When considering no man is an island—assessing bioenergy systems in a regional and LCA context: a review

Purpose

With many environmental burdens associated with bioenergy production occurring at the regional level, there is a need to produce more regional and spatially representative life cycle assessment of bioenergy systems. On the other hand, such assessments also need to account for the global and cumulative impacts along the full bioenergy life cycle in order to support effective regional policy measures and decision making. Therefore, the challenge is to find a balance. In other words, how should we define the regional context for bioenergy system assessments in order to complement life cycle thinking? The aim of this review is to answer this question by providing an overview of important considerations when assessing bioenergy systems in a regional and LCA context and how these two contexts intersect. It also aims to help guide and orientate LCA practitioners interested in including more regional aspects in their bioenergy studies. Until now, such a review which explores the integration of regional and life cycle contexts in relation to bioenergy systems and their products has not been done.

Methods

As a first step, we define what we mean by the term region. We then look at the potential burdens relating to bioenergy systems and their relationship with the regional context. In a next step, we explore life cycle thinking and the intersection between the regional and LCA contexts by providing some examples from the literature. We then discuss the benefits and limitations of such regionally contextualized life cycle approaches in relation to bioenergy production systems and indeed other alternative biomass uses.

Results and discussion

Three regional contexts were identified to help orientate life cycle thinking aiming to assess the regional and nonregional environmental implications of bioenergy production. These contexts were as follows: “within regional,” “regional and ROW,” and “regionalized.” The added value of implementing a regionally contextualized life cycle approach is the ability, therefore, to include greater regional and spatial details in the assessments of bioenergy production systems, without losing the links to the diversity of global supply chains. Thus, providing greater geographical and regional insight into how such potential burdens can be reduced or shifted burdens avoided or how associated regional production activities could be optimized to mitigate such burdens.

Conclusions

The use of different regional contexts as proposed in this paper is not only useful to orientate life cycle thinking in relation to bioenergy systems but also for the assessment of alternative novel bio-based systems.

     

Pseudo current density maps of electrophysiological heart,nerve or brain function and their physical basis

Background

In recent years the visualization of biomagnetic measurement data by so-called pseudo current density maps or Hosaka-Cohen (HC) transformations became popular.

Methods

The physical basis of these intuitive maps is clarified by means of analytically solvable problems.

Results

Examples in magnetocardiography, magnetoencephalography and magnetoneurography demonstrate the usefulness of this method.

Conclusion

Hardware realizations of the HC-transformation and some similar transformations are discussed which could advantageously support cross-platform comparability of biomagnetic measurements.

     

Attributional and consequential LCA in the ILCD handbook

Purpose

This discussion article aims to highlight two problematic aspects in the International Reference Life Cycle Data System (ILCD) Handbook: its guidance to the choice between attributional and consequential modeling and to the choice between average and marginal data as input to the life cycle inventory (LCI) analysis.

Methods

We analyze the ILCD guidance by comparing different statements in the handbook with each other and with previous research in this area.

Results and discussion

We find that the ILCD handbook is internally inconsistent when it comes to recommendations on how to choose between attributional and consequential modeling. We also find that the handbook is inconsistent with much of previous research in this matter, and also in the recommendations on how to choose between average and marginal data in the LCI.

Conclusions

Because of the inconsistencies in the ILCD handbook, we recommend that the handbook be revised.

     

Identifying marginal supplying countries of wood products via trade network analysis

Purpose

The consequential inventory modeling approach for life cycle assessment implies that an increase in the demand for a specific product is met by the marginal suppliers within the market. The identification of marginal suppliers is however complicated by difficulties in defining appropriate geographical market delimitations. In this study, an advanced system thinking approach is proposed to address this challenge in the identification of marginal supplying countries of wood products.

Methods

Groups of countries which represent geographical markets are identified from trade data by using a network analysis-based clustering technique. Within these markets, marginal supplying countries are selected based on positive historical increments. The analysis covers 12 different products and all countries in the world using trade data for the period 1998–2013.

Results and discussion

Global indices allow differentiating how product-specific trade networks are separated into communities and how interconnected these networks are. Large differences between products and minor differences between trade years are observed. Communities identified for each product tend to overlap with existing geographical regions and seem thus realistic. By combining this information with product-specific production increment rankings, marginal supplying countries of wood products were identified.

Conclusions

The identified geographical market delimitation is a key for proper consequential life cycle assessment (LCA) inventory modeling in areas such as timber-based construction and biomass-based energy production. The method can in principle be applied to any product for which trade network data are available and ideally should be accompanied by a detailed analysis of technological constrains within the identified supplying country.

