Model-based Estimation of Methane Emission from Rice Fields in Bangladesh

Transcription

1 Model-based Estimation of Methane Emission from Rice Fields in Bangladesh Md. Reaz Uddin Khan 1, Abul Fazal M. Saleh 2 1 Centre for Climate Change and Environmental Research (C3ER), BRAC University, Dhaka 1212, Bangladesh 2 Institute of Water and Flood Management (IWFM), Bangladesh University of Engineering and Technology (BUET), Dhaka 1, Bangladesh 1 rezu4es@gmail.com or reaz@bracu.ac.bd; 2 saleh@iwfm.buet.ac.bd Abstract-Methane, a leading heat-trapping greenhouse gas (GHG), is produced primarily as a byproduct of intensive water use in rice cultivation. Though Bangladesh is the fourth-largest rice producing country in the world, its methane emission status has yet to be determined in order to consider future mitigation measures. Hence, this study employed CH4MOD2.5, the most widely-validated computer simulated semi-empirical model and the Intergovernmental Panel on Climate Change (IPCC) proposed simulation model were used in this study for estimation of methane emissions. Three focus group discussions (FGDs) were conducted with farmers of the Gazipur District to collect information for model inputs. Using IPCC methods, the average methane emission of Bangladesh was estimated to reach 171 Gg yr -1. The rate estimated by the CH4MOD2.5 model was 464 Gg yr -1. Cultivar-specific average emissions for BR 11, BRRI dhan 28 and BRRI dhan 29 were , and kg CH 4 ha -1 day -1, respectively. The projected emission values for all types of rice cultivation in Bangladesh conducted by United States Environmental Protection Agency (US- EPA) were 85 and 918 Gg in 25 and 21, respectively. Conversely, according to the IPCC methodology and the CH4MOD2.5 model, those figures were respectively estimated at 187 and 1146 Gg in 25, and at 471 and 496 Gg in 211. Among the three methods, emission estimation was highest according to the IPCC methodology and lowest according to the CH4MOD2.5 model (45% lower than the US-EPA value). The variation is primarily due to the consideration of field level data as CH4MOD2.5 model inputs. In the business as usual scenario, Bangladesh s predicted methane emission is approximately 653 and 96 Gg for 23 and 25, respectively. Keywords- Methane Emission; CH4MOD2.5 Model; IPCC Model; Climate Change I. INTRODUCTION Rice fields are a substantial source of methane, emitting approximately 31,112 Tg (Teragram) globally [1]. Most rice (approximately 57% globally) is grown in irrigated or continuous flooded fields under extremely anaerobic conditions, which stimulate methane production and emission. As a consequence, methane emission from continuously flooded rice fields represents the net methane production in soil by methane producing bacteria (methanogens), methane oxidation within oxic zones of the soil and floodwater produced by methane oxidizing bacteria (methanotrophs) and vertical transport of the gas from soil to the atmosphere [2]. Holzapfel-Pschorn et al reported that the transportation of methane from the soil to the atmosphere is carried out through three distinctive pathways, including transport through plants, ebullition and diffusion [3]. Among the three distinctive pathways, plant-mediated transport is the primary mechanism for methane transport from the soil to the atmosphere which contributes approximately 9% of total methane transportation [4, 5, 6]. In the plant aerenchyma, methane is emitted through micro-pores in the leaf sheath at the lower leaf position, as well as through the stomata in the leaf blades, culms and roots [7, 8]. Hence, the methane transportation rate is regulated by the structure and formation of the plant s aerenchyma as well as by the porosity of the roots. Ebullition occurs at the very beginning of the plant life cycle (the transplanting and vegetative stages), when rice plants have not developed well enough to transport methane. Bubble formation and vertical movement in the bulk of the soil are the main transfer mechanisms of methane, but only account for approximately 1% of the total methane emission during a plant s emitting cycle [9, 1]. However, this only occurs at the surface layer, and its rate is regulated by methane concentration, temperature and soil porosity [11]. Diffusion contributes a tiny portion (around <1%) of methane transportation in total methane emissions [4, 12]. The methane formation process and the pathway by which produced methane is emitted from the soil to the atmosphere are shown in Fig. 1. Agro-climatic factors such as roots, plant litter, organic manure, residues from preceding crops, atmospheric temperature and carbon dioxide, chemical and organic fertilizer, soil texture, water regime and rice cultivars influence the rate of methane emission from paddy fields as methane is the final product of several anaerobic microbial degradations of organic matter (OM). Various studies suggest that the world s rice production must increase from the present 52 million tons to at least 88 million tons by expanding harvested areas by 7% by 225 to meet the demand of the expanding human population [13]. In this regard, extensive rice cultivation may become a potential contributor to the enhancement of global warming. Therefore, initiatives to estimate country-specific contributions to the global methane emissions from paddy fields have already been undertaken by numerous countries around the world, including China, India, Indonesia, Thailand and the Philippines, and which are coordinated by the International Rice Research Institute (IRRI) [14]. Depending on the estimation methods, the emission rate may vary within the same rice fields or within a country. Using the guidelines of IPCC 26, Yen et al. 29 estimated the annual methane emission from irrigated rice fields of the major rice producing countries such as China, India,

