1 00:00:00,080 --> 00:00:19,320 Speaker 1: Welcome to zero. I am Actra Tarti this week water scarcity. 2 00:00:20,000 --> 00:00:22,799 Speaker 1: We perhaps take for granted how critical access to water 3 00:00:23,040 --> 00:00:26,360 Speaker 1: is for the future of life on this planet, not 4 00:00:26,440 --> 00:00:28,600 Speaker 1: just for people around the world to quench their thirst 5 00:00:28,840 --> 00:00:32,400 Speaker 1: and have access to good sanitation, but also for the 6 00:00:32,440 --> 00:00:36,559 Speaker 1: global economy. Climate change is caused by the accumulation of 7 00:00:36,600 --> 00:00:39,919 Speaker 1: green ass castles in the atmosphere, but mostly felt by 8 00:00:40,000 --> 00:00:43,920 Speaker 1: humans through the force of water too much in storms 9 00:00:43,920 --> 00:00:48,760 Speaker 1: and floods, to little in droufts. From agriculture to e commerce, 10 00:00:49,159 --> 00:00:52,960 Speaker 1: water access is central to so many industries, and those 11 00:00:53,000 --> 00:00:56,560 Speaker 1: industries are likely to feel pressure as climate change drives 12 00:00:56,680 --> 00:00:59,960 Speaker 1: water scarcity. In the years to come. By t thirty, 13 00:01:00,000 --> 00:01:03,440 Speaker 1: the fresh water demand is expected to outpace supply by 14 00:01:03,600 --> 00:01:08,360 Speaker 1: forty percent. It's a challenge, but also an opportunity. That's 15 00:01:08,360 --> 00:01:12,639 Speaker 1: what Bloomberg Intelligence researcher Melanie Ruas says. She's co authored 16 00:01:12,640 --> 00:01:15,120 Speaker 1: a new report on water scarcity, and some of the 17 00:01:15,160 --> 00:01:18,839 Speaker 1: examples she's shared on just how much financial impact companies 18 00:01:18,880 --> 00:01:22,440 Speaker 1: are already seeing as a result of water scarcity really 19 00:01:22,480 --> 00:01:26,039 Speaker 1: surprised me. She told me why investors now have enough 20 00:01:26,120 --> 00:01:29,560 Speaker 1: data to start to include water risks as they make 21 00:01:29,640 --> 00:01:45,200 Speaker 1: investment decisions. Melanie, welcome to the show. 22 00:01:45,760 --> 00:01:47,400 Speaker 2: Thanks so much for having me. It's a pleasure to 23 00:01:47,400 --> 00:01:47,720 Speaker 2: be here. 24 00:01:47,880 --> 00:01:50,520 Speaker 1: Now. Water scarcity is not a new issue, but it 25 00:01:50,600 --> 00:01:54,160 Speaker 1: is certainly becoming a more alarming issue around the world, 26 00:01:54,720 --> 00:01:57,240 Speaker 1: and your job is to dig into areas where investors 27 00:01:57,400 --> 00:02:01,720 Speaker 1: need more information to make decisions. What happened last year 28 00:02:01,760 --> 00:02:04,000 Speaker 1: that made you decide to focus on the issue of 29 00:02:04,120 --> 00:02:05,040 Speaker 1: water scarcity. 30 00:02:05,200 --> 00:02:08,919 Speaker 2: Yeah, absolutely, great question. You know, like you alluded to, 31 00:02:09,240 --> 00:02:13,640 Speaker 2: water scarcity is no longer a distant threat. It's a 32 00:02:13,760 --> 00:02:19,600 Speaker 2: present day financial and operational risk that companies across sectors 33 00:02:19,639 --> 00:02:23,880 Speaker 2: and globally are already facing. You pointed to some scary 34 00:02:23,919 --> 00:02:26,960 Speaker 2: stats of how demand for fresh water is expected to 35 00:02:27,000 --> 00:02:30,400 Speaker 2: outpace supply by forty percent by twenty thirty. That's only 36 00:02:30,520 --> 00:02:34,200 Speaker 2: five years from now, and up to seventy trillion dollars 37 00:02:34,200 --> 00:02:37,680 Speaker 2: of global GDP is at risk due to water stress, 38 00:02:38,040 --> 00:02:41,720 Speaker 2: you know, according to the World Resources Institute. So in 39 00:02:41,760 --> 00:02:45,160 Speaker 2: addition to overuse, to your point, climate change is also 40 00:02:45,240 --> 00:02:48,600 Speaker 2: a driver here. We have hotter, drier climate driving more 41 00:02:48,639 --> 00:02:51,720 Speaker 2: water demand and at the same time supply shrinks. This 42 00:02:51,840 --> 00:02:56,360 Speaker 2: is really contributing to that imbalance. So we're seeing this 43 00:02:56,520 --> 00:02:59,640 Speaker 2: risk manifest in real time. But I want to also 44 00:02:59,639 --> 00:03:04,360 Speaker 2: stress it's also in different ways. So in Mexico Constellation Brands, 45 00:03:04,440 --> 00:03:09,359 Speaker 2: you know, an alcoholic beverage