Modeling the Effects of Future Growing Demand for Charcoal in the Tropics

Global demand for charcoal is increasing mainly due to urban population in developing countries. More than half the global population now lives in cities, and urban-dwellers are restricted to charcoal use because of easiness of production, access, transport, and tradition. Increasing demand for charcoal, however, may lead to increasing impacts on forests, food, and water resources, and may even create additional pressures on the climate system. Here we assess how different charcoal scenarios based on the Shared Socio-economic Pathways (SSP) relate to potential biomass supply. For this, we use the energy model TIMER to project the demand for fuelwood and charcoal for different socio-economic pathways for urban and rural populations, globally, and for four tropical regions (Central America, South America, Africa and Indonesia). Second, we assess whether the biomass demands for each scenario can be met with current and projected forest biomass estimated with remote sensing and modeled Net Primary Productivity (NPP) using a Dynamic Global Vegetation Model (LPJ-GUESS). Currently one third of residential energy use is based on traditional bioenergy, including charcoal. Globally, biomass needs by urban households by 2100 under the most sustainable scenario, SSP1, are of 14.4 mi ton biomass for charcoal plus 17.1 mi ton biomass for fuelwood (31.5 mi ton biomass in total). Under SSP3, the least sustainable scenario, we project a need of 205 mi tons biomass for charcoal plus 243.8 mi ton biomass for fuelwood by 2100 (total of 450 mi ton biomass). Africa and South America contribute the most for this biomass demand, however, all areas are able to meet the demand. We find that the future of the charcoal sector is not dire. Charcoal represents a small fraction of the energy requirements, but its biomass demands are disproportionate and in some regions require a large fraction of forest. This could be because of large growing populations moving to urban areas, conversion rates, production inefficiencies, and regions that despite available alternative energy sources still use a substantial amount of charcoal. We present a framework that combines Integrated Assessment Models and local conditions to assess whether a sustainable sector can be achieved

Nitrogen leaching from natural ecosystems under global change : A modelling study

To study global nitrogen (N) leaching from natural ecosystems under changing N deposition, climate, and atmospheric CO2, we performed a factorial model experiment for the period 1901-2006 with the N-enabled global terrestrial ecosystem model LPJ-GUESS (Lund-Potsdam-Jena General Ecosystem Simulator). In eight global simulations, we used either the true transient time series of N deposition, climate, and atmospheric CO2 as input or kept combinations of these drivers constant at initial values. The results show that N deposition is globally the strongest driver of simulated N leaching, individually causing an increase of 88% by 1997-2006 relative to pre-industrial conditions. Climate change led globally to a 31%increase in N leaching, but the size and direction of change varied among global regions: Leaching generally increased in regions with high soil organic carbon storage and high initial N status, and decreased in regions with a positive trend in vegetation productivity or decreasing precipitation. Rising atmospheric CO2 generally caused decreased N leaching (33% globally), with strongest effects in regions with high productivity and N availability. All drivers combined resulted in a rise of N leaching by 73% with strongest increases in Europe, eastern North America and South-East Asia, where N deposition rates are highest. Decreases in N leaching were predicted for the Amazon and northern India. We further found that N loss by fire regionally is a large term in the N budget, associated with lower N leaching, particularly in semi-arid biomes. Predicted global N leaching from natural lands rose from 13.6 TgNyr-1 in 1901-1911 to 18.5 TgNyr-1 in 1997-2006, accounting for reductions of natural land cover. Ecosystem N status (quantified as the reduction of vegetation productivity due to N limitation) shows a similar positive temporal trend but large spatial variability. Interestingly, this variability is more strongly related to vegetation type than N input. Similarly, the relationship between N status and (relative) N leaching is highly variable due to confounding factors such as soil water fluxes, fire occurrence, and growing season length. Nevertheless, our results suggest that regions with very high N deposition rates are approaching a state of N saturation

Nitrogen leaching from natural ecosystems under global change : A modelling study

