Sustainable BECCS Pathways Evaluated by an Integrated Assessment Model

Negative emissions technologies, particularly Bioenergy with Carbon Capture and Storage (BECCS), are key components of mitigation strategies in future socio-economic scenarios that aim to keep mean global temperature rise below 2°C above pre-industrial, which would require net negative carbon emissions in the end of the 21st century (IPCC, 2013; Fuss et al., 2014). Also, in the context of Paris agreement from COP21, which denotes “a balance between anthropogenic emissions by sources and removals by sinks of greenhouse gases in the second half of this century”, RD&D of the negative emissions technologies in this decade has a crucial role for the early deployment of them. Because of the requirement of potentially extensive use for land and water for producing the bioenergy feedstock to get the anticipated level of negative emissions, researches on how to develop sustainable scenarios of BECCS is crucial. Here, we present BECCS deployment scenarios that consider interaction of economically viable flow of bioenergy system including power generation and conversion to liquid and gaseous fuels for transportation and heat, their carbon balances, biophysical limit of bioenergy productivity, and food security. In the modelling process, detailed bioenergy representations, i.e. various feedstock and conversion technologies with and without CCS, are implemented in an integrated assessment (IA) model GRAPE (Global Relationship Assessment to Protect the Environment). Also, to overcome a general discrepancy about assumed future agricultural yield between \u27top-down\u27 IA models and \u27bottom-up\u27 estimates, which would crucially affect the land-use pattern, we applied yields change of food and energy crops consistent with process-based biophysical crop models in consideration of changing climate conditions. Using the framework, economically viable strategy for implementing sustainable bioenergy and BECCS flow are evaluated in the emission scenarios targeting to keep global average temperature rise below 2°C and/or 1.5°C above pre-industrial

Demand-side decarbonization and electrification: EMF 35 JMIP study

Japan’s long-term strategy submitted to the United Nations Framework Convention on Climate Change emphasizes the importance of improving the electrification rates to reducing GHG emissions. Using the five models participating in Energy Modeling Forum 35 Japan Model Intercomparison project (JMIP), we focused on the demand-side decarbonization and analyzed the final energy composition required to achieve 80% reductions in GHGs by 2050 in Japan. The model results show that the electricity share in final energy use (electrification rate) needs to reach 37–66% in 2050 (26% in 2010) to achieve the emissions reduction of 80%. The electrification rate increases mainly due to switching from fossil fuel end-use technologies (i.e. oil water heater, oil stove and combustion-engine vehicles) to electricity end-use technologies (i.e. heat pump water heater and electric vehicles). The electricity consumption in 2050 other than AIM/Hub ranged between 840 and 1260 TWh (AIM/Hub: 1950TWh), which is comparable to the level seen in the last 10 years (950–1035 TWh). The pace at which electrification rate must be increased is a challenge. The model results suggest to increase the electrification pace to 0.46–1.58%/yr from 2030 to 2050. Neither the past electrification pace (0.30%/year from 1990 to 2010) nor the outlook of the Ministry of Economy, Trade and Industry (0.15%/year from 2010 to 2030) is enough to reach the suggested electrification rates in 2050. Therefore, more concrete measures to accelerate dissemination of electricity end-use technologies across all sectors need to be established

Implications of climate change mitigation strategies on international bioenergy trade

Most climate change mitigation scenarios rely on increased use of bioenergy to decarbonize the energy system. Here we use results from the 33rd Energy Modeling Forum study (EMF-33) to investigate projected international bioenergy trade for different integrated assessment models across several climate change mitigation scenarios. Results show that in scenarios with no climate policy, international bioenergy trade is likely to increase over time, and becomes even more important when climate targets are set. More stringent climate targets, however, do not necessarily imply greater bioenergy trade compared to weaker targets, as final energy demand may be reduced. However, the scaling up of bioenergy trade happens sooner and at a faster rate with increasing climate target stringency. Across models, for a scenario likely to achieve a 2 °C target, 10–45 EJ/year out of a total global bioenergy consumption of 72–214 EJ/year are expected to be traded across nine world regions by 2050. While this projection is greater than the present trade volumes of coal or natural gas, it remains below the present trade of crude oil. This growth in bioenergy trade largely replaces the trade in fossil fuels (especially oil) which is projected to decrease significantly over the twenty-first century. As climate change mitigation scenarios often show diversified energy systems, in which numerous world regions can act as bioenergy suppliers, the projections do not necessarily lead to energy security concerns. Nonetheless, rapid growth in the trade of bioenergy is projected in strict climate mitigation scenarios, raising questions about infrastructure, logistics, financing options, and global standards for bioenergy production and trade. © 2020, The Author(s)

Current Status and Future of Land Surface Models

Although climate conditions primarily determine the distribution and functioning of vegetation, vegetation also influences climate via biophysical and biogeochemical features such as evapotranspiration, albedo, carbon cycling, trace gas emissions, and the roughness of the land surface. Forecasts of rapid climate change during the next 100~200 years, fueled by an increase in greenhouse gases, have motivated the development of land surface models (LSMs) that predict changes in vegetation functions. Here, we review how these models have been developed and used to simulate interactive processes between climate and the land surface. Current limitations and future perspectives of the LSMs are also presented

Evaluation of global terrestrial evapotranspiration using state-of-the-art approaches in remote sensing, machine learning and land surface modeling