producer abandoned a merely completed brewery, 46 00:03:09,400 --> 00:03:12,480 Speaker 2: taking a six hundred and sixty million dollar right down 47 00:03:12,760 --> 00:03:15,640 Speaker 2: because of water concerns. You know, the company had to 48 00:03:15,639 --> 00:03:18,320 Speaker 2: build a new plant six hundred miles away, which adds 49 00:03:18,480 --> 00:03:22,720 Speaker 2: logistics costs and supply chain complexities. But there's also you know, 50 00:03:22,840 --> 00:03:26,640 Speaker 2: things happening for semiconductors, like look at semiconductor makers in 51 00:03:26,960 --> 00:03:31,920 Speaker 2: Taiwan where water shortages have become a recurring issue. You know, 52 00:03:32,040 --> 00:03:37,520 Speaker 2: have been trucking in water and TSMC, Taiwan Semiconductor manufacturing Company, 53 00:03:38,080 --> 00:03:41,720 Speaker 2: estimates that over half a billion dollars in revenues at 54 00:03:41,840 --> 00:03:45,200 Speaker 2: risk due to drought. So these examples really highlight that 55 00:03:45,360 --> 00:03:50,000 Speaker 2: water risk isn't theoretical, it's already affecting companies, their bottom 56 00:03:50,040 --> 00:03:53,520 Speaker 2: lines and really their ability to operate. So investors need 57 00:03:53,560 --> 00:03:58,040 Speaker 2: to understand which industries and businesses are most exposed to 58 00:03:58,200 --> 00:04:03,040 Speaker 2: these challenges, and in the same way, businesses must adapt 59 00:04:03,560 --> 00:04:05,480 Speaker 2: or face financial consquences. 60 00:04:06,080 --> 00:04:08,320 Speaker 1: You know, so you talked about food and beverage. You 61 00:04:08,400 --> 00:04:11,720 Speaker 1: talked about semiconductor things you wouldn't usually I mean food 62 00:04:11,720 --> 00:04:14,760 Speaker 1: and beverage. Yes, of course there's water involved, but semiconductors 63 00:04:14,800 --> 00:04:18,520 Speaker 1: people typically don't think about the use of water. But 64 00:04:18,560 --> 00:04:22,040 Speaker 1: there are other industries where water isn't the primary focus, 65 00:04:22,120 --> 00:04:24,680 Speaker 1: and yet it can bring things to a halt. So 66 00:04:24,960 --> 00:04:28,600 Speaker 1: I'm thinking power plants exact, natural gas pop plants, coal 67 00:04:28,680 --> 00:04:31,560 Speaker 1: pop plants, any thermal power plant needs a lot of water. 68 00:04:31,800 --> 00:04:34,920 Speaker 1: But tell me more, also about AI. There is a 69 00:04:35,000 --> 00:04:38,000 Speaker 1: huge amount of water need for AI data centers, right. 70 00:04:38,160 --> 00:04:42,040 Speaker 2: Yep, exactly that. You know, water risks really shows up 71 00:04:42,080 --> 00:04:46,080 Speaker 2: in different ways across industries. To your point, Yes, there's 72 00:04:46,160 --> 00:04:51,400 Speaker 2: obvious water intensive industries, agriculture, peril, power, the less obvious. 73 00:04:51,480 --> 00:04:54,080 Speaker 2: So I hinted at semiconductors. You know, can talk a 74 00:04:54,120 --> 00:04:57,520 Speaker 2: little bit about that. How manufacturing chips require one point 75 00:04:57,560 --> 00:05:00,680 Speaker 2: four to one point six Leaders of water, leader of 76 00:05:00,760 --> 00:05:05,080 Speaker 2: ultrapure water use. Also, forty percent of semiconductor plants announced 77 00:05:05,080 --> 00:05:08,440 Speaker 2: since twenty twenty one are being built in water stressed areas, 78 00:05:08,560 --> 00:05:13,040 Speaker 2: including Arizona, where concerns over water access are already emerging. 79 00:05:13,440 --> 00:05:16,719 Speaker 2: But to your point, something that's not so obvious data 80 00:05:16,720 --> 00:05:19,680 Speaker 2: centers generate a lot of heat. They need cooling, and 81 00:05:19,839 --> 00:05:23,920 Speaker 2: water based cooling is generally the most efficient, but it 82 00:05:24,000 --> 00:05:27,960 Speaker 2: is water base and so AI driven data centers. They've 83 00:05:28,080 --> 00:05:31,400 Speaker 2: used almost two billion gallons of water in twenty twenty 84 00:05:31,400 --> 00:05:34,000 Speaker 2: three in Virginia alone. You know, we mentioned this in 85 00:05:34,040 --> 00:05:37,840 Speaker 2: the report, a sixty four percent increase since twenty nineteen. 