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Livelihoods Under Climate Stress: A Nine-Country Study and Cross-Country Solution Patterns

About: an independent research brief compiled from public data and published reports. No affiliation with, commission from, or review by any government agency, utility, or company. Critical views are attributed to the named institutions that hold them; no company or official is named as a culprit; no political advocacy. Last updated: 2026-09-26 (UTC). The Chinese edition is the primary version.

Tags: verified figure read in the original source · derived computed by us from verified data · secondhand relayed via media or a third party · unverified could not be checked · estimate the source itself is a screening estimate or model output. Every figure carries a source number [S#] — see References.

0. Core conclusions

1. Climate stress on livelihoods is present tense, and at record scale. Disasters triggered 45.8 million internal displacements worldwide in 2024, the highest since monitoring began in 2008; 99.5% were weather-related verified [S7]. Heat-related deaths averaged ~546,000/yr in 2012–2021, up 63% from the 1990s estimate [S6]. Heat cost ~639–640 billion potential labour hours in 2024, worth ~US$1.09 trillion, near 1% of global GDP estimate [S6].
2. Deaths are the first loss proven compressible — even as hazards intensify. Bangladesh cut cyclone deaths from 300,000–500,000 (Bhola, 1970) to roughly 3,000 for comparable storms — a hundredfold decline in the World Bank's phrasing verified [S9][S29]. Philippines: Haiyan (2013) killed 6,293 with 126,000 pre-emptively evacuated; Rai (2021) caused comparable destruction, but 826,125 were evacuated ahead of landfall and 409 died verified [S37][S39][S40]. Early warning + pre-emptive evacuation + shelters is the strongest-evidence, lowest-unit-cost pattern here (P1).
3. Monetary losses are not yet compressible, and increasingly land on the unprotected. Pakistan 2022 floods: US$14.9bn damage + US$15.2bn losses, US$16.3bn reconstruction needs, 33 million affected, an estimated 8.4–9.1 million pushed into poverty verified [S26][S27]. Nigeria 2022 floods: median direct damage US$6.68bn verified [S41]. Lancet Countdown: US$304bn in 2024 global losses from weather extremes, +58.9% vs the 2010–14 average estimate [S6]. Evacuation saves lives; it does not protect homes, fields, or businesses.
4. Heat is shifting from "extreme event" to a daily livelihoods tax. China's 2025 mean temperature tied 2024 as the highest since 1951, with a record 16.5 hot days (≥35°C) since 1961 verified [S10]; India's 2024 was its warmest year since 1901 verified [S21]. Evaluated countermeasures are cheap: Ahmedabad's Heat Action Plan was associated with ~1,190 avoided deaths/yr (95% CI 162–2,218; observational) verified [S24]; Thailand's study finds efficient AC the cheapest peak resource (~0.76 baht per kWh saved) estimate [S58].
5. Exposure is not risk: state capability decides how big a hole the same weather punches. China has the world's highest disaster exposure (WRI exposure 64.59, rank 1) yet ranks 9th composite and 124th on INFORM verified/derived [S1][S2][S3]. Solutions must be tiered: for strong states the frontier is compound shocks (China's 2022 heat × drought × hydropower chain); for weak states it is fiscal space and the last mile.
6. At least eight solution patterns recur with cost evidence (Section 3): warning and evacuation (~US$800m/yr in developing countries avoids US$3–16bn/yr; 24h warning cuts damage ~30% — Global Commission on Adaptation verified [S8]); heat action plans; shock-responsive social protection and anticipatory cash (US$53 before a flood cut the odds of a day without eating by 36%, quasi-experimental verified [S34]); efficient cooling; water efficiency and new sources; stress-tolerant crops; distributed solar (Nigeria's DARES targets 17.5m people verified [S44]); urban flood management. Common law: systems built in advance — registries, volunteer networks, shelters, standards — determine disaster-time performance; improvising afterwards is always slower and more expensive.
7. Data gaps are themselves a finding. Subnational, end-use, and informal-sector data are scarce everywhere; India's heatwave deaths differ by an order of magnitude across tallies; China does not systematically publish provincial hourly load or heat-attributable excess mortality — stated factually, without speculation, per this study's public-safety rules.

