Matching human movement to climate change

By Greg Davies-Jones, 2020 IIASA Science Communication Fellow

Greg Davies-Jones sits down with 2020 IIASA Young Scientists Summer Program (YSSP) participant Lisa Thalheimer to discuss how attribution science can play a leading role in addressing disaster displacement.

We live in the era of the greatest human movement in recorded history – there are more people on the move today than at any other point in our past. Despite the common misconception that most migrants cross borders, a lot of migration actually occurs internally. According to the Internal Displacement Monitoring Center, a staggering 72% of internal migration is linked to displacement due to natural hazards or extreme weather.

Pinpointing the finer details of how human mobility might evolve remains a complex undertaking. Contemporary migratory movements reflect the complex patterns of social and economic globalization – they flow in all directions and affect all countries in one way or another. It is clear that given the rising global average temperatures, natural hazards and extreme weather events will increase in frequency, intensity, and duration, adversely effecting many parts of the globe. A better understanding of how human-induced climate change influences disaster displacement will undoubtedly be essential in addressing future human mobility and informing the debate on climate and migration policies.

Figure: Climate-related displacement on an axis of forced to voluntary human mobility. Thalheimer (2020)

 

The focus of 2020 YSSP participant Lisa Thalheimer’s research is on internal displacement in East Africa, in particular, Somalia. As part of her YSSP project, Thalheimer hopes to determine whether, and to what extent, human-induced climate change altered the likelihood of extreme weather-related displacement in Somalia by conflating econometric methods and Probabilistic Event Attribution (PEA).

“Econometrics is essentially the application of statistical methods to quantify impacts and PEA is a way of examining to what extent extreme weather events can be linked with past man-made emissions. By combining the two methods we hope to quantify the ramifications of extreme weather and displacement in East Africa,” she explains.

This is no mean feat, as PEA itself is a relatively new science and many challenges still exist in the field of event attribution  ̶  a field of research concerned with the process by which the causes of behavior and events can be explained. In this instance, the idea was to study each extreme weather event individually to determine if human-induced climate change may have added to the intensity or likelihood of the event occurring. PEA is a growing science within this field and relies on the availability of long-term meteorological observations and the reliability of climate model simulations. In terms of migration and the accompanying econometric methods, the complexity of this work is mainly in data capturing.

“The difficulty with migration data capturing is at the start – before you can capture anything, you must ascertain how the data is defined, as different countries define mobility in different ways. For instance, it could be time – where did you live one year ago as opposed to five years ago? That’s the first complexity. Then you must work out who collects data on who – in Europe, we have fundamental freedom of movement within the EU, so unless you file for residency, your movement is not recorded. Another complexity is because we want to see if climate change is part of the driver  ̶  directly or indirectly. We need to know not just where people are now, but where they have been and where they came from, so we can match the climate with their movements. All of this highlights how difficult it is to carry out this type of analysis,” Thalheimer adds.

In Somalia, the team relied on previously collected forced migration data, for example, from the UN High Commissioner for Refugees (UNHCR). These UNHCR datasets collected in Somalia were comprehensive and included not only origin and destination information but also a categorization of the primary reason for the displacement.

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The investigation homed in on one extreme weather case study in the region: The April 2020 heavy rainfall in Southern Ethiopia, which led to several severe flooding events in South Somalia. In this particular case, however, no appreciable connection could be made between human-induced climate change and the resultant displacement. Despite this somewhat chastening outcome, the achievement of this study is not proving a definitive attributable link between human-induced climate change and the April 2020 rainfall, but rather the construction of the adjustable attribution framework presented that can be applied directly to other events and displacement contexts.

As previously mentioned, there are, however, limitations to this novel methodology, especially in regions like Somalia that lack exhaustive observational weather and displacement data. According to Thalheimer, exploring ways of effectively applying this framework in countries vulnerable to climate change will be particularly important going forward.

“Event attribution studies do not usually form the basis of climate migration analysis, disaster risk reduction, or adaptation strategies. Yet, to respond appropriately to these impacts and affected populations, we must develop a comprehensive and detailed understanding of the nature of these impacts, as well as knowledge on how these might evolve over time. Event attribution is a tool we can employ to do this,” she concludes.

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

Exploring co-benefits of green cooling in China

By Xu Wang, IIASA Young Scientists Summer Program (YSSP) alumnus and Assistant Professor at Beijing University of Technology and Pallav Purohit, researcher in the IIASA Air Quality and Greenhouse Gases Program.

