JP

The feasibility, costs, and environmental implications of large-scale biomass energy

What are the feasibility, costs, and environmental implications of large-scale bioenegry? We investigate this question by developing a detailed representation of bioenergy in a global economy-wide model. We develop a scenario with a global carbon dioxide price, applied to all anthropogenic emissions except those from land use change, that rises from $25 per metric ton in 2015 to $99 in 2050. This creates market conditions favorable to biomass energy, resulting in global non-traditional bioenergy production of ~ 150 exajoules (EJ) in 2050. By comparison, in 2010, global energy production was primarily from coal (138 EJ), oil (171 EJ), and gas (106 EJ). With this policy, 2050 emissions are 42% less in our Base Policy case than our Reference case, although extending the scope of the carbon price to include emissions from land use change would reduce 2050 emissions by 52% relative to the same baseline. Our results from various policy scenarios show that lignocellulosic (LC) ethanol may become the major form of bioenergy, if its production costs fall by amounts predicted in a recent survey and ethanol blending constraints disappear by 2030; however, if its costs remain higher than expected or the ethanol blend wall continues to bind, bioelectricity and bioheat may prevail. Higher LC ethanol costs may also result in the expanded production of first-generation biofuels (ethanol from sugarcane and corn) so that they remain in the fuel mix through 2050. Deforestation occurs if emissions from land use change are not priced, although the availability of biomass residues and improvements in crop yields and conversion efficiencies mitigate pressure on land markets. As regions are linked via international agricultural markets, irrespective of the location of bioenergy production, natural forest decreases are largest in regions with the lowest barriers to deforestation. In 2050, the combination of carbon price and bioenergy production increases food prices by 3.2%–5.2%, with bioenergy accounting for 1.3%–3.5%.

The impact of climate change on wind and solar resources in southern Africa

The mitigation of potential climate change while sustaining energy resources requires global attention and cooperation. Among the numerous strategies to reduce Green House Gas (GHG) emissions is to decommission carbon intensive electricity production while increase the deployment of renewable energy technologies – such as wind and solar power generation. Yet the generation capacity, availability, and intermittency of these renewable energy sources are strongly climate dependent – and may also shift due to unavoidable human-induced change. In this study, we present a method, based on previous studies, that estimates the risk of climate-change on wind and solar resource potential. The assessment combines the risk-based climate projections from the Integrated Global Systems Model (IGSM), which considers emissions and global climate sensitivity uncertainty, with more regionally detailed climate information from 8 GCMs available from the Coupled Model Intercomparison Project phase 3 (CMIP-3). Southern Africa, specifically those in the Southern African Development Countries (SADC), is used as a case study. We find a median change close to zero by 2050 in the long-term mean of both wind speed and Global Horizontal Irradiance (GHI), both used as indicators of changes in electricity production potential. Although the extreme possibilities range from about −15% to +15% change, these are associated with low probability. The most prominent effect of a modest climate mitigation policy is seen in the doubled likelihood of the mode of the distribution of wind power change. This increased likelihood is made at the expense of decreased likelihood in the large changes of the distribution, but these trade-offs with the more extreme likelihoods are not symmetric with respect to the modal change.

The Impact of Climate Policy on Carbon Capture and Storage Deployment in China

Carbon capture and storage (CCS) from coal combustion is widely viewed as an important approach for China’s carbon dioxide (CO₂) emission mitigation, but the pace of its development is still fairly slow. In addition to the technological and economic uncertainties of CCS, lack of strong policy incentive is another main reason for the wide gap between early expectations and the actual progress towards its demonstration and commercialization. China’s mitigation scenario and targets are crucial to long-term development of CCS. In this research, impacts of CCS on energy and CO₂ emissions are evaluated under two mitigation scenarios reflecting different policy effort levels for China using the China-in-Global Energy Model (C-GEM). Results indicate that with CCS applications in the power sector China can achieve an added emissions reduction of 0.3 to 0.6 Gigatons CO₂ (GtCO₂) in 2050 at the same level of carbon taxes respectively in the two mitigation scenarios. Under the more ambitious mitigation scenario, approximately 56% of China’s fossil fuel fired power plants will have CCS installed, and CO₂ emission amounting to 1.4 GtCO₂ will be captured in 2050. A carbon price not lower than $35/tCO₂ appears to be necessary for the large-scale application of CCS in the power sector, indicating the vital role of policy in the deployment of CCS in China’s power sector.

The Influence of Gas-to-Liquids and Natural Gas Production Technology Penetration on the Crude Oil-Natural Gas Price Relationship

The paper examines conditions under which gas-to-liquids (GTL) technology penetration shifts the crude oil-natural gas price ratio. Technologies that enable direct substitution across fuels, as GTL does, may constrain the price ratio within certain bounds. We analyze the forecasted evolution of the crude oil-natural gas price ratio over the next several decades under alternative assumptions about the availability and cost of GTL and its natural gas feedstock. We do this using a computable general equilibrium model of the global economy with a focus on the refinery sector in the U.S. Absent GTL, a base case forecast of global economic growth over the next few decades produces dramatic increases in the oil-natural gas price ratio. This is because there is a more limited supply of low-cost crude oil resources than natural gas resources. The availability of GTL at conventional forecasts of cost and efficiency does not materially change the picture because it is too expensive to enhance direct competition between the two as fuels in the transportation sector. GTL only modulates the increasing oil-gas price ratio if both (i) natural gas is much cheaper to produce, and (ii) GTL is less costly and more efficient than conventional forecasts.

