# Environmental impact assessments of scientific fieldwork as a path to sustainability: A case study from the MOSAiC expedition

Amy R Macfarlane, Madison M Smith, Radiance Calmer, Elise S Droste, Sandra Tippenhauer, Hélène Angot, Verena Mohaupt

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## To cite this version:

Amy R Macfarlane, Madison M Smith, Radiance Calmer, Elise S Droste, Sandra Tippenhauer, et al. Environmental impact assessments of scientific fieldwork as a path to sustainability: A case study from the MOSAiC expedition. Elementa: Science of the Anthropocene, 2025, 13 (1), pp.00035. 10.1525/elementa.2025.00035. [hal-05371434](https://hal.science/hal-05371434v1)

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https://hal.science/hal-05371434v1

Submitted on 18 Nov 2025

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Distributed under a Creative Commons Attribution 4.0 International License
## RESEARCH ARTICLE

# Environmental impact assessments of scientific fieldwork as a path to sustainability: A case study from the MOSAiC expedition

Amy R. Macfarlane<fnref n="1" />,<fnref n="2" />,<fnref n="3" />,*† ID, Madison M. Smith<fnref n="4" />,†, Radiance Calmer<fnref n="5" />,<fnref n="6" />,†, Elise S. Droste<fnref n="7" />,<fnref n="8" />, Sandra Tippenhauer<fnref n="7" />, Hélène Angot<fnref n="9" />, and Verena Mohaupt<fnref n="10" />,†

Polar environments are increasingly important to study as they are some of the regions most dramatically impacted by climate change. However, large field campaigns in these remote and sensitive regions may have impacts on both the local environment they aim to study and the global climate. Understanding the impact of such activities is necessary to weigh the costs and benefits and minimize negative impacts. This study provides the first example of a methodology to conduct an environmental impact assessment (EIA) for a polar research expedition at sea. We first summarize prior work on quantifying the environmental impact of polar science (including those stipulated by the Antarctic Treaty) and highlight the need for a similar process in the Arctic. The proposed methodology for measuring the impact of Arctic expeditions at sea includes a collection of data that should be gathered pre-, during, and post-expedition. Future seagoing expeditions can follow this framework to quantify their impact. The methodology is applied to quantify the impact of the scientific component of the 2019–2020 MOSAiC expedition to highlight the value of this process and potential blind spots. Our main takeaways include the need for (i) standardization of EIAs to allow comparison, (ii) better preparation of logistic parameters and opportunistic data collection in the lead-up to the expedition, (iii) life cycle assessments for on-ice instrument deployments, water, and waste disposal, (iv) revisiting the EIA upon expedition completion, and publishing lessons learnt. We provide a methodology for scientific EIAs that balances being easily implementable and sufficiently detailed, such that we can build up a database of assessments across a range of expeditions that can, in the future, be used to make recommendations on how to best reduce impacts on the polar environment.

**Keywords:** Environmental impact assessment, Arctic, Fieldwork, Sustainability, Responsible science, Pollution

## 1. Introduction

Conversations about the impact and sustainability of earth sciences have long lingered around the edges of meetings and the community. With the increasing urgency around climate change, these conversations have become louder and more central. Much of this has focused on the large relative impact of scientists' travel and participation in international meetings, for example, Klöwer et al. (2020), but another key issue is the impact of doing the

science itself. Each type of science has its own associated impact: analytical science may produce large amounts of single-use plastic waste (Alves et al., 2021; Farley and Nicolet, 2023; Jones et al., 2024), and the increasing computational costs of modeling efforts use significant amounts of energy (García-Martín et al., 2019; Mytton and Ashtine, 2022), while field observations typically require great logistical efforts and carbon emissions (Bastmeijer and Roura, 2008). Sustainability is a term that has been

<footnote n="1">¹WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland</footnote>

<footnote n="2">²Earth Observation, Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø, Norway</footnote>

<footnote n="3">³Geography and Environmental Sciences, Northumbria University, Newcastle upon Tyne, UK</footnote>

<footnote n="4">⁴Department of Applied Ocean Physics and Engineering, Woods Hole Oceanographic Institution, Woods Hole, MA, USA</footnote>

<footnote n="5">⁵Extreme Environments Research Laboratory, Ecole Polytechnique Fédérale de Lausanne, Sion, Switzerland</footnote>

<footnote n="6">⁶Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA</footnote>

<footnote n="7">⁷Physical Oceanography, Alfred Wegener Institute for Polar and Marine Research, Am Handelshafen, Bremerhaven, Germany</footnote>

<footnote n="8">⁸School of Environmental Sciences, University of East Anglia, Norwich, UK</footnote>

<footnote n="9">⁹Université Grenoble Alpes, CNRS, INRAE, IRD, Grenoble INP, IGE, Grenoble, France</footnote>

<footnote n="10">¹⁰Alfred Wegener Institute for Polar and Marine Research, Telegrafenberg, Potsdam, Germany</footnote>

<footnote>†These authors contributed equally to the work.</footnote>

<footnote>*Corresponding author:
Email: amyrmacfarlane@gmail.com</footnote>
commonly used across many different venues in recent years, yet the specific meaning of this word can imply a wide range of concepts. Here, we focus on the goal of environmentally responsible science, which aims to minimize the environmental footprint. Responsible science may set a higher bar than simply sustainable science. The latter implies ensuring the ability to continue scientific activities in the future, while the former implies constant minimization of negative environmental impact, regardless of the resilience of the system. While current scientific operations may be sustainable, meaning they do not limit the possibility for future work, there are still many opportunities to reduce the environmental impact and conduct responsible science. Environmentally responsible science also encompasses our social responsibility to minimize our footprint, both for the direct environment we work in and the planet in the larger sense.

As awareness of issues around responsible science has risen (Murray et al., 2023; van Soest, 2023; Moraru et al., 2024), the lack of information and data on environmental impact has become largely apparent (Smith et al., 2025). A recent editorial called on the scientific community to acknowledge the issue by explicitly articulating the environmental impacts of their work (Grogan, 2021). This is a remarkably small ask compared to the quantification required for many disciplines. There has recently been a call for funding agencies to be a part of this shift by requiring and supporting scientists in the evaluation of the potential impacts of their proposed work (Macfarlane et al., 2024). While complete impact reports are a key step in planning activities in many fields, examples for scientific expeditions are limited. One recent example was provided by the EUR-EC4A program, which included an environmental impact section in their overview paper (Stevens et al., 2021), in which they made a rough estimate of the campaign's carbon footprint. However, other information and data on the impact of scientific activities or even individual campaigns are next to impossible to find.

There are ongoing efforts to improve the energy efficiency of Polar Stations and minimize the environmental impact of research vessels. Multiple studies and initiatives are available to follow the growing projects. The feasibility of installing photovoltaic panels and wind turbines at Neumayer III in Antarctica has been studied along with the associated reduction of CO₂ emission (Bockelmann et al., 2022). Wind field measurements have been conducted in Princess Elizabeth Antarctica Research Station to study the performance of wind turbines in Antarctica. A wind map of the continent is an ongoing project to provide support information for more wind turbine development (Jelena, 2024). Villum Research Station in Northern Greenland is already equipped with solar panels (Henrik, 2017), more are under construction, and talks to deploy electrical snowmobiles instead of the traditional 2- or 4-stroke snowmobiles are being discussed. A new research vessel from the Tara Ocean Foundation was entirely custom-built to drift with the Arctic sea ice for scientific measurements while minimizing the environmental impact of the platform and its operations (Etienne Bourgois, 2025).

## 1.1. The need for environmental impact assessments in polar environments

Polar environments are arguably some of the most sensitive and highly impacted by climate change. Unfortunately, their remoteness requires necessarily large and impactful field campaigns (Bezanson et al., 2013). As a result, there is a compelling need to quantify and evaluate environmental impacts. All Arctic states have legislation requiring environmental impact assessment (EIA) for large-scale development projects. In 1997 and 2019, working groups of the Arctic Council produced guidelines for how these assessments should be applied in the Arctic and recommendations for best practices (Strategy AEP, 1997; Noble and Hanna, 2015; Karvinen and Rantakallio, 2019). However, conducting EIAs of scientific activities is required in only a few polar regions. This is in contrast to the Antarctic Treaty, which requires EIAs before scientific and other expeditions (Madrid-Protocol, 1991). As part of the larger environmental protocol that governs all operations in the Antarctic region, all parties must outline impacts in an EIA for review by a committee. If an activity has more than a minor or transitory impact, a full Comprehensive Environmental Evaluation (CEE) must be prepared, and adjustments to the activity may be required or halted if determined too negatively impactful. Similarly, any scientific project planned in the Canadian Arctic region of Nunavut must submit an environmental impact application to be reviewed by the Nunavut Impact Review Board. Applications must detail impacts, including waste management, the environmental impact of the activities, and proposed mitigation measures. All documents are publicly available online, and public hearings are organized to allow the impacted local communities to participate in the project review process (Ings, 2024).

Despite suggestions (Koivurova et al., 2016), there are currently no official requirements for quantifying the environmental impacts of scientific activities in the Arctic in place, nor review of activities by a committee. Instead, scientific activities in the field are strongly recommended to follow guidelines set by research committees and national councils. In the United States, the Interagency Arctic Research Policy Committee (IARPC), chaired by the National Science Foundation (NSF), provides guidelines for conducting research activities in the Arctic (IARPC, 2015). In Norway, the Nordic Council of Ministers created guidelines to conduct research without a trace in Greenland, Iceland, and Svalbard (Njåstad et al., 2005). In addition, the INTERACT guidelines on impact and carbon dioxide (CO₂) reduction (Frendrup et al., 2021; Holste et al., 2022) and the European Polar Board (EPB) synthesis report on the environmental impacts of research and logistics in the polar regions (Elshout et al., 2023) outline requirements for EIAs, such as this one. The principles emphasize respect for Indigenous knowledge and relationship with communities and Arctic Indigenous residents (Croal and Tetreault, 2012), as well as environmentally responsible behavior to minimize impacts to terrestrial and marine habitats. While some institutions or countries may implement processes for sustainability and evaluation, there is no holistic approach or transparency in applications, and many regions are excluded by these
piecemeal requirements (e.g., the Arctic Ocean; Takei, 2013). The 1991 Strategy for the Protection of the Arctic Environment highlighted the importance of EIA's, leading to the establishment of the Arctic Monitoring and Assessment Programme (AMAP). However, AMAP implements a work plan that monitors and assesses human and climate change impacts in the Arctic region by conducting research on larger timescales and regions. To our knowledge, it does not assess the impacts of individual expeditions or scientific activities.

While the community is still far from being able to implement best practices, one exemplary polar expedition has demonstrated what sustainable science can look like. The Climate Sentinels project describes itself as the first-ever carbon-neutral polar research expedition, motivated to demonstrate that there is a “clean-science” future and that scientists must lead the way in preserving the environments they work in. They accomplished this lofty goal by completing approximately 5-week expedition to gather samples across Svalbard completely on skis, with carbon offsets to account for necessary travel to and from the field campaign location. Of course, the scale of such an expedition is incomparable to large international interdisciplinary expeditions. The holistic approach of these large expeditions is essential for our understanding of regional and global systems and processes, and other approaches for evaluating and reducing impact will be necessary.

## 1.2. Using the MOSAiC expedition as a case study

Ship-based polar expeditions face substantial challenges to achieving similar reductions in environmental impact compared to land-based fieldwork, and the path to getting there is largely unclear due to nonexistent (and thus unenforced) best-practice protocols for expedition impact minimization and public reporting. A systematic, standardized evaluation of the impact of the expedition logistics, weighed against the impact of the science undertaken, is essential to start along this path. Such evaluation requires detailed information about scientific aims and logistics, which will be highly specific for each expedition. Here, we make the first steps toward creating a holistic approach to assessing environmental impacts by ship-based expedition by using the 2019/2020 MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition as a case study. The MOSAiC expedition was arguably the largest scientific and logistical endeavor ever completed in the Arctic (Shupe et al., 2020). The expedition included hundreds of scientists from approximately 20 different countries quantifying processes within 5 aspects of the system: atmosphere, ocean, sea ice, ecosystem, and biogeochemistry, organized along 5 core research teams (Nicolaus et al., 2022; Rabe et al., 2022; Shupe et al., 2022; Fong et al., 2024). Additionally, there was a cross-cutting modeling research team and a logistics team. Scientific activities were conducted on an ice floe, alongside which an icebreaker research vessel (R/V Polarstern) drifted through the Arctic pack ice. There were 5 rotations of the onboard participants, called “legs.” The combined duration of all 5 legs was an entire

year. The expedition required several icebreakers utilized as scientific platforms and logistical support, international travel for transporting science and crew, and a myriad of instruments sprinkled on ice floes throughout the system around the expedition's "Central Observatory."

By using the case-study approach and outlining a methodology, we build upon the objectives and best practices outlined in Senécal et al. (1999) and Morgan (2012). Our evaluation provides us with an opportunity to assess each aspect of the fieldwork, and we develop a structured methodology that can be adapted for future assessments and accommodate diverse fieldwork formats in the future. This assessment was done on a voluntary basis and we acknowledge that future effective implementation will require the engagement of a designated individual/committee. We identify and highlight our gaps in knowledge and areas of uncertainty.

In this assessment, we propose a list of key metrics and quantities that should be collected during the logistical planning of an oceanographic expedition, as well as additional metrics that should be obtained from participants and scientific project leaders during and after the expedition. **Figure 1** outlines the optimal timeline for an impact assessment beginning long before the expedition begins. Our assessment outlines the post-expedition stages and is structured as follows. Section 2 explains the methods of how each data type was collected and organized according to logistic parameters, surveys, and opportunistic data. We provide details on how environmental impacts were mitigated or avoided during the expedition. This section concludes with details of the method we use to calculate an expedition's impact index (i-index). In Section 3, we present results on the impact of the MOSAiC campaign concerning CO₂ emissions, aerosols and trace gases, waste production and disposal, microplastics, environmental interactions, invasive species, and noise and light pollution. We summarize the environmental impact of MOSAiC in Section 4 using the proposed i-index. Finally, we conclude with advice for future expeditions (Section 5) and final remarks (Section 6).

## 2. Data and methods

In this section, we describe our data collection and impact assessment evaluation for the MOSAiC expedition. Most of the EIA methodologies for polar regions introduced above focus on the impact on that sensitive region ("local" impacts); here, we aim to additionally assess the impact on the environment generally ("global" impacts).

To conduct such an assessment, we used 3 primary data collection methods, which are further described below:

1. Collection of parameters from expedition logistics, including from vessel or expedition operators. We call these "logistic parameters" in Section 2.1.

2. Surveys sent to scientific participants and project-based principal investigators (PIs) in Section 2.2.

3. Opportunistic data from scientific activities in Section 2.3.
<figure><img src="image_3.png" /><figcaption>**Figure 1. Environmental impact assessment stages and timeline.** The optimal timeline of tasks for a thorough impact assessment, highlighting the order of the 6 stages and how the assessment is a working process, and is constantly added to and reevaluated throughout. The right-hand side of the figure shows the 3 periods of an expedition (pre-expedition, during, and post-expedition). This manuscript covers the final 4 post-expedition stages.</figcaption></figure>

## 2.1. Logistic parameters

The logistic parameters were obtained upon request from the shipping companies and the Alfred Wegener Institute (AWI), who led the scientific activities on board. Parameters included fuel used, wastewater discharge, onboard general waste, lab/hazardous waste, interactions with the environment, and invasive species. Such parameters are typically recorded in logs as part of standard protocol. These records were requested and subsequently analyzed.

### 2.1.1. Carbon dioxide emissions (fuel)

Information on fuel use to determine associated CO₂ emissions included details on (i) primary research vessel (R/V Polarstern), (ii) support vessels, (iii) on-ice vehicles (skidoo and piston bullies), (iv) on-ice activities (generators on the ice powering scientific instruments and chain saws), and (v) helicopter flights.

