Forecasting Turkey's cattle and sheep manure based biomethane potentials till 2026

Biomass and Bioenergy 132 (2020) 105440

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Research paper

Forecasting Turkey’s cattle and sheep manure based biomethane potentials till 2026 Mehmet Melikoglu *, Zeynep Kubra Menekse Department of Chemical Engineering, Gebze Technical University, 41400, Gebze, Kocaeli, Turkey

A R T I C L E I N F O

A B S T R A C T

Keywords: Biomethane Cattle Electricity Sheep Turkey

In this study, Turkey’s cattle and sheep manure based biomethane potentials are forecasted till 2026. Novel to this study, semi-empirical models based on per capita meat consumption and milk production are used to forecast Turkey’s cattle and sheep population. It is estimated that Turkey’s cattle and sheep population in 2026 could reach up to 18.7 and 39.2 million, respectively. At these population levels, Turkey’s cattle and sheep manure based biomethane generation could reach up to 1.99 billion m3 and 0.15 billion m3, respectively. This is equal to a total of nearly 2.14 billion m3 of biomethane in 2026. This amount of biomethane could provide nearly 6,600 GWh of electricity or supply nearly 2.9% of Turkey’s natural gas demand in 2026.

1. Introduction Turkey is an upper-middle-income country located between Asia and Europe [1]. As of 2018, Turkey’s population is over 82 million people with a median age of 32 years [2]. In Turkey, there is a growing demand for red meat and milk due to increasing young population and growing economy [3]. As a result, millions of animals are kept under control for breeding. These animals produce significant amount of manure each day [4]. Consequently, animal husbandries must get rid of huge amounts of manure each day in order to maintain operational hygiene. Animal manure cannot be disposed directly due to sanitation constraints. Ani­ mal manure is mostly stored at or around animal husbandries for fer­ tilizer application [5,6]. However, storage of animal manure at uncontrolled conditions leads to greenhouse gas emissions and create odour/hygiene problems [7–10]. Turkey’s agriculture sector including animal husbandries has a significant share in the country’s greenhouse gas emissions [11]. Therefore, authorities in Turkey must aim to reduce greenhouse gas emissions from manure management and find innova­ tive solutions to tackle this huge problem. Animal manure is a type of biomass. Therefore, it can be bio­ processed for the production of value added products. In that context, biogas can be generated from animal manure via anaerobic digestion (AD) [9,12–16]. When biogas is harnessed from animal manure the leftover called digested substrate or digestate can also be used as a valuable fertilizer or can be further processed for the production of water and fiber products [17,18]. Biogas mostly contains methane (CH4)

and carbon dioxide (CO2) together with small quantities of ammonia (NH3), carbon monoxide (CO), hydrogen (H2), hydrogen sulphide (H2S), nitrogen (N2), and oxygen (O2) [19–22]. Methane or biomethane in biogas is a major greenhouse gas but it is also the main component of natural gas [23,24]. Therefore, controlled biomethane generation from animal manure can solve the odour and health problems associated with untreated manure, reduce uncontrolled greenhouse gas emissions, generate energy and result in producing organic fertilizers [25–30]. As of today, controlled biogas generation from animal manure is a well-established technology. Biogas can be produced from animal manure by using an anaerobic digester at farms and animal husbandries [31]. Farm based digesters are mostly large tanks, where manure and bedding material are put together for harnessing biogas under anaerobic conditions [32]. Also, manure ponds/lagoons can be covered to harness biogas [32]. As a result, digester design is an important factor that af­ fects technical and economic feasibility of biogas processes [33]. Yet, the amount of biogas (generated) mostly depends on the type of animal manure management [34]. Cattle (or other large ruminant’s), sheep (or other small ruminant’s), chicken and pig manure can all be used for harnessing biogas at controlled conditions. Therefore, feasibility of biogas generation in Turkey from different types of animal manure must be analysed in detail. In Turkey, there has been a keen interest on utilisation of renewable energy sources for power generation [35,36]. This is mostly related to the country’s ambitious Vision 2023 energy targets, which aim to supply 30% of the country’s energy demand from renewable energy sources by

* Corresponding author. E-mail address: [email protected] (M. Melikoglu). https://doi.org/10.1016/j.biombioe.2019.105440 Received 17 April 2019; Received in revised form 28 November 2019; Accepted 29 November 2019 Available online 7 December 2019 0961-9534/© 2019 Elsevier Ltd. All rights reserved.

M. Melikoglu and Z.K. Menekse

Biomass and Bioenergy 132 (2020) 105440

the year 2023 [37,38]. The share of biomass in Turkey’s Vision 2023 energy targets is adequate at the moment. To be specific, nearly 2,000 MW of installed capacity is aimed for biomass based power plants [39, 40]. Yet, there is no specific target for manure based biogas generation in the Vision 2023 agenda [41,42]. It is envisaged that animal manure based biomethane generation can have an important role in Turkey’s renewable energy future [35,39,41]. However, information about this topic is scarce in the published literature and capacity build-up is at early stages of development. Therefore, Turkey’s manure based bio­ methane generation potentials must be accurately forecasted for the use of academics, animal farmers, researchers and policy planners. As a result, the aim of this study is to forecast Turkey’s biomethane and electricity generation potentials from cattle and sheep manure be­ tween 2018 and 2026. Pig and poultry based estimates are not made because consumption of pork is very limited in Turkey and a sound forecasting model for poultry population cannot be found from the literature. Novel to this study, biomethane generation forecasts are based on red meat consumption and milk production originated animal population projections.

