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The International Journal of Life Cycle Assessment (2023) 28:1132–1141

https://doi.org/10.1007/s11367-023-02200-x

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LCA ANDCHEMISTRY

Cradle‑to‑gate life cycle assessment ofiodine production fromcaliche

ore inChile

LindseyRoche1 · MarcoMuhl1· MatthiasFinkbeiner1

Received: 18 October 2022 / Accepted: 19 June 2023 / Published online: 11 July 2023

Abstract

Purpose Iodine and its compounds have several industrial uses, primarily in nutrition and healthcare. So far, no specific

LCA data for industrial iodine production are available. The purpose of this study is to provide the first LCA using primary

industry data for iodine production from caliche ore in Chile.

Methods The study is a process-based, attributional LCA and follows the relevant ISO standards 14040/44. Primary data

were collected from the world’s main producer representing their production for the years 2019 and 2020. Economic allo-

cation was applied to deal with the by-product sodium nitrate. The impact assessment was performed with a set of CML

2001 indicators.

Results and discussion Cradle-to-gate total LCIA results per 1000kg of iodine prill product include a GWP100 of 1.48E+04kg

CO2 eq., an AP of 2.53E+02kg SO2 eq., a POCP of 1.20E+01kg C2H4 eq., an EP of 9.60E+00kg PO4

3− eq., and an ADP

fossil of 2.44E+05MJ. The main contributor across process steps and for most impact categories is electricity consump-

tion. Other hotspots include diesel combustion, hydrogen peroxide, sulfur, sulfuric acid, kerosene, and sodium hydroxide.

A scenario analysis with renewable electricity revealed a reduction potential for all impact categories. As an example, the

GWP could be reduced by 33–38%.

Conclusions This study is the first LCA for iodine production from caliche ore based on primary industry data. The switch to

renewable sources was identified as the main improvement potential for the hotspot electricity consumption, with a potential

reduction of at least 25% for all impact categories except ODP.

Keywords Life cycle assessment· Iodine· Caliche· Mining· SQM· Global warming potential

1 Introduction

Iodine is a chemical element with the symbol I and atomic

number 53. The heaviest of the stable halogens, it exists as

a semi-lustrous, non-metallic solid at standard conditions

that melts to form a deep violet liquid at 114°C (237 °F),

and boils to a violet gas at 184°C (363 °F). The element

was discovered by the French chemist Bernard Courtois

in 1811. It is found in seaweed and brine extracted along

with natural gas as well as Chilean caliche deposits. Iodine

is a micronutrient element that is fundamental to a living

body and is essential for the subsistence and growth of

humans and animals (Kaiho 2015). It is on the World Health

Organization’s List of Essential Medicines (World Health

Organization 2021).

Iodine is used in a broad spectrum of products including

medicated gargle, X-ray contrast media, antimicrobial

agents, and catalyst and has many applications in the field

of agriculture. Recently, iodine has found a wide range of

applications in innovative materials, such as liquid–crystal

display (LCD) polarizing film and electrolytes of dye-

sensitized solar panels (Kaiho 2015).

The dominant producers of iodine today are in Chile

and Japan. The global production volume of iodine is

about 30,000 tons per year and almost 60% of this pro-

duction comes from the north of Chile, where two thirds

of the iodine reserves of the entire planet reside (SQM

Iodine 2022).

Communicated by Peter Rudolf Saling.

* Lindsey Roche

lindsey.roc[email protected]

1 Chair ofSustainable Engineering, Technische Universitaet

Berlin, Str. des 17. Juni 135, 10623Berlin, Germany

1133The International Journal of Life Cycle Assessment (2023) 28:1132–1141

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LCA information of iodine production is scarce. To the

knowledge of the authors, there is to date no primary indus-

try data based LCA of iodine production available in the

scientific literature or in LCA databases. Ecoinvent provides

a dataset for iodine production from brine, but the documen-

tation states that it is modeled based on bromine production

as it is considered to be similar to iodine production (Sutter

2011). Therefore, this study represents the first industry data

based LCA of iodine globally available.

This study was possible due to the collaboration with

Sociedad Química y Minera de Chile (SQM), the main

global producer of this product. The iodine produced by

SQM has a purity of 99.9%. SQM is a Chilean chemical

company and a supplier of plant nutrients, iodine, lithium,

and industrial chemicals. SQM’s headquarters are in San-

tiago de Chile, but its natural resources and its main pro-

duction facilities are located in the Atacama Desert in the

regions of Tarapacá and Antofagasta. Today, SQM has the

largest iodine plant in the world called Nueva Victoria and

a second site in Pedro de Valdivia. For this study, com-

prehensive and detailed production data were collected at

both sites.

