<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xi Liu</style></author><author><style face="normal" font="default" size="100%">Huibin Du</style></author><author><style face="normal" font="default" size="100%">Zengkai Zhang</style></author><author><style face="normal" font="default" size="100%">John C Crittenden</style></author><author><style face="normal" font="default" size="100%">Michael L Lahr</style></author><author><style face="normal" font="default" size="100%">Dabo Guan</style></author><author><style face="normal" font="default" size="100%">Zhifu Mi</style></author><author><style face="normal" font="default" size="100%">Jian Zuo</style></author><author><style face="normal" font="default" size="100%">Juan Moreno-Cruz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Can virtual water trade save water resources?</style></title><secondary-title><style face="normal" font="default" size="100%">Water Research</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.sciencedirect.com/science/article/pii/S0043135419306141</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">163</style></volume><pages><style face="normal" font="default" size="100%">114848</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gregory Casey</style></author><author><style face="normal" font="default" size="100%">Soheil Shayegh</style></author><author><style face="normal" font="default" size="100%">Juan Moreno-Cruz</style></author><author><style face="normal" font="default" size="100%">Martin Bunzl</style></author><author><style face="normal" font="default" size="100%">Oded Galor</style></author><author><style face="normal" font="default" size="100%">Ken Caldeira</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The impact of climate change on fertility</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental Research Letters</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year></dates><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">054007</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We examine the potential for climate change to impact fertility via adaptations in human behavior. We start by discussing a wide range of economic channels through which climate change might impact fertility, including sectoral reallocation, the gender wage gap, longevity, and child mortality. Then, we build a quantitative model that combines standard economic-demographic theory with existing estimates of the economic consequences of climate change. In the model, increases in global temperature affect agricultural and non-agricultural sectors differently. Near the equator, where many poor countries are located, climate change has a larger negative effect on agriculture. The resulting scarcity in agricultural goods acts as a force towards higher agricultural prices and wages, leading to a labor reallocation into this sector. Since agriculture makes less use of skilled labor, climate damage decreases the return to acquiring skills, inducing parents to invest less resources in the education of each child and to increase fertility. These patterns are reversed at higher latitudes, suggesting that climate change may exacerbate inequities by reducing fertility and increasing education in richer northern countries, while increasing fertility and reducing education in poorer tropical countries. While the model only examines the role of one mechanism, it suggests that climate change could have an impact on fertility, indicating the need for future work on this important topic.</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rong Wang</style></author><author><style face="normal" font="default" size="100%">Harry Saunders</style></author><author><style face="normal" font="default" size="100%">Juan Moreno-Cruz</style></author><author><style face="normal" font="default" size="100%">Ken Caldeira</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Induced Energy-Saving Efficiency Improvements Amplify Effectiveness of Climate Change Mitigation</style></title><secondary-title><style face="normal" font="default" size="100%">Joule</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.sciencedirect.com/science/article/pii/S254243511930368X</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Eve Tsybina</style></author><author><style face="normal" font="default" size="100%">Juan Moreno-Cruz</style></author><author><style face="normal" font="default" size="100%">Alexey Tereshin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Liberalisation lowers primary energy efficiency: Evidence from twin power systems</style></title><secondary-title><style face="normal" font="default" size="100%">Energy</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.sciencedirect.com/science/article/abs/pii/S0360544219301938?via%3Dihub</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">173</style></volume><pages><style face="normal" font="default" size="100%">423-435</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The question “What has been achieved by a reform of the power sector” remains important for governments since the beginning of&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/engineering/liberalization&quot; title=&quot;Learn more about Liberalization from ScienceDirect's AI-generated Topic Pages&quot;&gt;liberalisation&lt;/a&gt;&amp;nbsp;20 years ago. Usually it is difficult to say if liberalisation brings efficiency advantages due to the absence of a perfect counterfactual. This study uses a unique setting – two regions in Russia that have similar load, generation and transmission characteristics – to identify a causal relation between liberalisation and subsequent performance. Given that the only difference between these two regions is that one was liberalised and the other one remained a&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/engineering/natural-monopoly&quot; title=&quot;Learn more about Natural Monopoly from ScienceDirect's AI-generated Topic Pages&quot;&gt;natural monopoly&lt;/a&gt;, we can attribute any differences to changes in policy only. Moreover, our focus on the impacts in&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/engineering/infrastructure&quot; title=&quot;Learn more about Infrastructure from ScienceDirect's AI-generated Topic Pages&quot;&gt;infrastructure&lt;/a&gt;identifies changes that have not previously been explored. We find that&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/engineering/primary-energy&quot; title=&quot;Learn more about Primary Energy from ScienceDirect's AI-generated Topic Pages&quot;&gt;primary energy&lt;/a&gt;&amp;nbsp;efficiency increased in the monopoly region and decreased in the market region. There are three possible explanations for this effect. The first explanation is change in&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/engineering/unit-commitment&quot; title=&quot;Learn more about Unit Commitment from ScienceDirect's AI-generated Topic Pages&quot;&gt;unit commitment&lt;/a&gt;&amp;nbsp;in both regions resulting in different overall efficiency. The second one is deterioration of heat sector caused by decoupling of power and heat in the liberalised region. The third one is&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/engineering/investment&quot; title=&quot;Learn more about Investment from ScienceDirect's AI-generated Topic Pages&quot;&gt;investment&lt;/a&gt;&amp;nbsp;in more expensive and more efficient equipment in the monopoly region.