Xu Wang and Pallav Purohit write about their recent study in which they found that accelerating the transition to climate-friendly and energy-efficient air conditioning in the Chinese residential building sector could expedite building a low-carbon society in China.

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China saw the fastest growth worldwide in energy demand for space cooling in buildings over the last two decades, increasing at 13% per year since 2000 and reaching nearly 400 terawatt-hours (TWh) of electricity consumption in 2017. This growth was largely driven by increasing income and growing demand for thermal comfort. As a result, space cooling accounted for more than 10% of total electricity growth in China since 2010 and around 16% of peak electricity load in 2017. That share can reach as much as 50% of peak electricity demand on extremely hot days, as seen in recent summers. Cooling-related carbon dioxide (CO2) emissions from electricity consumption consequently increased fivefold between 2000 and 2017, given the strong reliance on coal-fired power generation in China [1].

In our recent publication in the journal Environmental Science and Technology, we used a bottom-up modeling approach to predict the penetration rate of room air conditioners in the residential building sector of China at the provincial level, taking urban-rural heterogeneity into account. Our results reveal that increasing income, growing demand for thermal comfort, and warmer climatic conditions, could drive an increase in the stock of room air conditioners in China from 568 million units in 2015 to 997 million units in 2030, and 1.1 billion units in 2050. In urban China, room air conditioner ownership per 100 households is expected to increase from 114 units in 2015 to 219 units in 2030, and 225 units in 2050, with slow growth after 2040 due to the saturation of room air conditioners in the country’s urban households. Ownership of room air conditioners per 100 households in rural China could increase from 48 units in 2015 to 147 units in 2030 and 208 units in 2050 [2].

The Kigali Amendment to the Montreal Protocol on Substances that Deplete the Ozone Layer will help protect the climate by phasing down high global warming potential (GWP) hydrofluorocarbons (HFCs), which are commonly used as refrigerants in cooling technologies [3]. Promoting energy efficiency of cooling technologies together with HFC phase-down under the amendment can significantly increase those climate co-benefits. It is in this context that we assessed the co-benefits associated with enhanced energy efficiency improvement of room air conditioners (e.g., using efficient compressors, heat exchangers, valves, etc.) and the adoption of low-GWP refrigerants in air conditioning systems. The annual electricity saving from switching to more efficient room air conditioners using low-GWP refrigerants is estimated at almost 1000 TWh in 2050 when taking account of the full technical energy efficiency potential. This is equivalent to approximately 4% of the expected total energy consumption in the Chinese building sector in 2050, or the avoidance of 284 new coal-fired power plants of 500 MW each.

Our results indicate that the cumulative greenhouse gas mitigation associated with both the electricity savings and the substitution of high-GWP refrigerants makes up 2.6% of total business-as-usual CO2 equivalent emissions in China over the period 2020 to 2050. Therefore, the transition towards the uptake of low-GWP refrigerants is as vital as the energy efficiency improvement of new room air conditioners, which can help and accelerate the ultimate objective of building a low-carbon society in China. The findings further show that reduced electricity consumption could mean lower air pollution emissions in the power sector, estimated at about 8.8% for sulfur dioxide (SO2), 9.4% for nitrogen oxides (NOx), and 9% for fine particulate matter (PM2.5) emissions by 2050 compared with a pre-Kigali baseline.

China can deliver significant energy savings and associated reductions in greenhouse gas and air pollution emissions in the building sector by developing and implementing a comprehensive national policy framework, including legislation and regulation, information programs, and incentives for industry. Energy efficiency and refrigerant standards for room air conditioning systems should be an integral part of such a framework. Training and awareness raising can also ensure proper installation, operation, and maintenance of air conditioning equipment and systems, and mandatory good practice with leakage control of the refrigerant during the use and end-of-life recovery. Improved data collection, research, and cooperation with manufacturers can equally help to identify emerging trends, technology needs, and energy efficiency opportunities that enable sustainable cooling.

References:

[1] IEA (2019). The Future of Cooling in China: Delivering on Action Plans for Sustainable Air Conditioning, International Energy agency (IEA), Paris.