To study global nitrogen (N) leaching from natural ecosystems under changing N deposition, climate, and atmospheric CO2, we performed a factorial model experiment for the period 1901-2006 with the N-enabled global terrestrial ecosystem model LPJ-GUESS (Lund-Potsdam-Jena General Ecosystem Simulator). In eight global simulations, we used either the true transient time series of N deposition, climate, and atmospheric CO2 as input or kept combinations of these drivers constant at initial values. The results show that N deposition is globally the strongest driver of simulated N leaching, individually causing an increase of 88% by 1997-2006 relative to pre-industrial conditions. Climate change led globally to a 31%increase in N leaching, but the size and direction of change varied among global regions: Leaching generally increased in regions with high soil organic carbon storage and high initial N status, and decreased in regions with a positive trend in vegetation productivity or decreasing precipitation. Rising atmospheric CO2 generally caused decreased N leaching (33% globally), with strongest effects in regions with high productivity and N availability. All drivers combined resulted in a rise of N leaching by 73% with strongest increases in Europe, eastern North America and South-East Asia, where N deposition rates are highest. Decreases in N leaching were predicted for the Amazon and northern India. We further found that N loss by fire regionally is a large term in the N budget, associated with lower N leaching, particularly in semi-arid biomes. Predicted global N leaching from natural lands rose from 13.6 TgNyr-1 in 1901-1911 to 18.5 TgNyr-1 in 1997-2006, accounting for reductions of natural land cover. Ecosystem N status (quantified as the reduction of vegetation productivity due to N limitation) shows a similar positive temporal trend but large spatial variability. Interestingly, this variability is more strongly related to vegetation type than N input. Similarly, the relationship between N status and (relative) N leaching is highly variable due to confounding factors such as soil water fluxes, fire occurrence, and growing season length. Nevertheless, our results suggest that regions with very high N deposition rates are approaching a state of N saturation

Modelling the response of net primary productivity of the Zambezi teak forests to climate change along a rainfall gradient in Zambia

Understanding climate change effects on forests is important considering the role forests play in mitigating climate change. We studied the effects of changes in temperature, rainfall, atmospheric carbon dioxide (CO2) concentration, solar radiation, and number of wet days (as a measure of rainfall intensity) on net primary productivity (NPP) of the Zambian Zambezi teak forests along a rainfall gradient. Using 1960-1989 as a baseline, we projected changes in NPP for the end of the 21st century (2070-2099). We adapted the parameters of the dynamic vegetation model, LPJ-GUESS, to simulate the growth of Zambian forests at three sites along a moisture gradient receiving annual rainfall of between 700 and more than 1000 mm. The adjusted plant functional type was tested against measured data. We forced the model with contemporary climate data (1960-2005) and with climatic forecasts of an ensemble of five general circulation models (GCMs) following Representative Concentration Pathways (RCPs) RCP4.5 and RCP8.5. We used local soil parameter values to characterize texture and measured local tree parameter values for maximum crown area, wood density, leaf longevity, and allometry. The results simulated with the LPJGUESS model improved when we used these newly generated local parameters, indicating that using local parameter values is essential to obtaining reliable simulations at site level. The adapted model setup provided a baseline for assessing the potential effects of climate change on NPP in the studied Zambezi teak forests. Using this adapted model version, NPP was projected to increase by 1.77% and 0.69% at the wetter Kabompo and by 0.44% and 0.10% at the intermediate Namwala sites under RCP8.5 and RCP4.5 respectively, especially caused by the increased CO2 concentration by the end of the 21st century. However, at the drier Sesheke site, NPP would respectively decrease by 0.01% and 0.04% by the end of the 21st century under RCP8.5 and RCP4.5. The projected decreased NPP under RCP8.5 at the Sesheke site results from the reduced rainfall coupled with increasing temperature. We thus demonstrated that differences in the amount of rainfall received in a site per year influence the way in which climate change will affect forest resources. The projected increase in CO2 concentration would thus have more effects on NPP in high rainfall receiving areas, while in arid regions, NPP would be affected more by the changes in rainfall and temperature. CO2 concentrations would therefore be more important in forests that are generally not temperature- or precipitation-limited; however, precipitation will continue to be the limiting factor in the drier sites.</p

