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Article

Spatial Assessment of Greenhouse Gas Emissions and Eutrophication Potential from Livestock Manure in Bangladesh

by
Zinat Mahal
1,
Helmut Yabar
2,* and
Takeshi Mizunoya
2
1
Degree Programs in Life and Earth Sciences, Graduate School of Science and Technology, Doctoral Program in Environmental Studies, University of Tsukuba, Tsukuba 305-0006, Japan
2
Faculty of Life and Environmental Sciences, University of Tsukuba, Tsukuba 305-0006, Japan
*
Author to whom correspondence should be addressed.
Sustainability 2024, 16(13), 5479; https://doi.org/10.3390/su16135479
Submission received: 14 May 2024 / Revised: 17 June 2024 / Accepted: 25 June 2024 / Published: 27 June 2024
Browse Figures
Review Reports Versions Notes

Abstract

:
Large amounts of livestock manure production in Bangladesh have created a challenge to the environment by increasing greenhouse gas (GHG) emissions and eutrophication potential (EP) risk. Though some studies have identified the impact of manure on emissions, the consequences of manure exploitation on water bodies are very rare. This study investigated the effects of livestock manure on both air and water environments in the regional context of Bangladesh. Mathematical equations were used to assess manure generation, GHG emissions, manure leach-out amount, EP, and geographic information system (GIS) spatial analysis tools were applied to visualize the outcomes of the research. Between 1990 and 2020, the GHG emissions increased from 7451.26 to 13,244.45 kilotons CO2eq, and the amount of manure leach-out to water also increased from 236.49 to 493.75 kilotons over these 30 years of time. In 2023, the study demonstrated that approximately 216.97 million tons of livestock manure were produced in Bangladesh, which accounted for a total GHG emission of 16.61 million tons CO2eq, and about 62.19 million tons of manure leached out to water, which has a total EP of 295.22 kg N-eq/ha/year. This study offers regional pattern emission intensity and eutrophication-susceptible area maps, which indicate the stimulus of livestock manure across Bangladesh. A long-term impact study, distinctive map formation, and eutrophication susceptibility analysis will be helpful for implementing specific policies and strategies to improve the environment of the livestock sector in Bangladesh.

1. Introduction

The increase in pollutants driven by livestock manure has a rising influence on the environment, including the degradation of air and water quality. Therefore, livestock manure management is a critical part of sustainable livestock production, where improper management may cause a potential increase in GHG emissions [1,2] and contamination of water bodies by leaching manure from pastureland and agricultural soil [3,4,5]. In Bangladesh, the livestock sector is considered one of the important agricultural subsectors, and there were about 443.75 million heads of farm animals in 2023, which comprised large ruminants, small ruminants, and poultry [6]. Hence, large numbers of livestock produce large volumes of manure, which may cause both air and water environmental pollution in Bangladesh.
In 2020, livestock accounted for about 51% (46,268.73 kilotons CO2eq) of the total emissions from the agricultural sector in Bangladesh, where livestock manure contributes approximately 11.32% of GHG emissions [7]. More precisely, the GHG emissions from manure management, manure applied to soil, and manure left on pasture represents 2.53%, 1.37%, and 7.49%, respectively, of the total GHG emissions from the agricultural sector in Bangladesh in 2020 [7]. However, poor management of livestock manure, inefficient application of manure to agricultural soil, and manure left on pastures during grazing influence emissions [8]. Livestock manure is an important and complex source of GHG emissions where methane (CH4) and nitrous oxide (N2O) are two main types of emissions [9]. Therefore, the spatial assessment of regional patterns of GHG emissions from different sections and types of livestock manure is necessary for taking specific manure management practices in specific regions that are rarely identified in Bangladesh.
Water pollution by leaching out of livestock manure is another important issue in this riverine country, where eutrophication is considered a common freshwater problem in Bangladesh. Eutrophication potential is defined as the abnormal production of nutrients, particularly nitrogen (N) and phosphorus (P), which may lead to the overdevelopment of biomass (e.g., algae) and its excessive presence in water and soil [10]. The nutrients contained in manure, mainly N and P, can be transported directly or by run-off from the agricultural fields and pastureland to the nearest water bodies and can also leach through the soil into groundwater over time [11,12]. As a result of this, reducing N and P loads is important for controlling and preventing eutrophication in freshwater systems equally [13,14].
Recent studies have identified the importance of describing site-specific characteristics of nutrient fate to improve the accuracy of eutrophication impact assessments, and the site-specific assessment could reveal the spatial difference in eutrophication susceptibility and provide policymakers with an integrated view to mitigate the damaging effects of nutrient inputs [15]. This study used a spatial modeling approach to identify eutrophication potential and eutrophication-susceptible areas at different district levels in Bangladesh. However, reflecting country-specific geographic factors, an in-depth assessment of eutrophication impacts associated with manure application to agricultural soil and manure left on pasture has not been carried out in the regional context of Bangladesh and is also lacking in the global context.
Overall, this research investigated the potential environmental effects of livestock manure in the regional context of Bangladesh. The assessment of GHG emissions, manure nutrients leach-out to water, and eutrophication potential was accomplished by this analysis, which is important for identifying specific and feasible mitigation options and prioritizing policies with national environmental protection goals. Eventually, this study used geographic spatial analysis tools to create regional pattern maps for both air and water pollution situations from existing livestock manure across Bangladesh, which is a very new concept for this country.

