In this episode, we explore how climate risk could play out in Asia, both in physical hazards and in the socioeconomic impacts resulting from those hazards, and what measures can be taken to manage the risk.
Oliver Tonby: You are listening to the by McKinsey & Company. I am Oliver Tonby, your host and chairman of McKinsey Asia. In this series, we feature leaders from across the region to discuss the forces, the opportunities and the challenges that are shaping the future of Asia. Future of Asia Podcast
Mitigating and adapting to climate risk in Asia
Yuito Yamada: Hello everyone. Thank you very much for joining this session on Physical Climate Risk and Response here in Asia. My name is Yuito Yamada. I’m a partner from the Tokyo office, from the Sustainability Practice. I will be your moderator today. I am joined by two other distinct panelists: Mekala Krishnan, who’s the Senior Fellow of the McKinsey Global Institute, who also led the global work on this climate risk and response report, and a lot of others as well. Ruslan [Fakhrutdinov], who is the consultant who led this work specifically for Asia, and one of the key leaders in the climate discussion as well. We also have Tetsu Watanabe, who is on standby if you have any other questions during the session as well.
Mekala Krishnan: Let’s start by understanding how much the Earth has already been impacted by climate change. As Yuito mentioned, we did a piece of work of a global nature that we then followed on with Asia-specific research. As we did all of this work, we collaborated with various climate science institutions to understand the state of the art in our understanding of how climate change is manifesting, how much it’s manifested to date, and how much we could expect the climate to change going forward. As we analyzed that, our work shows that, firstly, the Earth has warmed. You see different parts of the Earth relative to a period that was pre-industrial times, about 1880s to 1900s, most parts of the Earth are warmer today than they were in the past, and that degree of warming actually varies. There are some parts that have warmed more so than other parts.
Climate hazards, whether that’s warming or things like flooding or droughts, are essentially linked with a particular place. And therefore, understanding your exposure to risk requires understanding the geography of climate hazards and their manifestation. It requires, therefore, a new toolkit for stakeholders to bring, whether that’s to build, whether that’s companies as they think about supply chain decisions, investors as they think about where to allocate that capital; we now need to make all of these decisions with an understanding of space.
The other aspect of climate risk is that it’s all about probabilities. What this chart demonstrates is an example of that. What you see in the white here are temperatures that the northern hemisphere have experienced in the 1961 to 1980 period. And you see that distribution is roughly an even distribution centered toward the left of the chart. What you then see in blue is how that distribution has shifted in recent times. You see the distribution of temperatures in the 2011 to 2015 period. So, a few things immediately stand out looking at this chart. The first is that the distribution has shifted, has gone from the left to the right. So, on average, the northern hemisphere is experiencing warmer summers. But what you also see is that tail events have become more likely. So, an events that used to occur in the past with a 0.2 percent probability is now occurring with a 15 percent probability. That’s about a 75 times increase in risk in the last approximately 50 years, by this measure of risk.
And this matters, again, when you think about all socioeconomic systems that exist around us. If you think about how insurance schemes are designed, they’re often designed to withstand events up to what are called a “100-year events.” If you think about infrastructure, it’s designed to withstand a 100-year storm or 200-year flood. But now, what constitutes a 100-year event? What constitutes a 200-year event is changing. Events that had a probability of say 1 percent, that 100-year event, might now be occurring at a 3 percent, or 5 percent, or 10 percent probability. And so, all these socioeconomic systems that exist around us, that have been designed for these tail events, now may fail with increasing likelihood, with increased severity. And it’s important to understand therefore not just how means are shifting, but also how tails are shifting.
Before we talk about the socioeconomic impacts—so what this means for people, for companies, for economies—let’s first understand what the science tells us about how hazards are going to evolve.
What we see is that across the board, across a whole range of different hazards, we expect hazards to intensify in Asia. This chart is showing, in the different columns, various forms of hazards today, 10 years from now in 2030, and then about 30 years from now, in 2050. We’ve examined all of these hazards in a scenario called RCP 8.5. So, climate science uses various forms of scenarios to understand the evolution of hazards in the future. We’ve chosen RCP 8.5, which is a higher emission scenario. The reason for choosing this one is, essentially, what we wanted to quantify with our research was what we call inherent risk. What’s the full inherent risk? Absent adaptation action, absent mitigation action, that there are socioeconomic systems to better understand the scale of the problem, to dimension the scale of the problem that we’re trying to solve.
