Final Version of article available at this link http://authors.elsevier.com/a/1TGXK8M-mmSKCC
Estimating carbon emissions from forest fires over a decade in Similipal Biosphere Reserve, India K.R.L. Saranyaa,* C. Sudhakar Reddya , P.V.V. Prasada Raob *
[email protected] a
Forestry & Ecology Group, National Remote Sensing Centre, ISRO, Balanagar, Hyderabad- 500
037, India b
Department of Environmental Sciences, Andhra University, Visakhapatnam-530003, India
Abstract: The forest fire is a well-recognized threat to biodiversity and a significant cause of ecological degradation. Fires emit significant amounts of CO2 to the atmosphere. Studies have found that greenhouse gas emissions from forest fires strongly influence climate change. In the present study, the Spatio-temporal patterns of forest fires were examined from 2004 to 2013 in Similipal Biosphere Reserve, Eastern Ghats of India. This study focuses on estimation of carbon emissions from forest fires based on IPCC Guidelines for National Greenhouse Gas Inventories. The total area affected under forest fire has been estimated as 23.7% in 2004, 11.5% in 2005, 24.8% in 2006, 23.5% in 2007 and 18% in 2008, 27.9% in 2009, 16.4% in 2010, 16.3% km2 in 2011, 27% km2 in 2012 and 14% in 2013. CO2 emissions were estimated for tropical vegetation types i.e. semi-evergreen, moist deciduous, dry deciduous, high-level Sal, low-level Sal forest, scrub, savannah and grasslands. The total carbon emissions from forest fires in Similipal vary from 0.93 1
to 1.58 CO2 Tg yr-1 during the study. The mean annual rate of carbon emissions was observed to be 1.26 CO2 Tg yr-1. Similarly, other trace gases like CO, CH4, N2O and NOx has also been calculated. This study is helpful in formulating conservation plans and thus helps in mitigating the impact of climate change. Considering the global significance of Biosphere Reserves in the conservation of biodiversity, more scientific studies are required to understand the impact of ongoing fire regimes. Key words: Forest fires, CO2 emissions, Similipal, Odisha Introduction: Fires are a part of the earth system from the pre-human era. They play a vital role in ecosystem composition and distribution (Bond et al., 2005). Fires have been observed from the geological scale going back to the origin of terrestrial life (Bowman et al., 2009). Since the late 1970s; studies have found that greenhouse gas emissions from forest fires strongly influence climate change (Seiler and Crutzen, 1980). Forest fires represent an important source of atmospheric trace gases and aerosol particles. Fire influences global ecosystem patterns and processes, including vegetation distribution and structure, the carbon cycle and climate. The atmospheric carbon levels have increased after the domestic use of fire around 50,000 to 100,000 years (BarYosef, 2002). In the recent past, tropical forests consisting of fire-resistant species are being cleared due to the conversion of forests to non-forest owing to rapid industrialization (Mouillot and Field, 2005). Increased vegetation fire surge releases a high amount of carbon dioxide in the atmosphere. This high amount of CO2 in the atmosphere can be estimated and balanced by alternative conservation plans.