1. Risk indicators, nine countries

The four indices measure different things: CRI = realized impacts (retrospective); WRI and INFORM = exposure × vulnerability (× coping); ND-GAIN = vulnerability + readiness. Read from original files 2026-09-26 verified/derived [S1][S2][S3][S4]. INFORM 2026 scores not retrieved unverified.

1.1 Heat–cooling–power pressure indicators (data layer, first tranche)

Cooling access and peak-demand growth are the two most direct gauges of how heat becomes a livelihoods problem.

Two readings. (1) The cooling gap is the adaptation gap — China at 60% vs India at 5% and the Philippines/Vietnam below 10% means the latter cannot buffer heat mortality and lost work hours by "going home to the AC", and cooling demand will multiply from a very low base. (2) Peak growth generally exceeds routine planning assumptions — India's ~5.9%/yr doubles the peak roughly every 12 years derived. Bangladesh, Pakistan, and Nigeria are highly heat-exposed yet publish no peak series — stated as gaps.

2. Country studies (conclusions first)

2.1 China — highest exposure, strong capacity: the test case for adaptation at scale

• 2025 mean temperature 10.9°C (+1.0°C vs normal), tying 2024 as the highest since 1951; 16.5 hot days, most since 1961; the North China rainy season set volume and duration records verified [S10][S11].
• 2024 disasters: 94.13m person-times affected, 856 dead/missing, 3.645m emergency relocations, RMB 401.11bn direct losses verified [S12], ~0.3% of GDP derived.
• Compound shock on display: 2022's 64-day Yangtze heat event (National Climate Centre, via press) plus drought forced power rationing in hydro-dependent Sichuan secondhand [S16][S17]. National peak load hit 1,508 GW in July 2025, +57 GW over 2024's 1,451 GW (two annual points only) verified [S69].
• World's largest response: wind+solar 1.84 TW, 47.3% of capacity by end-2025, overtaking thermal verified [S13][S14]; National Adaptation Strategy 2035 issued by 17 ministries (2022) verified [S15].
• Urban flood lesson: sponge-city pilots cost US$15–22m/km² verified [S19], designed for ~180–200 mm/24h, vs Zhengzhou 2021's 800–900 mm/day (scholar's view via press) secondhand [S18]; the State Council investigation (as reported) recorded 398 dead/missing secondhand. Engineering + warning + evacuation must be combined.
• Data gaps (stated as gaps, no speculation): provincial hourly load not published; no systematic official series on heat-attributable excess deaths.

2.2 India — the largest heat-exposed population, birthplace of the heat action plan

• 2024: warmest year since 1901 (+0.65°C) verified [S21]; IMD release: ~2,400 extreme-weather deaths verified [S21]; media citing the full IMD summary: 3,200+ total, 459 from heatwaves secondhand [S22]; CSE: heatwaves on 77 of the first 274 days verified [S23]. The divergence is itself the data gap.
• The cooling gap is the core variable: ~5% household AC ownership in 2018 (China: 60%) verified [S63]; peak demand ≈+5.9%/yr FY2013-14→FY2024-25 (CEA) verified/derived [S65].
• Ahmedabad HAP (2013, South Asia's first): ~1,190 avoided deaths/yr (95% CI 162–2,218, observational) verified [S24][S62]; replicated across states and cities.
• India Cooling Action Plan (2019): by 2037–38, cooling demand −20–25%, cooling energy −25–40% verified [S25].

2.3 Pakistan — one flood erases years of development

• 2022 floods: a third of the country under water; 33m affected, ~8m displaced, >1,730 dead verified [S26][S27].
• Joint PDNA: US$14.9bn damage + US$15.2bn losses, US$16.3bn needs; housing worst hit (US$5.6bn); katcha (mud-brick) homes took 78% of housing damage; 8.4–9.1m pushed into poverty verified [S26].
• Pre-built registries decide cash speed: BISP paid Rs 25,000 to ~2.7m families (Rs 70bn, 97%+ disbursed) within weeks via the NSER registry verified [S28].
• Data-layer check: no verifiable national AC ownership rate, no public peak-demand series (gaps).

