Editing IPCC:AR6/SR15/Chapter-5 (section)

==== 5.4.2.4 Water security ====

<div id="section-5-4-2-4-block-1"></div>

Transformations towards low emissions energy and agricultural systems can have major implications for freshwater demand as well as water pollution. The scaling up of renewables and energy efficiency as depicted by low emissions pathways would, in most instances, lower water demands for thermal energy supply facilities (‘water-for-energy’) compared to fossil energy technologies, and thus reinforce targets related to water access and scarcity (see Chapter 4, Section 4.2.1). However, some low-carbon options such as bioenergy, centralized solar power, nuclear and hydropower technologies could, if not managed properly, have counteracting effects that compound existing water-related problems in a given locale (Byers et al., 2014; Fricko et al., 2016; IEA, 2016; Fujimori et al., 2017a; Wang, 2017; McCollum et al., 2018a) <sup>[[#fn:r250|250]]</sup> .

Under stringent mitigation efforts, the demand for bioenergy can result in a substantial increase of water demand for irrigation, thereby potentially contributing to water scarcity in water-stressed regions (Berger et al., 2015; Bonsch et al., 2016; Jägermeyr et al., 2017) <sup>[[#fn:r251|251]]</sup> . However, this risk can be reduced by prioritizing rain-fed production of bioenergy (Hayashi et al., 2015, 2018; Bonsch et al., 2016) <sup>[[#fn:r252|252]]</sup> , but might have adverse effects for food security (Boysen et al., 2017) <sup>[[#fn:r253|253]]</sup> .

Reducing food and energy demand without compromising the needs of the poor emerges as a robust strategy for both water conservation and GHG emissions reductions (von Stechow et al., 2015; IEA, 2016; Parkinson et al., 2016; Grubler et al., 2018) <sup>[[#fn:r254|254]]</sup> . The results underscore the importance of an integrated approach when developing water, energy and climate policy (IEA, 2016) <sup>[[#fn:r255|255]]</sup> .

Estimates across different models for the impacts of stringent mitigation pathways on energy-related water uses seem ambiguous. Some pathways show synergies (Mouratiadou et al., 2018) <sup>[[#fn:r256|256]]</sup> while others indicate trade-offs and thus increases of water use due to mitigation (Fricko et al., 2016) <sup>[[#fn:r257|257]]</sup> . The synergies depend on the adopted policy implementation or mitigation strategies and technology portfolio. A number of adaptation options exist (e.g., dry cooling), which can effectively reduce electricity-related water trade-offs (Fricko et al., 2016; IEA, 2016) <sup>[[#fn:r258|258]]</sup> . Similarly, irrigation water use will depend on the regions where crops are produced, the sources of bioenergy (e.g., agriculture vs. forestry) and dietary change induced by climate policy. Overall, and also considering other water-related SDGs, including access to safe drinking water and sanitation as well as waste-water treatment, investments into the water sector seem to be only modestly affected by stringent climate policy compatible with 1.5°C (Figure 5.4) (McCollum et al., 2018b) <sup>[[#fn:r259|259]]</sup> .

<div id="section-5-4-2-4-block-2"></div>

<span id="figure-5.3"></span>
<!-- START IMG -->
<!-- IMG TITLE -->
'''Figure 5.3'''

<span id="sustainable-development-implications-of-mitigation-actions-in-1.5c-pathways."></span>
<!-- IMG CAPTION -->
'''Sustainable development implications of mitigation actions in 1.5°C pathways.'''
<!-- IMG FILE -->
[[File:1844ff5cddcdb71268b4bf40b4f09ca1 figure-5.3-682x1024.jpg]]

