Greenhouse Gas Mitigation Policies Research Articles

Climate change and the economy in Baja California: Assessment of macroeconomic impacts of the State's Climate Action Plan

Despite its developing country status, Mexico ranks 10th worldwide in total greenhouse gas (GHG) emissions. However, Mexico's vulnerability to climate change impacts is a major motivating factor behind its announced intended contributions at COP21 to cut its baseline emissions by at least 25% in 2030. We analyze the macroeconomic impacts of the Climate Action Plan (CAP) process undertaken in the Mexican border state of Baja California (BC). We adapt a state-of-the-art regional macroeconometric model to analyze the BC economy-wide impacts of 22 GHG mitigation policy options recommended in the Baja California CAP. The combined effects include an average annual increase of 1680 new jobs (or about 0.11% of the average annual employment in the baseline economic forecast) and a Gross State Product (GSP) increase of $9.85 billion pesos in NPV over the 2015–2030 planning horizon. Although the main objective of GHG mitigation is to reduce atmospheric concentrations, and hence future potential damages of these pollutants, the stimulus to the BC economy from the implementation of its CAP represents a valuable co-benefit. Moreover, it is a tangible one that will take place in the near-term, in contrast to the more long-term and more uncertain benefits associated with reducing climate change damages.

Unilateral or Reciprocal Climate Policy? Experimental Evidence from China

The traditional political economy account of global climate change governance directs our attention to fundamental collective action problems associated with global public goods provision, resulting from positive or negative externalities as well as freeriding. The governance architecture of the 1997 Kyoto Protocol uses the traditional approaches of international diplomacy for addressing such challenges: legally binding commitments based on principles of reciprocity and (fair) cost/burden sharing via formalized carbon-budgeting. Yet, the 2015 Paris Agreement has essentially abandoned this approach, as it now operates on the basis of internationally coordinated and monitored unilateralism. On the presumption that public opinion matters for government policy, we examine how citizens view this shift in climate policy from reciprocity to unilateralism, after many years of exposure to strong reciprocity rhetoric by governments and stakeholders. To that end, we fielded a survey experiment in China, the world’s largest greenhouse gas (GHG) emitter. The results show that there is, perhaps surprisingly, strong and robust public support for unilateral, non-reciprocal climate policy. To the extent China is interested in pushing ahead with ambitious and thus costly GHG reduction policies, our results suggest that China can leverage segments of public support in order to overcome domestic obstacles to GHG mitigation policies.

Assessing Space Heating Demandon a Regional Level: Evaluation of a Bottom‐Up Model in the Scope of a Case Study

SummaryThe residential sector constitutes a major energy consumer, particularly on account of its needs for space heating. Offering a high leverage potential, this sector is a suitable starting point for greenhouse gas mitigation policies. By providing predictions of the energy demand of building stocks, bottom‐up building energy models represent a first step toward deriving strategies for abatement of detrimental effects related to housing energy use.This article aims at evaluating the performance of a simplified bottom‐up housing energy model. A global sensitivity analysis was performed to study the model's structure and the impact of individual model parameters. Moreover, an extensive final energy consumption data set allowed for an in‐depth comparison of this model with primary data in the scope of a case study in a Swiss municipality.On an individual building scale, the model fails to accurately simulate the energy demand. Deviations can be attributed to a range of factors, such as variability in occupants’ behavior and problems of representativeness in the underlying statistical database. Nevertheless, such under‐ or overestimations level off on an aggregated scale. In particular, the model reproduces the overall characteristics of the residential building stock's heating demand well. It is therefore well suited as a building stock model and provides a promising basis for an extended assessment of housing energy demands. In future research work, we will apply this model to a larger region in order to study various types of settlements from a life cycle perspective and to derive targeted measures aimed at reducing environmental impacts.

