Determining the regional potential for a grass biomethane industry

Grass biogas/biomethane has been put forward as a renewable energy solution and it has been shown to perform well in terms of energy balance, greenhouse gas emissions and policy constraints. Biofuel and energy crop solutions are country-specific and grass biomethane has strong potential in countries with temperate climates and a high proportion of grassland, such as Ireland. For a grass biomethane industry to develop in a country, suitable regions (i.e. those with the highest potential) must be identified. In this paper, factors specifically related to the assessment of the potential of a grass biogas/biomethane industry are identified and analysed. The potential for grass biogas and grass biomethane is determined on a county-by-county basis using multi-criteria decision analysis. Values are assigned to each county and ratings and weightings applied to determine the overall county potential. The potential for grass biomethane with co-digestion of slaughter waste (belly grass) is also determined. The county with the highest potential (Limerick) is analysed in detail and is shown to have ready potential for production of gaseous biofuel to meet either 50% of the vehicle fleet or 130% of the domestic natural gas demand, through 25 facilities at a scale of ca. 30ktyr of feedstock. The assessment factors developed in this paper can be used in other resource studies into grass biomethane or other energy crops. © 2010 Elsevier Ltd.

The indirect effects of biofuels and what to do about them:The case of grass biomethane and its impact on livestock

Grass biomethane surpasses the 60% greenhouse gas (GHG) savings relative to the fossil fuel replaced required by EU Directive 2009/28/EC. However, there are growing concerns that when the indirect effects of biofuels are taken into account, GHG savings may become negative. There has been no research to date into the indirect effects of grass biomethane; this paper aims to fill that knowledge gap. A causal-descriptive assessment is carried out and identifies the likely indirect effect of a grass biomethane industry in Ireland as a reduction in beef exports to the UK. Three main scenarios are then analyzed: an increase in indigenous UK beef production, an increase in beef imported to the UK from other countries (EU, New Zealand and Brazil), and a decrease in beef consumption leading to increased poultry consumption. The GHG emissions from each of these scenarios are determined and the resulting savings relative to fossil diesel vary between -636% and 102%. The significance of the findings is then discussed. It is the view of the authors that, while consideration of indirect effects is important, an Irish grass biomethane industry cannot be held accountable for the associated emissions. A global GHG accounting system is therefore proposed; however, the difficulty of implementing such a system is acknowledged, as is its probable ineffectualness. Such a system would not treat the source of the problem - rising consumption. The authors conclude that the most effective method of combating the indirect effects of biofuels is a reduction in general consumption. © 2011 Society of Chemical Industry and John Wiley & Sons, Ltd.

Can grass biomethane be an economically viable biofuel for the farmer and the consumer?

Farm incomes in Ireland are in decline and many farmers would operate at a loss in the absence of subsidies. Agriculture is responsible for 27% of Ireland's greenhouse gas emissions and is the largest contributing sector. Penetration of renewable energy in the heat and transport sectors is falling short of targets, and there is no clear plan for achieving them. The anaerobic digestion of grass to produce biogas or biomethane is put forward as a multifaceted solution, which could help meet energy and emissions targets, reduce dependence on imported energy, and provide additional farm income. This paper addresses the economic viability of such a system. Grass biogas/biomethane fares poorly under the current combined heat and power tariff structure, which is geared toward feedstock that attracts a gate fee. Tariff structures similar to those used in other countries are necessary for the industry to develop. Equally, regulation should be implemented to allow injection of biomethane into the gas grid in Ireland. Blends of natural gas and biomethane can be sold, offering a cost-competitive green fuel. Sale as a renewable transport fuel could allow profitability for the farmer and savings for the consumer, but suffers due to the lack of a market. Under current conditions, the most economically viable outlet for grass biomethane is sale as a renewable heating fuel. The key to competitiveness is the existing natural gas infrastructure that enables distribution of grass biomethane, and the renewable energy targets that allow renewable fuels to compete against each other. © 2010 Society of Chemical Industry and John Wiley & Sons, Ltd.