Panel (a) shows ranges for 1.5°C pathways for selected sustainable development dimensions compared to the ranges of 2°C pathways and baseline pathways. The panel (a) depicts interquartile and the full range across the scenarios for Sustainable Development Goal (SDG) 2 (hunger), SDG 3 (health), SDG 6 (water), SDG 7 (energy), SDG 12 (resources), SDG 13/14 (climate/ocean) and SDG 15 (land). Progress towards achieving the SDGs is denoted by arrow symbols (increase or decrease of indicator). Black horizontal lines show 2015 values for comparison. Note that sustainable development effects are estimated for the effect of mitigation and do not include benefits from avoided impacts (see Chapter 3, Section 3.5). Low energy demand (LED) denotes estimates from a pathway with extremely low energy demand reaching 1.5°C without bioenergy with carbon capture and storage (BECCS). Panel (b) presents the resulting full range for synergies and trade-offs of 1.5°C pathways compared to the corresponding baseline scenarios. The y-axis in panel (b) indicates the factor change in the 1.5°C pathway compared to the baseline. Note that the figure shows gross impacts of mitigation and does not include feedbacks due to avoided impacts. The realization of the side effects will critically depend on local circumstances and implementation practice. Trade-offs across many sustainable development dimensions can be reduced through complementary/re-distributional measures. The figure is not comprehensive and focuses on those sustainable development dimensions for which quantifications across models are available. Sources: 1.5°C pathways database from Chapter 2 (Grubler et al., 2018; McCollum et al., 2018b) <sup>[[#fn:r260|260]]</sup> .

<!-- END IMG -->
<div id="section-5-4-2-4-block-3"></div>

<span id="figure-5.4"></span>
<!-- START IMG -->
<!-- IMG TITLE -->
'''Figure 5.4'''

<span id="investment-into-mitigation-up-until-2030-and-implications-for-investments-for-four-sustainable-development-dimensions."></span>
<!-- IMG CAPTION -->
'''Investment into mitigation up until 2030 and implications for investments for four sustainable development dimensions.'''
<!-- IMG FILE -->
[[File:b89a9e2508483d361f915d41fb6626fa figure-5.4-1024x700.jpg]]

Cross-hatched bars show the median investment in 1.5°C pathways across results from different models, and solid bars for 2°C pathways, respectively. Whiskers on bars represent minima and maxima across estimates from six models. Clean water and air pollution investments are available only from one model. Mitigation investments show the change in investments across mitigation options compared to the baseline. Negative mitigation investments (grey bars) denote disinvestment (reduced investment needs) into fossil fuel sectors compared to the baseline. Investments for different sustainable development dimensions denote the investment needs for complementary measures in order to avoid trade-offs (negative impacts) of mitigation. Negative sustainable development investments for air pollution indicate cost savings, and thus synergies of mitigation for air pollution control costs. The values compare to about 2 trillion USD2010 (range of 1.4 to 3 trillion) of total energy-related investments in the 1.5°C pathways. Source: Estimates from CD-LINKS scenarios summarised by McCollum et al. (2018b) <sup>[[#fn:r261|261]]</sup> .

<!-- END IMG -->
<div id="section-5-4-2-4-block-4"></div>

In summary, the assessment of mitigation pathways shows that to meet the 1.5°C target, a wide range of mitigation options would need to be deployed (see Chapter 2, Sections 2.3 and 2.4). While pathways aiming at 1.5°C are associated with high synergies for some sustainable development dimensions (such as human health and air pollution, forest preservation), the rapid pace and magnitude of the required changes would also lead to increased risks for trade-offs for other sustainable development dimensions (particularly food security) (Figures 5.4 and 5.5). Synergies and trade-offs are expected to be unevenly distributed between regions and nations (Box 5.2), though little literature has formally examined such distributions under 1.5°C-consistent mitigation scenarios. Reducing these risks requires smart policy designs and mechanisms that shield the poor and redistribute the burden so that the most vulnerable are not disproportionately affected. Recent scenario analyses show that associated investments for reducing the trade-offs for, for example, food, water and energy access to be significantly lower than the required mitigation investments (McCollum et al., 2018b) <sup>[[#fn:r262|262]]</sup> . Fundamental transformation of demand, including efficiency and behavioural changes, can help to significantly reduce the reliance on risky technologies, such as BECCS, and thus reduce the risk of potential trade-offs between mitigation and other sustainable development dimensions (von Stechow et al., 2015; Grubler et al., 2018; van Vuuren et al., 2018) <sup>[[#fn:r263|263]]</sup> . Reliance on demand-side measures only, however, would not be sufficient for meeting stringent targets, such as 1.5°C and 2°C (Clarke et al., 2014) <sup>[[#fn:r264|264]]</sup> .

<span id="sustainable-development-pathways-to-1.5c-1"></span>