So, let’s see what under this RCP 8.5 scenario we understand for different hazards. The first thing we see on the very top is temperature. And what is immediate, looking from the left to the very right, is that the reds on the chart increase, more and more regions see red, and the regions that see red see darker reds. So, essentially, we’re experiencing hotter temperatures, expecting to experience hotter temperatures across Asia between today and 2050. To give you a sense of some of that across various parts of Asia, China, Australia, the Indian subcontinent, these areas in particular could experience more severe impact and we expect a 2°C or higher warming in these geographies.
The second variable we looked at is something called lethal heat waves. Now, of course, different parts of the Earth experience heat waves today, but nowhere on the Earth have we experienced a heat wave so intense that healthy human beings sitting in the shade are affected. But what we find is that already today, there is some likelihood of that occurring. There’s a relatively low likelihood of that occurring and it’s relatively focused on some specific parts of Asia. But fast forward to 2050, we see more and more parts of Asia likely to experience such lethal heat waves. The probability is significantly increasing to the tune of 500 million to 700 million people potentially living in parts of India, Bangladesh, and Pakistan, that could experience some probability, some nonzero likelihood of such lethal heat waves occurring.
What we see is that across the board, across a whole range of different hazards, we expect hazards to intensify in Asia ... we see various forms of hazards today, 10 years from now in 2030, and then about 30 years from now, in 2050. We’ve examined all of these hazards in a scenario called RCP 8.5.
It’s not just about heat and temperature effects. We also see a variety of other kinds of climate hazards potentially manifesting in Asia. There are two examples here that are complementary to each other. The first is looking at drought and then the second is looking at the implications of that drought on water supply and water stress. And again, across the board, what we see is that there’s an intensification in many parts of Asia both of drought as well as of increased water stress. Now, of course, there are parts of Asia that could also experience decreased drought, experience increases in water supplies, but there are also significant parts that could experience quite a large increase in risk.
As illustrations of that, we can look at the drought measure: more than 80 percent of a decade could be spent in drought in parts of Australia. About 40 to 60 percent of a decade could be spent in drought in parts of China. Similarly, when we look at the water supply, the water stress measure, parts of Australia could experience up to a 70 percent decrease in water supply. Parts of China, on the other hand, could experience up to a 20 percent increase in water supply. So, again, this the point I was making earlier, that it’s really important to understand these forms of hazards as they are linked to a specific place. There’s a magnitude of the risk, and the increase of that risk could vary significantly by place.
We see two other examples, which is the flip side of droughts and water stress, increased rain and likelihood of precipitation. We have two different measures of that. The first is just looking at the measures of extreme rainfall. And the second is specifically looking at typhoons or hurricanes. And for both of these, again, we see an intensification of these hazards in different parts of Asia. For example, for extreme precipitation, we see that parts of Japan, China, South Korea, Indonesia, could see about a 3–4 times increase in the likelihood of what used to be a 50-year event. A 50-year event in the past is now 3 or 4 times as likely. And similarly, when we look at 100-year hurricane, parts of China, South Korea, and Japan could see a three-times increase in the probability of such a hurricane.
So, what does all that mean, all these different hazards that I’ve described? What does that actually mean for Asia? The way we’ve translated the implications of these hazards to a variety of socioeconomic systems is through the understanding of different thresholds. What do I mean by thresholds? Essentially, if you look at all the socioeconomic systems that exist around us, let’s start with physical systems as an example: the human body, food systems, physical assets, each of these systems have either evolved or been designed for specific climatic parameters. For example, when we think about where we grow different forms of crops, the geography of crop production or agricultural production has essentially been optimized for the specific climate in those geographies. Rice and wheat are grown in India because the climate of India is suitable for rice and wheat, as an example. But as the climate changes, even by very small amounts, those systems could start to fail.
So, let’s start with food systems. This shows the yields of the reproductive growth rate of corn or maize, and how that varies with air temperature. And what we find is that above about 20°C, we start to see a dramatic decline in the reproductive growth rate of this crop. We also see that on the very right when we think about physical assets. This is an example for a train station. What you see is that up to about 3 meters of flooding, there’s small increases in damages of this asset, but above 3 meters of flooding, there’s catastrophic damage to the asset; the damage increases from about 30 percent to 100 percent. Then you see a similar example all the way to the left, when we think about the human body. The human body essentially is able to function … the normal body temperature is about 37°C. As that body temperature starts to rise, the human body’s ability to function starts to diminish. We get more tired, we need to take more breaks, we work less productively.