</style></abstract><issue><style face="normal" font="default" size="100%">Apr</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jevan Cherniwchan</style></author><author><style face="normal" font="default" size="100%">Juan Moreno-Cruz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Maize and Precolonial Africa</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Development Economics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.sciencedirect.com/science/article/pii/S0304387818303195?via%3Dihub</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">136</style></volume><pages><style face="normal" font="default" size="100%">137-150</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Columbus's arrival in the New World triggered an unprecedented movement of people and crops across the Atlantic Ocean. We study a largely overlooked part of this&amp;nbsp;&lt;em&gt;Columbian Exchange&lt;/em&gt;: the effects of New World crops in Africa. Specifically, we test the hypothesis that the introduction of maize increased&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/social-sciences/population-density&quot; title=&quot;Learn more about Population Density from ScienceDirect's AI-generated Topic Pages&quot;&gt;population density&lt;/a&gt;&amp;nbsp;and slave exports in precolonial Africa. We find robust empirical support for these predictions. We also find little evidence to suggest maize increased&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/economics-econometrics-and-finance/economic-growth&quot; title=&quot;Learn more about Economic Growth from ScienceDirect's AI-generated Topic Pages&quot;&gt;economic growth&lt;/a&gt;&amp;nbsp;or reduced conflict. Our results suggest that rather than stimulating development, the introduction of maize simply increased the supply of slaves during the slave trades.</style></abstract><issue><style face="normal" font="default" size="100%">jan</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jane Flegal</style></author><author><style face="normal" font="default" size="100%">Anna-Maria Hubert</style></author><author><style face="normal" font="default" size="100%">David Morrow</style></author><author><style face="normal" font="default" size="100%">Juan Moreno-Cruz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Solar Geoengineering: Social Sciences, Legal, Ethical and Economic Frameworks</style></title><secondary-title><style face="normal" font="default" size="100%">Annual Review of Environment and Resources</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.annualreviews.org/doi/abs/10.1146/annurev-environ-102017-030032</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">44</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Daniel Heyen</style></author><author><style face="normal" font="default" size="100%">Joshua Horton</style></author><author><style face="normal" font="default" size="100%">Juan Moreno-Cruz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Strategic implications of counter-geoengineering: Clash or cooperation?</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Environmental Economics and Management</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.sciencedirect.com/science/article/pii/S0095069618305035</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">95</style></volume><pages><style face="normal" font="default" size="100%">153-177</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;em&gt;Solar geoengineering&lt;/em&gt;&amp;nbsp;has received increasing attention as an&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/economics-econometrics-and-finance/options&quot; title=&quot;Learn more about Options from ScienceDirect's AI-generated Topic Pages&quot;&gt;option&lt;/a&gt;&amp;nbsp;to temporarily stabilize global temperatures. A key concern is that heterogeneous preferences over the optimal amount of cooling combined with low deployment&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/economics-econometrics-and-finance/costs&quot; title=&quot;Learn more about Costs from ScienceDirect's AI-generated Topic Pages&quot;&gt;costs&lt;/a&gt;&amp;nbsp;may allow the country with the strongest&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/economics-econometrics-and-finance/incentives&quot; title=&quot;Learn more about Incentives from ScienceDirect's AI-generated Topic Pages&quot;&gt;incentive&lt;/a&gt;&amp;nbsp;for cooling, the so-called free-driver, to impose a substantial&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/economics-econometrics-and-finance/externalities&quot; title=&quot;Learn more about Externalities from ScienceDirect's AI-generated Topic Pages&quot;&gt;externality&lt;/a&gt;&amp;nbsp;on the rest of the world. We analyze whether the threat of&amp;nbsp;&lt;em&gt;counter-geoengineering&lt;/em&gt;&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/economics-econometrics-and-finance/technology&quot; title=&quot;Learn more about Technology from ScienceDirect's AI-generated Topic Pages&quot;&gt;technologies&lt;/a&gt;&amp;nbsp;capable of negating the climatic effects of solar geoengineering can overcome the free-driver problem and tilt the game in favour of international cooperation. Our game-theoretical model of countries with&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/economics-econometrics-and-finance/asymmetric&quot; title=&quot;Learn more about Asymmetric from ScienceDirect's AI-generated Topic Pages&quot;&gt;asymmetric&lt;/a&gt;&amp;nbsp;preferences allows for a rigorous analysis of the&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/economics-econometrics-and-finance/strategic-interaction&quot; title=&quot;Learn more about Strategic Interaction from ScienceDirect's AI-generated Topic Pages&quot;&gt;strategic interaction&lt;/a&gt;surrounding solar geoengineering and counter-geoengineering. We find that counter-geoengineering prevents the free-driver outcome, but not always with benign effects. The presence of counter-geoengineering leads to either a climate clash where countries engage in a non-cooperative escalation of opposing climate interventions (negative welfare effect), a moratorium treaty where countries commit to abstain from either type of climate intervention (indeterminate welfare effect), or&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/economics-econometrics-and-finance/cooperative&quot; title=&quot;Learn more about Cooperative from ScienceDirect's AI-generated Topic Pages&quot;&gt;cooperative&lt;/a&gt;&amp;nbsp;deployment of solar geoengineering (positive welfare effect). We show that the outcome depends crucially on the degree of asymmetry in temperature preferences between countries.