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1.

Purpose

The rapid growth of vehicle sales and usage has highlighted the need for greenhouse gas (GHG) emission reduction in Macau, a special administrative region (SAR) of China. As the most primary vehicle type, light-duty vehicles (LDV, including light-duty gasoline vehicles (LDGVs) and light-duty diesel vehicles (LDDVs)) play a key role in promoting the GHG reduction and development of green transportation system in Macau.

Methods

This study, on the basis of real-world tested and statistical data, firstly performed a streamlined life-cycle assessment (SLCA) on LDVs, to evaluate the potential GHG emissions and reduction through shifting to hybrid electric vehicles (HEVs) and electric vehicles (EVs).

Results and discussion

The results show that the mean GHG emissions from the LDGVs, LDDVs, and HEVs per 100 km were 25.16, 20.30, and 15.00 kg CO2 eq, respectively. Under the current electricity mix in Macau, EVs with the emissions of 12.39 kg CO2 eq/100 km can achieve a significant GHG emission reduction of LDVs in Macau. The total GHG emissions from LDVs increased from 124.99 to 247.82 thousand metric tons over the periods 2001–2014, with a 5.42% annual growth rate. A scenario analysis indicated that the development of HEVs and EVs—especially EVs—has the potential to control the GHG emissions from LDVs. Under the electricity mix of natural gas (NG) and solar energy (SE), the GHG emissions from EVs would drop by about 22 and 28%, respectively, by 2030.

Conclusions

This study develops a useful approach to evaluate the potential GHG emissions and its reduction strategies in Macau. All the obtained results could be useful for decision makers, providing robust support for drawing up an appropriate plan for improving green transportation systems in Macau.
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2.

Purpose

The purpose of this study was to quantify the spatial and technological variability in life cycle greenhouse gas (GHG) emissions, also called the carbon footprint, of durum wheat production in Iran.

Methods

The calculations were based on information gathered from 90 farms, each with an area ranging from 1 to 150 ha (average 16 ha). The carbon footprint of durum wheat was calculated by quantifying the biogenic GHG emissions of carbon loss from soil and biomass, as well as the GHG emissions from fertilizer application and machinery use, irrigation, transportation, and production of inputs (e.g., fertilizers, seeds, and pesticides). We used Spearman’s rank correlation to quantify the relative influence of technological variability (in crop yields, fossil GHG emissions, and N2O emissions from fertilizer application) and spatial variability (in biogenic GHG emissions) on the variation of the carbon footprint of durum wheat.

Results and discussion

The average carbon footprint of 1 kg of durum wheat produced was 1.6 kg CO2-equivalents with a minimum of 0.8 kg and a maximum of 3.0 kg CO2-equivalents. The correlation analysis showed that variation in crop yield and fertilizer application, representing technological variability, accounted for the majority of the variation in the carbon footprint, respectively 76 and 21%. Spatial variation in biogenic GHG emissions, mainly resulting from differences in natural soil carbon stocks, accounted for 3% of the variation in the carbon footprint. We also observed a non-linear relationship between the carbon footprint and the yield of durum wheat that featured a scaling factor of ?2/3. This indicates that the carbon footprint of durum wheat production (in kg CO2-eq kg?1) typically decreases by 67% with a 100% increase in yield (in kg ha?1 year?1).

Conclusions

Various sources of variability, including variation between locations and technologies, can influence the results of life cycle assessments. We demonstrated that technological variability exerts a relatively large influence on the carbon footprint of durum wheat produced in Iran with respect to spatial variability. To increase the durum wheat yield at farms with relatively large carbon footprints, technologies such as site-specific nutrient application, combined tillage, and mechanized irrigation techniques should be promoted.
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3.

Purpose

Mangrove forests have been recognized as important regulators of greenhouse gases (GHGs), yet the resulting land use and land-use change (LULUC) emissions have rarely been accounted for in life cycle assessment (LCA) studies. The present study therefore presents up-to-date estimates for GHG emissions from mangrove LULUC and applies them to a case study of shrimp farming in Vietnam.