[2] Wang X, Purohit P, Höglund Isaksson L, Zhang S, Fang H (2020). Co-benefits of energy-efficient air conditioners in the residential building sector of China, Environmental Science & Technology, 54 (20): 13217–13227 [pure.iiasa.ac.at/16823]

[3] Purohit P, Höglund-Isaksson L, Dulac J, Shah N, Wei M, Rafaj P, Schöpp W (2020). Electricity savings and greenhouse gas emission reductions from global phase-down of hydrofluorocarbons, Atmospheric Chemistry and Physics, 20 (19): 11305-11327 [pure.iiasa.ac.at/16768]

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis (IIASA).

How to advance climate policies towards a low-carbon economy

By Shorouk Elkobros, IIASA Science Communication Fellow

Assessing energy-related choices and the behaviors of households can help us transition to a low-carbon economy. How can research provide more effective decision-making tools to policymakers for better climate change mitigation policies?

We live at a defining moment for climate change, where today’s actions affect tomorrow’s reality. Every little climate-friendly decision counts. Whether we decide to insulate our houses, put solar panels on our rooftops, or invest in energy-efficient appliances. However, our personal and energy-related decisions vary based on our awareness, age, education, income, energy provider services, social norms, culture, and many other factors. Researchers are starting to pay attention to how this diversity is not well represented in the economic models that politicians use to plan climate change policies.

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Designing policies inspired by people

Households contribute an average of 70% of global greenhouse gas emissions. Limiting global emissions requires holistic policy approaches that take households’ behaviors and lifestyle decisions into account. Adding such a dimension can potentially upscale low carbon behavioral and social changes to national and global levels, which is fundamental to tackling climate change.

Worried about the future of the planet and motivated to support policymakers in designing better climate change mitigation policies, the authors of a recent study published in the journal Environmental Modeling & Software aspired to build bridges through interdisciplinary research. The study presented a novel interdisciplinary method that aims to integrate households’ energy behavior and social dynamics in climate-energy-economy models and thus help politicians design policies inspired by people.

“I have always been interested in the science-policy-society aspect of mitigating climate change. Climate change is a collective challenge that we need to address together to come up with better solutions for future generations,” notes study lead author Leila Niamir, a researcher jointly associated with the Mercator Research Institute on Global Commons and Climate Change, Berlin and the IIASA Transitions to New Technologies Program.

Better models for a better future

Climate change mitigation policies play a pivotal role in achieving ambitious environmental targets like the Paris Agreement or the Sustainable Development Goals (SDGs). To be able to formulate appropriate mitigation policies, decision makers need assessment tools to measure complex systems quantitatively. In the past decade, a variety of assessment tools have emerged, which have since been predominantly used to support climate change policy debates. In the study, Niamir argues that current assessment models are missing bottom-up and grassroots dynamics, they cannot project realistic variables of what households’ lifestyles and social movement are, and they therefore may not be sufficient to provide reliable information for policymakers.

There is a gap between what policymakers’ current assessment tools can offer and what social scientists and behavioral economists highlight as pro-environmental behavior and climate change mitigation movements. By adding this complex behavior and social perspective to the models, the researchers make it easier for policymakers to design future policies to accommodate different societal behaviors and lifestyles.

Niamir and her team presented a novel method for systematically upscaling grassroots dynamics by linking the best of both “top-down” macroeconomic computable general equilibrium (CGE) models and “bottom-up” empirical agent-based models (ABM). Their approach demonstrates that with computational ABM directly linked to survey data and macroeconomic CGE models, individual behavioral diversity and social influences can be considered when designing implementable and politically feasible policy options.

“We need better assessment tools to quantitatively explore the complex climate-energy-economy system, and reveal the potential of demand-side mitigation strategies. To see substantial changes, we need a mix of external interventions, from soft information policies aimed at raising awareness bottom-up, to financial incentives altering the macro landscape of energy markets and technological transitions. Only modular and integrated models can help policymakers quantitatively explore this complex system and plan for changes in the coming decades,” says Niamir.

Towards a low-carbon economy

We cannot tackle what we do not know. Pathways to a low-carbon economy future entail diminishing the growing discrepancy between mitigation policies and individual and collective behaviors. When redesigning our socio-environmental systems to mitigate climate change, we need to start looking at people as case studies rather than numbers. To transition to a low-carbon economy and accelerate decarbonization, policymakers must adopt novel models that integrate energy consumption, individual behavior, heterogeneity, and social influence into current assessment tools.

