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Biogas and biomethane production and usage: technology development, advantages and challenges in europe.

1. Introduction

3. biogas production, 3.1. biogas composition, 3.2. the biogas production: from substrate to biomethane, 3.3. using technologies in biogas and biomethane production, 3.3.1. anaerobic digestion, 3.3.2. thermal and hydrothermal gasification, 3.3.3. process pretreatments, 3.4. biogas puification and upgrading, 3.5. biogas usage, 4. biogas production in europe, 5. discussion, 6. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Pavičić, J.; Novak Mavar, K.; Brkić, V.; Simon, K. Biogas and Biomethane Production and Usage: Technology Development, Advantages and Challenges in Europe. Energies 2022 , 15 , 2940. https://doi.org/10.3390/en15082940

Pavičić J, Novak Mavar K, Brkić V, Simon K. Biogas and Biomethane Production and Usage: Technology Development, Advantages and Challenges in Europe. Energies . 2022; 15(8):2940. https://doi.org/10.3390/en15082940

Pavičić, Josipa, Karolina Novak Mavar, Vladislav Brkić, and Katarina Simon. 2022. "Biogas and Biomethane Production and Usage: Technology Development, Advantages and Challenges in Europe" Energies 15, no. 8: 2940. https://doi.org/10.3390/en15082940

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Biogas Technology

• © 2020
• Liangwei Deng 0 ,
• Wenguo Wang 2

Biogas Institute of Ministry of Agriculture and Rural Affairs, Chengdu, China

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• Systematically addresses the principle and main features of three kinds of anaerobic digestion systems: household digesters, biogas septic tanks, and biogas plants
• Introduces readers to a broad range of anaerobic digestion systems, including the materials and design of digesters, biogas storage, cleaning, upgrading, biogas utilization, and digestate utilization
• Explains theories and application of biogas technology from a transdisciplinary perspective

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Biogas: Perspectives of an Old Technology

On-Farm Energy Production: Biogas

Advancement in Biogas Digester

• anaerobic microbe
• household digester
• construction materials
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• digestate utilization
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Table of contents (9 chapters)

Front matter, anaerobic digestion microorganisms.

Liangwei Deng, Yi Liu, Wenguo Wang

Rural Household Digesters

Biogas digester for domestic sewage treatment.

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Biogas Plant

Construction materials and structures of digesters, biogas cleaning and upgrading, biogas storage, biogas utilization, utilization of digestate, authors and affiliations, about the authors, bibliographic information.

Book Title : Biogas Technology

Authors : Liangwei Deng, Yi Liu, Wenguo Wang

DOI : https://doi.org/10.1007/978-981-15-4940-3

Publisher : Springer Singapore

eBook Packages : Earth and Environmental Science , Earth and Environmental Science (R0)

Copyright Information : The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2020

Hardcover ISBN : 978-981-15-4939-7 Published: 29 May 2020

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Number of Pages : XV, 363

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Modeling factors of biogas technology adoption: a roadmap towards environmental sustainability and green revolution

1 School of Economics and Management, North China Electric Power University, Beijing, 102206 China

Qingyou Yan

2 Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Beijing, 102206 China

Asif Razzaq

3 School of Management and Economics, Dalian University of Technology, Dalian, People’s Republic of China

4 School of Management and Economics, Beijing Institute of Technology, Beijing, 100081 China

Muhammad Irfan

5 Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing, 100081 China

6 Department of Business Administration, ILMA University, Karachi, 75190 Pakistan

Associated Data

The data supporting to findings of this study are available from the first author upon reasonable request.

In a developing country such as Pakistan, adopting biogas technology is a complicated process. The government has taken several steps to address energy issues by increasing biogas facilities. This research seeks to identify the major barriers to the deployment of biogas plants. Respondents were selected using the snowball sampling method. As a result, 79 adopters of biogas plants participated. Utilizing a structured questionnaire, primary data were collected. Hypotheses were evaluated using partial least squares structural equation modeling (PLS-SEM). Study results demonstrate that all influencing factors are favorably associated with implementing biogas technology, minimizing energy crises, and achieving cost-cutting objectives. In addition, the findings show that properly reducing economic and governmental barriers, encourage farmers to use biogas plants productively and substantially. To build biogas facilities, the government should adopt an economic strategy, owner training, day-to-day operations, and professional technical assistance.

Introduction

Climate change, depletion of natural resources, increasing air and water pollution, and a reduction in biodiversity are effects of rising material consumption on environmental quality. Like the rest of the developing world, Pakistan needs extensive energy to sustain its people and businesses (Irfan et al. 2021 ). Decades of uncontrolled electricity demand and supply gaps have plagued the country. During the summer, this vacuum is obvious. 16 to 18 h per day in rural regions and 10 to 12 h per day in metropolitan cities are without electricity in Pakistan. About 51 million people in Pakistan lack access to electricity, and 50% of the population lacks access to clean cooking facilities (IRENA 2020 ). Pakistan’s installed power generating capacity reached 34,501 megawatts in May 2021 (MW). It is anticipated to grow by 53,315 MW by 2030. The renewable energy contribution to energy needs is about 0.5%, which is insignificant (NEPRA 2021 ). Pakistan’s national energy mix for the fiscal year 2019–2020 is 121,691 Gigawatt hours (GWh) by the end of May 2021, with thermal plants accounting for 57% of power output, hydroelectric plants for 32%, renewable energy for 3%, and nuclear plants for 8% (NEPRA 2021 ).

Pakistan’s geographical location offers significant potential (about 81 million tonnes per year) for all types of renewable energy, including solar energy, wind energy, and bio-energy. Utilizing combustion, trans-esterification, gasification, and pyrolysis, the USA has enormous potential for producing biomass bio-energy. The impact of modern technology on the nation’s sustainable economic growth is enormous. Solar isolation (5.5Wh m−2d−1 ) and annual mean sunlight duration of 8–10 hd−1 are a boon in Pakistan. In the coastal areas of Sindh and Baluchistan, wind speeds range from 5 to 7 m per second, and the wind energy potential reaches 20,000 MW. Eighty percent area of Sindh, South Punjab and 65% area of Baluchistan’s daily average solar radioactivity force array from 1600 to 2750 W /m2 during 10 h. Monthly energy output per 100 m 2 in Pakistan must range between 45 and 83 MW (Ali et al. 2021 ).

This research model investigates the moderating influence of technical knowledge via social media on Pakistanis’ propensity to embrace biogas technology. We have addressed with farmers the major obstacles to implementing biogas plants in this nation. In this research, respondents were selected using a systematic sampling technique. Using quantitative data collection techniques, questionnaires were utilized to obtain the information required to achieve the study goals. PLS-SEM was utilized to evaluate the collected data. The findings show that Pakistan’s thorough elimination of economic and governmental barriers stimulates farmers to build biogas systems greatly and favorably. The report suggests that the government draught an economic strategy, raise awareness via social media, teach owners, and eliminate maintenance hurdles with skilled technicians to promote biogas facilities. The regulatory authorities must prioritize the usage of biogas plants and attract investment. This research investigated the technical obstacles and important sociocultural factors preventing Pakistan from adopting biogas-powered plants. Existing social practices are related to individual behavior, which is the source of social niche. The reasons of plant users acquire biogas plants are outlined in Table ​ Table1 1 .

Motivation to attract farmers on different factors

Table ​ Table1 1 demonstrates why biogas plant building is of relevance to farmers. Consequently, several obstacles and important issues hinder the nation’s adoption of biogas technology. This research aims to identify the key barriers and causes why farmers abandon biogas technology. Despite its economic benefits, scientific viability, and environmental advantages, biogas technology is still not widely accepted in Pakistan. Existing research has shown a considerable knowledge gap about the most important contributory factors of dependence, including the selection of market, institutional, and home fuel sources. Adopting biogas has negative implications on collection time and fuel wood prices but large favorable benefits on agricultural income and revenue (GoP 2020 ).

All previous research on the energy sector in Pakistan (Ali et al. 2022b ) focused on energy gap based on demand and supply, (ii) source of energy production, (iii) upcoming of energy division, (iv) the valuation of the whole energy area in Pakistan, and (v) the renewable energy combination. Investors and all kinds of investments are discouraged by the absence of an examination of technical obstacles and critical social considerations related to adopting biogas-installed plants; and (iii) planned expenditures to realize the economic advantages of biogas-installed facilities. We analyses the key obstacles and crucial variables of biogas-installed plants in the country that impede the sustainable development of biogas technology; (ii) we emphasize installation and maintenance hurdles for the elimination of these obstacles to attracting biogas plant investors for the growth of biogas energy on a sustainable basis; and (iii) we practically evaluate the moderation of biogas plant size. The conclusions of this research study will aid government institutions, competent authorities, and non-governmental groups in simplifying the wasteful procedure. Biogas plants are meant to deliver renewable energy at an affordable price to reduce rural farmers’ greenhouse smoke discharges via biogas and effective leftover controlling. In addition, the present study seeks to educate farmers on the benefits of adopting biogas plants, enhance their abilities, and urge them to extend their installations owing to the low initial share and long-standing profits. This research work aims to decrease economic threats, eliminate barriers to farmer biogas plant investment, provide free energy for farmer self-consumption through small-scale biogas plants, and improve biogas plant competence. In addition, the objective of this study is to enhance collaboration between knowledge institutions, government organizations, and municipalities in the biogas business.

Consequently, the key aim of this research was to identify and explain the most significant obstacles that deter agrarians to adopt modern biogas machinery. This study demonstrates Pakistan’s biogas potential to persuade financiers to spend in biogas technology sector for the justifiable for biogas energy expansion. This article explores the important characteristics of biogas-installed plants in Pakistan to promote the long-term expansion of modern biogas machinery. The subsequent sector examines the literature assessment, research methodology, study design, and formulation of hypotheses. The discussion focuses on the findings, implications, conclusion, and important research limitations.

Literature review

The production of energy from fossil fuels is a global concern (Curtin et al. 2019 ; Gani 2021 ). Without a sustained global energy supply, the current standard of living and economic growth are unattainable (Azam et al. 2019 ; Gielen et al. 2019 ; Hoang et al. 2021 ; Lowe and Drummond 2022 ). Consistent energy supply is essential for contemporary life (Gabr et al. 2018 ; Grunewald and Diakonova 2018 ; Popp et al. 2021 ). The nation’s economic growth and prosperity rely heavily on efficient energy resources (Bhattacharya et al. 2020 ; Usman et al. 2020 ). Improving a country’s or nation’s level of living and economic growth requires energy (Roy and Dalei 2020 ; Sueyoshi and Yuan 2018 ). Energy was vital to emerging countries’ economic and social growth (Saito et al. 2019 ; Wang et al. 2021 ). It keeps around USD 214,406 (PRs 46,290) million on runny fuel gas, firewood, paraffin oil, and bio fertilizer every month (Arshad et al. 2018 ). Biogas is a crucial inexpensive drive basis for the maintainable growth of any country. Utilizing modern technologies, energy production is now a challenging endeavor. The country’s high energy consumption is due to its growing population and economy. The disparity between energy demand and supply causes issues in almost every aspect of national life, plus supportable growth, affluence, the expansion of supplementary productions houses, and commercial progress. These type of barriers harm anthropological fitness, liquid supplies, agrarian output, and environmental actions (Amir et al. 2019 ; Murad et al. 2019 ).

Multiple investigation studies demonstrate that biogas offers energy to pastoral regions and fulfills several economic demands, such as reducing poverty, providing local jobs, and improving local health (Bates et al. 2019 ; Mikhail et al. 2020 ; Ozturk 2016 ). Biogas production provides several environmental benefits, including producing electricity and renewable energy, treating waste, and using bio-slurry as biological nourishment to recover crop resilience. In rural regions of low- and middle-income countries, other reasons for deforestation are investigated, including energy shortages, slow economic development, and a lack of biogas production. In rural places, women are thus responsible for cooking and heating using fire and wood (Jayarathne et al. 2018 ; Liu et al. 2021 ). Biogas enabled the generation of biogas and the collection of bio-slurry for soil enrichment (Ashraf et al. 2019 ). Importing petroleum and natural gas throws rising countries under severe economic strain. Adoption of biogas is economically and environmentally feasible (Sun et al. 2021 ). Pakistan derives the bulk of its energy from fossil fuels. These energy sources are pricey and have variable environmental consequences. To overcome the grave energy problem, the government of Pakistan has decided to use an alternative, cost-effective, and ecologically friendly energy sources. Modern RE plans to account for environmental limits and provide practical answers to all energy concerns (Morgunova et al. 2020 ; Nasirov et al. 2018 ; Wu et al. 2020a ). Despite this, the government of Pakistan has pledged to boost the RE share by 5% by 2030, and biomass energy will be essential to achieving this goal (Yasmin and Grundmann 2019 ). Pakistan spends a large percentage of its national budget on gas and oil imports to compensate for a temporary energy deficit. Pakistan saved $8–$9 billion on energy imports in 2019–2020 (Aziz et al. 2018 ; Roussel et al. 2021 ).

Biogas may be a viable and efficient alternative energy source for addressing the nation’s energy deficit. As the sixth-largest livestock-based economy in the world, Pakistan has considerable potential for biogas energy production (Khan et al. 2021b ; Yasmin and Grundmann 2019 ). Of Pakistan’s energy demands, 28.12% are met by imported oil and gas (Rafique and Rehman 2017 ; Yaqoo et al. 2021 ). Over the last two decades, commercial contractors, (global private organizations), (local governmental organizations), and the government sector have erected biogas facilities. Pakistan has a large animal population and can produce biogas from animal waste (Awan et al. 2022 ). The biogas plant is cost-effective and excellent for lowering ophthalmic and lung pollutants due to its cheap installation cost. Animal dung may create an average of 12–804 m 3 biogases per day in rural Pakistan (Sun et al. 2021 ). The Pakistani government began biogas project 4109 in 1974 using biogas technology for societal gain. In rural areas, 4137 biogas plants were constructed by 1987. The daily biogas plant capacity for cooking and lighting varied from 3000 to 5000 Free Triiodothyronine Feet (biogas measurement unit) (Kamran 2018 ). Agriculture is Pakistan’s major sector, providing 18.5% of its gross domestic product (GDP) and employing 38.5% of the population (Afridi and Qammar 2020 ).