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Forest fires in India are mostly anthropogenic (Giriraj et al., 2010); however, the intensity of fire depends on climate, fuel type, the wind, topography, and demography. The observations in the past 20 years show that the increasing intensity and spread of forest fires in Asia were largely related to the rise in temperature and decline in precipitation in combination with the change in land uses (IPCC, 2007). There are shreds of evidence towards increased frequency of anthropogenic fires than in the past in Indian forests (Kodandapani, 2013; Harikrishna and Reddy, 2012). To evaluate and represent the impact of biomass burning, models of atmospheric transport and chemistry, accurate data on the emission of trace gases from biomass burning through forest fires are required. The advancement in satellite remote sensing supports spatial and multi-temporal fire detection and damage assessment. In multi-temporal approach, identification of burnt areas is easier, due to typical spectral separability, because of the different ground coverage between
pre-fire
(vegetation) and post-fire (ash, bare soil or dead vegetation or low photosynthetic activity) conditions (Bucini and Lambin, 2002; Chirici and Corona, 2005). Sensors such as Advanced Wide Field Sensor (AWiFS), Landsat-7 Enhanced Thematic Mapper+ (ETM+), Indian Remote Sensing Satellite P6 Linear Imaging Self-Scanner (IRS P6 LISS-III), Satellite Pour l' Observation de la Terre (SPOT), Advanced Along-Track Scanning Radiometer (AATSR), Advanced Very High Resolution, Radiometer (AVHRR), Moderate Resolution Imaging Spectro radiometer (MODIS) will provide
synergistic datasets having potential application in forest fire studies (Chand et al., 2006). Resourcesat-1 data of 2004–2013 time periods have been used for monitoring and assessment of forest fires and the area has been extracted for a decade (Saranya et al., 2014). The statistics were further extracted for estimating emissions for the protected area. In the early 1990s, global biomass burning has become a major perturbation to atmospheric chemistry having an impact on 3
the earth's climate (Levine, 1991 and 1995). Today’s global biomass burning contributes to about 50% of the total direct CO emissions (Petron et al., 2004) and 15% of the surface NOx emissions (IPCC, 2001). Van der werf et al. (2006) has reported global average biomass burning estimation of 2.5Pg C yr-1 over 1997-2004. Mieville et al. (2010) estimated historical biomass burning as ~7400 CO2 Tg yr-1 in the 1970s and increased emission rate as ~9,950 CO2Tg yr-1 in 1980s. With respect to the area and amount of biomass burnt in India, the study by Srivastava and Garg (2013) reported that CO2 emissions for different types of forest ranged from 74.95 Tg to 123.84 Tg over five time periods (2003, 2005, 2007, 2009 and 2010). Globally, Man and Biosphere programme launched in 1971 calls for international scientific cooperation for nature conservation (http://www.unesco.org/). Subsequently, the idea of Biosphere Reserve was introduced for the conservation of large wildlife areas in their present state (UNESCO, 2008). It is not clear whether all Protected Areas are effectively protected as there is a little research comparing ecological degradation before and after the protected areas were established (Liu et al., 2001). The government of India has established 17 Biosphere Reserves (Palni et al., 2012). There is no geospatial data available on the extent of the fire, such as burnt area and frequency in Biosphere Reserves of India to highlight the threat of forest fires for the conservation prioritization. Comprehensive information on the conservation effectiveness of Protected Areas is inadequate and must be available for conservation planning. The present work of estimating carbon emissions from forest fires has been taken up for Similipal Biosphere Reserve (SBR) to assess the amount of trace gas releasing at decadal scale (2004 to 2013).
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Study Area Similipal is the only biosphere reserve of the northern Eastern Ghats, situated in Mayurbhanj district of Odisha (Fig. 1). It lies between 21 28' to 22 15' N latitude and 86 03' to 86 37' E longitude. The government of India declared Similipal as a biosphere reserve (5569 km2) due to its rich biodiversity and natural heritage on 22nd June 1994.The hills, with their innumerable crests and valleys interspersed with countless streams and rivers, exhibit a great degree of topographic variation, ranging from 200 to 1165 m above sea level. The mean annual rainfall varies from 1200mm to 2000 mm. A range of 9°C to 33.5°C temperature is observed in Similipal. About 1276 species of vascular plants have been recorded from the area including 60 species of ferns, 92 species of orchids and two gymnosperms (Saxena and Brahmam, 1989; Bahali et al., 1998). SBR was brought into the Man and Biosphere Programme of UNESCO in May 2009 (Palni et al., 2012).