Chile is the only country that produces iodine from the

mineral caliche. The word caliche derives from a Quechua

word, which means salt. The caliche mineral from northern

Chile contains the largest known nitrate and iodine deposits

in the world and is the world’s only source of commercial

exploitation of natural nitrate (SQM Iodine 2022). As such

the LCA presented here is only representative for the caliche

route and not for the production from brine as the second

most relevant production process for iodine.

2 Methods

This study was conducted in accordance with relevant ISO

standards, ISO 14040 2006 and ISO 14044 2006 (Interna-

tional Organization for Standardization 2006a, b). This sec-

tion documents the main elements and decisions of the goal

and scope definition for the study. First, Sect.2.1 introduces

the goal of the study. Section2.2 then goes into the different

aspects of the scope definition.

2.1 Goal definition

The aim of this study was to quantify relevant resource

inputs and emissions associated with the production of pri-

mary iodine from caliche ore to iodine prill product, to iden-

tify hotspots in the production of iodine, and to develop the

first detailed LCA of iodine globally with primary data. The

main target audience for the original study commissioned

by SQM were internal company stakeholders and decision

makers, while the communication to customers is seen as an

option. For this paper, the main goal is to share the results

with the scientific community.

2.2 Scope definition

This section documents the scope definition intended to

achieve the goal described in Sect.2.1. In the following,

the product system and functional unit (Sect.2.2.1), system

boundaries (Sect.2.2.2), allocation procedures (Sect.2.2.3),

life cycle inventory and data collection (Sect.2.2.4), impact

assessment (Sect.2.2.5), and interpretation (Sect.2.2.6)

are presented.

2.2.1 Product system andfunctional unit

The studied product system is the production of iodine

prill from caliche ore in Chile where it is produced with

a minimum purity of 99.8% (SQM Iodine 2023). During

this process, sodium nitrate is produced as a co-product.

The co-product is included in the system boundary, but

has been treated using the allocation approach described in

Sect.2.2.3. Iodine is an intermediate product with multiple

uses. Consequently, 1000kg of iodine prill product from cal-

iche ore at the factory gate in Chile with a minimum purity

of 99.8% has been defined as a mass-based functional unit

and reference flow. This functional unit is also consistent

with the goal of providing data to LCA practitioners and

other stakeholders, as they typically connect their models on

a mass basis to a cradle-to-gate system boundary.

The producing company, SQM, operates two production

sites (Nueva Victoria and Pedro de Valdivia). Their contri-

butions to the reported results per functional unit are scaled

according to their respective production volumes.

2.2.2 System boundaries

As iodine is an intermediate product, the study is a “cradle-

to-gate” LCA covering all process steps from caliche ore

mining (i.e., the cradle) to the finished iodine prill product

(i.e., the gate). Figure1 schematically shows the system

boundary defined for the LCA.

The two production sites of Nueva Victoria and Pedro

de Valdivia operate in a similar manner, but overall have

different production routes. In Nueva Victoria, caliche ore

is mined and then treated by heap leaching, while at

Pedro de Valdivia, caliche ore is recovered from tailings

of previously mined caliche deposits. From there, similar

production routes for the resulting brine are taken with both

sites including iodide production plants, in-process brine

neutralization plants, and iodine production plants. They are

also interconnected with a portion of the iodide produced

at Nueva Victoria being transported by truck to Pedro de

Valdivia for the iodine production step.

1134 The International Journal of Life Cycle Assessment (2023) 28:1132–1141

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It is important to note that the in-process brine neutrali-

zation plant process step was allocated solely to the iodine

prill product. If the iodide production process step was not

occurring, the feeble brine would not need to be neutral-

ized before proceeding to the next process step for sodium

nitrate production; therefore, the inputs and outputs for the

neutralization plant are considered to be within the iodine

prill production system. It is modeled within the iodide pro-

duction process step.

