Here, we analyse spatial congruence between current (operational) and under development large-scale renewable energy facilities that produce electricity (hereafter renewable energy facilities) and the established PA estate, and mapped areas of globally significant wilderness and KBAs. Our study is focused on hydropower, solar PV and onshore wind power, as they are the mature renewable energy technologies for electricity generation that dominate the renewables sector. We use an industry-standard dataset of renewable energy facilities locations. As such, we provide the first comprehensive global assessment of current and possible future overlaps between renewable energy technologies and important biodiversity conservation areas.

Strategic planning that simultaneously integrates conservation objectives with the needs of the transitioning energy sector, setting clear limits on development within important conservation areas is urgently needed

Out of 12,658 large-scale renewable energy facilities distributed globally, we found that 2,206 (17.4%) currently operate inside important conservation areas (Table 1). Of these facilities, 1,018 overlap with 634 PAs (1.5% of the total number of PAs), of which 122 are classified as strictly managed PAs (IUCN Categories I–IV), where no development activity should occur (Table 2; Figure 1). These 122 strictly managed PAs contain 169 renewable energy facilities (Table 2). We identified 42 facilities overlapping with 25 contiguous wilderness areas (2.7% of total wilderness blocks), and 1,147 facilities within 583 KBAs (3.2% of the total number of KBAs). Wind power overlaps with the largest number of important conservation areas (n = 543 PAs, KBAs and wilderness areas combined).

Our results show that renewable energy development has already encroached on many of the world's most important places for conserving biodiversity, with 2,206 facilities already operational within PAs, KBAs and wilderness areas (Figure S2). Furthermore, the number of active renewable energy facilities inside important conservation areas could increase by ~42% by 2028, suggesting conflicts will likely intensify in the near future

Despite the strong and often negative feedbacks between biodiversity conservation and renewable energy expansion, policies to promote these two objectives are almost always planned separately (Koppel, Dahmen, Helfrich, Schuster, & Bulling, 2014)

Wind power turbines negatively affect birds and bats, which collide with the turbine blades, with ramifications for species in other trophic levels too, and they also modify the natural airflow of local climates (Arnett et al., 2016; Saidur, Rahim, Islam, & Solangi, 2011; Schuster, Bulling, & Koppel, 2015; Thaker, Zambre, & Bhosale, 2018; Zhou et al., 2012)

Although crucial for mitigating climate change, renewable energy infrastructure development can negatively affect biodiversity

Both conservation action and renewable energy production can require large areas of land, with the latter requiring up to ten times more land area than fossil fuel thermal facilities to produce equivalent amounts of energy (Lee & David, 2018; Trainor, McDonald, & Fargione, 2016; UNCCD, 2018)

We identified 2,206 fully operational renewable energy facilities within the boundaries of these conservation areas, with another 922 facilities under development. Combined, these facilities span and are degrading 886 PAs, 749 KBAs and 40 distinct wilderness areas

Cite this articleCarley, S., Baldwin, E., MacLean, L.M. et al. Global Expansion of Renewable Energy Generation: An Analysis of Policy Instruments. Environ Resource Econ 68, 397–440 (2017). https://doi.org/10.1007/s10640-016-0025-3Download citationAccepted: 04 May 2016Published: 23 May 2016Issue date: October 2017

The study sample includes data on 164 countries between 1990 and 2010, the years that capture the majority of RE policy activity. The data are unbalanced; although a balanced panel is desirable, balancing the data would require us to omit a large number of countries that are missing variables in one or more years, including most of Eastern Europe and all former Soviet Union countries. All RPS and FIT policies included in this evaluation were adopted after 1990. While our initial dataset included 213 countries, 49 countries dropped out of the analysis due to missing data on key variables. 31 of these are small island nations whose basic demographics are not consistently tracked by the World Bank, such as American Samoa and the U.S. Virgin Islands; others, such as Myanmar and Timor-Leste, experienced destabilizing regime changes or civil wars during the study period. The final sample of 164 countries is representative of the world at large. Based on 2010 UN Human Development Index (HDI) ratings, the final sample comprises 35 very high HDI countries, 39 high HDI countries, 37 medium HDI countries, and 53 low HDI countries. Table 1 presents the countries included and excluded from the analysis, ranked by 2010 UN HDI category; this table demonstrates that we do not disproportionately lose countries from any specific HDI level. It also demonstrates that the resulting sample is representative of the global population. Not only is the study conducted on a sample that is as close to the entire population of countries as possible, it is a sample that sufficiently represents countries from across the full spectrum of economic conditions. This larger sample also allows us to include a greater amount of renewable energy development and instances of policy implementation than any previous study.

The results of this study provide four important insights to the literature on RE policy effects and effectiveness. First, results reveal that national level policies are a primary driver of renewable energy markets. Second, these strong policy effects persist regardless of whether RE is defined as including or excluding hydroelectricity, or when we use other approaches to operationalize RE markets. Third, the factors that drive RE development differ somewhat from those that increase national reliance on RE as a percentage of total energy generation. This means that simply increasing RE generation does not necessarily decrease reliance on fossil fuels nor help countries make the transition to a clean energy economy. Finally, it remains inconclusive whether FIT policies produce anticipatory market effects in the years immediately before policy adoption or whether the FIT policy variable suffers from endogeneity and thus compromises estimates of policy effects.

Published: 23 May 2016 Volume 68, pages 397–440, (2017)

Besides the prominent role of these policies, results reveal that factors related to annual increases in renewable energy differ from those related to an overall transition toward greater reliance on renewable energy. This suggests that simply increasing renewable generation does not necessarily decrease reliance on fossil fuels or help countries make the shift to a clean energy economy.

This study analyzes the degree to which renewable energy policies, in particular feed-in tariffs and renewable portfolio standards, facilitate renewable energy generation growth across a wide range of countries using an original cross-national dataset of 164 countries between 1990 and 2010