Methods

To estimate the global warming impacts of mangrove LULUC, a combination of the International Panel for Climate Change (IPCC) guidelines, the Net Committed Emissions, and the Missed Potential Carbon Sink method were used. A literature review was then conducted to characterize the most critical parameters for calculating carbon losses, missed sequestration, methane fluxes, and dinitrogen monoxide emissions.

Results and discussion

Our estimated LUC emissions from mangrove deforestation resulted in 124 t CO2 ha?1 year?1, assuming IPCC’s recommendations of 1 m of soil loss, and 96% carbon oxidation. In addition to this, 1.25 t of carbon would no longer be sequestered annually. Discounted over 20 years, this resulted in total LULUC emissions of 129 t CO2 ha?1 year?1 (CV = 0.441, lognormal distribution (ln)). Shrimp farms in the Mekong Delta, however, can today operate for 50 years or more, but are 1.5 m deep (50% oxidation). In addition to this, Asian tiger shrimp farming in mixed mangrove concurrent farms (the only type of shrimp farm that resulted in mangrove deforestation since 2000 in our case study) resulted in 533 kg methane and 1.67 kg dinitrogen monoxide per hectare annually. Consequently, the LULUC GHG emissions resulted in 184 and 282 t CO2-eq t?1 live shrimp at farm gate, using mass and economic allocation, respectively. These GHG emissions are about an order of magnitude higher than from semi-intensive or intensive shrimp farming systems. Limitations in data quality and quantity also led us to quantify the uncertainties around our emission estimates, resulting in a CV of between 0.4 and 0.5.

Conclusions

Our results reinforce the urgency of conserving mangrove forests and the need to quantify uncertainties around LULUC emissions. It also questions mixed mangrove concurrent shrimp farming, where partial removal of mangrove forests is endorsed based upon the benefits of partial mangrove conservation and maintenance of certain ecosystem services. While we recognize that these activities limit the chances of complete removal, our estimates show that large GHG emissions from mangrove LULUC question the sustainability of this type of shrimp farming, especially since mixed mangrove farming only provide 5% of all farmed shrimp produced in Vietnam.
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4.

Background

The greenhouse gas (GHG) mitigation is one of the most important environmental benefits of using bioenergy replacing fossil fuels. Nitrous oxide (N2O) and methane (CH4) are important GHGs and have drawn extra attention for their roles in global warming. Although there have been many works of soil emissions of N2O and CH4 from bioenergy crops in the field scale, GHG emissions in large area of marginal lands are rather sparse and how soil temperature and moisture affect the emission potential remains unknown. Therefore, we sought to estimate the regional GHG emission based on N2O and CH4 releases from the energy crop fields.

Results

Here we sampled the top soils from two Miscanthus fields and incubated them using a short-term laboratory microcosm approach under different conditions of typical soil temperatures and moistures. Based on the emission measurements of N2O and CH4, we developed a model to estimate annual regional GHG emission of Miscanthus production in the infertile Loess Plateau of China. The results showed that the N2O emission potential was 0.27 kg N ha?1 year?1 and clearly lower than that of croplands and grasslands. The CH4 uptake potential was 1.06 kg C ha?1 year?1 and was slightly higher than that of croplands. Integrated with our previous study on the emission of CO2, the net greenhouse effect of three major GHGs (N2O, CH4 and CO2) from Miscanthus fields was 4.08 t CO2eq ha?1 year?1 in the Loess Plateau, which was lower than that of croplands, grasslands and shrub lands.

Conclusions

Our study revealed that Miscanthus production may hold a great potential for GHG mitigation in the vast infertile land in the Loess Plateau of China and could contribute to the sustainable energy utilization and have positive environmental impact on the region.
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5.