2. Materials and Methods

2.1. Data Sources

Data were collected from the Department of Livestock Services of Bangladesh (DLS), Bangladesh Bureau of Statistics (BBS), the Statistics Division of the Food and Agricultural Organization (FAOSTAT), scientific journals, publications, and books related to livestock manure management. The district-wise data for the total livestock population of each type were collected from a survey report performed by DLS and published by the BBS in 2023 [16,17]. Some data like manure generation, GHG emissions, manure leach-out amount, and EP, were generated by mathematical equations that are discussed in specific sections. The GIS spatial data of geographic factors were collected from DIVA [18]. However, prior to spatial analysis, the survey and mathematically generated data were processed to obtain shape file data and analyzed using GIS software (ArcGIS 10.8).
This study considered cattle and buffalo as large animals, sheep and goats as small animals, and chickens and ducks as poultry for the calculation of total livestock manure generation and other indicators (GHG emissions and manure leach-out amount) of this study. These six species are the major livestock species raised in the country [6]. Livestock population growth by type from 2001 to 2023 and the geographic distribution of livestock in 2023 are shown in Figure 1 and Figure 2.

2.2. Review the Impact of Livestock Manure on Air and Water

The long-term impacts of livestock manure on air and water bodies were evaluated using the data from all six types of animals in Bangladesh from 1990 to 2020. This study estimated data related to manure emissions and manure leaching from FAOSTAT “http://www.fao.org/faostat/en/#dat (accessed on 15 December 2023)” and revealed that emissions come from manure management, manure left on pasture, and manure applied to soils, whereas leaching occurs during manure left on pasture and manure applied to soils.

2.3. Assessment of Existing Effects of Livestock Manure

2.3.1. Livestock Manure Generation Estimation

The volume of manure from livestock differs according to the animal type, feeding process, body size, and breeding type [19]. From a literature study, it was found that the average manure volume for large animals, small animals, and poultry was 10–22.5 kg, 1.6–2 kg, and 0.045–0.1 kg per day [19,20,21]. In this study, the amount of manure was estimated to be 10%, 4%, and 3% of the body weight of large animals, small animals, and poultry, respectively [21,22]. However, the average body weight of livestock in Bangladesh is 190 kg (large animals), 20 kg (small animals), and 1.5 kg (poultry) [23]. So, the estimated livestock manure generation per day was 19 kg, 0.8 kg, and 0.045 kg for large animals, small animals, and poultry, respectively.

2.3.2. Assessment of District-Wise GHG Emissions

For estimating the total GHG emission (in kg CO2eq) from livestock manure, this study combined the CH4 and N2O emissions by using Equations (1)–(3).
Total Emissions = CH4 Emissions + N2O Emissions
CH4 Emission = NLDT × EFMT × GPM
where, NLDT = Number of livestock in each district and type
EFMT = Emission factor for CH4 in each type of livestock manure (kg/head/year)
GPM = Global warming potential of CH4 relative to CO2 (25kg CO2 kg−1 CH4) [24].
N2O Emission = NLDT × NET × EFNT × CF × GPN
where, NET = Nitrogen excretion by livestock types (kg N/head/year)
EFNT = Emission factor from N2O in each type of livestock manure (kg N2O-N/kg Nitrogen excretion)
CF = Conversion factor from N2O-N emission to N2O emission (CF = 44/28) [25]
GPN = Global warming potential of N2O relative to CO2 (265kg CO2 kg−1 N2O) [25]
According to the Intergovernmental Panel on Climate Change (IPCC) guidelines (2006), the CH4 and N2O emissions from manure are different based on animal type, age, sex, lactation status, location, manure management systems, temperature, and region of the world, etc. The range of CH4 and N2O emission factors and the data for nitrogen excretion by livestock type used in this study are shown in Table 1.

