We investigate empirically how national-level CO2 emissions are affected by urbanization and environmental policy. We use statistical modeling to explore panel data on annual CO2 emissions from 80 countries for the period 1983-2005. Random- and fixed-effects models indicate that, on the global average, the urbanization-emission elasticity value is 0.95 (i.e., a 1% increase in urbanization correlates with a 0.95% increase in emissions). Several regions display a statistically significant, positive elasticity for fixed- and random-effects models: lower-income Europe, India and the Sub-Continent, Latin America, and Africa. Using two proxies for environmental policy/outcomes (ratification status for the Kyoto Protocol; the Yale Environmental Performance Index), we find that in countries with stronger environmental policy/outcomes, urbanization has a more beneficial (or, a less negative) impact on emissions. Specifically, elasticity values are -1.1 (0.21) for higher-income (lower-income) countries with strong environmental policy, versus 0.65 (1.3) for higher-income (lower-income) countries with weak environmental policies. Our finding that the urbanization-emissions elasticity may depend on the strength of a country's environmental policy, not just marginal increases in income, is in contrast to the idea of universal urban scaling laws that can ignore local context. Most global population growth in the coming decades is expected to occur in urban areas of lower-income countries, which underscores the importance of these findings.

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Despite substantial gains in the past few decades, 550 million people in sub-Saharan Africa still lack access to electricity. Rural areas present the largest electrification challenge, with access levels below 12% in most countries. Public rural electrification efforts, where undertaken, have generally effected slow and limited change. Further, to motivate the substantial investment required for traditional large-scale generation and transmission projects, strong demand for electricity services is required, and this demand is not easily demonstrated in rural African settings in which little data and substantial uncertainty exist. In this paper, we develop a predictive model for mapping induced residential demand for electricity -the hypothetical demand that would exist if access to electricity services were made available. We apply this model on a fine geographic basis to Kenya to demonstrate the applicability of the approach to informing public or private electrification efforts. Together with spatially explicit cost models for generation, transmission, and distribution, these induced demand predictions can be used to evaluate various technology options, business models, and tariff structures, or to guide public sector electrification program development.

A B S T R A C TMexico's recent energy reform (2013) has provided the foundations for increased private participation in attempts to offset or reverse the country's continued decline in fossil fuel production. This country is currently on path to becoming a net energy importer by 2020. Conversely, in 2015, and for the first time in over 20 years, the United States (US) became a net oil exporter to Mexico. One of the strategies being pursued by Mexico to prevent an impending supply-demand energy imbalance is the development of shale resources using horizontal drilling and hydraulic fracturing techniques. Hence, an evaluation of the inherent risks associated with hydraulic fracturing is crucial for Mexico's energy planning and decision-making process. This paper draws lessons from the recent 'shale boom' in the US, and it analyzes and summarizes the environmental, social, economic, and community impacts that Mexico should be aware of as its nascent shale industry develops. The analysis seeks to inform mainly Mexican policy makers, but also academics, nongovernmental organizations, and the public in general, about the main concerns regarding hydraulic fracturing activities, and the importance of regulatory enforcement and community engagement in advancing sustainability. Furthermore, using the US as a case study, we argue that development of unconventional oil and gas resources in Mexico could lead to a short-term boom rather than to a dependable and sustainable long-term energy supply. Our analysis concludes with a set of recommendations for Mexico, featuring best practices that could be used to attenuate and address some of the impacts likely to emerge from shale oil and gas development.

The global carbon emissions budget over the next decades depends critically on the choices made by fast-growing emerging economies. Few studies exist, however, that develop country-specific energy system integration insights that can inform emerging economies in this decision-making process. High spatial-and temporal-resolution power system planning is central to evaluating decarbonization scenarios, but obtaining the required data and models can be cost prohibitive, especially for researchers in low, lower-middle income economies. Here, we use Nicaragua as a case study to highlight the importance of high-resolution open access data and modeling platforms to evaluate fuelswitching strategies and their resulting cost of power under realistic technology, policy, and cost scenarios (2014)(2015)(2016)(2017)(2018)(2019)(2020)(2021)(2022)(2023)(2024)(2025)(2026)(2027)(2028)(2029)(2030). Our results suggest that Nicaragua could cost-effectively achieve a low-carbon grid (80%, based on non-large hydro renewable energy generation) by 2030 while also pursuing multiple development objectives. Regional cooperation (balancing) enables the highest wind and solar generation (18% and 3% by 2030, respectively), at the least cost (US$127 MWh −1 ). Potentially risky resources (geothermal and hydropower) raise system costs but do not significantly hinder decarbonization. Oil price sensitivity scenarios suggest renewable energy to be a more cost-effective long-term investment than fuel oil, even under the assumption of prevailing cheap oil prices. Nicaragua's options illustrate the opportunities and challenges of power system decarbonization for emerging economies, and the key role that open access data and modeling platforms can play in helping develop low-carbon transition pathways.