2 Bangladesh, Indonesia and Thailand to be 7.41, 3.99,.47, 1.28, and.18 Tg, respectively [15, 16]. However, by using Geographic Information System (GIS) tools and model, Matthews et al. 2 estimated the emission from the irrigated rice fields of China, India, Indonesia, the Philippines and Thailand to be 3.73, 2.14, 1.65,.14 and.18 Tg CH 4 yr -1, respectively [17]. The disparity between estimated emission rates in the same country arises because of using different tools and estimation techniques. Estimation by using country-specific tools or techniques is more suitable than general methods. Model-based estimation is also useful to determine the effects of multiple factors on methane emission, and helps to resolve methodological uncertainty. Fig. 1 Conceptual diagram of methane production and emission pathways from rice plants and soil [3] Bangladesh is the fourth-largest rice producing country in the world, containing 7.4% of the total global rice area [18]. In the context of Bangladesh, methane emission from different water management regimes (e.g., upland, irrigated and rain-fed rice) was measured at 767 Gg (Gigagram) by US-EPA in 199 [19]. Alternatively, for flooded rice cultivation in the same year, the median estimated value was 439 Gg [2]. Both studies were based on IPCC methodology. Those emission rates are no longer valid, due to the expansion of the irrigated rice area in Bangladesh; there is no current estimation of the volume of methane emission from rich fields in Bangladesh. The primary goal of this study was to estimate the status of methane emissions from rice fields in Bangladesh. Additionally, the current study also attempts to predict future methane emissions from irrigated rice fields under the business as usual perspective in Bangladesh. A simulation model was used to calculate the total emissions, and results were compared with those of two methods previously applied to the same inventory. Several Participatory Rural Appraisal (PRA) tools and techniques such as FGD and KII (Key Informants Interview) were applied to collect the input values for the simulation model. A detailed methodology is provided in a further section. The overall findings will aid researchers and policy makers to determine future mitigation options as well as to harmonize the rice cultivation process. II. METHODS Following carbon dioxide, methane stemmed from anthropogenic sources is the most effective GHG in the earth s atmosphere, which contributes approximately 2% of the effects of global warming over the last century [21]. Like other GHGs such as carbon dioxide, nitrous oxide and chlorofluorocarbons, methane has a strong infrared absorption band and traps outgoing long-wave radiation from the surface of the earth, particularly thermal radiation [22]. Though the concentration of methane is less than that of carbon dioxide, methane is a 3 times more competent heat trapper as compared to carbon dioxide [23]. The methane concentration in the atmosphere was estimated at 1.75 parts per million volumes (ppmv) in 2, and due to anthropogenic activities, the emission rate is increasing at a rate of 1% per year [24]. It is projected that the global average temperature will increase by approximately 1 C and 3 C by the years 225 and 21, respectively [21]. Consequently, researchers have paid increasing attention to methane emission as it plays a significant role in concurrent climate change issues. In this study, the CH4MOD2.5 estimation model was used to estimate methane emissions from rice fields in Bangladesh

3 Results are then compared to emission values generated by a model proposed by the IPCC in a 26 inventory of national greenhouse gases. The two calculated values are then compared to US-EPA estimated and projected values. The CH4MOD2.5 model was also employed to estimate projections of future methane emissions from irrigated rice fields in 23 and 25, for the business as usual scenario. A. Calculation of Methane Emission from Rice Fields According to IPCC Methodology An estimation of the methane emissions from rice fields in Bangladesh (both Aman and Boro rice) was calculated for the decade from 2 to 29 by employing Eq. (1), below, as prescribed in the Guidelines for National Greenhouse Gas Inventories [15]. IPCC prescribed the value of the harvested area A i.j.k for a single cropping pattern, representing the total cultivated area for that particular rice in a given year. However, in Bangladesh, the total cultivable land used for Aman rice in a given year is not identical to the total cultivable land dedicated to Boro rice. Therefore, the specific harvested areas for Aman and Boro rice were collected in a given year, and collectively considered to be the annual harvested area for that particular year. Where, CH 4 Rice = Annual methane emissions from rice cultivation, Gg CH 4 yr -1 EF i,j,k = A daily emission factor for i, j and k conditions, kg CH 4 ha -1 day -1 t i,j,k = Cultivation period of rice for i, j and k conditions, day A i,j,k = Annual harvested area of rice for i, j and k conditions, ha yr -1 CH 4 Rice = i,j,k (EF i,j,k t i,j,k A i,j,k 1-6 ) (1) i, j and k = Representations of different ecosystems, water regimes, types and amounts of organic amendments, and other conditions under which CH 4 emissions from rice may vary. To calculate the daily emission factor (EF i,j,k ) IPCC also prescribed Eq. (2), below. The scaling factor SF s.r for soil type and rice cultivar was not considered, because the IPCC did not establish this as a default value. Where, EF i EF c SF w SF p SF o SF s,r = Adjusted daily emission factor for a particular harvested area. EF i = EF c SF w SF p SF o SF s,r (2) = Baseline emission factor for continuously flooded fields without organic amendments. = Scaling factor to account for differences in water regimes during the cultivation period. = Scaling factor to account for differences in water regimes in the pre-season before the cultivation period. = Scaling factor should vary for both type and amount of organic amendment applied. = Scaling factor for soil type, rice cultivar, etc., (not yet available for IPCC source). The scaling factor for organic amendments was calculated according to Eq. (3), as governed by IPCC. As farm manure, the retained rice biomass in the fields from previous crop was considered as OMs for the study. The equation was then further modified in order to calculate the scaling factor of both OMs. Information collected during FGD was used to calculate both the production rate of farm manure and rice straw incorporation into the rice fields for a particular rice cultivation period. SF o = (1 + i ROA i CFOA i ).59 (3) Where, ROA i = Application rate of organic amendment (in dry weight for rice straw and fresh weight for others) ton ha -1. CFOA i = Conversion factor for organic amendments. B. Calculation of Methane Emission from Rice Fields According to the CH4MOD2.5 Model The CH4MOD2.5 model is the most widely-validated computer simulated semi-empirical model to date [25], which simulates methane emissions from rice fields during the rice growing season under either ambient or elevated atmospheric concentrations of CO 2, with multiple intermittent irrigations and drainages [2]. The first hypothesis of this model contended that methanogenic substrates result primarily from rice plants themselves (i.e., roots and exudates) as well as form the addition of OMs into the rice fields, such as the straw of previous crops that is retained in fields after harvesting or the incorporation of organic manure. Another hypothesis was methane produced in the soil enters the atmosphere via two basic pathways i.e. plant mediated transport and bubble ebullition, both of which are controlled by rice growth and development. The diffusion of methane from paddy soil is a function of surface water concentration of CH 4, wind speed and CH 4 supply to the surface water after anaerobic decomposition of OMs [26]. Methane diffusion is a very slow process due to the slow diffusion rate of gaseous CH 4 in a liquid phase. Therefore, the CH4MOD2.5 model doesn t take into account of CH 4 that come to the atmosphere through the diffusion process. The ability to incorporate different water management practices (such as irrigation or drainage), which stimulates elevated concentrations of atmospheric CO 2, and the application of nitrogen fertilizers, are important aspects of the model which make it practical and application-oriented. A flow diagram of the model is presented in Fig

4 CH4 Emission Plant Transport Bubble Transport CH4 Production CH4 Substrates Environmental Influences Rice Plants Exudation Organic Matter Decomposition Soil Texture Soil Eh Soil Temp. Biomass OMN OMS Sand Content Water Management Air Temperature C. Materials and Study Area Fig. 2 Conceptual diagram of CH4MOD2.5 model [2] Aus, Aman and Boro are three major rice seasons in Bangladesh. Their modes of cultivation vary, including time, water requirement, adoption rate and yield. For instance, Aman rice is rain-fed and its cultivation period spans early September to late December depending on land elevation and local practices. Boro rice is irrigation-dependent and cultivated from mid- January to mid-may, also depending on local factors. In contrast, the adoption rate of Aus rice is very poor, and cultivated between late May and mid-august. To ensure food security for the vast population of Bangladesh (approximately 16 million) and to successfully cope with frequent and intense erratic climatic events (i.e., drought or prolonged flooding), the irrigated rice-area of the country is currently expanding. Out of the 8.21 million ha which constitutes the net cultivable area, 5.13 million ha was irrigated in [27]. Considering the intensity of rice cultivation and in order to obtain the necessary model inputs, the Gazipur District was selected as representative of the country s rice status. Gazipur District is located in the Agro-ecological Zone (AEZ) 8 [28]. Hence, all characteristics of AEZ 8 (i.e., altitude, soil ph, soil texture) were considered as the representative values of Bangladesh. Climatic parameters such as the maximum and minimum temperatures and daily precipitation are necessary model inputs. The atmospheric concentration of CO 2 data was taken from NOAA-ESRL [29]. Three individual FGDs were conducted with the local farmers of Gazipur District to collect information about aboveground biomass on the transplanting dates, OM types and application rates, transplanting, harvesting and flooding dates, as shown in Table 1. In this regard, three unions (Kayaltia, Pubail and Kashimpur) were selected from Gazipur Sadar Upazila. The first FGD was conducted in the Vaurait Village of Kayaltia Union. The second and third FGDs were conducted in the Megdubi and Niler Para Villages of the Pubail and Kashimpur Unions, respectively. The number of participants in each of the three sessions was persons. Selection criteria for inclusion in the FGDs included more than 7 years experience with Boro and Aman rice cultivation. A map of the study area is shown in Fig. 3. Fig. 3 Location of the study area

5 TABLE 1(A) INPUT DATA FOR THE MODEL Input parameter Data Data source Transplanting Date (MM/DD) 1/15 FGD Harvest Date (MM/DD) 5/15 FGD Application of Nitrogen Fertilizer (kgn/ha) 12 FGD 5-day mean air temperature before transplant ( C) Bangladesh Meteorological Department (Undated) Flooding date (MM/DD) 1/15 FGD Drainage date (MM/DD) 5/1 FGD Water depth(m).5 FGD All data is related to farming management interface and categorized as transplant/harvest related data TABLE 1(B) INPUT DATA FOR THE MODEL Input Parameter Data Data Source Organic matter application date (MM/DD) 1/8 FGD Grain yield of the previous crop (kg/ha) for BRRI dhan 28 and BRRI dhan FGD OM ratio of previous yield FGD OM Type/Amount (kg/ha dry) Farm Manure /6 FGD OMn (%) 25.3 Model default value OMs (%) 74.6 Model default value All data is related to organic matter incorporation interface of the model. OM ratio of previous yield, OM amount, OM type, OMn and OMs are included in OM type and content category TABLE 1(C) INPUT DATA FOR THE MODEL Input parameter Data Data source Longitude/Latitude/Altitude (m) E/24.3 N/1 [3] Atmospheric concentration of CO 2 ppm for the year [29] Atmospheric concentration of CO 2 ppm for the year [29] Atmospheric concentration of CO 2 ppm for the year [29] Atmospheric concentration of CO 2 ppm for the year [29] Atmospheric concentration of CO 2 ppm for the year [29] Atmospheric concentration of CO 2 ppm for the year [29] Atmospheric concentration of CO 2 ppm for the year [29] Atmospheric concentration of CO 2 ppm for the year [29] Atmospheric concentration of CO 2 ppm for the year [29] Atmospheric concentration of CO 2 ppm for the year [29] Aboveground biomass on transplanting date (kg/ha) for BRRI dhan FGD Aboveground