However, an up to date global review that provides average values for fresh manure yield per animal per day (kg/day), total solids in different types of animal manure (%), availability factors (%) of different types of animal manure, methane content (%) in biogas generated from different types of animal manure, and methane yield from different types of an­ imal manure (m3/tonne fresh matter) is not found in the published literature. Therefore, such a guide is prepared in this study for the use of academics, animal farmers, researchers and policy planners. The amount of methane that can be generated from animal manure is directly proportional to the amount of bioprocessed raw material, which is animal manure. Therefore, daily fresh manure generation (kg/day per animal) data are found from the literature and summarised in Table 1 [21,43–47]. The total solids content of biomass directly affects biogas and concurrently methane generation. Therefore, data for total solids in different types of animal manure (%) are found from the literature and summarised in Table 2 [18,44,48–56]. The availability factor shows what percentile of the fresh animal manure can be recovered for biogas generation. Therefore, availability factor data for different types of animal manure (%) are found from the literature and summarised in Table 3 [15,57–59]. As can be seen from Table 3, the availability factors can vary from one publication to another. In real life the availability factors should be estimated locally in line with the local breeding conditions for each animal type at [60,61]. Yet, the average values given in this publication could be used in large

2. Data for animal manure based biomass and energy calculations In the literature there are various data about biogas and concurrently biomethane generation from different types of animal manure.

Table 1 Estimation of daily fresh manure production from different animals (kg/day) [21,43–47]. Raw Data

Calculated in this study

Calculated in this study

Source: Livestock type Beef cattlea Dairy cattleb

[43] Total manure (lbs/day/1000-lb animal unit)c 59.1 80.0

Animal Cattle (average)

Fresh animal manure (kg/day) 38.8

Source: Feedlot cattle

[44] Manure production (kg/day)d 27.0

Animal Cattle (average)

Fresh animal manure (kg/day) 27.0

Source: Animal type Large ruminantse Small ruminantse Poultrye

[21] Manure (kg/day) 22.5 1.6 0.045

Animal Large ruminants (average) Small ruminants (average) Poultry (average)

Fresh animal manure (kg/day) 22.5 1.6 0.045

Source: Animal type Cow Sheep Poultry

[45] Manure/Excreta (kg/day) 23 1.3 0.01

Animal Cattle (average) Sheep (average) Poultry (average)

Fresh animal manure (kg/day) 23.0 1.3 0.01

Source:

[46] Manure (kg/day) 3.06 � 2.0

Animal Pig (average)

Fresh animal manure (kg/day) 3.06

[47] Manure (kg/day) 100 pigs produce nearly 2,850 kg of pig manure per day

Animal Pig (average)

Fresh animal manure (kg/day) 2.85

Animal Cattle (average) Sheep (average) Poultry (average) Pig (average)

Fresh animal manure (kg/day) 27.8 1.45 0.0275 2.955

f

Pig

Source: Pig

Average Values

a

High forage diet. Lactating cow. c Manure production is expressed in terms of 1,000 pound animal units. It is assumed that a single dairy cow weighs about 1,400 pounds, or 1.4 animal units; a typical steer weighs about 1,000 pounds or 1 animal unit. d From a 450 kg beast (volatile solids generation: 2.7 kg/day). e Average animal body weights large ruminants: 250 kg, small ruminants: 40 kg, poultry: 1.5 kg. f Pigs weight between 26 kg and 75 kg. b

2

M. Melikoglu and Z.K. Menekse

Biomass and Bioenergy 132 (2020) 105440

Table 2 Total solids, %, in different types of animal manure [18,44,48–56]. Raw Data

Calculated in this study

Calculated in this study

Source: Animal manure type Cattle dung Sheep droppings

[49] Total solids 20% 49%

Animal manure type Cattle (average) Sheep (average)

TS, % 20% 49%

Source: Animal manure type Cow dung (CD) Sheep manure (SM)

[18] TS (g/kg) 121.3 252.8

Animal manure type Cattle (average) Sheep

TS, % 12.1% 25.3%

Source:

[44] Manure production (kg/day)d 27.0

Animal manure type Cattle (average)

TS, % 11.5%

[50] Total solids, % 20%–25%

Animal manure type Poultry (average)

TS, % 22.5%

[51] Total solids, % 25%

Animal manure type Chicken (average)

TS, % 25%

[52] Total solids, % 24.9% � 2.3%

Animal manure type Chicken (average)

TS, % 24.9%

[53] Total solids, % 9%

Animal manure type Pig (average)

TS, % 9%

[54] Total solids, % 6.0%–7.8%

Animal manure type Pig (average)

TS, % 6.9%

[55] g TS∙ ∙ kg¡1 50.4

Animal manure type Pig (average)

TS, % 5.0%

[56] Total Solids, % 5%–7%

Animal manure type Pig (average)

TS, % 6.0%

[48] TS (% fresh weight) 12.6%

Animal manure type Pig (average)

TS, % 12.6%

Animal manure type Cattle (average) Sheep (average) Chicken (average) Pig (average)

TS, % 14.5% 37.2% 24.1% 7.9%

Feedlot cattle Source: Poultry manure Source: Chicken manure (CM) Source: Chicken manure (CM) Source: Pig manure Source: Pig manure Source: Pig manure Source: Pig manure Source: Pig manure