2.3.3. Assessment of District-Wise Manure Nutrients Leaching Out

Due to the lack of available related data, this study assessed the manure leach-out ratio factor by dividing the total leach-out manure from agricultural and pastureland by the total manure applied to soils and left on pasture using Equation (4). The data for total leach-out manure, manure applied to soil, and manure left on pasture in Bangladesh were estimated from the data provided by FAOSTAT. District-wise, the existing amount of leach-out manure was estimated by multiplying the manure leach-out ratio factor by the total manure generation from livestock in each district using Equation (5). However, the nutrients (N and P) contained in the leach-out manure were also estimated using the average value of the reference range for N and P content in livestock manure (Table 2).
RFL = TML/(MAS + MLP)
where, RFL = Ratio factor for manure leach-out
TML = Total manure that leach-out from agricultural soil and pastureland (kg/year)
MAS = The manure applied to soils (kg/year)
MLP = The manure left on pasture (kg/year)
MLD = NLDT × MPDT × RFL
where, MLD = Manure Leach-out amount in each district (kg/year)
NLDT = Number of livestock in each district and type
MPDT = Manure production in each district and type (kg/heads/year)

2.4. Eutrophication Potential Assessment

For estimating district-wise total eutrophication potential (in kg N-eq) from livestock manure, the manure N2O emissions and manure nutrient (N and P) leaching out were accounted for by using Equation (6). The eutrophication potential characterization factors are given in Table 3.
EP = Σi(mi × EPi)
where, EP = eutrophication potential in kg N-eq
mi = mass (in kg) of inventory flow i,
EPi = kg of nitrogen with the same eutrophication potential as one kg of inventory flow ‘i’

2.5. Eutrophication Susceptibility Analysis

To identify eutrophication-susceptible areas from livestock manure in Bangladesh, three geographic factors (distance from the river, rainfall, and elevation) were combined with the eutrophication potential of the districts. Geographic factors were reclassified as a quantile method and combined by applying the AHP (analytical hierarchy process) tools to determine the comparative weights of these factors. AHP is made up of four major steps: (1) breakdown of a specific issue into some sub-problems or issues, features, and elements; (2) pair-wise comparison of specific elements in a pre-defined mathematical scale; (3) evaluating the consistency of the values given during comparison and (4) calculating the results to obtain a final ranking [34]. AHP is used to determine the values for different criteria in any comparative analysis, where the consistency ratio (CR) is important. If CR is less than 0.10 or 10%, it signifies a strong consistency of the weights among the criteria [35]. The final weighted preferences were calculated (Table 4) and used to analyze eutrophication susceptibility, where the consistency ratio was less than 1.0%.

3. Results

3.1. Impacts on GHG Emissions

The carbon footprint is based on the principal GHG emissions from livestock manure by different sections (manure management, manure applied to soil, manure left on pasture) and emissions categories (CH4 and N2O emissions). The study observed that the carbon footprint of livestock manure showed an increasing trend in production from 1990 to 2020 (Figure 3). In 2020, the annual GHG emissions from livestock manure were more than 13,244 kilotons CO2eq, with 8717 kilotons CO2eq from manure left on pasture, 1591 kilotons CO2eq from manure applied to soils, and 2936 kilotons CO2eq lost in manure management systems (Figure 3a). Total GHG emissions from livestock manure have increased by about 43.74% in 2020 compared to 1990, and this emission consists of 18.57% methane and 81.43% nitrous oxide. Mainly, CH4 and N2O emissions were observed during manure management, whereas only N2O emissions were observed in both manure left on pasture and manure applied to soil cases (Figure 3b). From only manure management systems, the CH4 and N2O emissions were 2459 and 477 kilotons CO2eq, respectively. However, the N2O emissions from manure left on pasture were higher (8717 kilotons CO2eq) than any other type of emissions from manure, which accounted for 65.82% of the total livestock manure emissions in 2020. The long-term trend analysis indicates that N2O emissions from manure have significantly increased from 5554 to 10,785 kilotons CO2eq, which is almost double the emissions in 2020 compared to the value of 1990. CH4 emissions were also increased from 1897 to 2460 kilotons CO2eq respectively in 1990 and 2020.