But above a certain core body temperature, above 42°C, the human body, essentially, is unable to function. Human beings are at risk of fatality. And this is what I meant with my lethal heat wave example; above a certain temperature threshold, the human body will no longer be able to function, and we are expected to see increased likelihood of crossing those thresholds by 2030 and then by 2050 in parts of Asia.
Why am I talking about all this? The reason for all of this is as we think about translating hazards to their impacts, whether it’s on people, it’s on agriculture, or it’s on physical capital and infrastructure, it’s important to understand the thresholds, these tolerance parameters for all of these different systems. As we look to quantify the impact, what these thresholds also show is that impacts would be nonlinear and quite large. So, let’s try and understand how large some of these impacts could be. We looked at a range of different systems on livability and workability for the human system, physical assets and infrastructure of buildings, and physical capital, and then two forms of natural capital, both looking at food systems specifically, as well as natural capital more broadly. And we developed a range of metrics to think about the risks that each of these systems experience between now and 2050. This was essentially quite an extensive geospatial analysis we did, looking pixel by pixel across the Earth, understanding how hazards could evolve, understanding where people, economic activity, physical assets actually existed, and then these damage functions, the thresholds of all of these systems.
And putting that all together, what we essentially find is that across a range of these metrics, all parts of the world see an increase in risk. But that Asia maybe in some areas is expected to see more severe impacts than global averages. For example, when we look at livability and workability, we find that globally, about $4 trillion to $6 trillion of GDP is at risk by 2050 as a result of lower labor productivity as heat conditions rise. As I was saying, human body fatigues more easily, needs to take more breaks, the workers—in particular those in manual labor and outdoor work—could see labor productivity diminish, and as a result, GDP drop. So, while $4 trillion to $6 trillion of that impact will be felt globally, a substantial portion of that, about $2.8 trillion to $4.7 trillion, is in Asia. And that’s because of a few different reasons. Asia, on the one hand, is actually expected to see more severe increases in heat and humidity conditions. A lot of labor in Asia also is still engaged in manual activities that engage in outdoor work, and even accounting for some of the shifts we could experience between now and 2050, Asia is disproportionately exposed.
The same is true when we think about lethal heat waves. Most of the global population exposed to lethal heat waves lives in Asia: about 0.6 to 1 billion folks in Asia could be exposed by 2050 to rising heat waves. Similarly, when we look at physical capital and examine the amount of capital stock that could be damaged as a result of river flooding, rivers overflowing from extreme rain, about 75 percent of that damage, $1.2 trillion out of a global total of $1.6 trillion, is in Asia. When we look at food systems and natural capital, Asia’s numbers are roughly on par with global averages across the board. What this tells us is that Asia, like many other parts of the world, is expected to see an increase in risk. And that for certain types of risks, Asia is disproportionately exposed, particularly those to do with heat, humidity, and extreme rain.
So, I’ve presented kind of Asia in total, but how that breaks down across different parts of Asia actually looks quite different. What we did was examine a set of countries in Asia and looked at the patterns of the types of impacts that these countries could experience. And what they suggested to us when we took a look at these climate hazards and their evolution, as well as understood really the socioeconomic characteristics of these different countries in Asia, for example, the expected GDP growth, that essentially led us to five different categories of impacts in Asia across four different “types of Asia.” We identified one group called Frontier Asia; this is countries like India and Pakistan. And really a lot of the impacts here arise from heat and humidity increases. A lot of the impact that populations could experience have to do with lethal heat waves and GDP loss from outdoor work. There’s also a risk in this part of Asia from increased damage from river flooding.
The second category is Emerging Asia. This is countries like Indonesia and Vietnam. Again, many of the impacts have to do with heat. The lethal heat wave impact compared to Frontier Asia is more diminished but this group of countries also experiences significant GDP impacts as a result of rising heat and humidity conditions, and also, we see substantial amounts of capital stock at risk of river flooding.