2.4 Bangladesh — how deaths fell a hundredfold

• Bhola (1970): 300,000–500,000 dead (deadliest cyclone on record, WMO); comparable storms now kill ~3,000; >2m evacuated ahead of Amphan (2020) verified [S9][S29].
• The mechanism is a system: the government–Red Crescent CPP with 55,000–76,000 volunteers carrying warnings door-to-door verified [S31]; shelters that double as schools verified [S29][S30].
• Anticipatory cash, quasi-experimental: US$53 four days before the 2020 flood (145,000 people) cut the odds of a day without eating by 36%; lower asset losses, less costly borrowing; ~100 days earlier than traditional aid verified [S34][S35].
• Delta Plan 2100: ~US$38bn capital plan, 2.5% GDP target verified [S32]. Counter-evidence: neighbour adoption of new saline-tolerant rice just 2.55%/0.80%; demonstrations add 11–18 pp — breeding success ≠ livelihood improvement verified [S36].
• Solar home systems: 4.13m units / 18m people by 2019 (IDCOL) verified [S33].

2.5 Philippines — world's highest risk index: an eight-year before/after on evacuation

• ~20 tropical cyclones enter the area of responsibility yearly, 8–9 crossing — the world's most verified [S38]. OCHA attributes the mortality gap to pre-emptive evacuation and post-Haiyan warning investment verified [S40].
• The unsolved problem has moved from saving lives to saving livelihoods; the UN piloted anticipatory-action financing (US$7.5m CERF) verified [S59].
• The next gap beyond typhoons: AC ownership <10% (2017, upper bound) secondhand [S64]; peak demand ≈+3.9%/yr 2003–2025 (DOE) verified/derived [S66].

2.6 Nigeria — floods stacked on the world's largest electricity access gap

• 2022 floods: >600 dead, 3.2m affected, 1.4m displaced; direct damage US$3.79–9.12bn (median 6.68) verified [S41]. 2024: the Alau dam failed after extreme rain; ~15% of Maiduguri flooded, >1m affected secondhand [S42] (mechanism described; no party blamed).
• ~85m people (43%) lack grid power — the world's largest deficit; unreliable power costs ~US$25–26bn/yr (~2% GDP) verified [S43][S45].
• DARES (US$750m IDA) targets access for 17.5m and replacing 250,000+ fuel generators; predecessor NEP connected 5.5m verified [S44].
• Data-layer check: no verifiable AC ownership rate, no public peak series — for a country where 43% lack electricity, these gaps are themselves telling.

2.7 Ethiopia — four failed rainy seasons: social protection as drought first response

• 2020–23 Horn of Africa drought: at least four consecutive failed rainy seasons; >30m people food-insecure across Ethiopia/Kenya/Somalia verified [S47].
• PSNP: ~2.5m households / 8m regular beneficiaries; shock-year scale-ups average +3.8m; the 2011 expansion was assessed by the World Bank as timelier and cheaper than relief verified [S46][S48].
• Counter-evidence: during the 2020–22 northern conflict, >1m beneficiaries in Tigray lost transfers (facts per the cited source; no attribution of blame) verified [S48].
• ~56m people without electricity (2020, world's third largest) verified [S45].

2.8 Mozambique — the rebuild loop: cyclone frequency outpacing fiscal recovery

• Idai (2019): 603 dead, 1.5m+ affected; Kenneth six weeks later — first recorded season with two strong landfalls; combined damage ~US$3bn, needs ~US$3.4bn verified [S49][S50].
• Since then, every one to two years: Freddy (2023) 492k+ affected, 53 dead verified [S51]; Chido (2024) 454k affected, 120 dead verified [S52]. Reconstruction unfinished when the next storm lands.
• Tools include ARC parametric insurance and warning investment verified [S51]; the financing gap keeps dependence on international funds high.