In 2019, IIASA and the Research Institute of Innovative Technology for the Earth (RITE), Japan co-organized an international workshop towards improved understanding, concepts, policies, and models of energy demand, where Niamir presented her research and received the young scientist award to continue and extend her research.

“Mitigating climate change indeed requires a massive effort from individual and social movements to advance national and international collaboration. Each individual small step towards shrinking our carbon footprint creates cascading changes in social behavior and consequently mitigates climate change,” Niamir concludes.

Reference:

Niamir L, Ivanova O, & Filatova T (2020). Economy-wide impacts of behavioral climate change mitigation: linking agent-based and computable general equilibrium models. Environmental Modelling & Software 134: e104839. [pure.iiasa.ac.at/16671]

Note: This article gives the views of the authors, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

Global hunger and trade under global warming

By Charlotte Janssens, guest researcher in the IIASA Ecosystems Services and Management Program and researcher at the University of Leuven and Petr Havlík, Acting Ecosystems Services and Management Program Director.

Charlotte Janssens and Petr Havlik write about their recent study in which they found that world trade can relieve regional impacts of climate change on food production and provide a way to reduce the risk of hunger.

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In a warmer world, decreasing crop yields and rising food prices are expected to strongly jeopardize the achievement of Sustainable Development Goal (SDG) 2 – ending global hunger. Climate change has consequences for food production worldwide, but there are clear differences between regions. Sufficient food is expected to remain available in the Northern hemisphere, while in regions such as sub-Saharan Africa or South Asia, falling crop yields may lead to higher food prices and a sharp rise in hunger.

In our recent publication in Nature Climate Change, we find that world trade can relieve these regional differences and provide a way to reduce hunger risks under climate change. For example, if regions like Europe and Latin America where wheat and corn thrive increase their production and export food to regions under heavy pressure from the warming of the Earth, food shortages can be reduced.

Global Hunger by 2050

The State of Food and Nutrition Security in the World 2020 reports that globally almost 690 million people were at risk of hunger in 2019. Many factors determine how global hunger will develop in the future, including population growth and economic development, as demonstrated in a study in Environmental Research Letters. Our article uses the “middle-of-the-road” socioeconomic pathway where population reaches 9.2 billion, income grows according to historical trends, and the number of undernourished people decreases to 122 million by 2050. Within this socioeconomic setting, we investigate the impact of different climate change scenarios and trade policies on global hunger by 2050.

The worst-case climate scenario of a 4°C warming leads to an extra 55 million people enduring hunger – a 45% increase compared to the situation without climate change. In a protectionist trade environment where vulnerable regions cannot increase their food imports as a response to climate impacts, this effect rises to 73 million. The largest hunger risks are located in South Asia and sub-Saharan Africa, with respectively a 33 million and 15 million increase in people at risk of hunger in the worst-case climate scenario.

Where barriers to trade are eliminated, “only” 20 million people endure food shortages due to climate change. While this number is high, it is a vast improvement on the 73 million people that would potentially be exposed to hunger without the suggested measures. In the milder climate change scenarios, an intensive liberalization of trade may prevent even more people from enduring hunger owing to global warming. Yet a liberalization of international trade may also involve potential dangers. If Asian countries increase rice exports without making more imports of other products possible, they could well end up with a food shortage within their own borders.

Mobilizing Investment

Our study shows not only that the challenge of ending global hunger is strongly determined by the extent of progress on SDG 13 (climate action), but also that achievement of SDG 2 (zero hunger) is affected by developments articulated in SDG 9 (resilient infrastructure). We find that international trade can relieve regional food shortages and reduce hunger, particularly where trade barriers are eliminated. Such trade integration requires phasing out import tariffs as well as the facilitation of trade through investment in transport infrastructure and technology. Especially in low-income regions such as sub-Saharan Africa infrastructure is weak. In its 2018 African Economic Outlook, the African Development Bank (AfDB) estimates that between USD 130 billion and 170 billion a year is needed to bridge the infrastructure gap in the region by 2025. Given that infrastructure finance averaged only USD 75 billion in recent years, and the largest contribution is coming from budget-constrained national governments, alternative financing through institutional and private investments could be crucial in the face of climate change.

Crisis and Protectionism

In times of crisis, countries are inclined to adopt a protectionist stance. For example, in the face of the current COVID-19 pandemic, several countries have temporarily closed their borders for the export of important food crops (see IFPRI Food Trade Policy Tracker for updated information). Some commentators warn that such measures can have large detrimental effects on food security. Our study finds that also in the context of climate change, a well-thought-out liberalization of trade is needed in order to be able to relieve food shortages properly.