Fuel used by R/V Polarstern was recorded per leg and was obtained from Report RFL through AWI logistics. Depending on the support vessel data source, the fuel used for support vessels was calculated using a combination of bunker fees (the expenses related to purchasing, storing, and supplying marine fuel) in euros per tonne (€/t), total volume of fuel in tonnes (t), and fuel usage per day (t/day), for example, when the vessel was traveling through ice and ice-breaking versus when the ship was traveling in ice-free waters.

Helicopter fuel use was calculated based on the number of hours flown per leg. The calculations for converting fuel type and volume to CO₂ emissions are provided in Section 3.1.2.

On-ice vehicle fuel (skidoo and piston bullies) volume and fuel type were recorded per leg, in addition to the number of hours the vehicles were used. Prior studies have shown reduction in local air quality with snow machine use, which increases air concentration of nitrogen oxides (NOₓ, NO), and carbon monoxide (CO) (Musselman and Korfmacher, 2007), as well as an increase in acidity and concentrations of sodium, ammonium, calcium, magnesium, fluoride, and sulfate within the snowpack (Ingersoll, 1999; Musselman and Korfmacher, 2007). Similarly, Helmig et al. (2020) showed that exhaust emissions from a remote Antarctic research station significantly altered the chemical composition of the surrounding snowpack, potentially compromising its natural chemical integrity and, by extension, its suitability for use in environmental or paleoclimate research. This local impact is reduced when there is high wind (Musselman and Korfmacher, 2007), which was often the case during the expedition. Although a detailed analysis of impacts on snow chemistry is beyond the scope of this assessment, the potential for on-site emissions to alter snowpack composition deserves careful attention and should be considered in future studies aiming to characterize background conditions in remote environments.

### 2.1.2. Waste (wastewater discharge)

Ship wastewater includes greywater, blackwater, and bilge water. Greywater is generated on board from sources including sinks, showers, and washing machines. Wastewater generated from toilets is referred to as blackwater. Bilge water contains leftover oil, lubricating oil, and condensation water
that has accumulated beneath the engine room. The total volume of wastewater generated on each leg of a typical expedition on the R/V Polarstern is too large to be stored until returning to port. It is therefore part of the vessel's protocol to discharge this wastewater into the ocean after it has been treated on board. Despite treatment, this wastewater will have different physical and chemical properties than the ambient seawater. Its impacts on the water column, as well as its impacts on seawater sampling activities, therefore need to be considered.

Bilge water was treated in an oil separator, from which oily solutions were collected in a special tank along with waste oil and then disposed of according to regulations in the next port. The remaining purified water, called boiler water, was pumped into the sea directly at the surface and had an unknown temperature.

Greywater and blackwater were filtered and treated onboard with UV radiation and enzymes. According to the standard protocol on R/V Polarstern, the treated wastewater is then released back into the ocean. Treated greywater and blackwater are named "standard wastewater" in this manuscript (also known as technical clean water). Given the slow drifting pace during MOSAiC, the protocol for standard wastewater discharge was altered to minimize the risk of contamination of seawater samples and measurements, as detailed below.

R/V Polarstern pumped surface seawater into the ship. A fraction of the total volume of seawater intake was desalinated, while the rest was stored (along with the salt removed from the first fraction) in the ballast chambers of the ship. Once used by onboard facilities, the desalinated water, now greywater or blackwater, is collected, cleaned with UV radiation and enzyme treatment, mixed with the seawater stored in the ballast chambers, and released back into the ocean. This ensured that the end product's salinity was similar to the surface seawater initially pumped into the ship. The temperature of the standard wastewater was also similar to the surface water, as the ballast chambers were below the ship's waterline. The standard wastewater was then discharged using a long hose at a depth of 150 m, which was considered a good compromise between logistic feasibility and avoiding contamination of samples. The hose was retracted after every discharge.

To avoid contamination of seawater samples collected by the conductivity-temperature-depth (CTD) rosette (a stainless steel structure mounted with sensors and sampling bottles, lowered into the seawater from the side of the ship), standard wastewater was only ever discharged after a CTD cast deployment or at least 24 h before a CTD cast deployment. Additionally, no seawater samples were collected at the depth where standard wastewater was discharged (i.e., 150 m). Moreover, to monitor the presence of standard wastewater, a tracer dye, rhodamine Water Tracer (WT, C₂₉H₂₉ClN₂Na₂O₅), was added in the form of pellets (Bright DyesTM Fluorescent Red FWT Dye) to the standard wastewater prior to discharge. A rhodamine sensor (Cyclops-6KTM, with a detection limit for rhodamine of 0.1 ppb) was mounted on the CTD rosette to detect the presence of the standard wastewater. Rhodamine WT is a red dye that was chosen for its

detectability and its low toxicity upon release in the natural environment (Kasnavia et al., 1999), including the marine environment (Jensen and Kristensen, 1989). Rhodamine WT in the Bright DyesTM product is classified as "not hazardous" according to the Hazard Communication Standard set by the Occupational Safety and Health Administration (OSHA) as part of the Code of Federal Regulations (CFR) in the United States (29 CFR 1910/1200), nor is it classified as environmentally hazardous. Rhodamine has been safely used as a tracer in multiple tracer studies, including groundwater, surface, ocean water, and even wastewater studies (see Richardson et al., 2004, and references therein). The impact of the use of rhodamine itself on marine life during MOSAiC is, therefore, considered to be negligible and essential for tracking standard wastewater discharge.

### 2.1.3. Waste (onboard)

The waste generated from R/V Polarstern for each leg of the expedition was divided into (i) ship's garbage, (ii) special waste, and (iii) scrap metal. Ship's garbage was divided into the following categories: A: Plastics, B: Food waste, C: Domestic waste, D: Cooking oil, E: Incinerator ashes, F: Operational wastes, G: Animal carcasses, H: Fishing gear, and I: E-waste. Garbage disposal sites varied depending on the expedition leg. Details on the disposal site are provided in Section 3.3, where the volume (m³) of garbage disposed of through burning, disposal into the sea, and disposal to a facility or ship is provided. Details of the volume of waste for Leg 5 are missing in our data records, and therefore, our analysis underestimates the total waste generated.

We do not have details or records of the garbage disposal for supply vessels. There is evidence that a proportion of the domestic waste generated onboard AK Tryoshnikov was disposed of at sea, the volume of which is unknown.

### 2.1.4. Waste (lab/hazardous)

Hazardous materials were carefully managed during the expedition to ensure there was no expected environmental impact, and hazardous laboratory waste was not included in the results. Throughout the expedition, protective safety measures and safety precautions for handling, storing, and transporting hazardous materials were followed for each chemical used on board, as required by national and international regulations. People using chemicals at sea either had training for their use at their home institutions or they were trained on board during leg transfers. One person in each team was in charge of the hazardous waste collection, reviewed how and when it needed to be done, and kept track of the generated waste. Waste containers and labeled bottles were used. Discharges to the environment were not permitted. Secondary containment during transfer and storage was also put in place. This organization was required by expedition planning. "Travel kits" for chemicals were available for excursions on the sea ice, ensuring no spills occurred, and no waste was created or left behind. A tight coordination between institutes within the ecosystem (ECO) and biogeochemistry (BGC) teams enabled the group to bring the appropriate amount of materials and
chemicals, avoiding duplicates and minimizing stocks on board the R/V Polarstern. Following the respective safety data sheet (SDS) for each chemical, chemical waste was stored in suitable containers on board until it was returned to land, where it was disposed of using chemical waste facilities and following SDS protocols.

Laboratory waste (e.g., single-use plastics) was project-specific, and in this evaluation, we did not identify general laboratory waste guidelines implemented for MOSAiC. As a result, the plastic used in laboratories depended on the laboratory setup of individual projects. In the future, we advise following the INTERACT guidebook (Arndal et al., 2024), which references Kilcoyne et al. (2022).

### 2.1.5. Environmental interactions

Interactions with the environment are inevitable when conducting fieldwork. This impact is highly dependent on the location and the duration of planned activities. Possible interactions with the environment during the MOSAiC expedition included wildlife disturbances, ice-breaking, water mixing, and anchoring to the sea ice floes. Breaking of ice, ocean mixing, and anchoring are assumed to be a minor local impact due to the scale of the expedition and are not able to be explicitly evaluated here.

Wildlife disturbances, especially interactions with polar bears on the ice, were recorded throughout the expedition and published by AWI. Details are given in Section 3.5, alongside references to publications that give details on the scientific sampling of certain species. To mitigate the interactions with wildlife, all members of the logistics team and most other participants took a specialized polar bear safety training course before the expedition. During the expedition, when work on the ice was ongoing, look-outs were permanently stationed on the ship's bridge, and those trained for polar bear safety were assigned lookout stations along the perimeter of scientific activities. Whenever a polar bear was spotted, everyone on the ice was instructed to return to the ship immediately. Only once there was sufficient space between the polar bear and the ship were scientists allowed to go back on the ice. In many instances, on-ice work resumed the next day.

### 2.1.6. Invasive species

To avoid introducing invasive species, only treated wood was brought on board and onto the ice to avoid the possible import of insects. Boiler water was not exchanged from outside the region, and standard wastewater was properly treated when it was discharged (see Section 2.1.2).

## 2.2. Surveys

Certain datasets needed for this EIA were collected after the completion of the expedition through a survey sent to (1) all participants, covering all individual aspects (Supplementary material C) and (2) project-based PIs (Supplementary material D).

The participant survey was structured into 4 parts: general information, CO₂ emissions, experiences, and perspectives. The PI survey was structured into 3 parts: general information, project impact, and perspectives. The PI survey aimed to assess the impact of each project to avoid

duplication in the data. Both surveys were tested and adjusted with a small group before being shared with the entire group from the expedition.

The participant questionnaire was sent via the global MOSAiC mailing list, which included 887 email addresses. The PI questionnaire was sent to the MOSAiC PI mail list, which included 107 email addresses. Ninety-six of 107 PI email addresses were on both lists. Reaching all members after the expedition was challenging. We had a total number of survey responses for the participant survey of 141, corresponding to an email response rate of 16%. However, it is important to note that many scientists had multiple email addresses on the lists, and the list also included many of the MOSAiC community who were not directly involved in the expedition itself. Thus, the response rate is likely closer to 50%, given the number of participants on each leg of the expedition, but the exact number is not known.

We obtained 32 responses from the PI survey, resulting in a response rate of 30%. Collecting the data in this way, following the completion of the expedition, is a significant limitation in our analysis and a source of underestimation of the expedition's environmental impact. We discuss this further in Section 5.

### 2.2.1. Carbon dioxide emissions (participant travel)

The survey sent to the participants collected data on travel modes and distances. The survey covers the period of workshops before the expedition and until September 2022 (i.e., approximately 2 years after the expedition). The survey included all the campaign leg rotations.

From the answers provided by the participants, the distance covered by each transportation mode was calculated and then converted into CO₂ emissions via 2 websites. MyClimate (myclimate Foundation, 2024) was used to calculate the CO₂ equivalent linked to air transportation. Based on user inputs of airport locations and cabin class, CO₂ equivalent is provided, considering direct and indirect CO₂ effects. The calculation considered flight distance, aircraft type, cargo load, cabin class, aircraft and infrastructure emissions related to the plane life cycle and airport operations, and other non-CO₂ emission effects on atmospheric radiative forcing. The calculations are based on the European standard DIN EN 16258, and other relevant information is available on the information web page (myclimate Foundation, 2024).

A second website was used for other transportation modes, including train, bus, car, and so on (Carbon Footprint Ltd, 2002). The calculation follows the UK government guidelines (UK Government, 2013) using the "Greenhouse gas reporting: conversion factors 2022." The conversion factors in the spreadsheet correspond to the ones used by the calculator website to obtain CO₂ equivalent for each transport mode.

### 2.2.2. Waste (scientific)

One of the most visible impacts of scientific research in remote locations such as MOSAiC is the equipment left behind, intentionally or unintentionally/accidental. Intentional equipment includes permanent scientific installations that may allow a longer time series than
permitted by manned installations. This typically includes the use of autonomous instrumentation to expand the observational range (spatially or temporally) beyond what is possible from the ship alone. Intentional equipment waste occurred primarily through profiling of the atmosphere (e.g., radiosondes), observations of changes in the ocean (e.g., SIMBA buoys, ocean temperature recorders), and measurements of the evolution of the ice pack (e.g., ice mass balance buoys, thermistor chains). Unintentional equipment waste is often the result of ice dynamics damaging equipment, insufficient time for recovery, limitations in helicopter use for instrument recovery (e.g., for heavier instruments which were not removable by participants), or accidents resulting in loss of gear.

The scientific waste data was collected through the participant and PI surveys. Specifically, PIs provided details of scientific instruments sent to and returned from the expedition. The participant survey provided information on accidental loss of items while in the field.

## 2.3. Opportunistic data

### 2.3.1. Aerosols and trace gases

During the MOSAiC expedition, aerosols and trace gases were measured in 3 different containers onboard R/V Polarstern. The objective of these measurements was to capture the background concentration of aerosols and trace gases. Therefore, any local emission was considered as pollution and flagged during data quality control (Beck et al., 2022a), as explained below. The local sources of contamination were fresh exhaust plumes from ships (see Figure 2), skidoo use for scientific activities on the ice (see Figure 3), helicopter flights for scientific surveys, and diesel generators used on the sea ice to power scientific instruments. The pollution events were characterized by enhanced aerosol or trace gas concentrations and strong variations in the signal amplitude (Beck et al., 2022a). During the MOSAiC expedition, the R/V Polarstern was embedded in the sea ice and could not reposition to face the wind to avoid local contamination of measurements. At first, a mechanical filter inlet purge blower was implemented for the Aerosol Observing System (AOS), which was activated with an elevated carbon monoxide mixing ratio (Boyer et al., 2023; see Supplementary material) to avoid contamination of the measurements. However, the purge blower did not work as well as expected (carbon monoxide not being a good tracer for local emissions; Beck et al., 2022a), and data still needed to be post-processed to remove local pollution. The University of Colorado (CU) container employed an alternative strategy, wherein measurements automatically ceased whenever the wind direction fell within a specified sector encompassing the ship's exhaust (Angot et al., 2022). Although this approach proved beneficial, it still had its imperfections (as discussed in Beck et al., 2022a), prompting the development of a pollution detection algorithm tailored for the post-processing of such datasets. Figure S1 in Boyer et al. (2023) shows the aerosol size distribution for particle diameters between 10 and 140 nm, including a high concentration of particles from the ship exhaust (diameter lower than 70 nm). It also shows that the final

<figure><img src="image_4.png" /></figure>

**Figure 2.** Example of a narrow exhaust plume from R/V Polarstern under stable atmospheric conditions. This image captures a specific instance where calm and stable meteorological conditions allowed the vessel's exhaust to disperse in a narrow plume downwind. Such behavior is characteristic of limited vertical mixing and low atmospheric turbulence. However, this is only one example—plume dispersion can vary considerably depending on weather conditions. Under stronger winds, convective mixing, or increased surface roughness, the plume may become more dispersed and reach the surface much closer to the ship. Lateral winds can also redirect the plume toward the surface near the vessel, potentially influencing local air quality measurements. Photo credit: Ivo Beck.

<figure><img src="image_5.png" /></figure>

**Figure 3.** Photo of potential sources of pollution on the ice. Skidoos were used for transport during scientific activities on the ice, and polyester flags were used for navigating, which were observed to generate microplastics. Photo credit: Delphin Ruché.

dataset was significantly reduced after the pollution detection algorithm was applied, which is further discussed in the Results (Section 3.2). The pollution detection algorithm can be conversely used as an indication of the fraction of time when the ship was having an impact on the expedition's local measurements.

