Low-income households may be disproportionately affected by ozone pollution and ozone policy. We quantify how three factors affect the relative benefits of ozone policies with household income: (1) unequal ozone reductions; (2) policy delay; and (3) economic valuation methods. We model ozone concentrations under baseline and policy conditions across the full continental U.S. to estimate the distribution of ozone-related health impacts across nine income groups. We enhance an economic model to include these impacts across household income categories, and present its first application to evaluate the benefits of ozone reductions for low income households. We find that mortality incidence rates decrease with increasing income. Modeled ozone levels yield a median of 11 deaths/100,000 people in 2005. Proposed policy reduces these rates by 13%. Ozone reductions are highest among low income households, which increases their relative welfare gains by up to 4%, and decreases them for the rich by up to 8%. The median value of reductions in 2015 is either $30 billion (in 2006 U.S. dollars) or $1 billion if reduced mortality risks are valued with willingness-to-pay or as income from increased life expectancy. Ozone reductions were relatively twice as beneficial for the lowest compared to the highest income households. The valuation approach affected benefits more than a policy delay or differential ozone reductions with income.

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 sensitivities, and representations of natural variability. By the end of the 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.

China is currently attempting to reduce greenhouse gas emissions and increase natural gas consumption as a part of broader national strategies to reduce the air pollution impacts of the nation’s energy system. To assess the scenarios of natural gas development up to 2050, we employ a global energy-economic model — the MIT Economic Projection and Policy Analysis (EPPA) model. The results show that a cap-and-trade policy will enable China to achieve its climate mitigation goals, but will also reduce natural gas consumption. An integrated policy that uses a part of the carbon revenue obtained from the cap-and-trade system to subsidize natural gas use promotes natural gas consumption, resulting in a further reduction in coal use relative to the cap-and-trade policy case. The integrated policy has a very moderate welfare cost; however, it reduces air pollution and allows China to achieve both the climate objective and the natural gas promotion objective.