How much carbon offsetting and where? Implications of efficiency, effectiveness, and ethicality considerations for public opinion formation

A fundamental policy design choice in government-led climate change mitigation is: what role should flexibility mechanisms like carbon offsetting play in reducing greenhouse gas (GHG) emissions. Since public opinion affects the policy choices of government, we investigate how arguments regarding carbon offsetting's economic efficiency, effectiveness, and ethicality, which have been key points in the public debate, impact the public's preferences. We fielded an online framing experiment in the United States (N=995) to empirically identify how arguments for and against carbon offsetting influence public preferences for the inclusion of offsetting in national GHG mitigation policy. We find that the public's support for international offsetting increases and support for reductions at their source (i.e. within firms' own operations) diminishes when considerations of economic efficiency gains are at the forefront. Support for offsetting declines when individuals are confronted with arguments concerning its effectiveness and ethicality, which suggests that future policies will require clear standards of additionality in order to address these concerns. Moreover, we find that how carbon offsetting is framed matters even amongst climate skeptics and support could potentially be enhanced via improved communication on efficiency gains.

Patterns and processes of pasture to crop conversion in Brazil: Evidence from Mato Grosso State

The rate and location of cropland expansion onto cattle pastures in Brazil could affect global food security, climate change, and economic growth. We combined mapping, statistical modeling, and qualitative methods to investigate patterns and processes of pasture to crop conversion (P2C) in Mato Grosso State (MT), Brazil, a globally important center of agricultural production. P2C land constituted 49% of cropland expansion from 2000 to 2013. For a random sample of ̃250m pixels in MT, we estimated a regression model skilled at predicting P2C land in the rest of the state as a function of cattle ranching suitability, cropping suitability, and P2C conversion costs. Surprisingly, just 1/7 of pasture agronomically suitable for cultivation had undergone P2C. Hedonic regressions revealed that agronomic characteristics of land were associated with less than 20% of the variation in cropland suitability. Instead, the majority of the variation stemmed from a combination of proximity to agricultural infrastructure, characteristics of neighboring lands, and time fixed effects. The weak relationship between agronomic characteristics of land and P2C location suggests a less certain future for P2C than projections made with agronomic models. Consequentially, complications may arise for greenhouse gas mitigation policies in Brazil predicated on widespread expansion of cropland on pasture vs. natural areas. Our follow-up qualitative research shows that because P2C has often involved land rentals or sales, poorly functioning land institutions may have constrained P2C. Locally poor land quality, omitted from agronomic P2C predictions, can either catalyze or constrain P2C by limiting returns to ranching, farming, or both. Interventions to control rates and locations of P2C should take these insights into account.

New Aspects to Greenhouse Gas Mitigation Policies for Low Carbon Cities

Methane (CH4) is an important greenhouse gas emitted by vehicles. This study provides estimates of emissions of this important and often not well characterized greenhouse gas (GHG) emission related to transportation energy use. It aims to assist urban community planners and policymakers to prioritize and choose implementation strategies for low carbon cities. The paper focuses on emissions of CH4 from vehicles. Unlike emissions of CO2, which are relatively easy to estimate, emissions of CH4 are a function of many complex aspects of combustion dynamics and depend on the type of emission control systems used. In this context, they cannot be derived easily and instead must be determined through the use of published emission factors for each combination of fuel, end-use technology, combustion conditions, and emission control systems. Emissions of CH4 play a significant role with regards to the relative CO2–equivalent GHG emissions of the use of alternative transportation fuels, in comparison with the use of conventional fuels. By analyzing a database based on literature review this study analyzes all the factors affecting the creation of CH4 emissions from different vehicle types. Statistical analysis indicated “r” values ranging from 0.10 to 0.85 for all vehicles.

Climate and Land: Tradeoffs and Opportunities

Climate and Land: Tradeoffs and Opportunities Land management for carbon sequestration offers an opportunity to avoid about 0.5°C of warming if landowners have full economic incentives to participate in a global greenhouse gas mitigation policy. In an energy-only policy aimed at about 550 ppm CO2- eq stabilization the additional 0.5°C of avoided warming brings the world close to staying below the 2°C above preindustrial target. While greater incentives for mitigation from energy and land would be needed to actually meet the 2°C target even holding temperature to 2.2°C or so would be a great improvement over the path we are on now.