Atmospheric processing of ship emissions has been studied at multiple locations and provided analysis beyond CO₂ and black carbon (BC) concentration. Results on total particle number concentration and their composition in SO₂, NOₓ, and organic matter provided a better
understanding of the chemical, physical, and optical
properties of the ship emissions and their impact of radi-
ative forcing (Lack et al., 2009). Cloud condensation nuclei
and the ability of ship emissions to affect cloud cover are
also pivotal research topics to improve the comprehension
of the Earth's energy balance (Benas et al., 2024). As the
Arctic atmosphere demonstrates major differences for the
stability of the boundary layer compared to lower lati-
tudes, and ships are using distinct engine regimes when
breaking the ice or idling close to an ice floe, a specific
study of the Polarstern emissions during MOSAiC is ongo-
ing and will complement the sparse literature already
available on icebreaker emissions (Aliabadi et al., 2016).

Importantly, the impact of these emissions likely
 extends beyond atmospheric observations to the snow
 and ice surface itself. The example shown in **Figure 2**
 illustrates a narrow and elevated ship plume under calm,
 stable meteorological conditions. However, as noted in the
caption, exhaust behavior can vary considerably: under
turbulent or convective conditions, or with lateral winds,
emissions may disperse more broadly and reach the sur-
face closer to the vessel. This variability underscores the
potential for localized surface contamination. It highlights
the importance of accounting for such effects in future
work to establish baseline or background conditions in
remote polar environments.

While this study does not attempt a quantitative assess-
ment of BC or other pollutants deposited locally, prior work
suggests such contamination is a valid concern. As discussed
in Section 3.1.2, vehicle emissions have been shown to
increase snowpack acidity and alter ionic composition (Inger-
soll, 1999; Musselman and Korfmacher, 2007). Similarly, Hel-
mig et al. (2020) documented how exhaust from a remote
Antarctic research station degraded snowpack chemical
integrity, raising concerns about its suitability for environ-
mental or paleoclimate analyses. Some of these challenges
and potential future directions are discussed in Section 5.

2.3.2. Microplastics

Plastic fragments known as microplastic or nanoplastic with
sizes ≤5 mm and ≤1 µm, respectively (Gigault et al., 2018),
are pervasive in the Arctic, even in areas with no apparent
human activity, such as the sea ice surface (Peeken et al.,
2018) and the deep seafloor (Walther and Bergmann, 2022).
Two recent studies by Bergmann et al. (2023) and Leis-
tenschneider et al. (2024) showed microplastics in high
quantities in Arctic ice algae communities growing under-
neath the sea ice and in surface water samples in Antarctica,
respectively. Identifying the source of these microplastics
comes with major challenges. The sources of microplastics
in the Arctic are widespread and highly contaminating. Pol-
lutants can be transported in the ice and water column from
where water enters the ocean, that is, from Siberian rivers,
and can get taken up when the sea ice is formed. We know
the MOSAiC expedition originated as landfast ice in the
Siberian Arctic (Krumpen et al., 2020) and may hold a pol-
lutant "memory." It has also been shown that vessels used
for tourism, scientific research, transportation of goods, and
fishing enter these sensitive environments and are a local
microplastic source (Leistenschneider et al., 2021). In

addition to the introduced microplastics, larger plastic
objects can erode as a result of sunlight, mechanical abra-
sion, biotic interaction, wave action, and temperature fluc-
tuations, producing microplastics and entering the
environment (Bergmann et al., 2022). An example of this
process is the flags installed for navigation on the sea ice
during MOSAiC. These were observed to erode and distrib-
ute microplastic fibers across the sea ice and snow surface
(see the frayed flags in **Figure 3**). A study measuring micro-
plastics in the snow cover in Antarctica (Aves et al., 2022)
highlighted the degradation of flags as a source of micro-
plastics in the area. A study in the western Arctic Ocean
showed that <1% of measured microplastics in sea ice could
originate from the overlying snow, while the remaining pro-
portion was a result of microplastics sequestered from sea-
water (Kim et al., 2021; Hamilton et al., 2022). These studies
highlight the importance of extensive sampling in the field
in proximity to the research vessel to better understand
microplastic sources.

The detailed analysis of microplastics found during the MOSAiC expedition requires extensive sampling of the atmosphere, snow, ice, and water column. This sampling was completed on the MOSAiC expedition; however, the analysis is ongoing and beyond the scope of this manuscript. Nonetheless, in Section 3.4, we summarize the possible sources of microplastics, the analysis and datasets known to take place on MOSAiC datasets, and associated scientific publications.

2.3.3. Noise and light pollution

Underwater noise has been observed to impact the behav-
ior of marine species, especially marine mammals that
depend on sound for basic functions (Prospathopoulos,
2025), but the long-term impacts are not fully understood
(Erbe and Farmer, 2000; Erbe et al., 2019). Helicopters and
snowmobiles create significant but episodic noise pollu-
tion (Mullet et al., 2017), primarily in the air, which may
similarly disrupt or harm birds and mammals (such as
polar bears and foxes). As no acoustic measurements were
conducted during the MOSAiC expedition, noise pollution
impacts are inferred.

Light pollution can impact ecosystems during the polar
night and seasonal transitions when the Arctic is other-
wise primarily dark. Prior work has suggested that anthro-
pogenic light pollution in marine protected areas can
impact marine species' behavior (Davies et al., 2016).
Working lights from ships in the Arctic polar night have
been found to impact the behavior of fish and zooplank-
ton down to 200 m depth within approximately 100 m of
the vessel (Berge et al., 2020). The floodlights used
throughout the polar night during MOSAiC are shown
in **Figure 4**. As no specific measurements of light pollu-
tion were made, we infer possible impacts based on
results from a MOSAiC-specific study in Section 3.7.

## 2.4. Excluded impacts

Impacts on water consumption and soil degradation are
not included in this assessment as they were not relevant
to this expedition.
<figure><img src="image_6.png" /><figcaption>**Figure 4.** R/V Polarstern's floodlights in operation during the polar night. Photo credit: Ivo Beck.</figcaption></figure>

**2.5. Calculating an expedition i-index**

The overall environmental impact of the expedition is summarized using a parameter list and impact scale adapted from Elshout et al. (2023). The parameter descriptions for the impact's geographical scale, duration, and spreadability are also adapted from Elshout et al. (2023). We added frequency as an additional parameter to our impact scale.

This provides a basis for comparisons with future expeditions. In Section 4.3, we quantify the magnitude of the environmental impact (i-index) based on the parameters listed below, each of which is assigned a value for the MOSAiC expedition.

* **Geographical scale:** The geographical scale of the impact is the “ability of an environmental impact to directly affect a specific area. For example, dumping waste is considered a local environmental impact as it initially affects the direct environment, whereas CO₂ emissions have a global environmental impact as they contribute to climate change” (Elshout et al., 2023).

1. Local environmental impacts (within a radius of less than 100 km)

2. Regional environmental impacts (within a radius of 100–1,000 km)

3. Global/continental environmental impacts (within a radius of more than 1,000 km)

* **Duration/persistence:** The duration or persistence relates to the degree and permanence of the impact, that is, “how long the impact lasts” (Elshout et al., 2023). For example, invasive species, loss of habitat, or damage to cultural heritage can establish a lasting presence. This also considers the concentration with respect to standards of acceptability that include applicable legislation and international guidance, its toxicity or potential for bioaccumulation, and its likely persistence in the environment.

1. Short: discrete impact without sequence

2. Repeated: sequenced, short impacts (up to 1 week)

3. Longer lasting: impacts that continue after research has been completed (including an estimation of how long the impact will remain) (more than 1 week and up to 1 month)

4. Permanent: irreversible impact that alters the environment permanently (periods longer than 1 month to permanent)

* **Spreadability:** The spreading of an environmental impact refers to the “ability of an impact to either multiply or spread throughout regions” (Elshout et al., 2023).

1. Non-spreading: environmental impact cannot expand and/or multiply, for example, wildlife disturbances

2. Semi-spreading: environmental impact has the potential to expand and/or multiply on a regional scale

3. Spreading impact: environmental impact expands and/or multiplies (usually exponentially), for example, invasive species and oil spills

* **Frequency:** The rate or number of times at which the disturbance/impact occurs over the entire expedition or in a given fieldwork campaign.

1. Once

2. Up to 50 times

3. More than 50 times or continuously

**3. Results**

Following the structure of EPB's synthesis report (Elshout et al., 2023), the results are summarized for CO₂ emissions (including BC), waste, microplastics, interactions with the environment (wildlife disturbance), invasive species, and noise and light pollution. The parameters and methods used in the analysis for each are summarized in **Table 1**.

**3.1. Carbon dioxide emissions**

CO₂ emissions during the cruise were a result of individual activities, primarily participant travel, as well as the overarching logistics of the expedition, including fuel used by ships and other vehicles.

**3.1.1. Participant travel**

The main individual contributions of CO₂ emissions originate from the transportation of the participants to associated planning workshops and meetings, and the expedition itself. Two hundred ninety-four participants sent details of their travel for the period in consideration. **Figure 5** summarizes the types of transport utilized by participants to participate in planning and analysis workshops and the expedition. For both, the mode of transportation that had the highest percentage was travel by airplane. In addition, 32% of participants traveled by train to attend workshops, almost matching the 36% that traveled by plane, with the longest train rides from central Europe to Tromso, Norway. The locations of the workshops and the ports of mobilization for the expedition have a large influence on the choice of travel modes, depending
<table><caption>**Table 1.** Details of the impact parameters used for this scientific environmental impact assessment of the MOSAiC expedition</caption><thead><tr><th>Results Section</th><th>Parameter</th><th>Data Collection Method</th><th>Quantification/Notes</th></tr></thead><tbody><tr><td rowspan="2">Carbon dioxide emissions</td><td>3.1.1. Participant travel</td><td>Survey</td><td>Distance and mode of transport</td></tr><tr><td>3.1.2. Fuel (skidoo, helicopter, aircraft campaigns, ships: PS and supporting vessels)</td><td>Logistic</td><td>Volume and fuel type, bunker fees, and fuel usage per day</td></tr><tr><td>Aerosols and trace gases</td><td>3.2. Ship exhaust (PS, support vessels)</td><td>Opportunistic</td><td>Bow particulate measurements</td></tr><tr><td rowspan="3">Waste</td><td>3.3.1. Scientific instrumentation left behind (intentional/unintentional)</td><td>Survey</td><td>Weight, material type, batteries, design (sinking or floating)</td></tr><tr><td>3.3.2. Wastewater discharge: standard wastewater (treated greywater and blackwater) and boiler water (treated bilge water) released</td><td>Logistic</td><td>Volume, composition, chemicals added</td></tr><tr><td>3.3.3. Generated onboard</td><td>Logistic</td><td>Volume, composition, disposal method</td></tr><tr><td rowspan="2">Microplastics</td><td>3.3.4. Lab/hazardous waste</td><td>Logistic</td><td>Specific for individual projects</td></tr><tr><td>3.4. Sediment traps, snow samples, ice cores</td><td>Opportunistic</td><td>Difficult to distinguish between local versus transported sources</td></tr><tr><td>Environmental interactions</td><td>3.5. (i) Wildlife disturbances, (ii) breaking of ice, (iii) mixing of water, (iv) anchoring</td><td>Logistic</td><td>Disturbance of the individual animals, limited data available for latter three</td></tr><tr><td>Invasive species</td><td>3.6. Steps and precautions to avoid introducing invasive species</td><td>Logistic</td><td>Unquantifiable</td></tr><tr><td>Noise and light pollution</td><td>3.7. Noise and light pollution from the ship</td><td>Opportunistic</td><td>Unquantifiable</td></tr></tbody></table>

<figure><img src="image_7.png" /><figcaption>**Figure 5.** Transportation modes for participant travel to legs and for workshops. Summary of the percentage of participants attending workshops (orange) and traveling between legs of the expedition (blue) utilizing each mode of transportation. Modes of transportation utilized include plane, train, bus, car, bike, ferry, and combinations thereof.</figcaption></figure>

on their availability. The answers collected by the survey on combined transportation modes also highlight the complexity of traveling when multiple modes often have

to be used to reach a destination. We note that the percentage in **Figure 5** for combined transportation might be underestimated as some participants answered the survey with their main mode of transport, and others provided details for each mode.

**Figure 6** shows the CO₂ emissions estimated for participant travel to workshops and campaign legs, both as a total number and scaled by participant number. The results emphasize a higher impact of traveling by plane compared to train in terms of CO₂ emissions. There are more journeys to attend workshops (208) compared to journeys to attend expedition legs (86). As a consequence, **Figure 6a** shows a higher CO₂ impact of workshops compared to the leg rotations. However, when CO₂ emissions are calculated per participant (**Figure 6b**), traveling to the ports to join the ships for the expedition had a higher CO₂ impact. This is likely because these destinations (i.e., Tromso, Norway) had fewer options for train transportation than places where the workshops were (i.e., Potsdam, Germany) and were often further from the home of participants. Beyond providing only numbers associated with CO₂ emissions from transport during the MOSAiC project, **Figures 5 and 6** highlight the complexity of travel modes for international expeditions, particularly when ships are involved and require participants to access departure ports of the vessels that are not necessarily accessible by lower impact transportation, such as train. The CO₂ equivalent provided in **Figure 6** might be
<figure><img src="image_8.png" /><figcaption>**Figure 6.** Carbon dioxide emissions associated with transportation modes used by participants. Tons of CO₂ emitted by transport of participants during the MOSAiC project for workshops (maroon; orange) and legs (blue). (a) Total number of CO₂ emissions. (b) CO₂ emissions per participant for attending workshops and the expedition.</figcaption></figure>

underestimated for plane transport, as a direct flight itiner-
ary was assumed in the calculation when survey responses
did not specify an airport connection.

**3.1.2. Fuel**

Fuel used by logistical activities of the expedition included
those used by (i) primary research vessel (R/V Polarstern), (ii)
support vessels, (iii) on-ice vehicles (skidoo and piston bullies),
(iv) on-ice activities (generators on the ice powering scientific
instruments and chain saws), and (v) helicopter journeys.

Fuel used by the R/V Polarstern was primarily Marine
Diesel/Distillate Oil (MDO DMA Sulfr < 0.1, Foretich et al.
(2021), of which a total of 6,836 metric tonnes (t) was used
(see calculation breakdown in Supplementary Table 1).

Supplementary Figure 1 provides a schematic outline
of the exchanges and support vessels used throughout the
expedition. We assume that all support vessels also used
Marine Diesel (MDO DMA Sulfr < 0.1) fuel. As fuel usage
was not reported, reported bunkerage fees are used for
conversions where the cost was reported to be 616$/t for
Low Sulfur Fuel (LSF < 0.1) in 2020 (Ramsey, 2020), equat-
ing to 550€/t (the average exchange rate USD/EUR for
October 2019 to October 2020 was 0.893; X-Rates:
Monthly average rates, 2024). The support vessels used
8,006 t of fuel, a detailed breakdown of the calculations
are provided in Supplementary Table 2.

The approximation of 3.15 t of CO₂ emitted per 1 t of marine diesel is used throughout these calculations of CO₂ emissions (Alfred Wegner Institute, 2019). Using this statistic, the 6,836 t of fuel used by R/V Polarstern emitted 21,534 t of CO₂, and the 8,006 t of fuel used by support vessels emitted 25,218 t of CO₂. These two values make up the majority of the expedition's CO₂ emissions, as seen in **Figure 7**.

Fuel for on-ice vehicles included fuel for skidoo and pis-
ton bullies. The breakdown of fuel used for each Leg is as
follows: 1,900 L (Leg 1), 3,800 L (Leg 2), Unknown (Leg 3), 50
L (Leg 4), 150 L (Leg 5). Leg 3 is likely to have a comparable
fuel use to Leg 2, we therefore approximate this by using the

same value and estimate that the total used by on-ice vehi-
cles was 9,700 L. We assume a 2-Stroke skidoo was used with
regular gasoline, which has a fuel economy of 13 miles per
gallon (5.53 km/L) following the methodology in Bishop
et al. (2006). **Table 2** in Bishop et al. (2006) shows, on
average, 1,250 g of carbon monoxide (CO) is emitted per
gallon (330 g/L) of fuel used and 1,150 g of unburned
hydrocarbons per gallon (304 g/L), assuming a fuel density
of 726 g/L and a carbon fraction of 0.86. These values are
given for skidoos running above 0°C (Bishop et al., 2006).
Dividing 330 gCO/L by 0.54 CO/CO₂ we obtain CO₂ values
of 611 gCO₂/L. This gives, in total, 5,926,700 g (6 t) CO₂, 3 t
carbon monoxide, and 3 t unburned hydrocarbons emitted
from skidoo use during the expedition.

