Afforesting arid land with renewable electricity and desalination to mitigate climate change

Afforestation, the deliberate conversion of non-forested land to forests, is a widely practiced carbon dioxide removal (CDR) method. However, its widespread application is limited by the availability of suitable land and sufficient water resources, especially in arid and semi-arid regions. Current afforestation efforts often compete with agriculture and grazing, leading to concerns about food security and land use conflicts. Furthermore, the success of afforestation projects is highly dependent on a reliable water supply, as evidenced by tree mortality in projects in China and Turkey. This study addresses these limitations by exploring the potential of combining low-cost renewable electricity (RE) with seawater reverse osmosis (SWRO) desalination to provide irrigation for afforestation projects on arid lands. The decreasing cost of RE, coupled with increasing water scarcity, makes RE-based SWRO desalination an increasingly attractive water supply option. The research investigates the potential of this approach to restore forests on arid or semi-arid lands over a 70-year period (2030-2100), considering the long-term carbon sequestration potential of established forests, not short-rotation commercial plantations. The LUT Energy System Transition Model (LUT-ESTM) is employed to assess the energy requirements, water demand, and associated costs of such a large-scale afforestation project globally. Understanding the cost-effectiveness and potential of this approach is crucial for developing effective climate change mitigation strategies and integrating it within existing portfolios that include bioenergy carbon capture and storage (BECCS) and direct air carbon capture and storage (DACCS). The context of this study is the urgent need for large-scale carbon dioxide removal to mitigate global warming, with estimates suggesting a requirement of 150-1180 GtCO₂ removal by the end of the century to limit warming to 1.5°C. Existing afforestation efforts, while significant, are insufficient to meet this demand, highlighting the need for innovative approaches like the one presented here.

Existing literature highlights the potential and limitations of afforestation as a CDR method. Studies estimate global afforestation potentials, ranging up to 1.5 GtCO₂ yr⁻¹ in 2050 at US$50 per tCO₂, with higher potentials at higher costs. However, these estimates often neglect the limitations imposed by water availability and land use conflicts with agriculture. Several studies have examined the economic and environmental limitations of various CDR technologies, including afforestation, highlighting the significant land and water requirements of afforestation compared to other methods. The cost-effectiveness of afforestation has been estimated, but the constraint of water resources has significantly restricted the projected role of afforestation in limiting global temperature rise to 1.5 °C. Previous research has modeled the potential of using seawater desalination to irrigate urban trees to offset carbon emissions, focusing on smaller-scale projects. This study builds upon these findings by expanding the scope to a global level, considering large-scale afforestation projects on arid lands with RE-powered desalination. The feasibility of RE-based SWRO desalination is well-established, with studies demonstrating its cost-effectiveness in regions with abundant renewable resources and limited freshwater sources. The literature on carbon sequestration by various tree species in arid and tropical climates provides essential data for modeling the long-term carbon sequestration potential of the proposed afforestation approach. Studies investigating the biogeophysical effects of afforestation in arid regions, such as the impact on radiation load and precipitation, are also considered in the analysis. Finally, the literature on the comparison of different CDR options, including BECCS and DACCS, provides a basis for assessing the relative cost-effectiveness and potential of the proposed afforestation approach.

The study utilizes the LUT Energy System Transition Model (LUT-ESTM) to analyze the potential of afforestation on arid lands using RE-based SWRO desalination. First, suitable land areas are identified by combining data on restoration potential (areas where natural tree cover would exist without human influence), bare land areas, and water stress maps. Areas requiring desalination are determined based on water stress levels, water supply, and demand. A combination of eight tree species suitable for arid and tropical conditions is selected, and their carbon sequestration and water demands are modeled over the period 2030-2100. The carbon sequestration potential is calculated based on allometry equations and carbon sequestration data from the literature, considering aboveground and belowground biomass, dead wood, litter, and soil carbon. The water demand is calculated based on canopy area, location-specific reference evapotranspiration (ET), tree-specific water use, and irrigation efficiency. The model accounts for potential increases in precipitation due to increased tree cover, with an upper limit of 26% based on data from the Sahara Desert. The LUT-ESTM then analyzes the energy requirements for desalination and water pumping, optimizing the energy system using solar PV, wind power, and battery storage. The model determines the levelized cost of electricity (LCOE), levelized cost of water (LCOW), and the cost of CO₂ sequestration for each region and country, considering energy costs, desalination costs, irrigation costs, land costs, and the cumulative CO₂ sequestered. The model operates at an hourly temporal resolution and a 0.5° x 0.5° spatial resolution. The economic parameters, including capital costs, operating costs, and lifetimes of energy system components and desalination systems, are based on data from the literature. The model considers the decommissioning and replacement of system components throughout the 70-year period. The annual historic CO₂ cost is calculated by annualizing the total system costs and dividing them by the average annual CO₂ sequestration rate. Detailed calculations and equations are provided in the Supplementary Data 1. Data sources include publicly available global land cover maps, water stress maps, climate data, and literature on tree allometry, carbon sequestration, water use, and energy system costs.

