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sustainability
Article
Renewable Energy and Land Use in India: A Vision to
Facilitate Sustainable Development
Joseph Kiesecker 1, *, Sharon Baruch-Mordo 1, * , Mike Heiner 1, Dhaval Negandhi 2,
James Oakleaf 1, Christina Kennedy 1and Pareexit Chauhan 3
1Global Lands, The Nature Conservancy, 117 E. Mountain Ave, Suite 201, Fort Collins, CO 80524, USA;
mheiner@tnc.org (M.H.); joakleaf@TNC.ORG (J.O.); ckennedy@TNC.ORG (C.K.)
2India Program, The Nature Conservancy, Link Road, Lajpat Nagar Part III, New Delhi 110024, India;
dhaval.negandhi@TNC.ORG
3
Center for Study of Science, Technology and Policy, No. 18 & 19, 10th Cross, Mayura Street, Papanna Layout,
Nagashettyhalli (RMV II Stage), Bengaluru 560094, India; pareexit@cstep.in
*Correspondence: jkiesecker@tnc.org (J.K.); sbaruch-mordo@TNC.ORG (S.B.-M.)
Received: 25 November 2019; Accepted: 19 December 2019; Published: 30 December 2019
Abstract:
India has committed to reduce emissions with a goal to increase renewable energy
production to 175 gigawatts (GW) by 2022. Achieving this objective will involve rapidly increasing
the deployment of solar and wind energy, while at the same time addressing the related challenges of
the financing requirements, environment impacts, and power grid integration. Developing energy on
lands degraded by human activities rather than placing new infrastructure within natural habitats
or areas of high production agriculture would reduce cumulative impacts and minimize land use
conflicts. We estimated that converted lands have the potential capacity of 1789 GW across India,
which is >10 times the 2022 goals. At the same time, the total land footprint needed to meet India’s
2022 renewable energy target is large, ranging from ~55,000 to 125,000 km
2
, which is roughly the
size of Himachal Pradesh or Chhattisgarh, respectively. If renewable energy is advanced with the
singular aim of maximizing resource potential, approximately 6700–11,900 km
2
of forest land and
24,100–55,700 km
2
of agricultural land could be impacted. Subsidies and incentive programs aimed
at promoting low-impact renewable energy deployment and establishing mitigation obligations that
raise costs for projects that create land-impacts could improve the public support for renewable energy.
Keywords:
renewable energy; Paris climate agreement; nationally determined contributions; energy
development impacts; sustainable development; energy sprawl; wind energy; solar energy
1. Introduction
India, the world’s third largest greenhouse gas (GHG) emitter, has committed to renewable
energy as a solution to reduce emissions and to address the challenges of energy access and poverty.
The Government of India (GoI) declared its intention to increase domestic renewable energy to
175 gigawatts (GW) by 2022. Within the 2022 target, wind energy will comprise ~60 GW and
photovoltaic (PV) solar will be ~100 GW (40 GW from rooftop installations) [
1
]. In addition, India
aims to achieve 40% cumulative electric power installed capacity from renewable sources by 2030
and 100% electrification of vehicles by 2030: goals that are expected to add an additional power
requirement of 125 GW and 150 GW, respectively [
2
]. Many studies have, however, questioned the
land-based targets for solar energy deployment and have highlighted the difficulties related to grid
access and disputes over land use [
3
–
5
]. The acquisition of the land is also a major challenge for private
companies operating in the wind energy sector [
6
,
7
]. With a significant portion of India’s land already
under high human modification, and given its population is projected to increase by 20% in the next
Sustainability 2020,12, 281; doi:10.3390/su12010281 www.mdpi.com/journal/sustainability
Sustainability 2020,12, 281 2 of 14
40 years [
8
], meeting the land requirements needed to install renewable energy in line with 2022 target
can, therefore, exacerbate land conflicts in India [9,10].
In addition to commitments to expand renewable energy production, India’s Green India Mission
(GIM) acknowledges the impact of the forestry sector on climate mitigation, food and water security,
conservation of biodiversity, and livelihood of forest dependent communities [
11
]. The GIM seeks
to increase forest/tree cover and forest condition on 10 million hectares over 10 years [
11
]. Moreover,
by 2025, India’s population is also projected to surpass China’s [
8
], consequently requiring more land to
house, feed, and provide energy for this growing population [
10
]. Simultaneously meeting renewable
energy development goals, increasing forest cover, and devoting land to support a growing population
(e.g., food production) will require proactive land use planning in order to avoid dire land use conflicts.
Previous studies [
3
,
12
–
15
] have estimated the total amount of renewable energy potential available
in India, and even whether India can meet 2022 goals [
16
], but to the best of our knowledge, none
have examined the potential impacts to existing agricultural and natural lands from renewable energy
development if it is sited without the consideration of existing land use. The aim of this study was
to quantify the potential impacts to existing agricultural and natural lands from renewable energy
development if it is sited regardless of current land use (unconstrained scenario). We also assessed
if the 2022 goals can be met if the renewable energy development was constrained to lands already
converted or degraded by human activities (constrained scenario). We suggest that doing so reduces
future conflict with other human uses and would minimize the loss and degradation of natural lands
and associated biodiversity and ecosystem services. Our projections are based on the GoI’s 2022
vision for wind and solar energy development projected for each state (Figure 1, Table 1). The 2022
forecast details a spatial and temporal roadmap to achieve the wind and solar renewable energy
goals, including unique wind and solar GW targets for each state. Because some renewable energy
facilities have already been installed (~60 GW), we report results as a range between the full 2022
goals and the remaining goals (i.e., 2022 goals—2017 installed capacity; hereafter referred to as full
goals and remaining goals, respectively). Lastly, proliferation of rooftop solar has been slow in India
and solar development to date largely consists of ground-mounted solar [
15
] (Table 1). If this trend
continues it could increase the land use requirement for development. To address the potential of
rooftop solar we compared the land use change impacts when all solar renewable energy targets are
met only with ground-mounted development, and when states and territories meet their rooftop and
ground-mounted solar goals separately. By calculating the different land use change results between
the two analyses we determined the amount of natural and agricultural lands conversion that can be
avoided if rooftop and ground-mounted solar goals were met separately.
Sustainability 2020,12, 281 3 of 14
Table 1.
Solar (rooftop and ground mounted photovoltaics), wind, and total GW goals based on the 2022 vision [
1
], and installed capacities up to 2017 for each state,
union territory, and district [15].
