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The economic complexity index, which indicates the level of knowledge and skills needed in the production of the exported goods, is a measure of economic development. Some researchers have investigated the validity of the environmental Kuznets curve (EKC) hypothesis by considering the effect of economic complexity on environmental pollution. This study, for the first time, examines the impact of economic complexity, globalization, and renewable and non-renewable energy consumption on both CO 2 emissions and ecological footprint within the framework of the EKC hypothesis in the USA. To this end, the combined cointegration test and three different estimators are utilized for the period from 1980 to 2016. The main finding of the study indicates that the inverted U-shaped EKC relationship between economic complexity and environmental pollution holds for the USA. In addition to this finding, globalization and renewable energy consumption play a dominant role in reducing environmental pollution, while non-renewable energy consumption contributing factor to environmental pressure. Overall, the outcomes indicate that increasing economic complexity helps to minimize environmental degradation after a threshold, and the US government can provide a better environment by using renewable energy sources and globalization. Graphical abstract

A key problem with solar energy is intermittency: solar generators produce only when the sun is shining, adding to social costs and requiring electricity system operators to reoptimize key decisions. We develop a method to quantify the economic value of large-scale renewable energy. We estimate the model for southeastern Arizona. Not accounting for offset carbon dioxide, we find social costs of $138.40 per megawatt hour for 20 percent solar generation, of which unforecastable intermittency accounts for $6.10 and intermittency overall for $46.00. With solar installation costs of $1.52 per watt and carbon dioxide social costs of $39.00 per ton, 20 percent solar would be welfare neutral.

While debates over the consequences of climate change are often pessimistic, historical data from the past two centuries indicate many viable opportunities for responding to potential changes. This volume takes a close look at the ways in which economies—particularly that of the United States—have adjusted to the challenges climate change poses, including institutional features that help insulate the economy from shocks, new crop varieties, irrigation, flood control, and ways of extending cultivation to new geographic areas. These innovations indicate that people and economies have considerable capacity to acclimate, especially when private gains complement public benefits. Options for adjusting to climate change abound, and with improved communication and the emergence of new information and technologies, the potential for adaptation will be even greater in the future.

Much literature on federalism and multilevel governance argues that federalist institutional arrangements promote renewable energy policies. However, the U.S. case supports a different view that federalism has ambivalent effects. Policy innovation has occurred at the state level and to some extent has led to policy adoption by other states and the federal government, but the extent is limited by the veto power of fossil fuel interests that are rooted in many state governments and in Congress, buttressed by increasing Republican Party hostility to environmental and climate policy. This argument is supported by a detailed analysis of five periods of federal and state renewable energy policy-making, from the Carter to the Trump administrations. The negative effects of federalism on national renewable energy policy in the United States, in contrast to the West European cases in this special issue, are mainly due to the interaction of its federalist institutions with party polarization and a strong domestic fossil fuel industry.

We provide a detailed estimate of the technical potential of rooftop solar photovoltaic (PV) electricity generation throughout the contiguous United States. This national estimate is based on an analysis of select US cities that combines light detection and ranging (lidar) data with a validated analytical method for determining rooftop PV suitability employing geographic information systems. We use statistical models to extend this analysis to estimate the quantity and characteristics of roofs in areas not covered by lidar data. Finally, we model PV generation for all rooftops to yield technical potential estimates. At the national level, 8.13 billion m2 of suitable roof area could host 1118 GW of PV capacity, generating 1432 TWh of electricity per year. This would equate to 38.6% of the electricity that was sold in the contiguous United States in 2013. This estimate is substantially higher than a previous estimate made by the National Renewable Energy Laboratory. The difference can be attributed to increases in PV module power density, improved estimation of building suitability, higher estimates of total number of buildings, and improvements in PV performance simulation tools that previously tended to underestimate productivity. Also notable, the nationwide percentage of buildings suitable for at least some PV deployment is high-82% for buildings smaller than 5000 ft2 and over 99% for buildings larger than that. In most states, rooftop PV could enable small, mostly residential buildings to offset the majority of average household electricity consumption. Even in some states with a relatively poor solar resource, such as those in the Northeast, the residential sector has the potential to offset around 100% of its total electricity consumption with rooftop PV.

Meeting a greenhouse gas (GHG) reduction target of 80% below 1990 levels in the year 2050 requires detailed long-term planning due to complexity, inertia, and path dependency in the energy system. A detailed investigation of supply and demand alternatives is conducted to assess requirements for future California energy systems that can meet the 2050 GHG target. Two components are developed here that build novel analytic capacity and extend previous studies: (1) detailed bottom-up projections of energy demand across the building, industry and transportation sectors; and (2) a high-resolution variable renewable resource capacity planning model (SWITCH) that minimizes the cost of electricity while meeting GHG policy goals in the 2050 timeframe. Multiple pathways exist to a low-GHG future, all involving increased efficiency, electrification, and a dramatic shift from fossil fuels to low-GHG energy. The electricity system is found to have a diverse, cost-effective set of options that meet aggressive GHG reduction targets. This conclusion holds even with increased demand from transportation and heating, but the optimal levels of wind and solar deployment depend on the temporal characteristics of the resulting load profile. Long-term policy support is found to be a key missing element for the successful attainment of the 2050 GHG target in California.

We are in an energy crisis caused by years of neglect to alternative energy sources. There are many possible solutions and a number of these are based on microorganisms. These include bioethanol, biobutanol, biodiesel, biohydrocarbons, methane, methanol, electricity-generating microbial fuel cells, and production of hydrogen via photosynthetic microbes. In this review, I will focus on the first four possibilities.

In the United States, the electricity sector is a major focus for implementing policies to meet national, state, or local mandatory or voluntary CO2 emissions reductions goals. Thus, it is important to have timely and available information on greenhouse gas emissions generated by the power sector to ensure that the policies implemented achieve intended emissions reductions. This work is the first to develop a transparent method to compute the emissions intensity for the US electricity section from 2001 through 2017 at different temporal (annual, quarterly, monthly) and regional (US, NERC, and state) levels. We find that between 2001 and 2017 the average annual CO2 emissions intensity of electricity production in the United States decreased by 30%, from 630 g CO2 kWh−1 to 439 g CO2 kWh−1. This change in CO2 intensity is attributable to an increase in generation from natural gas and wind accompanied by a reduction in coal-fired power generation. The decline in carbon intensity varies across regions, with the largest reduction between 2001 and 2017 from power plants in the Northeast (58%) and the smallest reduction from power plants in the Texas region (27%). In absolute terms the South-central region saw the largest decrease in emissions intensity (358 g CO2 kWh−1) and Texas saw the smallest (164 g CO2 kWh−1). We also find that replacing coal generation with natural gas or renewables has increased the monthly correlation of CO2 intensity between regions. At the state level, Delaware saw the largest decrease in CO2 intensity (466 g CO2 kWh−1), and Idaho is the only state that has not decreased CO2 intensity since 2001.

Recent analysis has highlighted agricultural land conversion as a significant debit in the greenhouse gas accounting of ethanol as an alternative fuel. A controversial element of this debate is the role of crop yield growth as a means of avoiding cropland conversion in the face of biofuels growth. We find that standard assumptions of yield response are unduly restrictive. Furthermore, we identify both the acreage response and bilateral trade specifications as critical considerations for predicting global land use change. Sensitivity analysis reveals that each of these contributes importantly to parametric uncertainty.