Daily animal dung production in the nation is 650 million kilograms. In addition, it can provide clients with 16.25 million m 3 /day if 50% of animal waste is collected and handled domestically. More than 8 million families produce animal products directly, accounting for 35–40% of their entire output (Jabeen et al. 2020 ; Ullah et al. 2021 ). The government devoted fewer resources to the agricultural subsector of forestry, which was judged inferior to others (Mir et al. 2021 ). Pakistani literature suggests that many research types focus on biogas technology (Iqbal et al. 2018 ). However, this study’s major objective was to adopt biogas technology. No one has investigated why farmers abandoned biogas technology and the fundamental barriers they encountered. Adopting biogas technology will provide Pakistani farmers with a prosperous future and alleviate the country’s energy issue (Wang et al. 2020c ). In 2008–2009, Pakistan began its home biogas project program to offer biogas plants and replace conventional fuels such as residual crops, liquefied petroleum gas, wood, and animal dung cake with biogas (Jan 2021 ). EKN-RSPN (embassy of the Netherlands-rural support programs network) reported that Pakistan had built the maximum number of biogas plants authorized for phase one of the domestic biogas program (PDBP) in Punjab: ten biogas plants. This program’s primary objective was to establish 12,000 biogas plants. Unfortunately, only around 3000 biogas plants were networked, and the intended results were not achieved. The project offered subsidies as incentives to encourage and support rural residents’ social and technical adaptation. However, biogas technology acceptability has not yet reached an adequate level (Gelani et al. 2022 ; Lei et al. 2021 ).

As the world’s fourth most significant energy source, biogas provides more than 14% of primary energy (Khan et al. 2021a ; Yaqoo et al. 2021 ; Yasar et al. 2017a ). Numerous countries, especially those with low-to-middle incomes, have exploited energy sources like hydro, biomass, and solar thermal, to provide dependable, local, and inexpensive power (Mohsin et al. 2022 ; Saghir et al. 2019 ; Tareen et al. 2018 ). Reputation and time savings are two more driving factors that account for 33.5% each. Technical advancement and social acceptability are strongly correlated in low- and middle-income nations. In Pakistan, the installation and construction of biogas plants are largely driven by energy, time savings, and subsidies. Of the most significant motivating and subsidizing aspects, 42.5% were support, taxation, and finance for using cleaner fuels (Puzzolo et al. 2016 ). However, this depends on adoption awareness (Mohsin et al. 2022 ; Pilloni et al. 2020 ). Biogas production from biological leftover has recognized as a renewable energy cause (Afridi et al. 2019 ). There are several productive biogas plants in South Asian nations, including India, Bangladesh, China, and Nepal (Wang et al. 2020b ).

Formulation of hypotheses with the theoretical background

Maintenance barriers of biogas plants.

The development of biogas technology in rural areas of Pakistan establishes its dominance over energy decisions to alleviate the economic problems caused by energy inefficiency. Analyzing the durables dominating energy efficiency and the consequences of biogas technologies requires dominance. Biogas energy has huge potential and is a promising form of renewable energy for satisfying the nation’s energy and financial requirements. There are 15 million potential biogas power plants in Pakistan, which might greatly influence the country's economic growth (Kamran 2018 ). Biogas facilities require qualified technicians nationwide. The government has abundant biogas supplies, such as agricultural wastes, fuel wood, municipal solid waste, and animal manure. Forty-eight percent of the country’s energy needs are met by burning wood, while animal byproducts and crops meet 32%. Pakistan’s potential energy output of 4800 to 5600 MW from animal waste. The biochemical and thermochemical potential for generating power from municipal solid waste is 220 kWh/t and 560 kWh/t, respectively (Afridi and Qammar 2020 ). Due to its agricultural character, Pakistan possesses many animal-based biogas resources. In rural locations, the successful deployment of these biogas resources might offer positive outcomes. Using manure and straw biogas properly can reduce emissions and increase economic benefits (Nevzorova and Kutcherov 2019 ). The biogas plants provide electricity, reduce greenhouse gas emissions, stimulate economic expansion by improving earnings, and their upgrading can enhance environmental performance (Iqbal et al. 2018 ; Iram et al. 2020 ). Adopting biogas technology in rural regions can substantially help the nation’s economic growth. Its parallel situation correctly depicts sites’ biogas uptake and economic growth projections. Based on these findings, we offered the following initial hypothesis:

• Hypothesis 1 (H1): There is a correlation between the maintenance difficulties of biogas plants and the desire to embrace biogas technology in Pakistan.

Economic and policy barriers

Approximately 63% of the population of Pakistan lives in rural regions and requires business and household energy sources. Existing portable biogas plants are desirable owing to their high methane gas output, low price, open policy, and portability. This biogas factory may aid rural communities in increasing and meeting their domestic requirements (Wang et al. 2020b ). There is a correlation between the deployment of biogas plants and the prosperity of rural areas. Components of biogas development include household biogas digesters, biomethane plants, biogas grid plants for electricity generation, large-scale biogas plants, and micro biogas digesters in rocky locations (Baloch et al. 2020 ; Iqbal et al. 2018 ). These findings fit with Pakistan’s goal to construct biogas facilities. This sign highlights the relevance of biogas for private share and this one connection to economic development. Utilizing biogas plants efficiently in rural areas may provide financial development that exceeds the limitations of biogas adoption. Biogas is, from the perspective of a professional management unit, the finest renewable energy choice for the development and prosperity of the area. In addition to its social, economic, and environmental advantages, commercial biogas is seen as the future of rural communities (Haile et al. 2019 ). This study’s conceptual approach overcomes the issues of Pakistan’s solar biogas plant and rural prosperity in general. These factors lead to the formation of the following next supposition:

• Hypothesis 2 (H2): There is a correlation between economic and policy barriers and adoption intentions for biogas technology.

Owner satisfaction with biogas plant

Biogas has recently been used to generate power. The feedstock substantial is a supportable renewable energy (RE) basis (Luyer et al. 2021 ). Using biogas to generate energy might minimize power outages, enhance feedstock material management, and alleviate Pakistan’s environmental problems. Agricultural, plant, and nutrition excess are the most efficient drive causes and crucial elements of a supportable evolution. Enhanced use of these resources for energy production may reduce the nation’s CO 2 emissions. The overall biogas production potential in Pakistan is 226.8 Mm 3 d1, whereas the predicted power generation for 2018 is 59,536 GWh y1 (Sun et al. 2020 ; Wu et al. 2020b ; Yaqoo et al. 2021 ). The use of biogas may create 280 MWh of electricity per day from chicken dung (Gebreegziabher et al. 2018 ). It enhances people’s living level and may also affect their lives favorably. The utilization of Pakistan’s biogas potential is essential for its economic growth. In all rural regions of the country, the biogas support program (BSP) must be implemented (Jan and Akram 2018 ). Due to the fixed installation cost of the biogas plant, the advantages achieved in later years exceed those of the first year. Affording to a cost-energy benefit study, by rice peapod and chicken manure to produce a biogas modern technology in Pakistan, is possible. The third hypothesis was formulated based on the following findings:

• Hypothesis 3 (H3): There is a correlation between owner satisfaction with biogas plants and the intention to adopt biogas technology in Pakistan.

Financial support for biogas plants

The biogas business in Pakistan has enormous unrealized potential, which must be achieved by disseminating relevant information to local farmers. If the Pakistani government offers operational and maintenance assistance to biogas plant customers, foreign investors may aid in addressing the sector’s issues. Operating and maintenance expenditures vary based on the magnitude of the installation. For similar projects, the technical and operational design of the chosen biogas plant should be evaluated. The government may significantly promote the biogas industry in the USA by providing grants, enticements, and existing plans that entice investors and financiers (Jarrar et al. 2020 ). Permanent cupola biogas unit offer excellent economic enactment due to cheap investment expenditures (fixing and response), reduced operating and maintenance budgets, and a short reimbursement period (Wu et al. 2020c ; Yasar et al. 2017b ). The thermal energy supplied by biogas has a favorable effect on evaluation outcomes. If the policy is updated to permit independent renewable plug-in projects, the RE policy incentives may attract biogas investors and improve the economic sustainability of biogas facilities (Govender et al. 2019 ). Pakistan’s economic position may help the biogas power plant. These variables are potential outcomes of certain parts of operation and maintenance, and they have an immediate impact on the growth of biogas power plants. In light of these reasons, the following idea was proposed:

• Hypothesis 4 (H4): Financial assistance for biogas plants correlates positively with the desire to embrace biogas technology in Pakistan.

The moderating role of awareness through social media between maintenance barriers of biogas plants and the intention to adopt biogas technology in Pakistan

Positive and considerable economic feedback is related to rural farmers’ exposure to biogas technology through social media. Adaptation to climate change is contingent upon the contribution, availability of local specialists, and attractiveness of the expanding biogas technology RE market (Hasan et al. 2020 ). Biogas technology may improve biogas output in developing nations such as Pakistan, as has been convincingly proved. Fifty percent of productive biogas systems fail after 2 years of contracting owing to technological and logical obstacles. Due to poor digester feed eminence and a nonexistence of facility expertise, biogas production could not be maintained. Local technical expertise in replacing replacements is inadequate to maintain biogas production in the case of a lack of primary feedstock (Tumusiime et al. 2019 ). The evaluation is based on biogas plant knowledge and comprehension, encompassing a broader geographical perspective. These parameters have a close relationship with the installation and production of biogas. Certain circumstances contributed to the postponement of certain biogas plants, although developing nations view biogas plants and their services favorably. Recognizing responsibility, customer effectiveness, environmental concern, and repercussions knowledge have a substantial and lasting influence on the farmer’s standards. Therefore, human variables impact Pakistani farmers’ propensity to employ biogas technology (Hao et al. 2020 ; Wang et al. 2020 ). Considering these factors, the following hypothesis was formulated:

• Hypothesis 5 (H5): The project’s awareness through social media positively moderates the association between biogas plant maintenance barriers and the intention to adopt biogas technology in Pakistan.
• Hypothesis 6 (H6): The project’s awareness through social media positively moderates the association between financial support for biogas plants and the intention to adopt biogas technology in Pakistan.
• Hypothesis 7 (H7): The project’s awareness through social media positively moderates the association between economic and policy barriers and the intention to adopt biogas technology in Pakistan.
• Hypothesis 8 (H8): The project’s awareness through social media positively moderates the association between Owner satisfaction with biogas plants and the intention to adopt biogas technology in Pakistan.
• Hypothesis 9 (H9): There is a relationship between the awareness through social media and the intention to adopt biogas technology in Pakistan.

The theory backs the energy selection hypothesis in this paper. This research applies the concept of energy choice to a particular issue. Depending on the availability of gas connections in areas where it is viable to connect to a Sui fume nationwide, biogas from agricultural leftover, or additional substitute energy, the study will be done. Each household can choose a certain fuel according to the energy ladder paradigm. This linear process allows for the transformation of several fuel kinds. Depending on the median household income in Pakistan, old-fashioned energies corresponding slurry cube, plants, and fuel are utilized less often than contemporary gases alike electrical cooktops and methane gas. This strategy emphasizes the specific cost of each energy option (Gautam et al. 2020 ). For many countries studying new RE sources, meeting the clean energy demands of their people with conventional energy sources is a problem. This notion consists of two essential elements: economics and wealth (Ozoh et al. 2018 ; Wu et al. 2021 ). This study was conducted in Pakistan using a theoretical framework to investigate the variables influencing the adoption of biogas energy plants. It cannot be ruled out that environmental, social, and technological aspects are responsible for the failure or success of biogas energy plants with customers or society. The mental paradigm shown in Fig.  1 may influence a customer’s selection of a living energy source. The conceptual model depicts the predictable association between the self-determining variable (IV) and reliant variable (DV) (DV). In addition, the suggested model illustrates the estimated moderation between the independent and dependent variable.

Conceptual model

Research methodology

This study assessed the potential of biogas using non-random sampling (snowball) sample surveys and transportable presentations to enhance the present biogas technology in Pakistan. The non-random sampling technique is used for exploratory research, pilot studies, and qualitative research. Existing biogas plants were selected for research to enhance their service and quality. Using the snowball sampling approach, a representative sample of biogas plants from around the country was gathered, beginning with particular biogas plants. To do this, researchers conducted a poll between March and September 2021; when the fourth wave of the delta mutant coronavirus (COVID-19) peaked in Pakistan, there was a considerable risk of addressing applicable defendants (biogas plant financers). Moreover, each delegate has a unique grasp of biogas technology and demographic measurements (see Tables ​ Tables9 9 and ​ and10 10 in Appendix). In addition, this study used snowball sampling to choose Pakistani respondents (owners of biogas facilities) exhibiting varied performances. Snowball selection is insufficient for hypothetical oversimplification, especially in the absence of randomization and when participants are linked to one another (Ozoh et al. 2018 ). This research aims to examine the benefits and drawbacks of biogas technology and assess the financial performance of biogas plants whose owners are satisfied. Awareness and comprehension are moderating influences on biogas plant adoption is one of the satisfaction nexus’ moderating elements and removes barriers. Following a quantitative research approach, questionnaires were utilized to obtain quantitative data from respondents in this study (biogas plant financer).