The Value of Electricity Storage under Large-Scale Penetration of Renewable Energy: a Hybrid Modeling Approach

Due to the physics of electricity, and the current high costs of storage technologies, electricity generation and demand need to be instantaneously balanced at all times. The large-scale deployment of intermittent renewables requires increased operational flexibility to accommodate fluctuating and unpredictable power supply while maintaining this balance. This dissertation investigates the value of electricity storage for the economy. Specifically, what is the value of storage under large-scale penetration of renewable energy in the context of climate policy? To answer this question, I develop a new hybrid modeling approach that couples an electricity sector model to the MIT EPPA model, a general equilibrium model for climate change policy analysis. The electricity sector model includes the main constraints for reliable and secure operation; electricity demand; wind, solar and hydro resources on the hourly time-scale; and utility-scale storage technologies. The hybrid modeling approach reconciles the very short-term dynamics required for renewables and storage technologies assessment, and the long-term time-scale required for the analysis of economic and environmental outcomes under climate policy.

Using Mexico as a case study, this dissertation analyses policies currently under discussion in the country. The experimental design explores increasing shares of renewables with varying levels of storage capacity. Under scenarios with increasing shares of renewables in the power grid, the value of storage increases sharply. By 2050, with 50% renewables penetration, the present value of storage capacity per MW installed in Mexico is estimated at $1500/MW and $200/MWh. Energy management services resulted in the highest value component (58%), followed by operational reserves provision (22%) and capacity payments (18%). Storage capacity in the system changes both investments and operational decisions, allowing larger penetration of wind technologies and displacing gas technologies. Storage capacity in the system reduces price volatility and the occurrence of negative prices that would otherwise result as renewables scale up.

The general equilibrium analysis shows that the availability of competitive storage technologies under an economy-wide climate policy reduces the overall policy costs. Simulating a 50% emissions reduction by 2050, the model demonstrated that storage could decrease total welfare losses by 0.7% when compared to the case without storage. Despite the sharp increase in the value of storage driven by renewables penetration, the findings suggest that the current cost of most storage technologies will still have to drastically be reduced for them to be economical.

U.S. Air Quality and Health Benefits from Avoided Climate Change under Greenhouse Gas Mitigation

We evaluate the impact of climate change on U.S. air quality and health in 2050 and 2100 using a global modeling framework and integrated economic, climate, and air pollution projections. Three internally consistent socioeconomic scenarios are used to value health benefits of greenhouse gas mitigation policies specifically derived from slowing climate change. Our projections suggest that climate change, exclusive of changes in air pollutant emissions, can significantly impact ozone (O₃) and fine particulate matter (PM_2.5) pollution across the U.S. and increase associated health effects. Climate policy can substantially reduce these impacts, and climate-related air pollution health benefits alone can offset a significant fraction of mitigation costs. We find that in contrast to cobenefits from reductions to coemitted pollutants, the climate-induced air quality benefits of policy increase with time and are largest between 2050 and 2100. Our projections also suggest that increasing climate policy stringency beyond a certain degree may lead to diminishing returns relative to its cost. However, our results indicate that the air quality impacts of climate change are substantial and should be considered by cost-benefit climate policy analyses.

Updates to disaggregating the refined oil sector in EPPA: EPPA6-ROIL

This note describes how to disaggregate the standard version of EPPA’s refined oil (ROIL) commodity into specific refined petroleum products. EPPA’s treatment of all refined products as a single commodity implies that all refined fuels are fungible, that the ease of international trade in each fuel is equal, and that all refined fuels face the same drivers of demand. This treatment precludes examination of competition between specific refined fuels (e.g., gasoline cars vs. diesel cars), modeling the impacts of low-sulfur fuel requirements (which would prohibit usage of residual fuel oils in maritime shipping, for example), or the examination of technologies that could compete with oil refining in specific fuels (e.g., gas-to-liquids (GTL), coal-to-liquids (CTL), or even a rigorous treatment of biofuel production. The methodology described here disaggregates the refined oil product imported from Global Trade Analysis Project (GTAP) by calculating the volume and value flow shares of six refined fuel categories. Data from the International Energy Agency (IEA), the U.S. Energy Information Administration (EIA), and the International Council on Clean Transportation (ICCT) are utilized to calculate these shares.

