Projecting the Impact of Socioeconomic and Policy Factors on Greenhouse Gas Emissions and Carbon Sequestration in U.S. Forestry and Agriculture.

Understanding greenhouse gas mitigation potential of the U.S. agriculture and forest sectors is critical for evaluating potential pathways to limit global average temperatures from rising more than 2° C. Using the FASOMGHG model, parameterized to reflect varying conditions across shared socioeconomic pathways, we project the greenhouse gas mitigation potential from U.S. agriculture and forestry across a range of carbon price scenarios. Under a moderate price scenario ($20 per ton CO2 with a 3% annual growth rate), cumulative mitigation potential over 2015-2055 varies substantially across SSPs, from 8.3 to 17.7 GtCO2e. Carbon sequestration in forests contributes the majority, 64-71%, of total mitigation across both sectors. We show that under a high income and population growth scenario over 60% of the total projected increase in forest carbon is driven by growth in demand for forest products, while mitigation incentives result in the remainder. This research sheds light on the interactions between alternative socioeconomic narratives and mitigation policy incentives which can help prioritize outreach, investment, and targeted policies for reducing emissions from and storing more carbon in these land use systems.

Importance of Cross-Sector Interactions When Projecting Forest Carbon across Alternative Socioeconomic Futures.

In recent decades, the carbon sink provided by the U.S. forest sector has offset a sizable portion of domestic greenhouse gas (GHG) emissions. In the future, the magnitude of this sink has important implications not only for projected U.S. net GHG emissions under a reference case but also for the cost of achieving a given mitigation target. The larger the contribution of the forest sector towards reducing net GHG emissions, the less mitigation is needed from other sectors. Conversely, if the forest sector begins to contribute a smaller sink, or even becomes a net source, mitigation requirements from other sectors may need to become more stringent and costlier to achieve economy wide emissions targets. There is acknowledged uncertainty in estimates of the carbon sink provided by the U.S. forest sector, attributable to large ranges in the projections of, among other things, future economic conditions, population growth, policy implementation, and technological advancement. We examined these drivers in the context of an economic model of the agricultural and forestry sectors, to demonstrate the importance of cross-sector interactions on projections of emissions and carbon sequestration. Using this model, we compared detailed scenarios that differ in their assumptions of demand for agriculture and forestry products, trade, rates of (sub)urbanization, and limits on timber harvest on protected lands. We found that a scenario assuming higher demand and more trade for forest products resulted in increased forest growth and larger net GHG sequestration, while a scenario featuring higher agricultural demand, ceteris paribus led to forest land conversion and increased anthropogenic emissions. Importantly, when high demand scenarios are implemented conjunctively, agricultural sector emissions under a high income-growth world with increased livestock-product demand are fully displaced by substantial GHG sequestration from the forest sector with increased forest product demand. This finding highlights the potential limitations of single-sector modeling approaches that ignore important interaction effects between sectors.

Effects of technology assumptions on US power sector capacity, generation and emissions projections: Results from the EMF 32 Model Intercomparison Project.

This paper is one of two syntheses in this special issue of the results of the EMF 32 power sector study. This paper focuses on the effects of technology and market assumptions with projections out to 2050. A total of 15 models contributed projections based on a set of standardized scenarios. The scenarios include a range of assumptions about the price of natural gas, costs of end-use energy efficiency, retirements of nuclear power, the cost of renewable electricity, and overall electricity demand. The range of models and scenarios represent similarities and differences across a broad spectrum of analytical methods. One similarity across almost all results from all models and scenarios is that the share of electricity generation and capacity fueled by coal shrinks over time, although the rate at which coal capacity is retired depends on the price of natural gas and the amount of electricity that is demanded. Another similarity is that the models project average increases in natural gas power generating capacity in every scenario over the 2020-2050 period, but at lower average annual rates than those that prevailed during the 2000-2015 period. The projections also include higher gas capacity utilization rates in the 2035-2050 period compared to the 2020-2050 period in every scenario, except the high gas price sensitivity. Renewables capacity is also projected to increase in every scenario, although the annual new capacity varies from modest rates below the observed 2000-2015 wind and solar average to rates more than 3 times that high. Model estimates of CO2 emissions largely follow from the trends in generation. Low renewables cost and low gas prices both result in lower overall CO2 emission rates relative to the 2020-2035 and 2035-2050 reference. Both limited nuclear lifetimes and higher demand result in increased CO2 emissions.

Electric sector policy, technological change, and U.S. emissions reductions goals: Results from the EMF 32 model intercomparison project.

The Energy Modeling Forum (EMF) 32 study compares a range of coordinated scenarios to explore implications of U.S. climate policy options and technological change on the electric power sector. Harmonized policy scenarios (including mass-based emissions limits and various power-sector-only carbon tax trajectories) across 16 models provide comparative assessments of potential impacts on electric sector investment and generation outcomes, emissions reductions, and economic implications. This paper compares results across these policy alternatives, including a variety of technological and natural gas price assumptions, and summarizes robust findings and areas of disagreement across participating models. Under a wide range of policy, technology, and market assumptions, model results suggest that future coal generation will decline relative to current levels while generation from natural gas, wind, and solar will increase, though the pace and extent of these changes vary by policy scenario, technological assumptions, region, and model. Climate policies can amplify trends already under way and make them less susceptible to future market changes. The model results provide useful insights to a range of stakeholders, but future research focused on intersectoral linkages in emission reductions (e.g., the role of electrification), effects of energy storage, and better coverage of bioenergy with carbon capture and storage (BECCS) can improve insights even further.