Name
2022 Vision Targets (GW) 2017 Installed Capacity (GW)
Name
2022 Vision Targets (GW) 2017 Installed Capacity (GW)
Solar
Rooftop
Solar
Ground-Mounted Wind Solar
Rooftop
Solar
Ground-Mounted Wind Solar
Rooftop
Solar
Ground-Mounted Wind Solar
Rooftop
Solar
Ground-Mounted Wind
Andaman &
Nicobar 0.020 0.007 0.001 0.011 Lakshadweep 0.010 0.001
Andhra
Pradesh 2.000 7.834 8.100 0.022 2.143 3.835 Madhya
Pradesh 2.200 3.475 6.200 0.017 1.193 2.498
Arunachal
Pradesh 0.050 0.004 <0.001 Maharashtra 4.700 7.226 7.600 0.152 0.620 4.778
Assam 0.250 0.413 0.002 0.010 Manipur 0.050 0.055 0.001
Bihar 1.000 1.493 0.004 0.138 Meghalaya 0.050 0.111 <0.001
Chandigarh 0.100 0.053 0.014 0.005 Mizoram 0.050 0.022 <0.001
Chhattisgarh 0.700 1.083 0.013 0.166 Nagaland 0.050 0.011 0.001
Dadar &
Nagar Haveli 0.200 0.249 0.003 Odisha 1.000 1.377 0.003 0.076
Daman & Diu 0.100 0.099 <0.001 0.010 Puducherry 0.100 0.146 <0.001 <0.001
Delhi 1.100 1.662 0.067 0.003 Punjab 2.000 2.772 0.078 0.836
Goa 0.150 0.208 0.001 Rajasthan 2.300 3.462 8.600 0.053 2.259 4.282
Gujarat 3.200 4.820 8.800 0.092 1.262 5.537 Sikkim 0.050 <0.001
Haryana 1.600 2.542 0.086 0.130 Tamil Nadu 3.500 5.384 11.900 0.110 1.712 7.970
Himachal
Pradesh 0.320 0.456 0.001 Telangana 2.000 2.000 0.027 2.963 0.101
Jammu &
Kashmir 0.450 0.705 0.001 0.001 Tripura 0.050 0.055 <0.001 0.005
Jharkhand 0.800 1.195 0.007 0.017 Uttar Pradesh 4.300 6.397 0.056 0.495
Karnataka 2.300 3.397 6.200 0.085 1.717 3.793 Uttarakhand 0.350 0.550 0.018 0.231
Kerala 0.800 1.070 0.038 0.050 0.052 West Bengal 2.100 3.236 0.023 0.017
Sustainability 2020,12, 281 4 of 14
Sustainability 2019, 11, x FOR PEER REVIEW 4 of 14
Figure 1. Scenarios considered in the assessment. The aim of this study was to quantify the potential
impacts to existing agricultural and natural lands from renewable energy development if it is sited
regardless of current land use (unconstrained scenario) or constrained to lands already converted or
degraded by human activities (constrained scenario). Because some renewable energy facilities have
already been installed (~60 GW), we examined impacts as a range between the full 2022 goals and
the remaining goals (i.e., 2022 goals—2017 installed capacity. Because proliferation of rooftop solar
has been slow in India and solar development to date largely consists of ground-mounted solar, we
compared the land use change impacts when all solar renewable energy targets are met only with
ground-mounted development, and when states meet their rooftop and ground-mounted solar
goals separately as planned.
2. Methods
2.1. Renewable Energy Potential on Converted Lands
We focused our analyses on terrestrial lands and excluded water bodies and snow cover types
based on the 2011–2012 Land Use Land Cover (LULC) layer provided by India’s National Remote
Sensing Centre [17]. We also excluded areas where utility-scaled ground mounted wind and solar
energy development is less likely to occur, i.e., within urban areas (build-up cover types in LULC)
and protected areas (including all types of designation) [18,19]. All spatial analyses were conducted
in ArcMap v. 10.3 (Environmental Systems Research Institute, Redlands, CA, USA) [20] and
program R version 3.4.3 (R Foundation for Statistical Computing, Vienna, Austria) [21].
We then estimated renewable energy technical potential on suitable terrestrial lands for
utility-scale wind and photovoltaics solar (PV; also referred to as ground-mounted solar) at 1-km
resolution, following what is set out in Baruch-Mordo et al. 2019 [22]. Consistent with the feasibility
criteria for each sector’s development we excluded for wind: any cell with wind speed <5 m/s, slope
>30% and elevation >2000 m; and for PV: any cell with slope >5%. PV technologies harvest global
horizontal irradiance (GHI). Because many global or regional PV technical potential estimates do not
apply GHI thresholds [23–26], and because GHI values in India exceeded most thresholds
previously used (e.g., 1500 kWh/m2 and 1400 kWh/m2 [27,28]), we did not apply any GHI resource
threshold for PV. For each remaining ith suitable cell, we then estimated the available annual GWh
generation using: PD*CFi*8760/1000, where PD is power density or the MW produced per km2 (2
MW/km2 for wind, and 26 MW/km2 for PV), CFi is the spatially explicit capacity factor based on Wu
Figure 1.
Scenarios considered in the assessment. The aim of this study was to quantify the potential
impacts to existing agricultural and natural lands from renewable energy development if it is sited
regardless of current land use (unconstrained scenario) or constrained to lands already converted
or degraded by human activities (constrained scenario). Because some renewable energy facilities
have already been installed (~60 GW), we examined impacts as a range between the full 2022 goals
and the remaining goals (i.e., 2022 goals—2017 installed capacity. Because proliferation of rooftop
solar has been slow in India and solar development to date largely consists of ground-mounted solar,
we compared the land use change impacts when all solar renewable energy targets are met only with
ground-mounted development, and when states meet their rooftop and ground-mounted solar goals
separately as planned.
2. Methods
2.1. Renewable Energy Potential on Converted Lands
We focused our analyses on terrestrial lands and excluded water bodies and snow cover types
based on the 2011–2012 Land Use Land Cover (LULC) layer provided by India’s National Remote
Sensing Centre [
17
]. We also excluded areas where utility-scaled ground mounted wind and solar
energy development is less likely to occur, i.e., within urban areas (build-up cover types in LULC) and
protected areas (including all types of designation) [
18
,
19
]. All spatial analyses were conducted in
ArcMap v. 10.3 (Environmental Systems Research Institute, Redlands, CA, USA) [
20
] and program R
version 3.4.3 (R Foundation for Statistical Computing, Vienna, Austria) [21].
We then estimated renewable energy technical potential on suitable terrestrial lands for utility-scale
wind and photovoltaics solar (PV; also referred to as ground-mounted solar) at 1-km resolution,
following what is set out in Baruch-Mordo et al. 2019 [
22
]. Consistent with the feasibility criteria for
each sector’s development we excluded for wind: any cell with wind speed <5 m/s, slope >30% and
elevation >2000 m; and for PV: any cell with slope >5%. PV technologies harvest global horizontal
irradiance (GHI). Because many global or regional PV technical potential estimates do not apply
GHI thresholds [
23
–
26
], and because GHI values in India exceeded most thresholds previously used
(e.g., 1500 kWh/m
2
and 1400 kWh/m
2
[
27
,
28
]), we did not apply any GHI resource threshold for PV.