Purpose

The effect of regional factors on life cycle assessment (LCA) of camelina seed production and camelina methyl ester production was assessed in this study. While general conclusions from LCA studies point to lower environmental impacts of biofuels, it has been shown in many studies that the environmental impacts are dependent on location, production practices, and even local weather variations.

Methods

A cradle-to-farm gate and well-to-pump approaches were used to conduct the LCA. To demonstrate the impact of agro-climatic and management factors (weather condition, soil characteristics, and management practices) on the overall emissions for four different regions including Corvallis, OR, Pendleton, OR, Pullman, WA, and Sheridan, WY, field emissions were simulated using the DeNitrification-DeComposition (DNDC) model. openLCA v.1.4.2 software was used to quantify the environmental impacts of camelina seed and camelina methyl ester production.

Results and discussion

The results showed that greenhouse gas (GHG) emissions during camelina production in different regions vary between 49.39 and 472.51 kg CO2-eq./ha due to differences in agro-climatic and weather variations. The GHG emissions for 1 kg of camelina produced in Corvallis, Pendleton, Pullman, and Sheridan were 0.76 ± 11, 0.55 ± 10, 0.47 ± 18, and 1.26 ± 6 % kg CO2-eq., respectively. The GHG emissions for 1000 MJ of camelina biodiesel using camelina produced in Corvallis, Pendleton, Pullman, and Sheridan were 53.60 ± 5, 48.87 ± 5, 44.33 ± 7, and 78.88 ± 4 % kg CO2-eq., respectively. Other impact categories such as acidification and ecotoxicity for 1000 MJ of camelina biodiesel varied across the regions by 43 and 103 %, respectively.

Conclusions

It can be concluded that process-based crop models such as DNDC in conjunction with Monte Carlo analysis are helpful tools to quantitatively estimate the influence of regional factors on field emissions which consequently can provide information about the expected variability in LCA results.
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6.

Purpose

The well-to-wheel (WTW) methodology is widely used for policy support in road transport. It can be seen as a simplified life cycle assessment (LCA) that focuses on the energy consumption and CO2 emissions only for the fuel being consumed, ignoring other stages of a vehicle’s life cycle. WTW results are therefore different from LCA results. In order to close this gap, the authors propose a hybrid WTW+LCA methodology useful to assess the greenhouse gas (GHG) profiles of road vehicles.

Methods

The proposed method (hybrid WTW+LCA) keeps the main hypotheses of the WTW methodology, but integrates them with LCA data restricted to the global warming potential (GWP) occurring during the manufacturing of the battery pack. WTW data are used for the GHG intensity of the EU electric mix, after a consistency check with the main life cycle impact (LCI) sources available in literature.

Results and discussion

A numerical example is provided, comparing GHG emissions due to the use of a battery electric vehicle (BEV) with emissions from an internal combustion engine vehicle. This comparison is done both according to the WTW approach (namely the JEC WTW version 4) and the proposed hybrid WTW+LCA method. The GHG savings due to the use of BEVs calculated with the WTW-4 range between 44 and 56 %, while according to the hybrid method the savings are lower (31–46 %). This difference is due to the GWP which arises as a result of the manufacturing of the battery pack for the electric vehicles.

Conclusions

The WTW methodology used in policy support to quantify energy content and GHG emissions of fuels and powertrains can produce results closer to the LCA methodology by adopting a hybrid WTW+LCA approach. While evaluating GHG savings due to the use of BEVs, it is important that this method considers the GWP due to the manufacturing of the battery pack.
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7.

Purpose

This study examines the inter-annual variability of production data in an organic dairy farm and its effect on the estimation of product-related greenhouse gas emissions (GHG) using a detailed material flow model. It is believed that the examination of only one production year may not adequately reflect temporal representativeness and may therefore lead to unreliable results. The current study also provides a method to deal with variability when temporal representativeness cannot be ensured.

