Regional Analysis

The sustainability of future water resources is of paramount importance and is affected by many factors, including population, wealth and climate. Inherent in current methods to estimate these factors in the future is the uncertainty of their prediction. In this study, we integrate a large ensemble of scenarios—internally consistent across economics, emissions, climate, and population—to develop a risk portfolio of water stress over a large portion of Asia that includes China, India, and Mainland Southeast Asia in a future with unconstrained emissions. We isolate the effects of socioeconomic growth from the effects of climate change in order to identify the primary drivers of stress on water resources. We find that water needs related to socioeconomic changes, which are currently small, are likely to increase considerably in the future, often overshadowing the effect of climate change on levels of water stress. As a result, there is a high risk of severe water stress in densely populated watersheds by 2050, compared to recent history. There is strong evidence to suggest that, in the absence of autonomous adaptation or societal response, a much larger portion of the region’s population will live in water-stressed regions in the near future. Tools and studies such as these can effectively investigate large-scale system sensitivities and can be useful in engaging and informing decision makers.

© 2016 the authors

This paper develops and applies methods to quantify and monetize projected impacts on terrestrial ecosystem carbon storage and areas burned by wildfires in the contiguous United States under scenarios with and without global greenhouse gas mitigation. The MC1 dynamic global vegetation model is used to develop physical impact projections using three climate models that project a range of future conditions. We also investigate the sensitivity of future climates to different initial conditions of the climate model. Our analysis reveals that mitigation, where global radiative forcing is stabilized at 3.7 W/m2 in 2100, would consistently reduce areas burned from 2001 to 2100 by tens of millions of hectares. Monetized, these impacts are equivalent to potentially avoiding billions of dollars (discounted) in wildfire response costs. Impacts to terrestrial ecosystem carbon storage are less uniform, but changes are on the order of billions of tons over this time period. The equivalent social value of these changes in carbon storage ranges from hundreds of billions to trillions of dollars (discounted). The magnitude of these results highlights their importance when evaluating climate policy options. However, our results also show national outcomes are driven by a few regions and results are not uniform across regions, time periods, or models. Differences in the results based on the modeling approach and across initializing conditions also raise important questions about how variability in projected climates is accounted for, especially when considering impacts where extreme or threshold conditions are important.

© 2015 the authors

We quantitatively examine the relative importance of uncertainty in emissions and physicochemical properties (including reaction rate constants) to Northern Hemisphere (NH) and Arctic polycyclic aromatic hydrocarbon (PAH) concentrations, using a computationally efficient numerical uncertainty technique applied to the global-scale chemical transport model GEOS-Chem. Using polynomial chaos (PC) methods, we propagate uncertainties in physicochemical properties and emissions for the PAHs benzo[a]pyrene, pyrene and phenanthrene to simulated spatially resolved concentration uncertainties. We find that the leading contributors to parametric uncertainty in simulated concentrations are the black carbon-air partition coefficient and oxidation rate constant for benzo[a]pyrene, and the oxidation rate constants for phenanthrene and pyrene. NH geometric average concentrations are more sensitive to uncertainty in the atmospheric lifetime than to emissions rate. We use the PC expansions and measurement data to constrain parameter uncertainty distributions to observations. This narrows a priori parameter uncertainty distributions for phenanthrene and pyrene, and leads to higher values for OH oxidation rate constants and lower values for European PHE emission rates.

© 2015 American Chemical Society

The European Union (EU) recently adopted CO2 emissions mandates for new passenger cars, requiring steady reductions to 95 gCO2/km in 2021. We use a multi-sector computable general equilibrium (CGE) model, which includes a private transportation sector with an empirically-based parameterization of the relationship between income growth and demand for vehicle miles traveled. The model also includes representation of fleet turnover, and opportunities for fuel use and emissions abatement, including representation of electric vehicles. We analyze the impact of the mandates on oil demand, CO2 emissions, and economic welfare, and compare the results to an emission trading scenario that achieves identical emissions reductions. We find that vehicle emission standards reduce CO2 emissions from transportation by about 50 MtCO2 and lower the oil expenditures by about €6 billion, but at a net added cost of €12 billion in 2020. Tightening CO2 standards further after 2021 would cost the EU economy an additional €24–63 billion in 2025, compared with an emission trading system that achieves the same economy-wide CO2 reduction. We offer a discussion of the design features for incorporating transport into the emission trading system.