     

Metabolomic profiling of maternal hair suggests rapid development of intrahepatic cholestasis of pregnancy

Introduction

Intrahepatic cholestasis of pregnancy (ICP) is a common maternal liver disease; development can result in devastating consequences, including sudden fetal death and stillbirth. Currently, recognition of ICP only occurs following onset of clinical symptoms.

Objective

Investigate the maternal hair metabolome for predictive biomarkers of ICP.

Methods

The maternal hair metabolome (gestational age of sampling between 17 and 41 weeks) of 38 Chinese women with ICP and 46 pregnant controls was analysed using gas chromatography–mass spectrometry.

Results

Of 105 metabolites detected in hair, none were significantly associated with ICP.

Conclusion

Hair samples represent accumulative environmental exposure over time. Samples collected at the onset of ICP did not reveal any metabolic shifts, suggesting rapid development of the disease.

     

Quantitative analysis of tetrahydrofolate metabolites from <Emphasis Type="Italic">clostridium autoethanogenum</Emphasis>

Introduction

Quantification of tetrahydrofolates (THFs), important metabolites in the Wood–Ljungdahl pathway (WLP) of acetogens, is challenging given their sensitivity to oxygen.

Objective

To develop a simple anaerobic protocol to enable reliable THFs quantification from bioreactors.

Methods

Anaerobic cultures were mixed with anaerobic acetonitrile for extraction. Targeted LC–MS/MS was used for quantification.

Results

Tetrahydrofolates can only be quantified if sampled anaerobically. THF levels showed a strong correlation to acetyl-CoA, the end product of the WLP.

Conclusion

Our method is useful for relative quantification of THFs across different growth conditions. Absolute quantification of THFs requires the use of labelled standards.

     

Blue mussel (<Emphasis Type="Italic">Mytilus edulis</Emphasis>) bouchot culture in Mont-St Michel Bay: potential mitigation effects on climate change and eutrophication

Purpose

Bivalve production is an important aquaculture activity worldwide, but few environmental assessments have focused on it. In particular, bivalves’ ability to extract nutrients from the environment by intensely filtering water and producing a shell must be considered in the environmental assessment.

Methods

LCA of blue mussel bouchot culture (grown out on wood pilings) in Mont Saint-Michel Bay (France) was performed to identify its impact hotspots. The chemical composition of mussel flesh and shell was analyzed to accurately identify potential positive effects on eutrophication and climate change. The fate of mussel shells after consumption was also considered.

Results and discussion

Its potential as a carbon-sink is influenced by assumptions made about the carbon sequestration in wooden bouchots and in the mussel shell. The fate of the shells which depends on management of discarded mussels and household waste plays also an important role. Its carbon-sink potential barely compensates the climate change impact induced by the use of fuel used for on-site transportation. The export of N and P in mussel flesh slightly decreases potential eutrophication. Environmental impacts of blue mussel culture are determined by the location of production and mussel yields, which are influenced by marine currents and the distance to on-shore technical base.

Conclusions

Bouchot mussel culture has low environmental impacts compared to livestock systems, but the overall environmental performances depend on farming practices and the amount of fuel used. Changes to the surrounding ecosystem induced by high mussel density must be considered in future LCA studies.

     

Metabolic response of porcine colon explants to in vitro infection by <Emphasis Type="Italic">Brachyspira hyodysenteriae</Emphasis>: a leap into disease pathophysiology

Introduction

Swine dysentery caused by Brachyspira hyodysenteriae is a production limiting disease in pig farming. Currently antimicrobial therapy is the only treatment and control method available.

Objective

The aim of this study was to characterize the metabolic response of porcine colon explants to infection by B. hyodysenteriae.

Methods

Porcine colon explants exposed to B. hyodysenteriae were analyzed for histopathological, metabolic and pro-inflammatory gene expression changes.

Results

Significant epithelial necrosis, increased levels of l-citrulline and IL-1α were observed on explants infected with B. hyodysenteriae.

Conclusions

The spirochete induces necrosis in vitro likely through an inflammatory process mediated by IL-1α and NO.

     

The alpha-1A adrenergic receptor agonist A61603 reduces cardiac polyunsaturated fatty acid and endocannabinoid metabolites associated with inflammation in vivo

Introduction

Alpha-1-adrenergic receptors (α1-ARs) are G-protein coupled receptors (GPCRs) with three highly homologous subtypes (α1A, α1B, and α1D). Of these three subtypes, only the α1A and α1B are expressed in the heart. Multiple pre-clinical models of heart injury demonstrate cardioprotective roles for the α1A. Non-selective α1-AR activation promotes glycolysis in the heart, but the functional α1-AR subtype and broader metabolic effects have not been studied.