Afforestation for climate change mitigation: Potentials, risks and trade-offs, and the role of biophysical climate effects

Afforestation is considered a cost-effective and readily available climate change mitigation option. In recent studies afforestation is presented as a major solution to limit climate change. However, estimates of afforestation potential vary widely. Moreover, the risks in global mitigation policy and the negative trade-offs with food security are often not considered. Here, we present a new approach to assess the economic potential of afforestation with the IMAGE 3.0 integrated assessment model framework (Doelman et al., 2019). In addition, we discuss the role of afforestation in mitigation pathways and the effects of afforestation on the food system under increasingly ambitious climate targets. We show that afforestation has a mitigation potential of 4.9 GtCO2/yr at 200 US/tCO2 in 2050 leading to large-scale application in an SSP2 scenario aiming for 2°C (410 GtCO2 cumulative up to 2100). Afforestation reduces the overall costs of mitigation policy. However, it may lead to lower mitigation ambition and lock-in situations in other sectors. Moreover, it bears risks to implementation and permanence as the negative emissions are increasingly located in regions with high investment risks and weak governance, for example in Sub-Saharan Africa. Our results confirm that afforestation has substantial potential for mitigation. At the same time, we highlight that major risks and trade-offs are involved. Pathways aiming to limit climate change to 2°C or even 1.5°C need to minimize these risks and trade-offs in order to achieve mitigation sustainably.The afforestation study published as Doelman et al. (2019) excluded biophysical climate effects of land use and land cover change on climate, even though this is shown to have a substantial effect especially locally (Alkama & Cescatti, 2016). As a follow-up to this study we implement the grid-specific temperature effects as derived by Duveiller et al. (2020) to the mitigation scenarios with large-scale afforestation to assess the effectiveness of afforestation for climate change mitigation as increased or reduced effectiveness may change cost-optimal climate policy. Notably in the boreal regions this can have a major effect, as transitions from agricultural land to forest are shown to have a substantial warming effect due to reduced albedo limiting the mitigation potential in these regions. Conversely, in the tropical areas the already high mitigation potential of afforestation could be even more efficient, as increased evapotranspiration from forests leads to additional cooling. However, it is uncertain whether the high efficiency of afforestation in tropical regions can be utilized as these are also the regions with high risks to implementation and permanence. ReferencesAlkama, R., & Cescatti, A. (2016). Biophysical climate impacts of recent changes in global forest cover. Science, 351(6273), 600-604.Doelman, J. C., Stehfest, E., van Vuuren, D. P., Tabeau, A., Hof, A. F., Braakhekke, M. C., . . . Lucas, P. L. (2019). Afforestation for climate change mitigation: Potentials, risks and trade-offs. Global Change BiologyDuveiller, G., Caporaso, L., Abad-Viñas, R., Perugini, L., Grassi, G., Arneth, A., & Cescatti, A. (2020). Local biophysical effects of land use and land cover change: towards an assessment tool for policy makers. Land Use Policy, 91, 104382

Modeling forest plantations for carbon uptake with the LPJmL dynamic global vegetation model

