Integrated assessment modeling of a zero-emissions global transportation sector.

Currently responsible for over one fifth of carbon emissions worldwide, the transportation sector will need to undergo a substantial technological transition to ensure compatibility with global climate goals. Few studies have modeled strategies to achieve zero emissions across all transportation modes, including aviation and shipping, alongside an integrated analysis of feedbacks on other sectors and environmental systems. Here, we use a global integrated assessment model to evaluate deep decarbonization scenarios for the transportation sector consistent with maintaining end-of-century warming below 1.5 °C, considering varied timelines for fossil fuel phase-out and implementation of advanced alternative technologies. We highlight the leading low carbon technologies for each transportation mode, finding that electrification contributes most to decarbonization across the sector. Biofuels and hydrogen are particularly important for aviation and shipping. Our most ambitious scenario eliminates transportation emissions by mid-century, contributing substantially to achieving climate targets but requiring rapid technological shifts with integrated impacts on fuel demands and availability and upstream energy transitions.

Supply and Demand Drivers of Global Hydrogen Deployment in the Transition toward a Decarbonized Energy System.

The role of hydrogen in energy system decarbonization is being actively examined by the research and policy communities. We evaluate the potential "hydrogen economy" in global climate change mitigation scenarios using the Global Change Analysis Model (GCAM). We consider major hydrogen production methods in conjunction with delivery options to understand how hydrogen infrastructure affects its deployment. We also consider a rich set of hydrogen end-use technologies and vary their costs to understand how demand technologies affect deployment. We find that the availability of hydrogen transmission and distribution infrastructure primarily affects the hydrogen production mix, particularly the share produced centrally versus on-site, whereas assumptions about end-use technology primarily affect the scale of hydrogen deployment. In effect, hydrogen can be a source of distributed energy, enabled by on-site renewable electrolysis and, to a lesser extent, by on-site production at industrial facilities using natural gas with carbon capture and storage (CCS). While the share of hydrogen in final energy is small relative to the share of other major energy carriers in our scenarios, hydrogen enables decarbonization in difficult-to-electrify end uses, such as industrial high-temperature heat. Hydrogen deployment, and in turn its contribution to greenhouse gas mitigation, increases as the climate objective is tightened.

Choices in land representation materially affect modeled biofuel carbon intensity estimates.

Estimates of biofuel carbon intensity are uncertain and depend on modeled land use change (LUC) emissions. While analysts have focused on economic and agronomic assumptions affecting the quantity of land converted, researchers have paid less attention to how models classify land into broad categories and designate some categories as ineligible for LUC. To explore the effect of these land representation attributes, we use three versions of a global human and Earth systems model, GCAM, and compute the "carbon intensity of land-use change" (CI-LUC) from increased U.S. corn ethanol production. We consider uncertainty in model parameters along with the choice of land representation and find the latter is one of the most influential parameters on estimated CI-LUC. A version of the model that protects 90% of non-commercial land reduced estimated CI-LUC by an average of 32% across Monte Carlo trials compared to our baseline model. Another version that mimics the GTAP-BIO-ADV land representation, which protects all non-commercial land, reduced CI-LUC by an average of 19%. The results of this experiment demonstrate that land representation in biofuel LUC models is an important determinant of CI-LUC.

Implication of imposing fertilizer limitations on energy, agriculture, and land systems.

Since the 1950's, global fertilizer usage has increased by more than 800% resulting in detrimental impacts to the environment. The projected increase in crop production due to increasing demands for food, feed, biofuel, and other uses, may further increase fertilizer usage. Studies have examined achieving agricultural intensification in environmentally sustainable ways, however, they have not focused on the whole-system economic aspects of changes in fertilizer usage over the long term. We utilize the Global Change Analysis Model (GCAM) to explore the impact of reducing global fertilizer usage on land use change, agricultural commodity price and production, energy production, and greenhouse gas emissions. We find that constrained fertilizer availability results in reduced global cropland area, particularly land used for bioenergy production, and expanded forested area. These results are driven by price impacts which lead to shifts in agricultural production between commodity types, regions, and technologies, and which lead to decreased agricultural commodity demands.

