Asia has the world's largest population and the largest number of biogas digesters, with implementation across 25 countries. These countries can be categorised into four groups based on their biogas ...development status. Asia has approximately 45.03 million biogas digesters, of which about 99.72% are household units and 0.28% are industrial digesters. Predominantly located in less developed rural areas, a substantial number of household digesters have ceased operation or been abandoned. Some Asian countries and regions are witnessing a transition from household to industrial digesters, driven by economic growth and favourable environmental policies. However, many industrial digesters smaller than 500 m3 are underperforming, unprofitable, or inactive. Larger digesters are better managed and more sustainable. From 1958 through 2023, 163 biogas safety incidents were recorded in seven Asian countries, resulting in 321 fatalities, 220 injuries, and substantial property damage. This study identifies and discusses seven key factors influencing biogas development in Asia: climate conditions, energy demand, biowaste resources, economic development, government policy, technical service, and biogas programs. These factors range from objective and independent to external dependencies and direct, dynamic influences. Future biogas development in Asia will benefit from favourable technoeconomic growth and increased climate change awareness, supported by societal priorities and government policies. However, it must also confront and address several significant challenges.
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•Biogas development activities have been in 25 Asian countries.•Asia has approximately 45.03 million biogas digesters and 99.72% are household units.•From 1958 through 2023, 163 biogas accidents resulted in 321 deaths and 220 injuries.•Seven key factors influence biogas development in Asia.•Future biogas development is optimistic, but challenges must be addressed.
•A Fuzzy Comprehensive Evaluation (FCE) method for animal environment was developed.•Data from two swine buildings were evaluated for multi-factor environment with FCE.•Predetermined weights were ...chosen using the Analytic Hierarchy Process.•A swine building environmental quality assessment index system was built and used.•The FCE achieved an integration evaluation compared with Single Factor Evaluation.
In confined swine buildings, temperature, humidity, and air quality are all important for animal health and productivity. However, the current swine building environmental control is only based on temperature; and evaluation and control methods based on multiple environmental factors are needed. In this paper, fuzzy comprehensive evaluation (FCE) theory was adopted for multi-factor assessment of environmental quality in two commercial swine buildings using real measurement data. An assessment index system and membership functions were established; and predetermined weights were given using analytic hierarchy process (AHP) combined with knowledge of experts. The results show that multi-factors such as temperature, humidity, and concentrations of ammonia (NH3), carbon dioxide (CO2), and hydrogen sulfide (H2S) can be successfully integrated in FCE for swine building environment assessment. The FCE method has a high correlation coefficient of 0.737 compared with the method of single-factor evaluation (SFE). The FCE method can significantly increase the sensitivity and perform an effective and integrative assessment. It can be used as part of environmental controlling and warning systems for swine building environment management to improve swine production and welfare.
In the past 25 years, we have conducted more than 20 laboratory and field studies related to hydrogen sulfide (H2S) in animal production. From millions of first-hand and real-world H2S data points, ...we found that sulfur (S) source, release mechanism, and ventilation are three critical factors affecting toxic H2S concentrations. Source of S determines how much H2S mass can be potentially produced. Sulfur in water for animal drinking and barn cleaning can be a more important S source than S from animal feed and can cause extremely high H2S concentrations. Release of H2S from liquid swine manure exhibits a dynamic mechanism of Bubble Release and Reservoir Effect. High H2S concentrations induced by manure disturbance and sudden H2S release depend on the amount of H2S that has been trapped in manure gas bubbles. Release patterns of H2S are complicated and irregular and are difficult to predict. Ventilation or air exchange dilutes the H2S mass in a defined space. The importance of ventilation, especially during manure operations, cannot be over-emphasized. Insufficient ventilation has claimed many deaths and injuries of farm workers and animals.
•Three factors affecting toxic H2S concentrations on swine farms are discussed.•Sulfur in water is more important than sulfur in feed for H2S generation.•A H2S Bubble Release mechanism impacts dynamic H2S concentrations.•Ventilation is critical to lower H2S concentrations and keep healthy and safe.
