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.

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.

© Raul Mellado Ortiz | Dreamstime.com

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.

Mapping habitats in support of biodiversity research

By Martin Jung, postdoctoral research scholar in the IIASA Ecosystems Services and Management Program.

IIASA postdoc Martin Jung discusses how a newly developed map can help provide a detailed view of important species habitats, contribute to ongoing ecosystem threat assessments, and assist in biodiversity modeling efforts.

Biodiversity is not evenly distributed across our planet. To determine which areas potentially harbor the greatest number of species, we need to understand how habitats valuable to species are distributed globally. In our new study, published in Nature Scientific Data, we mapped the distribution of habitats globally. The habitats we used are based on the International Union for Conservation of Nature (IUCN) Red List habitat classification scheme, one of the most widely used systems to assign species to habitats and assess their extinction risk. The latest map (2015) is openly available for download here. We also built an online viewer using the Google Earth Engine platform where the map can be visually explored and interacted with by simply clicking on the map to find out which class of habitat has been mapped in a particular location.

Figure 1: View on the habitat map with focus on Europe and Africa. For a global view and description of the current classes mapped, please read Jung et al. 2020 or have a look at the online interactive interface.

The habitat map was created as an intersection of various, best-available layers on land cover, climate, and land use (Figure 1). Specifically, we created a decision tree that determines for each area on the globe the likely presence of one of currently 47 mapped habitats. For example, by combining data on tropical climate zones, mountain regions and forest cover, we were able to estimate the distribution of subtropical/tropical moist mountainous rain forests, one of the most biodiverse ecosystems. The habitat map also considers best available land use data to map human modified or artificial habitats such as rural gardens or urban sites. Notably, and as a first, our map also integrates upcoming new data on the global distribution of plantation forests.

What makes this map so useful for biodiversity assessments? It can provide a detailed view on the remaining coverage of important species habitats, contribute to ongoing ecosystem threat assessments, and assist in global and national biodiversity modeling efforts. Since the thematic legend of the map – in other words the colors, symbols, and styles used in the map – follows the same system as that used by the IUCN for assessing species extinction risk, we can easily refine known distributions of species (Figure 2). Up to now, such refinements were based on crosswalks between land cover products (Figure 2b), but with the additional data integrated into the habitat map, such refinements can be much more precise (Figure 2c). We have for instance conducted such range refinements as part of the Nature Map project, which ultimately helped to identify global priority areas of importance for biodiversity and ecosystem services.

Figure 2: The range of the endangered Siamang (Symphalangus syndactylus) in Indonesia and Malaysia according to the IUCN Red List. Up to now refinements of its range were conducted based on land cover crosswalks (b), while the habitat map allows a more complete refinement (c).

Similar as with other global maps, this new map is certainly not without errors. Even though a validation has proved good accuracy at high resolution for many classes, we stress that – given the global extent and uncertainty – there are likely fine-scale errors that propagate from some of the input data. Some, such as the global distribution of pastures, are currently clearly insufficient, with existing global products being either outdated or not highly resolved enough to be useful. Luckily, with the decision tree being implemented on Google Earth Engine, a new version of the map can be created within just two hours.

In the future, we plan to further update the habitat map and ruleset as improved or newer data becomes available. For instance, the underlying land cover data from the European Copernicus Program is currently only available for 2015, however, new annual versions up to 2018 are already being produced. Incorporating these new data would allow us to create time series of the distribution of habitats. There are also already plans to map currently missing classes such as the IUCN marine habitats – think for example of the distribution of coral reefs or deep-sea volcanoes – as well as improving the mapped wetland classes.

Lastly, if you, dear reader, want to update the ruleset or create your own habitat type map, then this is also possible. All input data, the ruleset and code to fully reproduce the map in Google Earth Engine is publicly available. Currently the map is at version 003, but we have no doubt that the ruleset and map can continue to be improved in the future and form a truly living map.

Reference:

Jung M, Raj Dahal P, Butchart SHM, Donald PF, De Lamo X, Lesiv M, Kapos V,Rondinini C, & Visconti P (2020). A global map of terrestrial habitat types. Nature Scientific Data DOI: 10.1038/s41597-020-00599-8 

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.