86 00:05:38,440 --> 00:05:42,520 Speaker 2: You have companies like Microsoft and AWS Amazon Web Services 87 00:05:42,520 --> 00:05:46,440 Speaker 2: that have set water positive targets for twenty thirty, meaning 88 00:05:46,480 --> 00:05:50,080 Speaker 2: they're replenishing more water than they're using. But the scale 89 00:05:50,120 --> 00:05:53,359 Speaker 2: of water use in this industry is enormous, and you know, 90 00:05:53,440 --> 00:05:57,839 Speaker 2: water scarcity is already reshaping industries and forcing companies to 91 00:05:57,960 --> 00:06:01,960 Speaker 2: really rethink sourcing, product and expansion plans. 92 00:06:02,800 --> 00:06:07,200 Speaker 1: So in typical decisions that investors are trying to make 93 00:06:07,480 --> 00:06:11,599 Speaker 1: about which company to invest in and understanding what risks 94 00:06:11,920 --> 00:06:14,679 Speaker 1: the companies that they have in their portfolio might be facing. 95 00:06:15,240 --> 00:06:18,880 Speaker 1: Climate change and carbon dioxide features quite high in these 96 00:06:19,000 --> 00:06:23,440 Speaker 1: environmental social governance metrics. But on the environment, water is 97 00:06:23,560 --> 00:06:26,480 Speaker 1: kind of now getting to the point where there's reporting happening, 98 00:06:26,480 --> 00:06:29,520 Speaker 1: and with your report and others that have come around 99 00:06:29,720 --> 00:06:32,880 Speaker 1: water scarcity, it's starting to become an issue that is 100 00:06:32,920 --> 00:06:39,240 Speaker 1: being highlighted. Yet are there investors who are making decisions 101 00:06:39,360 --> 00:06:43,719 Speaker 1: based on water scarcity just like there are investors today 102 00:06:43,720 --> 00:06:46,800 Speaker 1: that make decisions based on COO two emissions. 103 00:06:47,400 --> 00:06:51,240 Speaker 2: Yep, So you know exactly what you're talking about, you know, 104 00:06:51,279 --> 00:06:54,159 Speaker 2: for investors when we're talking about risk, you know, like 105 00:06:54,200 --> 00:06:58,680 Speaker 2: this really means assessing portfolio exposure to water intensive industries 106 00:06:59,160 --> 00:07:01,640 Speaker 2: and being able to tie identify the companies which are 107 00:07:01,800 --> 00:07:06,880 Speaker 2: most at risk. And beyond corporate exposure, banks and investors 108 00:07:06,920 --> 00:07:11,040 Speaker 2: are also exposed through their lending and financing decisions. But 109 00:07:11,440 --> 00:07:14,119 Speaker 2: to your point, it's not really a risk that's yet 110 00:07:14,160 --> 00:07:18,080 Speaker 2: widely disclosed. Just to cover a bit, you know, our 111 00:07:18,120 --> 00:07:22,320 Speaker 2: analysis did look at financed water consumption, finding that banks 112 00:07:22,320 --> 00:07:25,000 Speaker 2: like Bank of America, Wells Fargo, some of the largest 113 00:07:25,080 --> 00:07:28,400 Speaker 2: finance also some of the highest water consumption and risk 114 00:07:28,520 --> 00:07:33,360 Speaker 2: exposure in such water intensive industries. And yet water risk 115 00:07:33,440 --> 00:07:35,960 Speaker 2: hasn't to your point, been accounted for in the same 116 00:07:36,000 --> 00:07:37,920 Speaker 2: way as finance CO two missions. 117 00:07:38,200 --> 00:07:39,800 Speaker 1: And so the finance part of it here is the 118 00:07:39,880 --> 00:07:43,400 Speaker 1: fact that if a bank is lending money to a 119 00:07:43,560 --> 00:07:47,920 Speaker 1: company that then has either consumption of water or is 120 00:07:48,080 --> 00:07:51,960 Speaker 1: producing CO two, those emissions, or that water consumption is 121 00:07:52,000 --> 00:07:55,760 Speaker 1: then considered as financed water or financed emissions on the 122 00:07:55,800 --> 00:07:59,040 Speaker 1: books of the lender, And does the lender is being 123 00:07:59,040 --> 00:08:02,400 Speaker 1: exposed to all this that the company that has taken 124 00:08:02,440 --> 00:08:04,280 Speaker 1: their money is going to be facing. 125 00:08:04,720 --> 00:08:07,680 Speaker 2: Yep, exactly. That we really just apply similar to the 126 00:08:07,720 --> 00:08:11,480 Speaker 2: CO two finance emissions methodology of you know, the PEA 127 00:08:11,520 --> 00:08:14,760 Speaker 2: CAF methodology, doing the same thing for water. And so 128 00:08:15,360 --> 00:08:19,680 Speaker 2: though for investors they don't yet systematically price in water risk, 129 00:08:19,880 --> 00:08:23,880 Speaker 2: as these financial impacts grow, it's really going to become 130 00:08:24,120 --> 00:08:28,440 Speaker 2: increasingly difficult to ignore. Right the cost of inactions already evident. 