For each remaining ith suitable cell, we then estimated the available annual GWh generation using:
PD*CF
i
*8760/1000, where PD is power density or the MW produced per km
2
(2 MW/km
2
for wind,
and 26 MW/km
2
for PV), CF
i
is the spatially explicit capacity factor based on Wu et al. [
29
] as estimated
in Baruch-Mordo et al. [
22
], 8760 are the number of hours per year, and 1000 is a conversion factor from
Sustainability 2020,12, 281 5 of 14
MW to GW. Finally, we refined the derived wind and PV technical potential maps to include only cells
that overlapped with converted lands, which were defined as any cell with LULC categories of current
fallow, gullied, other wasteland, scrubland, and shifting cultivation. While we recognize that electricity
transmission capacity can influence siting, the basis for identifying the most attractive locations to site
new facilities is most commonly a measure of energy resource intensity [
30
]. This is especially relevant
for larger facilities sought by the Indian government [
31
,
32
], for which the benefits of high production
can outweigh the need to be close to electricity consumption [
33
]. In addition for the planning of PV
and wind-power infrastructure, region-specific thresholds are used to determine an energy resource
intensity (ERI), below which generation facilities would not likely be cost-effective. While these vary
depending on regional characteristics, the thresholds typically capture those areas with an ERI greater
than 85–95% of the maximum regional ERI [
31
,
32
], supporting our focus on maximizing the energy
resource potential as a key guide for siting.
2.2. Renewable Energy Credits and Deficits
Once we estimated technical potential for wind and ground-mounted solar (PV) on converted
lands, we summarized for each state or territory the available GW capacity and GWh energy generation.
We compared the summed wind and solar technical potential on converted lands to the sector specific
(wind, ground-mounted solar) full or remaining renewable energy goals for each state (Table 1;
see definitions for full and remaining goals in main text). We derived generation goals (GWh) by
multiplying the 2022 vision capacity goals reported in MW by 8760 h per year and dividing by
1000 (MW/GW).
2.3. Impacts of Renewable Energy Footprint
We examined the impacts of renewable energy siting on the potential conversion of current
natural lands (forested and non-forested) and agricultural lands under the unconstrained scenario,
where the full or remaining renewable energy goals were met by facilities being located where wind
and solar energy resources are the highest. Because goals were specified separately for solar and
wind, and because any given location may have the potential to produce energy for both sectors,
we first sited ground-mounted solar and then allocated the remaining suitable cells for wind. Because
installation of rooftop solar has been, to date, slow in India [
15
,
34
], we repeated the two allocation
scenarios (full or remaining goals) where we assumed ground-mounted solar would provide both
ground-mounted and rooftop solar goals (Figure 1). The latter allowed us to compare the amount of
impact that can be avoided if rooftop solar installations are included as planned in the 2022 vision. Once
targets were identified in accordance with the scenarios (Figure 1), we spatially allocated renewable
energy to maximize output by (1) ranking cells within each state by sector from highest to lowest
based on their technical potential, and (2) starting from the top classified cell, and then siting each
sector’s development by ranked order until the total sited energy potential equaled or just surpassed
the capacity goals. If at the stopping point more than one cell had similar technical potential value,
we randomly sited renewable energy to the last few cells to meet goals. We then examined the potential
impact of converting selected cells to each renewable energy sector by calculating losses (km
2
) of
forested natural lands (LULC categories: evergreen forest, deciduous forest, and scrub/degraded
forest cover types), non-forested natural lands (LULC categories: littoral swamp, grassland, and Rann
cover types), and agricultural lands (LULC categories: Karif, Rabi, Zaid, double/triple crop, and
plantation/orchard cover types).
Sustainability 2020,12, 281 6 of 14
3. Results
After removing areas unsuitable for renewable energy development (i.e., urban areas, permanently
protected lands, and areas without economically viable wind and solar resource potential), our analysis
indicates that a network of land-based wind turbines and solar arrays have the potential capacity
of 1789 GW (or generation of >15 million GWh) across India in areas already converted by human
activities (Figure 2; Table S1). Despite the extensive solar resources across India, seven states (Goa,
Kerala, Manipur, Meghalaya, Mizoram, Nagaland, and Tripura) and three union territories (Dadar &
Nagar Haveli, Daman & Diu, and Delhi) are unable to meet their full 2022 goals for ground-mounted
solar within already converted lands (Table S1). However, when focused on the remaining goals,
only Daman & Diu, Delhi, Kerala, and Tripura were unable to meet ground-mounted solar objectives.
Notwithstanding the overage of wind resources across India, two states (Madhya Pradesh and Tamil
Nadu) are unable to meet the full goals within already converted lands, while all can meet the remaining
wind goals (Table S1).
The total land footprint needed to meet India’s 2022 renewable energy target is large, ranging
from ~55,000 to 125,000 km
2
, but a development scenario that would meet the full goals by siting on
converted lands would avert the displacement of 50,621 km
2
of agricultural land, 11,607 km
2
of forest,
and 1315 km
2
of other natural lands relative to the unconstrained scenario in which development is
focused on exploiting the max wind and solar renewable energy potential (Figures 3and 4; Table S2).
By constraining only remaining goals to converted lands, it would still avert the conversion of 24,074 km
2
,
6731km
2
, and 190 km
2
of agricultural land, forest, and non-forest natural lands, respectively. In addition,
impacts to agricultural and natural habitats can be further reduced if rooftop solar energy goals are met;
achieving the full goals of ~40 GW rooftop solar would avert the conversion of an additional 5089 km
2
of agricultural land, 331 km
2
of forest, and 32 km
2
of other natural lands with similar outcomes for only
the remaining goals (Table S2). Not surprisingly, states with the largest projected renewable energy
goals had the most agricultural and natural lands impacted.
Sustainability 2019, 11, x FOR PEER REVIEW 6 of 14
3. Results
After removing areas unsuitable for renewable energy development (i.e., urban areas,
permanently protected lands, and areas without economically viable wind and solar resource
potential), our analysis indicates that a network of land-based wind turbines and solar arrays have
the potential capacity of 1789 GW (or generation of >15 million GWh) across India in areas already
converted by human activities (Figure 2; Table S1). Despite the extensive solar resources across
India, seven states (Goa, Kerala, Manipur, Meghalaya, Mizoram, Nagaland, and Tripura) and three
union territories (Dadar & Nagar Haveli, Daman & Diu, and Delhi) are unable to meet their full 2022
goals for ground-mounted solar within already converted lands (Table S1). However, when focused
on the remaining goals, only Daman & Diu, Delhi, Kerala, and Tripura were unable to meet
ground-mounted solar objectives. Notwithstanding the overage of wind resources across India, two
states (Madhya Pradesh and Tamil Nadu) are unable to meet the full goals within already converted
lands, while all can meet the remaining wind goals (Table S1).
The total land footprint needed to meet India’s 2022 renewable energy target is large, ranging
from ~55,000 to 125,000 km2, but a development scenario that would meet the full goals by siting on
converted lands would avert the displacement of 50,621 km2 of agricultural land, 11,607 km2 of
forest, and 1315 km2 of other natural lands relative to the unconstrained scenario in which
development is focused on exploiting the max wind and solar renewable energy potential (Figures 3
and 4; Table S2). By constraining only remaining goals to converted lands, it would still avert the
conversion of 24,074 km2, 6731km2, and 190 km2 of agricultural land, forest, and non-forest natural
lands, respectively. In addition, impacts to agricultural and natural habitats can be further reduced if
rooftop solar energy goals are met; achieving the full goals of ~40 GW rooftop solar would avert the
conversion of an additional 5089 km2 of agricultural land, 331 km2 of forest, and 32 km2 of other
natural lands with similar outcomes for only the remaining goals (Table S2). Not surprisingly, states
with the largest projected renewable energy goals had the most agricultural and natural lands
impacted.