Methods

All material flows related to milk production from six consecutive milk years in an organic dairy farm in northern Germany were analysed. The milk yield of the 75 to 91 cows varied between 5418 and 7102 kg energy corrected milk (ECM) per cow and year. GHG emissions were estimated using calculation guidelines from the International Dairy Federation (IDF) and the Intergovernmental Panel on Climate Change (IPCC). Emissions were calculated in the Flow Analysis and Resource Management (FARM) model ensuring mass balances for nitrogen and phosphorous in every subsection of the model. Based on the variability of crop yields, the number of years for representative average data was calculated as well as an uncertainty when only a limited number of years was available.

Results and discussion

Estimated GHG emissions varied between 0.88 and 1.09 kg CO2-eq kg?1 ECM?1 (mean, standard deviation of the mean = 0.97 and 0.07 kg CO2-eq kg?1 ECM?1). Emissions from ruminant digestion had the highest contribution (50.9 ± 2.3) percent in relation to overall product-related GHG emissions. Direct emissions from soil showed the highest coefficient of variation (36%) due to simultaneous changes in fertilization amount, crop yield and milk yield which showed no significant direct relationship. The number of years needed to be assessed for representative average yields was between 27 and 215 years for clover grass and maize silage, respectively. When performing a sensitivity analysis based on the variability of crop yields, the assessed farm showed reliable results with average data of at least 4 years.

Conclusions

Temporal representativeness should be dealt with explicitly in GHG assessments for dairy farming. If the representativeness of crop yields cannot be ensured, an uncertainty bandwidth of the results based on variability of yields can provide a basis for comparing different farms or farming systems. This approach could also be extended to other variabilities in dairy farming for more reliability of results.
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8.

Purpose

The crude palm oil (CPO) extraction is normally done by a wet extraction process, and wastewater treatment of the wet process emits high levels of greenhouse gases (GHGs). A dry process extracts mixed palm oil (MPO) from palm fruit without using water and has no GHG emissions from wastewater treatment. This work is aimed at determining the GHG emissions of a dry process and at evaluating GHG savings on changing from wet to dry process, including land use change (LUC) effects.

Methods

Life cycle assessment from cradle to gate was used. The raw material is palm fruits. The dry process includes primary production, oil room, and utilities. MPO is the main product, while palm cake and fine palm residue are co-products sold for animal feed. Case studies were undertaken without and with carbon stocks of firewood and of nitrogen recycling at plantations from fronds. Allocations by mass, economic, and heating values were conducted. The trading of GHG emissions from co-products to GHG emissions from animal feed was assessed. The GHG emissions or savings from direct LUC (dLUC) and from indirect LUC (iLUC) effects and for the change from wet to dry process were determined.

Results and discussion

Palm fruit and firewood were the major GHG emission sources. Nitrogen recycling on plantations from fronds significantly affects the GHG emissions. With the carbon stocks, the GHG emissions allocated by energy value were 550 kg CO2 eq/t MPO. The GHG emissions were affected by ?3 to 37% for the change from wet to dry process. When the plantation area was increased by 1 ha and the palm oil extraction was changed from wet to dry process, and the change included dLUC and iLUC, the GHG savings ranged from ?0.94 to 5.08 t CO2 eq/ha year. The iLUC was the main GHG emission source. The GHG saving mostly originated from the change of extraction process and from the dLUC effect. Based on the potential use of biodiesel production from oil palm, during 2015–2036 in Thailand, when the extraction process was changed and dLUC and iLUC effects were included, the saving in GHG emissions was estimated to range from ?35,454 to 274,774 t CO2 eq/year.

Conclusions

The change of palm oil extraction process and the LUC effects could minimize the GHG emissions from the palm oil industry. This advantage encourages developing policies that support the dry extraction process and contribute to sustainable developments in palm oil production.
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9.