Total solids (kg/day)d 3.1

Average Values

Abbreviations: TS: total solids. d From a 450 kg beast.

scale or nationwide feasibility and forecasting studies. Estimation of methane content in biogas generated from different types of animal manure, %, is a key parameter for energy related cal­ culations. Therefore, data for methane content in biogas generated from different types of animal manure are found from the literature and summarised in Table 4 [18,49,62–69]. Biogas and methane yield are key parameters for energy related calculations. Therefore, data for biogas and methane yield from different types of animal manure are found from the literature and summarised in Table 5 [15,56,70–74]. Finally, average values for fresh manure yield per animal per day (kg/day), total solids in different types of animal manure (%), avail­ ability factors (%) of different types of animal manure, methane content (%) in biogas generated from different types of animal manure, and methane yield from different types of animal manure (m3/tonne fresh

matter) given in Tables 1–5 are summarised in Table 6 for the ease of readers [15,18,21,43–59,62–74]. As a remark, chicken and pig manure based energy estimations are not made in this study due to the afore­ mentioned reasons. However, the data given in Tables 1–6 are for cattle (or other large ruminant’s), sheep (or other small ruminant’s), chicken and pig manure. Therefore, it is believed that the valuable information given in these tables can be used by other researchers for energy and biomass related calculations from different types of animal manure. 3. Modelling and forecasting studies As a remark, biomethane potentials given in this study are theoret­ ical maxima because in real life biomethane separation and upgrading from biogas will encounter some losses [75,76]. The data given in Sec­ tion 2 are used in the calculations given below. 3

Biomass and Bioenergy 132 (2020) 105440

M. Melikoglu and Z.K. Menekse

Table 3 Availability factors for different types of animal manure [15,57–59]. Raw Data Source: Animal manure type Cattle

[57] Availability of waste, % 50%

Small ruminants

13%

Poultry

99%

Source: Animal manure type Cattle

[15] Availability, % Low availability; moderate availability; high availability 50%; 60%; 70%

Pig

70%; 80%; 90%

Poultry

70%; 80%; 90%

Source: Animal manure type Cow (average) Light live stock

Source: Animal manure type Ruminal content, manure, other solids (average)

[58] Availability coefficient 0.14 0.10

[59] Availability (%)

Calculated in this study

Calculated in this study

Animal manure type Cattle (average) Small ruminants (average) Poultry (average)

Availability factor, %a

50%–80%

Raw Data

50% 13% 99%

Animal manure type

Availability factor, %a

Cattle (average) Pig (average) Poultry (average)

60%

Animal manure type Cattle (average) Small ruminant (average)

Availability factor, %a

Animal manure type Cattle (average)

Table 4 Estimation of methane content in biogas generated from different types of ani­ mal manure, % [18,49,62–69].

80%

Source: Animal manure type Cattle dung

[49] Methane content in biogas, % 56%–60%

Sheep droppings

70%–72%

Source: Animal manure type Cow dung (CD) Sheep manure (SM)

[18] Methane content in biogas, % 64%

Source:

[62] Methane content in biogas, % 45%–60%

80% Animal manurea

Source:

14% 10%

Animal manure, farm biogas planta

Availability factor, %a

Source:

65%

Pig manureb Source:

Average Values

Animal manure type Cattle (average) Sheep (average) Pig (average) Poultry (average)

54%

[63] Methane content in biogas, % 55%–58%

[64] Methane content in biogas, % 60%–70% [65] Methane content in biogas, % 62%

Availability factor, %a

Pig manurec

47.3%

Source:

[66] Methane content (%)

80.0%

Pig manure

65.9

89.5%

Source:

[67] Methane content (%)

Swine manure

79%

Source:

[68] Methane content (%)

Manure of laying hens

70%

Source:

[69] CH4 (%)

11.5%

a

The availability factor shows what percentile of the fresh animal manure can be recovered for biogas generation.

3.1. Forecasting Turkey’s cattle and sheep populations till 2026 It is known that cattle and sheep population strongly depend on per capita meat consumption and milk production. Novel to this study, Turkey’s sheep and cattle populations are estimated based on these two parameters. It is known that Turkey is not a closed economy so increased milk and meat consumption may not be met internally but rather through increased imports. Animal population estimations in this study consider this factor. The semi-empirical models generated in this study are used to estimate animal populations based on meat and milk de­ mands. Turkey is not considered as a closed system but accepted as an

Calculated in this study

Calculated in this study

Animal manure type

Methane content in biogas, % 58.0%

Cattle (average) Sheep (average)

71.0%

Animal manure type Cattle (average) Sheep (average)

Methane content in biogas, % 64.0% 54.0%

Animal manure type Animal manure (average)

Animal manure type Animal manure (average)

Animal manure type Pig manure (average) Animal manure type Pig manure (average) Animal manure type Pig manure (average) Animal manure type Pig manure (average)

Animal manure type Chicken manure (average)

Methane content in biogas, % 52.5%

Methane content in biogas, % 56.5%

Methane content in biogas, % 65.0% Methane content in biogas, % 62.0% Methane content in biogas, % 65.9% Methane content in biogas, % 79.0%

Methane content in biogas, % 70.0%

Animal manure type (continued on next page)