Radiative forcing and climate response to projected 21st century aerosol decreases

Abstract. It is widely expected that global emissions of atmospheric aerosols and their precursors will decrease strongly throughout the remainder of the 21st century, due to emission reduction policies enacted to protect human health. For instance, global emissions of aerosols and their precursors are projected to decrease by as much as 80 % by the year 2100, according to the four Representative Concentration Pathway (RCP) scenarios. The removal of aerosols will cause unintended climate consequences, including an unmasking of global warming from long-lived greenhouse gases. We use the Geophysical Fluid Dynamics Laboratory Coupled Climate Model version 3 (GFDL CM3) to simulate future climate over the 21st century with and without the aerosol emission changes projected by each of the RCPs in order to isolate the radiative forcing and climate response resulting from the aerosol reductions. We find that the projected global radiative forcing and climate response due to aerosol decreases do not vary significantly across the four RCPs by 2100, although there is some mid-century variation, especially in cloud droplet effective radius, that closely follows the RCP emissions and energy consumption projections. Up to 1 W m−2 of radiative forcing may be unmasked globally from 2005 to 2100 due to reductions in aerosol and precursor emissions, leading to average global temperature increases up to 1 K and global precipitation rate increases up to 0.09 mm day−1. However, when using a version of CM3 with reduced present-day aerosol radiative forcing (−1.0 W m−2), the global temperature increase for RCP8.5 is about 0.5 K, with similar magnitude decreases in other climate response parameters as well. Regionally and locally, climate impacts can be much larger than the global mean, with a 2.1 K warming projected over China, Japan, and Korea due to the reduced aerosol emissions in RCP8.5, as well as nearly a 0.2 mm day−1 precipitation increase, a 7 g m−2 LWP decrease, and a 2 μm increase in cloud droplet effective radius. Future aerosol decreases could be responsible for 30–40 % of total climate warming (or 10–20 % with weaker aerosol forcing) by 2100 in East Asia, even under the high greenhouse gas emissions scenario (RCP8.5). The expected unmasking of global warming caused by aerosol reductions will require more aggressive greenhouse gas mitigation policies than anticipated in order to meet desired climate targets.

The effect of near-term policy choices on long-term greenhouse gas transformation pathways

To successfully limit climate change, today’s greenhouse gas mitigation policies should encourage reductions that will continue for decades. History suggests, however, that some policy reforms lead to societal changes that persist over the long-term while others fade without long-term effect. Current climate policy literature provides little guidance on how today’s policy choices can successfully shape long-term emission reduction paths. To address such questions, this paper introduces a new agent-based, game theoretic model designed to compare how near-term choices regarding alternative policy architectures influence long-term emission reduction trajectories. Drawing on political science literature that identifies the characteristics of policies that persist over time, this simulation for the first time integrates the co-evolution of an industry sector, its technology base, and the shifting political coalitions that influence the future stringency of the government’s emission reduction policies—all as influenced by the initial choice of policy architecture. An exploratory modeling analysis that represents deeply uncertain phenomena such as the future potential for innovation and the behavior of future governments draws policy-relevant conclusions from this model. The analysis finds that near-term choices regarding the architecture of a carbon pricing policy may affect long-term decarbonization rates significantly. In particular, such rates are higher if program revenues are returned to firms in proportion to their market share, thus, creating a political constituency for continuing the carbon pricing policy. More generally, the analysis provides a framework for considering how near-term policy choices can affect long-term emission transformation pathways within integrated assessment models.

U.S. Air Quality and Health Benefits from Avoided Climate Change under Greenhouse Gas Mitigation.

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.