2.2.3 Allocation

The product system leads to two products, i.e., iodine prill

and sodium nitrate (NaNO3). The processes of caliche ore

Fig. 1 System boundary considered in the production of iodine prill product

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mining and heap leaching serve the purpose of producing

both products. The process step caliche ore mining is done

as a joint process for both iodine and sodium nitrate pro-

duction, while the heap leaching process step is conducted

largely for the recovery of iodine and its economic value. In

order to calculate the intended LCA for iodine prill only, the

co-product sodium nitrate needs to be allocated. Avoiding

allocation by subdivision of the processes is not possible.

System expansion was not applied in order to keep the total

results for both co-products consistent and to ensure that

the sum of the allocated inputs and outputs are equal to the

inputs and outputs of the unit processes before allocation.

Furthermore, SQM is the only company producing both

nitrates and iodine from caliche ore. SQM uses an alloca-

tion approach within their company and wanted to have an

environmental profile for the co-product as well, necessitat-

ing allocation over system expansion.

Allocation by underlying physical relationships between

the co-products, e.g., mass or energy, was not seen as pre-

ferred option as sodium nitrate is produced in a much larger

quantity (differing two orders of magnitude in the 2019 and

2020 production quantities), whereas iodine has significantly

higher economic value (earnings in 2019 and 2020 from

iodine prill were two orders of magnitude higher per ton than

that of nitrate derivatives: fertilizers and/or industrial chem-

icals (SQM 2020)). Consequently, the burdens have been

allocated in proportion to their internal cost distribution for

the mining and heap leaching processes with an economic

allocation (73% to iodine and 27% to sodium nitrate). This

allocation choice is in line with the harmonization of LCA

methodologies for the metal and mining industry, where

economic allocation is the preferred choice in cases where

mass allocation would fail to capture the main purpose for

the operations (Santero and Hendry 2016).

2.2.4 Life cycle inventory anddata collection

The life cycle inventory was modeled in GaBi software (ver-

sion 10.5.1.124) (Sphera Solutions GmbH 2021). The geo-

graphical scope was the production in Chile and the techno-

logical scope was the existing production processes of SQM

in the years 2019 and 2020. For higher representativity and

since the heap leaching process takes longer than oneyear, it

was decided to usetwoyears of data to calculate the average

of the iodine prill production process at SQM.

A significant amount of primary data for all produc-

tion steps operated by SQM was collected and validated.

Table1 shows the processes and flows collected as primary

data. The last three columns in Table1 show the second-

ary dataset which was used to model the inputs. For con-

sistency reasons and coverage, preference was given to the

GaBi database, whereas ecoinvent data were used in case no

appropriate GaBi dataset was available.

In some instances, multiple datasets were combined to

create the identified input material as shown in Table1.

This was the case for sulfonitric acid (combining sulfuric

acid and nitric acid) and for the plastic packaging bags

(e.g., Krealon bags and Maxibags). Additionally, a mix

of ferrous metals was created for the ferrous metal waste

output since the exact metals were unknown. In the case of

sodium metabisulfite, there was no dataset available and a

substitution was made using the dataset for sodium sulfite

as a proxy since they have equivalent functions (Delgove

etal. 2019). The impact of this replacement is discussed

in the results (Sect.3.3).

2.2.5 Impact assessment

The impact categories and indicators considered to be of

relevance to the goals of the study are shown in Table2.

Various impact assessment methodologies are applicable

for use in this context including, e.g., CML (Heijungs

etal. 1992), ReCiPe (Goedkoop etal. 2009), and selected

methods recommended by the ILCD as part of their EU

Product Environmental Footprint (PEF) Initiative (European

Commission 2013). For this study, the CML impact assessment

methodology framework (CML 2001 update January 2016)

was chosen (CML - Department of Industrial Ecology 2016).

CML characterization factors are widely used and tested.

Many companies and industry associations still prefer this

method due to its robustness and for consistency with previous

studies (PE International 2014). As demonstrated by Bach

and Finkbeiner (2017) for selected impact categories, more

recent impact assessment methods are not per se superior to

established methods like CML.

Normalization and weighting are optional steps in LCA

(International Organization for Standardization 2006a, b)

and it was chosen not to apply them. No appropriate nor-

malization data set was available and therefore, applying

normalization would not provide added value.

2.2.6 Interpretation

The results of the LCI and LCIA were interpreted accord-

ing to the procedure described in ISO 14044. First, sig-

nificant issues such as the main process steps, inputs, and

emissions with a high contribution to the overall results

were identified. Second, the completeness and consistency

of the data and model were checked. Third, sensitivity

analysis for a mass-based allocation between iodine and

sodium nitrate was performed. Finally, a scenario anal-

ysis for the use of alternative electricity sources (natu-

ral gas and renewables instead of the Chilean grid mix)

was performed.