The level of questions and how respondents (owners of biogas plants) contradicted the semi-structured interview. Part A: Demographic features of respondents (biogas plant owners)

Adoption of sustainable upgrading measures for biogas plants

Our study used structural equation modeling (SEM) to examine facts (Ali et al. 2022a ). Because it is a component-centered technique, it was utilized to investigate the relationship dimensions (Urbach and Ahlemann 2010 ). Widespread adoption of PLS-SEM in succeeding research is proof of its validity; the author of this work also used it (Ying et al. 2020 ). Conventional statistical analysis methods lag behind structural equation modeling (SEM). It is useful for statistically assessing a product’s effectiveness, convenience, and precision (Franziska et al. 2016 ). SEM addresses the issues inherent to first-generation analysis while being a technology of the second generation. SEM is a multivariate analysis method that may be used to examine numerous variables concurrently. SEM is prevalent in business research due to its potential to concurrently handle complicated and many interactions (Chin and Newsted 1999 ). Variance-based SEM (VB-SEM), partial least square (PLS)-SEM, and covariance-based SEM (CB) are well-known SEM techniques (Henseler et al. 2009 ). Utilizing improper analytical procedures may result in erroneous findings.

For commercial and social science research, however, a reliable statistical approach is of utmost importance (Ramayah et al. 2010 ). PLS-measurement structural equation models and structural models are dual phase analytical procedures consisting of measurement outcomes (Osborne et al. 2010 ). Measurement investigation revealed convergent validity based on the average variance extracted (AVE), interior constancy dependability based on composite reliability (C.R.), and item reliability based on external loading. The measurement assessment model includes the evaluation of reliability and validity as well as the inner model. The structural assessment model includes evaluation of external models and testing of hypotheses/relationships. This study examined the associations between the relevant variables by analyzing primary data using PLS 3.0 software. Moreover, smart-PLS for VB-SEM use PLS-SEM route modeling to assess the association between variables (Solangi et al. 2019 ). Smart-PLS is designed to test hypotheses, and complex model research has changed accordingly. Smart-PLS utilizes two methodologies: measurement evaluation and structural model-based analysis. The evaluation measurement model includes convergent and discriminant validity tests for the dependability and validity of the constructs.

Sample and procedure

We were able to reach 91 pertinent responders (biogas plant owners). Eighty-six (86) of these individuals consented to participate in the poll. After receiving permission from respondents (owners of biogas plants), the researchers distributed open- and closed-ended questionnaires to every responder (biogas plant financer) through what’s App and LinkedIn . The total number of completed questionnaires received for the questionnaire survey was 79. The response rate was 86.81%; however, the researchers eliminated 5 surveys because of unmatched and inadequate responses. The sample yielded 79 valid respondents (owners of biogas plants) for study analysis. The respondents collected their personal information based on the visit of researchers and friends in the study area. The conclusion is based on an accurate depiction of the sample. The demographic characteristics of the respondents, which include age, experience, education, and gender, also demonstrate the various backgrounds of the respondents who supplied the correct response in this study (see Appendix Table ​ Table9). 9 ). The first half of the questionnaire pertains to the respondents’ personal information, while the second piece is concerned with the characteristics of biogas plants. Using non-probability (snowball) sample surveys and mobile applications, this study assessed the potential of biogas in Pakistan and enhanced existing biogas plants. This sampling technique is utilized for specialized demographic features, pilot studies, qualitative research, and exploratory research; it does not give every population member an equal chance to participate. Existing biogas facilities were chosen for study to improve their service and quality. Due to the unique nature of biogas plants, the snowball sampling method was used to create a nationally representative sample of biogas plants. To do this, researchers conducted a poll between March and September 2021; when the fourth wave of the delta mutant coronavirus (COVID-19) peaked in Pakistan, there was a considerable risk of addressing appropriate defendants (biogas plant financer). Moreover, each delegate has a wealth of knowledge about biogas plants and demographic measurements (see Tables ​ Tables9 9 and ​ and10 10 in Appendix). In addition, this study used snowball sampling to choose Pakistani respondents (owners of biogas plants) with different habits. Snowball sampling is inadequate for theoretical generalization, especially in the absence of randomization and when participants are linked to one another (Ozoh et al. 2018 ). This research aims to investigate the pros and cons of installing biogas technology and assess the financial performance of biogas plants whose owners are satisfied. The moderating influence of awareness and understanding on adopting biogas plants is part of the satisfaction nexus and decreases hurdles. This study used questionnaires to obtain respondents’ information per a quantitative data collection strategy (biogas plant financer).

Our study combined structural equation modeling with data analysis (SEM). Because it is a component-centered method, this approach was used to explore the relationship factors (Urbach and Ahlemann 2010 ). The widespread use of PLS-SEM in subsequent research is proof of its validity; the author of this work also employed it (Ying et al. 2020 ). SEM is better than standard statistical approaches for modeling. It is beneficial for the statistical analysis of efficiency, comfort, and accuracy (Schlegel et al. 2016 ). As a second-generation technique, SEM overcomes the problems inherent to first-generation analysis. SEM is a multivariate analytic technique that may be used to investigate many variables simultaneously. SEM is common in business research owing to its ability to manage complex simultaneously and many interactions (Chin and Newsted 1999 ). Variance-based SEM (VB-SEM), partial least square (PLS)-SEM, and covariance-based SEM (CB) are established SEM methods (Henseler et al. 2009 ). If analytical processes are used poorly, erroneous conclusions are generated for commercial and social scientific research.

However, a trustworthy statistical methodology is highly significant (Ramayah et al. 2010 ). PLS-measurement structural equation models and structural models are two-stage analytical procedures comprised of measurement outcomes (Osborne 2010 ). Measurement analysis was used to assess the convergent validity of the extracted average variance (AVE), inner stability dependability regarding composite reliability (C.R.), and element consistency regarding outer loading. The measurement assessment model includes the evaluation of reliability and validity as well as the inner model, and the structural assessment model tests hypotheses/relationships and evaluates the outer model. This study evaluated the associations between the researched variables using PLS 3.0 software to analyze primary data. In addition, smart-PLS for VB-SEM use PLS-SEM route modeling to examine the relationship between variables (Solangi et al. 2019 ). Cronbach’s alpha, composite reliability, and item loading were used to assess the link between the items'’ convergent validity. Despite this, discriminant validity depends on the correlation between variables as assessed by Fornell Larker, cross-loading, and the ratio of heterotraits to monotraits. In addition, the evaluation of the measurement model includes testing hypotheses using route analysis, as mentioned in the section describing the study’s findings. Path analysis has shown interdependencies between variables.

Instrument and variables measurement

In this study, the researchers have included all elements from earlier works. The investigation led to the construction of items depending on maintenance barriers of biogas plants (Jan 2017 ). The financial support for biogas plants aspects of government assistance was taken from the research (Shah and Sahito 2017 ). Assumed were items associated with the economic and policy barriers (Ozoh et al. 2018 ). The construction of objects is connected to owner satisfaction with biogas plants (Chin and Newsted 1999 ). Adopted were components of awareness through social media (Wang et al. 2020c ). Finally, this research embraced elements linked to adopting biogas technology (Hair et al. 2014 ).

Data analysis and results

The following tables detail the confirmed validity and reliability of this measuring approach. Figure  2 of the measurement assessment model shows the variable influence loadings. All factor loading levels are more than 0.5, and all items’ convergent validity in the measurement assessment model is valid. According to the findings of the route analysis performed to test the hypotheses, MBBP, ATSM, and FSFBP are all true. In contrast, MBBP is detrimental to ITABT but acceptable to MBBP, ATSM, EPB, and OSWBP. ATSM moderates the associations between MBBP, FSFBP, EPB, OSWBP, and ITABT and accepts MBBP, FSFBP, OSWBP, and EPB. This section investigates convergent validity, which demonstrates the connection between things. Table ​ Table2 2 shows the loadings and AVE values above 0.50, while the alpha and composite reliability (C.R) values exceed 0.70. These results indicate that convergent validity is a substantial and valid relationship between the components. AVE levels exceed 0.50, but composite reliability (C.R) standards surpass 0.70. These numbers imply a significant level of item correlation and convergent validity.

Measurement model assessment

Convergent validity analysis

N  = 79 ; SFL , standard factor loading; AVE , average variance extracted; CR , composite reliability

Measurement assessment model

The measurement model evaluates the constructs’ dependability and cogency and the item influence loadings (Hair et al. 2019 ). Consistent is the paradigm for testing validity and reliability (convergent and discriminant validity, respectively) (Hair et al. 2011 ). All item loadings exceed the 0.5 thresholds (Hair et al. 2014 ) (Table ​ (Table2). 2 ). Each average factor loading was above 0.50, and every reflection subsidized to the generated adjustable, as determined by the study’s analysis (Arbuckle 2011 ). AVE larger than the recommended criterion of 0.5. Each standard’s composite dependability rating is more than 0.70, indicating the accuracy of the measurements (Anderson and Gerbing 1988 ). From 0.913 (implementation of biogas technology) to 0.979 (economic and transparent policies), C.R. scores range (low-cost and clear policy). All additional loadings have values between 0.5 and 0.946%.

The study results also analyze the discriminant validity of the relationship between variables. To examine the discriminant validity, cross-loading was performed. These results support discriminant validity and show a low correlation between variables. In addition, Table ​ Table3 3 of the findings section illustrates the discriminant validity using Fornell-Larcker for the variable relationships. Table ​ Table4’s 4 ’s italicized numbers show that the components have a high correlation, while the remaining elements have a poor correlation. The discriminant validity is examined by comparing the bold values of the cross-loadings with other components in each column. The variable’s values show that those indicating a link through the inconstant are larger than folks indicating a connection through extra inconstant. These findings indicated that discriminant validity is a genuine, tenuous relationship between variables. All factor loading levels above 0.5 and the convergent cogency of all items are valid.

Fornell-Larcker

N  = 79; MBBP , maintenance barriers of biogas plants; FSFBP , financial support for biogas plants; EPB , economic and policy barriers; OSWBP , owner satisfaction with biogas plant; ATSM , awareness through social media; ITABT , intention to adopt biogas technology

Cross-loading

Numerous studies have critiqued the Fornell-Larcker criterion; hence, the heterotrait–monotrait ratio of correlations (HTMT) is regarded as a suitable discriminant validity measure (Akbar et al. 2019 ). It is confirmed if the discriminant validity value is less than 0.85 or 0.90 (Ali et al. 2022b ). Each number in Table ​ Table5 5 is below 0.90. The results section also presents the discriminant validity of the variable’ nexus. The values of the variable indicate that values suggesting a relationship with the variable are greater than those indicating a connection with other variables. This study also assessed the interaction between factors using the HTMT ratio. According to HTMT statistics, the values are less than 0.85.

Heterotrait–monotrait ratio (HTMT) for discriminant validity

Structural assessment model

The measuring model was evaluated first, followed by the structural assessment model, which examined the link among exogenous and endogenous components. The structural model is evaluated using many statistical measures, including effect size ( f 2 ), t values, predictive relevance ( Q 2 ), coefficient of determination ( R 2 ), and path coefficient (values). Using PLS-SEM literature criteria, this research analyses hypotheses and estimates the significance of path coefficients. To determine the significance of the hypotheses, the bootstrapping method was utilized using 5000 subsamples and a significance level of 5% (one-tailed). The results reveal that all hypotheses except H2 and H3 are accepted. MBBP ( β  = 0.238, t  = 4.251 > 1.64, p 0.05), maintenance barriers of biogas plants relationship (moderator), ( β  = 0.026, t  = 0.045 < 1.64, p 0.281), FSFBP ( β  = 0.107, t  = 2.148 >), 1.64, p 0.05), financial support for biogas plants relationship (moderator), ( β  = 0.176, t  = 2.342 > 1.64, p 0.05), EPB ( β  = 0.010, t  = 0.212 < 1.64, p 0.05), economic and policy barriers relationship (moderator) ( β  = 0.371, t  = 4.861 > 1.64, p 0.05), OSWBP ( β  = 0.091, t  = 1.650 > 1.64, p 0.05), owner satisfaction with biogas plant relationship (moderator), ( β  = 0.087, t  = 1.729 > 1.64, p 0.05), ATSM ( β  = 0.144, t  = 2.016 > 1.64, p 0.05), and intention to adopt biogas technology affect significantly and positively. All biogas plants have positive significance results for the intention to adopt biogas technology.

The R 2 value for maintenance hurdles of biogas plants is 0.462, showing that the model has substantial explanatory power for adopting biogas technology in Pakistan. However, aiding a model based on its R 2 score is not a practical and successful technique. The model’s Q 2 projected relevance measurement is hence the most accurate. Showing that the value of Q 2 exceeds zero, the latent exogenous norms have excessive predictive importance, indicating that Q 2 is greater than zero. The findings suggest that the value of Q 2 is 0.231, indicating that social media may increase the desire to embrace biogas technology, confirming the model’s excellent predictive validity. These are the typical values of f 2 , containing 0.02, 0.15, and 0.35, representing modest, moderate, and major effects, respectively, across three categories. Consequently, f 2 assumed the impact magnitude fluctuated between mild and big (see Table ​ Table6). 6 ). Table ​ Table6 6 contains a variety of statistical methods. Figure  3 ’s structural evaluation model suggests a substantial connection between the variables since the T- values are greater than zero (1.64). All hypotheses except H2 and H3 are approved. All moderated variable values in the structural assessment model for biogas technology adoption in Pakistan are positive and exhibit a substantial association.

