• Energy Research

Abstract The climate mitigation potential of urban nature-based solutions (NBSs) is often perceived as insignificant and thus overlooked, as cities primarily pursue NBSs for local ecosystem services. Given the rising interest and capacities in cities for such projects, the potential of urban forests for climate mitigation needs to be better understood. We modelled the global potential and limits of urban reforestation worldwide, and find that 10.9 ± 2.8 Mha of land (17.6% of all city areas) are suitable for reforestation, which would offset 82.4 ± 25.7 MtCO2e yr−1 of carbon emissions. Among the cities analysed, 1189 are potentially able to offset >25% of their city carbon emissions through reforestation. Urban natural climate solutions should find a place on global and local agendas.

Abstract The climate mitigation potential of urban nature-based solutions (NBSs) is often perceived as insignificant and thus overlooked, as cities primarily pursue NBSs for local ecosystem services. Given the rising interest and capacities in cities for such projects, the potential of urban forests for climate mitigation needs to be better understood. We modelled the global potential and limits of urban reforestation worldwide, and find that 10.9 ± 2.8 Mha of land (17.6% of all city areas) are suitable for reforestation, which would offset 82.4 ± 25.7 MtCO2e yr−1 of carbon emissions. Among the cities analysed, 1189 are potentially able to offset >25% of their city carbon emissions through reforestation. Urban natural climate solutions should find a place on global and local agendas.

Abstract Despite the looming land scarcity for agriculture, cropland abandonment is widespread globally. Abandoned cropland can be reused to support food security and climate change mitigation. Here, we investigate the potentials and trade-offs of using global abandoned cropland for recultivation and restoring forests by natural regrowth, with spatially-explicit modelling and scenario analysis. We identify 101 Mha of abandoned cropland between 1992 and 2020, with a capability of concurrently delivering 29 to 363 Peta-calories yr− 1 of food production potential and 290 to 1,066 MtCO2 yr− 1 of net climate change mitigation potential, depending on land-use suitability and land allocation strategies. We also show that applying spatial prioritization is key to maximizing the achievable potentials of abandoned cropland and demonstrate other possible approaches to further increase these potentials. Our findings offer timely insights into the potentials of abandoned cropland and can inform sustainable land management to buttress food security and climate goals.

Abstract Despite the looming land scarcity for agriculture, cropland abandonment is widespread globally. Abandoned cropland can be reused to support food security and climate change mitigation. Here, we investigate the potentials and trade-offs of using global abandoned cropland for recultivation and restoring forests by natural regrowth, with spatially-explicit modelling and scenario analysis. We identify 101 Mha of abandoned cropland between 1992 and 2020, with a capability of concurrently delivering 29 to 363 Peta-calories yr− 1 of food production potential and 290 to 1,066 MtCO2 yr− 1 of net climate change mitigation potential, depending on land-use suitability and land allocation strategies. We also show that applying spatial prioritization is key to maximizing the achievable potentials of abandoned cropland and demonstrate other possible approaches to further increase these potentials. Our findings offer timely insights into the potentials of abandoned cropland and can inform sustainable land management to buttress food security and climate goals.