biomass on transplanting date (kg/ha) for BRRI dhan FGD r (instinct growth rate).8 Model default value Cultivar Index (VI) 1 Model default value Grain Yield (kg/ha) for BRRI FGD Grain Yield (kg/ha) for BRRI FGD Soil ph 6.5 [28] Sand (-1).3 [28] Clay and Silt.7 [28] All data is related to general interface of the model. Longitude, latitude, altitude and atmospheric concentration of CO 2 are mentioned as general site parameters. Aboveground biomass on transplanting date, instinct growth rate, cultivar index and grain yield are rice-growth related parameters. In the soil texture parameter, soil ph, sand, clay and silt are included. BRRI dhan 28 and BRRI dhan 29 varieties were used to estimate methane emissions from irrigated rice fields (in the Boro season) due to their adoptions rates (4% and 6%, respectively) on a national scale in a given year [31]. BR 11 variety was used to estimate emissions from rain-fed rice fields (in the Aman season) as it is the most common variety [32]. Aus (premonsoon rice) cultivation was not considered in the study, as its adoption rate is significantly lower than that of the other two rice types. In the year 27, the total areas cultivated for Aman, Boro and Aus rice were approximately 48%, 43% and 8%, respectively [32]. The total cultivation period (t i ) for all varieties was considered to be 12 days with three distinct phases: vegetative (duration is 6 days), reproductive (duration is 3 days) and ripening (duration is 3 days) [33]. The doublecropping pattern (Boro followed by Transplanted Aman i.e. T. Aman) was considered as the representative model for the entire country, and the total annual harvested areas (A i ) for BRRI dhan 28, BRRI dhan 29 and BR 11 were calculated according to their rates of adoption. D. Projection of Future Emissions The CH4MOD2.5 model was used to predict the future methane emission pattern of Bangladesh according to existing cultivation and management practices related to Boro rice. Daily atmospheric temperatures (both maximum and minimum), precipitation and concentration of CO 2 were the only variables in estimated projections; all other parameters remained unchanged. A study was conducted by Climate Change Cell to predict maximum and minimum temperatures and precipitation in the years 23, 231, 25, 251, 27, and 271 according to the PRECIS (Providing Regional Climates for Impacts Studies) model for different grids of Bangladesh by using an SRES (Special Report on Emissions Scenarios) A1B emissions scenario as a model input with the base years from 1961 to 199. The basic characteristics of the A1B emissions scenario include a world of rapid economic growth, a global population that reaches 9 billion in 25 and then declines, the quick

6 spread of new and efficient technologies, a convergent world (i.e., extensive global social and cultural interactions) with a balanced emphasis on all energy sources. The concentration of atmospheric CO 2 for 23 and 25 were collected from Nigel and Osborne, 211 [35]. TABLE 2 PROJECTED MAXIMUM AND MINIMUM TEMPERATURES AND PRECIPITATION DATA FOR THE YEARS 23 AND 25 Month Temp Max ( C) Temp Min ( C) Precipitation (mm/day) Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec Concentration of atmospheric CO 2 [35] In the Year 23 In the year ppm 532 ppm III. RESULTS AND DICUSSION A. Methane Emission Estimation from Rice Fields According to IPCC Guidelines In local practice, rice straw incorporation of previous crops was the major source of organic amendments, which enhance the rate of methane emission. Although local varieties of rice are grown in the Boro and Aman seasons; however, their adoption rates are nominal. Moreover, the plant height of local varieties is lower, so straw incorporation rate for local varieties are not particularly high. Therefore, the contribution of local varieties to annual methane emissions was considered to be negligible. The calculated annual harvested area of Boro rice varieties are shown in Table 3, as dependent on their adoption rates. As shown in Table 3, the adoption rate for all selected varieties have gradually increased; the year 28 is the only exception, due to the devastating tropical cyclone Sidr which struck the low-lying coastal areas of Bangladesh in November 27, and continued toward the North-Northeast portion of the country. As a consequence of the cyclone, heavy rainfall, strong winds and a storm surge were observed, resulting in loss of life and property, and damages to cropland around the country. It was difficult for damaged farmland to regain productivity and for farmers to regain their livelihoods. In some coastal areas, agricultural land was submerged for a portion of time, resulting in a major loss of crop productivity. The cumulative impact was clearly observed in agricultural production in the subsequent year, evidenced by a drastic decrease in the total annual harvested area. IPCC provided the default value of the baseline emission factor (EF c ) for different rice cultivation practices, considered in this study to be 1.3 kg CH 4 ha -1 day -1 for both types of rice cultivation [15]. The selected condition represents no flooded fields for fewer than 18 days prior to rice cultivation, and continuous flooding during the rice cultivation period without organic amendments. Depending on the type of water regime, IPCC prescribed different scaling factors. Therefore, irrigated and continuously flooded water regimes were considered for Boro rice, and a regular rain-fed water regime was considered for Aman rice. Their respective scaling factors (SF w ) were 1 and.28 [15]. The emission estimation represented the entire cultivation period of a double-cropping pattern; therefore, the fields were not flooded pre-season (18 days prior to transplant), and the water regime scaling factor was considered to be equal to 1 [15]. TABLE 3 CALCULATION OF ANNUAL HARVESTED AREA FOR BORO AND AMAN RICE SEASONS Year Annual Boro harvested area ( 1 6 ha) Annual Aman harvested Total harvested area Country total BRRI dhan 28 (4% of total) BRRI dhan 29 (6% of total) area (BR 11) ( 1 6 ha) ( 1 6 ha) Average