5
Fig.1 Location map of Similipal Biosphere Reserve Materials and Methods The present study has been carried out from the forest burnt extraction in SBR. Emission of trace gases such as CO2, CO, CH4, NOx and N2O has been calculated to the fire burnt area. Forest fire analysis SBR is distributed with tropical forests of semi-evergreen, Moist Deciduous, Dry deciduous, high level-Sal, low-level Sal and Riparian types. SBR is considered as a fire prone area as it was 6
observed under fire every year. Forest fire analysis has been carried out using AWiFS and IRS P6 LISSIII satellite datasets to find out the temporal trends in every year (Saranya et al., 2014) The area statistics reported for each year is based on the extent of forest burnt area as existing in the date of IRS imagery used. The total area affected under forest fire has been estimated as 860.9 km2 (23.7%) in 2004, 418 km2 (11.5%) in 2005, 902.5 km2 (24.8%) in 2006, 855.3 km2 (23.5%) in 2007, 653.6 km2 (18%) in 2008, 1,014.7 km2 (27.9%) in 2009, 594.9 km2 (16.4%) in 2010, 592.8 km2 (16.3%) in 2011, 982.2 km2 (27%) in 2012, and 508.2 km2 (14%) in 2013 (Saranya et al., 2014) (Fig. 2).Emissions were calculated for each vegetation type as “the amount of carbon emission releasing per unit area under burnt”.
Fig. 2. Classification map of forest-burnt area (2004–2013) in Similipal Biosphere Reserve 7
During our field visit, the site (Upper Barakmuda) has been observed under fire. The fire affected area observed in AWiFS image after field visit was represented in Fig 3.
Fig. 3. Image showing forest fire in AWiFS Satellite data and fire events captured in onsite location. IRS P6 AWiFS Image with the Short wave Infrared, Near Infrared and Red band combination highlights the active fire pixels and burnt area pixels. a. Fire observed in the study area during the field visit b. Image of smoke emitting from the burnt area c. Post fire signature captured in the study area 8
Calculation of Emissions The burnt area of Forest, scrub and grassland are typically estimated from the area burned, fuel load and combustion efficiency, along with appropriate emission factors. To calculate emissions, the forest burnt area observed in the study area for a decade is taken into consideration. The parameters considered for the estimation of emissions are; the amount of land area burned, the amount of fuel load (emission ratio), Burning efficiency and the emission factor for the gas (smoke) emitted. For the calculation of emissions following equation has been considered (Seiler and Crutzen, 1980).
ε=Α×Β×β×ΕF Where ε is the emissions (CO2 in grams), A is the total land area burned (m2), B is the Average biomass/fuel load (kg/dry matter/m2), β is the Burning efficiency of above ground biomass and EF is emission factor (mass of species per mass of dry matter burned in g/kg units). The emission factor for carbon emissions from forest fire for different vegetation types was derived from (Andrea and Merlet 1998, 2001) Table 1. For the tropical forests of SBR, the values of 4.76, 2
3.64, 2.7, 2.94 kg dry matter/m for Closed to open semi-evergreen forest, Closed deciduous forest, Open deciduous forest, Mosaic forest/grassland/scrub/savannah have been used (IPCC 2006). Badarinath and Prasad (2011) have used combustion efficiency of 40% and they expected that this value as a conservative estimate. Srivastava and Garg (2013) have used combustion efficiency of 25%, 85% and 95% for forest, scrub and grassland respectively. The combustion efficiency of 25% has been applied for SBR to estimate carbon emissions. 9
Table 1.Emission factors used for different vegetation types in g species per kg dry matter burned (Tropical/subtropical) Trace gas