4

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Biomass and Bioenergy 132 (2020) 105440

using the statistical functions provided by Microsoft Excel 2010. This is done to generate a business as usual (BAU) scenario (based on data between 2002 and 2017). The y-intercepts and slopes of the BAU models are found as 782.1 and 0.395 for the cattle population and 1041.8 and 0.532 for the sheep population, respectively. A sensitivity analysis is also made on the linear extrapolations and it is found that the coefficient of determination, R2, values for the cattle and sheep population BAU models are 0.8951 and 0.5490, respectively. It is not possible to calcu­ late the percentile error in forecasting models until the desired time arrives and actual data is obtained. However, it is possible to compare forecasts with each other and calculate the deviation. As a result, it is calculated that the cattle and sheep population forecasts generated in this study deviate between 0.44% and 4.67% and 6.92% and 7.91% from the BAU linear models between 2018 and 2026, respectively. Cattle and sheep population projections given in Fig. 1(g) may seem to be linear; however, they are semi-empirical functions generated using Equations (1) and (2). Cattle per capita projections follow a polynomial type growth pattern with decreasing slope and sheep per capita pro­ jections follow an exponential type growth pattern with increasing slope. Overall, cattle population projection has an increasing trend with deceleration and sheep population has an increasing trend with accel­ eration. When compared to the BAU scenario both projections slightly deviate from the linear extrapolations. It is known that cattle and sheep population might not increase only by birth but also via animal imports (live). As a remark, the animal populations given here are potential maxima because if red meat demand is supplied via red meat imports then livestock population would be smaller. Milk production data from OECD are used in livestock population estimations [80]. This is because milk production is directly related to live animal population; whereas milk consumption data can include imported milk. Turkey’s cattle and sheep populations based on per capita milk production data are estimated using Equation (3).

Table 4 (continued ) Raw Data

Pre-treated chicken manure Raw chicken manure

Calculated in this study

61.75%

Chicken manure (average)

51.01%

Average Values

Animal manure type Cattle (average) Sheep (average) Chicken (average) Pig (average)

Calculated in this study Methane content in biogas, % 56.4%

Methane content in biogas, % 57.8% 58.5% 63.2% 68.0%

a

Average animal manure methane content in biogas values are used for estimating cattle and sheep because distinction is not made in the source publications. b Average of various studies from the literature for pig manure. c Co-digestion of acid-treated glycerol with pig manure.

open one with import/export (livestock, meat and milk) options. Therefore, it must be stated that the animal populations given in here are potential maxima because if red meat and milk is imported to supply the internal demand instead of live animals then it is evident that the animal populations won’t rise to the forecasted levels. Turkey’s cattle and sheep populations based on per capita meat consumption data are estimated using Equation (1). Panimal ðtÞ ¼ Phuman ðtÞ � PCApcmc ðtÞ þ εt

(1)

Panimal ðtÞ ¼ Phuman ðtÞ � PCApcmp ðtÞ þ εt

In Equation (1), Panimal(t) is animal population (cattle or sheep) in year t; Phuman(t) is human population in year t; PCApcmc(t) is per capita animal based on per capita meat consumption (beef or sheep meat) in year t; and εt is a “random” error term. Phuman(t) projections between 2018 and 2026 are found from the Turkish Statistical Institute (TurkStat) [77] and shown in Fig. 1(a). PCApcmc(t) is estimated using Equation (2). PCMCðtÞ PCApcmc ðtÞ ¼ PCAðtref Þ � � CCmeat ðtÞ þ εt PCMCðtref Þ

(3)

In Equation (3), Panimal(t) is animal population (cattle or sheep) in year t; Phuman(t) is explained in Equation (1); PCApcmp(t) is per capita animal based on per capita milk production in year t; and εt is a “random” error term. Phuman(t) projections were shown in Fig. 1(a). PCApcmp(t) is estimated using Equation (4). PCApcmp ðtÞ ¼ PCAðtref Þ �

(2)

PCMPðtÞ � CCmilk ðtÞ þ εt PCMPðtref Þ

(4)

In Equation (4), PCApcmp(t) is explained in Equation (3); tref is taken as 2017, PCA(tref) data were estimated in Equation (2); PCMP(t) is per capita milk production in year t; PCMP(tref) is per capita milk production in year tref; CCmilk(t) is a correlation coefficient (annual) between per capita milk production and per capita animal in year t, 1�CCmilk(t)�1; and εt is a “random” error term. In the second methodology, Turkey’s milk production data between 2017 and 2026 are found from the OECD (in thousand tonnes) [80]. Then, using Turkey’s population projection given in Fig. 1(a) Turkey’s per capita milk production projection is calculated and shown in Fig. 2 (a) [77,80,81]. Here, it must be emphasized that OECD’s timeline data for milk production (in thousand tonnes) between 2002 and 2017 are significantly higher than that of Turkey’s Ministry of Agriculture and Forestry’s cow milk production data [80,82]. Therefore, OECD data should include sheep and goat milk data together with cow milk. As a result, a single milk production per capita forecast (Fig. 2(a)) is used for estimating cattle and sheep population between 2018 and 2026. Tur­ key’s per capita cattle and sheep population between 2018 and 2026 is expected to grow parallel to its per capita milk production. The reason for this was explained in the paragraph above Equation (3). Therefore, CCmilk(t) in Equation (4) is assumed as 1.0 for strongest possible agreement between 2018 and 2026.