1136 The International Journal of Life Cycle Assessment (2023) 28:1132–1141

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Table 1 Processes and flows collected as primary data and the datasets used to model the inputs. The GaBi database is the source of datasets and

flows unless otherwise stated in the table

Secondary dataset or elementary flow Reference year Geographic scope

Inputs

 Electricity CL: electricity grid mix 1–60kV 2017 Chile

 Ammonium nitrate EU-28: ammonium nitrate 2020 European Union—28

 Diesel RSA: diesel mix at refinery 2017 South America

 Ground water Elementary flow—ground water,

regionalized, CL (water)

– Chile

 Mineral extraction site Elementary flow—mineral extraction site,

regionalized, CL (occupation)

– Chile

 Fresh water Elementary flow—fresh water,

regionalized, CL (water)

– Chile

 Sulfur RSA: sulfur (elemental) at refinery 2017 South America

 Sulfuric acid EU-28: sulfuric acid (96%) 2020 European Union—28

 Caustic soda EU-28: sodium hydroxide mix (50%) 2020 European Union—28

 Kerosene US: kerosene/jet A1 at refinery and RSA:

kerosene at refinery

2017, 2017 USA, South America

 Soda EU-28: soda (Na2CO3) 2020 European Union—28

 Quick lime BR: lime (CaO; quicklime lumpy) 2020 Brazil

 Coya Sur process water EU-28: process water from ground water 2020 European Union—28

 Diatomea Elementary flow—diatomite (non-

renewable resources)

– –

 Fuel oil RSA: light fuel oil at refinery 2017 South America

 Sulfonitric acid EU-28: sulfuric acid (96%) and DE: nitric

acid (98%)

2020, 2020 European Union—28, Germany

 Sodium metabisulfite RoW: sodium sulfite production

(ecoinvent 3.7.1)

2020 Rest-of-the-world

 Activated carbon DE: activated carbon 2020 Germany

 Hydrogen peroxide DE: hydrogen peroxide (100%; H2O2)

(hydrogen from steam cracker)

2020 Germany

 Filter sand (cellulose) DE: cellulose fiber boards (EN 15804

A1-A3)

2020 Germany

 Paper drums RoW: paper sack production ecoinvent

3.7.1

2020 Rest-of-the-world

 Polyethylene (PE) bags RER: polyethylene film (PE-LD) plastics

Europe

2005 Europe

 Krealon bags (PE and PVDC) RER: polyethylene film (PE-LD) plastics

Europe and RER: polyvinylidene

chloride (PVDC) plastics Europe

2005, 2005 Europe, Europe

 Maxibags (Krealon bag + PP bag

stitched together) RER: polyethylene film (PE-LD) plastics

Europe and RER: polyvinylidene

chloride (PVDC) plastics Europe and

DE: polypropylene film (PP) without

additives

2005, 2005, 2020 Europe, Europe, Germany

 Thermal energy from natural gas CL: thermal energy from natural gas 2017 Chile

Outputs

 Diesel combustion GLO: crude oil combustion—diesel 2017 Global

 Sulfur combustion Elementary flow—sulfur dioxide

(inorganic emissions to air)

– –

 Fuel oil combustion GLO: crude oil combustion—fuel oil 2017 Global

 Hazardous waste EU-28: hazardous waste (statistical

average) (no C, worst case scenario incl.

landfill)

2020 European Union—28

 Non-hazardous waste EU-28: municipal waste landfill

(EN15804 C4)

2020 European Union—28

1137The International Journal of Life Cycle Assessment (2023) 28:1132–1141

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3 Results anddiscussion

This section presents and discusses the results of the study.

First, selected results of the life cycle inventory are pre-

sented in Sect.3.1. Then, Sect.3.2 documents the life

cycle impact assessment results and a contribution analysis

before Sect.3.3 goes into a more detailed hotspot analysis.

A sensitivity analysis for the allocation choice is discussed

in Sect.3.4. Finally, the results of the electricity scenarios

are discussed in Sect.3.5.

3.1 Life cycle inventory

A full disclosure of the primary data and associated inven-

tory is not possible due to confidentiality reasons. How-

ever, Table3 shows selected, important inventory data in

partly aggregated and rounded form.