Structural model results (hypotheses testing)

(*), the moderating relationship indicated by the asterisk among the variables

Structural model assessment

t -values are more significant than p -values; the structural assessment model depicts the relationship between the variables (1.64). Adopting biogas technology benefits and considering the maintenance barriers of biogas plants in Pakistan. All moderated variable values are indicative of favorable outcomes. The structural evaluation approach for deploying biogas technology in Pakistan to attract green FDI demonstrates a substantial correlation. We conducted semi-structured interviews with illiterate biogas plant owners (those unable to fill out the questionnaires) to acquire insight into the genuine problems of biogas plant owners and practical information about the maintenance difficulties. Aspects include the economic and policy barriers, maintenance barriers of biogas plants, the original installation and investment cost, and knowledge of new technology. We have interviewed 37 rural Pakistani biogas plant proprietors. Tables ​ Tables7 7 and ​ and8 8 provide the examined criteria intended for biogas technology and the responses (%) from biogas plant financer. All percentages reflect responses from (illiterate) proprietors of biogas plants. The viewpoints and degrees of satisfaction of Pakistani respondents (biogas plant financer) to their biogas technology are shown in Table ​ Table7. 7 . The key factors are the ease of biogas plant operation, the availability of engineers and experts, the economic policy benefits, the suitable collection of gas for kitchen use, the use of gas for illumination, and the positive social reputation. Countries in South Asia, including India, Nepal, and Bangladesh, have a sufficient supply of technical services to stimulate the expansion of social projects in general (Breitenmoser et al. 2019 ). Fifty-nine percent of respondents (biogas-plant financiers) indicated that customer satisfaction with a Pakistani biogas plant is necessary for adopting biogas technology. About 23% of respondents (biogas plant professionals) said biogas technology needs a cheaper price and simpler policy. In addition, 16% of respondents recognized that customer happiness and plant quality are vital. Additionally, 50% of biogas plant customers (financiers of biogas plants) said that their facilities are operational and functional.

Views and satisfaction of biogas plant owners

Barriers and challenging factors

Inspiring factors and important barriers

A variety of problems hinder the partial adaptation of biogas plants. Unavailability of experts and fully trained technicians was the greatest response at 17.5%, followed by frequent operational problems at 14% and insufficient biogas pressure at 5.5%. The biogas facilities confront various operating issues, including rusting of the steel components, roof and wall cracking, and gas pressure leaks (Haile et al. 2019 ; Scheutz and Fredenslund 2019 ). The lowest pressure reported for biogas was 5.8%, which poses a serious problem for cooking meals adequately. The key cause aimed at squat heaviness or biogas secret the device is inadequate mixing of the feed. Twenty-one biogas facilities must have the right stirring mechanism to increase gas burden aimed at ultimate − user convenience (Nsair et al. 2019 ). Regular technical troubles have delayed the biogas plant's functioning, as 23% of the owners have complained. The controlled biogas plan used 16% of the globe, 13.5% of gas was lost, and customers of biogas got no technical help. Due to these factors, biogas plant customers endure failure and disillusionment, and the regulatory framework of the project is blamed for the technicians’ poor acceptability. Without a background framework and technical assistance, the profitability of a biogas plant project is severely compromised (Pandyaswargo et al. 2019 ). The barriers and problems faced by Pakistan’s biogas consumers are outlined in Table ​ Table8 8 .

Discussions and implications

This study has together hypothetical and practical consequences. The present important fictional effort underwrites to the literature on bio-technology and socioeconomics. The current research examines the impact of four influences, including the MBBP, FSFBP, EPB, OSWBP, ATSM, and ITABT, on the adoption of biogas plants by Pakistani farmers and the growth of biogas technology over the long term. This research study suggested government sector executives, private, non-governmental organizations (NGOs), policymakers, and advice for encouraging farmers to adopt biogas plants and develop biogas technology. This study emphasizes the critical need for politicians, economists, and energy sector authorities to eliminate key hurdles and provide financial aid to farmers who embrace biogas technology plants. Superior planning may limit the impact of a biogas plant's essential components and hurdles, advancing biogas-related knowledge. Biogas technology may reduce the energy problem and improve farmers’ financial conditions.

Nonetheless, government assistance may enhance biogas plant adoption in rural regions and investor excitement among new investors. The findings imply that biogas plant maintenance and economic and legislative constraints must be addressed to attract investment. Social media and open policies significantly influence the adoption of biogas plants and attract fresh financiers outstanding to cost savings and fulfillment with the machine. Removing economic and governmental hurdles with care encourages farmers to use biogas plants and improves rural living conditions. Similar results are supported by prior research (Garfí et al. 2019 ). This research also demonstrates that social media knowledge is not an ideal moderator of the link between the maintenance barriers of biogas plants and the desire to embrace biogas technology. According to the research, the adoption potential of biogas technology in rural Pakistan is affected by the awareness of biogas plants via social media. The given results correlate to the findings of this research (Luo et al. 2021 ). A prior study reveals that social media knowledge of biogas plants affects installation parameters and the uptake of biogas technology. This research also shows that social media knowledge of biogas plants is a key mediator of the relationship between financial support for biogas plants and the desire to use biogas technology. Consistent with a previous study’s results (Havrysh et al. 2020 ), the findings show that social media knowledge of biogas technology influences government economic policies and encourages rural farmers to use biogas plants and save money (Wang et al. 2020c ).

According to this study, eliminating maintenance obstacles and the availability of professionals validates the choice to adopt biogas plants and provides social and economic benefits for rural farmers. Farmers and new investors are drawn to biogas facilities by the advantageous economic policies, low price, and maintenance assistance. The research also reveals a strong correlation between government funding, the appeal of biogas plants to consumers, and their socioeconomic worth. Investor’s fulfillment and plant eminence are inventive ways to persuade agrarians and original financiers to use biogas technology, minimizing the global energy disaster and stimulating the home economy. Purchaser fulfillment and plant eminence may show a crucial part in enticing home − grown agrarians, commercial and non-governmental organizations, and fresh financiers to Pakistan’s biogas technology and reaping commercial and societal advantages. These findings provide policymakers, experts, institutional bodies, regulators, the ministry of water power, and the upper management of the alternative energy development board (AEDB) with guidelines for adopting these factors in order to achieve a high level of former satisfaction, thereby attracting rural farmers of certain regions to the sustainable development of biogas technology. The relevant institutional authorities must investigate the MBBP, FSFBP, EPB, and OSWBP in order to save farmers time, decrease costs and energy crises, and improve the living conditions of rural farmers who provide inexpensive biogas energy systems.

Based on respondents’ comments, this study also evaluates the financial benefits of biogas technology. Fifty-six percent of respondents (financiers of biogas plants) feel that biogas plants have decreased fuel prices, while 41% disagree. A recent study indicates a drop in gas prices (Negri et al. 2020 ). In addition, 36% of respondents (financiers of biogas plants) said their family’s financial status improved after constructing a biogas plant. Fifty-four percent of respondents (financiers of biogas plants) said their financial status had not changed. This difference is due to the number of family members and related expenses. In rural Pakistan, joint families save less, but nuclear households benefit more from equivalent contributions. Fifty-one percent of families could not retain their money owing to the causes above. The results of the present investigation are comparable to those of prior studies (Akter et al. 2021 ). In addition, the results of this research suggest that the availability of specialists and the elimination of maintenance barriers for biogas plants evaluating the adoption of biogas plants have a significant and favorable relationship with the development of supportable biogas technology. Current research verifies the results of a prior study stressing the importance of biogas plant technicians on farmers’ intent to employ biogas technology (Getachew et al. 2016 ). The current study reveals that technology for biogas plant components promotes biogas plant adoption and enhances biogas plant management by reducing installation barriers. In addition, the research results indicate that maintenance and financial government assistance substantially impact the adoption and motivation of biogas plants among farmers. This research reveals that government support for biogas plant maintenance has large societal and financial paybacks. These consequences confirm the conclusions of earlier investigation (Wang et al. 2020a ). This research demonstrates that management assistance for the operation and maintenance of biogas technology increases the likelihood that new farmers will embrace this technology and the demand for biogas plants.

After establishing a biogas plant, the customers’ expenditures have fallen considerably. Cost reduction is the most important adaptive element for partly pleased consumers at a given period. This variable implies that biogas plants may enhance the financial status of a family. After the construction of biogas plants, the environment is enhanced in several ways, including cleanliness and safety, a large reduction in fire incidents, and reduced smoke generation due to better health and cleaner kitchens. Thirty-five percent of respondents (financiers of biogas plants) reported a significant decrease in fire incidences. Seventeen percent of respondents claimed to be free of disease, which was connected with the absence of black filth in the kitchen and house, and 11% of respondents opted to reduce their regular expenditures on fitness. However, the key benefits of biogas plants are cleanliness and wellness. Forty-three percent of the interviewees did not reply to the questions.

Our research findings give vital information to rural Pakistanis and government/NGO staff. The study demonstrates that biogas facilities are well suited for rural areas of Punjab, Pakistan, reducing expenses and boosting economic growth and prosperity. Government and non-governmental organizations (NGOs) should commence the simultaneous deployment of biogas plants with comprehensive material on the fixing procedure to aid pastoral individuals and economic development. Adopting biogas plants positively and strongly correlates with technician availability and plant owner satisfaction in Pakistan. The owners of biogas plants must comply with biogas plant maintenance regulations to reduce production costs. In addition, the study reveals that knowledgeable and educated owners enjoy more financial and upkeep benefits than incompetent and uneducated owners. In addition, the research indicated that biogas facilities are more advantageous when both specialized knowledge and necessary equipment are readily available. Moreover, we recommend that the government of Pakistan INGOs and NGOs provide supports for biogas technology and financial expansion for native agrarians. Assume that one member of the biogas plant’s family is trained and capable of managing maintenance difficulties. In such a case, most problems may be resolved, and the family’s day-to-day expenses may drop. Instead of Faisalabad, the report recommended expanding biogas facilities to other regions of Punjab with government and NGO participation.

Conclusions and policy implications

Biogas is generally recognized as an effective energy source. The greatest barrier to installing modern biogas technology in Pakistan and additional small revenue nations is the growth rate of biogas plants. Although Pakistan’s government and many prominent INGOs and NGOs are attempting to make this technology acceptable by sponsoring biogas systems for home farmers, the acceptance rate among rural and village residents remains abysmally low. The main determination of this investigation is to assess the significant problems and maintenance obstacles Pakistani farmers encounter while establishing biogas systems. This study seeks to analyze the key features of biogas − installed plants in Pakistan to encourage biogas technology’s long-term growth. This report highlights Pakistan’s potential to attract investment in biogas technology for the supportable expansion of biogas drive. The energy choice theory indicates that the locals of this research region were more interested in using biogas in traditional farming practices than modern methods. Contrarily, the most challenging feature of biogas plants was their maintenance obstacles. Installation and building of biogas plants are generally driven by structure-based incentives, social subsidy benefits, present biogas plant owners as examples, and energy conservation. Although an increase in workload, gas leaks from connections, inadequate gas for cooking and lighting, complicated biogas plant operations, technical problems, and a shortage of easily accessible specialists are the most common reasons, they are not the only ones.

In conclusion, the current research reveals that all independent variables are important and favorably associated with rural Pakistan’s adoption of biogas technology, alleviating the energy crisis, and achieving cost-saving goals. Before installing biogas plants in rural areas of Pakistan, it is preferable and more pertinent to eliminate specific obstacles, according to the findings of this study. These obstacles include financial management, cost-effectiveness, capital investment return, and fixed component evaluation. The research findings will also demonstrate to the government the urgency with which it must share information about adopting biogas technology and initiate its future development initiatives. Table ​ Table6’s 6 ’s R 2 value for MBBP is 0.462, indicating that the current conceptual model has a high explanatory capacity for encouraging farmers in rural Pakistan to employ biogas plants. Q 2 yields a score of 0.231, indicating that the theoretical outline consumes strong and optimistic extrapolative value and proposing that the highlighted restrictions be resolved to enhance the possibility that biogas facilities would be constructed in rural Pakistan. Figure  1 of the model depicts the significant relationship between the selected variables and an EPB; the standards of the t measurement are outcome-oriented and greater than (1.64), indicating that the EPB has a positive and statistically significant impact on encouraging farmers in rural Pakistan to install biogas plants. The relevance of the moderated variable gives positive signals in the structural evaluation model, suggesting the existence of a substantial relationship.

Moreover, the current research demonstrated that the chosen criteria and their moderation in this conceptual model had a substantial and positive effect on the structural assessment model for developing biogas plants in rural Pakistan. In conclusion, customers did not assist the after-sales services offered by construction and installation businesses and bodies. The following suggestions are offered to the government of Pakistan about developing and promoting biogas technology in rural Pakistan. To encourage biogas plants, the government should develop an economic strategy for the maintenance barriers of renewable energy projects, capacity-building sessions, financial and technical assistance, and media complaints about maintenance. Biogas technology has the potential to reduce household energy shortages in rural Pakistan. Therefore, the appropriate NGO/INGO and the Pakistani government should conduct certain training measures to guarantee the sustainable development, maintenance, and social media awareness of rural biogas plants. Therefore, Pakistani government institutions and relevant INGO/NGOs should develop technical centers operated by trained professionals and provide after-sales services for the construction of biogas plants. Other elements that impact the adoption of biogas plants, like deficiency, biogas technology investors learning, the number of animals, the needed acreage, and other social and economic factors, have been largely ignored. Consequently, interested academics must determine the remaining components of biogas plant acceptance while reviewing the outcomes of this research. The researchers decided to establish a biogas technology in the pastoral zones of Pakistan, a growing nation. Therefore, the conclusions of the present research do not apply equally to industrialized and underdeveloped countries. Therefore, the authors must investigate the incentives for farmers in developed countries to use biogas plants in the future.