In Equation (2), PCApcmc(t) is explained in Equation (1); tref is taken as 2017, PCA(tref) is per capita animal population (cattle or sheep) in year tref; PCMC(t) is per capita meat (beef or sheep meat) consumption in year t; PCMC(tref) is per capita meat (beef or sheep meat) consumption in year tref; CCmeat(t) is a correlation coefficient (annual) between per capita meat consumption and per capita animal in year t, 1�CCmeat(t)�1; and εt is a “random” error term. Turkey’s per capita beef (cattle meat) and sheep meat consumption projections, PCMC(t) data, between 2018 and 2026 are found from the Organisation for Economic Co-operation and Development (OECD) and shown in Fig. 1 (c) and (d) [78]. Panimal(t) data between 2002 and 2017 [79] is found from TurkStat and shown in Fig. 1(b). PCA(tref) is calculated using Pan­ imal(t) data and Phuman(t) projections given in Fig. 1(a) for the year 2017 as 0.1973 for cattle and 0.4167 for sheep. CCmeat(t) is assumed as 1.0 for strongest possible agreement between 2018 and 2026. PCApcmc(t) fore­ casts between 2018 and 2026 are generated using Equation (2) and shown in Fig. 1(e) and (f). Finally, Turkey’s cattle and sheep population between 2018 and 2026 are forecasted using Equations (1) and (2) and data given in Fig. 1 (a)–(f) and shown in Fig. 1(g). All the aforemen­ tioned data and results are shown in Fig. 1 [77–79]. In Fig. 1(g), historical Panimal(t) data is also extrapolated till 2026 5

Biomass and Bioenergy 132 (2020) 105440

M. Melikoglu and Z.K. Menekse

Table 5 Biogas and methane yield from different types of animal manure [15,56,70–74]. Raw Data

Calculated in this study

Calculated in this study

Animal manure type Cattle (average) Pig (average) Poultry (average)

Methane yield from fresh animal manure (m3/tonne FM) 26.2

Animal manure type Cattle (average) Sheep or goat (average) Pig (average)

Methane yield from fresh animal manure (m3/tonne FM) 14.6

Poultry (average)

51.2

Animal manure type Cattle (average) Pig (average) Poultry (average)

Methane yield from fresh animal manure (m3/tonne FM)a,b,c 20.1

Methane yield (NL/kg odw) – literature values

Animal manure type

150

Cattle (average) Pig (average)

Methane yield from fresh animal manure (m3/tonne FM)a,b,c calculated from lab þ literature data 39.9

Source: Animal manure type Cattle manure, liquid Cattle manure Pig manure, liquid Poultry manure Laying hens manure

[70] Biomethane specific yield (Nm3/ tonne VS) 240

Biomethane specific yield (Nm3/ tonne FM) 14.1

212 300

38.3 9.7

320 300

106.6 150.0

Source: Animal manure type Cattle manure

[71] Methane yield (m3/tonne VS)

Methane yield (m3/tonne FM)

200

13.6

Dairy cows manure Sheep/goats manure Pigs

230

15.6

200

48.0

300

14.4

Poultry

320

51.2

Source: Animal manure type Cattle manure

[15] Biogas yield based on TS (m3/ tonne) 240

Pig manure Poultry manure

370 400

Source: Animal manure type

[72] Methane yield (NL/kg odw) – lab scale measurement (fresh from the stable) 364 (�14)

Dairy cow, liquid manure Dairy cow, solid manure Fattening cattle, liquid manure Fattening cattle, solid manure Pig, liquid Hen

359 (�14)

250

326 (�2)

150

355 (�3)

250

411 (�3) 259 (�9)

250 290

Source: Animal manure type Cow manure

[73] Biogas potential (Nm3/kgTS) 0.211

Source: Animal manure type Cattle manure

[74] Specific biogas production (Nm3/ kgDM)d 0.20–0.30

Chicken manure

0.31

Pigs manure Sheep manure

0.25–0.50 0.30–0.40

Source: Animal manure type

[74] Specific biogas production (Nm3/ kgDM)d

Buffaloes

0.25

Maximum methane production potential for developing countries (Nm3/kg VS) 0.10

9.7 128.3

48.0 14.4

19.9 60.9

26.1

Poultry (average)

66.2

Animal manure type Cattle (average)

Methane yield from fresh animal manure (m3/tonne FM)a,b,c 17.7

Animal manure type Cattle (average) Poultry (average) Pig (average) Sheep (average)

Methane yield from fresh animal manure (m3/tonne FM)a,b,c 21.0

Animal manure type

Methane yield from fresh animal manure (m3/tonne FM)a,b,c

Cattle (average)

21.0

47.2 20.1 76.2

(continued on next page)

6

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Biomass and Bioenergy 132 (2020) 105440

Table 5 (continued ) Raw Data Cattle

0.25

0.11

Chickens Pigs

0.31 0.37

0.24 0.29

Sheep

0.35

0.13

Source: Animal manure type Cattle (average)

[56] Methane yield (CH4/tonne of manure treated) 0.10–0.20

Average Values

Calculated in this study

Calculated in this study

Poultry (average) Pig (average) Sheep (average)

47.2

Animal manure type Cattle (average)

Methane yield from fresh animal manure (m3/tonne FM) 15.0

Animal manure type Cattle (average) Sheep (average) Poultry (average) Pig (average)

Methane yield from fresh animal manure (m3/tonne FM)a,b,c 22.1

20.1 76.2

62.1 70.8 18.0

3

Abbreviations: VS: volatile solids; FM: fresh matter; NL: normal litre; odw: organic dry weight; Nm : normal cubic metre; DM: dry matter; TS: total solids. a Total solids/fresh animal manure (%) is assumed as 14.5% for cattle manure and 37.2% for sheep manure, 24.1% for poultry manure, and 7.9% for pig manure (average values are taken from Table 2). b Methane % in biogas generated from cattle, sheep, chicken and pig manure are assumed as 57.8, 58.5%, 63.2%, and 68.0% respectively (average values are taken from Table 4). c It is assumed that odw ¼ DM ¼ TS. d Reference [74] is used once for calculating average methane yield values.