</style></abstract><issue><style face="normal" font="default" size="100%">May</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Garth Heutel</style></author><author><style face="normal" font="default" size="100%">Soheil Shayegh</style></author><author><style face="normal" font="default" size="100%">Juan Moreno-Cruz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Solar Geoengineering, Uncertainty, and the Price of Carbon.</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Environmental Economics and Management</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.sciencedirect.com/science/article/pii/S0095069617307714</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">87</style></volume><pages><style face="normal" font="default" size="100%">24-41</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We consider the socially optimal use of solar geoengineering to manage climate change and its implications for carbon emissions abatement policy. We show that solar geoengineering is a substitute for emissions abatement; optimal policy includes less abatement, by up to eight percentage points, and has a lower carbon price, by up to fifteen percent, than recommended by models that ignore solar geoengineering. However, it is an imperfect substitute, since it reduces temperature without reducing atmospheric or ocean carbon concentrations. Carbon concentrations are higher but temperature is lower when allowing for solar geoengineering. Ignoring geoengineering in climate models can lead to welfare losses of up to 4 percent of GDP. Uncertainty over climate sensitivity leads to more abatement and solar geoengineering, while uncertainty over solar geoengineering damages leads to less geoengineering.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yuan Wang</style></author><author><style face="normal" font="default" size="100%">Nan Lai</style></author><author><style face="normal" font="default" size="100%">Guozhu Mao</style></author><author><style face="normal" font="default" size="100%">Jian Zuo</style></author><author><style face="normal" font="default" size="100%">John Crittenden</style></author><author><style face="normal" font="default" size="100%">Yi Jin</style></author><author><style face="normal" font="default" size="100%">Juan Moreno-Cruz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Air pollutants emission from economic sectors in China: A linkage analysis</style></title><secondary-title><style face="normal" font="default" size="100%">Ecological Indicators</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2017</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.sciencedirect.com/science/article/pii/S1470160X1730078X</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">77</style></volume><pages><style face="normal" font="default" size="100%">250-260</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We employ the Hypothetical Extraction Method (HEM) using the Input-Output (IO) table and emissions data for China in 2010 to map flows of embodied air pollutant emissions. The results showed that the Construction sector (28.21% of SO&lt;sub&gt;2&lt;/sub&gt;, 29.84% of NO&lt;sub&gt;x&lt;/sub&gt;, 34.74% of Soot, 39.62% of Dust) dominates other sectors in terms of demand embodied emissions, followed by the Machinery Manufacturing (20.63% of SO&lt;sub&gt;2&lt;/sub&gt;, 19.20% of NO&lt;sub&gt;x&lt;/sub&gt;, 18.03% of Soot, 24.05% of Dust) and Service sectors (13.86% of SO&lt;sub&gt;2&lt;/sub&gt;, 13.18% of NO&lt;sub&gt;x&lt;/sub&gt;, 12.67% of Soot, 10.09% of Dust). The Power &amp;amp; Gas (48.98%, 60.45% and 30.66% of SO&lt;sub&gt;2&lt;/sub&gt;, NO&lt;sub&gt;x&lt;/sub&gt;, Soot emissions, respectively), Nonmetal Products (26.87% of Dust) and Metal Mining, Smelting &amp;amp; Pressing (29.51% of Dust) sectors, which provide electricity, steel, and cement and so on, were significant contributors to direct air pollutant emissions. The largest inter-sector flow of SO&lt;sub&gt;2&lt;/sub&gt;&amp;nbsp;emissions was from the Power &amp;amp; Gas sector to Construction sector (2301.3&amp;nbsp;kt). Meanwhile, the largest inter-sector flow of industrial dust emissions was from Nonmetal Products to Construction sector (1560.0&amp;nbsp;kt). From the regional perspective, Hebei and Shanxi provinces were the main sources of output emissions in China, with their industrial output dominated by energy (mainly coal) and heavy industry. Based on our findings, we suggest a few strategies to control air-pollution in China: (1) designing differentiated sectoral control strategies by considering supply chain; (2) establishing a regional responsibility sharing mechanism for air pollutants emissions; and (3) using pricing mechanisms to implement internalize the emissions along the supply chain.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">M. Scott Taylor</style></author><author><style face="normal" font="default" size="100%">Juan Moreno-Cruz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">An Energy-centric Theory of Agglomeration.</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Environmental Economics and Management</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2017</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.sciencedirect.com/science/article/pii/S009506961630537X</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">84</style></volume><pages><style face="normal" font="default" size="100%">153-172</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This paper sets out a simple spatial model of energy exploitation to ask how the location and productivity of energy resources affects the distribution of economic activity across geographic space. By combining elements from energy economics and economic geography we link the productivity of energy resources to the incentives for economic activity to agglomerate. We find a novel scaling law links the productivity of energy resources to population sizes, while rivers and roads effectively magnify productivity. We show how our theory's predictions concerning a single core, aggregate to predictions over regional landscapes and city size distributions at the country level.