Then we come to Advanced Asia; this is countries like Australia and Japan. What we find here is that in general, the degree of climate hazard intensification on average across these countries is not as large. In some pockets of these countries, of course, there could be larger impacts as we discussed in the previous slides related to Australia. But in general, this is a group of relatively lower-risk increase countries. And then finally, we put China as a separate category on its own, given the size of the country, as well as how different climatic conditions existed across different parts of China. We call this effect in China essentially a climatically heterogeneous set of impacts. There is expected to be the heat wave effect that I described as well as some of the GDP impacts from lost working hours. But these are expected to be in specific parts of China and other parts of China may be less exposed.
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Mekala Krishnan: So, let’s take another closer look at that. This is showing a similar view, where you see the breakdown as well across countries and you see the distribution across the different types of indicators that we described on the previous slides as well. We looked at impacts on livability and workability, impacts of food systems, physical assets, and infrastructure and natural capital. And you see similar patterns emerge, where the Frontier Asia group of countries essentially sees increases in risk across multiple indicators. These are the blues, particularly the darker shades of blues on the chart. Some of the most extreme impacts have to do with heat and humidity. Emerging Asia, again, seeing a similar pattern, but less intense impacts of heat and humidity. These two groups of countries, if you think about the implications for Asia as a whole, the groups of countries in these two geographies in particular are ones where Asia is expected to see significant economic growth in the coming years. So, if Asia is to meet that aspiration, managing physical risk in the countries is going to be especially important. And then Developed Asia, as I was describing, across many indicators is seeing less of an increase in risk, but for a few indicators.
For example, when we look at water stress in Australia, there are still pockets of risk even in this group of countries. And then finally, for China, as we described, there are impacts potentially on livability and workability, as well as some implication on natural capital. But I think the story for China is that impacts actually vary quite significantly across different geographies and understanding the spatial characteristics is particularly important in this country. So, with that, I’ve given you kind of the macro perspective.
Let’s think about what this means for people. We’ve talked about a few implications in terms of GDP, in terms of people impacted by heat waves. But one of the key characteristics of our research suggests that climate risk is regressive in nature. You see an illustration of that where on the Y axis, what we’ve shown is how much GDP could be at risk from rising heat and humidity. What you see on the X axis is per capita GDP levels. And in general, what the trend here shows is that countries with lower per capita GDP levels are also the ones that could see a higher magnitude of share of GDP at risk. What this essentially means is that the poorer parts of the world are more exposed. They’re more exposed because they rely more on outdoor work and the natural world. They’re more exposed because oftentimes they are at a more climate extreme. So, understanding how to manage this risk requires us to recognize that this is a regressive form of risk and the more vulnerable parts of the world are among the most exposed.
The next bit of analysis that Ruslan will take us through is pivoting from the more macro perspective, the more country-based perspective, to look at implications in specific parts of Asia. We’ve looked at a set of case studies that cover different geographies, different asset types, different types of impacts, to really understand not just the magnitude of the risk as I’ve described, but also some of the nature of the stress, the way it could manifest in different parts of Asia. So, let me it hand over to Ruslan now. Thank you.
Ruslan Fakhrudtinov: Mekala, thank you. Let me briefly cover select case studies that illustrate exposure to climate change extremes in proximity of various systems to the physical thresholds, which Mekala has just introduced. To start with, let’s consider the impact of extreme heat and humidity on workability in India. An analysis reveals that already by 2030, almost a quarter of all the working hours is expected to be lost as a result of heat and humidity in India, with northern parts of the country affected the most. This, in total, would lead to up to 10 percent of GDP loss by 2030, with industries that rely on outdoor working hours being hit the most. And those industries are, for example, agriculture, mining, and construction. Given that those industries typically provide employment to low-skilled, and therefore least-protected parts of the workforce, the socioeconomic effects of increased heat and humidity and decreased workability could be severe. Longer term, in the 2050 horizon, up to a third of outdoor working hours are expected to be lost, but the socioeconomic impact on the longer term, in the 2050 horizon, would be less severe, given the reduction in the number of working hours.
Another interesting case study, which we have considered is the impact of floods in Tokyo. So, for the purpose of the analysis, we have taken a compound 100-year flood event, which is basically a combination of rainfall, storm surge, and ravine flooding, and consider its frequency and impact today. So, what we found out is that both frequency and impact of flooding in Tokyo is increasing, meaning that floods are becoming more frequent and more intense by 2050. So, in terms of potential impact of a 100-year flood, we’re talking 2050, it will be more than 1.5 times deeper than today, and we’ll have more than two times bigger damage than today.