Tables ​ slurry67.599 9 and ​ benefits11.310 10

Author contribution

S.A: conceptualization, writing—original draft, formal analysis, data handling, variable construction, and methodology. Q.Y: supervision, funding acquisition. A. Razzaq: writing—review and editing. I. Khan: writing—review and editing. M. Irfan: conceptualization, writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Data availability

Declarations.

This research study was conducted according to the Declaration of Helsinki guidelines. The Institutional Review Board of Superior University has proved Pakistan (protocol code 815–5 on 27 November 2021).

Informed consent was obtained from all respondents belonging to this research study.

The authors declare no competing interests.

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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• Published: 15 December 2017

Biogas production from food waste via co-digestion and digestion- effects on performance and microbial ecology

• Mirzaman Zamanzadeh 1 , 2 , 3 ,
• Live Heldal Hagen 1 ,
• Kine Svensson 4 ,
• Roar Linjordet 4 &
• Svein Jarle Horn   ORCID: orcid.org/0000-0002-1590-9001 1  

Scientific Reports volume  7 , Article number:  17664 ( 2017 ) Cite this article

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• Applied microbiology
• Environmental biotechnology

In this work, performance and microbial structure of a digestion (food waste-only) and a co-digestion process (mixture of cow manure and food waste) were studied at mesophilic (37 °C) and thermophilic (55 °C) temperatures. The highest methane yield (480 mL/g VS) was observed in the mesophilic digester (MDi) fed with food waste alone. The mesophilic co-digestion of food waste and manure (McoDi) yielded 26% more methane than the sum of individual digestions of manure and food waste. The main volatile fatty acid (VFA) in the mesophilic systems was acetate, averaging 93 and 172 mg/L for McoDi and MDi, respectively. Acetate (2150 mg/L) and propionate (833 mg/L) were the main VFAs in the thermophilic digester (TDi), while propionate (163 mg/L) was the major VFA in the thermophilic co-digester (TcoDi). The dominant bacteria in MDi was Chloroflexi (54%), while Firmicutes was dominant in McoDi (60%). For the mesophilic reactors, the dominant archaea was Methanosaeta in MDi, while Methanobacterium and Methanosaeta had similar abundance in McoDi. In the thermophilic systems, the dominant bacteria were Thermotogae, Firmicutes and Synergistetes in both digesters, however, the relative abundance of these phyla were different. For archaea, the genus Methanothermobacter were entirely dominant in both TDi and TcoDi.

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Introduction.

Anaerobic digestion process has widely been employed for treatment of various organic wastes because the process can be used for production of value-added products such as an energy-rich gas and bio-fertilizer. This process is carried out by a complex microbial community which degrade various organic compounds into final products such as methane and carbon dioxide, collectively called biogas.

There are presently many research efforts worldwide on anaerobic digestion of food waste to improve process efficiency, stability and economic competitiveness. Studies of co-digestion of food waste generally found that inclusion of food waste was beneficial for methane yield 1 , 2 , 3 , while digestion processes with food waste as the sole substrate were often found to be unstable 3 , 4 , 5 . Several researchers have reported the benefits of using mixed feedstocks, including increased biogas production, enhanced degradation rates and higher digester capacity 1 , 6 , 7 . The beneficial effects of co-digestion are mostly related to a balanced availability of macro- and micronutrient required by the microbial community, optimal moisture content, buffer capacity and dilution of inhibitory or toxic compounds. Additionally, co-digestion may improve the process kinetics rather than the bioavailability of the feedstock. Ebner et al . 8 measured hydrolysis rates using bio-methane potential assays, and found that co-digestion increased hydrolysis rates when food waste and manure was co-digested compared to mono-digestion in BMP assays. The synergistic effect was attributed to dilution of inhibitory compounds and improved nutrient balance due to co-digestion 8 , 9 . The enzymes involved in hydrogenotrophic methanogenesis and syntrophic acetate oxidation requires trace elements such as selenium (Se), molybdenum (Mo) tungsten (W), cobolt (Co), nickel (Ni) and iron (Fe) 4 . Lack of these trace elements can limit the syntrophic acetate oxidation as well as formate oxidation 3 , 4 , 5 . The resulting accumulation of formate may again inhibit propionic acid oxidation. This will result in an overall acid accumulation, which eventually can cause the pH in the digester to drop, severely affecting or completely stopping the methanogenesis. Notably, the toxicity of intermediate compounds also increases with increasing temperature 10 and thermophilic digesters are commonly considered to be more prone to process inhibition than mesophilic digesters 7 . Moreover, anaerobic digestion processes operating at high-temperature often selects for a less diverse microbial community, which is more vulnerable to stress and operational changes 11 , 12 . Most studies in the literature have focused on enhancing functionality and operation of anaerobic co-digesters using food waste and other feedstocks. Several studies have compared performance of mesophilic and thermophilic digesters 2 , 3 , but comparison of community structures and diversity in anaerobic digesters and anaerobic co-digesters at these different temperatures are rare in the literature.

Accordingly, the aim of this study was to investigate the microbial structure of co-digestion of food waste and cow manure under mesophilic (37 °C) and thermophilic (55 °C) conditions. Additionally, we compared the microbial structure of the co-digestion process to that of food waste digestion alone to determine how the co-digestion process influences the microbial communities. Also, performance parameters were studied under the various conditions and it was attempted to explain performance efficiencies using microbial data.

Results and Discussion

Performance of the biogas reactors.

The average pH values for MDi, McoDi, TDi and TcoDi were 7.7 ± 0.1, 7.9 ± 0.1, 7.8 ± 0.2 and 8.2 ± 0.1, respectively. As illustrated in Fig.  1 , the average pH of McoDi and MDi was comparable, although slightly higher in McoDi. Notably, while the pH of TDi was similar to mesophilic processes, an elevated pH was clearly seen for TcoDi. This agrees with the higher ammonia concentrations in the co-digestion systems (McoDi and TcoDi), which were 16.5% and 13.7% higher than the MDi and TDi digesters, respectively (Fig.  2 ). Additionally, as shown in Fig.  1 , alkalinity was also higher in the co-digesters than the digestion systems. This is most likely due to the addition of manure, as manure typically has high content of nitrogen-bearing material 8 that are released as ammonia during the fermentation process and acts as a buffering system.

The pH and alkalinity in the various digesters, presented as an average of measurements over a period. For comparison, the values of pH and alkalinity in the mesophilic manure-only fed digester (MMD) is also presented.

Total ammonia and free ammonia concentrations in the digestion and co-digestion systems.

The degradation of organic material in all the digesters was measured in terms of TCOD removal (Fig.  3 ). Regardless of the operational temperature, the removal efficiencies were higher for the digestion systems (MDi: 73.0% and TDi: 66.4%) than the co-digesters (McoDi: 61.4% and TcoDi: 56.7%). This was expected due to a general high degradability of food waste 13 . MDi had the highest methane yield of all four digesters with 479.5 ± 33.9 ml CH 4 /g VS feed , which was 11.5%, 7.0% and 31.6% higher than the McoDi, TDi and TcoDi, respectively (Fig.  3 ). These results are in agreement with earlier studies reported elsewhere 8 , 14 . Additionally, lower methane production in the thermophilic reactors may be related to the presence of higher free ammonia concentrations that was, on average, 198 mg/L for TDi and 431 mg/L in TcoDi (Fig.  2 ), potentially causing inhibition of the methanogenesis process 15 .

TCOD concentrations in the influent (blue) and effluent (red) and average methane generation (grey) from each digester.

It has been observed that co-digestion of food waste and manure may enhance biogas production, and lead to more stable digestion processes 7 , 16 , 17 , 18 . We also observed higher methane production when we compared the methane yield of McoDi fed with the mixture of food waste and manure with that of manure-only fed mesophilic (37 °C) digester. The methane yields of manure-fed digester and McoDi were 133 ± 18 and 430 ± 28 mL CH 4 /g VS feed , respectively. Based on the measured specific methane yield from MDi and the manure-only reactor, the expected methane yield for McoDi without any synergistic effects would be 341 mL CH 4 /g VS feed . However, our results showed that the observed methane yield of McoDi was 430 mL CH 4 /g VS feed , meaning that the co-digestion of food waste and manure (McoDi) resulted in 26% higher methane production than the sum of digestions of individual substrates.

The solubilization values estimated for MDi, McoDi, TDi and TcoDi were 56, 55, 63 and 48%, respectively (see Equation  1 ). The highest solubilization extent was observed in the TDi (63%), although less methane was generated in this system as compared to MDi and McoDi (discussed above). It was also noticed that the SCOD fraction of the extent of solubilization in TDi was quite high (10%) and thus less solubilized compounds were converted into the final product methane. This accumulation of soluble COD was likely prompted by the higher degradability of the food waste as compared to manure. The SCOD accounted for 1, 2 and 6% of the solubilization extent in MDi, McoDi and TcoDi, respectively. Moreover, the TcoDi showed the lowest solubilization extent (48%), indicating less efficient solubilization of the substrate mixture. Additionally, when the SCOD results were compared between the digester sets (i.e., MDi vs. TDi and McoDi vs. TcoDi), it revealed that the SCOD was 10 and 4 times higher in the effluent of the TDi and TcoDi than those of MDi and McoDi. However, the effluent SCOD concentrations were statistically comparable in the mesophilic digester (932 ± 151) and co-digester (1537 ± 511) (p value  = 0.05).

Overall, both mesophilic digesters had low concentrations of volatile fatty acids (VFAs). Analysis of the VFAs measurements (Fig.  4 ) revealed acetate as the main VFA in the mesophilic digesters MDi and McoDi, which was, on average, 172 ± 61 and 93 ± 54 mg/L, respectively. The remaining VFAs detected in the mesophilic digesters, propionic, iso-butyric and butyric acids, were all below 50 mg/L (Fig.  4 ). Thus, it appeared that the fermenting and methanogenic processes were in balance preventing accumulation of intermediate products in MDi and McoDi. Low VFAs concentrations were reported for an anaerobic digester operated under mesophilic condition for food waste treatment 19 . The analysis of the VFA profiles (Fig.  4 ) revealed a totally different behavior in the thermophilic digester TDi and co-digester TcoDi. Acetate and propionate accumulated in TDi, averaging 2150 ± 208 and 833 ± 282 mg/L, respectively. These results were consistent with previous works reported in literature that under thermophilic condition increased concentrations of VFAs were observed, while mesophilic digesters were capable of achieving lower VFA concentrations 19 , 20 . As can be seen from Fig.  4 , the concentrations of total VFAs in TcoDi were less than 300 mg/L, in which propionate was the main VFA with an average concentration of 163 ± 27 mg/L. This difference in the VFA profile in TDi and TcoDi might be due to an improved synergistic performance of acetogens and methanogens in TcoDi that prevented the accumulation of the intermediate products and resulted in significantly lower concentrations of VFAs in TcoDi. The slow degradation of the manure which constituted 40% (on VS basis) of the feedstock in the co-digesters may also explain this difference.

Volatile fatty acids concentrations in ( A ): MDi; ( B ) McoDi; ( C ): TDi; and ( D ): TcoDi digestion systems.

Microbial composition of the mesophilic reactors

Statistical analysis demonstrated that the anaerobic co-digestion process resulted in a significantly (p value  < 0.005) higher microbial richness compared to the digesters fed with food waste alone (see Supplementary Fig.  S1 ). The major bacteria in both mesophilic digesters included Firmicutes , Chloroflexi , Bacteroidetes and Actinobacteria (Fig.  4 ). However, the distribution of these major bacteria in the digesters was different. Chloroflexi , which in the final phase constituted 54% of the sequences, was the dominant phylum in MDi, followed by 25% Firmicutes and 15% Bacteroidetes . Firmicutes (60% of the sequences in the final phase) was the dominant phylum in McoDi, while the relative abundance of Chloroflexi (22%) and Bacteroidetes (8%) was noticeably lower in McoDi than MDi. Additionally, the candidate phylum WWE1 was identified in McoDi and accounted for 5% of the relative abundance. Limam et al . 21 investigated the metabolic function of WWE1 members and suggested that the members of this division were involved in hydrolysis of cellulosic materials. WWE1 was also found in mesophilic co-digestion studies of manure with various agricultural residues 22 , 23 . Thus, the addition of cow manure to the co-digestion system seems to spur the growth of WWE1 members, probably involved in decomposition of cellulose content of the manure. It should be noted that WWE1 was not detected in the cow manure in the current study. The dominance of Chloroflexi in MDi (Fig.  5 ), which was mainly made up of the T78 group of family Anaerolinacea , was probably due to the presence of fermentable carbohydrates in the preprocessed food waste used (pasteurized at 70 °C). Anaerolinacea are mostly saccharolytic anaerobes and use a number of carbohydrates for growth 24 , 25 . Use of manure in the feedstock of the co-digestion systems resulted in a different relative abundance of bacterial communities in McoDi and prompted the prevalence of Firmicutes , which include members with very versatile metabolic characteristics and more potential to degrade the recalcitrant manure 26 , 27 . Firmicutes has been reported as one of the major microbial contributors in several studies carried out on anaerobic digesters, indicating that the phylum is common in both mesophilic and thermophilic processes 28 , 29 . Additionally, Firmicutes dominance has also been linked to better reactor performance 20 . The higher relative abundance of Bacteroidetes in MDi, which was fed with the preprocessed food waste, probably indicates involvement of their members in degradation of intermediate degradation products of carbohydrates and proteins.