Reference

Janssens C, Havlík P, Krisztin T, Baker J, Frank S, Hasegawa T, Leclère D, Ohrel S, et al. (2020). Global hunger and climate change adaptation through international trade. Nature Climate Change [pure.iiasa.ac.at/16575]

This blog post first appeared on the SDG Knowledge Hub website. Read the original post here.

Note: This article gives the views of the authors, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

Modeling ancient history to inform the future

By Marcus Thomson, IIASA alumnus and a researcher at the National Center for Ecological Analysis and Synthesis (NCEAS), the University of California, Santa Barbara

IIASA alumnus Marcus Thomson explains how what we have learnt about prehistoric farming cultures can be used to provide useful insights on human societal responses to climate change.

The climate of the western half of the North American continent, between the Rocky Mountains and the Pacific coastal region, is dry by European standards. The American Southwest, in particular, centered roughly on the intersection of the states of Colorado, New Mexico, Arizona, and Utah, is predominantly desert between high mountain plateaus. It is, and has always been, a challenging environment for farmers. Yet the prehistoric Southwest was home to complex maize-based agricultural societies. In fact, until the 19th century growth of industrial cities like New York, the Southwest contained ruins of the largest buildings north of Mexico — and these had been abandoned centuries before the Spanish arrived in the Americas.

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For more than a century, researchers have pored over data, from proxies of paleo-environmental change, to historiographies collected by explorers, to archaeology and computational models of human occupation, and produced a detailed picture of the socio-environmental, economic, and climatic conditions that could explain why these sites were abandoned. While details vary in fine-grained analyses of the various sub-groupings of peoples in the region, the big picture is one of societal transformation in adapting to climate change.

Also important is just how the climate changed during the period, because similar dynamics are expected to emerge in the future as a consequence of global warming. European historians point to a medieval era with generally warmer mean annual temperatures. In the Southwestern United States however, which is more sensitive to changes in drought than temperature, the period between roughly AD 850 to 1350 is known as the Medieval Climate Anomaly (MCA). The warm, dry MCA was followed by a long stretch of increased changes in the availability of water, known as the Little Ice Age (LIA). More frequent “warm droughts” at the end of the MCA, and generally increasing changes in water resources at the onset of the LIA, is thought to be a good analogy for future conditions in western North America.

When I had the good fortune to visit IIASA as a participant of the Young Scientists Summer Program (YSSP) in 2016, I worked with research scholars Juraj Balkovič and Tamás Krisztin to develop a model of ancient Fremont Native American maize. The Fremont were an ancient forager-farmer people who lived in the vicinity of modern Utah. We used a climate model reconstruction of the temperature and rainfall between AD 850 and 1450 to drive this maize crop model, and compared modeled crop yields against changes in radiocarbon-derived occupations – in other words, the information gathered from carbon dated artifacts that show that an area was occupied by a particular people – from a few archaeological areas in Utah.

© Galyna Andrushko | Dreamstime.com

Among our findings was that changes in local temperatures appeared to play a larger role in the lives, practices and habits of the people who lived there than changes in regional, long-term temperature conditions [1]. Later, while a researcher at IIASA myself, I returned to the subject with one of our coauthors, professor Glen MacDonald of the University of California, Los Angeles, using an expanded geographic range and a more sophisticated treatment of radiocarbon dated occupation likelihoods.

We used the climate model to reconstruct prehistoric maize growing season lengths and mean annual rainfall for Fremont sites. We found that the most populous and resilient Fremont communities were at sites with low-variability season lengths; and low populations coincided with, or followed, periods of variable season lengths. This study confirmed the important dependence on climate variability; and more importantly, our results are in line with others on modern smallholder farming contexts.

More details on our latest study [2] have just been published online in Environmental Research Letters (ERL). It will become part of an ERL special issue looking at societal resilience drawing lessons from the past 5000 years. Studies like these can give useful insights on human societal responses to climate change because these ancient civilizations are, in a sense, completed experiments with complex human-environmental systems. For decision makers, who must plan early to commit resources to offset the effects of future climate change on smallholder farmers in similarly drought-sensitive, marginally productive environments, these studies indicate that year-to-year climatic variability drives occupation change more than long-term temperature change.