3.2. Impacts on Water Pollution

When livestock manure accumulates in open sites or agricultural land, it causes surface water pollution by leaching manure. The study observed that livestock manure showed an increasing trend of leaching out to waterbodies from 1990 to 2020 (Figure 4). Total leach-out amount of manure from livestock increased by about 52.11% in 2020 compared to that in 1990. In 2020, about 493.76 kilotons of manure (N content) were lost from the total amount of manure (1645 kilotons) applied to the soil and left on the pasture during grazing. It was found that 17.94% of manure leached when manure was applied to soils, and 82.06% leached from manure left on pasture via water run-off, leading to the pollution of waterways and, ultimately, the rivers of Bangladesh.

3.3. Regional Pattern of GHG Emissions

The carbon footprint of livestock manure was presented by spatial analysis at the district level in Bangladesh. The districts were classified into five categories, from very low to very high, with an equal group interval based on the maximum and minimum values of emissions and emission intensity of livestock manure. Among districts for annual GHG emissions from manure, five districts (Dinajpur, Bogra, Noagaon, Sirajgonj, Mymensingh) were in the very high group, which has 48.13 to 58.53 kilotons CO2eq emissions, whereas the other 9, 8, and 21 districts were offered in the high, moderate, and low groups, respectively (Figure 5a). Correspondingly, six districts (Nilphemari, Rangpur, Joypurhat, Sirajgonj, Kushtia, and Meherpur) had very high intensities (204–250 tons CO2eq/sq. km), and 12 districts (Thakurgaon, Dinajpur, Kurigram, Lalmonirhat, Gaibandha, Bogra, Noagaon, Pabna, Manikganj, Chuadanga, Meherpur and Jhenaidah) have high intensity (157–203 tons CO2eq/sq.km) of emissions from livestock manure of Bangladesh (Figure 5b). However, the rest of the districts had moderate to very low (15–156 tons CO2eq/sq.km) emission intensity.
The detailed spatial analysis in terms of CH4 emission intensity (tons CO2eq/sq.km) and N2O emission intensity (tons CO2eq/sq.km) are shown in Figure 6a,b, respectively. CH4 emission intensity indicated that eight districts (Nilphamari, Rangpur, Gaibandha, Lalmonirhat, Sirajganj, Manikganj, Meherpur, and Kustia) fall under the very high emitting category, while 21 districts fall under the high emitting category, and only four districts (Khagrachari, Rangamati, Bandarban and Khulna) are classified as under very low emitting category (Figure 6a). On the other hand, only three districts (Joypurhat, Kustia, and Meherpur) fell under the very high emission category, ten districts (Nilphemari, Rangpur, Sirajgonj, Lalmonirhat, Gaibandha, Noagaon, Pabna, Manikganj, Chuadanga, and Jhenaidah) fell under the high emission category, and the remaining districts were categorized as moderate to very low in terms of N2O emissions (Figure 6b).
The total GHG emissions from the manure of different livestock categories are presented in Figure 7. This study estimated that total emissions from livestock manure in 2023 were 16,604.92 kilotons CO2eq, with the main share (63.13%) of that emission being emitted by cattle manure, whereas other large ruminant buffaloes contribute only 3.85%. Small ruminant manure has only a 13.97% share of the total emissions, whereas goat manure accounted for 12.25%, and sheep accounted for only 1.72%. Chicken constitutes a major part of the emission from poultry manure, accounting for 15.77%, while duck accounts for merely 3.28% of the total emissions from livestock manure in Bangladesh for the year 2023.
GHG emissions from cattle manure were the highest in Sirajganj, followed by Mymensingh, Dinajpur, Naogaon, Bogra, Pabna, and Chittagang (Figure 7a), whereas emissions from buffalo manure were the highest in Patuakhali district, followed by Bhola, Feni, Sylhet, and Noakhali (Figure 7b). Similarly, emissions from goat manure were highest in Jashore, followed by Naogaon, Rajshahi, Chuadanga, Kustia, and Jhenaidah (Figure 7c), while emissions from sheep manure were the highest in Gaibandha, followed by Naogaon, Bogura, Dinajpur, and Sirajgan (Figure 7d). However, emissions from chicken manure were highest in only one district (Mymensingh), whereas Comilla was in the highest position in terms of emissions from duck manure in 2023 (Figure 7e,f).