Phylogenetic distribution of the 16S rRNA gene sequences in anaerobic digesters and co-digesters, presented at phylum level. The effect of co-digestion was tested at mesophilic (T37 °C) and thermophilic (T55 °C) temperature.

Notably, the relative abundance of Fimicutes increased in the final phase of McoDi compared to MDi. This could be due to the addition of manure which is a potential source of Firmicutes , as organisms belonging to this phylum dominated the microbial profile of the manure feedstock with 78% of all sequences (Fig.  5 ). To evaluate this, the genus level distribution of the sequences was investigated and a high diversity within the Firmicutes -phylum was noticed (Fig.  6A ). An unclassified genus of the family Tissierellaceae accounted for 32% of the sequences assigned to the phylum Firmicutes in the final phase of MDi, while this value was much lower in McoDi (11% of phylum) where the main genus was Clostridium (42% of phylum). In compliance, three OTUs assigned to Clostridium were significantly more abundant in McoDi compared to MDi (Supplementary Fig.  S2 , see also Fig.  7A ). Thus, it would appear that Firmicutes in general and Clostridium in particular played an important role in McoDi system. This genus was also represented in the cow manure samples, accounting for 9% of the Firmicutes -related sequences. A principle component analysis (PCA) was used to investigate possible links between microbiome and performance. Based on this analysis an association of Clostridium to the concentration of n-Butyrate was observed, although only low levels of butyrate were measured in both mesophilic digesters (Fig.  7B ). Notably, a correlation was observed between the abundance of Clostridium and the cow manure used in the feedstock mixture of the co-digestion system. It is therefore reasonable to believe that the increase in relative abundance of Clostridium in the co-digestion system was originated from the cow manure as a feedstock. It should nevertheless be mentioned that some Clostridium species can form endospores that enable them to tolerate moist heat 30 and pasteurization pretreatment applied on the food waste collected from the processing center. The food waste can therefore not be eliminated as a source of Clostridium . However, a carry-over from the cow manure used seems more likely due to the abovementioned increase of Clostridium in McoDi. This was further supported by the correlation of higher numbers of Clostridium with the addition of cow manure.

Phylogenetic distribution of the genera within ( A ) phylum Firmicutes and ( B ) phylum Euryarchaeota . Although all genera (>0.005% of total sequences) are included in the pie chart for Firmicutes , only the genera representing ≥1% of the sequences in at least one of the samples is included in the legend to reduce size. The most dominant genera are highlighted in bold type to ease the visual interpretation.

Relative abundance of the OTUs, classified at genus level or highest possible ranked taxonomic level ( A ), and their association with operational conditions and process variables in the mesophilic ( B ) and the thermophilic ( C ) digesters assessed through principal component analysis (PCA). The chemical variables included in the PCA plots are the values of NH 3 , CH 4 (ml/week), and VFAs (propionate; “Pro”, Acetate; “AC”, n-Butyrate; “n-Bu”, i-Butyrate; “i-Bu”, i-Valerate; “i-Va”). Only the most abundant taxa are annotated in the barchart to reduce the complexity. A comprehensive OTU table is supplied in the Electronical supplementary material, Table  S1 .

Archaea belonging to the phylum Euryarchaeota were dominated by Methanobacterium and Methanosaeta in both MDi and McoDi (Fig.  6B ). The genus distribution within this phylum was similar for initial and final phase in MDi, where Methanosaeta was dominant, constituting 53% and 62% (in initial and final phase, respectively) of the archaeal sequences. Methanosaeta was also prominent in the McoDi (43% and 36% in initial and final phase, respectively), yet significantly lower compared to MDi (Supplementary Fig.  S2 ). In addition to Methanobacterium and Methanosaeta , a noticeable portion of the methanogenic population was also assigned to the genus Methanobrevibacter in McoDi, with increasing relative abundance over time (from 7% of the archaeal sequences in the initial phase, to 22% in the final phase). Methanobrevibacter most likely originated from the manure used in this study as the analysis of manure samples showed Methanobrevibacter as the only dominant archaea (Fig.  6B ). While Methanosaeta is known as an acetate-utilizing methanogen, Methanobacterium and Methanobrevibacter both contain H 2 utilizing methanogens 31 , suggesting a mixed pathway for methane production in the mesophilic co-digestion system. The reason for the presence of high hydrogen utilizers might partly be due to slightly higher free ammonia observed in McoDi (81 mg/L vs. 50 mg/L in MDi) and partly due to the continual addition of Methanobrevibacter through manure. This agrees with previous studies indicating the dominance of hydrogen utilizing methanogens in manure-fed digesters 32 , 33 .

Microbial composition in the thermophilic digesters

The bacterial communities in TDi and TcoDi were mainly composed of the four phyla (relative abundancy >1%) Thermotogae , Firmicutes , Synergistetes and Bacteroidetes (Fig.  5 ). However, the relative abundance of these phyla was remarkably different within TDi and TcoDi, except for Bacteroidetes that accounted for 1–2% of the total sequences in both digesters. The profound effect of co-digestion on the bacterial community in the final phase of TcoDi was reflected by increased relative abundance of Firmicutes (62% of all sequences) and a decreased relative abundance of Thermotogae (15% of all sequences). In comparison, the relative abundance of Firmicutes and Thermotogae was 35% and 40% in the TDi, respectively. Notably, the distribution of Synergistetes , mainly represented by genus Anaerobaculum , differed significantly in the thermophilic digesters (Supplementary Fig.  S2 ), accounting 11% and 4% in the final phase of TDi and TcoDi, respectively. The members of this taxon fermentatively convert polypeptides and organic acids to acetate, H 2 and CO 2 34 . Compared to the initial phase, the relative abundance of Thermotogae increased over time in both thermophilic reactors, while the relative abundance of Firmicutes decreased only in TDi (Fig.  5 ). Similar to the mesophilic digesters, co-digestion of manure and food waste seemingly spurred the growth and dominance of Firmicutes in the TcoDi, while the digestion of food waste alone induced more even-distribution of Thermotoga and Firmicutes and supported the development of more Synergistetes in TDi.

While phylotypes assigned to genus Coprothermobacter accounted for more than 50% of the sequences assigned to Firmicutes in the initial samples of both TDi and TcoDi, this portion was largely reduced in the final phase (15% and 8% of Firmicutes , in TDi and TcoDi respectively). Instead, a more even distribution of several genera was observed in the final phase (Fig.  6A ), with prominence of Syntrophomonas (16% and 11% of Firmicutes , in TDi and TcoDi respectively), Thermactogenium (9% and 10% in TDi and TcoDi respectively) and unclassified phylotypes assigned to the candidate divisions SHA-98 (17% and 9% in TDi and TcoDi respectively) and MBA08 (8% and 28% in TDi and TcoDi respectively). Coprothermobacter is a proteolytic bacterium involved in the syntrophic fermentation of polypeptides, and the high dominance in the initial phase was most likely reflected by a strong dominance of the Coprothermobacter population in the seed culture from the FREVAR biogas plant, as reported in a previous study 35 . The OTUs assigned to genus Thermacetogenium were in all probability affiliated to Thermacetogenium phaeum 35 , a bacterium able to oxidize acetate syntrophically and grow acetogenically on organic acids and alcohols 36 , 37 .

The phylotype affiliated to candidate order MBA08 was noticeably higher in the TcoDi compared to TDi. This probably suggests the role of the members of the candidate group MBA08 in the co-digestion of food waste and manure. Li 38 also reported the candidate order MBA08 as one of the major bacterial groups in the thermophilic reactor of a staged system used for the co-digestion of whey and manure. However, none of the Firmicutes -associated sequences obtained from cow manure were related to MBA08 in the current study. On the contrary, the relative abundance of the candidate order SHA-98 was greater in the food waste-fed digester (i.e., TDi). There is almost no knowledge regarding the function of the members of the unclassified order SHA-98 and no genera could be assigned in this group.

Most of the phylotypes that could be assigned to a known genus in the order Clostridiales were probably involved in the degradation of polysaccharides, fermentable carbohydrates and syntrophic oxidation of saturated fatty acids 26 . Members of Syntrophomonas are believed to oxidize anaerobically C 4 -C 18 saturated fatty acids 39 . Clostridium consists of bacteria that display metabolic versatility 26 , 40 . Ruminococccaceae , Caldicoprobacteriaceae and Lachnospiraceae were less dominant families. Caldicoprobacter , which exclusively was represented by Caldicoprobacteriaceae in both digesters, ferments xylan and simple sugars to lactate, acetate, H 2 and CO 2 41 . Interestingly, the family Lachnospiracea , although less abundant, differed in the genus and was mainly composed of Butyrivibrio in TcoDi and of Coprococcus in TDi. Members of the Butyrivibrio and Coprococcus both use fermentable carbohydrates, however, the Butyrivibrio members are also involved in degradation of plant materials and are a major component of rumen microbiota 41 . The Butyrivibrio members probably came from cow manure and were able to retain their activities and growth in TcoDi.

Unlike the large diversity observed within Firmicutes , the second most dominant phylum, Thermotogae (Fig.  5 ), demonstrated very low diversity as almost all sequences were assigned to the candidate division Thermotoga S1. Notably, a clear difference was found in the relative abundance of this phylum in the final phase of TDi (40% of all sequences) and TcoDi (15% of all sequences). As described earlier 42 , the members of Thermotoga are capable to grow on the various simple (e.g., glucose) and complex (e.g., xylan and starch) polysaccharides. The lower abundance of Thermotoga species may explain the lower methane yield in the TcoDi (23% less) than the TDi, especially considering the higher amount of particulate COD (44% higher) that left the TcoDi as compared to that of the TDi. Presence of the higher particulate COD might be due to an inefficient conversion of the complex carbohydrates in the feed, in particular in the recalcitrant manure. Additionally, principle component analysis (Fig.  7C ) showed a correlation between the relative abundance of S1 and the concentrations of VFAs, indicating that the elevated concentrations of VFAs in TDi could be a cause-effect of an enhanced degradation of polysaccharides by Thermotoga S1. Furthermore, the free ammonia measured was 2.2 times greater in TcoDi (431 mg/L) than TDi (198 mg/L), suggesting that ammonium may possibly influence the abundance of the Thermotoga species 43 .

Overall, it would appear that the detection of higher relative abundance of 16S rRNA genes assigned to the genera Anaerobaculum , Coprothermobacter , Thermotoga and Syntrophomonas in TDi might indirectly imply an enhanced hydrolysis and acidogenesis of the food waste as compared to the co-digestion of food waste and manure. This might further be supported by the presence of significantly greater amount of VFAs (acetate, propionate and butyrate) in TDi than TcoDi (Fig.  4 ).

Analysis of the archaeal sequences (Fig.  6 ) showed that the process configuration (digestion vs. co-digestion) had little influence on the composition of methanogens and that the genus Methanothermobacter , which contains hydrogen utilizers, was almost entirely predominant in TDi and TcoDi. A correlation between Methanothermobacter and Coprothermobacter was observed, as well as an association with methane production (Fig.  7C ). Such co-existence has frequently been reported in literature, drawing a scenario of a synergic relationship where Coprothermobacter supply Methanothermobacter with hydrogen 44 . The dominance of Methanothermobacter agrees with a previous study on community structure in a thermophilic biogas plant (FREVAR), from where the inoculum was taken for the start-up of the thermophilic digesters used in this study 35 . The lack of Methanosaetaceae species reflected an unfavorable environment (e.g., high free ammonia content) for their activities in TDi and TcoDi, suggesting the prevalence of the hydrogenotrophic methanogensis pathway in both digesters. In addition to an unfavorable environment, the prevalence of Methanothermobacter members might be due to the improved hydrolysis and fermentation at the elevated temperature that required syntrophic reactions to efficiently convert intermediates such as H 2 and carboxylic organic acids.

The anaerobic digesters fed solely food waste performed better than the co-digesters (food waste and cow manure), most probably due to the addition of a more recalcitrant material in the form of cow manure in the co-digesters. Nevertheless, co-digestion resulted in a higher microbial diversity at both temperatures, compared to anaerobic digestion of food waste as sole substrate. This could be a reflection of the increased complexity of feedstocks in co-digestion, selecting for a richer microbial community. Although similar in the initial phase, the microbial community compositions diverged when cow manure was added at both temperatures. Based on our observations, we speculate that this variation is mostly explained by cow manure providing trace minerals and a balanced C/N ratio, rather than carry-over of microorganisms from the cow manure. However, the increased population Clostridium in both McoDi and TcoDi indicates that the establishment of this population is a direct result of microbiome transmission from the cow manure. Carry-over of methanogens from the cow manure, represented by Methanobrevibacter was also suggested for the mesophilic co-digestion system (McoDi), while only to a minor extent in the thermophilic co-digestion system (TcoDi). As higher microbial diversity often is associated with a microbiome that is more resilient to environmental changes and stress, co-digestion could potentially enhance the robustness of the anaerobic digestion process. Additionally, co-digestion at mesophilic temperature clearly showed a synergistic effect, yielded more methane than the digestion of manure-alone.

Materials and Methods

Food waste (FW) was shipped from Norsk Matretur AS (Norwegian food recycling, Finstadjordet, Norway), which is a central food waste pre-treatment plant which reduces particle size to <7 mm and sanitizes the waste at 70 °C for 1 hour, as required by Norwegian health regulations. Dairy cow manure was collected at the farm of the Norwegian University of Life Sciences (Ås, Norway). Both manure and FW were stored at 4 °C and diluted using tap water to achieve the targeted organic loading rate. The waste batch were characterized on a weekly basis to ensure a constant organic loading. The average characteristics of the substrates are shown in Table  1 .