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sjak Smulders</style></author><author><style face="normal" font="default" size="100%">Juan Moreno-Cruz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Revisiting the economics of climate change: the role of geoengineering</style></title><secondary-title><style face="normal" font="default" size="100%">Research in Economics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2017</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.sciencedirect.com/science/article/pii/S1090944316302484</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">71</style></volume><pages><style face="normal" font="default" size="100%">212-224</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Technically simple measures to directly reduce mean global temperatures could be available in the near future. We introduce “geoengineering” into a simple analytical model of climate change. We model the technical and economic characteristics of geoengineering in line with the recent literature from physical and environmental management sciences. We investigate: (i) under which circumstances geoengineering can substitute, partly or completely, for traditional abatement strategies, (ii) under which conditions and at what level geoengineering is optimally employed, and (iii) whether geoengineering can mitigate free-riding problems.</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Christopher Blackburn</style></author><author><style face="normal" font="default" size="100%">Anthony Harding</style></author><author><style face="normal" font="default" size="100%">Juan Moreno-Cruz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Toward Deep-Decarbonization: An energy-service system framework.</style></title><secondary-title><style face="normal" font="default" size="100%">Curr Sustainable Renewable Energy Rep.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2017</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://link.springer.com/article/10.1007%2Fs40518-017-0088-y</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">181-190</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;h3&gt;
	Purpose of Review
&lt;/h3&gt;

&lt;p id=&quot;Par1&quot;&gt;
	This paper reviews the historical and applied literature on energy transitions from an integrated system-level framework. We synthesize the literature using a simple energy-service system framework to highlight the main problems and possible pathways for a transition to a decarbonized energy system.
&lt;/p&gt;

&lt;h3&gt;
	Recent Findings
&lt;/h3&gt;

&lt;p id=&quot;Par2&quot;&gt;
	Recent literature suggests that the combination of demand-pull and technology-push policy instruments will be necessary to tip markets in favor of low-carbon energy alternatives. These studies illustrate that complex feedback mechanisms between the different components of an energy system, such as lock-in and push-back, complicate prescriptive policy design.
&lt;/p&gt;

&lt;h3&gt;
	Summary
&lt;/h3&gt;

&lt;p id=&quot;Par3&quot;&gt;
	The transition to a decarbonized energy system is one of the most pressing problems facing modern society. Energy systems are complex systems with many layers of feedback between social, technical, and institutional systems. Given these complexities, policy design and analysis must evolve to incorporate these feedbacks more explicitly.
&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rong Wang</style></author><author><style face="normal" font="default" size="100%">Ken Caldeira</style></author><author><style face="normal" font="default" size="100%">Juan Moreno-Cruz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Will the use of a carbon tax for revenue generation produce an incentive to continue carbon emissions?</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental Research Letters</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2017</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://iopscience.iop.org/article/10.1088/1748-9326/aa6e8a</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">12</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Integrated assessment models are commonly used to generate optimal carbon prices based on an objective function that maximizes social welfare. Such models typically project an initially low carbon price that increases with time. This framework does not reflect the incentives of decision makers who are responsible for generating tax revenue. If a rising carbon price is to result in near-zero emissions, it must ultimately result in near-zero carbon tax revenue. That means that at some point, policy makers will be asked to increase the tax rate on carbon emissions to such an extent that carbon tax revenue will fall. Therefore, there is a risk that the use of a carbon tax to generate revenue could eventually create a perverse incentive to continue carbon emissions in order to provide a continued stream of carbon tax revenue. Using the Dynamic Integrated Climate Economy (DICE) model, we provide evidence that this risk is not a concern for the immediate future but that a revenue-generating carbon tax could create this perverse incentive as time goes on. This incentive becomes perverse at about year 2085 under the default configuration of DICE, but the timing depends on a range of factors including the cost of climate damages and the cost of decarbonizing the global energy system. While our study is based on a schematic model, it highlights the importance of considering a broader spectrum of incentives in studies using more comprehensive integrated assessment models. Our study demonstrates that the use of a carbon tax for revenue generation could potentially motivate implementation of such a tax today, but this source of revenue generation risks motivating continued carbon emissions far into the future.</style></abstract><issue><style face="normal" font="default" size="100%">6</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Soheil Shayegh</style></author><author><style face="normal" font="default" size="100%">Ken Caldeira</style></author><author><style face="normal" font="default" size="100%">Juan Moreno-Cruz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Adapting to rates versus amounts of climate change: a case of adaptation to sea-level rise.