ENERGY INTENSIVE MANUFACTURING INDUSTRIES AND GHG EMISSIONS.

This paper analyzes changes in U.S. energy-intensive, trade-exposed (EITE) manufacturing over the past decade, through the lens of previously proposed climate policy measures. The American Clean Energy and Security Act of 2009 defined measures and thresholds for EITE eligibility and proposed compensatory allowances designed to reduce negative competitive impacts to domestic industry and to prevent emissions leakage. We undertook a retrospective analysis of the 2009 eligibility criteria, using the same methods with more recent data to examine trends over the 2004-2017 period. We find that energy intensity, emissions intensity, output, and emissions have fluctuated with economic conditions, and defining measures and thresholds that remain informative is challenging. Had ACES been enacted as written and not revised, the number of sectors qualifying for rebates would have decreased from 39 to 26, after adjustment for the changes in North American Industry Classification System definitions. Emissions from the eligible sectors fell 26% across the three periods of analysis, while emissions from manufacturing as a whole fell 5%. We decompose the changes in emissions into scale and intensity measures based on a hybrid measure derived from Grossman and Krueger [(1993). Environmental impacts of a North American free trade agreement. In The US-Mexico Free Trade Agreement, PM Garber (ed.). Cambridge, MA: MIT Press] and Kaya and Yokoburi [(1997). Environment, Energy, and Economy: Strategies for Sustainability. Tokyo: United Nations University Press]. As an alternative, we perform the same analyses using the EPA's Greenhouse Gas Reporting Program data. These data, not available when ACES was written, offer annual greenhouse gas estimates for facilities that emit more than 25,000 tons CO2e annually. Finally, we draw some recommendations for future policy including (1) using measures that make price level adjustments straightforward or unnecessary, (2) keeping EITE policy focused on a small group of industries to minimize sectoral reclassification problems, (3) identifying industries prone to emissions leakage rather than just changes in output and (4) consider spatial heterogeneity of emissions and trade patterns.

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.

THE IMPACT OF CARBON TAXATION AND REVENUE RECYCLING ON U.S. INDUSTRIES.

This paper provides a detailed, cross-model analysis and discussion of the implications of carbon tax scenarios on changes in sectoral output, energy production and consumption and the competitiveness of the United States' economy. Our analysis focuses on the broad patterns apparent across models in both qualitative and quantitative terms at the sector level, with a focus on energy-intensive, trade-exposed sectors. We identify how variations in carbon tax trajectories and different options for using the revenue from the tax drive these results.

Structural change as a key component for agricultural non-CO2 mitigation efforts.

Agriculture is the single largest source of anthropogenic non-carbon dioxide (non-CO2) emissions. Reaching the climate target of the Paris Agreement will require significant emission reductions across sectors by 2030 and continued efforts thereafter. Here we show that the economic potential of non-CO2 emissions reductions from agriculture is up to four times as high as previously estimated. In fact, we find that agriculture could achieve already at a carbon price of 25 $/tCO2eq non-CO2 reductions of around 1 GtCO2eq/year by 2030 mainly through the adoption of technical and structural mitigation options. At 100 $/tCO2eq agriculture could even provide non-CO2 reductions of 2.6 GtCO2eq/year in 2050 including demand side efforts. Immediate action to favor the widespread adoption of technical options in developed countries together with productivity increases through structural changes in developing countries is needed to move agriculture on track with a 2 °C climate stabilization pathway.

Evaluating the effects of climate change on US agricultural systems: sensitivity to regional impact and trade expansion scenarios.

Agriculture is one of the sectors that is expected to be most significantly impacted by climate change. There has been considerable interest in assessing these impacts and many recent studies investigating agricultural impacts for individual countries and regions using an array of models. However, the great majority of existing studies explore impacts on a country or region of interest without explicitly accounting for impacts on the rest of the world. This approach can bias the results of impact assessments for agriculture given the importance of global trade in this sector. Due to potential impacts on relative competitiveness, international trade, global supply, and prices, the net impacts of climate change on the agricultural sector in each region depend not only on productivity impacts within that region, but on how climate change impacts agricultural productivity throughout the world. In this study, we apply a global model of agriculture and forestry to evaluate climate change impacts on US agriculture with and without accounting for climate change impacts in the rest of the world. In addition, we examine scenarios where trade is expanded to explore the implications for regional allocation of production, trade volumes, and prices. To our knowledge, this is one of the only attempts to explicitly quantify the relative importance of accounting for global climate change when conducting regional assessments of climate change impacts. The results of our analyses reveal substantial differences in estimated impacts on the US agricultural sector when accounting for global impacts vs. US-only impacts, particularly for commodities where the United States has a smaller share of global production. In addition, we find that freer trade can play an important role in helping to buffer regional productivity shocks.

Implications of Alternative Land Conversion Cost Specifications on Projected Afforestation Potential in the United States.

The Forestry and Agriculture Sector Optimization Model with Greenhouse Gases (FASOMGHG) has historically relied on regional average costs of land conversion to simulate land use change across cropland, pasture, rangeland, and forestry. This assumption limits the accuracy of the land conversion estimates by not recognizing spatial heterogeneity in land quality and conversion costs. Using data from Nielsen et al. (2014), we obtained the afforestation cost per county, then estimated nonparametric regional marginal cost functions for land converting to forestry. These afforestation costs were then incorporated into FASOMGHG. Three different assumptions for land moving into the forest sector (constant average conversion cost, static rising marginal costs, and dynamic rising marginal cost) were run in order to assess the implications of alternative land conversion cost assumptions on key outcomes, such as projected forest area and cropland use, carbon sequestration, and forest product output.