Tropical Forest: Ground Fire
Grassland, Savannah and Scrub
CO2
1580
1613
CO
104
65
CH4
6.8
2.3
N2O
0.2
0.21
NOx
1.6
3.9
In the present study, when the emission factors were given in a direct estimation of the selected data, the values were converted into other units to generate appropriate emissions for the type of forest fire. In this regard, the emission factors were multiplied with the appropriate conversion factors and the units were set to the range of equation and thus calculated for different forest types such as Semi-evergreen, moist deciduous, dry deciduous, Sal forests, scrub, savannah and grasslands represented in Table 2. Table 2. Areal extent of vegetation types in SBR Sl.no
Vegetation type
Area(km2)
% of area
1
Semi-evergreen
223.94
4.0
2
Moist Deciduous
2031.66
36.5
3
Dry Deciduous
586.06
10.5
4
Low Level Sal
258.54
4.6
5
High Level Sal
32.28
0.6
6
Riparian forest
3.17
0.1
7
Tree savannah
18.69
0.3
8
Shrub savannah
8.75
0.2 10
Total forest
3163.08
56.8
486.37
8.7
9
Scrub
10
Plantations
2.28
0.0
11
Grassland
3.17
0.1
12
Orchards
74.89
1.3
13
Agriculture
1733.12
31.1
14
Barren land
12.18
0.2
15
Water
63.89
1.1
16
Settlements
28.55
0.5
17
Mining
1.07
0.0
Total non-forest
2405.54
43.2
Grand total
5568.62
100.0
Results and Discussion Fire incidences are more during March to May due to high temperature, air humidity and low fuel moisture which contribute to increased emissions. Therefore, fire analysis will be done during these months. During the study, the deciduous forest was recorded under maximum CO2 emission of about 76.3%. Emissions were observed high during 2009 since it is the warmest year. About, 1.58 Tg CO2 yr-1 was noted in 2009 followed by 2012 1.57 Tg CO2 yr-1. Estimation of carbon emissions in SBR reveals that total of 12.68 Tg of CO2 was emitted for a decade. Annually, 1.26 Tg CO2 yr-1 was recorded during the study. The Dense forest is contributing major emissions since; Similipal is predominant with the dense type of forest (Table 3). Among different forests, deciduous type of forest contributes about 76.3% of carbon emissions over a decade. The amount of emission CO, CH4, N2O and NOx released from 2000 to 2004 has also been calculated in the study. 11
Table. 3 Areal extent of type wise CO2 emissions produced from 2004 to 2013 (CO2 Tg yr-1) % of Vegetation type
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
Total
area
Semi-evergreen
0.04
0.01
0.05
0.04
0.04
0.07
0.02
0.00
0.04
0.00
0.30
2.4
Dense moist deciduous
0.40
0.21
0.49
0.60
0.39
0.62
0.31
0.33
0.52
0.23
4.10
32.3
Open moist deciduous
0.11
0.07
0.12
0.07
0.09
0.12
0.10
0.11
0.15
0.09
1.02
8.1
Dense dry deciduous
0.31
0.31
0.31
0.31
0.31
0.31
0.31
0.31
0.31
0.31
3.06
24.1
Open dry deciduous
0.15
0.14
0.15
0.14
0.15
0.15
0.15
0.16
0.15
0.15
1.49
11.8
Dense low level Sal
0.03
0.03
0.03
0.06
0.01
0.05
0.03
0.01
0.04
0.01
0.29
2.3
Open low level Sal
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.02
0.01
0.12
0.9
Dense high level Sal
0.01
0.00
0.02
0.02
0.00
0.03
0.01
0.01
0.01
0.00
0.11
0.9
Open high level Sal
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.1
Scrub
0.19
0.09
0.27
0.14
0.09
0.18
0.11
0.14
0.32
0.12
1.64
13.0
Grasslands
0.00
0.00
0.01
0.01
0.01
0.00
0.01
0.01
0.00
0.00
0.05
0.4
Savannah
0.03
0.07
0.04
0.06
0.07
0.03
0.05
0.06
0.03
0.06
0.49
3.8
Grand Total
1.28
0.93
1.49
1.45
1.16
1.58
1.10
1.15
1.57
0.97
12.68
100