</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental Research Letters</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://iopscience.iop.org/article/10.1088/1748-9326/11/10/104007</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">11</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Adaptation is the process of adjusting to climate change in order to moderate harm or exploit beneficial opportunities associated with it. Most adaptation strategies are designed to adjust to a new climate state. However, despite our best efforts to curtail greenhouse gas emissions, climate is likely to continue changing far into the future. Here, we show how considering rates of change affects the projected optimal adaptation strategy. We ground our discussion with an example of optimal investment in the face of continued sea-level rise, presenting a quantitative model that illustrates the interplay among physical and economic factors governing coastal development decisions such as rate of sea-level rise, land slope, discount rate, and depreciation rate. This model shows that the determination of optimal investment strategies depends on taking into account future rates of sea-level rise, as well as social and political constraints. This general approach also applies to the development of improved strategies to adapt to ongoing trends in temperature, precipitation, and other climate variables. Adaptation to some amount of change instead of adaptation to ongoing rates of change may produce inaccurate estimates of damages to the social systems and their ability to respond to external pressures.</style></abstract><issue><style face="normal" font="default" size="100%">10</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Garth Heutel</style></author><author><style face="normal" font="default" size="100%">Kate Ricke</style></author><author><style face="normal" font="default" size="100%">Juan Moreno-Cruz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Climate Engineering Economics</style></title><secondary-title><style face="normal" font="default" size="100%">Annual Review of Resource Economics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.annualreviews.org/doi/pdf/10.1146/annurev-resource-100815-095440</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">99-118</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This article reviews and evaluates the nascent literature on the economics of climate engineering. The literature distinguishes between two broad types of climate engineering: solar radiation management and carbon dioxide removal. We review the science and engineering characteristics of these technologies and analyze the implications of those characteristics for economic policy design. We discuss optimal policy and carbon price, interregional and intergenerational equity issues, strategic interaction in the design of international environmental agreements, and the sources of risk and uncertainty surrounding these technologies. We conclude that climate engineering technologies, similar to mitigation and adaptation, should be a fundamental part of future domestic and global climate policy design. We propose several avenues in need of additional research.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Garth Heutel</style></author><author><style face="normal" font="default" size="100%">Soheil Shayegh</style></author><author><style face="normal" font="default" size="100%">Juan Moreno-Cruz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Climate tipping points and solar geoengineering</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Economic Behavior and Organization</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.sciencedirect.com/science/article/pii/S0167268116301317</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">132</style></volume><pages><style face="normal" font="default" size="100%">19-45</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We study optimal climate policy in the presence of climate tipping points and solar geoengineering. Solar geoengineering reduces temperatures without reducing greenhouse gas emissions. Climate tipping points are irreversible and uncertain events that can alter the dynamics of the climate system. We analyze three different rules related to the availability of solar geoengineering, and we model three distinct types of tipping points. Before reaching the tipping point, the introduction of solar geoengineering reduces the amount of mitigation, lowers temperatures and increases carbon concentrations. The capacity of solar geoengineering to deal with climate damages depends on the type of tipping point. Solar geoengineering is most effective at dealing with tipping points that affect the responsiveness of temperature to carbon, and it is least effective at dealing with tipping points that cause direct economic losses.</style></abstract><issue><style face="normal" font="default" size="100%">Part B</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Marshall Burke</style></author><author><style face="normal" font="default" size="100%">M. Craxton</style></author><author><style face="normal" font="default" size="100%">CD. Kolstad</style></author><author><style face="normal" font="default" size="100%">C. Onda</style></author><author><style face="normal" font="default" size="100%">H. Allcott</style></author><author><style face="normal" font="default" size="100%">E. Baker</style></author><author><style face="normal" font="default" size="100%">L. Barrage</style></author><author><style face="normal" font="default" size="100%">R. Carson</style></author><author><style face="normal" font="default" size="100%">K. Gillingham</style></author><author><style face="normal" font="default" size="100%">J. Graff-Zivin</style></author><author><style face="normal" font="default" size="100%">M. Greenstone</style></author><author><style face="normal" font="default" size="100%">S. Hallegatte</style></author><author><style face="normal" font="default" size="100%">WM. Hanemann</style></author><author><style face="normal" font="default" size="100%">G. Heal</style></author><author><style face="normal" font="default" size="100%">S. Hsiang</style></author><author><style face="normal" font="default" size="100%">B. Jones</style></author><author><style face="normal" font="default" size="100%">DL. Kelly</style></author><author><style face="normal" font="default" size="100%">R. Kopp</style></author><author><style face="normal" font="default" size="100%">M. Kotchen</style></author><author><style face="normal" font="default" size="100%">R. Mendelsohn</style></author><author><style face="normal" font="default" size="100%">K. Meng</style></author><author><style face="normal" font="default" size="100%">G. Metcalf</style></author><author><style face="normal" font="default" size="100%">R. Pindyck</style></author><author><style face="normal" font="default" size="100%">S. Rose</style></author><author><style face="normal" font="default" size="100%">I. Rudik</style></author><author><style face="normal" font="default" size="100%">J. Stock</style></author><author><style face="normal" font="default" size="100%">RSJ. Tol</style></author><author><style face="normal" font="default" size="100%">J. Moreno-Cruz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Opportunities for advances in climate change economics</style></title><secondary-title><style