2.9 Egypt — chronic scarcity: no "disaster day", but tighter every year

• Renewable water per capita ~570 m³/yr by 2018 (from ~2,000 in the 1960s; scarcity line 1,000); the Nile supplies ~97–98% of renewable water; the ~55.5bn m³/yr allocation has been roughly fixed for decades while population passed 100m verified [S53][S54][S55]. Upstream development adds uncertainty; negotiations continue (no position taken).
• Peak demand ≈+3.5%/yr over ~2010–2024 (Ministry of Electricity/EEHC) verified/derived [S67]; no verifiable national AC ownership rate (gap).
• Response: US$50bn national water plan to 2037 verified [S53]; canal lining targeting 20,000 km (3,134 km by 2021) secondhand [S57]; desalination to 8.85m m³/day by 2050 verified [S56]. Engineering volumes verified; independent water-savings evaluations missing.

2.10 Thailand (reference) — the completed energy/cooling template

• Core finding: no shortage of capacity, a shortage of cheap evening power; AC efficiency is the cheapest peak measure (~0.76 baht per kWh saved; ~2,150 MW off the evening peak; 2–4-year household payback) estimate [S58].
• Data-layer addition: EGAT peak demand ≈+2.5%/yr over 2010–2025, the lowest checkable series in this study verified/derived [S68].

3. Cross-country solution patterns (P1–P8)

P1 Early warning + pre-emptive evacuation + shelters (evidence: strong)

• Evidence: Bangladesh's hundredfold decline [S9][S29]; Philippines Haiyan→Rai counterfactual [S37][S39][S40]; China's routinized 3.645m relocations in 2024 [S12].
• Cost: ~US$800m/yr in developing countries avoids US$3–16bn/yr; 24h warning cuts damage ~30%; benefits ≥10× cost (GCA) verified [S8].
• Failure modes: forecasts without the last mile; too few shelters; no effect on property losses.

P2 City/sector heat action plans (evidence: medium)

• Ahmedabad: ~1,190 avoided deaths/yr (observational) verified [S24]; mostly organizational, not capital, cost.
• Failure modes: warnings without changed work arrangements; night-time heat; households without cooling have nowhere to go (links to P4).

P3 Shock-responsive social protection + anticipatory cash (evidence: fairly strong)

• Bangladesh US$53 anticipatory cash: −36% odds of a day without eating (quasi-experimental) [S34][S35]; Ethiopia PSNP scale-ups assessed timelier and cheaper than relief [S48]; Pakistan BISP: Rs 70bn within weeks [S28].
• The point: spend in peacetime on registries and payment rails. Failure modes: the unregistered fall through; conflict interrupts payments; transfers lag inflation.

P4 Efficient cooling: standards, replacement, financing (evidence: strong on engineering/cost)

• Thailand: ~0.76 baht per kWh saved, ~5× cheaper than new gas capacity estimate [S58]; India's ICAP sets national targets [S25].
• The cross-country reading: AC ownership China 60%, India 5%, Indonesia 9% (2018) verified [S63]; Philippines/Vietnam <10% (2017, upper bound) secondhand [S64]. Peak demand is moving first: India ≈+5.9%/yr, Philippines ≈+3.9%, Egypt ≈+3.5%, Thailand ≈+2.5% [S65]–[S68]; China +57 GW in one year [S69]. Locking in efficiency standards and financing before the ownership boom is this pattern's window.
• Failure modes: standards without financing; poor installation/maintenance; the unelectrified are out of reach (links to P7).

P5 Water efficiency and new sources (evidence: weak–medium)

• Verified volumes, not effects: Egypt's lining, desalination, water plan [S53][S56][S57]; independent savings evaluations missing — the study's largest evaluation gap.
• Failure modes: lined canals cut "losses" that recharged groundwater; desalination costs pass into tariffs.

P6 Stress-tolerant crops and extension (evidence: medium; adoption is the bottleneck)

• Bangladesh's saline-tolerant rice performs, but neighbour adoption is 2.55%/0.80%; demonstrations add 11–18 pp verified [S36]. Variety released ≠ problem solved.