Industrial energy conservation programs in China form a cornerstone of China’s energy and environmental management efforts, engaging thousands of major energy-using enterprises, and targeting hundreds of million tons of annual coal-equivalent energy savings during the Eleventh and Twelfth Five-Year Plans (2006 to 2015). An important question in China and other developing countries is to understand how compliance systems develop and perform, especially in settings where regulators have limited prior experience and resources to support evaluation and enforcement. We use detailed, newly-released compliance reports, combined with industrial census data on participating firms, to identify the drivers of compliance at the firm level. We find evidence consistent with manipulation of reported compliance data during the Eleventh Five-Year Plan (2006–2010), but not during the expanded program under the Twelfth Five-Year Plan (2011–2015). We show that the non-compliance rate increased with the expansion of the program, and publicly-reported reasons for non-compliance vary widely. We find that firms that are large, and new program entrants, as well as firms in cities with low growth exhibit higher non-compliance rates after program expansion. Our findings demonstrate that although expanding coverage increases potential energy savings, regulators must grapple with increased heterogeneity in firms’ internal energy-saving opportunities and capabilities as well as in the degree of external accountability to regulators. Introducing a market for energy saving or CO2 emissions may help to solve the problem of uneven abatement costs, but differences in the strength of accountability relationships could undermine performance.

I present work on the relationship between inorganic atmospheric aerosol impacts and their precursor emissions from the United States of America. The inorganic aerosol ions nitrate (NO ̶3), sulfate (SO2 ̶4), and ammonium (NH+4) form from emissions of nitrogen oxides (NOx), sulfur dioxide (SO2), and ammonia (NH3). Emissions of NOx and SO2 in the US have recently decreased, by 42% and 62% respectively for annual totals between 2005 and 2012, in response to economic, political, and technological developments. Under such large changes, the processes of aerosol formation may behave nonlinearly. The sensitivity of aerosol impacts to future emissions reductions – the change in a metric per unit change in emissions – can be very different from the sensitivity to past reductions. In this thesis, I use a chemical transport model to examine the sensitivities, changes in sensitivities, and the importance of nonlinear interactions for both health and climate impacts of inorganic aerosols.

The first section of this thesis focuses on surface concentrations of inorganic fine particulate matter (PM2.5), a relevant metric for human health. In winter, PM2.5 across the central US is primarily composed of ammonium nitrate, whose formation is highly dependent on thermodynamics. The recent NOx and associated total nitrate (HNO3+NO ̶3) reductions have made aerosol formation in this region limited by total nitrate availability. Future NOx emissions reductions will thus have a much larger impact than they would have in the past. In summer, SO2 ̶4 aerosols dominate PM2.5. The reduced NOx emissions lead to higher peroxide concentrations and faster aqueous SO2 oxidation, without increasing sulfate wet deposition to the same degree. With faster oxidation, a larger fraction of the emitted SO2 forms sulfate and particulate matter, increasing the sensitivity of surface aerosol concentrations to SO2 emissions even as emissions themselves have decreased. These results suggest that NOx and SO2 emissions reductions will continue to improve US air quality.

The second section of this thesis focuses on sensitivities of the direct radiative effect (DRE) of inorganic aerosols to US emissions, a key quantity for studying climate impacts. The DRE and changes in DRE in winter are largest over the ocean. The summertime DRE includes a long tongue of advected aerosols over the Atlantic as well as a broad area of large DRE over the eastern US. As with surface concentrations, sensitivity of DRE to NOx and SO2 emissions increased between 2005 and 2012, while sensitivity to NH3 emissions decreased. A simple scaling estimate of the DRE in the 2012 case from the 2005 DRE and sensitivities overestimates the magnitude of the DRE by 10.3mWm−2 in January and 21.4mWm−2 in July. These values are equivalent to underestimating the SO2 emissions reductions by 13.6% and 10.6%, respectively. These processes cause small errors for climate studies that assume scaling of aerosol radiative effects for current conditions, but greater errors could occur under future emission changes.