Set up and operation of digesters

Four completely mixed reactors (Belach Bioteknik, Sweden) with a working volume of 6 L were used in this study. Two of the digesters were only fed with food waste, where one of them was kept at mesophilic temperature (37 ± 0.1 °C; MDi), while the other one was kept at thermophilic temperature (55 ± 0.1 °C; TDi). The Co-digestion systems consisted of one mesophilic co-digester (McoDi) and one thermophilic co-digester (TcoDi), which both were fed with a mixture of food waste and cow manure in a ratio of 60:40 on volatile solid (VS) basis. The start-up of the reactors was performed as previously described by Estevez et al . 45 . Seed sludge for the mesophilic reactors came from the Oslo EGE biogas plant (Nes, Norway); a full scale mesophilic anaerobic digester with food waste as its sole substrate. Seed sludge for the thermophilic reactors came from the FREVAR biogas plant (Fredrikstad, Norway); a full scale thermophilic reactor with sludge and food waste as its substrates. The feeding of the experimental reactors was done manually once per day, 6 days a week. Hydraulic retention time (HRT) and organic loading rate (OLR) for all the digesters were 20 days and 3 g VS/L/d, respectively. Temperature, pH, biogas volume and stirrer speed (set at 100 rpm) of the digesters were monitored and recorded online using BIOPHANTOM software (Belach Bioteknik, Sweden). Additionally, samples of the effluent were regularly taken to monitor the performance of the digesters and co-digesters.

Analytical methods

Total solids (TS), volatile solids (VS), total chemical oxygen demand (TCOD) and soluble chemical oxygen demand (SCOD) were measured following Standard Methods 46 . Chemical oxygen demand was measured using Merck Spectroquant® COD Cell test with measuring range 0.5–10 g/L. The extent of solubilization was calculated using Equation ( 1 ).

where COD CH4 is the COD equivalent of the CH 4 produced; SCOD is effluent soluble COD; SCOD in is influent soluble COD and PCOD in is the influent particulate COD.

Ammonium (NH 4 + ) was measured with an ammonium ion selective electrode according to the company’s manual (Orion 93; Thermoscientific, USA). Biogas composition was analyzed online for methane and carbon dioxide as previously described Zamanzadeh et al . 15 , with the use of an SRI gas chromatograph (Model 8610 C) equipped with a thermal conductivity detector (TCD, RCH3100, USA) and a 2 m Haysep-D column. Volatile fatty acids (VFAs) were determined by high-pressure liquid chromatography (HPLC; Dionex 3100, USA) with a Zorbax Eclipse Plus C18 column (150 × 2.1 mm column; 3.5 µm particles; Agilent, USA) as previously described by Zamanzadeh et al . 15 . The samples were centrifuged at 14000 rpm for 5 min, adjusted to pH < 2.5 using 95–98% H 2 SO 4 and then filtered through a 0.45 µm cellulose acetate syringe filter.

DNA extraction

Samples were collected for 16S rRNA gene sequencing during the initial stable phase of the anaerobic digestion (after 68 days) and in the final phase (after 152 days) from reactors MDi, McoDi, TDi and TcoDi, in addition to the cow manure used for co-digestion. Food waste was also sampled for the same purpose, but genomic DNA was not successfully recovered, likely due to the sanitization treatment (70 °C for 1 hour). All samples were frozen immediately after sampling, and stored at −20 °C until DNA extraction. For DNA extraction, thawed samples were centrifuged at 18 800 x g for 7 min. to remove the liquid. The pellet was then re-suspended in S.T.A.R buffer (Roche Diagnostics Corporation, USA) to stabilize nucleic acid and prevent bacterial growth. The suspension was vortexed followed by a subsequently slow spin to dissociate cells from large particles. The cell-containing suspension was transferred to FastPrep24 tubes with acidic washed glass beads for mechanical lysis. DNA was extracted using a commercial DNA extraction kit (LGC Genomics, UK), and DNA concentration measured with Qubit™ fluorometer and Quant-iT™ dsDNA BR Assay Kit (Invitrogen, USA). The DNA samples were stored at −20 °C until sequencing preparation.

16 S rRNA gene sequencing

The 16S rRNA gene amplicons were prepared for the Illumina MiSeq system (Illumina Inc.) as described in Zamanzadeh et al . 15 . In brief, 16S rRNA gene PCR amplification was carried out using the Pro341F/Pro805R primer set selected from Takahsahi et al . 47 modified with an Illumina adapter overhang in, and iProof HF DNA polymerase (BioRad, USA). A second PCR was carried out to attach unique 8-bp indices (Nextera XT Index Kit) to the Illumina sequencing adaptors to allow multiplexing of samples. A clean-up step (Agencourt AMPure XP beads, Beckman Coulter, USA) was preformed after each PCR. The amplicons were quantified (Quant-iT™ dsDNA HS Assay Kit and Qubit™ fluorometer, Invitrogen, USA), normalized and pooled to equimolar concentration, and then spiked with 30% PhiX control. A final concentration of 8 pm denaturated DNA was sequenced on an Illumina MiSeq instrument using the MiSeq reagent kit V3.

Sequencing analysis

All 16S rRNA gene sequences were processed using the QIIME version 1.8.0 software package 48 . Single-ends were trimmed to 200 bp and quality filtered as follows: only three sequential low-quality (Phred quality score <20) bases were allowed per sequence before truncating, and sequences with <75% (of total length) consecutive high-quality base calls were discarded. No N characters or barcodes were allowed in the sequence. Chimeric sequences were removed from the dataset using UCHIME incorporated in USEARH 49 and a threshold of 3% dissimilarity between 16S rRNA gene sequences was used to cluster sequences into de novo operational taxonomic units (OTUs) 49 . Taxonomy (up to rank ‘genus’) was assigned to each OTU using the uclust-based consensus taxonomy assigner implemented in QIIME with default parameters. Alpha rarefaction plot of the phylogenetic diversity was generated using the script alpha_rarefaction.py with default parameters in QIIME. Low abundant OTUs (those with a total count less than 0.005%) and singletons were filtered out. Statistical analysis and visualization was carried out using Calypso version 8.20 50 , 51 . The alpha diversity of the microbial communities was measured by OTU richness in addition to the Shannon index. The diversity were further compared with ANOVA to evaluate the significance between the different subgroups (digestion vs. co-digestion, mesophilic vs. thermophilic). ANOVA was also used to compare taxa abundance across the different digesters. Finally, associations between reactor performance and the community composition were assessed. For this, a principle component analysis (PCA) was applied to examine how much of the variance in the 16S rRNA gene sequencing dataset could explain the process variables (day-specific concentration of VFA and NH 3 , and weekly measurements of CH 4 production).

Data Availability

Sequence data are available at NCBI Sequence Read Archive under accession number SRP123045.

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Acknowledgements

This work was financially supported by the ENERGIX-program of the Research Council of Norway, grant no. 228747 (BiogasFuel).

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R.L., S.J.H. and M.Z. participated in the design of the study. M.Z. and K.S. carried out the reactor digestion experiments. L.H.H. carried out the microbial analyses and the bioinformatics. M.Z. wrote the original manuscript. All authors read, revised and approved the final manuscript.

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Zamanzadeh, M., Hagen, L.H., Svensson, K. et al. Biogas production from food waste via co-digestion and digestion- effects on performance and microbial ecology. Sci Rep 7 , 17664 (2017). https://doi.org/10.1038/s41598-017-15784-w

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DOI : https://doi.org/10.1038/s41598-017-15784-w

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An Overview of Biogas Production: Fundamentals, Applications and Future Research

2019, International Journal of Energy Economics and Policy

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Biogas, a renewable source of energy has been the focus of research for the past decades. It is simple to produce and environmentally friendly. Due to the current increase in population, emission of greenhouse gases and the UN concern to achieve 100% renewable energy globally by 2050, the use of biogas for electricity and for combined heat and power is the surest way forward. Anaerobic digestion thus far has been the surest way to achieve in the production of this renewable energy. The process, however, involves the consortium of microorganisms to breakdown feedstocks such as food waste and agricultural biomass through a complex pathway to generate mainly the methane and carbon dioxide. Feedstocks utilized by researchers from the past decades include water hyacinth, wood chips, corn silage, food wastes, and sugarcane bagasse. Process parameters that influence the anaerobic digestion process include pH, temperature, organic loading rate, feedstock type, mixing, hydraulic retention time, and the carbon to nitrogen ratio. This paper reviews the scope of biogas production from the anaerobic digestion process and details the various parameters affecting the process.

antony raja

In 21 st century, sustainable development has a colossal and crucial role to play in global environmental apprehensions such as GHG emission from fossil fuel combustion, damage to the environment by the haphazard disposal of waste. Under these current circumstances, biogas production technology has flourished and has proved to be a meritorious success story today. Biogas is produced by microbial anaerobic digestion of organic wastes such as animal waste, plant material, sewage crops etc. Biogas principally comprises of 50% -60% of methane and 25%-45% of CO2. In the recent past, research on this technology has been limited to some extent due to the complex phenomenon existed with various factors and parameters influencing it. Optimization of parameters like organic loading rate, pH, C/N ratio, total solids, volatile solids content hydraulic retention time and temperature of the digester will have a synergistic effect on the yield. Adopting the principle of co-digestion, for biogas pr...

Applied Microbiology and Biotechnology

Esteban Amon

Anaerobic digestion of energy crops, residues, and wastes is of increasing interest in order to reduce the greenhouse gas emissions and to facilitate a sustainable development of energy supply. Production of biogas provides a versatile carrier of renewable energy, as methane can be used for replacement of fossil fuels in both heat and power generation and as a vehicle fuel. For biogas production, various process types are applied which can be classified in wet and dry fermentation systems. Most often applied are wet digester systems using vertical stirred tank digester with different stirrer types dependent on the origin of the feedstock. Biogas is mainly utilized in engine-based combined heat and power plants, whereas microgas turbines and fuel cells are expensive alternatives which need further development work for reducing the costs and increasing their reliability. Gas upgrading and utilization as renewable vehicle fuel or injection into the natural gas grid is of increasing interest because the gas can be used in a more efficient way. The digestate from anaerobic fermentation is a valuable fertilizer due to the increased availability of nitrogen and the better short-term fertilization effect. Anaerobic treatment minimizes the survival of pathogens which is important for using the digested residue as fertilizer. This paper reviews the current state and perspectives of biogas production, including the biochemical parameters and feedstocks which influence the efficiency and reliability of the microbial conversion and gas yield.

Applied Sciences

Fabio Napolitano

The production of biogas from anaerobic digestion (AD) of residual agro-food biomasses represents an opportunity for alternative production of energy from renewable sources, according to the European Union legislation on renewable energy. This review provides an overview of the various aspects involved in this process with a focus on the best process conditions to be used for AD-based biogas production from residual agro-food biomasses. After a schematic description of the AD phases, the biogas plants with advanced technologies were described, pointing out the strengths and the weaknesses of the different digester technologies and indicating the main parameters and operating conditions to be monitored. Subsequently, a brief analysis of the factors affecting methane yield from manure AD was conducted and the AD of fruit and vegetables waste was examined. Particular attention was given to studies on co-digestion and pre-treatments as strategies to improve biogas yield. Finally, the se...

Antonio Comparetti , Santo Orlando

Kiros Hagos

A B S T R A C T Globally, there is increasing awareness that renewable energy and energy efficiency are vital for both creating new economic opportunities and controlling the environmental pollution. AD technology is the biochemical process of biogas production which can change the complex organic materials into a clean and renewable source of energy. AcoD process is a reliable alternative option to resolve the disadvantages of single substrate digestion system related to substrate characteristics and system optimization. This paper reviewed the research progress and challenges of AcoD technology, and the contribution of different techniques in biogas production engineering. As the applicability and demand of the AcoD technology increases, the complexity of the system becomes increased, and the characterization of organic materials becomes volatile which requires advanced methods for investigation. Numerous publications have been noted that ADM1 model and its modified version becomes the most powerful tool to optimize the AcoD process of biogas production, and indicating that the disintegration and hydrolysis steps are the limiting factors of co-digestion process. Biochemical methane potential (BMP) test is promising method to determine the biodegradability and decomposition rate of organic materials. The addition of different environmentally friendly nanoparticles can improve the stability and performance of the AcoD system. The process optimization and improvement of biogas production still seek further investigations. Furthermore, using advanced simulation approaches and characterization methods of organic wastes can accelerate the transformation to industrializations, and realize the significant improvement of biogas production as a renewable source and economically feasible energy in developing countries, like China. Finally, the review reveals, designing and developing a framework, including various aspects to improve the biogas production is essential.

Bioresource Technology Reports

Fatihah Suja

Elsevier eBooks

Gerasimos Lyberatos

Zenodo (CERN European Organization for Nuclear Research)

Himanshu Rajput

Results in Chemistry

Hamidreza Sayadi

Biogas is obtained from the breakdown of biomass by microorganisms and bacteria in the absence of oxygen. Biogas is considered a renewable source of energy, similar to solar energy and wind energy. Biogas can be produced from biomass or bio-waste; thus, it is environmentally friendly. Biogas is obtained in a suspended monoxide decomposition process by anaerobic bacteria or in a fermentation process of decomposable materials such as agricultural manure, sewage, municipal waste, green waste (gardens and parks), plant material and agricultural products. Biogas is a renewable natural energy source that leaves effective effects on nature and industries. This gas is produced from the decomposition of organic materials, including animal manure, food waste and sewage. Fertilizers and waste produce biogas through anaerobic digestion (ie without the presence of oxygen). Biogas is a mixture of gases generated by decaying biodegradable material without the presence of oxygen. Its main contents are 50–70 % of methane (CH4) by volume, 30–50 % of carbon dioxide (CO2), and traces of other gases, like hydrogen sulfide (H2S) and water vapor (H2O). CO2, H2S, and water vapor content in biogas may affect the performance and life of the energy conversion devices; consequently, their removal before end-use is essential for improving the quality of biogas. This combination is an ideal option for making renewable energy. The most important advantages of biogas (production of energy, reduction of the amount of discarded waste, reduction of pathogens, conversion of waste containing organic matter into high quality fertilizer, protection of vegetation, soil, water, increasing productivity in the field of livestock and agriculture) and It is also one of the disadvantages of biogas (incomplete and small technologies, containing impurities, the effect of temperature on biogas production, unsuitable for urban and dense areas, not affordable). For economical use of biogas, the fermentation process can be carried out under controlled conditions in a relatively simple device called a digestion reservoir. This review summarizes the current state-of-the-art and presents future perspectives related to the anaerobic digestion process for biogas production. Moreover, a historical retrospective of biogas sector from the early years of its development till its recent advancements give an outlook of the opportunities that are opening up for process optimization.