131 00:08:28,720 --> 00:08:32,480 Speaker 2: You know, investors who don't proactively assess their exposure might 132 00:08:32,600 --> 00:08:38,319 Speaker 2: find themselves holding companies with significant unrecognized liabilities. 133 00:08:38,559 --> 00:08:41,520 Speaker 1: Yeah. Now we are going to talk about solutions and 134 00:08:41,520 --> 00:08:45,120 Speaker 1: opportunities in the space, but before that, can you spill 135 00:08:45,120 --> 00:08:47,840 Speaker 1: out some of the worst case scenarios that might happen, 136 00:08:48,080 --> 00:08:51,360 Speaker 1: or perhaps there are already case studies that you can 137 00:08:51,440 --> 00:08:54,200 Speaker 1: point to saying this could have been a cause that 138 00:08:54,240 --> 00:08:57,160 Speaker 1: would have been avoided had they thought about water scarcity risk. 139 00:08:57,880 --> 00:09:01,079 Speaker 2: Yeah. Absolutely, I think this really goes back to the 140 00:09:01,120 --> 00:09:03,760 Speaker 2: idea of the report of how water risks shows up 141 00:09:03,760 --> 00:09:06,880 Speaker 2: in different ways, and we really want to highlight the 142 00:09:06,920 --> 00:09:10,679 Speaker 2: importance of focusing on water intensive industries. So giving you 143 00:09:10,720 --> 00:09:14,360 Speaker 2: like real examples. Looking at agriculture, a quarter of the 144 00:09:14,360 --> 00:09:17,280 Speaker 2: world's food crops are grown in high water stress regions. 145 00:09:17,760 --> 00:09:21,080 Speaker 2: You know, severe drought in Brazil Ca Arabica coffee production 146 00:09:21,160 --> 00:09:23,800 Speaker 2: by eleven million bags, which really cause an eighty percent 147 00:09:23,840 --> 00:09:28,000 Speaker 2: spike in future prices. And yes, though coffee prices surged 148 00:09:28,280 --> 00:09:31,800 Speaker 2: exceptionally high levels due to impart to drought as well 149 00:09:31,840 --> 00:09:35,040 Speaker 2: as flooding in some cases. In apparel, half of the 150 00:09:35,080 --> 00:09:37,960 Speaker 2: world's cotton crop will be exposed to drought by twenty forty. 151 00:09:38,160 --> 00:09:40,800 Speaker 2: You know, you have companies like Nike whose supply chain 152 00:09:41,160 --> 00:09:43,679 Speaker 2: relies on cotton for eighty percent of its water footprint. 153 00:09:43,880 --> 00:09:48,520 Speaker 2: They're investing in recycled fabrics and waterless dying techniques. So 154 00:09:48,600 --> 00:09:52,520 Speaker 2: there are companies also like Levi's pushing cottonized hemp, which 155 00:09:52,720 --> 00:09:56,160 Speaker 2: uses a quarter of the water needed for cotton. I 156 00:09:56,280 --> 00:10:01,120 Speaker 2: mentioned semiconductors on the production side, but it's the development too, right, 157 00:10:01,200 --> 00:10:04,199 Speaker 2: Like the forty percent of semiconductor plants since twenty twenty 158 00:10:04,240 --> 00:10:08,200 Speaker 2: one that are being built in water stressed areas. You know, 159 00:10:08,800 --> 00:10:13,840 Speaker 2: water can basically slow or halt growth depending on access 160 00:10:13,880 --> 00:10:17,240 Speaker 2: of it. So these are also like a few ways 161 00:10:17,280 --> 00:10:19,920 Speaker 2: in which investors can really think of water risk and 162 00:10:19,960 --> 00:10:23,440 Speaker 2: sometimes in ways that are not so obvious. For the 163 00:10:23,520 --> 00:10:27,000 Speaker 2: industry agriculture, like I mentioned, it was a lot about crops, 164 00:10:27,520 --> 00:10:32,120 Speaker 2: but Archie Daniel's Midland their carbon sequestration facility leaked due 165 00:10:32,120 --> 00:10:35,880 Speaker 2: to compromise monitoring wells, So this raised concerns over long 166 00:10:35,960 --> 00:10:39,760 Speaker 2: term water security risks and shell. Yes, you know water 167 00:10:39,840 --> 00:10:43,439 Speaker 2: is needed in extractive industries, but they agreed in California 168 00:10:43,559 --> 00:10:46,080 Speaker 2: to a two hundred and thirty million dollars settlement over 169 00:10:46,160 --> 00:10:49,040 Speaker 2: contaminated wells. So this really shows that companies are not 170 00:10:49,120 --> 00:11:00,120 Speaker 2: only vulnerable to water scarcity but also water related liability. 