An analysis reveals that by 2030, almost a quarter of all the working hours is expected to be lost as a result of heat and humidity in India, with northern parts of the country affected the most.
Here, what’s interesting is that all impacts are calculated under existing levels of flood protection infrastructure, implying that even Tokyo, a city with world-class flood protection facilities, is expected to see significant growth of potential damage. And basically, other cities also located in areas of growing countries, for example, Vietnam or Bangladesh will be hit even more, because here the level of action is obviously lower than in Tokyo.
The other topic we have looked at is wildfires in Australia. Climate science here predicts that wildfires will become more frequent both by 2030 and 2050. So, by 2050, almost a third of the country will experience and will see a more than 20-day increase in the number of high fire-risk days per year. Here, the most interesting part is that the most populated and capital-dense areas in the southeastern part of the country will be affected the most and we’ll see the steepest increase in the number of high fire-risk days. Last but not least is that climate science also predicts that climate change will intensify degradation of natural capital in Asia and those impacts will manifest across different systems of natural capital. Glaciers, with up to 40 percent decrease of glaciers in the Himalayan region in the next 30 years. Oceans, with up to 90 percent degradation of coral reefs, etc. And external estimates suggest that degradation of natural capital due to climate change could lead to more than $4 trillion accumulated GDP loss by 2050 in Asia overall, which is basically more than twice bigger than GDP of South Korea as of today.
Case studies, which we have just considered on climate change extremes as well as the macroeconomic analysis presented earlier revealed seven key characteristics of climate change. So, first, climate change is increasing across Asia. Second, climate change is spatial, meaning that climate hazards manifest locally, and the risk and the impact of those climate risks vary between countries and also within. Climate risks are also nonstationary, meaning that further warming is already locked in up to the 2030 horizon, given the existing emissions. And as Mekala has described, climate risks are nonlinear, meaning that once the physical thresholds are breached, the impacts of climate risks are nonlinear.
Apart from that, they are systemic, meaning that there are not only the physical risks of climate change, but also other types of risk, given that all systems are interconnected. Then, as we have seen on the example of the interdependency between the impact on GDP in countries, we see that climate risks are aggressive, meaning that the poorest countries will be affected the most. And overall, we are underprepared for climate risk, given the pace and scale of adaptation, as well as the mitigation. We’ll need to significantly increase those to meet the climate risks.
Yuito Yamada: Mekala, there was a question that came in around the analysis implications of considering wet-bulb temperature. That came through from people.
Mekala Krishnan: Wet-bulb temperature is essentially a measure of temperature that includes both actual temperature levels and air temperature levels, but also accounts for humidity levels. So, the human body’s ability to function is both a function of heat levels themselves, temperature levels themselves, but also humidity levels, because that affects our body’s ability to cool. And so typically, when considering analyses, like the regional heat wave analyses I mentioned, or the analysis of worker productivity, it’s important to include a measure that is not just measuring dry air temperatures, but heat and humidity levels. And so, all of our analysis actually considered this measure of wet-bulb temperature that factored in both dry air temperatures as well as humidity levels.
Ruslan Fakhrudtinov: Up until now, we have been mainly discussing the socioeconomic impact and characteristics of climate change, but there is also another critical subject that often lacks attention: it’s basically how we manage parameters. Fundamentally, the paradigm is quite simple, but very hard to map. There are three primary elements of the paradigm and how to manage it. The first one is to embed climate risks into all decision making, meaning that we need to understand, measure, monitor, and base our decisions on the climate. Second is to adapt the existing climate risks. And the third one is obviously to decarbonize the use of resources to reduce future risk. So, integration of climate risks in decision making at various organizational layers requires a robust managerial framework with your processes to identify, measure, and monitor climate. At the top of those processes, in turn requires an organization with proper talent, skills, and capabilities, governance mechanisms, with corresponding policies and decision making authority, and of course, enablers, such as availability of data, technology, and more importantly, fostering a culture at the organization to take climate change seriously, and base decisions on them.