An approach to computing marginal land use change carbon intensities for bioenergy in policy applications

Accurately characterizing the emissions implications of bioenergy is increasingly important to the design of regional and global greenhouse gas mitigation policies. Market-based policies, in particular, often use information about carbon intensity to adjust relative deployment incentives for different energy sources. However, the carbon intensity of bioenergy is difficult to quantify because carbon emissions can occur when land use changes to expand production of bioenergy crops rather than simply when the fuel is consumed as for fossil fuels. Using a long-term, integrated assessment model, this paper develops an approach for computing the carbon intensity of bioenergy production that isolates the marginal impact of increasing production of a specific bioenergy crop in a specific region, taking into account economic competition among land uses. We explore several factors that affect emissions intensity and explain these results in the context of previous studies that use different approaches. Among the factors explored, our results suggest that the carbon intensity of bioenergy production from land use change (LUC) differs by a factor of two depending on the region in which the bioenergy crop is grown in the United States. Assumptions about international land use policies (such as those related to forest protection) and crop yields also significantly impact carbon intensity. Finally, we develop and demonstrate a generalized method for considering the varying time profile of LUC emissions from bioenergy production, taking into account the time path of future carbon prices, the discount rate and the time horizon. When evaluated in the context of power sector applications, we found electricity from bioenergy crops to be less carbon-intensive than conventional coal-fired electricity generation and often less carbon-intensive than natural-gas fired generation.

The cost of climate change: Ecosystem services and wildland fires

Little research has focused on the economic impact associated with climate-change induced wildland fire on natural ecosystems and the goods and services they provide. We examine changes in wildland fire patterns based on the U.S. Forest Service's MC1 dynamic global vegetation model from 2013 to 2115 under two pre-defined scenarios: a reference (i.e., business-as-usual) and a greenhouse gas mitigation policy scenario. We construct a habitat equivalency model under which fuels management activities, actions commonly undertaken to reduce the frequency and/or severity of wildland fire, are used to compensate for climate change-induced losses in ecosystem services on conservation lands in the contiguous U.S. resulting from wildland fire. The benefit of the greenhouse gas mitigation policy is equal to the difference in fuels management costs between the reference and policy scenarios. Results suggest present value ecosystem service benefits of greenhouse gas mitigation on the average of $3.5 billion (2005 dollars, assuming a three percent discount rate). Our analysis highlights the importance of considering loss of ecosystem services when evaluating the impacts of alternative greenhouse gas mitigation policies.

How Economic Analysis Can Inform the Climate Change Policy Debate: The Case of Northern Ireland

SummaryThis article aims to illustrate policy issues surrounding attempts to develop greenhouse gas (GHG) mitigation policy in a small region – Northern Ireland – with a relatively large agri‐food sector of strategic economic importance. A common difficulty faced by many regions is that proposals to legislate mitigation targets may not be based on a technically and economically feasible strategy to deliver emission reductions at reasonable economic cost. We demonstrate the contribution that economic analysis can make to promote and inform discussion of the economic and environmental trade‐offs. We consider critically proposals to adopt similar GHG mitigation frameworks as other parts of the UK, in particular taking account of the interdependency of different sectors in the regional economy. A regional Computable General Equilibrium model is used to analyse the impacts of policy shocks designed to reduce GHG emissions in the absence of mitigation technology adoption. We conclude that in a small open economy, without the adoption of feasible technology, there is a risk of serious damage to agri‐food competitiveness with relatively limited economy‐wide environmental gain, leading to trade diversion and GHG emission leakages. Great care is needed in regional GHG policy design, based on robust evidence, so as not to over‐promise and to balance environmental and economic implications.