Turkey’s per capita cattle and sheep projections based on per capita milk production are generated using Equations (3) and (4) for a period between 2018 and 2026 and shown in Fig. 2(b) and (c). Turkey’s cattle and sheep population between 2018 and 2026 are projected using the per capita cattle and sheep projections and Turkey’s population pro­ jection given in Fig. 1(a). The results are shown in As can be seen from Fig. 2(d). Finally, the results of per capita milk production based modelling studies are given together in Fig. 2 [77,80,81]. As can be seen from Fig. 2(b) and (c), Turkey’s milk production based cattle and sheep per capita projections have a decreasing trend between 2018 and 2026. These decreases are not linear but follow a polynomial trend. Overall, Turkey’s cattle and sheep population projections based on per capita milk production follow a polynomial growth pattern with deceleration. As can be seen from Fig. 2(d) cattle population projections are smaller than the BAU scenario. This is also means that Turkey’s per capita milk production is decreasing much steeper than its per capita population growth. This is an important finding for milk producers and animal farmers. The y-intercepts, slopes and R2 values of the BAU models are same as the meat consumption based parameters given above because the timeline data for the cattle and sheep population does not change. The milk production based models are compared with the BAU models. As a result, it is calculated that the cattle and sheep population forecasts generated in this study deviate between 6.01% and 3.98% and 2.58% and 7.26% from the BAU linear models between 2018 and 2026, respectively.

CH4/tonne fresh animal manure); Amanure is availability factor of fresh animal manure (%); εt is a “random” error term; and there are 365 days in a year. Average values for Gmanure, Ymethane, and Amanure are given in Table 6 and Panimal projections are given in Figs. 2 and 3. Gmethane ðtÞ ¼ Panimal ðtÞ � Gmanure � 365 � Amanure � Ymethane þ εt

(5)

Using Equation (5) and data from Table 6, Figs. 2 and 3, Turkey’s biomethane generation potential from cattle and sheep manure between 2018 and 2026 are forecasted and shown in Fig. 3. As can be seen from this figure, Turkey’s cattle and sheep manure based biomethane gen­ eration could reach up to 1.99 billion m3 and 0.15 billion m3 in 2026, respectively (based on meat consumption based forecasts). This means that a total of nearly 2.14 billion m3 of biomethane can be generated from Turkey’s cattle and sheep manure in 2026. There is no estimate in the literature to check the soundness of this estimate. However, the methodology explained in the next paragraph can be used to approxi­ mately assess the accuracy. Avcioglu and Turker estimated Turkey’s cattle and sheep manure based biogas potential in 2009 as nearly 1.5 billion m3 from a cattle population of nearly 10.8 million and nearly 0.1 billion m3 from sheep population of nearly 26.9 million [57]. Taking average methane content in cattle manure as 57.8% and sheep manure as nearly 58.5% (see Table 6) and based on the calculations of Avcioglu and Turker [57]: Turkey’s biomethane generation potential in 2009 was nearly 0.867 billion m3 from cattle and nearly 0.059 billion m3 from sheep. In the current study, Turkey’s cattle and sheep population in 2026 was esti­ mated at nearly 18.7 and 39.2 million. Thus, as a ballpark figure, based on Avcioglu and Turker’s calculation [57]: Turkey’s biomethane gen­ eration potential in 2026 should be 18.7/10.8 � 0.867 ¼ 1.501 billion m3 from cattle manure and 39.2/26.9 � 0.1 ¼ 0.086 billion m3 from sheep manure. Adding to a total of nearly 1.587 billion m3 biomethane, which is nearly 75% of the current estimate of nearly 2.14 billion m3. According to the United States Environmental Protection Agency (EPA) methane has a global warming (GWP) of 28–36 over 100 years [83]. This means that on average 1 tonnes of CH4 has an emission equivalent to nearly 32 tonnes of CO2. Methane (gas) has a density of

3.2. Forecasting Turkey’s biomethane and electricity generation potentials from cattle and sheep manure till 2026 The following methodology is used for biomethane and electricity related calculations from animal manure. Biomethane generation from different types of animal manure can be calculated using Equation (5). In Equation (5), Gmethane(t) is methane generation per annum (m3 CH4/ year) in year t; Panimal(t) is animal population (animal) in year t; Gmanure is manure generation per animal per day (kg fresh animal manure/ (day∙animal)); Ymethane is methane yield from fresh animal manure (m3 7