Objectives

Given the high metabolic demands of the heart and previous evidence indicating benefit from α1A activation, we chose to investigate the effects of α1A activation on the cardiac metabolome in vivo.

Methods

Mice were treated for 1 week with a low, subpressor dose of A61603, a highly selective and potent α1A agonist. Cardiac tissue and serum were analyzed using a non-targeted metabolomics approach.

Results

We identified previously unrecognized metabolic responses to α1A activation, most notably broad reduction in the abundance of polyunsaturated fatty acids (PUFAs) and endocannabinoids (ECs).

Conclusion

Given the well characterized roles of PUFAs and ECs in inflammatory pathways, these findings suggest a possible role for cardiac α1A-ARs in the regulation of inflammation and may offer novel insight into the mechanisms underlying the cardioprotective benefit of selective pharmacologic α1A activation.

     

Minimal variation of the plasma lipidome after delayed processing of neonatal cord blood

Background

Cord blood lipids are potential disease biomarkers. We aimed to determine if their concentrations were affected by delayed blood processing.

Method

Refrigerated cord blood from six healthy newborns was centrifuged every 12 h for 4 days. Plasma lipids were analysed by liquid chromatography/mass spectroscopy.

Results

Of 262 lipids identified, only eight varied significantly over time. These comprised three dihexosylceramides, two phosphatidylserines and two phosphatidylethanolamines whose relative concentrations increased and one sphingomyelin that decreased.

Conclusion

Delay in separation of plasma from refrigerated cord blood has minimal effect overall on the plasma lipidome.

     

Does centrifugation matter? Centrifugal force and spinning time alter the plasma metabolome

Background

Centrifugation is an indispensable procedure for plasma sample preparation, but applied conditions can vary between labs.

Aim

Determine whether routinely used plasma centrifugation protocols (1500×g 10 min; 3000×g 5 min) influence non-targeted metabolomic analyses.

Methods

Nuclear magnetic resonance spectroscopy (NMR) and High Resolution Mass Spectrometry (HRMS) data were evaluated with sparse partial least squares discriminant analyses and compared with cell count measurements.

Results

Besides significant differences in platelet count, we identified substantial alterations in NMR and HRMS data related to the different centrifugation protocols.

Conclusion

Already minor differences in plasma centrifugation can significantly influence metabolomic patterns and potentially bias metabolomics studies.

     

Promoting life cycle thinking for sustainability in the mining sector of the Philippines

Purpose

This paper aims to promote life cycle thinking for the mining sector in the Philippines in enhancing the interventions intended for mining as a catalyst of sustainable development in the country. The environmental ills of mining hinder the sector’s acceptability as a catalyst, which is detrimental to its sustainability at the same time.

Methods

Previous works on mining impacts and life cycle thinking and assessment in the country had been reviewed to glean insights on integrating life cycle thinking in mining. Why and how such thinking and approach should be accounted for in mining is examined from these works to figure out the strategies through which mining is helped in mitigating its environmental ills.

Results and discussion

Life cycle thinking helps establish a logical approach in analysing issues associated with mining processes and products. It is of great relevance in preparing for contingencies for the adverse environmental outcomes that arise at any point of mining’s life cycle (exploration to mine closure) and the mining products’ life cycles (extraction to recycling or to accumulation). With its associated assessment procedures, life cycle thinking provides a logical system in obtaining scientific evidence for forward planning particularly on the aspect of sustainable mitigation of mining’s environmental outcomes.

Conclusions

It is apt that life cycle thinking be seriously accounted for in mining to improve the current undertakings of troubleshooting and addressing the adverse environmental outcomes of mining. Important insights from it facilitate the identification of sustainable mitigation strategies and who could take the lead actions, such as in developing business linkages and new markets to capitalize on the wastes and emissions from mining operations. The insights can greatly help the mining sector build its capability to come in harmony with people and nature, and work as a catalyst of sustainable development in the country.

     

Real-time environmental assessment of electricity use: a tool for sustainable demand-side management programs

Purpose

Demand-side management is a promising way to increase the integration of renewable energy sources by adapting part of the demand to balance power systems. However, the main challenges of evaluating the environmental performances of such programs are the temporal variation of electricity generation and the distinction between generation and electricity use by including imports and exports in real-time.

Methods

In this paper, we assessed the environmental impacts of electricity use in France by developing consumption factors based on historical hourly data of imports, exports, and electricity generation of France, Germany, Great Britain, Italy, Belgium, and Spain. We applied a life cycle approach with four environmental indicators: climate change, human health, ecosystem quality, and resources. The developed dynamic consumption factors were used to assess the environmental performances of demand-side management programs through optimized changes in consumption patterns defined by the flexibility of 1 kWh every day in 2012–2014.