Two thousand five hundred kilograms of caliche ore is

required as input per 1000kg of iodine prill product. Other

key material inputs include kerosene, ammonium nitrate,

sulfur, sulfuric acid, hydrogen peroxide, quick lime,

sodium hydroxide, and sodium carbonate. The blue water

consumed (the consumptive water use defined within GaBi

as the ground and surface water that leaves the water-

shed, e.g., by evaporation and freshwater integration into

products (Koehler and Thylmann 2016)) per 1000kg of

iodine prill product is 130 m3. Water is consumed in most

process steps of iodine production, with the majority of

blue water consumption occurring in the heap leaching

process. Energy inputs consist mainly of electricity usage

with 38,000MJ per 1000kg of iodine prill product and

63,000MJ per 1000kg of iodine prill product from diesel

combustion during caliche ore mining and transport. Addi-

tionally, there are energy inputs from fuel oil combustion

(2000MJ/1000kg iodine prill product) and thermal energy

from natural gas (2MJ/1000kg iodine prill product).

3.2 Life cycle impact assessment results

This section summarizes the LCIA results in absolute terms

and presents a relative contribution analysis of the various

process steps. Table4 presents the total results for the impact

categories selected per 1000kg of iodine prill.

Figure2 presents a contribution analysis for the main

process steps with regard to their share in the total results.

Mining, heap leaching, and iodide production in general

Table 1 (continued)

Secondary dataset or elementary flow Reference year Geographic scope

 Ferrous metal waste for recycling EU-28: stainless steel product (2205)—

value of scrap Eurofer and GLO: steel

sections, including recycling worldsteel/

ELCD and DE: cast iron component

(EN15804 A1-A3)

2014, 2007, 2020 European Union—28, Global, and

Germany

Table 2 CML 2001 Jan 2016

impact categoriesincluded in

the study

Impact category Unit Characterization factor Abbreviation

Climate change kg CO2 eq. Global warming potential GWP 100

Acidification kg SO2 eq. Acidification potential AP

Ozone layer depletion kg R11 eq. Ozone layer depletion potential ODP

Photo-oxidant creation kg C2H4 eq. Photochem. ozone creation potential POCP

Eutrophication kg PO4

3− eq. Eutrophication potential EP

Abiotic depletion (fossil) MJ Abiotic depletion potential (fossil) ADP fossil

Human toxicity kg DCB eq. Human toxicity potential HTP

Table 3 Material and energy flow summary per 1000 kg of iodine

prill product

Per 1000kg iodine prill Input Unit

Materials input

 Caliche ore 2500 kg

 Sulfur 1100 kg

 Ammonium nitrate 900 kg

 Sulfuric acid 700 kg

 Kerosene 600 kg

 Others 850 kg

 Water consumed 130 m3

Energy input

 Electricity 38,000 MJ

 Diesel 63,000 MJ

 Fuel oil 2000 MJ

 Natural gas 2 MJ

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contribute to more than 80% of the impacts. Mining has the

highest contribution to GWP and EP, whereas iodide pro-

duction has the highest contribution to AP, POCP, and ADP

fossil. Heap leaching dominates HTP. Operations at Pedro de

Valdivia and iodine production are generally less relevant for

the overall results. However, iodine production as an excep-

tion dominates the ODP result, but it has to be noted that the

absolute values of ODP are very small.

With regard to the contribution of elementary flows,

the GWP is clearly determined by CO2 emissions making

up 92.6% of the total GWP, followed by methane with

4.9%, and then nitrous oxide with 2.5%. Sulfur dioxide

with 89.3% is the largest contributor for AP, followed by

nitrogen oxides (8.4%) and hydrogen chloride (1.4%).

ODP is determined by carbon tetrachloride (66.9%) and

halon 1301 (21.4%). POCP is contingent upon sulfur diox-

ide (75.1%), nitrogen oxides (9.9%), and carbon monox-

ide emissions (4.5%). Nitrogen oxides (57.4%) and nitrate

(10.6%) emissions determine the EP. Crude oil (57.7%),

natural gas (20.8%), and hard coal (18.7%) make up the

largest contributions to ADP fossil. HTP is determined by

hydrogen fluoride (28.6%), arsenic (+ V) (18.4%), sele-

nium (13.1%), and nickel emissions (8.3%).