What is the energy balance of grass biomethane in Ireland and other temperate northern European climates?

Biofuels have had bad press in recent years. There are primarily two distinct issues. The biofuel crops with the best yields (such as sugarcane or oil palm) grow in tropical countries where habitat destruction has occurred in association with the biofuel system. First generation indigenous energy crops commonly used for transport fuel in Europe (such as rapeseed and wheat) have low yields and/or the energy balance of the associated biofuel system is poor. This paper shows that grass is a crop with significant yields and grass biomethane (a gaseous renewable transport biofuel) has a very good energy balance and does not involve habitat destruction, land use change, new farming practices or annual tilling. The gross and net energy production per hectare are almost identical to palm oil biodiesel; the net energy of the grass system is at least 50% better than the next best indigenous European biofuel system investigated. Ten percent of Irish grasslands could fuel over 55% of the Irish private car fleet. © 2009 Elsevier Ltd. All rights reserved.

How much gas can we get from grass?

Grass biomethane has been shown to be a sustainable gaseous transport biofuel, with a good energy balance, and significant potential for economic viability. Of issue for the designer is the variation in characteristics of the grass depending on location of source, time of cut and species. Further confusion arises from the biomethane potential tests (BMP) which have a tendency to give varying results. This paper has dual ambitions. One of these is to highlight the various results for biomethane potential that may be obtained from the same grass silage. The results indicated that methane potential from the same grass silage varied from 350 to 493 L CH4 kg−1 VS added for three different BMP procedures. The second ambition is to attempt to compare two distinct digestion systems again using the same grass: a two stage continuously stirred tank reactor (CSTR); and a sequentially fed leach bed reactor connected to an upflow anaerobic sludge blanket (SLBR–UASB). The two engineered systems were designed, fabricated, commissioned and operated at small pilot scale until stable optimal operating conditions were reached. The CSTR system achieved 451 L CH4 kg−1 VS added over a 50 day retention period. The SLBR–UASB achieved 341 L CH4 kg−1 VS added at a 30 day retention time.

Soil Moisture Deficit as a predictor of the trend in soil water status of grass fields

Nutrient loss from agricultural land following organic fertilizer spreading can lead to eutrophication and poor water quality. The risk of pollution is partly related to the soil water status during and after spreading. In response to these issues, a decision support system (DSS) for nutrient management has been developed to predict when soil and weather conditions are suitable for slurry spreading. At the core of the DSS, the Hybrid Soil Moisture Deficit (HSMD) model estimates soil water status relative to field capacity (FC) for three soil classes (well, moderately and poorly drained) and has potential to predict the occurrence of a transport vector when the soil is wetter than FC. Three years of field observation of volumetric water content was used to validate HSMD model predictions of water status and to ensure correct use and interpretation of the drainage classes. Point HSMD model predictions were validated with respect to the temporal and spatial variations in volumetric water content and soil strength properties. It was found that the HSMD model predictions were well related to topsoil water content through time, but a new class intermediate between poor and moderate, perhaps ‘imperfectly drained’, was needed. With correct allocations of a field into a drainage class, the HSMD model predictions reflect field scale trends in water status and therefore the model is suitable for use at the core of a DSS.

Trait directed de novo population transcriptome dissects genetic regulation of a balanced polymorphism in phosphorus nutrition/arsenate tolerance in a wild grass Holcus lanatus

The aim of this study was to characterize the transcriptome of a balanced polymorphism, under the regulation of a single gene, for phosphate fertilizer responsiveness/arsenate toler- ance in wild grass Holcus lanatus genotypes screened from the same habitat.

De novo transcriptome sequencing, RNAseq (RNA sequencing) and single nucleotide poly- morphism (SNP) calling were conducted on RNA extracted from H.lanatus. Roche 454 sequencing data were assembled into c. 22 000 isotigs, and paired-end Illumina reads for phosphorus-starved (P) and phosphorus-treated (P+) genovars of tolerant (T) and nontoler- ant (N) phenotypes were mapped to this reference transcriptome.