Results and discussion

Between 2012 and 2014, dynamic consumption factors in France were higher on average than generation factors by 21.8% for the climate change indicator. Moreover, the dynamic consideration of electricity generation of exporting countries is essential to avoid underestimating the impacts of electricity imports and therefore electricity use. The demand response programs showed a range of mitigation up to 38.5% for the climate change indicator. In addition, an environmental optimization cost 1.4 € per kg CO2 eq. for 12% mitigation of emissions as compared to an economic optimization. Finally, embedding the costs of some environmental impacts in the electricity price with a carbon price enhanced the efficiency of economic demand response strategies on the GHG emissions mitigation.

Conclusions

The main scientific contribution of this paper is the development of more accurate dynamic electricity consumption factors. The dynamic consumption factors are relevant in LCAs of industrial processes or operational building phases, especially when consumption varies over time and when the power system participates in a wide market with exports and imports such as in France. In the case of demand-side management programs, dynamic consumption factors could prevent an environmentally damaging energy from being imported, despite the economic interest of system operators. However, the approach used in this study was attributional and did not assess the local grid responses of load shifting programs. Therefore, a more comprehensive model could be created to assess the local short-term dynamic consequences of located prospective consumptions and the global long-term consequences of demand-side management programs.

     

Optimization of fecal sample preparation for untargeted LC-HRMS based metabolomics

Introduction

Collecting feces is easy. It offers direct outcome to endogenous and microbial metabolites.

Objectives

In a context of lack of consensus about fecal sample preparation, especially in animal species, we developed a robust protocol allowing untargeted LC-HRMS fingerprinting.

Methods

The conditions of extraction (quantity, preparation, solvents, dilutions) were investigated in bovine feces.

Results

A rapid and simple protocol involving feces extraction with methanol (1/3, M/V) followed by centrifugation and a step filtration (10 kDa) was developed.

Conclusion

The workflow generated repeatable and informative fingerprints for robust metabolome characterization.

     

Our local experience with the surgical treatment of ampullary cancer

Background

The aim of this study is to report the outcome after surgical treatment of 32 patients with ampullary cancers from 1990 to 1999.

Methods

Twenty-one of them underwent pancreaticoduodenectomy and 9 local excision of the ampullary lesion. The remaining 2 patients underwent palliative surgery.

Results

When the final histological diagnosis was compared with the preoperative histological finding on biopsy, accurate diagnosis was preoperatively established in 24 patients. The hospital morbidity was 18.8% as 9 complications occurred in 6 patients. Following local excision of the ampullary cancer, the survival rate at 3 and 5 years was 77.7% and 33.3% respectively. Among the patients that underwent Whipple's procedure, the 3-year survival rate was 76.2% and the 5-year survival rate 62%.

Conclusion

In this series, local resection was a safe option in patients with significant co-morbidity or small ampullary tumors less than 2 cm in size, and was associated with satisfactory long-term survival rates.

     

Emission payback periods for increased residential insulation using marginal electricity modeling: a life cycle approach

Purpose

Increases in residential insulation can reduce energy consumption and corresponding life cycle emissions, but with increased manufacturing and transportation of insulation and the associated impacts. In this study, we conducted life cycle analyses of residential insulation and estimated payback periods for carbon dioxide (CO₂), nitrogen oxides (NOx), and sulfur dioxide (SO₂) emissions, using modeling techniques that account for regional variability in climate, fuel utilization, and marginal power plant emissions.

Methods

We simulated the increased production of insulation and energy savings if all single-family homes in the USA increased insulation levels to the 2012 International Energy Conservation Code, using an energy simulation model (EnergyPlus) applied to a representative set of home templates. We estimated hourly marginal changes in electricity production and emissions using the Avoided Emissions and Generation Tool (AVERT), and we estimated emissions related to direct residential combustion. We determined changes in upstream emissions for both insulation and energy using openLCA and ecoinvent. Payback periods were estimated by pollutant and region. In sensitivity analyses, we considered the importance of marginal versus average power plant emissions, transportation emissions, emission factors for fiberglass insulation, and sensitivity of emission factors to the magnitude of electricity reduction.

Results and discussion

Combining the life cycle emissions associated with both increased insulation manufacturing and decreased energy consumption, the payback period for increased residential insulation is 1.9 years for CO₂ (regional range 1.4–2.9), 2.5 years for NOx (regional range 1.8–3.9), and 2.7 years for SO₂ (regional range 1.9–4.8). For insulation, transportation emissions are limited in comparison with manufacturing emissions. Emission benefits displayed strong regional patterns consistent with relative demands for heating versus cooling and the dominant fuels used. Payback periods were generally longer using average instead of marginal emissions and were insensitive to the magnitude of electricity savings, which reflects the structure of the intermediate complexity electricity dispatch model.