We present an extension of the dynamic global vegetation model, Lund-Potsdam-Jena Managed Land (LPJmL), to simulate planted forests intended for carbon (C) sequestration. We implemented three functional types to simulate plantation trees in temperate, tropical, and boreal climates. The parameters of these functional types were optimized to fit target growth curves (TGCs). These curves represent the evolution of stemwood C over time in typical productive plantations and were derived by combining field observations and LPJmL estimates for equivalent natural forests. While the calibrated model underestimates stemwood C growth rates compared to the TGCs, it represents substantial improvement over using natural forests to represent afforestation. Based on a simulation experiment in which we compared global natural forest versus global forest plantation, we found that forest plantations allow for much larger C uptake rates on the timescale of 100 years, with a maximum difference of a factor of 1.9, around 54 years. In subsequent simulations for an ambitious but realistic scenario in which 650Mha (14% of global managed land, 4.5% of global land surface) are converted to forest over 85 years, we found that natural forests take up 37PgC versus 48PgC for forest plantations. Comparing these results to estimations of C sequestration required to achieve the 2°C climate target, we conclude that afforestation can offer a substantial contribution to climate mitigation. Full evaluation of afforestation as a climate change mitigation strategy requires an integrated assessment which considers all relevant aspects, including costs, biodiversity, and trade-offs with other land-use types. Our extended version of LPJmL can contribute to such an assessment by providing improved estimates of C uptake rates by forest plantations.Atmospheric Remote Sensin

Afforestation for climate change mitigation: Potentials, risks and trade-offs, and the role of biophysical climate effects

Afforestation is considered a cost-effective and readily available climate change mitigation option. In recent studies afforestation is presented as a major solution to limit climate change. However, estimates of afforestation potential vary widely. Moreover, the risks in global mitigation policy and the negative trade-offs with food security are often not considered. Here, we present a new approach to assess the economic potential of afforestation with the IMAGE 3.0 integrated assessment model framework (Doelman et al., 2019). In addition, we discuss the role of afforestation in mitigation pathways and the effects of afforestation on the food system under increasingly ambitious climate targets. We show that afforestation has a mitigation potential of 4.9 GtCO2/yr at 200 US/tCO2 in 2050 leading to large-scale application in an SSP2 scenario aiming for 2°C (410 GtCO2 cumulative up to 2100). Afforestation reduces the overall costs of mitigation policy. However, it may lead to lower mitigation ambition and lock-in situations in other sectors. Moreover, it bears risks to implementation and permanence as the negative emissions are increasingly located in regions with high investment risks and weak governance, for example in Sub-Saharan Africa. Our results confirm that afforestation has substantial potential for mitigation. At the same time, we highlight that major risks and trade-offs are involved. Pathways aiming to limit climate change to 2°C or even 1.5°C need to minimize these risks and trade-offs in order to achieve mitigation sustainably.The afforestation study published as Doelman et al. (2019) excluded biophysical climate effects of land use and land cover change on climate, even though this is shown to have a substantial effect especially locally (Alkama & Cescatti, 2016). As a follow-up to this study we implement the grid-specific temperature effects as derived by Duveiller et al. (2020) to the mitigation scenarios with large-scale afforestation to assess the effectiveness of afforestation for climate change mitigation as increased or reduced effectiveness may change cost-optimal climate policy. Notably in the boreal regions this can have a major effect, as transitions from agricultural land to forest are shown to have a substantial warming effect due to reduced albedo limiting the mitigation potential in these regions. Conversely, in the tropical areas the already high mitigation potential of afforestation could be even more efficient, as increased evapotranspiration from forests leads to additional cooling. However, it is uncertain whether the high efficiency of afforestation in tropical regions can be utilized as these are also the regions with high risks to implementation and permanence. ReferencesAlkama, R., & Cescatti, A. (2016). Biophysical climate impacts of recent changes in global forest cover. Science, 351(6273), 600-604.Doelman, J. C., Stehfest, E., van Vuuren, D. P., Tabeau, A., Hof, A. F., Braakhekke, M. C., . . . Lucas, P. L. (2019). Afforestation for climate change mitigation: Potentials, risks and trade-offs. Global Change BiologyDuveiller, G., Caporaso, L., Abad-Viñas, R., Perugini, L., Grassi, G., Arneth, A., & Cescatti, A. (2020). Local biophysical effects of land use and land cover change: towards an assessment tool for policy makers. Land Use Policy, 91, 104382