The helicopter was used for 339.5 h in total (see the
breakdown in Supplementary Table 1). The Airbus helicop-
ter BK117C1 uses 295 L/h of fuel, which is equivalent to
0.75 t of CO₂ per hour using the Conklin & de Decker
Associates, Inc. (2024) calculator. This results in a total of
255 t of CO₂ emitted by helicopter use. The pilots onboard
informed us that fuel use heavily depends on flight speed.
As a result, this CO₂ emission value is an approximation.

We estimated that the total CO₂ emissions for MOSAiC
were equivalent to approximately 10,000 average per
capita carbon dioxide emissions worldwide in 2019. This
was calculated using the CO₂ emissions in metric tons per
capita of 4.78 in 2019 (Global Carbon Project, 2024), com-
pared to the MOSAiC emitted 47,864 t of CO₂.

**3.2. Aerosols and trace gases**

Atmospheric pollutants could originate locally from (1) the exhaust of the R/V Polarstern, (2) the ship exhaust of the support vessels and other equipment, and (3) the burning of waste aboard the vessels. Regarding this latter point, burning of waste is a common practice on ocean vessels in the Arctic (and elsewhere) due to limited storage space and as an alternative to disposal at sea. Incineration is subject to strict environmental regulation, but may still
<table><caption>Table 2. The assigned impact scale for each impact group</caption><thead><tr><th>Impact Group</th><th>Geographical<br>Scale Max: 3</th><th>Duration/Persis-<br>tence Max: 4</th><th>Spreadability<br>Max: 3</th><th>Frequency<br>Max: 3</th><th>Grades<br>Max: 13</th><th>Fraction</th></tr></thead><tbody><tr><td>CO<sub>2</sub> emissions</td><td>3</td><td>4</td><td>3</td><td>3</td><td><strong>13</strong></td><td>1</td></tr><tr><td>Aerosols and trace<br>gases</td><td>3</td><td>4</td><td>3</td><td>3</td><td><strong>13</strong></td><td>1</td></tr><tr><td>Waste</td><td>3</td><td>4</td><td>2</td><td>3</td><td><strong>12</strong></td><td>0.92</td></tr><tr><td>Microplastics</td><td>3</td><td>4</td><td>3</td><td>3</td><td><strong>13</strong></td><td>1</td></tr><tr><td>Environmental<br>interaction</td><td>1</td><td>1</td><td>1</td><td>2</td><td><strong>5</strong></td><td>0.38</td></tr><tr><td>Invasive species</td><td>0</td><td>0</td><td>0</td><td>0</td><td><strong>0</strong></td><td>0</td></tr><tr><td>Noise and light<br>pollution</td><td>1</td><td>3</td><td>1</td><td>3</td><td><strong>8</strong></td><td>0.62</td></tr><tr><td>Water consumption</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>N/A</td></tr><tr><td>Soil degradation</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>N/A</td></tr></tbody><tfoot><tr><td colspan="7" style="text-align: right;">i-index = 0.70</td></tr></tfoot></table>

Note: Details on each impact group and the scale can be seen in Section 2.5. The sum for each impact group row is provided in the column titled “Grade,” the maximum value is 13. The fraction of the impact grade relative to the maximum impact grade is given in the final column named “Fraction.” i-index is the mean fraction value for the relevant impact groups, see Section 4.2 for calculation details.

<figure><img src="image_9.png" /><figcaption>**Figure 7. The contribution CO₂ emissions from each fuel source.** CO₂ emissions associated with fuel used by the R/V Polarstern, support vessels, travel by participants to expedition legs and workshops, and fuel consumption by on-ice generators, on-ice vehicles, and helicopters. All values are given in tonnes, and are displayed alongside the percentage relative to the expedition's total CO₂ emissions.</figcaption></figure>

release some BC. This is regulated by the International Maritime Organization within the International Convention for the Prevention of Pollution from Ships (MARPOL) regulations 16.1–16.4 (MEPC, 1978). Dada et al. (2022) identified the ship pollution chemical spectrum (see their supplementary figure 16), and we can qualitatively assess the presence of anthropogenic exhaust based on data quality check protocols. Ultimately, 42% of the annual aerosol size distribution dataset remained after applying the pollution detection algorithm. For BC data, the pollution mask developed by Beck et al. (2022b) was applied

(Heutte et al., 2022), and 70% of the annual dataset was flagged as likely polluted by local sources, leaving 30% of the data suitable for scientific evaluation.

### 3.3. Waste

#### 3.3.1. Scientific

During the MOSAiC expedition, just over 1,500 kg of instrumentation was classified as intentionally left behind, and 750 kg of instrumentation was unintentionally left behind (Figure 8a). Most of these instruments (in both categories) contained lithium (recently shown to introduce recalcitrant contaminants into the environment; Guelfo et al., 2024) or no batteries at all (Figure 8b). Lead and alkaline batteries were relatively rare. A high fraction of these instruments included metal, styrofoam or foam, and rubber (Figure 8c). However, it is important to note that we cannot determine the fraction of these materials by weight.

#### 3.3.2. Wastewater discharge

A total of 19,602 m³ wastewater was discharged from R/V Polarstern during the MOSAiC expedition. Of this, 16,990 m³ was standard wastewater (i.e., treated greywater and blackwater) generated from life on board, while 2,612 m³ was boiler water produced by the engine (Figure 9). Throughout the expedition, the mean volume of standard wastewater released per discharge was 151 m³, although this was variable per leg (see Supplementary Table 3). Standard Wastewater was discharged on average once to twice per week (Figure 10).

Despite the intentions of tracking the standard wastewater discharge at depth during MOSAiC by adding rhodamine as a tracer, the rhodamine sensor was not mounted onto the CTD rosette until Leg 3. For CTD casts during Leg 3 and most casts during Leg 5, the rhodamine signal was below the
<figure><img src="image_10.png" /><figcaption>**Figure 8.** Summary of scientific instruments left in the Arctic during the MOSAiC expedition. (a) Total weight of instruments left behind, categorized by whether it was intentional or planned for instruments to be left behind. (b) Quantity of batteries left behind, categorized by type. (c) The number of instances of materials included in instruments left behind.</figcaption></figure>

<figure><img src="image_11.png" /><figcaption>**Figure 9.** Summary of wastewater discharged by the R/V Polarstern. Total volume of wastewater types discharged by the R/V Polarstern during MOSAiC, including standard wastewater (treated greywater and blackwater) and boiler water.</figcaption></figure>

sensor's detection limit of 0.1 ppb (Figures 10b, 11a, and 11c). The interpretation of these results has been complicated by the following issues. (1) The addition of rhodamine was not logged, and we are therefore unable to verify it for each standard wastewater release date. We suspect that rhodamine was either not added or not consistently added to the standard wastewater during Legs 3 and 5. (2) The rhodamine sensor was replaced on August 19, 2020, after the first sensor flooded during a cast deployment (marked by the dashed line in Figure 11b). The rhodamine profiles from the 2 previous CTD casts during transit on August 17 and 18, 2020, had clear rhodamine signals (max. 0.5 ppb; Figures 10b and 11c). No significant signal was detected in the profiles directly after the sensor replacement. These

issues make assessing the impact of the standard wastewater discharge on the marine environment, as well as the collected seawater samples, challenging. Given the uncertainties, it is still possible that rhodamine signals were sufficiently diluted during discharge and were not detected by the sensor. It is also possible that, as we did not measure a single rhodamine peak at 150 m, we successfully avoided sampling seawater affected by R/V Polarstern's standard wastewater discharge. The latter is particularly feasible as Polarstern and the sea ice's drift were, on average, 6 times faster than the mean ocean velocity (Schulz et al., 2024).

We have a high degree of certainty that rhodamine was added to the standard wastewater during most discharges on Leg 4. We present and discuss these rhodamine results here in light of lessons learned and how a protocol like this can be improved in the future.

Clear rhodamine signals were recorded during Leg 4 (max. 0.7 ppb; **Figure 10b**). Only a few profiles do not show any signal, that is, in the first and third week of July 2020 (seen in the lighter colors in **Figure 10b**). As we have no record of the consistency of the rhodamine addition to the standard wastewater discharge, we must here again highlight the uncertainty as to the cause. When rhodamine was detected in the water column, the peak of the signal was usually seen between 300 and 400 m depth. This is much deeper than expected, given that all standard wastewater was released at 150 m. The vertical extent of the signal is considered deep, especially as the peak signal is 100–200 m deeper than the core of relatively warm Atlantic Water. If the only source of rhodamine is indeed the dye in the wastewater discharge of MOSAiC, these results imply that the standard wastewater must have sunk considerably after release, which requires a large density difference between the wastewater and the surrounding water. In cold polar waters, density is strongly dependent on salinity. Although standard wastewater was relatively cold (i.e., sea surface temperature), its salinity–and therefore its density–was relatively low (i.e., sea surface salinity). The great depth of the rhodamine signal is therefore difficult to explain. Nevertheless, it suggests
<figure><img src="image_12.png" /><figcaption>**Figure 10.** Summary of wastewater (bilge water and standard wastewater) discharge volume and observations during the MOSAiC expedition. (a) Bar plot indicating the volume of wastewater discharge. The duration of discharge is indicated by the width of the bars. The time points when boiler water was released are indicated by the red triangle markers. The duration of each leg is indicated in the colored bars at the top. (b) Rhodamine profile data over the course of the MOSAiC expedition. Hashed areas indicate periods of time when rhodamine was either not measured or likely not added to the wastewater. Times when the vessel was in transit are also indicated in the plot. The cyan triangle markers at the top indicate times when conductivity–temperature–depth (CTD) casts were deployed, excluding the time before February 20, 2020, for which we have no rhodamine measurements. The vertical dashed line indicates the time of replacement of the rhodamine sensor on August 19, 2020.</figcaption></figure>

that the impact of standard wastewater discharge on surface water properties and organisms was likely negligible, but that standard wastewater could unexpectedly have reached deeper parts of the ocean water column than intended.

We did not find previous historical tracer studies with evidence for rhodamine release in the Arctic Ocean as an alternative explanation for the presence of rhodamine. It is suspicious that most profiles with signals were located in or near the Fram Strait, an important main entry of Atlantic Water and exit of Arctic Water. On one hand, rhodamine signals were detected on August 17 and 18 during CTD stations on R/V Polarstern's journey north to find a new ice floe, even though standard wastewater had not been discharged at depth for over 2 weeks (Figure 10a). This means that the detected rhodamine would have had to already be present in the water column. On the other hand, if

rhodamine was already present in the water column, we would have expected to see signals in all profiles while sampling at the new floe's location during Leg 5.

Despite the inconclusive data, this exercise has highlighted the challenges in tracking and assessing the impact of wastewater discharge during expeditions at sea.

### 3.3.3. Onboard

The garbage disposal methods for R/V Polarstern for each garbage type are displayed in Figure 12a. In total, 60 m³ of garbage was sent from R/V Polarstern to a facility or another ship to be disposed of, the rest was burnt or disposed of in the sea. We do not have details on the incinerators used. Figure 12b shows the breakdown per Leg. Legs 1 and 2 garbage was disposed of in Port via Kapitan Dranitsyn, Leg 3 via RV Maria S Merian, and Leg 4 via AK Tryoshnikov. Our dataset is
<figure><img src="image_13.png" /><figcaption>**Figure 11.** The detection of rhodamine added as a tracer to the standard wastewater. Individual rhodamine profiles during (a) Leg 3, (b) Leg 4, and (c) Leg 5. Markers are colored according to the potential temperature. The vertical red lines indicate the detection limit of the rhodamine sensor at 0.1 ppb. The horizontal dashed black lines indicate the depth at which the standard wastewater was released (approximately 150 m). The pink line in panel (b) shows the mean rhodamine signal over depth of all conductivity–temperature–depth profiles where the rhodamine signal was above detection limit.</figcaption></figure>

<figure><img src="image_14.png" /><figcaption>**Figure 12.** Garbage disposal on R/V Polarstern. (a) Garbage disposal methods (burned, disposed into the sea, sent to facility or ship) for the 7 categories of garbage. This data is given in garbage volume (m³). (b) The breakdown of the garbage volume sent to a facility or ship for Legs 1 to 5. This data is shown in 3 categories (i) ship's garbage, (ii) special waste, and (iii) scrap metal disposal in m³.</figcaption></figure>

missing information for Leg 5. Therefore, 60 m³ is likely to be an underestimation of the total garbage. The breakdown of this data is provided in Supplementary Table 4.

#### 3.3.4. Lab/hazardous

The lab and hazardous waste produced during the expe- dition were project-specific, and thus results on the type or volume of chemicals used are not presented here. All
chemical waste was collected in appropriate containers on board and processed in chemical waste facilities on land. Transport from the vessel to these waste facilities was organized by AWI staff, who similarly deal with hazardous chemical waste in their land-based facilities. We conclude that hazardous chemical waste had no environmental impact during the expedition.

### 3.4. Microplastics

Below we provide a non-exhaustive list of the possible sources of plastics and microplastics from the MOSAiC expedition:

* Ship paint and the ship exterior

* Clothing worn by the scientists in the field

* Deployed instruments on the sea ice

* Automotive parts (e.g., helicopter/skidoo)

* Synthetic flags used to mark the navigation routes (see Figure 3)

* Measuring vials and bags that were lost in the field

* Waste disposal: R/V Polarstern records show 2 m³ into the sea. Of this, 1 m³ were plastics, and 1 m³ were food waste (Figure 12a).

Analysis of snow samples collected during the MOSAiC expedition found the presence of microplastics, and 8 different types of plastic were identified (Hawly, 2021). Polyethylene (18%), polystyrene (13%), and polyvinyl alcohol (14%) were the most common plastic types. Resins as a cumulative class contributed to 34% of all microplastics found. During MOSAiC, ice cores were collected, and ocean sediment traps were deployed for microplastic studies. However, to our knowledge, the results are not yet published.

### 3.5. Environmental interactions

In total, there were 43 polar bear encounters, with no deterring action taken in about half of these (Mohaupt and König, 2025). Thirteen of these encounters included multiple polar bears. We did not record whether these were repeat encounters with the same polar bear. As detailed in the methods, most participants undertook training to avoid negative wildlife disturbances, specifically with polar bears. As a result, participants were aware of the necessary steps, and the expedition was a success in avoiding critical or deadly encounters with polar bears. Other wildlife disturbances, such as details of scientific fish sampling, can be found at European Commission et al. (2021). Other wildlife (seals, birds) were observed, but no negative or impactful interaction was recorded.

As we do not have data on the impact on wildlife, breaking of ice, mixing of seawater, or anchoring of R/V Polarstern to the ice floe, we are unable to assess their environmental impact.

### 3.6. Invasive species

There were no known issues with invasive species during the MOSAiC expedition, and standard preventative measures were taken wherever possible.

### 3.7. Noise and light pollution

Noise pollution, both in the air and underwater, from vessels (icebreakers), helicopters, and snowmobiles during the MOSAiC expedition may have resulted in localized impacts on marine species. As at least one engine was in use on the R/V Polarstern during the entirety of the expedition, there was likely persistent underwater noise pollution in the vicinity of the vessel. The highest underwater noise levels from icebreakers occur during backing and ramming, with levels up to 200 dB recorded on other vessels (Roth et al., 2013). This result suggests that higher levels of noise pollution likely occurred during transfers between legs, during repositioning along the floe, and when the ship had to maintain its position alongside the floe during sea ice divergence, compared to calm conditions when sea ice pressure maintained the ship's position along the floe. Noise levels were not measured directly at any point during the MOSAiC expedition. No active seismic or other major noise sources were used as part of science activities.