But I think the good news for Asia is that it’s uniquely positioned to respond to growing climate risks from an adaptation and mitigation perspective. So, being more heavily exposed to socioeconomic impacts of climate change, Asia needs to accelerate the pace and scale of adaptation. Here we have some key elements to do that. The first ones are investments to close the investment gap for adaptation. The other one is sharing best practice, with Asia-wide sharing of best practices. And the third one, which is probably one of the most important ones, is to attract private capital in financing of adaptation measures and to also have some other metrics.
Apart from that, Asia could definitely lead the global mitigation efforts, given its share in global emissions, as well as massive upcoming infrastructure investment. And basically, that can use the four primary levers. The first one is the shift from coal to renewable energy in power mix, the other one is decarbonizing industrial operations, and to advance employment of CCUS. The other, to transform agriculture and forestry, to preserve forests, and to make the agriculture more efficient and less carbon-intensive. And last but not least, is to electrify the daily lives and decarbonize road transport and buildings.
Yuito Yamada: I see one category of questions around RCP 8.5. Is the work being published using some scenarios other than RCP 8.5? Why are we using RCP 8.5? Any reasons? And is this becoming McKinsey’s base case now? That’s one sort of question. And then secondly, there is also a question around what is your view on increasing geopolitical risk with climate change? Perhaps Mekala, you can take those two and I’m happy to add on together with Ruslan. Let’s start off with that.
Mekala Krishnan: Sure. These are great questions to kick us off. RCP 8.5; it’s great that so many people have asked this question because it’s actually one that was quite an important design decision that we made. So, one of the things I omitted to say as we kicked off the work is the work was a collaboration with between the McKinsey Global Institute and Sustainability Practice and Risk Practice, and one of the standard approaches in risk management is to evaluate what is called inherent risk. It’s risk, absent action to manage the risk, because it gives you a sense of the full scale of the problem that you need to manage. The main reason for taking RCP 8.5 was not because we believe it’s a base case and I think we very explicitly avoid using the language of base cases for business as usual, but rather to say let’s understand the full inherent risks, serious gaps, and adaptation and mitigation to understand the scale of the problem that we’re looking to solve.
I think the other couple of points to make related to RCP 8.5, it has, I would say quite rightly so received a lot of critique. But it’s important to understand where that critique is: it’s really in the second half of the century where RCP 8.5 is being critiqued for having “unreasonable results.” It’s really important to actually recognize that by 2050, what RCP 8.5 gets you to is a 2.3°C world. So, it’s not a crazy hot world. It’s actually somewhat in line with thinking about managing a 2°C target. I think the other thing that’s important to remember with this choice of scenario is that the alternate choice that people often use is something called RCP 4.5. And essentially, what RCP 4.5 at least from a temperature standpoint does is it delays the RCP 8.5 values by about 15–20 years. So, I think for all of these reasons, what we felt was that choosing RCP 8.5 allowed us to get a sense of the bounds of the problem. It allowed us to better understand under other RCPs, how far back would it push some of these impacts, and really understand the scale of the challenge that we’re looking to solve.
To the question on geopolitical risk, that’s a great question. We are typically not a policy shop or an entity that thinks a lot about geopolitics. There are a few points I would make that are related to how country risk is likely to evolve and the implications for the world. I think, firstly, as we said a few times in this presentation, of course, climate risk is spatial in nature. It’s linked to specific geographies. But as Ruslan also mentioned, climate risk is also simultaneously systemic. What that means is that risk in one part of the world is unlikely to stay in that part of the world. If you think about things like global supply chains, as we’re all experiencing right now with the pandemic, risk in one part of the world can easily spread to other parts of the world, as bottlenecks are created in global production. And that’s the one type of manifestation you could also see with climate risk.
So, it’s quite important to remember that while specific countries may be more exposed in a globalized, connected world, risk doesn’t necessarily stay in one place. And in this globalized, connected economy, you are exposed not just because of your direct risks, but also your indirect risk, in your supply chain, in your customers, in your distribution channels. So, even if you’re a country that’s not directly at risk, you are likely exposed to some form of risk. And it’s important to recognize and assess what that form of risk actually looks like for you.
Yuito Yamada: Yeah. Maybe just two quick questions, Ruslan, it might be helpful for you to get. Why did we choose some countries versus some countries who are not included in the study? Maybe that’s a quick question that you could answer. And there’s also a question around GDP impact. When we looked at the GDP impact that you account for in the second or third deliberative events, flooding in one country, etc., how do we take that. Maybe we quickly go from there, and then maybe there’s a bigger question that’s coming in. Ruslan, do you want to answer a few of them?