Land-based climate change mitigation measures can affect agricultural markets and food security.

Earlier studies have noted potential adverse impacts of land-related emissions mitigation strategies on food security, particularly due to food price increases-but without distinguishing these strategies' individual effects under different conditions. Using six global agroeconomic models, we show the extent to which three factors-non-CO2 emissions reduction, bioenergy production and afforestation-may change food security and agricultural market conditions under 2 °C climate-stabilization scenarios. Results show that afforestation (often simulated in the models by imposing carbon prices on land carbon stocks) could have a large impact on food security relative to non-CO2 emissions policies (generally implemented as emissions taxes). Respectively, these measures put an additional 41.9 million and 26.7 million people at risk of hunger in 2050 compared with the current trend scenario baseline. This highlights the need for better coordination in emissions reduction and agricultural market management policies as well as better representation of land use and associated greenhouse gas emissions in modelling.

Deep mitigation of CO2 and non-CO2 greenhouse gases toward 1.5 °C and 2 °C futures.

Stabilizing climate change well below 2 °C and towards 1.5 °C requires comprehensive mitigation of all greenhouse gases (GHG), including both CO2 and non-CO2 GHG emissions. Here we incorporate the latest global non-CO2 emissions and mitigation data into a state-of-the-art integrated assessment model GCAM and examine 90 mitigation scenarios pairing different levels of CO2 and non-CO2 GHG abatement pathways. We estimate that when non-CO2 mitigation contributions are not fully implemented, the timing of net-zero CO2 must occur about two decades earlier. Conversely, comprehensive GHG abatement that fully integrates non-CO2 mitigation measures in addition to a net-zero CO2 commitment can help achieve 1.5 °C stabilization. While decarbonization-driven fuel switching mainly reduces non-CO2 emissions from fuel extraction and end use, targeted non-CO2 mitigation measures can significantly reduce fluorinated gas emissions from industrial processes and cooling sectors. Our integrated modeling provides direct insights in how system-wide all GHG mitigation can affect the timing of net-zero CO2 for 1.5 °C and 2 °C climate change scenarios.

Dynamic Linking of Upstream Energy and Freight Demands for Bio and Fossil Energy Pathways in the Global Change Analysis Model.

Comprehensive study of the environmental impacts associated with demand for an energy resource or carrier in any one sector requires a full consideration of the direct and indirect impacts on the rest of the regional and global energy system. Biofuels are especially complex since they have feedbacks to both the energy system and to regional and global crop markets. In this study, we present a strategy for dynamically including the upstream energy and transportation links to the Global Change Analysis Model. We incorporate the following inter-sectoral linkages: energy inputs to crop production, energy inputs to fossil resource production, and freight transport requirements of energy and agricultural commodities. We assess the implications of explicitly including these links by measuring the global impacts of increased corn ethanol demand in the United States with and without these links included. Although the net global impact of the upstream links on energy and emissions are relatively modest in the scenarios analyzed, the inclusion of these links illustrates interesting trade-offs in energy and transportation demand among fossil fuel and agriculture sectors. We find that the increment in agricultural energy driven by the additional biofuel production associated with the corn ethanol shock is higher than the decrease of energy associated with the displaced fossil fuel consumption. However, this effect is compensated by the reduction in freight transportation requirements of energy. These sectoral interactions suggest that this level of modeling detail could be important in evaluating future analytical questions.

The domestic and international implications of future climate for U.S. agriculture in GCAM.

Agricultural crop yields are susceptible to changes in future temperature, precipitation, and other Earth system factors. Future changes to these physical Earth system attributes and their effects on agricultural crop yields are highly uncertain. United States agricultural producers will be affected by such changes whether they occur domestically or internationally through international commodity markets. Here we present a replication study of previous investigations (with different models) showing that potential direct domestic climate effects on crop yields in the U.S. have financial consequences for U.S. producers on the same order of magnitude but opposite in sign to indirect financial impacts on U.S. producers from climate effects on crop yields elsewhere in the world. We conclude that the analysis of country-specific financial climate impacts cannot ignore indirect effects arising through international markets. We find our results to be robust across a wide range of potential future crop yield impacts analyzed in the multi-sector dynamic global model GCAM.