The study's key findings are as follows: 1. **Significant CO₂ Sequestration Potential:** The global cumulative CO₂ sequestration potential from afforesting arid lands with RE-based SWRO desalination is estimated to be 730 GtCO₂ between 2030 and 2100. The Middle East and North Africa (MENA) region exhibits the highest potential (131 GtCO₂ by 2070), followed by Sub-Saharan Africa (87 GtCO₂). 2. **Decreasing Costs:** The global average cost of CO₂ sequestration decreases significantly over time, from €457 per tCO₂ in 2030 to €99 per tCO₂ by 2100. This decrease is driven by declining RE costs and increasing CO₂ sequestration rates of the forests. 3. **Regional Cost Variation:** Regional differences in costs exist, with coastal regions with abundant solar resources and cooler climates experiencing the lowest costs. By 2070, some regions may achieve costs as low as €50 per tCO₂. 4. **Energy System Characteristics:** By 2050, solar PV constitutes over 80% of electricity generation in regions with afforestation potential. Battery storage complements solar PV generation, meeting up to 67% of the global electricity demand. 5. **Water Demand and Energy Efficiency:** The global average water demand per tonne of CO₂ stabilizes at around 198 m³ by 2100. The energy demand per unit tonne of CO₂ also stabilizes at around 1 MWh per tCO₂ by 2100. Countries with shorter pumping distances exhibit lower energy demands for water pumping. 6. **Comparison with other CDR options:** By mid-century, the cost of the proposed afforestation approach may be comparable to or higher than DACCS, but on a country-specific basis, it may be more cost-effective in certain regions, with the added benefit of land restoration. However, a significant time delay (around 20 years) exists before substantial CO₂ sequestration benefits are realized.

The findings suggest that afforestation on arid lands using RE-based SWRO desalination represents a substantial, albeit initially expensive, CDR opportunity. While the initial high costs (€457 per tCO₂ in 2030) might seem prohibitive, the rapidly decreasing costs of RE and the increasing carbon sequestration capacity of maturing forests make this approach increasingly competitive with other CDR technologies like DACCS and BECCS, particularly in the longer term. The study highlights the importance of considering not only techno-economic factors but also the significant co-benefits of forest restoration, such as combating desertification, soil erosion, and floods, and improving water cycles. The regional variation in costs emphasizes the potential for cost-effective implementation in specific locations. However, the 20-year time lag before substantial sequestration benefits are realized poses a challenge for integrating this approach into short-term climate mitigation strategies. Further research is needed to investigate the biogeophysical impacts of large-scale afforestation on arid lands and refine the model's assumptions regarding precipitation increase, tree growth, and water demands. Addressing the issue of brine discharge from desalination plants is also critical to the long-term sustainability of this approach. The potential for mineral recovery and brine reuse in industrial processes can further reduce costs and environmental impacts. The comparison with other CDR technologies suggests that this afforestation method could become a significant CDR option alongside DACCS, offering substantial co-benefits in regions with high solar irradiation and water scarcity.

This research demonstrates the substantial potential of afforesting arid lands using renewable energy-powered desalination as a CDR method. While initial costs are high, they decline significantly over time, making it increasingly competitive with other CDR options. The co-benefits of land restoration and improvements in local water cycles further enhance its attractiveness. Future research should focus on improving the accuracy of carbon sequestration and precipitation models, exploring brine management strategies, and investigating the biogeophysical impacts of large-scale afforestation on arid regions to refine cost estimations and optimize project planning. The findings highlight the need for diverse CDR portfolios that incorporate various approaches with varying temporal and spatial scales.

The study acknowledges several limitations. The model's accuracy depends on the reliability of data on carbon sequestration by trees in arid conditions, the diversity of tree species considered, and the relationship between tree cover and precipitation increases. The model's projection of future RE costs after 2050 is based on assumptions due to data limitations. The actual afforestation potential may vary from the theoretical potential estimated in the study, due to factors such as land conversion to agriculture, climate change impacts (forest fires, floods), and uncertainties in canopy cover estimations. The model also uses a simplified approach to the cost of pumping water over long distances. The assumption of a constant weighted average cost of capital (WACC) of 5% for all regions and years might not accurately reflect real-world conditions. The study does not account for the potential impacts of large-scale afforestation on dust plumes and their influence on other ecosystems. Finally, the long-term maintenance and management requirements of the forests and the uncertainties related to factors such as forest fires are not fully addressed. These factors could potentially influence the cost-effectiveness and long-term viability of the proposed approach.