During MOSAiC, sustained artificial light pollution was the largest concern, and floodlights (see Figure 4) used to continuously illuminate areas adjacent to the vessel may have had a cumulative effect on local sea ice microbial communities. There is a high likelihood that the bright, consistent lights had an effect on nearby wildlife. Instantaneous use of artificial light from floodlights and headlamps in the vicinity of the vessel and central work area was largely unavoidable and required for safe on-ice operations but is suspected of having had low/no impact at the scale of measurements. Additional “dark sites” outside of this region (>1 km from the ship; Fong et al., 2024) were set up where light pollution was not detectable, and only red lights were used for scientific activities. This approach limited the light pollution impacts on ecosystems for study. We do not have the means to assess the impact of light pollution in this assessment. However, preliminary scientific results show that primary productivity was initiated by very low light levels (Ludvigsen et al., 2018), including the full moon (Hoppe et al., 2024), suggesting that light pollution could have lasting regional impacts on ecosystem productivity. The MOSAiC ecosystem overview paper stated that there are minimal effects of light pollution on biogeochemical and many biological parameters, as the floe drifted in different directions and speeds compared to the water column below (Fong et al., 2024).

## 4. MOSAiC's environmental impact

### 4.1. Summary

* Carbon dioxide emissions:

- Participant travel: Leg travel = 505 t (1.01 t/participant × 500 participants). Workshop travel = 345 t (0.69 t/participant × 500 participants)

- R/V Polarstern: 21,534 t

- Support vessels: 25,218 t

- Helicopters: 255 t

- On-ice vehicles: 6 t
Total CO₂ emissions = 47,864 t of CO₂.

* Aerosols and trace gases: 70% of the annual dataset was flagged as likely polluted by local sources.

* Waste

- Scientific: 1,500 kg intentional + 750 kg unintentional + 1,630 batteries (lithium iron, lead, and alkaline)

- Wastewater: 16,990 m³ standard wastewater + 2,612 m³ boiler water

- Onboard from R/V Polarstern: 60 m³ was disposed of by another ship or an onshore facility. 1 m³ of plastics and 1 m³ of food waste were disposed of into the sea. 256 m³ was burned onboard.

- Onboard waste from support vessels: unknown. There is evidence that an unknown volume of garbage generated onboard AK Tryoshnikov was disposed of at sea.

- Lab and hazardous: Limited data available as this was project-specific.

* Microplastics: currently unknown (see references to publications where analysis is underway)

* Environmental interactions:

- Wildlife disturbances: 43 polar bear encounters, with no deterring actions taken in approximately half of these. Scientific fish sampling took place on board.

- Breaking of ice/mixing of water/anchoring: Unknown. More data needed.

* Invasive species = Negligible

* Noise and light pollution = Local impacts recorded

* Water consumption/soil and ice degradation = Not applicable

It is useful to put the total marine diesel consumption for the expedition (and resupply vessels) in the context of the total Arctic marine traffic. Based on a report from the Arctic Council (PAME-Arctic Shipping Status Report 2) in 2019, 1,725 ships entered the Arctic region defined by the International Code for Ships Operating in Polar Waters. These ships have consumed 917,704 m³ of fuel (equivalent to 890,445 tons of marine diesel). Therefore, the MOSAiC total consumption over 1 year represents 5% of the annual Arctic marine traffic consumption.

## 4.2. Introducing the i-index

To compare to future expedition and fieldwork EIAs, we introduce a grading system based on the EPB synthesis report (Elshout et al., 2023). In Table 2, we include the ranking of geographical scale, duration/persistence, spreadability, and frequency of each impact. The scales assigned are introduced here for the first time in this manuscript and were chosen in the context of the ranges and guidance provided in the EPB synthesis report (Elshout et al., 2023). We direct the reader to this report to understand the assigned grades.

In Table 2, an i-index is introduced as a tool to compare with other assessments conducted in the future. We present the MOSAiC i-index as 0.70. This is calculated using the equation $i-index = \sum \frac{Fraction}{n}$, where n is the number of relevant impact groups. In this study, we have 7 relevant impact groups. We introduce this scale as a conversation starter on this topic, and we hope that more expeditions are able to calculate their i-index for future comparisons and analysis.

We further propose calculating the ratio between the i-index and an output-index (o-index); a measure of the scientific output (o-index) could be a tool to assess the use of datasets and the value of going on international expeditions. These international expeditions are predicted to have a large scientific output (i.e., large o-index) for the associated i-index. Calculating the o-index is beyond the scope of this assessment, and we do not pursue this direction in this EIA. This new o-index concept relies on testing for multiple expeditions, not just MOSAiC, to make a comparison. Additionally, similarly to a scientist's h-index, an "early career" expedition has a relatively low o-index, which develops in time upon more paper publications. As a result, the initial o-index is not representative in the first few years upon completion of the expedition.

## 4.3. Revisiting the predicted environmental impact

Before the MOSAiC expedition began, AWI conducted an initial EIA (Alfred Wegner Institute, 2019). We want to highlight the benefit of conducting EIAs prior to departure as well as upon returning. The initial assessment is a valuable reference for understanding the predicted versus the true environmental impact. The 6,836 t of Marine Diesel was used for R/V Polarstern in comparison to the predicted 7,137 t. The reduction is likely due to the COVID pandemic, which reduced the number of scientific participant exchanges and the supply vessel use, and the total number of legs was reduced from 6 to 5. The total CO₂ emissions and fuel consumption were underestimated as the support vessels were not considered in the initial EIA. We calculated that they contributed to 53% of the total CO₂ emissions. Additional support vehicles were needed with a resupply of fuel (Dranitsyn) as the ice caused longer travel time between Legs 2 and 3, and the COVID pandemic resulted in R/V Polarstern temporarily leaving the floe, increasing total emissions. Finally, the sustainable factsheet stated, "Polarstern is carried by the natural ice drift, pushed on by the wind. This does not cost anything and is CO₂ emission-free." As a result of the ice dynamics onboard, this was almost impossible to achieve, and the engines were used to keep R/V Polarstern in place alongside the ice floe.

## 5. Lessons learnt and advice for future impact assessments

All the information used in this study was collected after the successful completion of the MOSAiC expedition. Gathering all data required for an impact assessment promptly while people involved were potentially moving on to other projects and positions was a major challenge and resulted in delays to the assessment. We recommend
that future expeditions collect data prior to and during the campaign and consider making a mandatory response at disembarkation. We encountered various other challenges during different parts of the assessment, for which we suggest solutions below.

**5.1. Collecting global parameter data**

We recommend (1) organizing an agreement during the expedition planning stage on sharing global parameters between ship logistics, the expedition planning board, and the impact assessment team, as they might have to be provided by different companies or institutes. Organizing this upon completion of the expedition caused significant delays. (2) Regular communication and feedback between scientists and crew regarding actions to track impact, for example, adding tracers to standard wastewater discharge and keeping a continuous log of lost/deployed equipment during the expedition.

**5.2. Data collected from surveys**

Interpreting responses to some survey questions, particularly in regard to travel methods given the typical combination of numerous means of travel, was difficult. Therefore, we recommend updating this question by allowing for sub-travels, which allows one to easily provide the distance traveled with each mode.

**5.3. Light pollution**

We recommend incorporating noise (acoustic) and light sensors above and below the ice or water on future expeditions to quantify noise and light pollution. Light pollution is particularly relevant during polar night. While safety considerations limit the degree to which light may be reduced in future fieldwork of a similar nature, additional measures may be taken to limit unnecessary light pollution. This can include shutting blinds on the ship during polar night and ensuring lights are shut off when not in use. During MOSAiC, we found it important to emphasize required behavioral changes with colleagues working in light-sensitive areas on sampling activities. The color or wavelengths of light can also be altered for periods when white light is unnecessary. We equipped all team members with high-power, rechargeable, battery-operated, red and white light adjustable headlamps whenever possible. This proved critical to providing the ability to switch between white and red light for different tasks while working for long periods at low temperatures. Many headlamp systems did not function well in those conditions, so selecting the appropriate equipment, especially for extreme winter conditions, is essential.

**5.4. Black carbon**

BC emitted by local sources, such as R/V Polarstern's exhaust and scientific activities on the ice (skidoo, helicopter, and generator use), deposits relatively quickly to snow and ice surfaces, where it accumulates (e.g., Helmig et al., 2020; Kang et al., 2020). BC sources and distribution from MOSAiC expedition activities could be better understood by assessing the hundreds of samples collected for BC with respect to wind directions, ice drift, ice rotation, and ship

orientation. BC can also be redistributed throughout the region through high wind velocities, making it difficult to separate BC produced from the expedition and BC generated inland and transported to the Arctic. Future work (1) comparing the amount of BC in the local snow samples compared to clean snow samples taken a few kilometers from the ship or (2) through a transect starting from the research vessel would be informative to understand the impact of a ship on BC deposits in the snow.

**5.5. Wastewater**

Several lessons can be learned from the rhodamine studies during MOSAiC with regard to protocols for tracking wastewater from vessels in the future: (1) Rhodamine additions to standard wastewater need to be logged, including the amount added per volume, date/time, and any deviations from the protocol. (2) Intentions and scientific understanding behind these protocols need to be clear to all those involved. In the future, the responsibility of adding a tracer to wastewater ideally needs to remain with the scientific party on board. (3) Tracer experiments are only effective when the environmental background signal is low enough. If possible, the background rhodamine levels of a region should be tested by measuring rhodamine in the water column prior to any tracer-containing standard wastewater discharge.

**5.6. Microplastics**

Our findings highlight the need for analysis to understand how much microplastic an expedition of such a size introduces into the Arctic environment. During the MOSAiC expedition, participants observed the degradation of synthetic polyester flags on the ice, which were placed for navigation purposes. In an attempt to minimize microplastic pollution, participants replaced these flags with painted bamboo poles, yet found that this paint also degraded and chipped away after some time. More work is needed to understand the best materials for use in cold, windy environments which are not plastic-based and do not erode over time.

**5.7. Interactions with the environment**

More quantitative analysis is needed into the impact of an icebreaker traveling through and breaking the ice, including the influence of the local mixing of the water column and anchoring to the ice (both of which are expected to be relatively minimal).

**5.8. Expedition planning**

The potential environmental impact needs to be taken into consideration during expedition planning stages, well before the expedition takes place. We suggest that individual- or project-level impact assessments and initiatives that work on reducing the environmental impact of scientific activities need to take higher priority at the funding stage, as in Macfarlane et al. (2024). We suggest that institutes introduce an internal Arctic-wide mandatory collection of data in the expedition reporting procedure, similar to the requirements to conduct scientific research in Antarctica. As no governing body enforces this,
scientific institutes could provide guidelines to their employees conducting work in remote, sensitive regions. We outline possible questions below that can be considered during the planning phase of an expedition:

* Are there institutional or national guidelines in place for the EIA?

* What information/parameters are needed for a complete EIA?

* What information is not available for a complete EIA? Is it possible to conduct additional tests in the field to provide additional information/data?

* What should be documented before and what can be recorded during the expedition?

* How could the data be collected most efficiently? (e.g., surveys, participation forms, etc.)

* How can we improve collaboration and knowledge transfer between logistics, scientists, ship coordination, and ship crew?

* Who will be responsible for compiling the data and doing the assessment?

## 5.9. Broader use of the i-index

It should be noted that the centers, institutes, and departments that operate polar research stations and vessels have been actively involved in the management of waste, finding solutions to reduce CO₂ emissions, and respecting environmental regulations (French Polar Institute, Princess Elizabeth Antarctica Research Station, etc.). However, more interactions between the logistical side of expeditions and scientists could speed up the environmental transition. Therefore, the method outlined above for calculating the i-index could be applied beyond sea-based expeditions and could be beneficial for research stations on land. The methodology outlined in the article provides a comprehensive framework that can guide EIA protocols. For example, (1) using similar methods to collect data on logistics, participant activities, and opportunistic data from scientific activities. (2) Following the structured approach described above to assess various environmental impacts, including CO₂ emissions, waste production, and interactions with the environment. (3) Implementation of the mitigation measures suggested to minimize negative impacts, such as proper waste management and reduction of light and noise pollution. This approach not only helps to comply with environmental regulations, but also promotes best practices in scientific research.

## 6. Concluding remarks

EIAs are extremely specific to the type of fieldwork conducted. We hope that the methodology outlined in this report can be adapted for future EIAs in other regions. This work aims to set a precedent, develop our understanding of the possible environmental impacts of fieldwork, and outline future steps to reduce this. Future expeditions may build upon the work we have outlined here to work toward quantifying and minimizing the environmental impact of scientific activities in remote regions of the world.

While the impacts of undertaking scientific activities to understand our environment are overwhelmed by impacts from industry and other activities, it is a worthwhile effort for scientists to understand their impact in order to aim to reduce it where possible. Collecting such datasets is necessary for data-driven decisions on how to reduce impact, for example, for consideration in future polar research vessel design. Regardless of efforts to reduce negative impact, polar research expeditions such as MOSAiC will still have a notable environmental impact. We asked all participants of MOSAiC, “What are the biggest barriers to developing and implementing more sustainable methods for scientific research?” to understand the perceived barriers to reducing impacts. The responses from 145 participants are summarized in **Figure 13**, where we show both the highest ranked barriers and barriers weighted by ranking. Technological advances and dedicated funding were ranked as the highest barriers by the highest number of respondents (26 each). The weighted rankings show more similar barriers from funding, technological advances, time, and lack of information to make informed choices (in descending order), suggesting that numerous factors contribute to the current situation. Lack of motivation/personal interest was rated lowest, suggesting that the environmental impact of scientific research can be reduced if other barriers are addressed.

Upon completing this EIA, we encourage other expeditions to publish their EIAs with open access so the broader scientific community can learn from past experiences and work toward creating best-practice approaches for expedition planning and execution that minimize our environmental impacts.

## Data accessibility statement

* Logistic parameters:

Fuel and waste/garbage disposal information from R/V Polarstern obtained from Report RFL is available in Supplementary Table 1.

A breakdown of the wastewater released during the expedition is published in Supplementary Table 3.

Details on wildlife interactions can be found in Mohaupt and König (2025).

* Surveys:

The surveys are provided in the manuscript's Supplementary material C and D. To protect anonymity, we do not publish the survey data.

* Opportunistic data:

Aerosols and trace gases were measured in 3 different containers onboard R/V Polarstern: the so-called “Swiss container” run by Ecole Polytechnique Fédérale de Lausanne, Switzerland, and the University of Helsinki, Finland (Angot et al., 2022; Heutte et al., 2023), the Aerosol Observing System (AOS) operated by the U.S. Department of Energy Atmospheric Radiation Measurements (ARM) user facility (Shupe et al., 2022; Boyer et al., 2023), and the so-called “CU container” run by the University of Colorado Boulder (Angot et al., 2022). Aerosols and trace gases datasets are publicly available, as detailed in Heutte
<figure><img src="image_15.png" /><figcaption>**Figure 13.** Summary of answers to the question “What are the biggest barriers you perceive to developing and implementing more sustainable methods for your scientific research?” by MOSAiC participants. The panel on the left shows the frequencies of each answer ranked first by respondents, and the panel on the right shows the weighted value of each answer ranked by respondents, where the lowest ranked answer would be given a value of one.</figcaption></figure>

et al. (2023) and Angot et al. (2022). The pollution detection algorithm for local pollution identification, described in Beck et al. (2022b), is also publicly available (Ivo et al., 2021).