Joint effects of storm surge and sea-level rise on US Coasts: new economic estimates of impacts, adaptation, and benefits of mitigation policy

Recent literature, the US Global Change Research Program’s National Climate Assessment, and recent events, such as Hurricane Sandy, highlight the need to take better account of both storm surge and sea-level rise (SLR) in assessing coastal risks of climate change. This study combines three models—a tropical cyclone simulation model; a storm surge model; and a model for economic impact and adaptation—to estimate the joint effects of storm surge and SLR for the US coast through 2100. The model is tested using multiple SLR scenarios, including those incorporating estimates of dynamic ice-sheet melting, two global greenhouse gas (GHG) mitigation policy scenarios, and multiple general circulation model climate sensitivities. The results illustrate that a large area of coastal land and property is at risk of damage from storm surge today; that land area and economic value at risk expands over time as seas rise and as storms become more intense; that adaptation is a cost-effective response to this risk, but residual impacts remain after adaptation measures are in place; that incorporating site-specific episodic storm surge increases national damage estimates by a factor of two relative to SLR-only estimates, with greater impact on the East and Gulf coasts; and that mitigation of GHGs contributes to significant lessening of damages. For a mid-range climate-sensitivity scenario that incorporates dynamic ice sheet melting, the approach yields national estimates of the impacts of storm surge and SLR of $990 billion through 2100 (net of adaptation, cumulative undiscounted 2005$); GHG mitigation policy reduces the impacts of the mid-range climate-sensitivity estimates by $84 to $100 billion.

Overview of the special issue: a multi-model framework to achieve consistent evaluation of climate change impacts in the United States

The Climate Change Impacts and Risk Analysis (CIRA) modeling exercise is a unique contribution to the scientific literature on climate change impacts, economic damages, and risk analysis that brings together multiple, national-scale models of impacts and damages in an integrated and consistent fashion to estimate climate change impacts, damages, and the benefits of greenhouse gas (GHG) mitigation actions in the United States. The CIRA project uses three consistent socioeconomic, emissions, and climate scenarios across all models to estimate the benefits of GHG mitigation policies: a Business As Usual (BAU) and two policy scenarios with radiative forcing (RF) stabilization targets of 4.5 W/m2 and 3.7 W/m2 in 2100. CIRA was also designed to specifically examine the sensitivity of results to uncertainties around climate sensitivity and differences in model structure. The goals of CIRA project are to 1) build a multi-model framework to produce estimates of multiple risks and impacts in the U.S., 2) determine to what degree risks and damages across sectors may be lowered from a BAU to policy scenarios, 3) evaluate key sources of uncertainty along the causal chain, and 4) provide information for multiple audiences and clearly communicate the risks and damages of climate change and the potentialmore » benefits of mitigation. This paper describes the motivations, goals, and design of the CIRA modeling exercise and introduces the subsequent papers in this special issue.« less

Mathematical modeling for improved greenhouse gas balances, agro‐ecosystems, and policy development: lessons from the Australian experience

If the land sector is to make significant contributions to mitigating anthropogenic greenhouse gas (GHG) emissions in coming decades, it must do so while concurrently expanding production of food and fiber. In our view, mathematical modeling will be required to provide scientific guidance to meet this challenge. In order to be useful in GHG mitigation policy measures, models must simultaneously meet scientific, software engineering, and human capacity requirements. They can be used to understand GHG fluxes, to evaluate proposed GHG mitigation actions, and to predict and monitor the effects of specific actions; the latter applications require a change in mindset that has parallels with the shift from research modeling to decision support. We compare and contrast 6 agro‐ecosystem models (FullCAM, DayCent, DNDC, APSIM, WNMM, and AgMod), chosen because they are used in Australian agriculture and forestry. Underlying structural similarities in the representations of carbon flows though plants and soils in these models are complemented by a diverse range of emphases and approaches to the subprocesses within the agro‐ecosystem. None of these agro‐ecosystem models handles all land sector GHG fluxes, and considerable model‐based uncertainty exists for soil C fluxes and enteric methane emissions. The models also show diverse approaches to the initialisation of model simulations, software implementation, distribution, licensing, and software quality assurance; each of these will differentially affect their usefulness for policy‐driven GHG mitigation prediction and monitoring. Specific requirements imposed on the use of models by Australian mitigation policy settings are discussed, and areas for further scientific development of agro‐ecosystem models for use in GHG mitigation policy are proposed. WIREs Clim Change 2014, 5:735–752. doi: 10.1002/wcc.304This article is categorized under: Integrated Assessment of Climate Change > Applications of Integrated Assessment to Climate Change The Carbon Economy and Climate Mitigation > Policies, Instruments, Lifestyles, Behavior