face="normal" font="default" size="100%">Science</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://science.sciencemag.org/content/352/6283/292</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">352</style></volume><pages><style face="normal" font="default" size="100%">292-293</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">There have been dramatic advances in understanding the physical science of climate change, facilitated by substantial and reliable research support. The social value of these advances depends on understanding their implications for society, an arena where research support has been more modest and research progress slower. Some advances have been made in understanding and formalizing climate-economy linkages, but knowledge gaps remain [e.g., as discussed in (&lt;em&gt;1&lt;/em&gt;,&amp;nbsp;&lt;em&gt;2&lt;/em&gt;)]. We outline three areas where we believe research progress on climate economics is both sorely needed, in light of policy relevance, and possible within the next few years given appropriate funding: (i) refining the social cost of carbon (SCC), (ii) improving understanding of the consequences of particular policies, and (iii) better understanding of the economic impacts and policy choices in developing economies.</style></abstract><issue><style face="normal" font="default" size="100%">6283</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kate Ricke</style></author><author><style face="normal" font="default" size="100%">Jacob Schewe</style></author><author><style face="normal" font="default" size="100%">Anders Levermann</style></author><author><style face="normal" font="default" size="100%">Ken Caldeira</style></author><author><style face="normal" font="default" size="100%">Juan Moreno-Cruz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Policy thresholds in mitigation</style></title><secondary-title><style face="normal" font="default" size="100%">Nature Geoscience</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.nature.com/articles/ngeo2607</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">5-6</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Some climate change impacts rise fast with little warming, and then taper off. To avoid diminishing incentives to reduce emissions and inadvertently slipping into a lower-welfare world, mitigation policy needs to be ambitious early on.</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Anthony Harding</style></author><author><style face="normal" font="default" size="100%">Juan Moreno-Cruz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Solar geoengineering: from incredible to inevitable and half-way back. </style></title><secondary-title><style face="normal" font="default" size="100%">Earth's Future</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2016EF000462</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">569-577</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Solar geoengineering technologies are unique in many ways, and the economic incentives they could unleash are just as interesting. Since their introduction as a potential alternative, economists have been intrigued by the potential of these technologies to dramatically alter the way we think about climate policy. As our scientific understanding of the technologies evolve, so does the way economists think about them. In this paper, we document the evolution of economic thinking around these technologies since before Crutzen (2006) until today and provide some fruitful areas for further research.</style></abstract><issue><style face="normal" font="default" size="100%">12</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gregory Macfarlane</style></author><author><style face="normal" font="default" size="100%">Laurie Garrow</style></author><author><style face="normal" font="default" size="100%">Juan Moreno-Cruz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Does Atlanta Value MARTA? Selecting an autoregressive model to recover willingness to pay.</style></title><secondary-title><style face="normal" font="default" size="100%">Transportation Research Part A: Policy and Practice</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.sciencedirect.com/science/article/pii/S096585641500138X</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">78</style></volume><pages><style face="normal" font="default" size="100%">214-230</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Understanding homeowners’ marginal willingness-to-pay (MWTP) for proximity to public transportation infrastructure is important for planning and policy. Naïve estimates of MWTP, however, may be biased as a result of spatial dependence, spatial correlation, and/or spatially endogenous variables. In this paper we discuss a class of spatial autoregressive models that control for these spatial effects, and apply them to sample data collected for the Atlanta, Georgia housing market. We provide evidence that a general-to-specific model selection methodology that relies on the generality of the spatial Durbin model (SDM) should be preferred to the classical specific-to-general methodology that begins with an assumption of no spatial effects. We show that applying the SDM raises the estimate of MWTP for transit proximity in Atlanta but also widens its confidence interval, relative to ordinary linear regression. This finding may have implications for risk estimations in land value capture forecasts and transportation policy decisions.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Juan Moreno-Cruz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mitigation and the geoengineering threat</style></title><secondary-title><style face="normal" font="default" size="100%">Resource and Energy Economics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.sciencedirect.com/science/article/pii/S092876551500038X</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">41</style></volume><pages><style face="normal" font="default" size="100%">248-263</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Recent scientific advances have introduced the possibility of engineering the climate system to lower ambient temperatures without lowering greenhouse gas concentrations. This possibility has created an intense debate given the ethical, moral and scientific questions it raises. This paper examines the economic issues introduced when geoengineering becomes available in a standard model where strategic interaction leads to suboptimal mitigation. Geoengineering introduces the possibility of technical substitution away from mitigation, but it also affects the strategic interaction across countries: mitigation decisions directly affect geoengineering decisions. With similar countries, I find these strategic effects create greater incentives for free-riding on mitigation, but with asymmetric countries, the prospect of geoengineering can induce inefficiently high levels of mitigation.