**Supplemental files**

The supplemental files for this article can be found as follows:

Supplementary_EIA.PDF

**Acknowledgments**

Data used in this manuscript were produced as part of the international Multidisciplinary drifting Observatory for

the Study of the Arctic Climate (MOSAiC) with the tag MOSAiC20192020 and the Project_ID: AWI_PS122_00 (Knust, 2017; Nixdorf et al., 2021). We would like to thank the MOSAiC project board and ship coordination team for their support of the project, as this analysis would not have been possible without their endorsement. We would like to acknowledge everyone onboard the R/V Polarstern Leg 4 (PS122_4) who contributed to the open-minded discussions aimed at reducing the environmental impact of scientific fieldwork. In particular, the role that Delphin Ruché took in organizing these discussions. We acknowledge and thank Linda Thielke for helping with the preparation and conception of the study and sending the survey. Pjotr Elshout from the European Polar Board for
guidance and invaluable discussions on the structure of this assessment. We also thank Allison Fong for providing input on decisions made in the expedition planning stages regarding adding a rhodamine tracer for standard wastewater tracking. We thank Celia Gelfman and Alessandra D'Angelo for providing insight on lab and hazardous material disposal during the expedition.

## Funding

We want to thank the ETH-Zurich CO₂-Fund, which was used to publish this manuscript. ARM was funded by the Swiss Polar Institute grant number INT-2023-001, the Antarctic Science Foundation as part of the MERTZ fellowship, and acknowledges support from the Swiss National Science Foundation (SNSF) Swiss-Mobility project number P500PN_217845, the Swiss Polar Institute (SPI reference DIRCR-2018-003) Funder ID: http://dx.doi.org/10.13039/501100015594, and the WSL Institute for Snow and Avallanche Research SLF. WSL_201812N1678. Funder ID: http://dx.doi.org/10.13039/501100015742. MMS was funded by the U.S. National Science Foundation (NSF) OPP 2138787. ESD was supported by NERC through the EnvEast Doctoral Training Partnership (NE/L002582/1), as well as NERC and the Department for Business, Energy & Industrial Strategy (BEIS) through the U.K. Arctic Office. RC was funded by the U.S. National Science Foundation (NSF) OPP 1805569.

## Competing interests

The authors of this manuscript were on board during the MOSAiC expedition, conducting scientific activities, but declare they have no competing interests. HA serves as an Associate Editor of the Elementa Atmospheric Sciences Domain but was not involved in the review process of this manuscript.

## Author contributions

Contributed to conception and design: ARM, MMS, RC, VM.

Contributed to the acquisition of data: All authors.

Contributed to the analysis of data: All authors.

Drafted and/or revised article: All authors.

Approved the submitted version for publication: All authors.

## References

* **Alfred Wegner Institute.** 2019. MOSAiC: Facts on sustainability. Available at https://www.mosaic-expedition.org/wp-content/uploads/2019/09/mosaic-factsheet-facts-on-sustainability.pdf. Accessed July 17, 2024.

* **Aliabadi, AA, Thomas, JL, Herber, AB, Staebler, RM, Leatch, WR, Schulz, H, Law, KS, Marelle, L, Burkart, J, Willis, MD, Bozem, H, Hoor, PM, Köllner, F, Schneider, J, Levasseur, M, Abbatt, JPD.** 2016. Ship emissions measurement in the Arctic by plume intercepts of the Canadian Coast Guard icebreaker Amundsen from the Polar 6 aircraft platform. *Atmospheric Chemistry and Physics* **16**(12): 7899–7916. DOI: https://doi.org/10.5194/acp-16-7899-2016.

* **Alves, J, Sargison, FA, Stawarz, H, Fox, WB, Huete, SG, Hassan, A, McTeir, B, Pickering, AC.** 2021. A case report: Insights into reducing plastic waste in a microbiology laboratory. *Access Microbiology* **3**(3): 000173. DOI: https://doi.org/10.1099/acmi.0.000173.

* **Angot, H, Blomquist, B, Howard, D, Archer, S, Bariteau, L, Beck, I, Boyer, M, Crotwell, M, Helmig, D, Hueber, J, Jacobi, H-W, Jokinen, T, Kulmala, M, Lan, X, Laurila, T, Madronich, M, Neff, D, Petäjä, T, Posman, K, Quéléver, L, Shupe, MD, Vimont, I, Schmale, J.** 2022. Year-round trace gas measurements in the central Arctic during the MOSAiC expedition. *Scientific Data* **9**(1): 723. DOI: https://doi.org/10.1038/s41597-022-01769-6.

* **Arctic Environment Protection Strategy (Strategy AEP).** 1997. Guidelines for environmental impact assessment (EIA) in the Arctic. Finland: Sustainable Development and Utilisation, Finnish Ministry of the Environment. Available at https://ceq.doe.gov/docs/get-involved/eiaguide.pdf. Accessed July 27, 2025.

* **Arndal, MF, Klutsch, CFC, Topp-Jørgensen, E, Rasch, M.** 2024. INTERACT reducing plastic consumption and pollution at Arctic Research Stations. Sweden: INTERACT. DOI: https://doi.org/10.5281/zenodo.10598401.

* **Aves, AR, Revell, LE, Gaw, S, Ruffell, H, Schuddeboom, A, Wotherspoon, NE, LaRue, M, McDonald, AJ.** 2022. First evidence of microplastics in Antarctic snow. *The Cryosphere* **16**(6): 2127–2145. DOI: https://doi.org/10.5194/tc-16-2127-2022.

* **Bastmeijer, K, Roura, R.** 2008. Environmental impact assessment in Antarctica, in Bastmeijer, K, Koivurova, T eds., *Theory and practice of transboundary environmental impact assessment*. The Netherlands: Brill Nijhoff: 175–219. DOI: https://doi.org/10.1163/ej.9789004164796.i-400.2.

* **Beck, I, Angot, H, Baccarini, A, Dada, L, Quéléver, L, Jokinen, T, Laurila, T, Lampimäki, M, Bukowiecki, N, Boyer, M, Gong, X, Gysel-Beer, M, Petäjä, T, Wang, J, Schmale, J.** 2022a. Automated identification of local contamination in remote atmospheric composition time series. *Atmospheric Measurement Techniques* **15**(14): 4195–4224. DOI: https://doi.org/10.5194/amt-15-4195-2022.

* **Beck, I, Quéléver, L, Laurila, T, Jokinen, T, Schmale, J.** 2022b. Continuous corrected particle number concentration data in 10 sec resolution, measured in the Swiss aerosol container during MOSAiC 2019/2020. PANGAEA. DOI: https://doi.org/10.1594/pangaea.941886.

* **Benas, N, Meirink, JF, Roebeling, R, Stengel, M.** 2025. Analysis of ship emission effects on clouds over the southeastern Atlantic using geostationary satellite observations. *Atmospheric Chemistry and Physics* **25**: 6957–6973. DOI: https://doi.org/10.5194/acp-25-6957-2025.
**Berge, J, Geoffroy, M, Daase, M, Cottier, F, Priou, P, Cohen, JH, Johnsen, G, McKee, D, Kostakis, I, Renaud, PE, Vogedes, D, Anderson, P, Last, KS, Gauthier, S.** 2020. Artificial light during the polar night disrupts Arctic fish and zooplankton behaviour down to 200 m depth. *Communications Biology* 3(1): 102. DOI: https://doi.org/10.1038/s42003-020-0807-6.

**Bergmann, M, Allen, S, Krumpen, T, Allen, D.** 2023. High levels of microplastics in the Arctic sea ice alga Melosira arctica, a vector to ice-associated and ben-thic food webs. *Environmental Science & Technology* 57(17): 6799-6807. DOI: https://doi.org/10.1021/acs.est.2c08010.

**Bergmann, M, Collard, F, Fabres, J, Gabrielsen, GW, Provencher, JF, Rochman, CM, van Sebille, E, Tek-man, MB.** 2022. Plastic pollution in the Arctic. *Nature Reviews Earth & Environment* 3(5): 323-337. DOI: https://doi.org/10.1038/s43017-022-00279-8.

**Bezanson, M, Stowe, R, Watts, SM.** 2013. Reducing the ecological impact of field research. *American Journal of Primatology* 75(1): 1-9. DOI: https://doi.org/10.1002/ajp.22086.

**Bishop, GA, Burgard, DA, Dalton, TR, Stedman, DH.** 2006. In-use emission measurements of snowmobiles and snowcoaches in Yellowstone National Park. Lakewood, CO: The National Park Service. Available at https://www.snowmobileinfo.org/snowmobile-access-docs/In-Use-Emission-Measurements-of-Snowmobiles-Coaches-in-YNP_2006.pdf. Accessed July 27, 2025.

**Bockelmann, F, Dreier, A-K, Zimmermann, J, Peter, M.** 2022. Renewable energy in Antarctica—Photovoltaic for Neumayer Station III. *Solar Energy Advances* 2: 100026. DOI: https://doi.org/10.1016/j.seja.2022.100026.

**Boyer, M, Aliaga, D, Pernov, JB, Angot, H, Quéléver, LLJ, Dada, L, Heutte, B, Dall'Osto, M, Beddows, DCS, Brasseur, Z, Beck, I, Bucci, S, Duetsch, M, Stohl, A, Laurila, T, Asmi, E, Massling, A, Thomas, DC, Nøjgaard, JK, Chan, T, Sharma, S, Tunved, P, Krejci, R, Hansson, HC, Bianchi, F, Lehtipalo, K, Wiedensohler, A, Weinhold, K, Kulmala, M, Petäjä, T, Sipilä, M, Schmale, J, Jokinen, T.** 2023. A full year of aerosol size distribution data from the central Arctic under an extreme positive Arctic oscillation: Insights from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. *Atmospheric Chemistry and Physics* 23(1): 389-415. DOI: https://doi.org/10.5194/acp-23-389-2023.

**Carbon Footprint Ltd.** 2002. CARBON CALCULATOR: Carbon footprint calculator for individuals and households. Available at https://www.calculator.carbonfootprint.com. Accessed July 17, 2024.

**Conklin & de Decker Associates, Inc.** 2024. CO₂ calculator for aircraft. Available at https://conklindedecker.jetsupport.com/co2-calculator. Accessed October 16, 2024.

**Croal, P, Tetreault, C.** 2012. Respecting indigenous peoples and traditional knowledge. Members of the IAIA IP Section, International Association for Impact Assessment, Special Publication Series (9). Available at https://iaia.org/wp-content/uploads/2025/02/BEST-PRACTICE-Indigenous-Peoples-Traditional-Knowledge.pdf. Accessed July 27, 2025.

**Dada, L, Angot, H, Beck, I, Baccarini, A, Quéléver, LLJ, Boyer, M, Laurila, T, Brasseur, Z, Jozef, G, de Boer, G, Shupe, MD, Henning, S, Bucci, S, Dütsch, M, Stohl, A, Petäjä, T, Daellenbach, KR, Jokinen, T, Schmale, J.** 2022. A central Arctic extreme aerosol event triggered by a warm air-mass intrusion. *Nature Communications* 13(1): 5290. DOI: https://doi.org/10.1038/s41467-022-32872-2.

**Davies, TW, Duffy, JP, Bennie, J, Gaston, KJ.** 2016. Stemming the tide of light pollution encroaching into marine protected areas. *Conservation Letters* 9(3): 164-171. DOI: https://doi.org/10.1111/conl.12191.

**Elshout, P, Chappellaz, J, Gibéryen, T, Hansen, C, Jania, J, Jones-Williams, K, Nolan, J, Reverdy, B, Topp-Jørgensen, E, Yılmaz, A, Badhe, R.** 2023. Synthesis report on the environmental impacts of polar research and logistics in the polar regions. The Environmental Impacts Action Group of the European Polar Board, EPFL Scientific Publications. DOI: https://doi.org/10.5281/zenodo.7907234.

**Erbe, C, Dähne, M, Gordon, J, Herata, H, Houser, DS, Koschinski, S, Leaper, R, McCauley, R, Miller, B, Müller, M, Murray, A, Oswald, JN, Scholik-Schlomer, AR, Schuster, M, Van Opzeeland, IC, Janik, VM.** 2019. Managing the effects of noise from ship traffic, seismic surveying and construction on marine mammals in Antarctica. *Frontiers in Marine Science* 6: 647. DOI: https://doi.org/10.3389/fmars.2019.00647.

**Erbe, C, Farmer, DM.** 2000. Zones of impact around ice-breakers affecting beluga whales in the Beaufort Sea. *The Journal of the Acoustical Society of America* 108(3): 1332-1340. DOI: https://doi.org/10.1121/1.1288938.

**Etienne Bourgois.** 2025. TARA POLAR STATION: Studying the Arctic, sentinel of the climate. Available at https://fondationtaraocean.org/en/schooner/tarapolar-station/. Accessed July 10, 2025.

**European Commission: European Climate, Infrastructure and Environment Executive Agency, Snoeijs-Leijonmalm, P, Flores, H, Niehoff, B, Hildebrandt, N, Castellani, G, Sakinan, S, Svenson, A.** 2021. Ecosystem mapping in the central Arctic Ocean (CAO) during the MOSAiC expedition—Final report. Publications Office. DOI: https://doi.org/10.2926/714618.

**Farley, M, Nicolet, BP.** 2023. Re-use of laboratory utensils reduces CO₂ equivalent footprint and running costs. *PLOS ONE* 18(4): e0283697. DOI: https://doi.org/10.1371/journal.pone.0283697.

**Fong, AA, Hoppe, CJM, Aberle, N, Ashjian, CJ, Assmy, P, Bai, Y, Bakker, DCE, Balmonte, JP, Barry, KR, Bertilsson, S, Boulton, W, Bowman, J, Bozzato,**
D, Bratbak, G, Buck, M, Campbell, RG, Castellani, G, Chamberlain, EJ, Chen, J, Chierici, M, Cornils, A, Creamean, JM, Damm, E, Dethloff, K, Droste, ES, Ebenhöh, O, Eggers, SL, Engel, A, Flores, H, Fransson, A, Frickenhaus, S, Gardner, J, Gelfman, CE, Granskog, MA, Graeve, M, Havermans, C, Heuzé, C, Hildebrandt, N, Hill, TCJ, Hoppema, M, Immerz, A, Jin, H, Koch, BP, Kong, X, Kraberg, A, Lan, M, Lange, BA, Larsen, A, Lebreton, B, Leu, E, Loose, B, Maslowski, W, Mavis, C, Metfies, K, Mock, T, Müller, O, Nicolaus, M, Niehoff, B, Nomura, D, Nöthig, E-M, Oggier, M, Oldenburg, E, Olsen, LM, Peeken, I, Perovich, DK, Popa, O, Rabe, B, Ren, J, Rex, M, Rinke, A, Rokitta, S, Rost, B, Sakinan, S, Salganik, E, Schaafsma, FL, Schäfer, H, Schmidt, K, Shoemaker, KM, Shupe, MD, Snoeijs-Leijonmalm, P, Stefels, J, Svenson, A, Tao, R, Torres-Valdés, S, Torstensson, A, Toseland, A, Ulfsbo, A, Van Leeuwe, MA, Vortkamp, M, Webb, AL, Zhuang, Y, Gradinger, RR. 2024. Overview of the MOSAiC expedition: Ecosystem. *Elementa: Science of the Anthropocene* 12(1): 00135. DOI: https://doi.org/10.1525/elementa.2023.00135.

Foretich, A, Zaimes, GG, Hawkins, TR, Newes, E. 2021. Challenges and opportunities for alternative fuels in the maritime sector. *Maritime Transport Research 2*: 100033. DOI: https://doi.org/10.1016/j.martra.2021.100033.

Frendrup, LL, Rasch, M, Topp-Jørgensen, E, Arndal, MF. 2021. INTERACT reducing the environmental impacts of Arctic fieldwork. Denmark: Aarhus University, DCE-Danish Centre for Environment and Energy. DOI: https://doi.org/10.5281/zenodo.5139698.

García-Martín, E, Rodrigues, CF, Riley, G, Grahn, H. 2019. Estimation of energy consumption in machine learning. *Journal of Parallel and Distributed Computing* 134: 75-88. DOI: https://doi.org/10.1016/j.jpdc.2019.07.007.