Figure 2. Solar (rooftop and ground mounted photovoltaics) and wind GW goals for each state,
union territory, and district based on the Indian government’s 160 GW forecast of wind and solar
energy production to meet the 2022 vision.
Figure 2.
Solar (rooftop and ground mounted photovoltaics) and wind GW goals for each state, union
territory, and district based on the Indian government’s 160 GW forecast of wind and solar energy
production to meet the 2022 vision.
Sustainability 2020,12, 281 7 of 14
Sustainability 2019, 11, x FOR PEER REVIEW 7 of 14
(a)
(b)
Figure 3. Ground-mounted solar (PV) (a) and Wind (b) technical potential in GWh overlaid on
converted lands, defined as land use land cover categories of current fallow, gullied, other
wastelands, scrubland, and shifting cultivation. Black areas are converted lands that did not have
renewable energy potential based on our biophysical thresholds (e.g., amount of wind resource,
slope, elevation, etc.).
4. Discussion
It is clear that in order to reach its 2022 vision, renewable energy goals India will need to
strengthen the political economy for clean energy [35], expand the renewable energy certificate
market [36], improve grid integration and management [37] and create financial viability [38]. It is
also clear that investments in energy conservation and improved efficiency can help reduce the new
energy needed by India, reducing the area impacted by new energy development. Solutions to the
challenge of land acquisition are less obvious given the high population density and strong rights
afforded to private landowners in India [39]. Our results demonstrate that potential land-use
conflicts from renewable energy in India have both challenges and opportunities. The transition
from fossil-fuel based energy generation to renewable energy generation would require a greater
land footprint [40], leading to tradeoffs on land use and potentially exacerbating land use conflicts
[41]. The total land footprint needed to meet India’s renewable energy targets is large, ranging from
approximately 55,000 to 125,000 km2, or areas roughly the size of Himachal Pradesh or Chhattisgarh,
respectively. Depending on the scenario’s goals (full or remaining, with rooftop solar or all
ground-mounted solar), if renewable energy development proceeds with the singular aim of
maximizing resource potential, approximately 6700–11,900 km2 of forest land and 24,100–55,700 km2
of agricultural land could be impacted. This lower range based on the remaining goal is likely
optimistic because some solar and wind projects have already been sited on forest or natural lands
[42,43]. These losses could cause environmental and social conflicts, jeopardize financial investment,
and in turn slow the expansion of renewable energy in the country. Fortunately, our analyses also
show that there is ample opportunity (>10 times what is needed) to achieve India’s solar and wind
goals on converted lands, which are likely to have lower biodiversity or agricultural values.
4.1. Blending Renewable Energy Planning with The Mitigation Hierarchy
Accelerating renewable energy development while meeting India’s commitment to increase
forest cover, along with other social and environmental goals, requires planning and
implementation tools in order to evaluate tradeoffs [44] and facilitate decisions to avoid, minimize
and mitigate impacts [45]. The converted lands prioritized for development in our scenarios likely
Figure 3.
Ground-mounted solar (PV) (
a
) and Wind (
b
) technical potential in GWh overlaid on
converted lands, defined as land use land cover categories of current fallow, gullied, other wastelands,
scrubland, and shifting cultivation. Black areas are converted lands that did not have renewable energy
potential based on our biophysical thresholds (e.g., amount of wind resource, slope, elevation, etc.).
4. Discussion
It is clear that in order to reach its 2022 vision, renewable energy goals India will need to strengthen
the political economy for clean energy [
35
], expand the renewable energy certificate market [
36
],
improve grid integration and management [
37
] and create financial viability [
38
]. It is also clear
that investments in energy conservation and improved efficiency can help reduce the new energy
needed by India, reducing the area impacted by new energy development. Solutions to the challenge
of land acquisition are less obvious given the high population density and strong rights afforded
to private landowners in India [
39
]. Our results demonstrate that potential land-use conflicts from
renewable energy in India have both challenges and opportunities. The transition from fossil-fuel
based energy generation to renewable energy generation would require a greater land footprint [
40
],
leading to tradeoffs on land use and potentially exacerbating land use conflicts [
41
]. The total land
footprint needed to meet India’s renewable energy targets is large, ranging from approximately
55,000 to 125,000 km
2
, or areas roughly the size of Himachal Pradesh or Chhattisgarh, respectively.
Depending on the scenario’s goals (full or remaining, with rooftop solar or all ground-mounted solar),
if renewable energy development proceeds with the singular aim of maximizing resource potential,
approximately 6700–11,900 km
2
of forest land and 24,100–55,700 km
2
of agricultural land could be
impacted. This lower range based on the remaining goal is likely optimistic because some solar and
wind projects have already been sited on forest or natural lands [
42
,
43
]. These losses could cause
environmental and social conflicts, jeopardize financial investment, and in turn slow the expansion of
renewable energy in the country. Fortunately, our analyses also show that there is ample opportunity
(>10 times what is needed) to achieve India’s solar and wind goals on converted lands, which are likely
to have lower biodiversity or agricultural values.
4.1. Blending Renewable Energy Planning with The Mitigation Hierarchy
Accelerating renewable energy development while meeting India’s commitment to increase forest
cover, along with other social and environmental goals, requires planning and implementation tools in
order to evaluate tradeoffs [
44
] and facilitate decisions to avoid, minimize and mitigate impacts [
45
].
The converted lands prioritized for development in our scenarios likely represent lower-quality habitats,
which are unlikely to support populations of imperiled species and natural community assemblages.
Sustainability 2020,12, 281 8 of 14
These areas may also have relatively lower potential for social conflicts for food security, settlement, and
use for biomass harvesting [
17
]. Thus, our results suggest that converted lands provide an opportunity
to meet renewable energy goals that reduce impacts for people and nature. However, we recognize
that ~27% India’s 329 million hectares are classified as wasteland, a key component of our converted
area designation, and that there is still a significant portion of the population that depends on this
land for livelihood [
46
]. Furthermore, given that the current designation of wastelands is based on
remotely sensed data [
17
], care should be taken to ensure the converted lands designation is not a
misclassification of important natural habitats, such as grasslands or wetlands [46,47]. If India wants
to reach its renewable energy development goals, then they will encounter land use tradeoffs—and our
analysis will help to illustrate the tradeoffs and provide options that may reduce conflicts—but the
assessment of tradeoffs involved with the conversion of land for renewable energy development will
need to happen at a scale where land use values can be accurately mapped and quantified.
