JP

Atmospheric chemical change, air pollution, and climate

Atmospheric Chemistry, Modeling and Biogeochemistry of Mercury

This chapter addresses the atmospheric chemistry and transport of mercury. It begins with an overview of the global biogeochemical budget of mercury, with particular attention to fluxes into and out of the atmosphere. It then surveys the different forms of atmospheric mercury and their distribution in the atmosphere. This includes the oxidation and reduction reactions that alter the form and properties of atmospheric mercury, and the wet and dry deposition processes that control its deposition to ecosystems. This is followed by a brief survey of atmospheric models that have been used in combination with measurements to further scientific understanding of atmospheric mercury. The chapter concludes by summarizing future challenges for atmospheric mercury research.

Atmospheric histories and growth trends of C4F10, C5F12, C6F14, C7F16 and C8F18

Atmospheric observations and trends are presented for the high molecular weight perfluorocarbons (PFCs): decafluorobutane (C4F10), dodecafluoropentane (C5F12), tetradecafluorohexane (C6F14), hexadecafluoroheptane (C7F16) and octadecafluorooctane (C8F18). Their atmospheric histories are based on measurements of 36 Northern Hemisphere and 46 Southern Hemisphere archived air samples collected between 1973 to 2011 using the Advanced Global Atmospheric Gases Experiment (AGAGE) “Medusa” preconcentration gas chromatography-mass spectrometry systems. A new calibration scale was prepared for each PFC, with estimated accuracies of 6.8% for C4F10, 7.8% for C5F12, 4.0% for C6F14, 6.6% for C7F16 and 7.9% for C8F18. Based on our observations the 2011 globally averaged dry air mole fractions of these heavy PFCs are: 0.17 parts-per-trillion (ppt, i.e., parts per 1012) for C4F10, 0.12 ppt for C5F12, 0.27 ppt for C6F14, 0.12 ppt for C7F16 and 0.09 ppt for C8F18. These atmospheric mole fractions combine to contribute to a global average radiative forcing of 0.35mWm−2, which is 6% of the total anthropogenic PFC radiative forcing (Montzka and Reimann, 2011; Oram et al., 2012). The growth rates of the heavy perfluorocarbons were largest in the late 1990s peaking at 6.2 parts per quadrillion (ppq, i.e., parts per 1015) per year (yr) for C4F10, at 5.0 ppq yr−1 for C5F12 and 16.6 ppq yr−1 for C6F14 and in the early 1990s for C7F16 at 4.7 ppq yr−1 and in the mid 1990s for C8F18 at 4.8 ppq yr−1. The 2011 globally averaged mean atmospheric growth rates of these PFCs are subsequently lower at 2.2 ppq yr−1 for C4F10, 1.4 ppq yr−1 for C5F12, 5.0 ppq yr−1 for C6F14, 3.4 ppq yr−1 for C7F16 and 0.9 ppq yr−1 for C8F18. The more recent slowdown in the growth rates suggests that emissions are declining as compared to the 1980s and 1990s.

Atmospheric modeling of high-frequency methane observations: Importance of interannually varying transport

We compare modeled and observed atmospheric methane (CH₄) between 1996 and 2001, focusing on the role of interannually varying (IAV) transport. The comparison uses observations taken at 13 high-frequency (∼hourly) in situ and 6 low-frequency (∼weekly) flask measurement sites. To simulate atmospheric methane, we use the global 3-D chemical transport model (MATCH) driven by NCEP reanalyzed winds at T62 resolution (∼1.8° × 1.8°). For the simulation, both methane surface emissions and atmospheric sink (OH destruction) are prescribed as annually repeating fields; thus, atmospheric transport is the only IAV component in the simulation. MATCH generally reproduces the amplitude and phase of the observed methane seasonal cycles. At the high-frequency sites, the model also captures much of the observed CH₄ variability due to transient synoptic events, which are sometimes related to global transport events. For example, the North Atlantic Oscillation (NAO) and El Niño are shown to influence year-to-year methane observations at Mace Head (Ireland) and Cape Matatula (Samoa), respectively. Simulations of individual flask measurements are generally more difficult to interpret at certain sites, partially due to observational undersampling in areas of high methane variability. A model-observational comparison of methane monthly means at seven coincident in situ and flask locations shows a better comparison at the in situ sites. Additional simulations conducted at coarser MATCH resolution (T42, ∼2.8° × 2.8°) showed differences from the T62 simulation at sites near strong emissions. This study highlights the importance of using consistent observed meteorology to simulate atmospheric methane, especially when comparing to high-frequency observations.