7 Methane emission from rice fields is influenced by the rate and type of OM applied. More methane is emitted by organic amendments which contain higher amounts of easily-decomposable carbon. During the FGD, farmers told that, as organic fertilizer, they used the rice straw which remained in their rice fields after harvesting. In practice, 15 to 2 days before transplant, the land is ploughed for preparation. When the plough is applied, the soil texture is broken up, and thus the straw from the previous crop is mixed into the soil and becomes the source of organic amendments for methane emission. The same practice was applied during both rice cultivation seasons. A few of the FGD participants (approximately 3%) use farm manure (cow dung) in addition to rice straw as organic fertilizer, which is also considered in this study. In this context, Eq. (3) is modified into Eq. (4). Therefore, the conversion factors (CFOA) of incorporated straw and farm manure (less than 3 days before cultivation) were considered to be 1 and.14, respectively [15]. SF o = [1 + {(ROA i RS CFOA i RS ) + (ROA i FM CFOA i FM )}].59 (4) Yield rate and the dry weight of rice straw are required to calculate the rate of rice straw incorporation. Yield was considered to be 3.62 t/ha, 4.5 t/ha and 5.5 t/ha for BR 11, BRRI dhan 28 and BRRI dhan 29, respectively, as confirmed by farmers participating in the FGD. The dry weight of straw was calculated according to the Harvest Index (HI), which is the ratio of grain weight vs. total weight (including grain and straw). So, the variety which has high HI indicates low straw yield. The HI values for the selected rice varieties were.42,.42 and.49, respectively [33]. The heights of selected varieties were 115 cm, 9 cm and 95 cm, respectively [36]. Most farmers reported that the rice plants were cut off approximately 18 cm above the ground during harvesting. Thus, 18 cm of rice straw is incorporated as organic amendments during land preparation. The straw yield and straw retained in the fields after harvesting are shown in Table 4. BRRI dhan 28 has the highest straw yield as compared to other two varieties. As the plant height of all three varieties is not identical, the proportion of straw retained in the rice fields is not identical. For instance, approximately 1.24 t/ha and 1.14 t/ha of straw were retained in the rice fields after harvesting BRRI dhan 28 and BRRI dhan 29, respectively, which represents approximately 2% of straw yields for each of the varieties. However, for BR 11, the proportion was approximately 16%, as shown in Table 4. TABLE 4 RATE OF STRAW YIELD AND STRAW RETAINED IN THE FIELDS FOR SELECTED VARIETIES Variety Straw yield t/ha Straw retained in the field after harvesting t/ha BR BRRI dhan BRRI dhan In the cropping pattern which consists of T. Aman rice following by Boro rice, the rice straw retained in the field after Aman harvesting is applied as input organic matter for Boro rice. In that case, the calculated amount of rice straw does not take part in the active decomposition process for methane emissions. The farmers reported that after the harvest of Boro rice, though the calculated amount of rice straw was retained, approximately 7% of the rice straw retained after Boro harvesting disappears in the time interval between Boro harvest and the next Aman harvest (the following year). Therefore, the actual application rate of rice straw was calculated further, and is given in the Table 5. Alternatively, for Boro cultivation, due to the shorter time interval between Aman to the immediate planting of Boro, all of the rice straw that was retained in the fields after harvesting of Aman actively participates in the methane formation process. The average application rate of farm manure was considered as 1.9 t/ha (fresh weight containing water). This practice was nearly identical for all types of rice cultivation. From FGDs it was observed that, the ratio of water to dry matter in the fresh weight of farm manure is 7:3. Therefore, the application rate of farm manure ROA i FM for dry weight consideration was approximately.6 t/ha. By inputting the value of ROA i RS, ROA i FM, CFOA i RS and CFOA i FM in the Eq. (4), the scaling factor for organic amendments of BR 11 was calculated to be 1.33 and of BRRI dhan 28 and that of BRRI dhan 29 was TABLE 5 APPLICATION RATE OF RICE STRAW FOR SELECTED VARIETIES Variety Calculated application rate of rice straw t/ha Actual application rate of rice straw (ROA i RS) t/ha BR BRRI dhan 28 BRRI dhan After considering all of the scaling factors, the methane emissions from different rice cultivars were calculated. For Aman rice (BR 11) the rate is lowest ( Gg CH 4 ha -1 yr -1 ) compared to the other two varieties of Boro rice. This is only because Aman rice is entirely rain-fed and hence, several wetting and drying cycles occur during Aman season. In contrast, Boro rice (both BRRI dhan 28 and BRRI dhan 29) emits more methane ( Gg CH 4 ha -1 yr -1 ) due to the presence of standing water in the rice fields throughout the growing period. By multiplying the annual harvested area (Table 3) by the emission rate, the total methane emissions in Bangladesh from 2 to 29 is estimated and shown in Table 6. An average of approximately 171 Gg of methane was emitted annually from Aman and Boro rice cultivation. The daily rate of methane emission for Boro season ( kg CH 4 ha -1 day -1 ) was three times higher than that of Aman season ( kg CH 4 ha -1 day -1 ). Among the selected three different rice cultivars, the emission rate was highest for BRRI dhan 29 for all studied years (Table 6). Table 6 shows a gradual increase in two seasons, except in 28. The rate of emission in the year 28 was lower compared to 27 because the total cultivable area in 27 was 8.8 million ha whereas in 28 this figure was 7.28 million ha