171 00:11:02,800 --> 00:11:05,800 Speaker 1: After the break, more of my conversation with Bloomberg Intelligence 172 00:11:05,840 --> 00:11:09,679 Speaker 1: researcher Melanie Rua. And if you've been enjoying this episode, 173 00:11:09,720 --> 00:11:11,560 Speaker 1: please take a moment to rate and review the show 174 00:11:11,679 --> 00:11:15,400 Speaker 1: on Apple Podcasts or Spotify. It helps other listeners find 175 00:11:15,440 --> 00:11:26,680 Speaker 1: the show now. In terms of technologies in the climate space, 176 00:11:26,720 --> 00:11:30,520 Speaker 1: there are a myriad of technologies that are now available 177 00:11:30,559 --> 00:11:34,320 Speaker 1: to try and start to reduce emissions from sectors. What 178 00:11:34,400 --> 00:11:37,520 Speaker 1: are the technology solutions available to try and deal with 179 00:11:37,600 --> 00:11:38,439 Speaker 1: water scarcity? 180 00:11:38,960 --> 00:11:41,680 Speaker 2: Yes, so I do have to say there's not one 181 00:11:41,760 --> 00:11:45,200 Speaker 2: solution for something like this, the water crisis. It's really 182 00:11:45,240 --> 00:11:52,479 Speaker 2: fueling demand for alternative water sources, efficiency technologies, the sustainable materials, 183 00:11:53,040 --> 00:11:55,560 Speaker 2: you know. To give you some more insights on these 184 00:11:55,600 --> 00:12:01,160 Speaker 2: different solutions. On desalination and treatment, you have companies like Veolia, 185 00:12:01,200 --> 00:12:04,480 Speaker 2: who plans to boost revenue from water treatment technologies by 186 00:12:04,520 --> 00:12:08,440 Speaker 2: fifty percent by twenty thirty. On cooling tech, you have 187 00:12:08,640 --> 00:12:13,679 Speaker 2: Lenovo's Neptune liquid cooled servers, which reduce power consumption by 188 00:12:13,720 --> 00:12:17,839 Speaker 2: forty percent, cutting water needs. And then you have alternative fibers. 189 00:12:18,200 --> 00:12:22,040 Speaker 2: So Gailey, which H and M invested in, is developing 190 00:12:22,160 --> 00:12:26,480 Speaker 2: lab grown cotton which uses ninety seven to ninety nine 191 00:12:26,520 --> 00:12:30,880 Speaker 2: percent less water than conventional cotton. So while yes, there's 192 00:12:31,040 --> 00:12:36,400 Speaker 2: multiple solutions, there's also trade offs. Right, Desalination is energy 193 00:12:36,440 --> 00:12:40,599 Speaker 2: intensive and switching from water cooling to air cooling and 194 00:12:40,760 --> 00:12:44,760 Speaker 2: data centers. While it may be more efficient stuff, this 195 00:12:44,760 --> 00:12:49,160 Speaker 2: would increase energy demand, can drive expenses, and it doesn't 196 00:12:49,240 --> 00:12:52,800 Speaker 2: work everywhere. So investors really need to evaluate that cost 197 00:12:52,840 --> 00:12:54,200 Speaker 2: benefit equation of. 198 00:12:54,120 --> 00:12:58,480 Speaker 1: These companies like Gailey that I've written about which will 199 00:12:58,520 --> 00:13:01,360 Speaker 1: link in the show notes. You know, interesting technology, but 200 00:13:01,600 --> 00:13:04,160 Speaker 1: adoption of those kinds of technologies that are mass scale 201 00:13:04,240 --> 00:13:08,240 Speaker 1: takes time, takes people to experiment. So yeah, there are 202 00:13:08,520 --> 00:13:12,319 Speaker 1: options available, but for water scarcity that is coming so 203 00:13:12,320 --> 00:13:15,200 Speaker 1: soon or is already here in many cases, there have 204 00:13:15,320 --> 00:13:19,439 Speaker 1: to be other options for investors to think about. Now again, 205 00:13:19,559 --> 00:13:22,560 Speaker 1: I'm taking the CO two lens, which I understand. Investors 206 00:13:22,600 --> 00:13:26,480 Speaker 1: have models now, quite sophisticated models where they can estimate 207 00:13:26,679 --> 00:13:29,120 Speaker 1: if this is the pathway that the world is taking, 208 00:13:29,160 --> 00:13:31,240 Speaker 1: this is the level of warming that the world is 209 00:13:31,280 --> 00:13:34,120 Speaker 1: likely to have. These are the companies in our portfolio 210 00:13:34,160 --> 00:13:37,199 Speaker 1: that become an investable that may have stranded assets on 211 00:13:37,240 --> 00:13:39,240 Speaker 1: their books, and so we should start to reduce our 212 00:13:39,280 --> 00:13:43,760 Speaker 1: exposure to these companies. Is that level of modeling available 213 00:13:43,760 --> 00:13:46,720 Speaker 1: for water scarcity for investors to be able to start 214 00:13:46,760 --> 00:13:47,880 Speaker 1: making decisions today? 