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Biomass and Bioenergy 132 (2020) 105440

manure is estimated based on biomethane generation data given in Fig. 4(a) and (b). The results are shown in part (a) of Fig. 4 [87]. As can be seen from this figure, up to 6,600 GWh of electricity (per annum) can be generated from cattle and sheep manure in Turkey till 2026. This is a significant amount and it could be more than 1% of Turkey’s electricity demand in 2026 [37]. Turkey’s natural gas demand projections between 2018 and 2026 were previously calculated by the first author of the current study [87]. It was estimated that Turkey’s natural gas demand in 2026 could reach up to nearly 73.4 billion m3 if Turkey’s Vision 2023 energy targets are realised [87]. These projections [87] are used to calculate animal manure based biomethane’s % supply of Turkey’s natural gas demand. The results are shown in Fig. 4(b). As can be seen from Fig. 4(b), if collected and processed properly Turkey’s cattle and sheep manure based biomethane generation could supply between 2.9% and 3.3% of Turkey’s natural gas demand (per annum) between 2018 and 2026. This is a significant amount and clearly shows the importance of biomethane investments in Turkey. However, as stated above, biomethane genera­ tion from animal manure is a relatively new topic in Turkey. Therefore, future of biomethane generation must be analysed based on the findings from this study.

Table 6 A global guide: Average values for fresh manure yield per animal per day (kg/ day), total solids in different types of animal manure (%), availability factors (%) of different types of animal manure, methane content (%) in biogas generated from different types of animal manure, and methane yield from different types of animal manure (m3/tonne fresh matter) are prepared [15,18,21,43–59,62–74]. Animal

Fresh animal manure (kg/day)

References [21,43–47]

Cattle (average) Sheep (average) Poultry (average) Pig (average)

27.8 1.45 0.0275 2.955

Animal manure type Cattle (average) Sheep (average) Chicken (average) Pig (average)

TS, %

Animal manure type Cattle (average) Sheep (average) Pig (average) Poultry (average)

Availability factor, %

Animal manure type Cattle (average) Sheep (average) Chicken (average) Pig (average)

Methane content in biogas, %

Animal manure type Cattle (average) Sheep (average) Poultry (average) Pig (average)

Methane yield from fresh animal manure (m3/tonne FM) 22.1 62.1 70.8 18.0

14.5% 37.2% 24.1%

[18,44, 48–56]

7.9% [15,57–59]

47.3% 11.5% 80.0% 89.5%

57.8% 58.5% 63.2%

4. Future of biomethane generation from animal manure in Turkey Results obtained in this study clearly showed that there is a great potential for manure based biomethane generation in Turkey. Yet, there are several challenges in front of a widespread integrated bioprocessing. The first challenge is the size of farm based biomethane systems. Animal husbandries are distributed throughout different regions of Turkey. It is often suggested that decentralised generation and utilisation of bio­ methane can speed up the shift towards sustainable development [88]. Therefore, biomethane generation from animal manure can provide various local and regional benefits in Turkey. The herd sizes of animal husbandries in Turkey vary greatly with location (geospatial). They can be grouped as small, mid and large scale operations. Anaerobic digestion of animal manure in small-scale biogas digesters have the following advantages: biomethane harnessing for combined heat and power at farm scale including utilisation at stoves for cooking, lightning, water boiling and utilisation of digestate as fertilizer [89]. Digestate when used as an organic fertilizer reduces the con­ sumption of fossil fuel based fertilizers-pesticides and hence help reducing farm based greenhouse gas emissions [90]. Production of biomethane from animal manure affects soil organic carbon (SOC) cycle of the farms [91]. In a recent study, high carbon input to soil has been observed in the areas involved in biomethane production, however it must be emphasized that this was highly related to the utilisation of digestate [91]. Therefore, animal population based feasibility analysis must be made at farm, region and larger scales before realising any potential investments in Turkey. The economics of centralised large scale and decentralised small scale biomethane generation systems must be well analysed. In a recent study, Lauer and colleagues found that herd size greater than 3,000 cows per farm is required for an economically feasible anaerobic plant oper­ ation; for farms up to 3,600 cows on-farm utilisation of biogas has the highest net present value; for farms larger than 3,600 cows the best economic results are attained via production of biomethane [92]. They also suggested that instead of small size anaerobic digestion plants a higher manure consumption rate could be achieved through co-operative (joint) manure transportation and anaerobic digestion plants [92]. Therefore, techno-economic evaluation of large scale inte­ grated animal husbandries must be carefully made before realising any investments. Another important issue is the composition of animal manure for biomethane generation. It is reported that the composition of biomass (proteins, fats, and carbohydrates) critically affects biomethane yield via

[18,49, 62–69]

68.0% [15,56, 70–74]

Abbreviations: FM: fresh matter; TS: total solids.