Gigault, J, ter Halle, A, Baudrimont, M, Pascal, P-Y, Gauffre, F, Phi, T-L, El Hadri, H, Grassl, B, Reynaud, S. 2018. Current opinion: What is a nanoplastic? *Environmental Pollution* 235: 1030-1034. DOI: https://doi.org/10.1016/j.envpol.2018.01.024.

**Global Carbon Project.** 2024. Global Carbon Atlas: Average per capita carbon dioxide emissions worldwide from 1960 to 2023 (in metric tons). Available at https://www.statista.com/statistics/268753/co2-emissions-per-capita-worldwide-since-1990/. Accessed July 7, 2025. Source link: globalcarbonatlas.org.

Grogan, P. 2021. Raising awareness of science's environmental footprint. *Frontiers in Ecology and the Environment* 19(3): 143. DOI: https://doi.org/10.1002/fee.2326.

Guelfo, JL, Ferguson, PL, Beck, J, Chernick, M, Doria-Manzur, A, Faught, PW, Flug, T, Gray, EP, Jayasundara, N, Knappe, DRU, Joyce, AS, Meng, P, Shojaei, M. 2024. Lithium-ion battery components are at the nexus of sustainable energy and

environmental release of per-and polyfluoroalkyl substances. *Nature Communications* 15(1): 5548. DOI: https://doi.org/10.1038/s41467-024-49753-5.

Hamilton, BM, Jantunen, I, Bergmann, M, Vorkamp, K, Aherne, J, Magnusson, K, Herzke, D, Granberg, M, Hallanger, IG, Gomiero, A, Peeken, I. 2022. Microplastics in the atmosphere and cryosphere in the circumpolar North: A case for multicompartment monitoring. *Arctic Science* 8(4): 1116-1126. DOI: https://doi.org/10.1139/as-2021-0054.

Hawly, M. 2021. Deposition of microplastics by snow in the Arctic. [PhD thesis]. Germany: Technische Hochschule Nürnberg.

Helmig, D, Liptzin, D, Hueber, J, Savarino, J. 2020. Impact of exhaust emissions on chemical snowpack composition at Concordia Station, Antarctica. *The Cryosphere* 14(1): 199-209. DOI: https://doi.org/10.5194/tc-14-199-2020.

Henrik, S. 2017. Solar cells at Villum Research Station, Station Nord. Available at https://villumresearchstation.dk/currently/news/nyhed/artikel/solar-cells-at-villum-research-station-station-nord. Accessed July 10, 2025.

Heutte, B, Beck, I, Quéléver, L, Jokinen, T, Laurila, T, Dada, L, Schmale, J. 2022. Equivalent black carbon concentration in 10 minutes time resolution, measured in the Swiss container during MOSAiC 2019/2020. DOI: https://doi.org/10.1594/PANGAEA.952251.

Heutte, B, Bergner, N, Beck, I, Angot, H, Dada, L, Quéléver, LLJ, Laurila, T, Boyer, M, Brasseur, Z, Daellenbach, KR, Henning, S, Kuang, C, Kulmala, M, Lampilahti, J, Lampimäki, M, Petäjä, T, Shupe, MD, Sipilä, M, Uin, J, Jokinen, T, Schmale, J. 2023. Measurements of aerosol microphysical and chemical properties in the central Arctic atmosphere during MOSAiC. *Scientific Data* 10(1): 690. DOI: https://doi.org/10.1038/s41597-023-02586-1.

Holste, S, Rasch, M, Topp-Jørgensen, E. 2022. INTERACT reducing CO₂ emissions of Arctic science. Zenodo. DOI: https://doi.org/10.5281/zenodo.6683739.

Hoppe, CJM, Fuchs, N, Notz, D, Anderson, P, Assmy, P, Berge, J, Bratbak, G, Guillou, G, Kraberg, A, Larsen, A, Lebreton, B, Leu, E, Lucassen, M, Müller, O, Oziel, L, Rost, B, Schartmüller, B, Torstensson, A, Wloka, J. 2024. Photosynthetic light requirement near the theoretical minimum detected in Arctic microalgae. *Nature Communications* 15(1): 7385. DOI: https://doi.org/10.1038/s41467-024-51636-8.

Ingersoll, GP. 1999. Effects of snowmobile use on snow-pack chemistry in Yellowstone National Park, 1998. U.S. Department of the Interior, U.S. Geological Survey (vol. 99). DOI: https://doi.org/10.3133/wri994148.

Ings, M. 2024. Nunavut impact review board. Available at https://www.nirb.ca. Accessed February 13, 2024.

Interagency Arctic Research Policy Committee (IARPC). 2015. Principles for conducting research in the Arctic. Available at https://www.nsf.gov/
geo/opp/arctic/conduct.jsp. Accessed Feburary 13, 2024.

Ivo, B, Hélène, A, Andrea, B, Markus, L, Matthew, B, Julia, S. 2021. Pollution Detection Algorithm (PDA). DOI: https://doi.org/10.5281/zenodo.5761101.

Jelena, R. 2024. Wind energy research in Antarctica. Available at https://swisspolar.ch/2024/04/wind-energy-research-in-antarctica-brandon-van-schaik/. Accessed July 10, 2025.

Jensen, M, Kristensen, KK. 1989. Effects of rhodamine water tracer on *Escherichia coli* densities. *Water Research* 23(2): 257-259. DOI: https://doi.org/10.1016/0043-1354(89)90051-1.

Jones, NR, de Jersey, AM, Lavers, JL, Rodemann, T, Rivers-Auty, J. 2024. Identifying laboratory sources of microplastic and nanoplastic contamination from the air, water, and consumables. *Journal of Hazardous Materials* 465: 133276. DOI: https://doi.org/10.1016/j.jhazmat.2023.133276.

Kang, S, Zhang, Y, Qian, Y, Wang, H. 2020. A review of black carbon in snow and ice and its impact on the cryosphere. *Earth-Science Reviews* 210: 103346. DOI: https://doi.org/10.1016/j.earscirev.2020.103346.

Karvinen, PA, Rantakallio, S. 2019. Good practices for environmental impact assessment and meaningful engagement in the Arctic—including good practice recommendations. CAPARDUS Practices. DOI: https://doi.org/10.25607/OBP-1767.

Kasnavia, T, Vu, D, Sabatini, DA. 1999. Fluorescent dye and media properties affecting sorption and tracer selection. *Groundwater* 37(3): 376-381. DOI: https://doi.org/10.1111/j.1745-6584.1999.tb01114.x.

Kilcoyne, J, Bogan, Y, Duffy, C, Hollowell, T. 2022. Reducing environmental impacts of marine biotoxin monitoring: A laboratory report. *PLOS Sustainability and Transformation* 1(3): e0000001. DOI: https://doi.org/10.1371/journal.pstr.0000001.

Kim, S-K, Lee, H-J, Kim, J-S, Kang, S-H, Yang, E-J, Cho, K-H, Tian, Z, Andrady, A. 2021. Importance of seasonal sea ice in the western Arctic ocean to the Arctic and global microplastic budgets. *Journal of Hazardous Materials* 418: 125971. DOI: https://doi.org/10.1016/j.jhazmat.2021.125971.

Klöwer, M, Hopkins, D, Allen, M, Higham, J. 2020. An analysis of ways to decarbonize conference travel after COVID-19. DOI: https://doi.org/10.1038/d41586-020-02057-2.

Knust, R. 2017. Polar research and supply vessel POLARSTERN operated by the Alfred-Wegener-Institute. *Journal of Large-Scale Research Facilities JLSRF* 3: A119. DOI: https://doi.org/10.17815/jlsrf-3-163.

Koivurova, T, Lesser, P, Bickford, S, Kankaanpää, P, Nenasheva, M. 2016. *Environmental impact assessment in the Arctic: A guide to best practice*. Edward Elgar. DOI: https://doi.org/10.1111/reel.12200.

Krumpen, T, Birrien, F, Kauker, F, Rackow, T, von Albedyll, L, Angelopoulos, M, Belter, HJ, Bessonov, V, Damm, E, Dethloff, K, Haapala, J, Haas, C, Harris, C, Hendricks, S, Hoelemann, J, Hoppmann,

M, Kaleschke, L, Karcher, M, Kolabutin, N, Lei, R, Lenz, J, Morgenstern, A, Nicolaus, M, Nixdorf, U, Petrovsky, T, Rabe, B, Rabenstein, L, Rex, M, Ricker, R, Rohde, J, Shimanchuk, E, Singha, S, Smolyanitsky, V, Sokolov, V, Stanton, T, Timofeeva, A, Tsamados, M, Watkins, D. 2020. The MOSAiC ice floe: Sediment-laden survivor from the Siberian shelf. *The Cryosphere* 14(7): 2173-2187. DOI: https://doi.org/10.5194/tc-14-2173-2020.

Lack, DA, Corbett, JJ, Onasch, T, Lerner, B, Massoli, P, Quinn, PK, Bates, TS, Covert, DS, Coffman, D, Sierau, B, Herndon, S, Allan, J, Baynard, T, Lovejoy, E, Ravishankara, AR, Williams, E. 2009. Particulate emissions from commercial shipping: Chemical, physical, and optical properties. *Journal of Geophysical Research: Atmospheres* 114(D7). DOI: https://doi.org/10.1029/2008JD011300.

Leistenschneider, C Burkhardt-Holm, P, Mani, T, Primpke, S, Taubner, H, Gerdts, G. 2021. Microplastics in the Weddell Sea (Antarctica): A forensic approach for discrimination between environmental and vessel-induced microplastics. *Environmental Science & Technology* 55(23): 15900-15911. DOI: https://doi.org/10.1021/acs.est.1c05207.

Leistenschneider, C, Wu, F, Primpke, S, Gerdts, G, Burkhardt-Holm, P. 2024. Unveiling high concentrations of small microplastics (11–500 µm) in surface water samples from the southern Weddell Sea off Antarctica. *Science of the Total Environment* 172124. DOI: https://doi.org/10.1016/j.scitotenv.2024.172124.

Ludvigsen, M, Berge, J, Geoffroy, M, Cohen, JH, De La Torre, PR, Nornes, SM, Singh, H, Sørensen, AJ, Daase, M, Johnsen, G. 2018. Use of an autonomous surface vehicle reveals small-scale diel vertical migrations of zooplankton and susceptibility to light pollution under low solar irradiance. *Science Advances* 4(1): eaap9887. DOI: https://doi.org/10.1126/sciadv.aap9887.

Macfarlane, AR, Ben-Ari, T, Blanc, G, Bozzato, D, Calmer, R, Haslett, S, Holste, S, Jardé, E, Rixen, C, Ruché, D, Schneebeli, M, Smith, MM, Thielke, L, Vandevelde, S, Wheeler, HC. 2024. A call for funding bodies to influence the reduction of environmental impacts in remote scientific fieldwork. *Frontiers in Sustainability* 5. DOI: https://doi.org/10.3389/frsus.2024.1338660.

**Madrid-Protocol.** 1991. Final report of the Eleventh Antarctic Treaty Special Consultative Meeting: the 1991 Madrid Protocol. Available at https://documents.ats.aq/SATCM11_4/fr/SATCM11_4_fr001_e.pdf. Accessed October 14, 2025.

MEPC. 1978. Protocol of 1978 relating to the International Convention for the Prevention of Pollution from ships, 1973. Available at https://wwwcdn.imo.org/localresources/en/KnowledgeCentre/ConferencesMeetings/Documents/MARPOL. Accessed July 25, 2025.

Mohaupt, V, König, B. 2025. Polar bear sightings during MOSAiC Expedition PS122. DOI: https://doi.org/10.1594/PANGAEA.983963.
**Moraru, A, Rasmussen, LH, Cal Quaglia, F, Middleton, A, Huynh, HM, López-Quirós, A.** 2024. Polar field-work in the 21st century: Early Career Researchers considerations regarding safety and sustainability. *PLOS Climate* **3**(7): e0000415. DOI: https://doi.org/10.1371/journal.pclm.0000415.

**Morgan, RK.** 2012. Environmental impact assessment: The state of the art. *Impact Assessment and Project Appraisal* **30**(1): 5–14. DOI: https://doi.org/10.1080/14615517.2012.661557.

**Mullet, TC, Morton, JM, Gage, SH, Huettmann, F.** 2017. Acoustic footprint of snowmobile noise and natural quiet refugia in an Alaskan wilderness. *Natural Areas Journal* **37**(3): 332–349. DOI: https://doi.org/10.3375/043.037.0308.

**Murray, DS, Cole, I, Nunez, N, Parker, EM, Mikulis, A, Herreid, AM, Donovan, M, Fazekas, HM, Wymore, AS.** 2023. The environmental responsibility framework: A toolbox for recognizing and promoting ecologically conscious research. *Earth's Future* **11**(4): e2022EF002964. DOI: https://doi.org/10.1029/2022EF002964.

**Musselman, RC, Korfmacher, JL.** 2007. Air quality at a snowmobile staging area and snow chemistry on and off trail in a Rocky Mountain subalpine forest, Snowy Range, Wyoming. *Environmental Monitoring and Assessment* **133**: 321–334. DOI: https://doi.org/10.1007/s10661-006-9587-9.

**myclimate Foundation.** 2024. Calculate and support. Available at https://co2.myclimate.org/en/calculate_emissions. Accessed: March 28, 2024.

**Mytton, D, Ashtine, M.** 2022. Sources of data center energy estimates: A comprehensive review. *Joule* **6**(9): 2032–2056. DOI: https://doi.org/10.1016/j.joule.2022.07.011.

**Nicolaus, M, Perovich, DK, Sreen, G, Granskog, MA, Albedyll, LV, Angelopoulos, M, Anhaus, P, Arndt, S, Belter, HJ, Bessonov, V, Birnbaum, G, Brauchle, J, Calmer, R, Cardellach, E, Cheng, B, Clemens-Sewall, D, Dadic, R, Damm, E, de Boer, G, Demir, O, Dethloff, K, Divine, DV, Fong, AA, Fons, S, Frey, MM, Fuchs, N, Gabarró, C, Gerland, S, Goessling, HF, Gradinger, R, Haapala, J, Haas, C, Hamilton, J, Hannula, H-R, Hendricks, S, Herber, A, Heuzé, C, Hoppmann, M, Høyland, KV, Huntemann, M, Hutchings, JK, Hwang, B, Itkin, P, Jacobi, H-W, Jaggi, M, Jutila, A, Kaleschke, L, Katlein, C, Kolabutin, N, Krampe, D, Kristensen, SS, Krumpen, T, Kurtz, N, Lampert, A, Lange, BA, Lei, R, Light, B, Linhardt, F, Liston, GE, Loose, B, Macfarlane, AR, Mahmud, M, Matero, IO, Maus, S, Morgenstern, A, Naderpour, R, Nandan, V, Niubom, A, Oggier, M, Oppelt, N, Pätzold, F, Perron, C, Petrovsky, T, Pirazzini, R, Polashenski, C, Rabe, B, Raphael, IA, Regnery, J, Rex, M, Ricker, R, Riemann-Campe, K, Rinke, A, Rohde, J, Salganik, E, Scharien, RK, Schiller, M, Schneebeli, M, Semmling, M, Shimanchuk, E, Shupe, MD, Smith, MM, Smolyanitsky, V, Sokolov, V, Stanton, T, Stroeve, J, Thielke, L, Timofeeva, A, Tonboe, RT, Tavri, A,

**Tsamados, M, Wagner, DN, Watkins, D, Webster, M, Wendisch, M.** 2022. Overview of the MOSAiC expedition: Snow and sea ice. *Elementa: Science of the Anthropocene* **10**(1). DOI: https://doi.org/10.1525/elementa.2021.000046.