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Paul Y Kerl</style></author><author><style face="normal" font="default" size="100%">Wenxian Zhang</style></author><author><style face="normal" font="default" size="100%">Thanos Nenes</style></author><author><style face="normal" font="default" size="100%">Matthew J Realff</style></author><author><style face="normal" font="default" size="100%">Armistead G Russell</style></author><author><style face="normal" font="default" size="100%">Joel Sokol</style></author><author><style face="normal" font="default" size="100%">Valerie M. Thomas</style></author><author><style face="normal" font="default" size="100%">Juan Moreno-Cruz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A New Approach for Optimal Electricity Planning and Dispatching with Hourly Time-Scale Air Quality and Health Considerations</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the National Academy of Sciences</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.pnas.org/content/pnas/early/2015/08/12/1413143112.full.pdf</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">112</style></volume><pages><style face="normal" font="default" size="100%">10884-10889</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Integrating accurate air quality modeling with decision making is hampered by complex atmospheric physics and chemistry and its coupling with atmospheric transport. Existing approaches to model the physics and chemistry accurately lead to significant computational burdens in computing the response of atmospheric concentrations to changes in emissions profiles. By integrating a reduced form of a fully coupled atmospheric model within a unit commitment optimization model, we allow, for the first time to our knowledge, a fully dynamical approach toward electricity planning that accurately and rapidly minimizes both cost and health impacts. The reduced-form model captures the response of spatially resolved air pollutant concentrations to changes in electricity-generating plant emissions on an hourly basis with accuracy comparable to a comprehensive air quality model. The integrated model allows for the inclusion of human health impacts into cost-based decisions for power plant operation. We use the new capability in a case study of the state of Georgia over the years of 2004– 2011, and show that a shift in utilization among existing power plants during selected hourly periods could have provided a health cost savings of $175.9 million dollars for an additional electricity generation cost of $83.6 million in 2007 US dollars (USD2007). The case study illustrates how air pollutant health impacts can be cost-effectively minimized by intelligently modulating power plant operations over multihour periods, without implementing additional emissions control technologies</style></abstract><issue><style face="normal" font="default" size="100%">35</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xwewei Yu</style></author><author><style face="normal" font="default" size="100%">John Crittenden</style></author><author><style face="normal" font="default" size="100%">Juan Moreno-Cruz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Regional energy rebound effect: the impact of economy-wide and sector level energy efficiency improvement in Georgia, USA.</style></title><secondary-title><style face="normal" font="default" size="100%">Energy Policy</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.sciencedirect.com/science/article/pii/S0301421515301063</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">87</style></volume><pages><style face="normal" font="default" size="100%">250-259</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Rebound effect is defined as the lost part of&amp;nbsp;&lt;em&gt;ceteris paribus&lt;/em&gt;&amp;nbsp;energy savings from improvements on&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/earth-and-planetary-sciences/energy-efficiency&quot; title=&quot;Learn more about energy efficiency&quot;&gt;energy efficiency&lt;/a&gt;. In this paper, we investigate economy-wide energy rebound effects by developing a computable general equilibrium (CGE) model for Georgia, USA. The model adopts a highly disaggregated sector profile and highlights the substitution possibilities between different energy sources in the production structure. These two features allow us to better characterize the change in&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/earth-and-planetary-sciences/energy-use&quot; title=&quot;Learn more about energy use&quot;&gt;energy use&lt;/a&gt;&amp;nbsp;in face of an efficiency shock, and to explore in detail how a sector-level shock propagates throughout the economic structure to generate aggregate impacts. We find that with economy-wide energy efficiency improvement on the production side, economy-wide rebound is moderate. Energy price levels fall very slightly, yet sectors respond to these changing prices quite differently in terms of local production and demand. Energy efficiency improvements in particular sectors (epicenters) induce quite different economy-wide impacts. In general, we expect large rebound if the epicenter sector is an&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/earth-and-planetary-sciences/energy-production&quot; title=&quot;Learn more about energy production&quot;&gt;energy production&lt;/a&gt;&amp;nbsp;sector, a direct upstream/downstream sector of energy production sectors, a transportation sector or a sector with high production elasticity. Our analysis offers valuable insights for policy makers aiming to achieve&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/earth-and-planetary-sciences/energy-conservation&quot; title=&quot;Learn more about energy conservation&quot;&gt;energy conservation&lt;/a&gt;&amp;nbsp;through increasing energy efficiency.