Ruslan Fakhrudtinov: Yes. So, for the first question, we follow a very simple approach. We basically do primary review. The first one is that we’ve taken the countries that constitute more than 95 percent of GDP and population in Asia. And second, for some of the smaller countries, it was hard to estimate some of the socioeconomic impact as well as the climate hazards themselves, given the geospatial resolution of the climate apps. That’s basically the approach to the country selection.
Yuito Yamada: Yeah. Very good. Do you want to say one word on the GDP impact?
Mekala Krishnan: Yeah, that’s a great question. I should clarify that the GDP impacts resize was specifically for workability as an indicator. So, the impact of heat and humidity particularly on outdoor and manual work. We did not attempt to do an extensive or expansive GDP calculation exercise. Part of the reason for that goes back to this nonlinearity point that we have made a few times. Our approach focused on better understanding the nature of the risk, the magnitude of the risk, for specific indicators and specific parts of the world, because our sense was that rather than the approach followed by a lot of economists, which tends to be more macro in nature, and trying to assess the GDP impact, our contribution would really be the more micro focus. So, understanding how specific hazards in specific geographies could impact specific socioeconomic systems.
The nonlinearity actually implies that estimating these GDP impacts is actually really hard. So, for example, imagine if there is a severe heat wave of the kind that we’ve described or imagine if there is catastrophic flooding in specific geographies that are vital for global supply chains, estimating how system-level failure could occur as we’re also, by the way, experiencing with a pandemic, estimating a magnitude of loss from events of this kind is actually quite challenging to do analytically and much more suited to more qualitative scenario-based analysis. And for all of those reasons, we chose to rather focus our efforts more on the nature, understanding the nature of the risk, and highlighting the more micro impact versus the more macro impacts.
Yuito Yamada: Very good, very good. Thank you for submitting a lot of questions. There are some more questions coming in. I think, Mekala, maybe a quick one, you could look into this. Disease and connections with climate risk, I think we looked at it a little bit. Number two, there’s also a question around, what can banks do to tackle climate risk? What are implications for credit risk? What are the capabilities required? What is maybe an institutional approach to this? And thirdly, how can technology play a role here? There’s also a question around what is the role of government versus a consumer? Something about the diseases, number one. Number two, about the banks. And number three, technology and consumer versus government would be great to hear.
Mekala Krishnan: Yes, disease is something we looked at a little bit in the research, not extensively, because we aren’t epidemiologists. But essentially, there is a variety of research out there that suggests that with shifting climatic conditions, there are certain disease vectors that could shift. Things like dengue, West Nile virus, etc. I think also interestingly, and importantly, there are a variety of other kinds of health impacts that are also important to keep in mind. So, for example, things like the rising prevalence of kidney failure and kidney disease as a result of heat and humidity conditions, things like impacts on human health and safety as a result of flood conditions. I think shifting disease vectors is one part of it but there’s also a variety of other health impacts that could occur as a result of climate change.
For many of these health impacts, it’s important to recognize that what climate change does is act as a threat multiplier. In many instances, it is not, in and of itself, introducing the disease variable or the morbidity, mortality variable. In some instances it is, but most of the time, what climate change is doing is it’s increasing the threat, increasing the risk of already pre-existing conditions. I think the second question had to do with banks. That’s a really interesting question. We’re getting a lot of interest on this topic from financial institutions across the world. I think one of the largest pieces of momentum on this topic has come from banks treating this, as it should be, as a financial risk to be evaluated. In many jurisdictions across the world, what we’re starting to see is regulators requiring banks to do climate stress tests. Many of you may have heard of the Bank of England’s climate stress test that is underway for 2021. And so, as banks think about this, there’s certainly stress-testing muscles that will need to be built that incorporates climate risk assessments. Some of that will come with understanding physical risk and physical exposures of the bank portfolio to rising hazards. The most common example of course, are things like exposure of real estate to flood hazard. But of course, banks are also interested in thinking about their exposure to transition risks.