This data package includes the two 1-km resolution global maps of tropical mangrove forests between ~31°N and 39°S produced from the study: 1) investible mangrove blue carbon (in tCO2e ha-1y-1) and 2) profitable mangrove blue carbon (in tCO2e ha-1y-1). It also includes a sample R script to reproduce these layers and the relative country-level project development and maintenance cost estimates. Investible mangrove blue carbon: To model and produce a spatially explicit map of investible mangrove blue carbon, we first estimated the total volume of CO2e across three pools in mangrove forest areas—aboveground carbon, belowground carbon and soil organic carbon: Aboveground carbon: We used a recent global mangrove aboveground biomass model by Simard et al. 2019 to estimate the volume of aboveground carbon. We applied a stoichiometric factor of 0.475 to convert biomass estimates to carbon stock values. We also performed an uncertainty analyses to account for variability in this stoichiometric factor. We then used a conversion factor of 3.67 to convert carbon stock values to CO2e volume. Belowground carbon: We then used the aboveground biomass from Simard et al. 2019to estimate the belowground (root) biomass, following the allometric equation from Hutchison et al. 2014: Belowground biomass = 0.073 •Aboveground biomass1.32. Our belowground biomass estimations fall within the range of previously derived ratios of aboveground:belowground (root) biomass ratios. We applied the same stoichiometric factor (0.475) and conversion factor (3.67) to estimate the volume of CO2e associated with belowground biomass. Soil organic carbon: Additionally, to fully consider ecosystem mangrove carbon stock, we also utilized mangrove soil carbon stocks obtained from Sanderman et al. 2018, applying a conversion factor (3.67) to estimate the volume of CO2e. To these biomass carbon estimates, we then applied key criteria that enables certification of carbon credits under the rules of the UNFCCC, Kyoto Protocol, and the various voluntary certification standards such as the Verified Carbon Standard (VCS). Importantly, our analyses were guided by the requirements stipulated by VCS—the most widely used voluntary greenhouse gas program globally: Additionality: A major component of certification is ‘additionality’ or the amount of carbon stocks that would have been lost without the intervention of forest protection of the proposed project. To estimate additionality, we assume future rates of mangrove forest loss to follow existing patterns between the years 2000–2016. This data was obtained from Goldberg et al. 2020. This was calculated as the annualized rate of mangrove loss within each ~1 km cell. We then applied this estimated annual deforestation rate to the volume of CO2e associated with mangrove forest (calculated above), to derive the volume of CO2e that would be certifiable and thus investible under the VCS. Decay rates: We also considered the annual decay rate specific to mangrove forests [29]. This was based on two carbon pools—the belowground (root) biomass, with a decay rate of 0.20, and soil organic carbon, with a decay rate of 0.10. These values are based on median estimates from Lovelock et al. 2017, and we also performed an uncertainty analyses to account for variability in these decay rates. Buffer credits: Lastly, we also applied the VCS requirement to set aside buffer credits of 20% net change carbon stocks in each area to account for risk of non-permanence. Profitable mangrove blue carbon: To estimate the relative profitability of these mangrove blue carbon sites, we utilized the map of investible mangrove blue carbon to calculate the net present values (NPV) based on several simplifying assumptions obtained from previous studies’ published data. We first used the cost of project establishment at US$232 ha-1, based on a wide range of costs that are key to the development of a project such as project design, governance and planning, and enforcement. We also used an annual maintenance cost of US$25 ha-1, which can include aspects such as monitoring, finance and administration. Given the potential for establishment and maintenance cost to vary between countries, then weighted this cost by countries’ per capita gross domestic product (GDP) to estimate the relative cost per country. We then assumed a constant carbon price of US$5 t-1CO2e for the first five years, roughly matching the average carbon price of all avoided deforestation projects recorded by Forest Trends’ Ecosystem Marketplace reports between 2006–2018. After the first five years, we assumed a 5% price appreciation for subsequent years over a 30-years project timeframe. Based on these criteria, we calculated the NPV as well as the accumulated profits over the next 30 years, based on a 10% risk-adjusted discount rate. Using the spatially explicit NPV estimates, we excluded areas that were not financially sustainable (negative NPV), and calculated the extent, climate mitigation potential and return-on-investment within the remaining, profitable, areas.. Further details for these datasets are presented in Zeng et. al. For questions or issues on the spatial data layers, please contact Yiwen Zeng (zengyiwen@nus.edu.sg).