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kate Ricke</style></author><author><style face="normal" font="default" size="100%">David W. Keith</style></author><author><style face="normal" font="default" size="100%">Juan Moreno-Cruz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Climate Policy under Uncertainty: A Case for Solar Geoengineering</style></title><secondary-title><style face="normal" font="default" size="100%">Climate Change</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://link.springer.com/article/10.1007%2Fs10584-012-0487-4</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">121</style></volume><pages><style face="normal" font="default" size="100%">431-444</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Solar Radiation Management (SRM) has two characteristics that make it useful for managing climate risk: it is quick and it is cheap. SRM cannot, however, perfectly offset CO&lt;sub&gt;2&lt;/sub&gt;-driven climate change, and its use introduces novel climate and environmental risks. We introduce SRM in a simple economic model of climate change that is designed to explore the interaction between uncertainty in the climate’s response to CO&lt;sub&gt;2&lt;/sub&gt;&amp;nbsp;and the risks of SRM in the face of carbon-cycle inertia. The fact that SRM can be implemented quickly, reducing the effects of inertia, makes it a valuable tool to manage climate risks even if it is relatively ineffective at compensating for CO&lt;sub&gt;2&lt;/sub&gt;-driven climate change or if its costs are large compared to traditional abatement strategies. Uncertainty about SRM is high, and decision makers must decide whether or not to commit to research that might reduce this uncertainty. We find that even modest reductions in uncertainty about the side-effects of SRM can reduce the overall costs of climate change in the order of 10%.</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Timo Goeschl</style></author><author><style face="normal" font="default" size="100%">Daniel Heyen</style></author><author><style face="normal" font="default" size="100%">Juan Moreno-Cruz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The Intergenerational Transfer of Solar Radiation Management Capabilities and Atmospheric Carbon Stocks</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental and Resource Economics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://link.springer.com/article/10.1007%2Fs10640-013-9647-x</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">56</style></volume><pages><style face="normal" font="default" size="100%">85-104</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Solar radiation management (SRM) technologies are considered one of the likeliest forms of geoengineering. If developed, a future generation could deploy them to limit the damages caused by the atmospheric carbon stock inherited from the current generation, despite their negative side effects. Should the current generation develop these geoengineering capabilities for a future generation? And how would a decision to develop SRM impact on the current generation’s abatement efforts? Natural scientists, ethicists, and other scholars argue that future generations could be more sanguine about the side effects of SRM deployment than the current generation. In this paper, we add economic rigor to this important debate on the intergenerational transfer of technological capabilities and pollution stocks. We identify three conjectures that constitute potentially rational courses of action for current society, including a ban on the development of SRM. However, the same premises that underpin these conjectures also allow for a novel possibility: If the development of SRM capabilities is sufficiently cheap, the current generation may for reasons of intergenerational strategy decide not just to develop SRM technologies, but also to abate more than in the absence of SRM.</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kate Ricke</style></author><author><style face="normal" font="default" size="100%">Ken Caldeira</style></author><author><style face="normal" font="default" size="100%">Juan Moreno-Cruz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Strategic incentives for climate geoengineering coalitions to exclude broad participation</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental Research Letters</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://iopscience.iop.org/article/10.1088/1748-9326/8/1/014021/meta</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">8</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Solar geoengineering is the deliberate reduction in the absorption of incoming solar radiation by the Earth's climate system with the aim of reducing impacts of anthropogenic climate change. Climate model simulations project a diversity of regional outcomes that vary with the amount of solar geoengineering deployed. It is unlikely that a single small actor could implement and sustain global-scale geoengineering that harms much of the world without intervention from harmed world powers. However, a sufficiently powerful international coalition might be able to deploy solar geoengineering. Here, we show that regional differences in climate outcomes create strategic incentives to form coalitions that are as small as possible, while still powerful enough to deploy solar geoengineering. The characteristics of coalitions to geoengineer climate are modeled using a 'global thermostat setting game' based on climate model results. Coalition members have incentives to exclude non-members that would prevent implementation of solar geoengineering at a level that is optimal for the existing coalition. These incentives differ markedly from those that dominate international politics of greenhouse-gas emissions reduction, where the central challenge is to compel free riders to participate.</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kate Ricke</style></author><author><style face="normal" font="default" size="100%">David W. Keith</style></author><author><style face="normal" font="default" size="100%">Juan Moreno-Cruz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A simple model to account for regional inequalities in the effectiveness of solar radiation management</style></title><secondary-title><style face="normal" font="default" size="100%">Climatic Change</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://link.springer.com/article/10.1007%2Fs10584-011-0103-z</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">110</style></volume><pages><style face="normal" font="default" size="100%">649-668</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We present a simple model to account for the potential effectiveness of solar radiation management (SRM) in compensating for anthropogenic climate change. This method provides a parsimonious way to account for regional inequality in the assessment of SRM effectiveness and allows policy and decision makers to examine the linear climate response to different SRM configurations. To illustrate how the model works, we use data from an ensemble of modeling experiments conducted with a general circulation model (GCM). We find that an SRM scheme optimized to restore population-weighted temperature changes to their baseline compensates for 99% of these changes while an SRM scheme optimized for population-weighted precipitation changes compensates for 97% of these changes. Hence, while inequalities in the effectiveness of SRM are important, they may not be as severe as it is often assumed.</style></abstract><issue><style face="normal" font="default" size="100%">3-4</style></issue></record></records></xml>