The mean of carbon dioxide emissions from 2004 to 2013 in the study area has been calculated and represented in (Fig. 4). Similarly, emissions have been estimated for each forest and density type of SBR (Fig 5). It was observed that dense types of forests are contributing to release more emissions (Table 4, Fig. 6). As compared to open forests, dense forests have more quantity of fuel that leads to high biomass burning and consequently high carbon emissions. In this context, monitoring of fires is critical for long-term conservation management of dense forest which is predominantly distributed throughout the reserve. Davis et al. (1999) from his previous work had reported that increasing canopy cover favor high tree species richness and reduced competition from grasses. 12
0.20
Mean of CO2 emitted in Tg
0.18 0.16 0.14 0.12 0.10
0.08 0.06 0.04 0.02 0.00
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
Fig.4. Mean (±SD) of CO2 emissions (Tg yr-1) from 2004 to 2013 35.00 30.00
% of CO2 emitted
25.00 20.00 15.00 10.00 5.00 0.00
Fig. 5.Percentage of CO2 (Tg yr-1) emitted from different forest types
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Table 4. The amount of CO2 (Tg yr-1) emitted from Dense and Open forest Year 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Open forest 0.28 0.22 0.29 0.23 0.24 0.29 0.26 0.28 0.32 0.25
Dense forest 0.77 0.55 0.89 1.02 0.75 1.07 0.68 0.66 0.91 0.55
Total 1.05 0.77 1.18 1.25 0.99 1.36 0.94 0.94 1.23 0.80
14.0
12.0
% of CO2 emissions
10.0 8.0 6.0 4.0 2.0 0.0
2004
2005
2006
2007
Open forest
2008
2009
2010
2011
2012
2013
Dense forest
Fig. 6. Percentage of CO2 (Tg yr-1) emitted from dense and open forests Along with CO2, other trace gases viz CO, CH4, N2O, and NOx have been analysed for different zones of Similipal and the results show that buffer zone is releasing 448.67 CO Gg yr-1, 27.96 Gg yr-1 CH4, 8.95 Gg yr-1 NOx and 0.92 Gg yr-1 N2 O followed by core zone at 152.52 CO Gg yr-1, 14
9.83 Gg yr-1 CH4, 2.56 Gg yr-1 NOx , 0.3 Gg yr-1 N2O and transition zone with 95.71 CO Gg yr-1 , 5.1 Gg yr -1 CH4, 3.2 Gg yr-1 NOx and 0.23 Gg yr-1 N2O over a decade (Table 5). This indicates that the core and buffer zones of Similipal need a strict conservation management in controlling fire. Table 5. The amount of carbon emissions emitted from different zones of SBR (CO2 in Tg yr-1 and other trace gases in Gg yr -1)
Transition
Buffer
Core
Trace gases
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
Total
CO2
0.30
0.11
0.30
0.33
0.21
0.47
0.17
0.10
0.28
0.09
2.36
CO
19.36
7.21
19.24
21.01 13.82 30.59 10.61
6.58
18.21
5.88
152.52
CH4
1.26
0.46
1.24
1.35
0.89
1.97
0.68
0.42
1.18
0.38
9.83
N2O
0.04
0.01
0.04
0.04
0.03
0.06
0.02
0.01
0.04
0.01
0.30
NOx
0.31
0.12
0.32
0.35
0.23
0.52
0.19
0.12
0.30
0.10
2.56
CO2
0.82
0.40
0.86
0.81
0.68
0.91
0.60
0.65
0.98
0.56
7.26
CO
50.93
24.83
52.78
50.71 42.41 56.06 36.59 40.27 59.87 34.21 448.67
CH4
3.17
1.55
3.28
3.20
2.67
3.50
2.26
2.50
3.70
2.12
27.96
N2O
0.10
0.05
0.11
0.10
0.09
0.12
0.08
0.08
0.12
0.07
0.92
NOx
1.02
0.48
1.07
0.95
0.81
1.11
0.75
0.81
1.24
0.69
8.95
CO2
0.21
0.11
0.28
0.19
0.08
0.19
0.13
0.16
0.33
0.12
1.83
CO
11.03
6.04
14.06
10.49
4.62
9.99
7.39
8.73
16.85
6.49
95.71
CH4
0.58
0.33
0.70
0.59
0.26
0.52
0.41
0.48
0.86
0.36
5.10
N2O
0.03
0.01
0.04
0.02
0.01
0.02
0.02
0.02
0.04
0.02
0.23
NOx
0.38
0.19
0.54
0.31
0.14
0.35
0.22
0.26
0.62
0.20
3.20
The results from the study show that deciduous type of forest contributing major emissions from forest fires among the other. Dense types of forest are contributing a major amount of emissions (Table 6). The Dense moist deciduous forest has emitted 269.56 Gg of CO yr -1,17.63 Gg CH4
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yr-1, 4.15 Gg NOx yr-1 and 0.52 Gg N2O yr-1 followed by Dense Dry deciduous 201.1 Gg of CO yr-1, 13.15 Gg CH4 yr-1, 0.39 Gg N2O yr-1, 3.09 4.15 Gg NOx yr-1 respectively.
