.

The toolset represents the state of the art as GREENPEG sees it. Technical innovation continues and will certainly mean that existing exploration techniques improve in their spatial resolution and detection limits and in the environments in which they can be deployed. Apart from the technical methods of mineral exploration, GREENPEG has also integrated ESG practices and considerations into this toolset. It is difficult to predict in any detail how this new key aspect of mineral exploration will evolve. The pervasive use of social media already allows erroneous, and sometimes deliberately false, information to rapidly fill information vacuums and to set agendas within communities. This situation will persist and likely intensify, highlighting the need for exploration companies to plan community engagement before starting exploration and to be open and transparent about their intentions and with their data where it is not commercially sensitive. The accurate application of the toolset, however, will minimize social and environmental impacts of the applied exploration activities employing today’s ESG standards.

Europe hosts many fertile pegmatite provinces, which are generally underexplored for various reasons but have high potential for new discoveries. The discovery of new pegmatite deposits in Europe is utmost important for economic growth and sustainability depending on a robust and secure raw material supply chain, because Li, high-purity quartz, ceramic feldspar, and other critical and strategic raw materials bound in pegmatite deposits are essential particularly for renewable energy production and storage. The application of the toolset by exploration and mining companies will increase the domestic resources of pegmatite-related commodities and in this way reduce Europe’s dependence on raw material imports from politically unstable regions or countries with uncertain trade relationships. Additionally, the discovery of new deposits in Europe will facilitate shorter supply chains and reduce transportation costs, promote technological innovation and competitiveness within the continent, and stimulate job creation and economic growth within the region. In conclusion, the widespread application of the GREENPEG toolset will increase the exploration success in Europe and elsewhere.

This study was funded by a European Commission Horizon 2020 innovation program grant (agreement 869274), through the GREENPEG project New Exploration Tools for European Pegmatite Green-Tech Resources. This publication has emanated from research supported in part by a research grant to JFM from Science Foundation Ireland (SFI) under grant 13/RC/2092_P2 and cofunded under the European Regional Development Fund. The Portuguese authors highly acknowledge the support by national funds of the Fundação para a Ciência e a Tecnologia (FCT), I.P., Portugal, through the projects UIDB/04683/2020 (doi: 10.54499/UIDP/04683/2020) and UIDP/04683/2020 (doi: 10.54499/UIDB/04683/2020).

The authors thank all GREENPEG partners for their contribution to the project. We are grateful to two anonymous reviewers for their careful and constructive comments and to the guest editors, Tom Benson, Simon M. Jowitt, and Adam Simon, for thoughtful editorial handling.

Axel Müller is professor of mineralogy and economic geology at the Natural History Museum, University of Oslo, and the head of the Norwegian Center for Mineralogy. Throughout his diverse academic and industrial career, he has explored and researched metal mineralization associated with granites, pegmatites, and porphyries and industrial mineral deposits. After completing his Ph.D. degree at the University of Göttingen in Germany, he furthered his research at the Natural History Museum, London. He then spent 11 years working as an exploration geologist. In 2015, he returned to academia. Since 2020, he has been coordinating the GREEN-PEG EU project, which develops methodologies for pegmatite exploration.