3.4. Regional Pattern of Leaching out of Manure

The detailed spatial analysis in terms of manure leach-out to waterbodies (in kilotons) indicated that seven districts (Dinajpur, Naogaon, Bogra, Sirajgang, Pabna, Mymensingh, and Chittagang) fall under the very high manure leaching category of 1847 to 2256 kilotons per year, while 8, 10, 18, and 21 districts were classified as high, moderate, low, and very low emitting categories, respectively (Figure 8a). On the other hand, in case of nutrients (N&P) leach-out amount through manure, only two districts (Mymensing and Comilla) fall under the very high leaching category (235.5 to 286.45 kilotons per year), while Dinajpur, Naogaon and Bogra fall under the high leaching category (184.55 to 235.5 kilotons per year), and rest of the districts were categorized as moderate to very low manure leaching group accordingly (Figure 8b).

3.5. Spatial Distribution of Eutrophication Potential

The eutrophication potential of the districts shown in Figure 9 was estimated based on the amounts of nutrient leach-out and NO2 emissions from livestock manure in Bangladesh. The districts were classified by equal intervals into five categories. The highest eutrophication potential (460–560 kg N-eq/ha/year) is concentrated in the ten districts (Nilphamari, Lalmonirhat, Rangpur, Gaibandha, Joypurhat, Bogra, Shirajgoanj, Manikganj, Kustia and Meherpur) of northern zone in the country (red areas in Figure 8), which has a dense livestock population and receives high nitrogen and phosphorus load from manure leach-out and NO2 emission, leading to a serious threat to the aquatic ecosystem. A relatively high eutrophication potential (360–450 kg N-eq/ha/year) is indicated by deep green color in 19 districts, whereas light green indicates moderate potential for eutrophication threats (260–350 kg N-eq/ha/year) in 18 districts of Bangladesh. Yellow and blue-colored districts are considered to have fewer potential areas compared to the other groups, which have 150–250 kg N-eq/ha/year and 41–140 kg N-eq/ha/year eutrophication potential, respectively (Figure 9).

3.6. Eutrophication Susceptibility

The geographically potential areas for eutrophication were appraised based on three factors: river distance, rainfall, and elevation of the study area. Three separate raster maps (Figure 10) were formed by the quantile reclassification method of GIS spatial tools and united together to obtain the final geographically potential areas for eutrophication risk from livestock manure. Subsequently, geographic factors (Figure 11a) were combined with the intensity of eutrophication potential at the district level (Figure 11b) to obtain a eutrophication susceptibility map (Figure 11c). In this map, the places are classified into five zones for identifying the eutrophication risk from livestock manure in Bangladesh: the most susceptible, highly susceptible, moderately susceptible, marginally susceptible, and low-susceptible areas. The most susceptible areas (red color) have 1597–2221 kg N-eq due to large manure nutrients leach-out together with low elevation allied to easy run-off in water bodies. Due to the riverine country, water networks are connected with sensitive freshwater ecosystems throughout Bangladesh. Relatively higher susceptible areas (deep green colored, 1345–1596 kg N-eq) were observed in the closer sites of most susceptible areas because of the closer river distance to run-off manure nutrients from livestock farms along with higher N2O emissions from manure.
The highest rainfall intensity is mostly in the hilly areas (Panchagarh, Dinajpur, Sylhet, Cox’s Bazar) of the country which has an effect on nutrients leaching out and eutrophication potential. Rainfall emphasizes that nutrients leach out into the water [36,37], and this study also observed that high rainfall intensity enforced the highest susceptibility to eutrophication risk, especially in the northern part of the country. The light green and yellow areas are considered less susceptible compared to the first two groups. However, low susceptibility areas (blue-colored) are found in the hilly region, especially in the Chittagong hill tracts, due to the low number of livestock populations. Since the district-level EP of manure contributes significantly to eutrophication susceptibility analysis, the most susceptible areas are found where manure generation is comparatively higher than in other areas of the country. For that reason, the geographic factors have considerably less effect than livestock manure intensity in obtaining eutrophication-susceptible areas.