Heatmaps of the gene expression data showed strong clustering of each P+/P treated genovar, as well as clustering by N/T phenotype. Statistical analysis identified 87 isotigs to be significantly differentially expressed between N and T phenotypes and 258 between P+ and P treated plants. SNPs and transcript expression that systematically differed between N and T phenotypes had regulatory function, namely proteases, kinases and ribonuclear RNA- binding protein and transposable elements.

A single gene for arsenate tolerance led to distinct phenotype transcriptomes and SNP pro- files, with large differences in upstream post-translational and post-transcriptional regulatory genes rather than in genes directly involved in P nutrition transport and metabolism per se.

A 30-Day-Ahead Forecast Model for Grass Pollen in North London, United Kingdom

A 30-day ahead forecast method has been developed for grass pollen at north London. The total period of the grass pollen season is covered by eight multiple regression models, each covering a 10-day period running consecutively from 21st May to 8th August. This means that three models were used for each 30-day forecast. The forecast models were produced using grass pollen and environmental data from 1961-1999 and tested on data from 2000 and 2002. Model accuracy was judged in two ways: the number of times the forecast model was able to successfully predict the severity (relative to the 1961-1999 dataset as a whole) of grass pollen counts in each of the eight forecast periods on a scale of one to four; and the number of times the forecast model was able to predict whether grass pollen counts were higher or lower than the mean. The models achieved 62.5% accuracy in both assessment years when predicting the relative severity of grass pollen counts on a scale of one to four, which equates to six of the eight 10-day periods being forecast correctly. The models attained 87.5% and 100% accuracy in 2000 and 2002 respectively when predicting whether grass pollen counts would be higher or lower than the mean. Attempting to predict pollen counts during distinct 10-day periods throughout the grass pollen season is a novel approach. The models also employed original methodology in the use of winter averages of the North Atlantic Oscillation to forecast 10-day means of allergenic pollen counts.

Constructing a 7-day Ahead Forecast Model for Grass Pollen at North London, United Kingdom

A number of media outlets now issue medium-range (~7 day) weather forecasts on a regular basis. It is therefore logical that aerobiologists should attempt to produce medium-range forecasts for allergenic pollen that cover the same time period as the weather forecasts. The objective of this study is to construct a medium-range (< 7 day) forecast model for grass pollen at north London. The forecast models were produced using regression analysis based on grass pollen and meteorological data from 1990-1999 and tested on data from 2000 and 2002. The modelling process was improved by dividing the grass pollen season into three periods; the pre-peak, peak and post peak periods of grass pollen release. The forecast consisted of five regression models. Two simple linear regression models predicting the start and end date of the peak period, and three multiple regression models forecasting daily average grass pollen counts in the pre-peak, peak and post-peak periods. Overall the forecast models achieved 62% accuracy in 2000 and 47% in 2002, reflecting the fact that the 2002 grass pollen season was of a higher magnitude than any of the other seasons included in the analysis. This study has the potential to make a notable contribution to the field of aerobiology. Winter averages of the North Atlantic Oscillation were used to predict certain characteristics of the grass pollen season, which presents an important advance in aerobiological work. The ability to predict allergenic pollen counts for a period between five and seven days will benefit allergy sufferers. Furthermore, medium-range forecasts for allergenic pollen will be of assistance to the medical profession, including allergists planning treatment and physicians scheduling clinical trials.

Examining High Magnitude Grass Pollen Episodes at Worcester, United Kingdom, Using Back-Trajectory Analysis

Trajectory analysis is a valuable tool that has been used before in aerobiological studies, to investigate the movement of airborne pollen. This study has employed back-trajectories to examine the four highest grass pollen episodes at Worcester, during the 2001 grass pollen season. The results have shown that the highest grass pollen counts of the 2001 season were reached when air masses arrived from a westerly direction. Back-trajectory analysis has a limited value to forecasters because the method is retrospective and cannot be employed directly for forecasting. However, when used in conjunction with meteorological data this technique can be used to examine high magnitude events in order to identify conditions that lead to high pollen counts.