Key determinants of global land-use projections.

Land use is at the core of various sustainable development goals. Long-term climate foresight studies have structured their recent analyses around five socio-economic pathways (SSPs), with consistent storylines of future macroeconomic and societal developments; however, model quantification of these scenarios shows substantial heterogeneity in land-use projections. Here we build on a recently developed sensitivity approach to identify how future land use depends on six distinct socio-economic drivers (population, wealth, consumption preferences, agricultural productivity, land-use regulation, and trade) and their interactions. Spread across models arises mostly from diverging sensitivities to long-term drivers and from various representations of land-use regulation and trade, calling for reconciliation efforts and more empirical research. Most influential determinants for future cropland and pasture extent are population and agricultural efficiency. Furthermore, land-use regulation and consumption changes can play a key role in reducing both land use and food-security risks, and need to be central elements in sustainable development strategies.

A pathway of global food supply adaptation in a world with increasingly constrained groundwater.

Many of the world's major freshwater aquifers are being exploited unsustainably, with some projected to approach environmentally unsafe drawdown limits within the 21st century. Given that aquifer depletion tends to occur in important crop producing regions, the prospect of running dry poses a significant threat to global food security. Here we use the Global Change Assessment Model (GCAM) to explore the response of land use and agriculture sectors to severe constraints on global water resources. We simulate a scenario in which a number of important groundwater aquifers become depleted to the point where further water withdrawal is unviable, either due to excessive extraction costs or environmental limits being reached. Results are then benchmarked against a scenario that neglects constraints on water withdrawals. We find that groundwater depletion and associated water price increases drive two distinct responses in the agriculture sector: an expansion of rain fed agriculture, and a shift in irrigated crop production toward regions with cheaper water resources. Losses in crop production are most pronounced in water stressed regions where groundwater is being depleted unsustainably to meet irrigation demands-namely northwest India, Pakistan, the Middle East, western United States, Mexico, and Central Asia. While these results highlight substantial risks for the affected regional agricultural economies, we show that modest changes in irrigation and location of crop growth, in a world with frictionless trade, could ensure global food demands are met despite severe water constraints.

The Paris pledges and the energy-water-land nexus in Latin America: Exploring implications of greenhouse gas emission reductions.

In the 2015 Paris Agreement, nations worldwide pledged emissions reductions (Nationally Determined Contributions-NDCs) to avert the threat of climate change, and agreed to periodically review these pledges to strengthen their level of ambition. Previous studies have analyzed NDCs largely in terms of their implied contribution to limit global warming, their implications on the energy sector or on mitigation costs. Nevertheless, a gap in the literature exists regarding the understanding of implications of the NDCs on countries' Energy-Water-Land nexus resource systems. The present paper explores this angle within the regional context of Latin America by employing the Global Change Assessment Model, a state-of-the-art integrated assessment model capable of representing key system-wide interactions among nexus sectors and mitigation policies. By focusing on Brazil, Mexico, Argentina and Colombia, we stress potential implications on national-level water demands depending on countries' strategies to enforce energy-related emissions reductions and their interplays with the land sector. Despite the differential implications of the Paris pledges on each country, increased water demands for crop and biomass irrigation and for electricity generation stand out as potential trade-offs that may emerge under the NDC policy. Hence, this study underscores the need of considering a nexus resource planning framework (known as "Nexus Approach") in the forthcoming NDCs updating cycles as a mean to contribute toward sustainable development.

Role of the Freight Sector in Future Climate Change Mitigation Scenarios.

The freight sector's role is examined using the Global Change Assessment Model (GCAM) for a range of climate change mitigation scenarios and future freight demand assumptions. Energy usage and CO2 emissions from freight have historically grown with a correlation to GDP, and there is limited evidence of near-term global decoupling of freight demand from GDP. Over the 21st century, greenhouse gas (GHG) emissions from freight are projected to grow faster than passenger transportation or other major end-use sectors, with the magnitude of growth dependent on the assumed extent of long-term decoupling. In climate change mitigation scenarios that apply a price to GHG emissions, mitigation of freight emissions (including the effects of demand elasticity, mode and technology shifting, and fuel substitution) is more limited than for other demand sectors. In such scenarios, shifting to less-emitting transportation modes and technologies is projected to play a relatively small role in reducing freight emissions in GCAM. By contrast, changes in the supply chain of liquid fuels that reduce the fuel carbon intensity, especially deriving from large-scale use of biofuels coupled to carbon capture and storage technologies, are responsible for the majority of freight emissions mitigation, followed by price-induced reduction in freight demand services.