Abstract
Hydrogen sulfide (H
2
S) is the most undesirable inorganic gas in biogas from anaerobic digestion (AD). However, H
2
S production in AD is complex and understanding of its processes is still ...limited. This study performed six controlled batch anaerobic co‐digestion experiments to investigate H
2
S production. Materials were obtained from four field anaerobic digester systems and co‐digestion feedstocks from agroindustry. An additional precipitation experiment was conducted to further examine H
2
S production dynamics. Digesters containing highly soluble, carbohydrate‐based wastes had a high H
2
S final specific production (FSP) value. Additionally, the FSP values were negatively correlated with the initial Fe(II):S ratios in the digester liquid of the batch tests. The precipitation experiment indicated that iron sulfide precipitation was preferred in the presence of an anaerobic community. The H
2
S production as a time series was successfully modeled using a generalized additive model (
R
2
> 0.82). This study revealed that sulfate, phosphorus, and iron concentrations are important predictors and potential inhibitors of H
2
S production in AD. Further examination of real‐time H
2
S modeling in AD is warranted.
•A prediction model of ammonia emission was built based on the indoor ammonia concentration prediction model using ANFIS.•Five kinds of membership functions were compared to get a well fitted ...prediction model.•Compared with the BP and MLRM model, the ANFIS prediction model with “gbell” membership function has the best performances.
Ammonia (NH3) is considered one of the significant pollutions contributor to indoor air quality and odor gas emission from swine house because of the negative impact on the health of pigs, the workers and local environment. Prediction models could provide a reasonable way for pig industries and environment regulatory to determine environment control strategies and give an effective method to evaluate the air quality. The adaptive neuro fuzzy inference system (ANFIS) simulates human’s vague thinking manner to solve the ambiguity and nonlinear problems which are difficult to be processed by conventional mathematics. Five kinds of membership functions were used to build a well fitted ANFIS prediction model. It was shown that the prediction model with “Gbell” membership function had the best capabilities among those five kinds of membership functions, and it had the best performances compared with backpropagation (BP) neuro network model and multiple linear regression model (MLRM) both in wintertime and summertime, the smallest value of mean square error (MSE), mean absolute percentage error (MAPE) and standard deviation (SD) are 0.002 and 0.0047, 31.1599 and 23.6816, 0.0564 and 0.0802, respectively, and the largest coefficients of determination (R2) are 0.6351 and 0.6483, repectively. The ANFIS prediction model could be served as a beneficial strategy for the environment control system that has input parameters with highly fluctuating, complexity, and non-linear relationship.
Large variabilities in ammonia (NH3) released from animal manure and emitted from different livestock buildings were frequently reported, but the factors influencing the emissions were not ...sufficiently investigated. In this paper, continuously monitored data of NH3 emissions and other relevant environmental variables under controlled conditions in a 12-room experimental swine building for a 155-d complete wean-to-finish cycle were studied. Measurement data mining was conducted at both spatial and temporal dimensions using panel data analysis with heterogeneous time trends. The pig diet, total pig weight, and the pit air temperature were identified as the major influencing factors for the variabilities by using multivariate linear regression. Two unidentified factors that imposed substantial influences on the NH3 emission variabilities were predicted. They were most possibly related to variations in microenvironment and microbial activity inside the manure in the pit. The results suggest necessary future research to identify physical properties of the new NH3 emissions factors in microbiological and biochemical processes.
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•Data of 155 days ammonia (NH3) emissions from a research swine building were mined.•Pig diet, total pig weight, and pit air temperature were identified as the major influencing factors.•Two unidentified factors influencing NH3 emissions were predicted using panel data analysis.
There was an increasing interest in reducing production and emission of air pollutants to improve air quality for animal feeding operations (AFOs) in the U.S. in the 21st century. Research was ...focused on identification, quantification, characterization, and modeling of air pollutions; effects of emissions; and methodologies and technologies for scientific research and pollution control. Mitigation effects were on pre-excretion, pre-release, pre-emission, and post-emission. More emphasis was given on reducing pollutant emissions than improving indoor air quality. Research and demonstrations were generally continuation and improvement of previous efforts. Most demonstrated technologies were still in a limited scale of application. Future efforts are needed in many fundamental and applied research areas. Advancement in instrumentation, computer technology, and biological sciences and genetic engineering is critical to bring major changes in this area. Development in research and demonstration will depend on the actual political, economic, and environmental situations.
•More emphasis was placed on pollutant emissions than indoor air quality.•Basic research dedicated to new pollutants, modeling, and baseline emissions.•Applied research focused on developing monitoring and mitigation technologies.•Field demonstrations combined with projects to evaluate new mitigation approaches.•Future efforts are needed in many fundamental and applied research areas.