In marked contrast to the converted lands that we prioritized in the constrained scenario, forested
areas are critically important for biodiversity [
48
]. Species of conservation concern that require large
intact habitats, such as tigers, are sensitive to human activity and may avoid lands with human
disturbance. In India, the significance of human disturbance in areas important for tiger movement
between protected areas has been highlighted as an important issue [
48
]. Poorly sited renewable energy
development that results in the clearing of natural habitats may be incompatible with preserving
the viability of species requiring large intact habitats. Apart from renewable energy, India also has
ambitious reforestation and forest restoration goals as described in the GIM and further articulated in
its Nationally Determined Contribution to UNFCCC [
2
]. Unplanned renewable energy development
has the potential to undermine these reforestation goals. Unfortunately, renewable energy development
is already occurring in areas outside of the converted lands we identified. These observations indicate
that the current regulatory process is largely inadequate at ensuring that wind and solar production
are low-impact. For example, by 2017, more than 4600 hectares of forest land was impacted by wind
projects [
42
,
43
]. Similarly, several solar projects have impacted native grasslands that are home to
endangered species such as the great Indian bustard [49].
4.2. Implementation Challenges and Opportunities
In India, wind and solar projects are considered “green” by most state regulatory agencies,
which means that projects do not need an Environmental Impact Assessment (EIA) regardless of
their size or location. Improving oversight through the use of an EIA or other centralized regulatory
processes could be an easy mechanism to reduce impacts. Since there is a lack of a centralized
regulatory framework or incentive structure, relying on farsighted developers to actively avoid a
site with significant biodiversity or agricultural value is unlikely to achieve the desired results as
past development patterns have demonstrated [
42
,
43
]. However, significant additional legislation
restricting the production of renewable energy resources on private land based on wildlife concerns is
unlikely given the present political climate [
39
]. Instead, improved incentives that provide a competitive
advantage to developers that comply can be helpful for the adoption of low-impact development
practices. Development of compliance standards could function as the basis for decision-making
on power procurement by utilities. Since the production of renewable energy would usually not be
funded without a long-term power purchase agreement, that would give developers strong incentives
to comply with any requirements. These guidelines should not only recognize low-impact areas,
but also identify areas of avoidance that cannot be approved for development. Formal standards and
accreditation that guide power procurement, as well as guiding subsides to low impact projects, can all
advance low impact siting [
50
]. Decision support tools that help to identify low conflicts solutions [
51
]
can provide the necessary foundation to implement formal guidelines and certification schemes.
Ensuring that renewable energy avoids productive agricultural lands will also reduce conflicts that
may slow proliferation. Maintaining the stability of the agriculture sector is an important part of India’s
overall economic progress. Besides providing food, agricultural development represents 17–18%
Sustainability 2020,12, 281 9 of 14
of total national income and >50% of the workforce is engaged in agricultural production [
52
,
53
].
In turn, growth in other sectors and economic stability overall depend, to a considerable extent, on the
performance of India’s agriculture sector. Because agriculture continues to be the dominant sector
in the Indian economy, ensuring that renewable energy avoids productive agricultural lands will
reduce conflicts that may slow proliferation. Furthermore, agricultural expansion is one of the most
important immediate deforestation drivers [
54
–
56
]; therefore, if we avoid displacing agriculture with
renewable energy, then it will reduce the “domino-effect” of additional natural land conversion to
replace the lost agricultural lands. However, while solar plants produce a major change in land use,
wind farms usually only use 2–4 percent of an area and can be co-developed within areas of agricultural
production [
57
]. In addition, farmers in the U.S.A. may earn $4000–$8000 per turbine each year when
they lease cropland for wind energy development [
58
]. However, wind requires almost 6 times as
much land as solar [
40
], and if feasible given constraints, switching solar for wind could reduce the
overall land needed to meet goals.
4.3. Analysis Caveats
While our study shows that wind and solar deployment can be placed in ways that mitigate
conflicts about land use, our research fails to consider several important issues and does not seek to
delineate exactly where renewable energy should be installed. For example, the opportunity to establish
renewable energy facilities on converted land can be limited by site-specific features or landowner
preferences. The proactive inclusion of land ownership, especially land claims of marginalized peoples,
such as indigenous groups, should be an important component of the decision making process.
However, the deployment of new renewable power facilities is restricted by transmission capacity;
therefore, the availability of transmission lines can have a huge impact on the development of new
wind farms and solar arrays. Transmission lines also result in land conversion and fragmentation,
which can substantially increase impacts to agriculture and natural lands. We, therefore, suggest
that site-specific siting (and general guidelines) target transmission lines to low-impact areas. Finally,
we suggest that our identification of converted lands represents the first step to guide renewable energy
development to reduce impacts to natural and agricultural land. Even in the areas that we say should
be the priority for future development, there may be important conservation values that can mitigated
by good micro-siting practices and better on-site management (e.g., reducing blade movement to
reduce bat or bird mortality) [
59
]. With the national surplus in wind and solar energy, it is possible
for states that do not meet wind and solar targets on converted lands to import electricity from states
with surpluses of low impact renewable energy. In fact, several states have a substantial overage of
renewable energy on low impact lands (Figure 3), where further growth could help mitigate disputes
over land use. If transmission and political restrictions make it practical, increasing the deployment of
renewable energy facilities to states with a surplus of renewable energy potential on converted areas
may mitigate some of the possible conflicts in land use. It may also be possible to reduce potential land
conflicts by switching the mix of wind and solar that states use to meet their goals.
5. Conclusions
The first obvious step towards sustainable renewable energy development will involve guiding
production onto previously converted or degraded lands [
41
]. Utilizing the power of systematic
conservation planning would allow stakeholders to evaluate the impact of development scenarios that
impact lands with a high conservation value while concurrently identifying low impact renewable
energy “go-zones”, thereby reducing conflicts that can slow investment [
40
,
41
,
50
]. There are two
main applications from the results of our study that can guide additional analysis. First and foremost,
our study will help decision-makers understand the scope and scale of future impacts of renewable
energy, providing the incentive to invest in the development of principles and planning that improve
renewable energy siting. As our research has shown, if these new renewable energy facilities are not
deployed carefully, they will adversely affect vital ecosystem services. For this level of development to
Sustainability 2020,12, 281 10 of 14
be sustainable in India, the challenge is to co-develop environments that satisfy the increasing energy
demand and reduce their impacts on both nature and people. Nevertheless, Indian society remains
largely unaware of the significant footprint from future energy development and the urgent need to
prepare for it [
39
,
42
,
43
]. Secondly, our research will help to identify areas where conservation values
are most at risk as a result of the expansion of renewable energy development and where more detailed
planning is urgently required. This type of planning will have to include stakeholders and data sets
that are normally not brought together—blending the fields of environmental science and energy
engineering. Given this difficulty, it will be important to carefully focus where these investments will
avoid the most harm and in turn deliver the best return on investment. States with the highest wind
and solar development objectives would also likely have the greatest difficulty finding solutions that
avoid impact. Nonetheless, these same states vary with respect to potential impacts on natural habitat
and high-production agriculture, and our research will help ensure that attention is focused on the
most vulnerable states (Table 1, Figures 3and 4).