Evapotranspiration (ET) is critical in linking global water, carbon and energy cycles. However, direct measurement of global terrestrial ET is not feasible. Here, we first reviewed the basic theory and state-of-the-art approaches for estimating global terrestrial ET, including remote-sensing-based physical models, machine-learning algorithms and land surface models (LSMs). We then utilized 4 remote-sensing-based physical models, 2 machine-learning algorithms and 14 LSMs to analyze the spatial and temporal variations in global terrestrial ET. The results showed that the ensemble means of annual global terrestrial ET estimated by these three categories of approaches agreed well, with values ranging from 589.6 mm yr−1 (6.56×104 km3 yr−1) to 617.1 mm yr−1 (6.87×104 km3 yr−1). For the period from 1982 to 2011, both the ensembles of remote-sensing-based physical models and machine-learning algorithms suggested increasing trends in global terrestrial ET (0.62 mm yr−2 with a significance level of p0.05), although many of the individual LSMs reproduced an increasing trend. Nevertheless, all 20 models used in this study showed that anthropogenic Earth greening had a positive role in increasing terrestrial ET. The concurrent small interannual variability, i.e., relative stability, found in all estimates of global terrestrial ET, suggests that a potential planetary boundary exists in regulating global terrestrial ET, with the value of this boundary being around 600 mm yr−1. Uncertainties among approaches were identified in specific regions, particularly in the Amazon Basin and arid/semiarid regions. Improvements in parameterizing water stress and canopy dynamics, the utilization of new available satellite retrievals and deep-learning methods, and model–data fusion will advance our predictive understanding of global terrestrial ET

Plant Regrowth as a Driver of Recent Enhancement of Terrestrial CO2 Uptake

The increasing strength of land CO2 uptake in the 2000s has been attributed to a stimulating effect of rising atmospheric CO2 on photosynthesis (CO2 fertilization). Using terrestrial biosphere models, we show that enhanced CO2 uptake is induced not only by CO2 fertilization but also an increasing uptake by plant regrowth (accounting for 0.33 ± 0.10 Pg C/year increase of CO2 uptake in the 2000s compared with the 1960s-1990s) with its effect most pronounced in eastern North America, southern‐eastern Europe, and southeastern temperate Eurasia. Our analysis indicates that ecosystems in North America and Europe have established the current productive state through regrowth since the 1960s, and those in temperate Eurasia are still in a stage from regrowth following active afforestation in the 1980s-1990s. As the strength of model representation of CO2 fertilization is still in debate, plant regrowth might have a greater potential to sequester carbon than indicated by this study

Contrasting effects of CO₂ fertilization, land-use change and warming on seasonal amplitude of Northern Hemisphere CO₂ exchange

Continuous atmospheric CO₂ monitoring data indicate an increase in the amplitude of seasonal CO₂-cycle exchange (SCA_(NBP)) in northern high latitudes. The major drivers of enhanced SCA_(NBP) remain unclear and intensely debated, with land-use change, CO₂ fertilization and warming being identified as likely contributors. We integrated CO₂-flux data from two atmospheric inversions (consistent with atmospheric records) and from 11 state-of-the-art land-surface models (LSMs) to evaluate the relative importance of individual contributors to trends and drivers of the SCA_(NBP) of CO₂ fluxes for 1980–2015. The LSMs generally reproduce the latitudinal increase in SCA_(NBP) trends within the inversions range. Inversions and LSMs attribute SCA_(NBP) increase to boreal Asia and Europe due to enhanced vegetation productivity (in LSMs) and point to contrasting effects of CO₂ fertilization (positive) and warming (negative) on SCA_(NBP). Our results do not support land-use change as a key contributor to the increase in SCA_(NBP). The sensitivity of simulated microbial respiration to temperature in LSMs explained biases in SCA_(NBP) trends, which suggests that SCA_(NBP) could help to constrain model turnover times

Respiration driven CO2 pulses dominate Australia's flux variability

The Australian continent contributes substantially to the year-to-year variability of the global terrestrial carbon dioxide (CO2) sink. However, the scarcity of in-situ observations in remote areas prevents deciphering the processes that force the CO2 flux variability. Here, examining atmospheric CO2 measurements from satellites in the period 2009-2018, we find recurrent end-of-dry-season CO2 pulses over the Australian continent. These pulses largely control the year-to-year variability of Australia's CO2 balance, due to 2-3 times higher seasonal variations compared to previous top-down inversions and bottom-up estimates. The CO2 pulses occur shortly after the onset of rainfall and are driven by enhanced soil respiration preceding photosynthetic uptake in Australia's semi-arid regions. The suggested continental-scale relevance of soil rewetting processes has large implications for our understanding and modelling of global climate-carbon cycle feedbacks.Comment: 28 pages (including supplementary materials), 3 main figures, 7 supplementary figure

Process-oriented analysis of dominant sources of uncertainty in the land carbon sink

The observed global net land carbon sink is captured by current land models. All models agree that atmospheric CO$_{2}$ and nitrogen deposition driven gains in carbon stocks are partially offset by climate and land-use and land-cover change (LULCC) losses. However, there is a lack of consensus in the partitioning of the sink between vegetation and soil, where models do not even agree on the direction of change in carbon stocks over the past 60 years. This uncertainty is driven by plant productivity, allocation, and turnover response to atmospheric CO$_{2}$ (and to a smaller extent to LULCC), and the response of soil to LULCC (and to a lesser extent climate). Overall, differences in turnover explain ~70% of model spread in both vegetation and soil carbon changes. Further analysis of internal plant and soil (individual pools) cycling is needed to reduce uncertainty in the controlling processes behind the global land carbon sink