Assessing uncertainties in land cover projections.

Understanding uncertainties in land cover projections is critical to investigating land-based climate mitigation policies, assessing the potential of climate adaptation strategies and quantifying the impacts of land cover change on the climate system. Here, we identify and quantify uncertainties in global and European land cover projections over a diverse range of model types and scenarios, extending the analysis beyond the agro-economic models included in previous comparisons. The results from 75 simulations over 18 models are analysed and show a large range in land cover area projections, with the highest variability occurring in future cropland areas. We demonstrate systematic differences in land cover areas associated with the characteristics of the modelling approach, which is at least as great as the differences attributed to the scenario variations. The results lead us to conclude that a higher degree of uncertainty exists in land use projections than currently included in climate or earth system projections. To account for land use uncertainty, it is recommended to use a diverse set of models and approaches when assessing the potential impacts of land cover change on future climate. Additionally, further work is needed to better understand the assumptions driving land use model results and reveal the causes of uncertainty in more depth, to help reduce model uncertainty and improve the projections of land cover.

Global and Regional Evaluation of Energy for Water.

Despite significant effort to quantify the interdependence of the water and energy sectors, global requirements of energy for water (E4W) are still poorly understood, which may result in biases in projections and consequently in water and energy management and policy. This study estimates water-related energy consumption by water source, sector, and process for 14 global regions from 1973 to 2012. Globally, E4W amounted to 10.2 EJ of primary energy consumption in 2010, accounting for 1.7%-2.7% of total global primary energy consumption, of which 58% pertains to fresh surface water, 30% to fresh groundwater, and 12% to nonfresh water, assuming median energy intensity levels. The sectoral E4W allocation includes municipal (45%), industrial (30%), and agricultural (25%), and main process-level contributions are from source/conveyance (39%), water purification (27%), water distribution (12%), and wastewater treatment (18%). While the United States was the largest E4W consumer from the 1970s until the 2000s, the largest consumers at present are the Middle East, India, and China, driven by rapid growth in desalination, groundwater-based irrigation, and industrial and municipal water use, respectively. The improved understanding of global E4W will enable enhanced consistency of both water and energy representations in integrated assessment models.

Hotspots of uncertainty in land-use and land-cover change projections: a global-scale model comparison.

Model-based global projections of future land-use and land-cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global-scale LULC change models representing a wide range of assumptions of future biophysical and socioeconomic conditions. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios, we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g., boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process and improving the allocation mechanisms of LULC change models remain important challenges. Current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches, and many studies ignore the uncertainty in LULC projections in assessments of LULC change impacts on climate, water resources or biodiversity.

21st century United States emissions mitigation could increase water stress more than the climate change it is mitigating.

There is evidence that warming leads to greater evapotranspiration and surface drying, thus contributing to increasing intensity and duration of drought and implying that mitigation would reduce water stresses. However, understanding the overall impact of climate change mitigation on water resources requires accounting for the second part of the equation, i.e., the impact of mitigation-induced changes in water demands from human activities. By using integrated, high-resolution models of human and natural system processes to understand potential synergies and/or constraints within the climate-energy-water nexus, we show that in the United States, over the course of the 21st century and under one set of consistent socioeconomics, the reductions in water stress from slower rates of climate change resulting from emission mitigation are overwhelmed by the increased water stress from the emissions mitigation itself. The finding that the human dimension outpaces the benefits from mitigating climate change is contradictory to the general perception that climate change mitigation improves water conditions. This research shows the potential for unintended and negative consequences of climate change mitigation.

Climate change effects on agriculture: economic responses to biophysical shocks.

Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change's representative concentration pathway with end-of-century radiative forcing of 8.5 W/m(2). The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.