Sustainability 2019, 11, x FOR PEER REVIEW 10 of 14
renewable energy, providing the incentive to invest in the development of principles and planning
that improve renewable energy siting. As our research has shown, if these new renewable energy
facilities are not deployed carefully, they will adversely affect vital ecosystem services. For this level
of development to be sustainable in India, the challenge is to co-develop environments that satisfy
the increasing energy demand and reduce their impacts on both nature and people. Nevertheless,
Indian society remains largely unaware of the significant footprint from future energy development
and the urgent need to prepare for it [39,42,43]. Secondly, our research will help to identify areas
where conservation values are most at risk as a result of the expansion of renewable energy
development and where more detailed planning is urgently required. This type of planning will
have to include stakeholders and data sets that are normally not brought together—blending the
fields of environmental science and energy engineering. Given this difficulty, it will be important to
carefully focus where these investments will avoid the most harm and in turn deliver the best return
on investment. States with the highest wind and solar development objectives would also likely
have the greatest difficulty finding solutions that avoid impact. Nonetheless, these same states vary
with respect to potential impacts on natural habitat and high-production agriculture, and our
research will help ensure that attention is focused on the most vulnerable states (Table 1, Figures 3
and 4).
Figure 4. Results of development scenario that allow for unconstrained development based solely
on maximizing wind and solar renewable energy potential. Pie charts and insert table highlight
agricultural lands, forest, and other natural land cover types that could be impacted if development
is based solely on maximizing wind and solar renewable energy potential and is not placed in a
restricted manner on converted lands of low value to agriculture and biodiversity, which is defined
as land use land cover categories of current fallow, gullied, other wastelands, scrubland, and
shifting cultivation.
In areas where the production of renewable energy will interfere with protecting natural
habitats, approaches are needed to balance development objectives and conservation outcomes.
Targeting renewable energy to converted areas with lower potential conflict will concurrently help
society achieve clean energy targets, maintain food security, improve restoration and health of
Figure 4.
Results of development scenario that allow for unconstrained development based solely
on maximizing wind and solar renewable energy potential. Pie charts and insert table highlight
agricultural lands, forest, and other natural land cover types that could be impacted if development is
based solely on maximizing wind and solar renewable energy potential and is not placed in a restricted
manner on converted lands of low value to agriculture and biodiversity, which is defined as land use
land cover categories of current fallow, gullied, other wastelands, scrubland, and shifting cultivation.
In areas where the production of renewable energy will interfere with protecting natural habitats,
approaches are needed to balance development objectives and conservation outcomes. Targeting
renewable energy to converted areas with lower potential conflict will concurrently help society achieve
clean energy targets, maintain food security, improve restoration and health of forests, and protect
biodiversity. Our analysis shows that all wind and solar energy demand from India’s 2022 target can
be met on lands likely to have a low impact on agriculture production and biodiversity conservation.
Avoiding the exacerbation of current and future land scarcity in the second most populous country in
the world would entail proactive landscape planning coupled with proper incentive mechanisms from
Sustainability 2020,12, 281 11 of 14
power purchasers and lending institutions. In India, renewable energy production on converted lands
could provide over 10 times the 2022 target, but the development of new strategies and interventions
are needed to ensure siting is sustainable.
Supplementary Materials:
The following are available online at http://www.mdpi.com/2071-1050/12/1/281/s1,
Table S1: India’s renewable energy generation goals (GWh), the available renewable energy technical potential on
converted lands (wastelands), and the ratio of GWh on converted to generation goals by state or union territory.
Goals and ratio are specified for the full 2022 vision goals for solar (rooftop and ground-mounted) and wind
renewable energy, and for the remaining goals if 2017 installed capacity is subtracted. Goals were converted from
MW to GWh by multiplying by 8760 h per year and dividing by 1000 (MW/GW). Ratios are also specified if all solar
goals (i.e., rooftop and ground-mounted) are met using ground-mounted solar based on current installation trends.
NA entries for GWh available on converted lands may reflect no suitable areas meeting development criteria
(e.g., slope <5% for solar) are available on converted lands, or that input layers (e.g., GHI irradiation) did not
cover the state or territory. Table S2: The amount of km
2
allocated by state or union territory to ground-mounted
solar or wind renewable energy to meet India’s renewable energy goals, and the potential impacts (km
2
loss) to
agriculture, forest, and on-forest natural lands if renewable energy is sited where solar and wind resources are the
highest. Allocation and impacts are provided for four goals scenarios considering the full 2022 vision goals or
only the remaining goals after subtracting 2017 installed capacity, and considering allocation of all solar goals
(rooftop and ground-mounted) to ground-mounted installation reflecting current trends, or allocation of rooftop
and ground-mounted goals separately. Differences summary row represent the difference of km
2
impact between
the latter scenarios (i.e., rooftop solar goals are fulfilled separately, or where all solar goals are met with ground
mounted solar).
Author Contributions: J.K. and D.N. conceived the study; S.B.-M. and J.K designed the study; S.B.-M. and M.H.
collected and analyzed the data, and produced figures and tables; J.O., P.C. assisted in data collection and provided
input on the analysis approach; J.K. and S.B.-M. interpreted results and wrote the paper with contributions from
D.N., C.K., J.O., and P.C. All authors have read and agreed to the published version of the manuscript.
Funding: Macarthur Foundation of India, Enterprise Foundation, The Nature Conservancy, and Roy Vagelos.
Acknowledgments:
We Thank Macarthur Foundation of India, Enterprise Foundation, The Nature Conservancy,
and Roy Vagelos for Funding Support. We appreciate input from Kunal Sharma, Sushil Saigal, Seema Paul,
Jai Asundi, Saroo Brierley and Gaurav Kapoor.
Conflicts of Interest:
The authors declare no conflict of interest. The funders had no role in the design of the
study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to
publish the results.
References
1.
Palchak, D.; Cochran, J.; Ehlen, A.; McBennett, B.; Milligan, M.; Chernyakhovskiy, I.; Sreedharan, P.W.
Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India’s Electric Grid, Vol.
I—National Study (2017); National Renewable Energy Lab. NREL: Golden, CO, USA, 2017. Available online:
https://www.osti.gov/servlets/purl/1369138 (accessed on 20 October 2019). [CrossRef]
2.
Government of India. India’s Intended Nationally Determined Contribution, as Submitted to the United
Nations Framework Convention on Climate Change. 2016. Available online: https://www4.unfccc.int/sites/
submissions/indc/Submission%20Pages/submissions.aspx (accessed on 28 December 2019).
3.
Khare, V.; Nema, S.; Baredar, P. Status of solar wind renewable energy in India. Renew. Sustain. Energy Rev.
2013,27, 1–10. [CrossRef]
4.
NITI Aayog. Report on India’s Renewable Electricity Roadmap 2030: Toward Accelerated Renewable Electricity
Deployment; NITI Aayog: New Delhi, India, 2015. Available online: http://niti.gov.in/writereaddata/files/
document_publication/RE_Roadmap_ExecutiveSummary.pdf (accessed on 4 April 2018).
5.