nearly 0.657 kg/m3 at 25 � C and 1 atm [84]. As a result, biomethane that can be generated from Turkey’s cattle and sheep manure in 2026 will have a global warming potential of nearly (2.14 � 109 m3 CH4) � (0.657 � 10 3tonne/m3) � (32 tonnes of CO2 equivalent/1 tonne of CH4) ¼ 45.0 million tonnes of CO2 equivalent. Considering that Turkey’s total and agriculture originated greenhouse gas emissions in 2016 were 496.1 and 56.5 million tonnes of CO2 equivalent [85], these calculations clearly show that there is a huge potential in Turkey for greenhouse gas emissions prevention via harnessing biomethane from animal manure under controlled conditions. The amount of electricity that can be generated from biogas can be calculated using Equation (6) [21,86]. In Equation (6), Ebiogas(t) is the amount of electricity generated from biogas per annum (kWh/year) in year t; ECbiogas is the energy content of biogas, which is assumed as 6.0 kWh/m3; Gmethane, total(t) is total methane generation per annum in year t, which is Gmethane(t) cattle and sheep values combined calculated via Equation (5) (m3 CH4/year) (Note: data are from per capita meat con­ sumption based modelling in order to estimate the potential maxima); Rmethane is methane content in biogas (%), average values of which are given in Table 6 as 57.8% for cattle ad 58.5% for sheep; η is the overall efficiency of biogas conversion to electricity in %, which is assumed as 30.0%; and εt is a “random” error term [21,86]. Ebiogas ðtÞ ¼ ECbiogas �

Gmethane;total ðtÞ � η þ εt Rmethane

(6)

Turkey’s electricity generation potential from cattle and sheep 8

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Biomass and Bioenergy 132 (2020) 105440

Fig. 1. All data and calculations are for Turkey (nationwide) (a) Population (people) projection between 2018 and 2026 (b) Livestock (cattle and sheep) population between 2002 and 2017 (c) Beef consumption per capita projection between 2018 and 2026 (d) Sheep meat consumption per capita projection be­ tween 2018 and 2026 (e) Cattle per capita forecast between 2018 and 2026 (based on meat consumption data) (f) Sheep per capita forecast between 2018 and 2026 (based on meat consumption data) (g) Animal (cattle and sheep) population forecast between 2018 and 2026 (based on meat consumption data and linear extrapolation of timeline se­ ries) (h) N/A [77–79].

anaerobic digestion [93]. The optimum biomass composition must be analysed and monitored for higher yields. The carbon-nitrogen C/N ratio must be optimised to enhance methane generation [94]. Animal manures are generally rich in nitrogen; as a result, optimum carbon to nitrogen (C/N) ratio required for anaerobic digestion cannot be attained in some cases [95,96]. In order to solve this problem carbon content of animal manure should be increased before anaerobic digestion [96]. Manure can be digested together with two or more feedstock in a process known as anaerobic co-digestion (AcoD) [97–99]. The use of a co-substrate generally enhances biogas yield due to supply of missing nutrients from the original feedstock [97]. AcoD also helps overcoming drawbacks of single feedstock anaerobic digestion and increase methane yield from biogas plants [99]. AcoD of cattle manure and corn silage is a well-established technology for digestate and biogas production in the European Union (EU) [73]. Crop straw and animal manure are the most widespread feedstock for biogas production [100]. In Denmark, the

main input for biogas generation is manure, which is mixed with different co-substrates in order to enhance the yield [101]. Therefore, co-digestion of animal manure with other agricultural wastes must be well analysed before realising any potential biomethane investments in Turkey. As a remark, the estimates given in this study do not include co-digestion as an option as it is not in the scope of this research. However, when co-digestion technologies are widely adopted then newer estimates should be made based on co-digestate type and bio­ processing technology. Finally, the main motivator behind rapid expansion of biomethane facilities in the EU are supportive government policies and economic subsidies to produce electricity from biomass [102,103]. Therefore, after carrying out detailed feasibility studies, biomethane generation in Turkey should be supported by government incentives and/or interna­ tional funds.

9

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Biomass and Bioenergy 132 (2020) 105440

Fig. 2. All data and calculations are for Turkey (nationwide) (a) Milk production per capita projection between 2018 and 2026 (b) Cattle per capita forecast between 2018 and 2026 (based on milk production data) (c) Sheep per capita forecast between 2018 and 2026 (based on milk production data) (d) Animal (cattle and sheep) population forecast between 2018 and 2026 (based on milk production data) [77,80,81].

Fig. 3. All data and calculations are for Turkey (nationwide) (a) Methane generation forecast from cattle manure between 2018 and 2026 (based on meat con­ sumption data) (b) Methane generation forecast from sheep manure between 2018 and 2026 (based on meat consumption data) (c) Methane generation forecast from cattle manure between 2018 and 2026 (based on milk production data) (d) Methane generation forecast from sheep manure between 2018 and 2026 (based on milk production data).

10

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Biomass and Bioenergy 132 (2020) 105440

Fig. 4. Potential calculations for Turkey (nationwide) (a): Electricity generation from cattle and sheep manure originated biomethane between 2018 and 2026 (methane data from Fig. 3(a) and (b) in order to assess potential maxima) (b) % supply of Turkey’s natural gas demand between 2018 and 2026 (natural gas projections are from Ref. [87] methane data from Fig. 3(a) and (b) in order to assess potential maxima).

5. Conclusion [16]

In this study, it is estimated that Turkey’s cattle and sheep popula­ tion could reach up to 18.7 and 39.2 million in 2026. It is also estimated that up to 2.14 billion m3 of biomethane can be generated from cattle and sheep manure in 2026. This amount of biomethane can supply nearly 2.9% of Turkey’s annual natural gas demand and generate up to 6,600 GWh of electricity in 2026. It is also shown that if collected and processed properly this amount of biomethane at could significantly reduce Turkey’s animal husbandry sector based greenhouse gas emis­ sions. Finally, it is pinpointed that nationwide biomethane generation from animal manure is a new topic for Turkey; therefore, it is suggested that nationwide planning must be carefully made before realising any large scale investments.

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