Different scales of basic and applied research were conducted and 15 mitigation technologies were demonstrated. Future work is needed in many fundamental and applied research areas.
Abstract
Digester acclimatization can improve the efficiency of anaerobic digestion (AD), a potentially sustainable process for generating biogas from the biological decomposition of organic ...byproducts from biodiesel production. This study examined the impact of acclimatization rate on biogas production and conversion efficiency in laboratory digesters using inocula from a wastewater treatment plant digester and from an agro‐industrial waste digester. The results showed that co‐digestion of crude glycerol and biodiesel wastewater at high organic loading rates, up to 6.8 g chemical oxygen demand (COD) L
−1
day
−1
, is possible without the addition of other substrates or pretreatment. Higher organic loading rates were achieved in the digesters using inocula from the agro‐industrial waste digester than in the digesters using the wastewater treatment plant digester, indicating that an inoculum with similar physical characteristics may be most appropriate for the AD of biodiesel waste. Of the two acclimatization rates studied, the slower rate improved the cumulative biogas production for both inocula. Both inocula also exhibited higher maximum daily efficiencies with a slower rate of acclimatization, up to a maximum average daily biogas yield of 621 mL biogas g
−1
COD added. This implied that the rate of acclimatization can impact the ability of the digester to adapt efficiently to a new substrate.
Indoor thermal environment is a critical factor for animal health and production in confined livestock facilities. In order to improve indoor thermal environment control and save energy, a novel ...dynamic thermal exchange model was developed using the energy balance equation (EBE) and 87 days of data collected in three different seasons in a pig building to simulate the heat transfer and energy consumption in the building. To evaluate the performances of the EBE model, a comparison was made using adaptive neuro fuzzy inferring system (ANFIS) for indoor air temperature prediction. Also, the EBE model was evaluated comparing its outputs of indoor temperature with the dataset of six days, under three different ventilation modes (Min-vent, Low-vent, and High-vent) that represent for the cold, warm and hot weather, obtained through a monitoring period in pig buildings during the production. The results showed that, under three different ventilations modes, the maximum errors between the EBE model simulated and measured data were 1.5 °C compared with 2.6 °C of the ANFIS model; and the averaged coefficients of determination R2 were 0.945 and 0.743, respectively, for the EBE and ANFIS models. Compared with the present ventilation operation, there was 358.301 kW h power saved with the EBE model in a pig room during the whole research period of 87 days. Therefore, this research has several practical applications: the model can be used in developing strategies of indoor thermal environmental control, it can also increase the knowledge about energy consumption in the livestock house.
•A dynamic thermal model for indoor air temperature prediction and energy saving was developed.•Data measured for 87 days in three different seasons from a swine room were used.•Model parameters can be determined with multiple non-linear regression method.•The model contributes to heat exchange and animal building environment control strategies.
Ammonia (NH3), carbon dioxide (CO2), and hydrogen sulfide (H2S) are predominant gases that are responsible for indoor air quality and air pollution emitted from pig buildings. They are critical for ...the health of pigs, farm workers, and people living nearby. To achieve an accurate estimation of gas emissions, firstly, hybrid deep learning driven sequential Concentration Transport Emission Model (DL-CTEM) was proposed to estimate the emissions of NH3, CO2, and H2S from a pig building. Then, optimal ventilation control strategies were put forward to improve health-related gas concentrations and air pollution from the pig building. Fifty-three days of hourly measurements data were divided into training data and test data for the DL-CTEM. It was shown that the mean errors between the measurements and the predictions of the proposed model for NH3, CO2, and H2S concentrations were 0.1 ppm, 79.2 ppm, and 106.3 ppb, respectively. The proposed model outperformed when it was built with an optimal structure in the long short-term memory (LSTM) layer. The mean emission rates of NH3, CO2, and H2S based on DL-CTEM were 4.2 mg min−1, 2887.5 mg min−1, and 2.1 μg min−1. It could provide a feasible way for air pollution emission estimation and health-related ventilation control in a pig building.
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•A novelty conception of pollutant gas concentration transport to emission was proposed.•A hybrid deep learning model for emission estimation from pig house was developed.•An optimal health-related ventilation control for indoor air quality and emission was built.•The deep learning driven emission estimation model achieved better performances.