215 00:13:48,280 --> 00:13:52,400 Speaker 2: Oh? Absolutely, to your point, right, Like companies with high 216 00:13:52,400 --> 00:13:55,200 Speaker 2: exposures need to be on the investors watch list, and 217 00:13:55,280 --> 00:13:57,840 Speaker 2: there is data available to do that. In the report 218 00:13:57,880 --> 00:14:01,280 Speaker 2: we include this. We have asset level now that leverages 219 00:14:01,360 --> 00:14:05,719 Speaker 2: Bloomberg's company acid data and wri's aqueduct tool. So we 220 00:14:05,800 --> 00:14:09,880 Speaker 2: really identified asset exposure to water stress out to twenty 221 00:14:09,920 --> 00:14:11,880 Speaker 2: thirty again five years from now, and you could do 222 00:14:11,920 --> 00:14:15,880 Speaker 2: it under three different scenarios pessimistic, optimistic, or business as usual. 223 00:14:16,080 --> 00:14:18,120 Speaker 2: We chose to do business as usual, and we did 224 00:14:18,120 --> 00:14:21,520 Speaker 2: it for metals and mining, power generation, and we also 225 00:14:21,560 --> 00:14:24,680 Speaker 2: did it for steel producers. And just to share insights 226 00:14:24,720 --> 00:14:28,120 Speaker 2: on that, we found that Spanish power company in Dessa 227 00:14:28,760 --> 00:14:32,240 Speaker 2: nearly seventy percent of its power plans could face high 228 00:14:32,360 --> 00:14:37,680 Speaker 2: or extremely high water stress in twenty thirty. Similarly, we 229 00:14:37,720 --> 00:14:43,160 Speaker 2: see Fresnillo where seventy percent of their metals and minds 230 00:14:43,200 --> 00:14:48,160 Speaker 2: are also in areas of high or extremely high water stress, 231 00:14:48,920 --> 00:14:52,680 Speaker 2: compared with you know, just fifty seven percent of bar 232 00:14:52,800 --> 00:14:56,960 Speaker 2: gold mines. And so this really is showing the risk 233 00:14:57,080 --> 00:15:01,560 Speaker 2: side of how you know, industry industries rely on water 234 00:15:01,760 --> 00:15:04,600 Speaker 2: for their cooling. You know, we're talking about power green 235 00:15:04,760 --> 00:15:09,080 Speaker 2: for production or for metals in mind extraction exposure to 236 00:15:10,000 --> 00:15:12,800 Speaker 2: water stress. So lack of access to water can really 237 00:15:12,840 --> 00:15:16,600 Speaker 2: be disruptive and huge risk to investors who are also 238 00:15:16,760 --> 00:15:17,920 Speaker 2: exposed to these companies. 239 00:15:18,600 --> 00:15:21,440 Speaker 1: And where are there still data gaps and what is 240 00:15:21,880 --> 00:15:25,400 Speaker 1: being done about it? At a regulatory level, or at 241 00:15:25,400 --> 00:15:27,560 Speaker 1: a corporate level, or at an investor level. 242 00:15:28,160 --> 00:15:33,960 Speaker 2: Great question. So in terms of data gaps, I do 243 00:15:34,120 --> 00:15:39,480 Speaker 2: have to say, while it's probably still early on or nascent, 244 00:15:39,520 --> 00:15:43,360 Speaker 2: in terms of having robust nature related data and water, 245 00:15:44,520 --> 00:15:46,520 Speaker 2: I do have to say there is sufficient data to 246 00:15:46,560 --> 00:15:50,600 Speaker 2: be able to make investment decisions and really draw out insights. 247 00:15:50,680 --> 00:15:53,440 Speaker 2: It would be great for more disclosure, you know, going 248 00:15:53,480 --> 00:15:57,400 Speaker 2: back to our financed water analysis, there were a lot 249 00:15:57,440 --> 00:16:02,520 Speaker 2: of limitations simply because of the fact that not all 250 00:16:03,160 --> 00:16:07,400 Speaker 2: banks are disclosing the purpose of their loans and for 251 00:16:07,480 --> 00:16:11,200 Speaker 2: their borrowers. Not all companies are disclosing their water consumption 252 00:16:11,400 --> 00:16:14,520 Speaker 2: or exposure to water stress, right, So that really falls 253 00:16:14,600 --> 00:16:20,000 Speaker 2: on just more more disclosure, more transparency. But water scarcity 254 00:16:20,040 --> 00:16:23,520 Speaker 2: is intensifying, the financial risks are already being fell and 255 00:16:23,600 --> 00:16:27,960 Speaker 2: companies are being forced to act. So I mentioned there's 256 00:16:28,040 --> 00:16:32,280 Speaker 2: enough data exists for investment decisions. We find that water 257 00:16:32,360 --> 00:16:35,720 Speaker 2: is deemed financially material for nearly half of Bloomberg's easy 258 00:16:35,720 --> 00:16:38,440 Speaker 2: scoring peer groups. This is forty seven industries out of 259 00:16:38,440 --> 00:16:41,280 Speaker 2: one hundred and six, you know, twenty twenty four A 260 00:16:41,320 --> 00:16:44,720 Speaker 2: loan has shown how urgent this is from record low 261 00:16:45,280 --> 00:16:48,800 Speaker 2: Rhne river levels, disrupting supply chains, to drought in Brazil, 262 00:16:48,920 --> 00:16:53,960 Speaker 2: driving food inflation. You know, these risks are already shaping markets. 