The types of capabilities being built are understanding how new forms of data need to be integrated into the stress-testing process, things like climate science data, things like climate scenarios, understanding how the existing stress-testing infrastructure needs to be expanded, for example, to do scenario expansion, to do downscaling of existing scenarios, to incorporate climate, and then thinking about how input into credit risk models may need to be adapted to reflect both macro risks from climate change, but also micro risks from climate change in specific jurisdictions. And then the last question around technology. I think this is a great point. And I think as Ruslan was teeing up on one of the slides toward the end, we really see three different imperatives for stakeholders. One is to integrate climate risk into all decision making, whether you’re a city thinking about urban planning, a company thinking about where to locate your supply chain: all of these decisions now need to be made with the climate of the future in mind.
Adapting to manage existing climate risk ... Climate science tells us that risk for the next 10 years is locked into the system from past emissions. So, regardless of what we do on mitigation action, some amount of risk we need to manage. Finally, mitigating to avoid the buildup of it. I think technology can play a role in all three.
The second is adapting to manage existing climate risk. Climate science tells us essentially that risk for the next 10 years is locked into the system from past emissions. So, regardless of what we do on mitigation action, some amount of risk we need to manage. And then finally, mitigating to avoid the buildup of it. I think technology can play a role in all three. As one example, where we’re seeing a lot of attention and momentum right now is thinking about climate data, making kinds of climate data fundamentally accessible to everyone. So, right now, it’s largely the realm of climate scientists. But what are technological solutions and tools that make these data, these maps accessible to everyone? A second example, which is also gaining a lot of traction, is how do we do emissions assessments, and track emissions? Maybe through ERP software, the same way we track supply chains and customer relations. And what’s the technology solution that actually allows, say a large consumer goods company to know that its supply chain is net-zero, and how can we actually use technology to create that kind of transparency, both for the consumer goods company, but also eventually the end consumer?
And then finally, of course, a whole range of technology solutions, as we think about the nuts and bolts of adaptation and mitigation. I think technology can both provide a tool to enable some of these measures, but also actually the solution itself. I’m actually quite excited and optimistic about various forms of technological solutions to this problem.
Yuito Yamada: Very good, thank you. Ruslan and Mekala, there’s also a question around water stress. They wanted to get maybe just a bit of elaboration in terms of the risk on water stress when it comes to Asia once again. And then there’s also a question around agriculture, which I would answer, in terms of what transformed agriculture looks like. If you could take the first one on water stress. Let me start off with agriculture side. I think, number one, when you look globally, there’s actually a few breadbaskets around the world. There are probably five or six locations that basically is 60 –70 percent of the production when it comes to big crops like soy and corn. Number two, I think there are going to be areas that are going to see increased productivity versus decreased productivity. So, I think we just need to be probably managing and trying to look at the portfolio of the places that we are actually going to produce in the future.
And finally, I think, with some of the unproductivity that Mekala was mentioning in the beginning, the threshold effect, for agriculture in the future, there’s going to be times where we have overproduction versus less production. And I think the next generation of agriculture needs to look through the supply chain, broadly, in order to adjust in terms of having the right logistics and storage to ensure that there’s going to be big years versus less years, etc. So, that’s something that the sector itself needs to probably be a little bit more clever in managing in the future. For water stress, Ruslan and Mekala, any comments on that point when it comes to Asia?
Ruslan Fakhrudtinov: In terms of, as we have mentioned previously, all climate has its base, meaning that the impact may be different across the globe. And I think for the water stress, the two primary locations we see being the most affected in the future, one is Australia, and the other one is South Korea. And for the purpose of the analysis, when we look at water stress, we assume that demand for water stays the same, so it doesn’t change over time.
Mekala Krishnan: Yeah, and just building on that. We’ve referred to the measure as water stress occasionally, but generally, the measure is a measure of water supply. A lot of what is discussed has to do with water stress in Asia, as Ruslan was saying, is due to expectations of substantially increased demand going forward, as well as poor water management practices with existing water supply.
Yuito Yamada: On behalf of McKinsey Sustainability Practice as well as the McKinsey Global Institute, I’d like to say a huge thank you to everyone who has participated here. Thank you very much. And also, thank you very much for the very interactive questions. We hope that you found the content informative, and we are going to send out more emails about the session itself and the upcoming report as well. So, we would appreciate if you could help out in sharing any of your feedback to the session. And thanks again, once again, to Mekala and Ruslan for presenting, and all the people who have attended and came up with questions. Thank you very much, everyone.
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