Conclusions

The life cycle benefits of increased residential insulation greatly exceed the adverse impacts related to increased production across all regions, given insulation lifetimes of multiple decades. The strong regionality in benefits and the influence of a marginal modeling approach reinforce the importance of site-specific attributes and time-dynamic modeling within LCA.

     

A novel approach to minimize false discovery rate in genome-wide data analysis

Background

High-throughput technologies, such as DNA microarray, have significantly advanced biological and biomedical research by enabling researchers to carry out genome-wide screens. One critical task in analyzing genome-wide datasets is to control the false discovery rate (FDR) so that the proportion of false positive features among those called significant is restrained. Recently a number of FDR control methods have been proposed and widely practiced, such as the Benjamini-Hochberg approach, the Storey approach and Significant Analysis of Microarrays (SAM).

Methods

This paper presents a straight-forward yet powerful FDR control method termed miFDR, which aims to minimize FDR when calling a fixed number of significant features. We theoretically proved that the strategy used by miFDR is able to find the optimal number of significant features when the desired FDR is fixed.

Results

We compared miFDR with the BH approach, the Storey approach and SAM on both simulated datasets and public DNA microarray datasets. The results demonstrated that miFDR outperforms others by identifying more significant features under the same FDR cut-offs. Literature search showed that many genes called only by miFDR are indeed relevant to the underlying biology of interest.

Conclusions

FDR has been widely applied to analyzing high-throughput datasets allowed for rapid discoveries. Under the same FDR threshold, miFDR is capable to identify more significant features than its competitors at a compatible level of complexity. Therefore, it can potentially generate great impacts on biological and biomedical research.

Availability

If interested, please contact the authors for getting miFDR.

     

Chilling slows anaerobic metabolism to improve anoxia tolerance of insects

Background

Insects are renowned for their ability to survive anoxia. Anoxia tolerance may be enhanced during chilling through metabolic suppression.

Aims

Here, the metabolomic response of insects to anoxia, both with and without chilling, for different durations (12–36 h) was examined to assess the potential cross-tolerance mechanisms.

Results

Chilling during anoxia (cold anoxia) significantly improved survival relative to anoxia at warmer temperatures. Reduced intermediate metabolites and increased lactic acid, indicating a switch to anaerobic metabolism, were characteristic of larvae in anoxia.

Conclusions

Anoxia tolerance was correlated survival improvements after cold anoxia were correlated with a reduction in anaerobic metabolism.

     

A lost opportunity for science: journals promote data sharing in metabolomics but do not enforce it

Introduction

Data sharing is being increasingly required by journals and has been heralded as a solution to the ‘replication crisis’.

Objectives

(i) Review data sharing policies of journals publishing the most metabolomics papers associated with open data and (ii) compare these journals’ policies to those that publish the most metabolomics papers.

Methods

A PubMed search was used to identify metabolomics papers. Metabolomics data repositories were manually searched for linked publications.

Results

Journals that support data sharing are not necessarily those with the most papers associated to open metabolomics data.

Conclusion

Further efforts are required to improve data sharing in metabolomics.

     

Estimation of the size of error introduced into consequential models by using attributional background datasets

Purpose

A systematic comparison is made of attributional and consequential results for the same products using the same unit process database, thus isolating the effect of the two system models. An analysis of this nature has only recently been made possible due to the ecoinvent database version 3 providing an access to both unallocated and unlinked unit process datasets as well as both attributional and consequential models based on these datasets. The analysis is therefore limited to the system models provided by ecoinvent.

Methods

For both system models, the analysis was made on the life cycle inventory analysis (LCIA) results as published by ecoinvent (692 impact categories from different methods, for 11,650 product/activity combinations). The comparison was made on the absolute difference relative to the smallest absolute value.

Results and discussion

The comparison provides quantified results showing that the consequential modelling provides large differences in results when the unconstrained (marginal) suppliers have much more/less impact than the average, when analysing the by-products, and when analysing determining products from activities with important amounts of other coproducts.

Conclusions

The analysis confirms that for consequential studies, attributional background datasets are not appropriate as a substitute for consequential background. The overall error will of course depend on the extent to which attributional modelling is used as part of the overall system model. While the identified causes of differences between the attributional and consequential models are of general nature, the identified sizes of the errors are specific to the way the two models are implemented in ecoinvent.