263 00:16:54,280 --> 00:16:57,600 Speaker 2: Financial costs are driving action, right. I mentioned Constellation six 264 00:16:57,720 --> 00:16:59,760 Speaker 2: hundred and sixty million dollars right down, but they're not 265 00:16:59,720 --> 00:17:04,280 Speaker 2: all basfs. Two hundred and fifty million euro loss from 266 00:17:04,400 --> 00:17:07,919 Speaker 2: Ryan River disruptions is another example. Or Intel was one 267 00:17:07,960 --> 00:17:11,639 Speaker 2: of the companies whose Arizona expansion is facing water constraints. 268 00:17:12,200 --> 00:17:16,040 Speaker 2: And you mentioned policy well three ms ten billion dollars 269 00:17:16,119 --> 00:17:19,720 Speaker 2: in PFAS settlements. All show how water related risks are 270 00:17:19,720 --> 00:17:23,520 Speaker 2: materializing into real losses and how companies are being forced 271 00:17:23,560 --> 00:17:27,320 Speaker 2: to address these challenges, whether proactively or reactively. And we 272 00:17:27,320 --> 00:17:29,720 Speaker 2: were able to use a lot of this data to 273 00:17:29,760 --> 00:17:33,160 Speaker 2: be able to identify a company level like asset level 274 00:17:33,200 --> 00:17:36,560 Speaker 2: exposure and being able to really identify also those who 275 00:17:36,600 --> 00:17:39,679 Speaker 2: are taking action right like being able to adapt to 276 00:17:39,840 --> 00:17:40,760 Speaker 2: the such risks. 277 00:17:41,240 --> 00:17:43,720 Speaker 1: Right. This is the theory that has been for a 278 00:17:43,760 --> 00:17:48,440 Speaker 1: long time considered important that there are non financial metrics 279 00:17:48,480 --> 00:17:52,320 Speaker 1: that have financial impact on companies. It's not just carbon, 280 00:17:52,400 --> 00:17:54,840 Speaker 1: it's water, but it's so many other things, right, and 281 00:17:54,880 --> 00:17:58,359 Speaker 1: we're going through this period where these non financial metrics 282 00:17:58,400 --> 00:18:03,680 Speaker 1: which are broadly cossed under ESG Environmental social governance is 283 00:18:03,720 --> 00:18:07,439 Speaker 1: seeing a political backlash. You're seeing that in the US 284 00:18:07,480 --> 00:18:10,359 Speaker 1: with the presidency of Donald Trump, but even before Trump 285 00:18:10,440 --> 00:18:12,879 Speaker 1: came to power, there were all these Republicans going after 286 00:18:13,280 --> 00:18:16,240 Speaker 1: investors to try and get them to not invest on 287 00:18:16,560 --> 00:18:20,120 Speaker 1: ESG criteria. Then you're seeing some of the ramifications show 288 00:18:20,200 --> 00:18:23,960 Speaker 1: up in Europe. We ran a recent episode on Zero 289 00:18:24,080 --> 00:18:28,359 Speaker 1: looking at how the ESG backlash is causing Europe, which 290 00:18:28,359 --> 00:18:31,880 Speaker 1: is a leader in rule making on ESG, to start 291 00:18:31,920 --> 00:18:35,080 Speaker 1: to undo some of them to try and please investors, 292 00:18:35,119 --> 00:18:38,959 Speaker 1: but also try and manage the relations across the Atlantic. So, 293 00:18:39,680 --> 00:18:41,760 Speaker 1: if water is so important, and we know COO two 294 00:18:41,800 --> 00:18:46,320 Speaker 1: is so important, how are you seeing investors think about 295 00:18:46,720 --> 00:18:50,680 Speaker 1: ESG in this moment and start to actually still take 296 00:18:50,720 --> 00:18:54,520 Speaker 1: the decisions that are necessary for investments, but perhaps do 297 00:18:54,560 --> 00:18:56,960 Speaker 1: it in a way where they're not advertising to the world. 298 00:18:57,720 --> 00:19:01,920 Speaker 2: Yes, great question and very time. To your point, I mean, look, 299 00:19:02,080 --> 00:19:06,159 Speaker 2: the backlash against is she investing. Yes, it's led to 300 00:19:06,280 --> 00:19:13,440 Speaker 2: increased scrutiny on climate related disclosures, for example, some sustainability initiatives. 