8 Gg methane Journal of Agricultural Engineering and Biotechnology Nov. 215, Vol. 3 Iss. 4, PP For both types of Boro rice varieties, the calculated emission rates were identical, which is neither theoretically nor practically correct. In the IPCC prescribed model, no value has been assigned for rice cultivar specific scaling factors. However, Table 6 represents higher emission values from BRRI dhan 29 due to its higher adoption rate compared to all other selected varieties. TABLE 6 TOTAL ANNUAL METHANE EMISSION FROM BOTH AMAN AND BORO RICE CULTIVATION Year Annual total emission from BR 11, Gg CH 4 Annual total emission for BRRI dhan 28, Gg CH 4 Annual total emission for BRRI dhan 29, Gg CH 4 National total annual emission, Gg CH Average Emission from Aman rice Emission from Boro rice Fig. 4 Annual methane emission trend B. Methane Emission Estimation from Rice Fields According to the CH4MOD2.5 Model Using all the input parameters depicted the Table 1 (A), (B) and (C) in the CH4MOD2.5 model, the total methane emission values for Bangladesh over the years 2 to 29 were calculated. The contribution to annual methane emissions from the three different rice cultivars is shown in Fig. 5 (a). Model results indicate that emissions from both Aman and Boro rice demonstrate a gradually increasing trend. Over the decade (2 to 29), Bangladesh emitted an average of 464 Gg of methane from its rice fields. The contribution of Aman rice is only 17% (approximately 79 Gg) while the remaining 83% (approximately 385 Gg) of methane emission is contributed by Boro rice cultivation (Fig. 5 (a)). The daily rate of methane emission from the three different rice cultivars is shown in Fig. 5(b). As shown in the figure, the average daily rate of methane emission was highest for BRRI dhan 29 (approximately kg CH 4 ha -1 day -1 ) among the three varieties, as its duration and yield are higher. However, the emission rate for BRRI dhan 28 was 27% lower than ( kg CH 4 ha -1 day -1 ) that of BRRI dhan 29. Though the model is applicable for Boro rice cultivation, emission rate of Aman rice is also required to provide the actual scenario of annual rate of methane emission from Bangladesh. The mean emission rate of the two Boro rice varieties was kg CH 4 ha -1 day -1. The emission ratio of Aman rice to Boro rice was 24%. On that basis, the calculated emission rate of BR 11 rice ( kg CH 4 ha -1 day -1 ) was 7%, which was 78% lower than the rate of BRRI dhan 28 and BRRI dhan 29, respectively (Fig. 5(b)). Year

9 15-Jan 17-Jan 19-Jan 21-Jan 23-Jan 25-Jan 27-Jan 29-Jan 31-Jan 2-Feb 4-Feb 6-Feb 8-Feb 1-Feb 12-Feb 14-Feb 16-Feb 18-Feb 2-Feb 22-Feb 24-Feb 26-Feb 28-Feb 2-Mar 4-Mar 6-Mar 8-Mar 1-Mar 12-Mar 14-Mar 16-Mar 18-Mar 2-Mar 22-Mar 24-Mar 26-Mar 28-Mar 3-Mar 1-Apr 3-Apr 5-Apr 7-Apr 9-Apr 11-Apr 13-Apr 15-Apr 17-Apr 19-Apr 21-Apr 23-Apr 25-Apr 27-Apr 29-Apr 1-May 3-May 5-May 7-May 9-May 11-May 13-May Gg methane Rate of methane emission Journal of Agricultural Engineering and Biotechnology Nov. 215, Vol. 3 Iss. 4, PP BRRI dhan 29 BRRI dhan 28 BR (a) 1 (b) kg CH 4 ha -1 day BR 11 BRRI dhan 28 BRRI dhan 29 Fig. 5(a) Contribution to annual methane emission from three different rice cultivars (b) Daily rate of methane emission from selected three different rice cultivars Among the three distinctive stages of rice growth, the highest rate of methane emission was observed in the reproductive stage. For instance, approximately 42% of the total methane from Boro rice was emitted during the reproductive stage for a particular crop calendar (Fig. 6). This may be due to the ready availability of decomposable matter in the soil during the reproductive stage; high rice plants exudation and crop water demand are high in this period. Additionally, the average daily maximum temperature is also high during this period, which further stimulates the rate of methane emission [37]. The remaining methane is emitted during the ripening stage (approximately 4% of the total) and the vegetative stage (approximately 18% of the total) kg CH 4 ha -1 day Vegetative stage Reproductive stage Ripening stage Rice growth stage Fig. 6 Daily emission pattern of methane from rice fields in a particular cropping year Notes: The given pattern represents BRRI dhan 29. Transplant date was 15 January and harvest began on 14 May. Total duration is 12 days in which the vegetative stage consists of the first 6 days, reproductive stage consists of the next 3 days and the ripening stage consists of the remaining 3 days C. Comparison of Different Rates of Methane Emission According to the US-EPA projection, Bangladesh will contribute an average of 85 Gg and 918 Gg CH 4 annually from rice cultivation (including all types of water regimes) in 25 and 21, respectively [19]. Considering the IPCC 26 methodology, the values estimated in this study are 187 Gg and 1146 Gg in 25 and 29, respectively. In contrast, the CH4MOD2.5 model estimations were 471 Gg and 496 Gg, respectively (Fig. 7). Among the three modes of estimation, emission was highest in IPCC 26 methodology and lowest according to the CH4MOD2.5 model result. The CH4MOD2.5 estimation was approximately 45% lower than that projected by the US-EPA (Fig. 7). US-EPA projection was based on an earlier IPCC method [38] in which all types of water regime including upland, irrigated, rain-fed, and others were taken into consideration. Alternatively, in the CH4MOD2.5 model, only rain-fed and continuously flooded water regimes were considered. In the earlier IPCC method, duration of rice cultivation was not taken into account; rather it considered a certain number of days as a rice cultivation season. Duration of rice cultivation period varies depending upon the type of rice cultivar, water regime, ecosystem, farm management practice, soil type, geo-physical location and climatic condition of the particular country. In US-EPA, it was not clearly mentioned how many days have been considered as the cultivation period for rice in Bangladesh. Another anomaly between IPCC 26 and 1996 method was found for the computation of scaling factor for organic amendments. In IPCC 1996 method, organic amendment was classified into two broad categories: (i) Fermented amendments (e.g., compost, residue of biogas, pits, etc.), and (ii) Non-fermented amendments while in IPCC 26 method all sorts of organic amendments were considered as a single category. This difference in approaches of computing scaling factors for organic amendments creates the differences between the two calculated emissions. In the dose-response table for nonfermented organic amendments [38], six distinctive scaling factors were recommended [39] based on the amount of nonfermented OM applied in the rice fields. However, among those six, the value that was considered for the projection of

