Climate Policy

Improving air quality across mainland China is an urgent policy challenge. While much of the problem is linked to China’s broader reliance on coal and other fossil fuels across the energy system, road transportation is an important and growing source of air pollution. Here we use an energy-economic model, embedded in the broader Regional Emissions Air Quality Climate and Health (REACH) modeling framework, to analyze the impacts of implementing vehicle emissions together with a broader economy-wide climate policy on total air pollution and its spatial distribution. We find that full and immediate implementation of existing vehicle emissions standards at China 3/III level or tighter will significantly reduce the contribution of transportation to degraded air quality by 2030. We further show that transportation emissions standards function as an important complement to an economy-wide price on CO2, which delivers significant co-benefits for air pollution reduction that are concentrated primarily in non-transportation sectors. Going forward, vehicle emissions standards and an economy-wide carbon price form a highly effective coordinated policy package that supports China’s air quality and climate change mitigation goals.

Scientific challenges exist on how to extract information from the wide range of projected impacts simulated by crop models driven by climate ensembles. A stronger focus is required to understand and identify the mechanisms and drivers of projected changes in crop yield. In this study, we investigate the robustness of future projections of five metrics relevant to agriculture stakeholders (accumulated frost days, dry days, growing season length, plant heat stress and start of field operations). We use a large ensemble of climate simulations by the MIT IGSM-CAM integrated assessment model that accounts for the uncertainty associated with different emissions scenarios, climate sensitivity, and natural variability. By end of century, the US is projected to experience fewer frosts, a longer growing season, more heat stress and an earlier start of field operations—although the magnitude and even the sign of these changes vary greatly by regions. Projected changes in dry days are shown not to be robust. We highlight the important role of natural variability, in particular for changes in dry days (a precipitation-related index) and heat stress (a threshold index). The wide range of our projections compares well the CMIP5 multi-model ensemble, especially for temperature-related indices. This suggests that using a single climate model that accounts for key sources of uncertainty can provide an efficient and complementary framework to the more common approach of multi-model ensembles. We also show that greenhouse gas mitigation has the potential to significantly reduce adverse effects (heat stress, risks of pest and disease) of climate change on agriculture, while also curtailing potentially beneficial impacts (earlier planting, possibility for multiple cropping). A major benefit of climate mitigation is potentially preventing changes in several indices to emerge from the noise of natural variability, even by 2100. This has major implications considering that any significant climate change impacts on crop yield would result in nation-wide changes in the agriculture sector. Finally, we argue that the analysis of agro-climate indices should more often complement crop model projections, as they can provide valuable information to better understand the drivers of changes in crop yield and production and thus better inform adaptation decisions.

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%.

© 2015 the authors

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.

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 (PM2.5) 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.

© 2015 American Chemical Society

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).

Nearly 40% of greenhouse gas (GHG) emissions in Latin America were from agriculture, forestry, and other land use (AFOLU) in 2008, more than double the global fraction of AFOLU emissions. In this article, we investigate the future trajectory of AFOLU GHG emissions in Latin America, with and without efforts to mitigate, using a multi-model comparison approach. We find significant uncertainty in future emissions with and without climate policy. This uncertainty is due to differences in a variety of assumptions including (1) the role of bioenergy, (2) where and how bioenergy is produced, (3) the availability of afforestation options in climate mitigation policy, and (4) N2O and CH4 emission intensity. With climate policy, these differences in assumptions can lead to significant variance in mitigation potential, with three models indicating reductions in AFOLU GHG emissions and one model indicating modest increases in AFOLU GHG emissions.

To mitigate climate change, governments ranging from city to multi-national have adopted greenhouse gas (GHG) emissions reduction targets. While the location of GHG reductions does not affect their climate benefits, it can impact human health benefits associated with co-emitted pollutants. Here, an advanced modeling framework is used to explore how subnational level GHG targets influence air pollutant co-benefits from ground level ozone and fine particulate matter. Two carbon policy scenarios are analyzed, each reducing the same total amount of GHG emissions in the Northeast US: an economy-wide Cap and Trade (CAT) program reducing emissions from all sectors of the economy, and a Clean Energy Standard (CES) reducing emissions from the electricity sector only. Results suggest that a regional CES policy will cost about 10 times more than a CAT policy. Despite having the same regional targets in the Northeast, carbon leakage to non-capped regions varies between policies. Consequently, a regional CAT policy will result in national carbon reductions that are over six times greater than the carbon reduced by the CES in 2030. Monetized regional human health benefits of the CAT and CES policies are 844% and 185% of the costs of each policy, respectively. Benefits for both policies are thus estimated to exceed their costs in the Northeast US. The estimated value of human health co-benefits associated with air pollution reductions for the CES scenario is two times that of the CAT scenario.

Policies that reduce greenhouse gas emissions can also reduce outdoor levels of air pollutants that harm human health by targeting the same emissions sources. However, the design and scale of these policies can affect the distribution and size of air quality impacts, i.e. who gains from pollution reductions and by how much. Traditional air quality impact analysis seeks to address these questions by estimating pollution changes with regional chemical transport models, then applying economic valuations directly to estimates of reduced health risks. In this dissertation, I incorporate and build on this approach by representing the effect of pollution reductions across regions and income groups within a model of the energy system and economy. This new modeling framework represents how climate change and clean energy policy affect pollutant emissions throughout the economy, and how these emissions then affect human health and economic welfare. This methodology allows this thesis to explore the effect of policy design on the distribution of air quality impacts across regions and income groups in three studies. The first study compares air pollutant emissions under state-level carbon emission limits with regional or national implementation, as proposed in the U.S. EPA Clean Power Plan. It finds that the flexible regional and national implementations lower the costs of compliance more than they adversely affect pollutant emissions. The second study compares the costs and air quality co-benefits of two types of national carbon policy: an energy sector policy, and an economy-wide cap-and-trade program. It finds that air quality impacts can completely offset the costs of a cost-effective carbon policy, primarily through gains in the eastern United States. The final study extends the modeling framework to be able to examine the impacts of ozone policy with household income. It finds that inequality in exposure makes ozone reductions relatively more valuable for low income households. As a whole, this work contributes to literature connecting actions to impacts, and identifies an ongoing need to improve our understanding of the connection between economic activity, policy actions, and pollutant emissions.

The primary approach to address climate change in China has been the use of CO2 intensity targets coupled with targets for low carbon energy deployment. We evaluate the impact of extending similar targets through 2050 on China's energy use profile and CO2 emissions trajectory using the China-in-Global Energy Model (C-GEM). The C-GEM is a global computable equilibrium model that includes energy and economic data provided by China's statistical agencies, calibration of savings, labor productivity, and capital productivity dynamics specific to China's stage of development, and regional aggregation that resolves China's major trading partners. We analyze the combined impact of extending CO2 intensity targets, implemented via a cap-and-trade program, and low carbon energy policies (directives for nuclear power expansion and feed-in tariffs for wind, solar, and biomass energy) through 2050. Although with the policy, simulated CO2 emissions are around 43% lower in 2050 relative to a reference (No Policy) counterfactual, China's CO2 emissions still increase by over 60% between 2010 and 2050. Curbing the rise in China's CO2 emissions will require fully implementing a CO2 price, which will need to rise to levels higher than $25/ton in order to achieve China's stated goal of peaking CO2 emissions by 2030.

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