P7 Distributed renewables (evidence: fairly strong on access)

• Bangladesh 4.13m systems / 18m people [S33]; Nigeria NEP 5.5m connected + DARES targeting 17.5m [S44].
• Failure modes: unprofitable low-income areas; stranded assets when the grid arrives; battery-lifetime neglect.

P8 Urban flood management and "sponge cities" (evidence: medium; explicit ceiling)

• China's 30 pilots, US$15–22m/km² [S19]; effective within design standards, powerless against Zhengzhou-2021-scale extremes (scholar's view via press) secondhand [S18]. Must be combined with P1.

Pattern × country matrix

● = evidence from that country cited here; ○ = relevant policy/program exists but not verified in this edition; — = not applicable or not found.

4. Policy options menu (no advocacy)

5. Limitations and data gaps

• Coverage: no representation of the Americas or small island states; Chad, Somalia, Haiti, Myanmar excluded as chapters on data grounds.
• Definition risk: India's heat deaths differ by an order of magnitude across tallies; China's 2025 anomaly has bulletin (+1.0°C) and quick-release (+1.1°C) figures — the bulletin is used.
• Estimate dependence: Lancet, GCA, and Thailand cooling costs are model/screening estimates; not a basis for investment decisions.
• Data-layer progress: tranche 1 (AC ownership; peak-demand series) merged 2026-09-26; no verifiable data found for Bangladesh, Pakistan, Nigeria, Mozambique, Chad (and Egypt's AC rate) — stated as gaps. Still pending: INFORM 2026, Egypt's Aqueduct score.
• Only P1 and P3 have multi-country, multi-year effectiveness evidence; P5 (water) has almost none.

References

All accessed 2026-09-26 (UTC). Status: verified = read in the original source; secondhand = relayed; mixed series/derived items are tagged inline in the text.