4. Discussion

The spatial distribution of GHG emissions and manure leach-out nutrients (N and P) were reviewed according to the divisions of Bangladesh (Table 5). Among divisions, the highest carbon footprint of 3.11 million tons CO2eq (18.72% of the total emission) was estimated from Rajshahi followed by Rangpur (2.91 million tons CO2eq), Khulna (2.53 million tons CO2eq), and Chittagong (2.27 million tons CO2eq) in 2023. Sylhet division had the least share (5.66%) of the total carbon footprint of livestock manure. The variation in emissions and manure leach-out amount was mainly due to the variation in the number and types of livestock populations in different divisions, as shown in Figure 2. For example, although the total livestock population in the Dhaka division is higher than that in Khulna, the total GHG emissions are lower in the Dhaka division compared to Khulna because of the small number of small ruminants (goats).
This study found that widely distributed livestock manure (from manure management systems, agricultural soil application, and pastureland) contributed to higher N2O emissions (11.76 million tons CO2eq) compared to CH4 emissions (4.84 million tons CO2eq), which agrees with the literature [24]. However, many studies have established that livestock manure contributes a small amount of N2O emissions compared to CH4 emissions because it considers only manure management data [8,38]. The diet of livestock can influence GHG emission production when manure is applied to soil. One study found that a corn-based diet has greater carbon dioxide (CO2) but lower N2O emissions than a barley-based diet [39]. Even the way of measuring emissions from different manure management practices like composting, anaerobic digestion, and liquid or solid application to soil also affects GHG emissions production rate [40]. Thus, different features such as manure management practices, housing systems, feedstuffs, and climate conditions might affect the variation of GHG emissions at different district levels in Bangladesh. However, emissions from manure should not be neglected due to the relatively lower spatial emission intensity (112.52 tons CO2eq/sq.km/year) despite the large total emissions amount (16.61 million tons CO2eq), which is similar to the study [38]. Afterwards, the GHG emissions from manure are expected to increase due to the increase in livestock population growth for increasing animal protein demand in the future [41,42].
In the case of water impacts, manure leach-out estimation is very rare in the literature review. This study estimated the amount of manure leaching out along with manure nutrients leaching out to water. Like the emissions, Rajshahi had the highest total manure leach-out to water (11.59 million kilotons), and the Sylhet had the lowest amount of leach-out manure (3.97 kilotons). However, it could be more practical if the leach-out ratio could be identified in specific water bodies for a specific time. Hence, eutrophication potential by districts and eutrophication susceptibility maps will be beneficial to obtain apparent information about water pollution risk by livestock manure in the future. This study estimated the total EP to be 4,356,497,127 kg N-eq from livestock manure in Bangladesh in 2023, which is closer to the results (total marine EP: 209,632,298 kg N-eq and freshwater EP: 2,044,136 kg PO4-eq from agricultural fertilizer application) in a study performed in Thailand [43]. Some studies indicate different numerical values due to the research scale and method selection during the estimation of nutrient loss and EP from different sources. This study found higher values because all generated manure was applied to the field or left on the pasture. One study found that life cycle impact assessment of eutrophication models simply assumed that more nutrients run-off and emissions could have larger impacts on EP [33].
However, the quantified eutrophication potential distribution cannot specifically infer the eutrophication status of specific water bodies, but the results could provide deeper insight than nitrogen and phosphorus fate analysis to designate the water environmental impact and facilitate manure nutrient management [44,45]. Moreover, the introduction of geographic factors has improved the simple estimate and made eutrophication potential results more rational by identifying eutrophication-susceptible areas in the study country.
Although the long-term impacts on GHG emissions to air and manure nutrients leach-out to water from different manure sections were analyzed, it will provide a clearer conception of the variability in the climatic conditions or seasonal variations over time that could be incorporated. This study opens the window to work with the impact of different manure management practices on the environment in future research.

5. Conclusions

Livestock manure production is increasing with the growing population of Bangladesh, which has a negative impact on the environment. This research estimated current emissions and nutrient leach-out amounts from livestock manure at the regional level in Bangladesh using spatially explicit livestock population data, along with the long-term impacts of manure on the environment. Further, eutrophication potential and eutrophication-susceptible areas from existing livestock manure emissions and nutrient leaching were estimated by combining them with geographic factors. This regional pattern of emissions and eutrophication-susceptible areas identification study will guide the adoption of various initiatives to introduce environment-friendly mitigation options and technologies for better manure management in commercial and public-owned livestock farms. Districts with higher emissions may use immediate manure management techniques, such as biogas generation and composting, to reduce air pollution. Similarly, most eutrophication-susceptible areas highlight the need for more urgent actions to reduce water pollution. The environmental effect assessment conducted in this study will contribute to improving the environmental situation in Bangladesh. However, this study found the following:
(a)
Livestock manure has an influence on GHG emissions and causes eutrophication susceptibility in waterbodies.
(b)
GHG emissions and manure leach-out from livestock showed an increasing trend in production from 1990 to 2020. In 2023, the total GHG emissions were 16.61 million tons CO2eq, and the total leach-out manure was 64.19 million tons in Bangladesh.
(c)
GHG emissions from manure were a combination of CH4 emissions (4.84 million tons CO2eq) and N2O emissions (11.76 million tons CO2eq). Leach-out manure nutrients were nitrogen (57.83 million tons) and phosphorus (2.95 million tons).
(d)
The EP by leaching manure nutrients and N2O emission was 295.22 kg N-eq ha−1,, and the spatial distribution of eutrophication susceptibility was also categorized into five groups (low-susceptible areas, marginally susceptible areas, moderately susceptible areas, highly susceptible areas, and most susceptible areas).