Patil, M. Modi Government’s Big Solar Push Could Run into Land Hurdle the Economic Times 2017. Available
online: http://economictimes.indiatimes.com/industry/energy/power/modi-governments-big-solar-push-
could-run-into-land-hurdle-readwhy/articleshow/57850475.cms (accessed on 8 January 2018).
6.
Rajaram, R. The Biggest Challenge is Acquiring Land for Wind Farms. Project Monitor 2012. Available
online: http://www.projectsmonitor.com/interviews/thebiggest-challenge-is-acquiring-land-for-wind-farms/
(accessed on 8 January 2019).
7.
Siraj, M.A. Wind Power Faces Rough Weather [WWW Document]. The Hindu. 2015. Available online: http://www.
thehindu.com/features/homes-and-gardens/wind-power-faces-roughweather/article7064997.ece (accessed on 8
January 2018).
Sustainability 2020,12, 281 12 of 14
8.
United Nations, Department of Economic and Social Affairs, Population Division. World Population Prospects:
The 2017 Revision, Custom Data Acquired via Website; United Nations, Department of Economic and Social
Affairs, Population Division: New York, NY, USA, 2017.
9.
Chakravorty, S. The Price of Land: Acquisition, Conflict and Consequence; Oxford University Press: New Delhi,
India, 2015.
10.
Rights and Resources Initiative. Land Conflicts in India—An Interim Analysis, Technical Report (2016), Tata
Institute of Social Sciences. Available online: https://rightsandresources.org/en/publication/land-conflicts-
india-interim-analysis/#.XT6tYOtKjIU (accessed on 27 March 2019).
11.
India Ministry of Environment and Forests (2015). National Mission for a Green India (Under the National
Action Plan on Climate Change). Available online: http://www.moef.gov.in/sites/default/files/GIM_Mission%
20Document-1.pdf (accessed on 12 May 2018).
12.
Mahtta, R.; Joshi, P.K.; Jindal, A.K. Solar power potential mapping in India using remote sensing inputs and
environmental parameters. Renew. Energy 2014,71, 255–262. [CrossRef]
13.
Mentis, D.; Siyal, S.H.; Korkovelos, A.; Howells, M. A geospatial assessment of the techno-economic wind
power potential in India using geographical restrictions. Renew. Energy 2016,97, 77–88. [CrossRef]
14.
CSTEP; WFMS; SSEF. Reassessment of India’s Onshore Wind Potential, Technical Report, Center for Study of
Science, Technology, and Policy, WinDForce Management Services, and Shakti Sustainable Energy Foundation.
2016. Available online: http://www.indiaenvironmentportal.org.in/files/file/IndiaWindPotentialAssessment.
pdf (accessed on 28 December 2019).
15.
India Ministry of New and Renewable Energy, Government of India. 2018. Available online: https:
//mnre.gov.in/physical- progress-achievements# (accessed on 4 November 2019).
16.
Deshmukh, R.; Wu, G.C.; Callaway, D.S.; Phadke, A. Geospatial and techno-economic analysis of wind and
solar resources in India. Renew. Energy 2019,134, 947–960. [CrossRef]
17.
National Remote Sensing Centre of India. Land Use/Land Cover Database on 1:50,000 Scale, Natural Resources
Census Project, LUCMD, LRUMG, RS & GIS AA; National Remote Sensing Centre, ISRO: Hyderabad,
India, 2012.
18.
UNEP-WCMC and IUCN. Protected Planet: India; The World Database on Protected Areas (WDPA)/The Global
Database on Protected Areas Management Effectiveness (GD-PAME); UNEP-WCMC and IUCN: Cambridge, UK,
2018. Available online: www.protectedplanet.net (accessed on 27 March 2019).
19.
International Union for Conservation of Nature. World Database on Protected Areas (WDPA). 2017. Available
online: https://www.iucn.org/theme/protected-areas/our-work/quality-and-effectiveness/world-database-
protected-areas-wdpa (accessed on 27 March 2019).
20. ESRI ArcGIS for Desktop: Release 10; Environmental Systems Research Institute: Redlands, CA, USA, 2015.
21.
R Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing:
Vienna, Austria, 2017. Available online: https://www.R-project.org/(accessed on 28 December 2019).
22.
Baruch-Mordo, S.; Kiesecker, J.; Kennedy, C.M.; Oakleaf, J.R.; Opperman, J.J. From Paris to practice:
Sustainable implementation of renewable energy goals. Environ. Res. Lett. 2019,14. [CrossRef]
23.
Deng, Y.Y.; Haigh, M.; Pouwels, W.; Ramaekers, L.; Brandsma, R.; Schimschar, S.; Grözinger, J.; de Jager, D.
Quantifying a realistic, worldwide wind and solar electricity supply. Glob. Environ. Chang.
2015
,31, 239–252.
[CrossRef]
24.
Lopez, A.; Roberts, B.; Heimiller, D.; Blair, N.; Porro, G.U.S. Renewable Energy Technical Potentials: A GIS Based
Analysis; Report no. NREL/TP-6A20–51946; National Renewable Energy Laboratory: Golden, CO, USA, 2012.
25. Köberle, A.C.; Gernaat, D.E.H.J.; van Vuuren, D.P. Assessing current and future techno-economic potential
of concentrated solar power and photovoltaic electricity generation. Energy 2015,89, 739–756. [CrossRef]
26.
Hernandez, R.R.; Hoffacker, M.K.; Murphy-Mariscal, M.L.; Wu, G.C.; Allen, M.F. Solar energy development
impacts on land cover change and protected areas. Proc. Natl. Acad. Sci. USA
2015
,112, 13579–13584.
[CrossRef]
27.
Hermann, S.; Miketa, A.; Fichaux, N. Estimating the Renewable Energy Potential in Africa GIS-Based Approach;
IRENA Working Paper; International Renewable Energy Agency: Abu Dhabi, UAE, 2014.
28.
He, G.; Kammen, D.M. Where, when and how much solar is available? A provincial-scale solar resource
assessment for China Renew. Energy 2016,85, 74–82. [CrossRef]
Sustainability 2020,12, 281 13 of 14
29.
Wu, G.C.; Deshmukh, R.; Ndhlukula, K.; Radojicic, T.; Reilly-Moman, J.; Phadke, A.; Callaway, D.S. Strategic
siting and regional grid interconnections key to low-carbon futures in African countries. Proc. Natl. Acad.
Sci. USA 2017,114, E3004–E3012. [CrossRef]
30.
Oakleaf, J.R.; Kennedy, C.M.; Baruch-Mordo, S.; Gerber, J.S.; West, P.C.; Johnson, J.A.; Kiesecker, J. Mapping
global development potential for renewable energy, fossil fuels, mining and agriculture sectors. Sci. Data
2019,6, 101. [CrossRef] [PubMed]
31.
IRENA (International Renewable Energy Agency). Data Quality for the Global Renewable Energy
Atlas—Solar and Wind. 2013. Available online: https://www.irena.org/publications/(accessed on 28
December 2019).
32.
IRENA (International Renewable Energy Agency). Global Atlas for Renewable Energy, Overview of Solar and
Wind Maps. 2014. Available online: https://www.irena.org/publications/(accessed on 28 December 2019).