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37. [S37] 菲律宾 NDRRMC：台风"Yolanda"（海燕）最终情况报告 SitRep No. 108（2014-04-03） (2014). https://reliefweb.int/attachments/a4cceb49-59e5-3540-a7a0-268812fa426f/NDRRMC%20Update%20-%20Sitrep%20No%20108%20re%20TY%20Yolanda%20-%2003%20April%202014.pdf — verified
38. [S38] 菲律宾 PAGASA：Tropical Cyclone Information（年均 20 个台风进入责任区、8–9 个过境） (2026 访问版). https://www.pagasa.dost.gov.ph/climate/tropical-cyclone-information — verified
39. [S39] 菲律宾 NDRRMC：台风"Odette"（雷伊）情况报告 SitRep No. 41（2022-01-28；死亡 409、预防性撤离 826,125 人） (2022). https://ndrrmc.gov.ph/attachments/article/4174/SitRep_No._41_for_Typhoon_ODETTE_2021.pdf — verified
40. [S40] UN OCHA：Super Typhoon Impact Comparison — Rai vs Haiyan（信息图） (2022). https://reliefweb.int/attachments/977e6f02-9891-372d-9144-54c0693ecbb6/OCHA-PHL-SuperTyphoonComparison-RaiHaiyan-220111.pdf — verified
41. [S41] 尼日利亚国家统计局（NBS）/NEMA/UNDP：Nigeria Flood Impact, Recovery and Mitigation Assessment Report 2022–2023（含世界银行 GRADE 损失区间） (2023). https://nigerianstat.gov.ng/pdfuploads/NigeriaFloodImpactRecoveryMitigationAssessmentReport2023.pdf — verified
42. [S42] AP News：Flooding in northeastern Nigeria（2024 年 Alau 大坝溃决、迈杜古里） (2024). https://apnews.com/article/flooding-northern-nigeria-borno-dam-collapse-60ed5b7bddfc4a5b65c0a0573d735d2b — secondhand
43. [S43] 世界银行新闻稿：Nigeria to Improve Electricity Access（8,500 万人无电、43%、年损失约 262 亿美元） (2021). https://www.worldbank.org/en/news/press-release/2021/02/05/nigeria-to-improve-electricity-access-and-services-to-citizens — verified
44. [S44] 世界银行新闻稿：Nigeria DARES 项目（7.5 亿美元、目标 1,750 万人；NEP 已建 125 个微电网、售出 100 万+ 套户用光伏） (2023). https://www.worldbank.org/en/news/press-release/2023/12/15/nigeria-to-expand-access-to-clean-energy-for-17-5-million-people — verified
45. [S45] 世界银行/联合国：Tracking SDG7 报告（2020 年无电人口：尼日利亚 9,200 万、埃塞俄比亚 5,600 万） (2022). https://documents1.worldbank.org/curated/en/099122223123530408/pdf/P1744811ffdf0c0f1b0f71ebda9ad18828.pdf — verified
46. [S46] 世界银行：Ethiopia PSNP-4 / Rural Productive Safety Net Project 实施状况报告（约 250 万户、800 万受益人） (2019/2021). https://documents1.worldbank.org/curated/en/537741610667593156/pdf/Disclosable-Version-of-the-ISR-Ethiopia-Rural-Productive-Safety-Net-Project-P163438-Sequence-No-06.pdf — verified
47. [S47] UNDRR：Horn of Africa floods and drought 2020–2023 — Forensic analysis（连续雨季失败、区域 3,000 万+ 人受旱） (2024). https://www.undrr.org/resource/horn-africa-floods-and-drought-2020-2023-forensic-analysis — verified
48. [S48] Sabates-Wheeler 等（BASIC Research）："Conflict Disruptions to Social Assistance…Northern Ethiopia Crisis (2020–22)"（PSNP 2011 年扩容证据、冲击年均再扩 380 万、北部中断） (2024). https://doi.org/10.19088/basic.2024.010 — verified
49. [S49] 世界银行：Mozambique Cyclone Idai & Kenneth Emergency Recovery and Resilience Project（项目文件；603 死、损失 30 亿美元、重建需求 34 亿美元） (2019). https://documents1.worldbank.org/curated/en/763461570154496796/pdf/Mozambique-Cyclone-Idai-and-Kenneth-Emergency-Recovery-and-Resilience-Project.pdf — verified
50. [S50] WHO 非洲区域办事处：Mozambique Tropical Cyclones Situation Report 5（同季两强气旋首次；Kenneth 数字） (2019). https://afro.who.int/sites/default/files/2019-05/WHOSitRep5Mozambique3May2019.pdf — verified
51. [S51] African Risk Capacity（ARC）：Tropical Cyclone Freddy Post-Event Briefing, Mozambique（受灾 49.2 万+、53 死） (2023). https://www.arc.int/sites/default/files/2023-03/FREDDY_2023_Post-Event%20Briefing%2C%20Mozambique%20%2817%20March%202023%29.pdf — verified