Table 6. Emissions of other trace gases emitted for a decade in Gg yr-1 Vegetation type
CO
CH4
N2O
NOx
Semi-evergreen
20.10
1.31
0.04
0.31
Dense Moist deciduous
269.56
17.63
0.52
4.15
Open Moist deciduous
67.40
4.41
0.13
1.04
Dense Dry deciduous
201.10
13.15
0.39
3.09
Open Dry deciduous
98.40
6.43
0.19
1.51
Dense Sal
18.90
1.24
0.04
0.29
Open Sal
7.90
0.52
0.02
0.12
Dense High Level Sal
7.20
0.47
0.01
0.11
Open High Level Sal
0.60
0.04
0
0.01
Scrub
66.20
2.30
0.21
3.97
Grasslands
1.90
0.10
0.01
0.11
Savannah
19.70
0.70
0.06
1.18
The estimates of CO2 emission from previous studies vary significantly due to the use of very coarse resolution satellite data. Venkataraman et al. (2006) has estimated an average of 10,101 km2 of burnt area annually in India based on MODIS 2001-2003 data and reported 49-100 CO2 Tg yr -1 from forest fires. Since each active fire pixel with a spatial resolution of 1 km is considered as burnt pixel, the area estimates derived from such an approach may not be the representative of actual burnt in the field. Badarinath & Prasad (2011) reported about 6.34 CO2Tg yr-1 emissions with an average annual burnt area of about 2414 km2 over seven years in India. The latter study has used SPOT L3JRC product with a resolution of 1 km (Badarinath and 16
Prasad, 2011). In the present study, the total carbon emissions from forest fires in Similipal vary from 0.93 to 1.58 Tg CO2 yr-1 over a decade. The mean annual rate of carbon emissions was observed to be 1.26 Tg CO2 yr-1 for a decade. The increased anthropogenic activities in the past 20 years have led to the substantial rise in atmospheric carbon. From geological studies, it was observed that an amount of concentration of carbon dioxide above 320 ppm last occurred 27 million years ago (Berner 1983). Increased amount of carbon dioxide shows detrimental effects on human health. Reduction in the pH value of blood serum leads to acidosis that causes restlessness and mild hypertension (Robertson 2006).The degree of acidosis affects the metabolism of human physical activity in the form of respiratory disorders, rapid pulse rate, and fatigue. Not only humans, the photosynthetic activity of plants will also be disturbed due to elevated carbon in the atmosphere. The elevated amount of CO2 causes acute heat stress in plants that affect plant growth, closing stomata causing a reduction in primary metabolism. This results in decreasing crop productivity (Ciais et al., 2005). Therefore, reducing emissions are possible through controlling fire and fossil fuel burning. Conclusions The results show that high amount of forest biomass burned over a decade in SBR of India. About, 12.68 Tg CO2 yr-1 has been released for a decade. Deciduous forests are producing 76.3 % of carbon emissions of which 32.8 % is from dense moist deciduous forests followed by dense dry deciduous with 24.1 %. This study helps in understanding the carbon emissions emitting through forest fires in the study area. Zone wise analysis of emissions indicates that buffer and core zones of Similipal emitting more carbonaceous gases rather than transition zone. This states that strict management practices should be followed in mitigating fire for the 17
conservation of biodiversity. This database can be helpful for better management plans towards ecological conservation and strategic planning in Similipal Biosphere Reserve in controlling forest fires. Acknowledgments The work has been carried out under national project “Inventorization and monitoring of biosphere reserves in India using remote sensing and GIS technology,” supported by the Ministry of Environment, Forests and Climate Change, Government of India. The authors are thankful to Dr. V.K. Dadhwal, Director, NRSC, Dr. C.S. Jha, Group Director, Forestry and Ecology Group, NRSC for encouragement and the Chief Wildlife Warden and Field Director, Similipal Biosphere Reserve, Odisha Forest Department for permission and facilities to carry out the field work.
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