We describe a new 4D-Var inversion framework for nitrous oxide (N2O) based on the GEOS-Chem chemical transport model and its adjoint, and apply it in a series of observing system simulation experiments to assess how well N2O sources and sinks can be constrained by the current global observing network. The employed measurement ensemble includes approximately weekly and quasi-continuous N2O measurements (hourly averages used) from several long-term monitoring networks, N2O measurements collected from discrete air samples onboard a commercial aircraft (Civil Aircraft for the Regular Investigation of the atmosphere Based on an Instrument Container; CARIBIC), and quasi-continuous measurements from the airborne HIAPER Pole-to-Pole Observations (HIPPO) campaigns. For a 2-year inversion, we find that the surface and HIPPO observations can accurately resolve a uniform bias in emissions during the first year; CARIBIC data provide a somewhat weaker constraint. Variable emission errors are much more difficult to resolve given the long lifetime of N2O, and major parts of the world lack significant constraints on the seasonal cycle of fluxes. Current observations can largely correct a global bias in the stratospheric sink of N2O if emissions are known, but do not provide information on the temporal and spatial distribution of the sink. However, for the more realistic scenario where source and sink are both uncertain, we find that simultaneously optimizing both would require unrealistically small errors in model transport. Regardless, a bias in the magnitude of the N2O sink would not affect the a posteriori N2O emissions for the 2-year timescale used here, given realistic initial conditions, due to the timescale required for stratosphere–troposphere exchange (STE). The same does not apply to model errors in the rate of STE itself, which we show exerts a larger influence on the tropospheric burden of N2O than does the chemical loss rate over short (< 3 year) timescales. We use a stochastic estimate of the inverse Hessian for the inversion to evaluate the spatial resolution of emission constraints provided by the observations, and find that significant, spatially explicit constraints can be achieved in locations near and immediately upwind of surface measurements and the HIPPO flight tracks; however, these are mostly confined to North America, Europe, and Australia. None of the current observing networks are able to provide significant spatial information on tropical N2O emissions. There, averaging kernels (describing the sensitivity of the inversion to emissions in each grid square) are highly smeared spatially and extend even to the midlatitudes, so that tropical emissions risk being conflated with those elsewhere. For global inversions, therefore, the current lack of constraints on the tropics also places an important limit on our ability to understand extratropical emissions. Based on the error reduction statistics from the inverse Hessian, we characterize the atmospheric distribution of unconstrained N2O, and identify regions in and downwind of South America, central Africa, and Southeast Asia where new surface or profile measurements would have the most value for reducing present uncertainty in the global N2O budget.<

International environmental negotiations often involve conflicts between developed and developing countries. However, considering environmental cooperation in a North-South dichotomy obscures important variation within the Global South, particularly as emerging economies become more important politically, economically, and environmentally. This article examines change in the Southern coalition in environmental negotiations, using the recently concluded Minamata Convention on Mercury as its primary case. Focusing on India and China, we argue that three key factors explain divergence in their positions as the negotiations progressed: domestic resources and regulatory politics, development constraints, and domestic scientific and technological capacity. We conclude that the intersection between scientific and technological development and domestic policy is of increasing importance in shaping emerging economies’ engagement in international environmental negotiations. We also discuss how this divergence is affecting international environmental cooperation on other issues, including the ozone and climate negotiations.

To assess the likely impact of climate change on U.S. agriculture, researchers typically run a combination of climate and crop models that project how yields of maize, wheat and other key crops will change over time. But the suite of models commonly used in these simulations, which account for a wide range of uncertainty, produces outcomes that can range from substantial crop losses to bountiful harvests. These mixed results often leave farmers and other agricultural stakeholders perplexed as to how best to adapt to climate change.

Recognizing the substantial costs involved in addressing climate change through both mitigation and adaptation measures, the Paris Agreement stipulates that developed countries provide at least $100 billion a year in climate financing to developing countries, and support their transition to lower-carbon economies through international cooperation. One avenue for such cooperation is to link carbon markets—emissions trading systems that put a cap on carbon—in developed and developing regions.

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