3.3 Hotspot analysis forindividual process step

A hotspot analysis was carried out for the main contributing

process steps. Over all process steps, the identified cross-

cutting hotspots were electricity, diesel combustion, hydrogen

peroxide, sulfur, sulfuric acid, kerosene, and sodium hydroxide.

As an example, Fig.3 displays the detailed hotspot assess-

ment for GWP for iodine production at Pedro de Valdivia. In

this case, electricity based on the Chilean grid mix has the

highest contribution with 44% (1% specific to water pump-

ing and 43% from all other electricity used in the process

step), followed closely by hydrogen peroxide with a contri-

bution of 39%. Sulfuric acid is the third largest contributor

with 6%. Sodium hydroxide, thermal energy, packaging,

activated carbon, sodium sulfite, and waste treatment play

minor roles with contributions of 2% or below. The potential

impact of using sodium sulfite as a replacement for sodium

metabisulfite is seen as negligible since it represents only a

small contribution to the GWP (e.g., 1% in the iodine pro-

duction process step).

3.4 Mass allocation sensitivity analysis

A sensitivity analysis for a mass-based allocation between

iodine and sodium nitrate was performed to understand the

impact of allocation choice. The results for mass-based allo-

cation were consistently lower across all impact categories

than for economic-based allocation. This is due to the sig-

nificant mass difference of iodine and sodium nitrate that

are produced which leads to the caliche ore mining and

heap leaching process steps being almost fully allocated to

the sodium nitrate when applying mass-based allocation.

The results of the sensitivity analysis indicate that the eco-

nomic-based allocation more accurately reflect the purpose

of the operations. Table5 displays the GWP per 1000kg

of iodine prill for the total, caliche ore mining, and heap

Table 4 Cradle-to-gate total LCIA results from direct and indirect

emissions per 1000kg of iodine prill product (CML 2001 indicators)

LCIA results (per 1000kg iodine prill product) Value

GWP 100 (kg CO2 eq.) 1.48E+04

AP (kg SO2 eq.) 2.53E+02

ODP (kg R11 eq.) 6.05E–06

POCP (kg C2H4 eq.) 1.20E+01

EP (kg PO4

3− eq.) 9.60E+00

ADP fossil (MJ) 2.44E+05

HTP (kg DCB eq.) 2.43E+03

Fig. 2 Contribution analysis

forthe main process steps of

iodine prill product produc-

tion (Nueva Victoria—NV and

Pedro de Valdivia—PV)

1139The International Journal of Life Cycle Assessment (2023) 28:1132–1141

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leaching process steps using economic-based and mass-

based allocation.

3.5 Electricity scenario analysis

Electricity was consistently identified as a hotspot for GWP,

AP, EP, POCP, ADP fossil, and HTP across the various pro-

cess steps. Therefore, an electricity scenarios analysis was con-

ducted. In the baseline model underlying the results presented

above, the Chilean electricity grid mix is used. The GaBi data-

set for the Chilean electricity grid mix 1–60kV (based on data

from 2008 to 2017) includes hard coal (36.9%), hydropower

(26.8%), natural gas (16.8%), biomass (7.6%), wind (4.4%),

photovoltaics (4.3%), fuel oil (2.4%), biogas (0.7%), and geo-

thermal (0.1%) (Sphera Solutions GmbH 2017). Despite the use

of renewables, it is mainly the relatively high share of hard coal

that leads to significant burdens for the grid mix in Chile. More

recent data on the total energy supply in Chile shows that in

2020, the share of wind and solar power had increased but coal

still makes up a significant share of the total supply (IEA 2022).

To assess the optimization potential for alternative elec-

tricity sources, electricity scenarios were conducted for

Fig. 3 Hotspots assessment GWP (% contribution) for iodine production at Pedro de Valdivia

Table 5 Cradle-to-gate total LCIA results per 1000kg of iodine prill product for GWP (CML 2001 indicators) for economic-based and mass-

based allocation

LCIA results (per 1000kg iodine prill product) Economic-based alloca-

tion

Mass-based allocation

GWP 100 (kg CO2 eq.) Total 1.48E+04 4.66E+03

Caliche ore mining 6.23E+03 1.09E+02

Heap leaching 3.29E+03 5.77E+01

1140 The International Journal of Life Cycle Assessment (2023) 28:1132–1141

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electricity from solar power, wind power, hydropower, and

natural gas by changing the electricity dataset from the Chil-

ean grid mix to the alternative source for 100% of electricity

usage in the foreground system (Fig.4 and Table5).