Automobile technology in a CO2-constrained world

Autonomous efficiency improvement or income elasticity of demand: Does it matter?

Observations of historical energy consumption, energy prices, and income growth in industrial economies exhibit a trend in improving energy effï¿½ciency even when prices are constant or falling. Two alternative explanations of this phenomenon are: a productivity change that uses less energy and a structural change in the economy in response to rising income. It is not possible to distinguish among these from aggregate data, and economic energy models for forecasting emissions simulate one, as an exogenous time trend, or the other, as energy demand elasticity with respect to income, or both processes for projecting energy demand into the future. In this paper, we ask whether and how it matters which process one uses for projecting energy demand and carbon emissions. We compare two versions of the MIT Emissions Prediction and Policy Analysis (EPPA) model, one using a conventional effï¿½ciency time trend approach and the other using an income elasticity approach. We demonstrate that while these two versions yield equivalent projections in the near-term, that they diverge in two important ways: long-run projections and under uncertainty in future productivity growth. We suggest that an income dependent approach may be preferable to the exogenous approach.

Autonomous Energy Efficiency Improvements: Relevance, Use and Empirical Basis for Global Warming Policy Analysis

Beyond 2020 - Strategies and Costs for Transforming the European Energy System

The Energy Modeling Forum 28 (EMF28) study systematically explores the energy system transition required to meet the European goal of reducing greenhouse gas (GHG) emissions by 80% by 2050. The 80% scenario is compared to a reference case that aims to achieve a 40% GHG reduction target. The paper investigates mitigation strategies beyond 2020 and the interplay between different decarbonization options. The models present different technology pathways for the decarbonization of Europe, but a common finding across the scenarios and models is the prominent role of energy efficiency and renewable energy sources. In particular, wind power and bioenergy increase considerably beyond current deployment levels. Up to 2030, the transformation strategies are similar across all models and for both levels of emission reduction. However, mitigation becomes more challenging after 2040. With some exceptions, our analysis agrees with the main findings of the “Energy Roadmap 2050” presented by the European Commission.

Cap-and-Trade Climate Policies with Price-Regulated Industries: How Costly are Free Allowances?

We examine the impacts of alternative cap-and-trade allowance allocation designs in a model of the U.S. economy where price-regulated electric utilities generate 30% of total CO2 emissions. Our empirical model embeds a generator-level description of electricity production—comprising all 16,891 electricity generators in the contiguous U.S.—in a multi-region multi-sector general equilibrium framework that features regulated monopolies and imperfectly competitive wholesale electricity markets. The model recognizes the considerable heterogeneity among households incorporating all 15,588 households from the Consumer and Expenditure Survey as individual agents in the model. Depending on the stringency of the policy, we find that distributing emission permits freely to regulated utilities increases welfare cost by 40- 80% relative to an auction if electricity rates do not reflect the opportunity costs of permits. Despite an implicit subsidy to electricity prices, efficiency costs are disproportionately borne by households in the lowest income deciles.

Carbon co-benefits of tighter SO2 and NOx regulations in China

Air pollution has been recognized as a significant problem in China. In its Twelfth Five Year Plan, China proposes to reduce SO2 and NOx emissions significantly, and here we investigate the cost of achieving those reductions and the implications of doing so for CO2 emissions. We extend the analysis through 2050, and either hold emissions policy targets at the level specified in the Plan, or continue to reduce them gradually. We apply a computable general equilibrium model of the Chinese economy that includes a representation of pollution abatement derived from detailed assessment of abatement technology and costs. We find that China's SO2 and NOx emissions control targets would have substantial effects on CO2 emissions leading to emissions savings far beyond those we estimate would be needed to meet its CO2 intensity targets. However, the cost of achieving and maintaining the pollution targets can be quite high given the growing economy. In fact, we find that the near term pollution targets can be met while still expanding the use of coal, but if they are, then there is a lock-in effect that makes it more costly to maintain or further reduce emissions. That is, if firms were to look ahead to tighter targets, they would make different technology choices in the near term, largely turning away from increased use of coal immediately.

MIT Global Change

JP

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