33. Li, X.; Hubacek, K.; Siu, Y.L. Wind power in China—Dream or reality? Energy 2012,37, 51–60. [CrossRef]
34.
Goel, M. Solar rooftop in India: Policies, challenges and outlook. Green Energy Environ.
2016
,1, 129–137.
[CrossRef]
35.
Rehman, S.; Hussain, Z. Renewable Energy Governance in India: Challenges and Prospects for Achieving
the 2022 Energy Goals. J. Resour. Energy Dev. 2018,14, 13–22. [CrossRef]
36.
Kaladharan, M. Renewable Energy in India: An Analysis of the Regulatory Environment and Evolving
Policy Trends. Centre for Policy Research. 2016. Available online: https://cprindia.org/(accessed on 17
November 2019).
37.
KAPSARC (King Abdullah Petroleum Studies and Research Center). Renewable Energy Policy in India:
Creation, Implementation and Efficacy. 2016. Available online: https://www.kapsarc.org/wp-content/uploads/
2016/08/KS-1632-WB031A-Renewable-Energy-Policy-in-India_Creation-Implementation- and-Efficacy.pdf
(accessed on 27 September 2019).
38.
IEEFA (Institute for Energy Economics and Financial Analysis). India Electricity Sector Transformation:
Global Capacity Building. 2015. Available online: http://ieefa.org/wp-content/uploads/2015/11/IEEFA-India-
Electricity-Sector-Transformation_Global-Capacity-Building_11112015.pdf (accessed on 20 September 2019).
39. Mohan, A. Whose land is it anyway? Energy futures & land use in India. Energy Policy 2017,110, 257–262.
40.
McDonald, R.I.; Fargione, J.; Kiesecker, J.; Miller, W.M.; Powell, J. Energy Sprawl or Energy Efficiency:
Climate Policy Impacts on Natural Habitat for the United States of America. PLoS ONE
2009
,4, e6802.
[CrossRef]
41.
Kiesecker, J.M.; Naugle, D.E. (Eds.) Energy Sprawl Solutions: Balancing Global Development and Conservation;
Island Press: Washington, DC, USA, 2017.
42.
Government of India, Loksabha Unstarred Question 1026. 2018. Available online: http://164.100.47.190/
loksabhaquestions/annex/14/AU1026.pdf (accessed on 4 October 2019).
43.
Egreenwatch, e-Green Watch—FCA Projects, Diverted Land, Compensatory Land Management 2018.
Available online: http://egreenwatch.nic.in/FCAProjects/Public/Rpt_State_Wise_Count_FCA_projects.aspx
(accessed on 4 October 2019).
44.
Kennedy, C.M.; Hawthorne, P.L.; Miteva, D.A.; Baumgarten, L.; Sochi, L.; Matsumoto, M.; Kiesecker, J.
Optimizing land use decision-making to sustain Brazilian agricultural profits, biodiversity, and ecosystem
services. Biol. Conserv. 2016,204, 221–230. [CrossRef]
45.
Kiesecker, J.M.; Copeland, H.; Pocewicz, A.; McKenney, B. Development by design: Blending landscape-level
planning with the mitigation hierarchy. Front. Ecol. Environ. 2010,8, 261–266. [CrossRef]
46.
Vanak, A.; Hiremath, A.; Rai, N. Wastelands of the Mind: The Identity Crisis of India’s Tropical Savannas;
Current Conservation, Issue 7.3. Delhi, India, 2013. Available online: https://www.currentconservation.org/
wastelands-of-the-mind-the-identity-crisis-of-indias-tropical-savannas/(accessed on 28 December 2019).
47.
Rawat, G.S.; Adhikari, B.S. (Eds.) Ecology and Management of Grassland Habitats in India; Wildlife Institute of
India: Dehradun, India, 2015.
48.
Borah, J.; Jena, J.; Yumnam, B.; Puia, L. Carnivores in corridors: Estimating tiger occupancy in Kanha—Pench
corridor, Madhya Pradesh, India. Reg. Environ. Chang. 2016,16, 43–52. [CrossRef]
Sustainability 2020,12, 281 14 of 14
49.
Vanak, A.; Kulkarni, A.; Gode, A.; Sheth, C.; Krishnaswamy, J. Extent and Status of Semi-Arid Savanna
Grasslands in Peninsular India. In Grassland Vegetation of India: An Update; Rawat, G.S., Adhikari, B.S.,
Eds.; ENVIS Bulletin: Wildlife & Protected Areas; Wildlife Institute of India: Dehradun, India, 2015;
pp. 192–201. Available online: http://wiienvis.nic.in/WriteReadData/Publication/19_Grassland%20Habitat_
2016.pdf (accessed on 4 October 2019).
50.
Cameron, D.R.; Crane, L.; Parker, S.S.; Randall, J.M. Solar Energy Development and Regional Conservation
Planning. In Energy Sprawl Solutions; Kiesecker, J.M., Naugle, D., Eds.; Island Press: Washington, DC, USA,
2017; pp. 66–75.
51.
The Nature Conservancy of India. Renewable Energy by Design Siting Tool. Available online: www.tncindia.
in/siteright (accessed on 28 December 2019).
52.
Tripathi, A.; Prasad, A.R. Agricultural Development in India since Independence: A Study on Progress,
Performance, and Determinants. J. Emerg. Knowl. Emerg. Mark. 2009,1, 8. [CrossRef]
53.
India Ministry of Finance. India Economic Survey 2017–18; Ministry of Finance, Government of India: New
Delhi, India, 2018.
54.
Jha, C.S.; Dutt, C.B.S.; Bawa, K.S. Deforestation and Land Use Changes in Western Ghats, India. Curr. Sci.
2000,79, 231–238.
55.
Reddy, C.S.; Jha, C.S.; Dadhwal, V.K.; Hari Krishna, P.; Pasha, S.V.; Satish, S.K.; Diwakar, P.G. Quantification
and Monitoring of Deforestation in India over Eight Decades (1930–2013). Biodivers. Conserv.
2016
,25,
93–116. [CrossRef]
56.
Yadav, P.K. Slash-and-Burn Agriculture in North-East India. J. Expert Opin. Environ. Biol.
2013
,2, 2–5.
[CrossRef]
57.
AWEA (American Wind Energy Association) Wind Energy and Wildlife. 2009. Available online: http:
//www.awea.org/documents/factsheets/Wind_Energy_and_Wildlife_Mar09.pdf (accessed on 4 October 2019).
58.
Burt, M.; Firestone, J.; Madsen, J.A.; Veron, D.E.; Bowers, R. Tall towers, long blades and manifest destiny:
The migration of land-based wind from the Great Plains to the thirteen colonies. Appl. Energy
2017
,206,
487–497. [CrossRef]
59.
Arnett, E.B.; Huso, M.M.P.; Schirmacher, M.M.; Hayes, J.P. Altering turbine speed reduces bat mortality at
wind-energy facilities. Front. Ecol. Environ. 2011,9, 209–214. [CrossRef]
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