Figure4 displays the results for the GWP impact cate-

gory for the different electricity scenarios across the process

steps. In total, the Chilean grid mix has the highest overall

contribution (14,800kg CO2 eq./1000kg iodine prill), fol-

lowed by natural gas (12,300kg CO2 eq./1000kg iodine

prill), then hydropower (9900kg CO2 eq./1000kg iodine

prill), solar power (9270kg CO2 eq./1000kg iodine prill),

and wind power (9050kg CO2 eq./1000kg iodine prill). For

the mining operations in Nueva Victoria, there is no signifi-

cant reduction in GWP through using alternative electricity

sources because the electricity is not the main hotspot in

this process step. For all other process steps, a reduction in

GWP is shown through using alternative electricity sources.

The heap leaching process step shows the most significant

reduction since electricity is the core contributor for GWP

in this process step.

Table6 shows the optimization potential of using alterna-

tive electricity sources in a quantitative overview. Replacing

the Chilean grid mix with either wind power, solar power,

hydropower, or electricity from natural gas leads to improve-

ments in all studied impact categories with the exception of

the ODP, which is not affected by the choice of the electric-

ity source at all. The three different types of renewables lead

to very similar results, which clearly shows that switching to

renewable energy would reduce the environmental burden

independent of the specific source.

The reduction of the GWP by renewables is in the range of

33–39%, whereas natural gas would lead to a reduction of 17%.

When it comes to AP, POCP, and HTP, both the renewables

and natural gas lead to similar reductions (23–28% for AP and

POCP; 75–79% for HTP). For EP, the reduction potential with

natural gas is, with 40%, slightly lower than for renewables

(49–51%). For ADP fossil, the difference is obviously larger as

natural gas barely leads to a reduction at all (just 6%), whereas

the renewables lead to reductions between 26 and 27%.

Fig. 4 Electricity scenarios

for GWP (kg CO2 eq./1000kg

iodine prill product)

Table 6 Percent deviation from

Chilean electricity grid mix for

the total impact in electricity

scenarios

Impact category Solar power Wind power Hydropower Natural gas

GWP 100 − 37% − 39% − 33% − 17%

AP − 25% − 25% − 25% − 23%

EP − 49% − 51% − 51% − 40%

POCP − 28% − 28% − 28% − 24%

ODP 0% 0% 0% 0%

ADP fossil − 26% − 27% − 27% − 6%

HTP − 75% − 77% − 79% − 78%

1141The International Journal of Life Cycle Assessment (2023) 28:1132–1141

1 3

4 Conclusions

This study is the first LCA for iodine production from caliche

ore in Chile based on primary industry data. Cradle-to-gate

total LCIA results per 1000kg of iodine prill product include

a GWP100 of 1.48E+04kg CO2 eq., an AP of 2.53E+02kg

SO2 eq., a POCP of 1.20E+01kg C2H4 eq., an EP of

9.60E+00kg PO4

3− eq., and an ADP fossil of 2.44E+05MJ.

The main contributor across process steps and for most impact

categories is electricity consumption. Other hotspots include

diesel combustion, hydrogen peroxide, sulfur, sulfuric acid,

kerosene, and sodium hydroxide. The switch to renewable

sources was identified as the main improvement potential. A

scenario analysis with renewable electricity revealed a reduc-

tion potential of at least 25% for all impact categories except

for ODP. The GWP could be reduced by 33–38%.

Acknowledgements We would like to thank Verónica Gautier, Beatriz

Oelckers, Sebastian Franco, and others from SQM for their support in

the data collection and for providing technical information.

Funding Open Access funding enabled and organized by Projekt

DEAL. Sociedad Química y Minera de Chile (SQM) provided fund-

ing for this study.

Declarations

Competing interests The authors declare no competing interests.

Open Access This article is licensed under a Creative Commons Attri-

bution 4.0 International License, which permits use, sharing, adapta-

tion, distribution and reproduction in any medium or format, as long

as you give appropriate credit to the original author(s) and the source,

provide a link to the Creative Commons licence, and indicate if changes

were made. The images or other third party material in this article are

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the article’s Creative Commons licence and your intended use is not

permitted by statutory regulation or exceeds the permitted use, you will

need to obtain permission directly from the copyright holder. To view a

copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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