301 00:19:13,560 --> 00:19:17,040 Speaker 2: But to your point, you know, when it comes to 302 00:19:17,480 --> 00:19:20,200 Speaker 2: issues like water, especially in this report, we're really talking 303 00:19:20,240 --> 00:19:24,200 Speaker 2: about a financially material issue that companies and investors cannot 304 00:19:24,280 --> 00:19:29,880 Speaker 2: afford to ignore. This isn't about ideology, It's about economics, right, 305 00:19:30,040 --> 00:19:33,280 Speaker 2: Like global GDPs at risk, and we have real world 306 00:19:33,320 --> 00:19:39,320 Speaker 2: examples of companies already facing operational shutdowns, rising costs, stranded assets, 307 00:19:39,680 --> 00:19:42,520 Speaker 2: all due to water stress, water scarcity, drought and what 308 00:19:42,640 --> 00:19:45,119 Speaker 2: have you. And the number of incidents. It's not just 309 00:19:45,200 --> 00:19:49,119 Speaker 2: increasing but intensifying, right, meaning companies and investors will have 310 00:19:49,200 --> 00:19:51,600 Speaker 2: to deal with these risks, whether or not is she 311 00:19:51,800 --> 00:19:55,400 Speaker 2: is politically popular if you will yes. At the same time, 312 00:19:55,440 --> 00:19:59,679 Speaker 2: policies uncertainty is a risks you know you mentioned and 313 00:19:59,720 --> 00:20:03,040 Speaker 2: you're up some of the undoing of some rules well 314 00:20:03,680 --> 00:20:07,119 Speaker 2: you know here in the US, particularly under the Trump administration, 315 00:20:07,920 --> 00:20:11,320 Speaker 2: which has signaled the rollback of environmental regulations. I can 316 00:20:11,359 --> 00:20:15,480 Speaker 2: give an example, right the EPA's new PFAZ Drinking Water rule, 317 00:20:15,920 --> 00:20:19,480 Speaker 2: So it requires utilities and companies to meet strict contamination 318 00:20:19,560 --> 00:20:23,520 Speaker 2: limits for forever chemicals to give background, the role will 319 00:20:23,560 --> 00:20:26,600 Speaker 2: cost US businesses and utilities around one point five billion 320 00:20:26,680 --> 00:20:30,960 Speaker 2: dollars annually with significant compliance and litigation risks for companies 321 00:20:31,000 --> 00:20:34,080 Speaker 2: like three m which I mentioned earlier, DuPont Keymores. You 322 00:20:34,080 --> 00:20:37,359 Speaker 2: know they've already settled over eleven billion dollars in PFAS 323 00:20:37,400 --> 00:20:41,120 Speaker 2: related lawsuits. And if the role is rolled back, which 324 00:20:41,160 --> 00:20:44,320 Speaker 2: I do think likely, but you know, if it is 325 00:20:44,359 --> 00:20:49,520 Speaker 2: even weakened, it could shift financial liabilities from regulated companies 326 00:20:49,600 --> 00:20:55,159 Speaker 2: back onto local governments and taxpayers, but increasing uncertainty for 327 00:20:55,240 --> 00:20:58,280 Speaker 2: businesses really trying to manage long term water risks. 328 00:20:58,800 --> 00:21:01,840 Speaker 1: This is very insightful. Thank you so much for this 329 00:21:01,960 --> 00:21:04,359 Speaker 1: report on motor scarcity, and thank you for coming on 330 00:21:04,400 --> 00:21:04,720 Speaker 1: the show. 331 00:21:05,080 --> 00:21:05,880 Speaker 2: Yeah, my pleasure. 332 00:21:15,440 --> 00:21:17,720 Speaker 1: Thank you for listening to Zero. And now for the 333 00:21:17,760 --> 00:21:21,800 Speaker 1: sound of the week. That's the sound of a salmon 334 00:21:21,960 --> 00:21:26,119 Speaker 1: cannon and it does what it says, which is helped 335 00:21:26,200 --> 00:21:30,320 Speaker 1: salmon cross a dam and continue their migration down a river. 336 00:21:30,720 --> 00:21:32,639 Speaker 1: If you like this episode, please take a moment to 337 00:21:32,720 --> 00:21:35,480 Speaker 1: rate and review the show on Apple Podcasts and Spotify. 338 00:21:35,960 --> 00:21:38,720 Speaker 1: Share this episode with a friend or with someone who 339 00:21:38,800 --> 00:21:41,680 Speaker 1: is thirsty. You can get in touch at zero pod 340 00:21:41,720 --> 00:21:45,800 Speaker 1: at Bloomberg dot Nex. Zero's producer is Mithlero, Bloomberg's head 341 00:21:45,800 --> 00:21:48,720 Speaker 1: a podcast is Sage Pauman, and head of Talk is 342 00:21:48,760 --> 00:21:52,480 Speaker 1: Brendan Muni. Our theme music is composed by wonder Land 343 00:21:53,119 --> 00:21:56,320 Speaker 1: Special Thanks to Shwan Wagner and Jessica beck I, am 344 00:21:56,320 --> 00:21:58,040 Speaker 1: Akshatrati back So