Mathematical properties and constraints representation for bottom-up approaches to the evaluation of GHG mitigation policies

Bottom-up models, including MARKAL, MESSAGE and AIM, are widely used when analyzing the effect of greenhouse gas (GHG) abatement policies. These bottom-up models are mostly formulated as a linear programming (LP) optimization model to find both the minimal cost combination of abatement technologies and energy flows while satisfying demands. It is not unusual that the bottom-up modeling involves a great number of technical, industrial, socioeconomic and environmental constraints. Investigating representative constraints needed for analyzing GHG abatement policies, this study proposes how to implement these constraints in bottom-up modeling.

Climate change impacts on extreme temperature mortality in select metropolitan areas in the United States

This paper applies city-specific mortality relationships for extremely hot and cold temperatures for 33 Metropolitan Statistical Areas in the United States to develop mortality projections for historical and potential future climates. These projections, which cover roughly 100 million of 310 million U.S. residents in 2010, highlight a potential change in health risks from uncontrolled climate change and the potential benefits of a greenhouse gas (GHG) mitigation policy. Our analysis reveals that projected mortality from extremely hot and cold days combined increases significantly over the 21st century because of the overwhelming increase in extremely hot days. We also find that the evaluated GHG mitigation policy could substantially reduce this risk. These results become more pronounced when accounting for projected population changes. These results challenge arguments that there could be a mortality benefit attributable to changes in extreme temperatures from future warming. This finding of a net increase in mortality also holds in an analog city sensitivity analysis that incorporates a strong adaptation assumption. While our results do not address all sources of uncertainty, their scale and scope highlight one component of the potential health risks of unmitigated climate change impacts on extreme temperatures and draw attention to the need to continue to refine analytical tools and methods for this type of analysis.

The effect of political cycles on power investment decisions: Expectations over the repeal and reinstatement of carbon policy mechanisms in Australia

Political uncertainty over global greenhouse gas (GHG) mitigation policy is likely to defer investment in cleaner technologies. It may also incentivise short-lived, high-cost interim investments while businesses wait for the uncertainty to subside. The range of possible policy responses to the issue has created uncertainty over the future of national mitigation pathways. Given that the electricity sector, globally, is a major emitter of GHGs, this represents a systematic risk to investment in electricity generation assets. This paper uses a real options analysis framework informed by a survey of experts conducted in Australia – used as a proxy to model the degree of the uncertainty – to investigate the optimal timing for investment in the conversion of a coal plant to a combined cycle gas turbine plant using the American-style option valuation method. The effect of market and political uncertainty is studied for the Clean Energy Act 2011 in Australia. Political uncertainty is addressed bi-modally in terms of: (1) uncertainty over the repeal of the carbon pricing policy, and (2) if it is repealed, uncertainty over the reinstatement of the policy, to represent the effect of electoral cycles and the possibility of more stringent future global mitigation efforts. Results of the analysis show that although political uncertainty with respect to GHG mitigation policy may delay investment in the conversion of the coal plant, expectations over the reinstatement of the carbon pricing reduces the amount of option premium to defer the conversion decision.

Greenhouse Gas Mitigation Options in the U.S. Electric Sector: A ReEDS Analysis

We apply a U.S. electric-sector capacity-expansion and dispatch model to assess possible implications—changes in generation mix, system cost, CO2 emissions, distribution of renewable energy deployment—of a set of potential greenhouse gas mitigation policy options over a range of technology projections. The model used, ReEDS, provides unique spatial and temporal detail to ensure electric-sys-tem constraints of reliable load provision are maintained throughout the system’s transformation.