This data package includes the two 1-km resolution global maps of tropical mangrove forests between ~31°N and 39°S produced from the study: 1) investible mangrove blue carbon (in tCO2e ha-1y-1) and 2) profitable mangrove blue carbon (in tCO2e ha-1y-1). It also includes a sample R script to reproduce these layers and the relative country-level project development and maintenance cost estimates. Investible mangrove blue carbon: To model and produce a spatially explicit map of investible mangrove blue carbon, we first estimated the total volume of CO2e across three pools in mangrove forest areas—aboveground carbon, belowground carbon and soil organic carbon: Aboveground carbon: We used a recent global mangrove aboveground biomass model by Simard et al. 2019 to estimate the volume of aboveground carbon. We applied a stoichiometric factor of 0.475 to convert biomass estimates to carbon stock values. We also performed an uncertainty analyses to account for variability in this stoichiometric factor. We then used a conversion factor of 3.67 to convert carbon stock values to CO2e volume. Belowground carbon: We then used the aboveground biomass from Simard et al. 2019to estimate the belowground (root) biomass, following the allometric equation from Hutchison et al. 2014: Belowground biomass = 0.073 •Aboveground biomass1.32. Our belowground biomass estimations fall within the range of previously derived ratios of aboveground:belowground (root) biomass ratios. We applied the same stoichiometric factor (0.475) and conversion factor (3.67) to estimate the volume of CO2e associated with belowground biomass. Soil organic carbon: Additionally, to fully consider ecosystem mangrove carbon stock, we also utilized mangrove soil carbon stocks obtained from Sanderman et al. 2018, applying a conversion factor (3.67) to estimate the volume of CO2e. To these biomass carbon estimates, we then applied key criteria that enables certification of carbon credits under the rules of the UNFCCC, Kyoto Protocol, and the various voluntary certification standards such as the Verified Carbon Standard (VCS). Importantly, our analyses were guided by the requirements stipulated by VCS—the most widely used voluntary greenhouse gas program globally: Additionality: A major component of certification is ‘additionality’ or the amount of carbon stocks that would have been lost without the intervention of forest protection of the proposed project. To estimate additionality, we assume future rates of mangrove forest loss to follow existing patterns between the years 2000–2016. This data was obtained from Goldberg et al. 2020. This was calculated as the annualized rate of mangrove loss within each ~1 km cell. We then applied this estimated annual deforestation rate to the volume of CO2e associated with mangrove forest (calculated above), to derive the volume of CO2e that would be certifiable and thus investible under the VCS. Decay rates: We also considered the annual decay rate specific to mangrove forests [29]. This was based on two carbon pools—the belowground (root) biomass, with a decay rate of 0.20, and soil organic carbon, with a decay rate of 0.10. These values are based on median estimates from Lovelock et al. 2017, and we also performed an uncertainty analyses to account for variability in these decay rates. Buffer credits: Lastly, we also applied the VCS requirement to set aside buffer credits of 20% net change carbon stocks in each area to account for risk of non-permanence. Profitable mangrove blue carbon: To estimate the relative profitability of these mangrove blue carbon sites, we utilized the map of investible mangrove blue carbon to calculate the net present values (NPV) based on several simplifying assumptions obtained from previous studies’ published data. We first used the cost of project establishment at US$232 ha-1, based on a wide range of costs that are key to the development of a project such as project design, governance and planning, and enforcement. We also used an annual maintenance cost of US$25 ha-1, which can include aspects such as monitoring, finance and administration. Given the potential for establishment and maintenance cost to vary between countries, then weighted this cost by countries’ per capita gross domestic product (GDP) to estimate the relative cost per country. We then assumed a constant carbon price of US$5 t-1CO2e for the first five years, roughly matching the average carbon price of all avoided deforestation projects recorded by Forest Trends’ Ecosystem Marketplace reports between 2006–2018. After the first five years, we assumed a 5% price appreciation for subsequent years over a 30-years project timeframe. Based on these criteria, we calculated the NPV as well as the accumulated profits over the next 30 years, based on a 10% risk-adjusted discount rate. Using the spatially explicit NPV estimates, we excluded areas that were not financially sustainable (negative NPV), and calculated the extent, climate mitigation potential and return-on-investment within the remaining, profitable, areas.. Further details for these datasets are presented in Zeng et. al. For questions or issues on the spatial data layers, please contact Yiwen Zeng (zengyiwen@nus.edu.sg).

Natural climate solutions (NCS) are an essential complement to climate mitigation and have been increasingly incorporated into international mitigation strategies. Yet, with the ongoing population growth, allocating natural areas for NCS may compete with other socioeconomic priorities, especially urban development and food security. Here, we projected the impacts of land-use competition incurred by cropland and urban expansion on the climate mitigation potential of NCS. We mapped the areas available for implementing 9 key NCS strategies and estimated their climate change mitigation potential. Then, we overlaid these areas with future cropland and urban expansion maps projected under three Shared Socioeconomic Pathway (SSP) scenarios (2020-2100) and calculated the resulting mitigation potential loss of each selected NCS strategy. Our results estimate a substantial reduction, 0.3-2.8 GtCO2 yr-1 or 4-39 %, in NCS mitigation potential, of which cropland expansion for fulfilling future food demand is the primary cause. This impact is particularly severe in the tropics where NCS hold the most abundant mitigation potential. Our findings highlight immediate actions prioritized to tropical areas are important to best realize NCS and are key to developing realistic and sustainable climate policies.