52. [S52] UN OCHA：Mozambique Tropical Cyclones Flash Appeal（气旋 Chido：受灾 453,971 人、120 死，转引 INGD） (2025). https://www.unocha.org/publications/report/mozambique/mozambique-tropical-cyclones-flash-appeal-january-june-2025-updated-february-2025 — verified
53. [S53] 联合国经社部（UN DESA）SDG 国家页：埃及（人均水资源 2018 年降至 570 m³；尼罗河年配额约 550 亿 m³；2037 年国家水计划约 500 亿美元） (2018 数据). https://sdgs.un.org/basic-page/egypt-34124 — verified
54. [S54] Nikiel & Eltahir, "Past and future trends of Egypt's water consumption and its sources", Nature Communications（尼罗河约占埃及可再生水资源 98%） (2021). https://pmc.ncbi.nlm.nih.gov/articles/PMC8302683/ — verified
55. [S55] FAO AQUASTAT 埃及国家概况（依赖率 96.91%；1959 年尼罗河水协定 55.5 km³/年） (数据年不一). https://www.fao.org/aquastat/en/ — verified (via country profile PDF)
56. [S56] 埃及主权基金（TSFE）新闻稿：海水淡化计划（2050 年 885 万 m³/日，第一期 2025 年 335 万 m³/日） (2023). https://tsfe.com/development/public/uploads/press_pdfs/16836441272WtfjvrVPqNiRVIjAP4p.pdf — verified
57. [S57] Ahram Online：埃及完成 3,134 公里渠道衬砌（总目标 20,000 公里；2050 水战略约 9,000 亿埃镑，转引水资源与灌溉部） (2021). https://english.ahram.org.eg/NewsContent/1/64/438280/Egypt/Politics-/Egypt-rehabilitates-over-,-kms-of-irrigation-canal.aspx — secondhand
58. [S58] 泰国电力研究（本系列已完成的单国模板；空调改造约 0.76 泰铢/节省一度电等筛选性成本） (2026). https://machengshen.github.io/thailand-energy/index.zh.html — verified
59. [S59] UN Connecting Business initiative：Five things you need to know about the response to Typhoon Rai（撤离至 2,861 个中心；CERF 预先行动试点） (2022). https://connectingbusiness.org/news-events/blog/five-things-you-need-know-about-response-typhoon-rai-philippines — verified
60. [S60] 央广网：2025 年全国平均气温再创历史新高（国家气候中心快报口径 11.0℃/常年 9.9℃；与《中国气候公报》评估口径 10.9℃并存） (2026). https://www.cnr.cn/newscenter/native/gd/kx/20260101/t20260101_527480467.shtml — secondhand
61. [S61] 尼日利亚联邦政府/世界银行 GRADE 评估（经 NBS 报告与 APP/Punch 报道）：2022 年洪水直接经济损害 37.9–91.2 亿美元、中位 66.8 亿美元 (2022). 见 S41 — verified (with S41)
62. [S62] 世界银行 India 气候投资案例汇编（引用艾哈迈达巴德 HAP 的事后评估） (2023). https://documents1.worldbank.org/curated/en/099826201272616643/pdf/IDU-ae8ad29c-bee3-4241-a9a3-09de535467c3.pdf — verified
63. [S63] IEA, The Future of Cooling（图表数据：家庭空调拥有率——中国 60%、印度 5%、印度尼西亚 9%，均为 2018 年口径；由数据层自图表数据核实） (2018). https://www.iea.org/reports/the-future-of-cooling — verified (data layer)
64. [S64] IEA, The Future of Cooling in Southeast Asia（正文表述：菲律宾、越南家庭空调拥有率低于 10%，2017 年口径；仅为上限，非精确值） (2019). https://www.iea.org/reports/the-future-of-cooling-in-southeast-asia — secondhand (data layer, upper bound)
65. [S65] 印度中央电力局（CEA）：Load Generation Balance Reports——全国最高用电负荷序列 2013-14 至 2024-25 财年；年均复合增速约 5.9% 由数据层推算 (2013–2025). https://cea.nic.in/ — verified (series) / derived (growth rate)
66. [S66] 菲律宾能源部（DOE）：电力统计附表——系统峰值负荷序列 2003–2025；年均复合增速约 3.9% 由数据层推算 (2003–2025). https://www.doe.gov.ph/ — verified (series) / derived (growth rate)
67. [S67] 埃及电力与可再生能源部 / 埃及电力控股公司（EEHC）年报——峰值负荷序列约 2010–2024；年均复合增速约 3.5% 由数据层推算 (2010–2024). http://www.moee.gov.eg/ — verified (series) / derived (growth rate)
68. [S68] 泰国发电局（EGAT）：系统峰值负荷序列 2010–2025；年均复合增速约 2.5% 由数据层推算 (2010–2025). https://www.egat.co.th/ — verified (series) / derived (growth rate)
69. [S69] 国家能源局迎峰度夏新闻发布会（2025-07-31）：2025 年全国最大电力负荷 15.08 亿千瓦，较 2024 年最大负荷（14.51 亿千瓦）增加 0.57 亿千瓦（仅两个年度点，不构成趋势） (2025). https://www.nea.gov.cn/20250731/d34b8a28ee5143bab558a06208ff1864/c.html — verified

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