10 Gg methane per year Journal of Agricultural Engineering and Biotechnology Nov. 215, Vol. 3 Iss. 4, PP Bangladesh is not addressed in the US-EPA projection report. It is obvious that throughout the rice cultivation period, multiple types of OM are applied on different dates to enhance crop yields. Therefore, in order to obtain a true reflection of methane emission estimation, this dominating factor was taken into account in the other two methods. The possibility of overestimation of methane has been mentioned by the US-EPA as it assumed all irrigated land was continually flooded with no aeration due to limited available information. In reality, farmers prefer to maintain a certain amount of water in the rice field throughout the entire cultivation period, though within this period they usually allow two or three aeration or drainage periods. Therefore, assuming continuously flooded irrigated conditions may also result in the higher emission value from the IPCC [15] and US- EPA projection methods US-EPA Projection Using IPCC Methodology CH4MOD2.5 Fig. 7 Comparison of methane emission rates from three different methods. In the US-EPA projection graph, 29 represents the year 21 D. Future Projection of Methane Emission from Boro Season From the model result, it has been estimated that Bangladesh will emit approximately 653 Gg of methane (213 Gg from BRRI dhan 28 and 44 Gg form BRRI dhan 29) in 23 and approximately 96 Gg (296 Gg from BRRI dhan 28 and 61 Gg form BRRI dhan 29) in 25 if the water management practice remain the same (Fig. 8). The rate of emission will be approximately 39% and 56% higher in 23 and 25, respectively, than the rate of emission in 29. As shown in Fig.8, the higher estimated rate of emission in 25 is due to the higher atmospheric temperature and concentration of atmospheric CO 2 (532 ppm) compared to that in 23 (452 ppm). Several studies have explored the correlation between higher atmospheric temperature under elevated atmospheric CO 2 and the rate of methane emission. According to Schrope et al. 1999, the elevated atmospheric temperature, especially at >35 C [41] with elevated concentration of CO 2 will stimulate plant productivity and methanogenic activity, leading to higher methane emissions from rice fields. Fig. 9 represents the trend line analysis of daily maximum temperatures of three different timelines for the years 23 and 25. The trend line shows that, throughout the whole rice growing season, the average daily maximum temperature projection is higher for the year 25 in comparison with the decade average daily maximum projected temperature in the year 23, except for a few days at the very beginning of the rice growth stage. In the reproductive and ripening stages, a gradual increasing trend is observed for the years 2-29, 23 and 25. In 23 and 25, a few days during the vegetative stage demonstrate an average daily maximum temperature lowers than the decade average value for the years Nonetheless, this does not affect the rate of emission as it relates to the rice growth stages (Fig. 6). The highest emission was observed from BRRI dhan 29 for both years, as compared to BRRI dhan 28. To estimate the projected values, the model-estimated emission rate has been multiplied by the annual harvested area of Boro rice in 29 to represent the projection data for the years 23 and 25. Hence, the future rate will be higher as Bangladesh expands its rice cultivation to enhance food security. In addition, the model is unable to predict HI, yield rate and root exudation rate, which are also foreseen as the driving factors to contribute to future emission rates. Therefore, further research is needed to control and mitigate emission rates in the future

11 Daily Maximum temperature C 15-Jan 17-Jan 19-Jan 21-Jan 23-Jan 25-Jan 27-Jan 29-Jan 31-Jan 2-Feb 4-Feb 6-Feb 8-Feb 1-Feb 12-Feb 14-Feb 16-Feb 18-Feb 2-Feb 22-Feb 24-Feb 26-Feb 28-Feb 2-Mar 4-Mar 6-Mar 8-Mar 1-Mar 12-Mar 14-Mar 16-Mar 18-Mar 2-Mar 22-Mar 24-Mar 26-Mar 28-Mar 3-Mar 1-Apr 3-Apr 5-Apr 7-Apr 9-Apr 11-Apr 13-Apr 15-Apr 17-Apr 19-Apr 21-Apr 23-Apr 25-Apr 27-Apr 29-Apr 1-May 3-May 5-May 7-May 9-May 11-May 13-May Gg methane Journal of Agricultural Engineering and Biotechnology Nov. 215, Vol. 3 Iss. 4, PP Boro season BRRI dhan 29 BRRI dhan Fig. 8 Projection of methane emission from Boro rice fields in 23 and 25 considering business as usual scenario. Business as usual scenario means, if no intervention has been taken into account to regulate methane emission from rice fields Year Projected daily T.max. for the year 25 Projected daily T.max. for the year 23 Daily maximum temperature (decade average 2-29) 5 Vegetative stage Reproductive stage Ripening stage Rice growth stage Fig. 9 Projection of methane emission from Boro rice fields in 23 and 25 considering business as usual scenario IV. CONCLUSIONS In this study, an attempt was made to identify the present status of methane emissions from Bangladesh rice fields, as it is one of the leading rice-producing countries in the world. The total harvested area in terms of Aus cultivation is not significant in Bangladesh, so Boro rice and Aman rice from specific water regimes were the only harvested areas considered in this study. BRRI dhan 28 and BRRI dhan 29 were selected as the Boro rice cultivars and BR 11 was been selected as the Aman rice cultivar for the estimation. The CH4MOD2.5 simulation model was employed to estimate methane emissions from rice fields in Bangladesh. IPCC-prescribed methodology [15] was also used to compare with model results. From the year 2 to 29, Bangladesh rice fields emitted an average of 171 Gg of methane in both seasons [15]. Variety-specific annual emission rates were calculated for BR 11 ( kg CH 4 ha -1 day -1 ) and for BRRI dhan 28 and BRRI dhan 29 ( kg CH 4 ha -1 day -1 ). Furthermore, due to lack of cultivar- specific scaling factors, identical emission rates were observed for BRRI dhan 28 and BRRI dhan 29. However, the model calculated average annual emission rates to be 464 Gg, in which 83% of methane emissions came from Boro rice, and the remaining from Aman rice. The emission rate for BRRI dhan 28 ( kg CH 4 ha - 1 day -1 ) was 27% lower than that of BRRI dhan 29 ( kg CH 4 ha -1 day -1 ). The lowest emission rate was calculated for BR 11 ( kg CH 4 ha -1 day -1 ). According to the IPCC [38] method, the US-EPA tried to project the emission of methane from all sorts of rice cultivars and water regimes in developing countries, which is also taken into consider to compare the values estimated by the other two methods. The projection reported that Bangladesh emitted approximately 85 Gg and 918 Gg of methane in the years 25 and 21, respectively. Conversely, this figure was estimated at 187 Gg and 471 Gg in 25 and 1146 Gg and 496 Gg in 29 according to IPCC 26 methodology and the CH4MOD2.5 simulation model, respectively. If no intervention is undertaken in the future, the country will emit approximately 653 Gg (213 Gg from BRRI dhan 28 and 44 Gg from BRRI dhan 29) and 96 Gg (296 Gg from BRRI dhan 28 and 61 Gg from BRRI dhan 29) of methane from irrigated Boro rice in the years 23 and 25, respectively, under the A1B emission scenario. The annual methane emission rate estimated through this study will help Bangladesh to identify its position in GHG emissions from rice cultivation in comparison to other rice-producing countries around the world. However, the on-field gas chamber primary estimation is highly recommended for Bangladesh. The result of future projections will help policy makers, researchers and relevant authorities take initiatives to investigate mitigation measures and create opportunities for carbon trade-offs

12 REFERENCES [1] K. L. Denman, G. Brasseur, A. Chidthaisong, P. Ciais, P. M. Cox, R. E. Dickinson, D. Hauglustaine, C. Heinze, E. Holland, D. Jacob, U. Lohmann, S. Ramachandran, P. L. da Silve Dias, S. C. Wofsy, and X. Zhang, Couplings between changes in the climate system and biochemistry. Climate change 27: The Physical Science Basis, Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 27. [2] B. H. Xie, Z. X. Zhou, X. H. Zheng, W. Zhang, and J. G. Zhu, Modeling methane emissions from paddy rice fields under elevated atmospheric carbon dioxide conditions. Advances in Atmospheric Sciences, vol. 27, 1-114, 21. [3] A. Holzapfel-Pschorn, R. Conrad, and W. Seiler, Effects of vegetation on the emission of methane from submerged paddy soil. Plant Soil, vol. 92, , [4] H. Schutz, A. Holzapfel-Pschorn, R. Conrad, H. Rennenberg, and W. Seiler, A three years continuous record on the influence of day time, season and fertilizer treatment on methane emission rates from an Italian rice paddy field. Journal of Geophysical Research, vol. 94, , [5] S. C. Tyler, R. S. Bilek, R. L. Sass, and F. M. Fisher, Methane oxidation and pathways of production in a Texas paddy field deduced from measurements of flux, delta-c-13, and delta-d of CH 4. Global Biogeochemical Cycles, vol. 11, , [6] R. Wassmann, R. S. Lantin, and H. U. Neue, Methane emissions from major rice ecosystems in Asia. Nutrient Cycling in Agroecosystems, vol. 58, 398, 2. [7] I. Nouchi, S. Mariko, and K. Aoki, Mechanism of methane transport from the rhizosphere to atmosphere through rice plants. Plant Physiology, vol. 94, 59-66, 199. [8] S. Sandin, Present and future methane emissions from rice fields in Dông NGac commune, Hanoi, Vietnam. Göteborg University, Department of Physical Geography, 41, 25. [9] B. H. Byrenes, E. R. Austin, and B.K. Tays, Methane emission from flooded rice soils and plants under controlled conditions. Soil Biology and Biochemistry, vol. 27, , [1] J. L. Mer, and P. Roger, Production, oxidation and consumption methane by soil: A review. European Journal of Soil Biology, vol. 37, 25-5, 21. [11] C.S. Li, Modeling trace gas emission from agricultural ecosystem. Nutrient Cycling in Agroecosystems, vol. 58, , 2. [12] M. S. Aulakh, R. Wassmann, and H. Rennegberg, Methane emissions from rice field-quantification, mechanism, role of management and mitigation options. Advances in Agronomy, vol. 7, , 21. [13] S.K. Dubey, Methane emission and rice agriculture. Current Science, vol. 81, , 21. [14] H.U. Neue, and R.L. Sass, The budget of methane from rice fields. IG Activities Newsletter, vol. 12, 3-11, [15] IPCC, Guidelines for National Greenhouse Gas Inventories. Agriculture, Forestry and Other Land Use, vol. 4, Chapter 5, , 26. [16] X. Yan, H. Akiyama, K. Yagi, and H. Akimoto, Global estimations of the inventory and mitigation potential of methane emissions from rice cultivation conducted using the 26 Intergovernmental Panel on Climate Change Guidelines. Global Biogeochemical Cycles, vol. 23, GB22, 29. [17] R.B. Matthews, R. Wassmann, J. K. Knox, and L. V. Buendia, Using a crop/soil simulation model and GIS techniques to assess methane emissions from rice fields in Asia. IV. Upscaling to national levels. Nutrient Cycling in Agroecosystems, vol. 58, , 2. [18] IRRI, Rice Knowledge Bank. The Philippines, 29. [19] E. Scheele, Emissions and projections of non-co 2 greenhouse gas from developing countries: United States Environmental Protection Agency, 22. [2] A.U. Ahmed, K. Islam, and M. Reazuddin, An Inventory of Greenhouse Gas Emissions in Bangladesh: Initial Results. Ambio, vol. 25, 3-33, [21] IPCC, Climate change 21: The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Houghton et al., Eds., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 881pp, 21. [22] D.J. Wuebbles, and K. Hayhoe, Atmospheric methane and global change. Earth-Science Reviews, vol. 57, , 22. [23] V. Ramanathan, R.J. Cicerone, H.B. Singh, and J.T. Kiehl, Trace gas trends and their potential role in climate change. Journal of Geophysical Research, vol. 9, , [24] N. N. Purkait, A. K. Saha, D. Sanghamitra, and D. K. Chakrabarty, Behaviour of methane emission from a paddy field of high carbon content. Indian Journal of Radio & Space Physics, vol. 36, 52-58, 27. [25] Y. Huang, W. Zhang, X. Zheng, J. Li, and Y. Yu, Modeling methane emission from rice paddies with various agricultural practices. Journal of Geophysical Research, vol. 19, D8113, 24. [26] D.T. Sebacher, R.C. Hams, and K.B. Bartlett, Methane flux across the air water interface air velocity effects. Tellus, vol. 35, 1-1, [27] BADC, Minor Irrigation Survey Report Ministry of Agriculture, 1-188, 29. [28] BARC, Fertilizer Recommendation Guide. Dhaka, Bangladesh, 25. [29] NOAA-ESRL: Mauna Loa Observatory, [Online]Available at: data.html