References:

[1] Thomson MJ, Balkovič J, Krisztin T, & MacDonald GM (2019). Simulated impact of paleoclimate change on Fremont Native American maize farming in Utah, 850–1449 CE, using crop and climate models. Quaternary International, 507, pp.95-107 [pure.iiasa.ac.at/15472]

[2] Thomson MJ, & MacDonald GM (In press). Climate and growing season variability impacted the intensity and distribution of Fremont maize farmers during and after the Medieval Climate Anomaly based on a statistically downscaled climate model. Environmental Research Letters.

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

How COVID-19 complicates the journey for climate migrants

By Lisa Thalheimer, 2020 IIASA Young Scientists Summer Program (YSSP) participant in the Risk and Resilience and World Population Programs

Lisa Thalheimer shares her journey in researching climate-related migration in the age of the COVID-19 pandemic and the importance of taking mental health issues into account in climate science and the policy realm.

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COVID-19 has changed our idea of normal. These unprecedented, stressful times affect us all – some of us more than others. Fear and anxiety over a new disease without any promise of a vaccine anytime soon, global economic downturn, along with feelings of loneliness and emotional exhaustion due to the lockdown, can leave us mentally exhausted. Rates of depression and addiction-related suicide are in fact already on the rise among young people like myself.

Now imagine you are advised to stay at home, but you cannot do so because climate change has turned your entire life upside down: your house is no longer there, you have lost your job, your family or friends – you are likely to feel unhinged. This is a reality for many migrants across the globe. It is inevitable that existing migration patterns will be shifted beyond disasters alone. Cascading impacts form the still unfolding pandemic could compound. No matter if you are a migrant yourself or not, agency and the choice over the decision whether to leave your house or not, and the luxury to socially distance could potentially not be an option with a systemic shock like COVID-19.

These changes in circumstances have also affected me as a young scientist. I would have been in Laxenburg, getting to know my YSSP peers and IIASA colleagues, but this year’s journey has been rewritten – courtesy of the COVID-19 pandemic.

I was living in Oxford in the UK when I came to realise that mental health is a game changer in the way I manage my day, make decisions, my ability to care for my partner who suffers from Amyotrophic Lateral Sclerosis (ALS), and making progress on my PhD thesis. Everything felt more difficult. I was overwhelmed. I wanted to understand why this is the case. My interest soon evolved into researching the links between mental health and my PhD topic of climate-related migration.

For the article “The hidden burden of pandemics, climate change and migration on mental health”, I teamed up with an epidemiologist who specialises in mental health at my old university home, the Earth Institute in New York City. This research experience was an eye-opener, both personally and scientifically.

In our article, we focused on the US, as it has been hit hardest by COVID-19 – in mid-August, the number of COVID-19 cases exceeded five million. On top of this, depression and anxiety are already prominent among Americans, as is costly impacts from disasters. Hurricanes cost the US around US$ 17 billion every year, but estimates show a higher probability of extremely damaging hurricane seasons with climate change. We may know the impact of climate change on assets and on physical health, but what about mental health impacts?

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Although my coauthor and I come from different scientific disciplines, I soon came to realize that our scientific approach has a common denominator: systems thinking. Accounting for interconnections and cascading effects, our article shed light on different systems affected by COVID-19 and situations where mental health issues are likely to become increasingly prevalent in a changing climate. The article focuses on already vulnerable parts of the population, for example those who have been impacted by Hurricane Katrina or Hurricane Harvey – the latter of which has been made worse by climate change. The article illustrates how COVID-19 becomes a risk multiplier for climate migrants in three distinct case studies: key workers in New York as urban setting, seasonal migration dynamics, and disproportionate effects on black and Latino communities. Unrelenting effects include loss of employment, and a lower likelihood of being able to work from home or to have health insurance than white people.

A better understanding of the mental health-migration-climate change nexus can help absorb adverse mental health outcomes from COVID-19, which would otherwise compound. We however need to tackle systemic risks affecting mental health through synergies in research and policy, and an integrated intervention approach. Free mental health support for key workers through tele-therapy and mental health hotlines provide a practical way forward. Personally, I learned that climate migrants have been relentlessly resilient to systemic shocks. Nevertheless, with mental health issues, it becomes increasingly hard to maintain such resilience. With this commentary, I hope that mental health and interdisciplinary research finds its way in climate science and in the policy realm. We all need a clear mind to attain the Sustainable Development Goals.

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.