Author Contributions

Z.M.: Conceived and designed the experiments; Performed the experiments; Analyzed and interpreted the data; Wrote the paper. H.Y.: Conceived and designed the experiments; Analyzed and interpreted the data; Contributed materials, analysis tools, or information. T.M.: Contributed materials, analysis tools, or data. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in the study are included in the article, and further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Livestock population growth (in million heads) by type in Bangladesh from 2001 to 2023.
Figure 1. Livestock population growth (in million heads) by type in Bangladesh from 2001 to 2023.
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Figure 2. (a) Division-wise distribution of livestock types in Bangladesh; (b) Livestock shares among the divisions of Bangladesh.
Figure 2. (a) Division-wise distribution of livestock types in Bangladesh; (b) Livestock shares among the divisions of Bangladesh.
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Figure 3. (a) Carbon footprints (kilotons CO2eq) of different sections of livestock manure between 1990 and 2020; (b) Carbon footprints (kilotons CO2eq) of different types of emissions from livestock manure between 1990 and 2020 in Bangladesh.
Figure 3. (a) Carbon footprints (kilotons CO2eq) of different sections of livestock manure between 1990 and 2020; (b) Carbon footprints (kilotons CO2eq) of different types of emissions from livestock manure between 1990 and 2020 in Bangladesh.
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Figure 4. Leach-out amounts of manure from agricultural land and pastureland from 1990 to 2020.
Figure 4. Leach-out amounts of manure from agricultural land and pastureland from 1990 to 2020.
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Figure 5. (a) District-wise annual GHG emissions (tons CO2eq) from livestock manure; (b) District-wise emission intensity (tons CO2eq/sq.km) of livestock manure in 2023 across Bangladesh.
Figure 5. (a) District-wise annual GHG emissions (tons CO2eq) from livestock manure; (b) District-wise emission intensity (tons CO2eq/sq.km) of livestock manure in 2023 across Bangladesh.
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Figure 6. (a) Spatial distribution of CH4 emission (tons CO2eq/sq.km) from livestock manure; (b) Spatial distribution of N2O emissions (tons CO2eq/sq.km) from livestock manure in 2023 across Bangladesh.
Figure 6. (a) Spatial distribution of CH4 emission (tons CO2eq/sq.km) from livestock manure; (b) Spatial distribution of N2O emissions (tons CO2eq/sq.km) from livestock manure in 2023 across Bangladesh.
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Figure 7. District-wise annual GHG emissions (tons CO2eq) from six major livestock manure in Bangladesh; (a) Emissions from cattle manure; (b) Emissions from buffalo manure; (c) Emissions from goat manure; (d) Emissions from sheep manure; (e) Emissions from chicken manure; (f) Emissions from duck manure.
Figure 7. District-wise annual GHG emissions (tons CO2eq) from six major livestock manure in Bangladesh; (a) Emissions from cattle manure; (b) Emissions from buffalo manure; (c) Emissions from goat manure; (d) Emissions from sheep manure; (e) Emissions from chicken manure; (f) Emissions from duck manure.
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Figure 8. (a) District-wise livestock manure that leaches to water (tons/year); (b) Manure nutrients that leach to water (tons/year) in 2023.
Figure 8. (a) District-wise livestock manure that leaches to water (tons/year); (b) Manure nutrients that leach to water (tons/year) in 2023.
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Figure 9. District-wise eutrophication potential (kg N-eq/ha/year) of livestock manure in 2023.
Figure 9. District-wise eutrophication potential (kg N-eq/ha/year) of livestock manure in 2023.
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Figure 10. Criteria for eutrophication susceptibility analysis (raster maps); (a) Distance to river; (b) Rainfall; (c) Elevation.