US Major Crops' Uncertain Climate Change Risks and Greenhouse Gas Mitigation Benefits

We estimate the costs of climate change to US agriculture, and associated potential benefits of abating greenhouse gas emissions. Five major crops yield responses to climatic variation are modeled empirically, and the results combined with climate projections for a no-policy, high-warming future, as well as moderate and stringent mitigation scenarios. Unabated warming reduces yields of wheat and soybeans by 2050, and cotton by 2100, but moderate warming increases yields of all crops except wheat. Yield changes are monetized using the results of economic simulations within an integrated climate-economy modeling framework. The economic effects of uncontrolled warming on major crops are slightly positive—annual benefits < $4B. These are amplified by emission reductions, but subject to diminishing returns—by 2100 reaching $17B under moderate mitigation, but only $7B with stringent mitigation. Costs and benefits are sensitive to irreducible uncertainty about the fertilization effects of elevated atmospheric carbon dioxide, without which unabated warming incurs net costs of up to $18B, generating benefits to moderate (stringent) mitigation as large as $26B ($20B).

Using Green's Functions to initialize and adjust a global, eddying ocean biogeochemistry general circulation model

The NASA Carbon Monitoring System (CMS) Flux Project aims to attribute changes in the atmospheric accumulation of carbon dioxide to spatially resolved fluxes by utilizing the full suite of NASA data, models, and assimilation capabilities. For the oceanic part of this project, we introduce ECCO2-Darwin, a new ocean biogeochemistry general circulation model based on combining the following pre-existing components: (i) a full-depth, eddying, global-ocean configuration of the Massachusetts Institute of Technology general circulation model (MITgcm), (ii) an adjoint-method-based estimate of ocean circulation from the Estimating the Circulation and Climate of the Ocean, Phase II (ECCO2) project, (iii) the MIT ecosystem model “Darwin”, and (iv) a marine carbon chemistry model. Air–sea gas exchange coefficients and initial conditions of dissolved inorganic carbon, alkalinity, and oxygen are adjusted using a Green’s Functions approach in order to optimize modeled air–sea CO₂ fluxes. Data constraints include observations of carbon dioxide partial pressure (pCO₂) for 2009–2010, global air–sea CO₂ flux estimates, and the seasonal cycle of the Takahashi et al. (2009) Atlas. The model sensitivity experiments (or Green’s Functions) include simulations that start from different initial conditions as well as experiments that perturb air–sea gas exchange parameters and the ratio of particulate inorganic to organic carbon. The Green’s Functions approach yields a linear combination of these sensitivity experiments that minimizes model-data differences. The resulting initial conditions and gas exchange coefficients are then used to integrate the ECCO2-Darwin model forward. Despite the small number (six) of control parameters, the adjusted simulation is significantly closer to the data constraints (37% cost function reduction, i.e., reduction in the model-data difference, relative to the baseline simulation) and to independent observations (e.g., alkalinity). The adjusted air–sea gas exchange parameter differs by only 3% from the baseline value and has little impact (−0.1%) on the cost function. The particulate inorganic to organic carbon ratio was increased more than threefold and reduced the cost function by 22% relative to the baseline integration, indicating a significant influence of biology on air–sea gas exchange. The largest contribution to cost reduction (35%) comes from the adjustment of initial conditions. In addition to reducing biases relative to observations, the adjusted simulation exhibits smaller model drift than the baseline. We estimate drift by integrating the model with repeated 2009 atmospheric forcing for seven years and find a volume-weighted drift reduction of, for example, 12.5% for nitrate and 30% for oxygen in the top 300 m. Although there remain several regions with large model-data discrepancies, for example, overly strong carbon uptake in the Southern Ocean, the adjusted simulation is a first step towards a more accurate representation of the ocean carbon cycle at high spatial and temporal resolution.

Water Body Temperature Model for Assessing Climate Change Impacts on Thermal Cooling

We develop and test a physically based semi-Lagrangian water body temperature model to apply climatological data and thermal pollution from river-based power plants to historical river flow data in order to better understand climate change impacts on surface water temperature and thermal power plant withdrawal allowances. The model is built for rapid assessment and use in Integrated Assessment Models. We first test the standalone model on a 190km river reach, the Delaware River, where we have detailed flow and temperature data. An R² of 0.88 is obtained on hourly data for this initial test. Next, we integrate the standalone temperature model into a series of models—rainfall-runoff model, water demand model, water resource management model, and power plant uptake and release model—for the contiguous USA (CONUS), with about 19,000 segments total. With this system in place, we then validate the standalone water temperature model within the system for 16 river stations throughout the CONUS, where we have measured daily temperature data. The model performs reasonably well with a median R² of 0.88. A variety of climate and emissions scenarios are then applied to the model to test regions of higher vulnerability to river temperature environmental violations, making use of output from two GCMs and six emissions scenarios focusing on projections out to 2050. We find that the two GCMs project significantly different impacts to water temperature, driven largely by the resulting changes in streamflow from the two models. We also find significantly different impacts on the withdrawal allowed by thermal power plants due to environmental regulations. Potential impacts on generation are between +3% and -4% by 2050 for the unconstrained emissions case and +3.5% to -2% for the stringent GHG mitigation policy (where 1% is equivalent to 32 TWh, or about 3 billion USD/year using 2005 electricity prices). We also find that once-through cooling plants are most vulnerable to climate change impacts, with summer impacts ranging from -0.8% to -6% for the unconstrained emissions case and +2.1% to -3.7% for the stringent GHG emissions case.

MIT Global Change

JP

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