**Nixdorf, U, Dethloff, K, Rex, M, Shupe, M, Sommerfeld, A, Perovich, DK, Nicolaus, M, Heuzé, C, Rabe, B, Loose, B, Damm, E, Gradinger, R, Fong, A, Maslowski, W, Rinke, A, Kwok, R, Sreen, G, Wendisch, M, Herber, A, Hirsekorn, M, Mohaupt, V, Frickenhaus, S, Immerz, A, Weiss-Tuider, K, König, B, Mengedoht, D, Regnery, J, Gerchow, P, Ransby, D, Krumpen, T, Morgenstern, A, Haas, C, Kanzow, T, Rack, FR, Saitzev, V, Sokolov, V, Makarov, A, Schwarze, S, Wunderlich, T, Wurr, K, Boetius, A. 2021. MOSAiC extended acknowledgement. DOI: https://doi.org/10.5281/zenodo.5179738.

**Njåstad, B, Fridriksdottir, S, Jessen, M-A, Johansen, BF, Nyegaard, H, Olafsdottir, R, Overrein, Ø.** 2005. Research without a trace: Integration of environmental considerations in the research and education sector—Greenland, Iceland and Svalbard. Norden. Available at https://pure.au.dk/portal/en/publications/forskning-uten-spor-integrering-avmilj%C3%B8hensyn-i-forsknings-og-ut. Accessed July 27, 2025.

**Noble, B, Hanna, K.** 2015. Environmental assessment in the Arctic: A gap analysis and research agenda. *Arc tic* 341–355. Available at http://www.jstor.org/stable/43872253. Accessed July 27, 2025.

**Peeken, I, Primpke, S, Beyer, B, Gütermann, J, Katlein, C, Krumpen, T, Bergmann, M, Hehemann, L, Gerdts, G.** 2018. Arctic sea ice is an important temporal sink and means of transport for microplastic. *Nature Communications* **9**(1): 1505. DOI: https://doi.org/10.1038/s41467-018-03825-5.

**Prospathopoulos, AM.** 2025. Advances in the monitoring, assessment and reduction of underwater noise from vessels with respect to its impact on marine life—A short review. *Oceanography & Fisheries Open Access Journal* **18**(3): 555987. DOI: https://doi.org/10.19080/OFOAJ.2025.18.555987.

**Rabe, B, Heuzé, C, Regnery, J, Aksenov, Y, Allerholt, J, Athanase, M, Bai, Y, Basque, C, Bauch, D, Baumann, TM, Chen, D, Cole, ST, Craw, L, Davies, A, Damm, E, Dethloff, K, Divine, DV, Doglioni, F, Ebert, F, Fang, Y-C, Fer, I, Fong, AA, Gradinger, R, Granskog, MA, Graupner, R, Haas, C, He, H, He, Y, Hoppmann, M, Janout, M, Kadko, D, Kanzow, T, Karam, S, Kawaguchi, Y, Koenig, Z, Kong, B, Krishfield, RA, Krumpen, T, Kuhlmey, D, Kuznetsov, I, Lan, M, Laukert, G, Lei, R, Li, T, Torres-Valdés, S, Lin, L, Lin, L, Liu, H, Liu, N, Loose, B, Ma, X, MacKay, R, Mallet, M, Mallett, RDC, Maslowski, W, Mertens, C, Mohrholz, V, Muilwijk, M, Nicolaus, M, O'Brien, JK, Perovich, D, Ren, J, Rex, M, Ribeiro, N, Rinke, A, Schaffer, J, Schuffenhauer, I, Schulz, K, Shupe, MD, Shaw, W, Sokolov, V, Sommerfeld, A, Sreen, G, Stanton, T,
Stephens, M, Su, J, Sukhikh, N, Sundfjord, A, Thomisch, K, Tippenhauer, S, Toole, JM, Vredenborg, M, Walter, M, Wang, H, Wang, L, Wang, Y, Wendisch, M, Zhao, J, Zhou, M, Zhu, J. 2022. Overview of the MOSAiC expedition: Physical oceanography. *Elementa: Science of the Anthropocene* 10(1): 00062. DOI: https://doi.org/10.1525/elementa.2021.00062.

Ramsey, M. 2020. Low sulfur fuel in 2020. North American Marine Environment Protection Association (NAMEPA). Available at https://namepa.net/s/The-Ramsey-Report-Low-Sulfur-Fuel-2020.pdf. Accessed October 07, 2020.

Richardson, SD, Willson, CS, Rusch, KA. 2004. Use of rhodamine water tracer in the marshland upwelling system. *Groundwater* 42(5): 678–688. DOI: https://doi.org/10.1111/j.1745-6584.2004.tb02722.x.

Roth, EH, Schmidt, V, Hildebrand, JA, Wiggins, SM. 2013. Underwater radiated noise levels of a research icebreaker in the central Arctic Ocean. *The Journal of the Acoustical Society of America* 133(4): 1971–1980. DOI: https://doi.org/10.1121/1.4790356.

Schulz, K, Koenig, Z, Muilwijk, M, Bauch, D, Hoppe, CJM, Droste, ES, Hoppmann, M, Chamberlain, EJ, Laukert, G, Stanton, T, Quintanilla-Zurita, A, Fer, I, Heuzé, C, Karam, S, Mieruch-Schnülle, S, Baumann, TM, Vredenborg, M, Tippenhauer, S, Granskog, MA. 2024. The Eurasian Arctic Ocean along the MOSAiC drift in 2019–2020: An interdisciplinary perspective on physical properties and processes. *Elementa: Science of the Anthropocene* 12(1). DOI: https://doi.org/10.1525/elementa.2023.00114.

Senécal, P, Goldsmith, B, Conover, S, Sadler, B, Brown, K. 1999. Principles of environmental impact assessment best practice. Special Publication, International Association for Impact Assessment, Fargo, USA. Available at https://www.eianz.org/document/item/2744. Accessed July 27, 2025.

Shupe, M, Rex, M, Dethloff, K, Damm, E, Fong, A, Gradinger, R, Heuzé, C, Loose, B, Makarov, A, Maslowski, W, Nicolaus, M, Perovich, D, Rabe, B, Rinke, A, Sokolov, V, Sommerfeld, A. 2020. The MOSAiC expedition: A year drifting with the Arctic sea ice. Arctic Report Card. DOI: https://doi.org/10.25923/9g3v-xh92.

Shupe, MD, Rex, M, Blomquist, B, Persson, POG, Schmale, J, Uttal, T, Althausen, D, Angot, H, Archer, S, Bariteau, L, Beck, I, Bilberry, J, Bucci, S, Buck, C, Boyer, M, Brasseur, Z, Brooks, IM, Calmer, R, Cassano, J, Castro, V, Chu, D, Costa, D, Cox, CJ, Creamean, J, Crewell, S, Dahlke, S, Damm, E, de Boer, G, Deckelmann, H, Dethloff, K, Dütsch, M, Ebell, K, Ehrlich, A, Ellis, J, Engelmann, R, Fong, AA, Frey, MM, Gallagher, MR, Ganzeveld, L, Gradinger, R, Graeser, J, Greenamyer, V, Griesche, H, Griffiths, S, Hamilton, J, Heinemann, G, Helmig, D, Herber, A, Heuzé, C, Hofer, J, Houchens, T, Howard, D, Inoue, J,

Jacobi, H-W, Jaiser, R, Jokinen, T, Jourdan, O, Jozef, G, King, W, Kirchgaessner, A, Klingebiel, M, Krassovski, M, Krumpen, T, Lampert, A, Landing, W, Laurila, T, Lawrence, D, Lonardi, M, Loose, B, Lüpkes, C, Maahn, M, Macke, A, Maslowski, W, Marsay, C, Maturilli, M, Mech, M, Morris, S, Moser, M, Nicolaus, M, Ortega, P, Osborn, J, Pätzold, F, Perovich, DK, Petäjä, T, Pilz, C, Pirazzini, R, Posman, K, Powers, H, Pratt, KA, Preußer, A, Quéléver, L, Radenz, M, Rabe, B, Rinke, A, Sachs, T, Schulz, A, Siebert, H, Silva, T, Solomon, A, Sommerfeld, A, Sreen, G, Stephens, M, Stohl, A, Svensson, G, Uin, J, Viegas, J, Voigt, C, von der Gathen, P, Wehner, B, Welker, JM, Wendisch, M, Werner, M, Xie, ZQ, Yue, F. 2022. Overview of the MOSAiC expedition: Atmosphere. *Elementa: Science of the Anthropocene* 10(1): 00060. DOI: https://doi.org/10.1525/elementa.2021.00060.

Smith, WV, Bebbington, A, Sircar, R, Pulver, SR. 2025. Doctoral students as carbon accountants: Calculating carbon costs of a PhD in Neuroscience. *bioRxiv*. 2025-01. DOI: https://doi.org/10.1101/2025.01.20.633775.

Stevens, B, Bony, S, Farrell, D, Ament, F, Blyth, A, Fairall, C, Karstensen, J, Quinn, PK, Speich, S, Acquistapace, C, Aemisegger, F, Albright, AL, Bellenger, H, Bodenschatz, E, Caesar, K-A, Chewitt-Lucas, R, de Boer, G, Delanoë, J, Denby, L, Ewald, F, Fildier, B, Forde, M, George, G, Gross, S, Hagen, M, Hausold, A, Heywood, KJ, Hirsch, L, Jacob, M, Jansen, F, Kinne, S, Klocke, D, Kölling, T, Konow, H, Lothon, M, Mohr, W, Naumann, AK, Nuijens, L, Olivier, L, Pincus, R, Pöhlker, M, Reverdin, G, Roberts, G, Schnitt, S, Schulz, H, Siebesma, AP, Stephan, CC, Sullivan, P, Touzé-Peiffer, L, Vial, J, Vogel, R, Zuidema, P, Alexander, N, Alves, L, Arixi, S, Asmath, H, Bagheri, G, Baier, K, Bailey, A, Baranowski, D, Baron, A, Barrau, S, Barrett, PA, Batier, F, Behrendt, A, Bendinger, A, Beucher, F, Bigorre, S, Blades, E, Blossey, P, Bock, O, Böing, S, Bosser, P, Bourras, D, Bouruet-Aubertot, P, Bower, K, Branellec, P, Branger, H, Brennek, M, Brewer, A, Brilouet, P-E, Brügmann, B, Buehler, SA, Burke, E, Burton, R, Calmer, R, Canonici, J-C, Carton, X, Cato, GJr, Charles, JA, Chazette, P, Chen, Y, Chilinski, MT, Choularton, T, Chuang, P, Clarke, S, Coe, H, Cornet, C, Coutris, P, Couvreux, F, Crewell, S, Cronin, T, Cui, Z, Cuypers, Y, Daley, A, Damerell, GM, Dauhut, T, Deneke, H, Desbios, J-P, Dörner, S, Donner, S, Douet, V, Drushka, K, Dütsch, M, Ehrlich, A, Emanuel, K, Emmanuelilidis, A, Etienne, J-C, Etienne-Leblanc, S, Faure, G, Feingold, G, Ferrero, L, Fix, A, Flament, C, Flatau, PJ, Foltz, GR, Forster, L, Furtuna, I, Gadian, A, Galewsky, J, Gallagher, M, Gallimore, P, Gaston, C, Gentemann, C, Geyskens, N, Giez, A, Gollop, J, Gouirand, I, Gourbeyre, C, de Graaf, D, de Groot, GE, Grosz, R, Güttler, J, Gutleben, M, Hall, K, Harris, G, Helfer, KC, Henze, D,
Herbert, C, Holanda, B, Ibanez-Landeta, A, Intrieri, J, Iyer, S, Julien, F, Kalesse, H, Kazil, J, Kellman, A, Kidane, AT, Kirchner, U, Klingebiel, M, Körner, M, Kremper, LA, Kretzschmar, J, Krüger, O, Kumala, W, Kurz, A, L'Hégaret, P, Labaste, M, Lachlan-Cope, T, Laing, A, Landschützer, P, Lang, T, Lange, D, Lange, I, Laplace, C, Lavik, G, Laxenaire, R, Le Bihan, C, Leandro, M, Lefevre, N, Lena, M, Lenschow, D, Li, Q, Lloyd, G, Los, S, Losi, N, Lovell, O, Luneau, C, Makuch, P, Malinowski, S, Manta, G, Marinou, E, Marsden, N, Masson, S, Maury, N, Mayer, B, Mayers-Als, M, Mazel, C, McGeary, W, McWilliams, JC, Mech, M, Mehlmann, M, Meroni, AN, Mieslinger, T, Minikin, A, Minnett, P, Möller, G, Morfa Avalos, Y, Muller, C, Musat, I, Napoli, A, Neuberger, A, Noisel, C, Noone, D, Nordsiek, F, Nowak, JL, Oswald, L, Parker, DJ, Peck, C, Person, R, Philippi, M, Plueddemann, A, Pöhlker, C, Pörtge, V, Pöschl, U, Pologne, L, Posyniak, M, Prange, M, Quiñones Meléndez, E, Radtke, J, Ramage, K, Reimann, J, Renault, L, Reus, K, Reyes, A, Ribbe, J, Ringel, M, Ritschel, M, Rocha, CB, Rochetin, N, Röttenbacher, J, Rollo, C, Royer, H, Sadoulet, P, Saffin, L, Sandiford, S, Sandu, I, Schäfer, M, Schemann, V, Schirmacher, I, Schlenczek, O, Schmidt, J, Schröder, M, Schwarzenboeck, A, Sealy, A, Senff, CJ, Serikov, I, Shohan, S, Siddle, E, Smirnov, A, Späth, F, Spooner, B, Stolla, MK, Szkółka, W, de Szoeke, SP, Tarot, S, Tetoni, E, Thompson, E, Thomson, J, Tomassini, L, Totems, J, Ubele, AA, Villiger, L, von Arx, J, Wagner, T, Walther, A,

Webber, B, Wendisch, M, Whitehall, S, Wiltshire, A, Wing, AA, Wirth, M, Wiskandt, J, Wolf, K, Worbes, L, Wright, E, Wulfmeyer, V, Young, S, Zhang, C, Zhang, D, Ziemen, F, Zinner, T, Zöger, M. 2021. EUREC⁴A. *Earth System Science Data Discussions* 13: 4067–4119. DOI: https://doi.org/10.5194/essd-13-4067-2021.

Takei, Y. 2013. Marine scientific research in the Arctic, in Baker, B, Molenaar, EJ, Oude Elferink, AG, Rothwell, DR eds., *The law of the sea and the Polar regions*. Brill Nijhoff: 343–365. DOI: https://doi.org/10.1163/9789004255210_016.

**UK Government.** 2013. Government conversion factors for company reporting of greenhouse gas emissions. Available at https://www.gov.uk/government/collections/government-conversion-factors-for-company-reporting. Accessed July 17, 2024.

van Soest, M. 2023. An Arctic expedition: A supposedly useful thing I'll never do again. *Polar Research* 42. DOI: https://doi.org/10.33265/polar.v42.9070.

Walther, BA, Bergmann, M. 2022. Plastic pollution of four understudied marine ecosystems: A review of mangroves, seagrass meadows, the Arctic Ocean and the deep seafloor. *Emerging Topics in Life Sciences* 6(4): 371–387. DOI: https://doi.org/10.1042/ETLS20220017.

**X-Rates: Monthly average rates.** 2024. Euro per 1 US Dollar Monthly average. Available at https://www.x-rates.com/average/?from=USD&to=EUR&amount=1&year=2020. Accessed October 07, 2024.

**How to cite this article:** Macfarlane, AR, Smith, MM, Calmer, R, Droste, ES, Tippenhauer, S, Angot, H, Mohaupt, V. 2025. Environmental impact assessments of scientific fieldwork as a path to sustainability: A case study from the MOSAiC expe- dition. *Elementa: Science of the Anthropocene* 13(1). DOI: https://doi.org/10.1525/elementa.2025.00035

**Domain Editor-in-Chief:** Detlev Helmig, Boulder AIR LLC, Boulder, CO, USA

**Associate Editor:** Paul B. Shepson, School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY, USA

**Knowledge Domain:** Atmospheric Science

**Part of an Elementa Special Feature:** The Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC)

**Published:** November 14, 2025

**Accepted:** August 19, 2025

**Submitted:** March 10, 2025

**Copyright:** © 2025 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/.