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Study reveals the benefits and downside of fasting

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Low-calorie diets and intermittent fasting have been shown to have numerous health benefits: They can delay the onset of some age-related diseases and lengthen lifespan, not only in humans but many other organisms.

Many complex mechanisms underlie this phenomenon. Previous work from MIT has shown that one way fasting exerts its beneficial effects is by boosting the regenerative abilities of intestinal stem cells, which helps the intestine recover from injuries or inflammation.

In a study of mice, MIT researchers have now identified the pathway that enables this enhanced regeneration, which is activated once the mice begin “refeeding” after the fast. They also found a downside to this regeneration: When cancerous mutations occurred during the regenerative period, the mice were more likely to develop early-stage intestinal tumors.

“Having more stem cell activity is good for regeneration, but too much of a good thing over time can have less favorable consequences,” says Omer Yilmaz, an MIT associate professor of biology, a member of MIT’s Koch Institute for Integrative Cancer Research, and the senior author of the new study.

Yilmaz adds that further studies are needed before forming any conclusion as to whether fasting has a similar effect in humans.

“We still have a lot to learn, but it is interesting that being in either the state of fasting or refeeding when exposure to mutagen occurs can have a profound impact on the likelihood of developing a cancer in these well-defined mouse models,” he says.

MIT postdocs Shinya Imada and Saleh Khawaled are the lead authors of the paper, which appears today in Nature .

Driving regeneration

For several years, Yilmaz’s lab has been investigating how fasting and low-calorie diets affect intestinal health. In a 2018 study , his team reported that during a fast, intestinal stem cells begin to use lipids as an energy source, instead of carbohydrates. They also showed that fasting led to a significant boost in stem cells’ regenerative ability.

However, unanswered questions remained: How does fasting trigger this boost in regenerative ability, and when does the regeneration begin?

“Since that paper, we’ve really been focused on understanding what is it about fasting that drives regeneration,” Yilmaz says. “Is it fasting itself that’s driving regeneration, or eating after the fast?”

In their new study, the researchers found that stem cell regeneration is suppressed during fasting but then surges during the refeeding period. The researchers followed three groups of mice — one that fasted for 24 hours, another one that fasted for 24 hours and then was allowed to eat whatever they wanted during a 24-hour refeeding period, and a control group that ate whatever they wanted throughout the experiment.

The researchers analyzed intestinal stem cells’ ability to proliferate at different time points and found that the stem cells showed the highest levels of proliferation at the end of the 24-hour refeeding period. These cells were also more proliferative than intestinal stem cells from mice that had not fasted at all.

“We think that fasting and refeeding represent two distinct states,” Imada says. “In the fasted state, the ability of cells to use lipids and fatty acids as an energy source enables them to survive when nutrients are low. And then it’s the postfast refeeding state that really drives the regeneration. When nutrients become available, these stem cells and progenitor cells activate programs that enable them to build cellular mass and repopulate the intestinal lining.”

Further studies revealed that these cells activate a cellular signaling pathway known as mTOR, which is involved in cell growth and metabolism. One of mTOR’s roles is to regulate the translation of messenger RNA into protein, so when it’s activated, cells produce more protein. This protein synthesis is essential for stem cells to proliferate.

The researchers showed that mTOR activation in these stem cells also led to production of large quantities of polyamines — small molecules that help cells to grow and divide.

“In the refed state, you’ve got more proliferation, and you need to build cellular mass. That requires more protein, to build new cells, and those stem cells go on to build more differentiated cells or specialized intestinal cell types that line the intestine,” Khawaled says.

Too much of a good thing

The researchers also found that when stem cells are in this highly regenerative state, they are more prone to become cancerous. Intestinal stem cells are among the most actively dividing cells in the body, as they help the lining of the intestine completely turn over every five to 10 days. Because they divide so frequently, these stem cells are the most common source of precancerous cells in the intestine.

In this study, the researchers discovered that if they turned on a cancer-causing gene in the mice during the refeeding stage, they were much more likely to develop precancerous polyps than if the gene was turned on during the fasting state. Cancer-linked mutations that occurred during the refeeding state were also much more likely to produce polyps than mutations that occurred in mice that did not undergo the cycle of fasting and refeeding.

“I want to emphasize that this was all done in mice, using very well-defined cancer mutations. In humans it’s going to be a much more complex state,” Yilmaz says. “But it does lead us to the following notion: Fasting is very healthy, but if you’re unlucky and you’re refeeding after a fasting, and you get exposed to a mutagen, like a charred steak or something, you might actually be increasing your chances of developing a lesion that can go on to give rise to cancer.”

Yilmaz also noted that the regenerative benefits of fasting could be significant for people who undergo radiation treatment, which can damage the intestinal lining, or other types of intestinal injury. His lab is now studying whether polyamine supplements could help to stimulate this kind of regeneration, without the need to fast.

“This fascinating study provides insights into the complex interplay between food consumption, stem cell biology, and cancer risk,” says Ophir Klein, a professor of medicine at the University of California at San Francisco and Cedars-Sinai Medical Center, who was not involved in the study. “Their work lays a foundation for testing polyamines as compounds that may augment intestinal repair after injuries, and it suggests that careful consideration is needed when planning diet-based strategies for regeneration to avoid increasing cancer risk.”

The research was funded, in part, by a Pew-Stewart Trust Scholar award, the Marble Center for Cancer Nanomedicine, the Koch Institute-Dana Farber/Harvard Cancer Center Bridge Project, and the MIT Stem Cell Initiative.

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A new study led by researchers at MIT suggests that fasting and then refeeding stimulates cell regeneration in the intestines, reports Katharine Lang for Medical News Today . However, notes Lang, researchers also found that fasting “carries the risk of stimulating the formation of intestinal tumors.” 

MIT researchers have discovered how fasting impacts the regenerative abilities of intestinal stem cells, reports Ed Cara for Gizmodo . “The major finding of our current study is that refeeding after fasting is a distinct state from fasting itself,” explain Prof. Ömer Yilmaz and postdocs Shinya Imada and Saleh Khawaled. “Post-fasting refeeding augments the ability of intestinal stem cells to, for example, repair the intestine after injury.” 

Prof. Ömer Yilmaz and his colleagues have discovered the potential health benefits and consequences of fasting, reports Max Kozlov for Nature . “There is so much emphasis on fasting and how long to be fasting that we’ve kind of overlooked this whole other side of the equation: what is going on in the refed state,” says Yilmaz.

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Researcher discusses two measures that predict effective managers

by Liz Mineo, Harvard Gazette

Good managers are hard to find. Most companies pick managers based on personality traits, age, or experience—and according to a recent National Bureau of Economic Research working paper , they may be doing it wrong.

Co-authored by David Deming, Isabelle and Scott Black Professor of Political Economy at Harvard Kennedy School, the study concludes that companies are better off when they select managers based on two measures highly predictive of leadership skills .

The Gazette talked to Deming about the study's findings. This interview has been edited for length and clarity.

What are the qualities that make a good manager, and why is it so hard to find them?

Being a good manager requires many different qualities that often don't exist in the same person. First is the ability to relate well to others, to create what Amy Edmondson and others have called psychological safety, meaning the ability to make people feel stable and secure in their role so they are comfortable with critical feedback. That's a key component of being a good manager.

Communication skills are also essential. As a manager, you should know that there's not one good way to deliver feedback to your workers because the words you use and the way you frame your statements also matter.

At the same time, you must also be analytically minded and open to different ways of doing things and be able to take a step back and reassess whether your team or organization is working as well as it could be.

Overall, being a good manager requires both interpersonal skills and analytical skills. You also need to have a strategic vision—which is something that our study does not capture. Managers must have a sense of what their organization is trying to accomplish. Any one of those skills is hard to find. Having all three, and knowing when to use them, is even more difficult.

One of the paper's most surprising findings is that people who self-nominate to be managers perform worse than those randomly assigned. Why is that?

In the study, we randomly assign the role of manager. That was half of the experiment. In the other half, we asked people which role they wanted, and we assigned the role of manager to the people with the greatest preferences for being in charge.

We found that people with the greatest preference for being in charge are, on average, worse than randomly assigned managers. It's hard to know exactly why because there are a lot of factors in play, but we show evidence in the paper that they are overconfident in their own capabilities, and they think they understand other people better than they do. We all know people like that.

This was a surprising finding. And it's important, because interest in leadership plays a big role in how companies pick managers. Companies have their own hiring and employee evaluation policies of course—they don't pick managers randomly like we did—but it's surely true that preference for leadership plays a big part in who gets promoted to management.

For example, we find that men are much more likely to prefer being in charge, but they aren't any more effective than women in the role of manager.

The main lesson I take from this finding is that there's a big difference between preferences and skills; just because you want to be a manager doesn't mean you're going to be good at it. Organizations that take more scientific or analytical approaches to identifying good managers are going to come out ahead.

What are the best predictors for selecting a good manager, according to your paper?

It has nothing to do with how a person looks, how they speak, or what their preferences or personality traits are. None of those things are predictive. There are only two things that are: One is IQ as measured by the Raven's Progressive Matrices test, which measures general and fluid intelligence, spatial reasoning, problem-solving , etc.

But the one that's more interesting to me is a measure of what we call economic-decision-making skill, or the ability to allocate resources effectively, that my co-authors and I created in a different paper. We use that very same measure in this experiment, and we found that it is highly predictive of being a good manager.

Why do you think these two tests predict being a good manager, but other traits like age, experience, personality, or gender do not?

If you want to predict who's going to be going to be good at a specific performance task, in this case, managing a team to solve a problem, the best predictors are most closely related to what you're asking someone to do.

What matters is the ability to make decisions about the allocation of resources under time constraints ; how to organize and motivate the members of your team to produce the most output. The lesson for me is that it's a crutch to use personality traits and preferences to predict performance because they're not that closely related to the performance you're interested in.

We see this pattern elsewhere. There's a huge amount of research literature on figuring out who's going to be a good teacher in the classroom, and study after study finds that characteristics such as age, gender, education, SAT scores, college major don't do a very good job of predicting who's going to be a good teacher.

Yet if I put you in the classroom for a little bit of time and I see how much you improve student learning, that is a very good predictor, because it's very closely related to the thing you ask people to do. If you want to know who's going to be a good manager, make them manage. Don't just rely on personality characteristics, or whether they raise their hand to say, "I want to do it."

Why is it important to have good managers?

At the broadest level, it's important to have good management because companies, universities, and other organizations face such an open-ended strategic landscape. They must tackle a variety of issues, such as where they should direct their attention, what are the most important things to focus on, and how to deploy resources toward solving certain problems.

If you look at major corporations , they tend to be conglomerates that have many different divisions that do many different things. Google, just to give one example, in the beginning had a core product: a search engine. But now Google is Alphabet, and it still does search, but it also does venture investing, autonomous driving, drug discovery, and many other things.

If you zoom down to the micro level, a manager who leads a team of three or four employees faces the same sort of problems: What should I focus on? Who's going to do what? How do I give people feedback? What are each person's strengths and weaknesses?

To be an effective manager, you must think about how to assign workers to roles to achieve the greatest success, and you must know how to communicate with a person to help them improve. The skill of being a good manager is probably underappreciated. Good managers are not necessarily the most vocal leaders; sometimes they're quiet but effective, like diamonds in the rough.

The paper you and your co-authors wrote came up with a novel method to identify good managers. Can you explain?

It's a hard problem to solve, because part of what makes a good manager is the people they're supervising. If you give a manager a team of workers who aren't very capable, that team is going to do a poor job, and if the workers are all-stars, they will make the manager look good regardless. In other words, when a team succeeds, we don't know how much credit or blame to assign to the manager compared to other members of the team.

To solve that problem, we bring a bunch of people into a controlled lab setting, and we assign them a group task that they must do together. We randomly assign the role of manager to one of the three people on the team, and we ask them to lead their group in the task, and we see how well they do. Then we randomly assign each manager again to another group of workers.

Each time, as a manager, you're getting a different set of people, so we have a way to account for the quality of the workers you're getting. And since we're assigning workers, we can also identify who's a good worker because we can see their performance with different managers.

What do you think the paper's main contributions are to the literature of leadership and management in general?

I think the paper's main contribution is to open the door to the idea that we can be scientific and analytical about selecting managers and that management is not a squishy thing that we can never get our arms around.

We can measure management skill, and measuring it well unlocks huge productivity gains for organizations and for people. We're doing this experiment in a lab; it's not a real-world setting, but we are in talks with several folks to do this in the field. I do think it would work because we're asking people to manage and we're measuring their performance, and we're showing you that there's a repeatable predictive quality to this.

Our contribution is to outline a very simple methodology for measuring who's a good manager, and to say to people that they can use it. Figure it out in your own organization, and you will unlock big productivity gains.

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