Figure 10. Criteria for eutrophication susceptibility analysis (raster maps); (a) Distance to river; (b) Rainfall; (c) Elevation.
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Figure 11. (c) Eutrophication susceptibility map derived from geographic factors and eutrophication potential of livestock manure in Bangladesh in 2023; (a) Geographic factors; (b) Eutrophication potential of districts in Bangladesh.
Figure 11. (c) Eutrophication susceptibility map derived from geographic factors and eutrophication potential of livestock manure in Bangladesh in 2023; (a) Geographic factors; (b) Eutrophication potential of districts in Bangladesh.
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Table 1. Values (average) used for estimation of total emissions from manure.
Table 1. Values (average) used for estimation of total emissions from manure.
Type of LivestockEFMT (kg/Head/Year) *EFNT (kg N2O-N/kg Nitrogen Excretion) *NE (kg N/Head/Year) **
Large animals2–60.005–0.0250
Small animals0.10–0.220.005–0.0212
Poultry0.012–0.0230.001–0.020.6
* [25]; ** [23].
Table 2. The N and P content in livestock manure.
Table 2. The N and P content in livestock manure.
ComponentsN (%)P (%)References
Large animal manure2.70.624[26]
1.791.68[27]
0.920.33[28]
0.550.90[29]
Small animal manure1.940.99[27]
1.040.28[28]
1.820.59[30]
Poultry manure4.521.68[27]
2.71.32[28]
1.652.40[29]
Table 3. Eutrophication potential characterization factors [31,32,33].
Table 3. Eutrophication potential characterization factors [31,32,33].
1 kg of SubstanceEPi (kg N-eq)
Nitrous Oxides (as N2O to air)0.09
Nitrogen to water (as nitrate, as nitrite)0.275 (0.23, 0.32)
Phosphorus to water7.29
Table 4. Geographic factors and their weights for eutrophication susceptibility analysis.
Table 4. Geographic factors and their weights for eutrophication susceptibility analysis.
CriteriaCommentsWeights
Distance to riverThe closer to the river, the higher the susceptibility. 48.6%
RainfallThe higher the intensity of rainfall, the higher the susceptibility.31.3%
ElevationThe higher elevation has lower susceptibility. 20.1%
Table 5. Division-wise estimates of emissions and nutrient leach-out from manure by 2023.
Table 5. Division-wise estimates of emissions and nutrient leach-out from manure by 2023.
DivisionsTotal Livestock
(in Million)		Manure Generation (Tons)Total Emissions (Tons CO2eq)CH4 Emissions (Tons CO2eq)N2O Emissions (Tons CO2eq)Manure Leach-Out (Tons) Nutrients (NPK) Leach-Out (Tons)
Barisal45.8316,995,264.911,327,327.39441,282.51886,044.895,021,514.02714,723.61
Chittagong74.5729,984,169.282,276,643.84749,585.231,527,058.618,859,286.821,176,343.82
Dhaka63.7528,318,250.852,151,818.26671,869.261,479,949.018,367,065.44999,756.18
Khulna57.3131,122,759.982,529,102.32656,594.941,872,507.399,195,701.06838,454.98
Mymensingh39.3018,447,865.411,361,829.30429,557.36932,271.955,450,707.32626,538.91
Rajshahi68.2539,232,203.663,111,780.65813,419.992,298,360.661,159,1761.71,013,972.18
Rangpur61.8839,424,912.042,905,683.93801,969.932,103,714.0111,648,700.4974,739.39
Sylhet21.5013,448,865.60941,463.53280,367.74661,095.793,973,675.46354,026.89
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Mahal, Z.; Yabar, H.; Mizunoya, T. Spatial Assessment of Greenhouse Gas Emissions and Eutrophication Potential from Livestock Manure in Bangladesh. Sustainability 2024, 16, 5479. https://doi.org/10.3390/su16135479

AMA Style

Mahal Z, Yabar H, Mizunoya T. Spatial Assessment of Greenhouse Gas Emissions and Eutrophication Potential from Livestock Manure in Bangladesh. Sustainability. 2024; 16(13):5479. https://doi.org/10.3390/su16135479

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Mahal, Zinat, Helmut Yabar, and Takeshi Mizunoya. 2024. "Spatial Assessment of Greenhouse Gas Emissions and Eutrophication Potential from Livestock Manure in Bangladesh" Sustainability 16, no. 13: 5479. https://doi.org/10.3390/su16135479

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