Purpose

This study aims at accounting for the variation in electricity production, processes and related impacts depending on season (heating, cooling), day of the week (tertiary building) and hour of the day. In this context, this paper suggests two alternative methods to integrate grid-building interaction in life cycle assessment of buildings and districts.

Methods

An attributional dynamic method (AD) and a marginal dynamic method (MD) are compared with an annual average method (AA), representative of standard practice, using electric space heating as an illustrative case. The different methods are based on a dispatch model simulating electricity supply on an hourly basis, averaging historically observed climatic and economic variability. The meteorological inputs of the model are identical to those of the building energy simulation. Therefore, the environmental benefits from smart buildings and onsite renewable energy production are more accurately evaluated.

Results and discussion

Using electricity production (or supply) data for a specific past year is a common practice in building LCA. This practice is sensitive to economic and meteorological hazards. The suggested methodology is based on a proposed reference year mitigating these hazards and thus could be seen as more representative of average impacts. Depending on the chosen approach (average or marginal) to evaluate electricity supply related impacts, the carbon footprint of the electric space heating option for the studied low-energy house in France is evaluated to 61.4 to 84.9 g CO2eq kWh?1 (AA), 78.8 to 110.2 g CO2eq kWh?1 (AD) and 765.1 to 928.7 g CO2eq kWh?1 (MD). Compared to wood and gas boiler, 22–107 and 218–284 g CO2eq kWh?1 respectively, the ranking between the different technical options depends on the chosen approach. Uncertainty analysis does not undermine the interpretation of the results.

Conclusions

The proposed electricity system model allows a more precise and representative evaluation of electricity supply related impacts in LCA compared to standard practices. Two alternative methods are suggested corresponding to attributional and consequential LCA. The approach has to be chosen in line with the assessment objectives (e.g. certification, ecodesign). Prospective assessment integrating long-term evolution of the electric system and influence of global warming on buildings behaviour are identified as relevant future research subjects.
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10.

Purpose

Variability in consumer behaviour can significantly influence the environmental performance of products and their associated impacts and this is typically not quantified in life cycle assessments. The goal of this paper is to demonstrate how consumer behaviour data can be used to understand and quantify the variability in the greenhouse gas emissions from domestic laundry washing across Europe.

Methods

Data from a pan-European consumer survey of product usage and washing habits was combined with internal company data on product format greenhouse gas (GHG) footprints and in-home measurement of energy consumption of laundry washing as well as literature data to determine the GHG footprint of laundry washing. The variability associated with four laundry detergent product formats and four wash temperature settings in washing machines were quantified on a per wash cycle basis across 23 European countries. The variability in GHG emissions associated with country electricity grid mixes was also taken into account. Monte Carlo methods were used to convert the variability in the input parameters into variability of the life cycle GHG emissions. Rank correlation analysis was used to quantify the importance of the different sources of variability.

Results and discussion

Both inter-country differences in background electricity mix as well as intra-country variation in consumer behaviour are important for determining the variability in life cycle GHG emissions of laundry detergents. The average GHG emissions related to the laundry washing process in the 23 European countries in 2014 was estimated to be 5?×?102 g CO2?eq/wash cycle, but varied by a factor of 6.5 between countries. Intra-country variability is between a factor of 3.5 and 5.0 (90% interval). For countries with a mainly fossil-based electricity system, the dominant source of variability in GHG emissions results from consumer choices in the use of washing machines. For countries with a relatively low-carbon electricity mix, variability in life cycle GHG emissions is mainly determined by laundry product-related parameters.

Conclusions

The combination of rich data sources enabled the quantification of the variability in the life cycle GHG emissions of laundry washing which is driven by a variety of consumer choices, manufacturer choices and infrastructural differences of countries. The improved understanding of the variability needs to be balanced against the cost and challenges of assessing of consumer habits.
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11.

Objectives

To degrade enzymatically bisphenol A (BPA) that causes serious environmental concerns and is difficult to be degraded by chemical or physical methods.

Results

BPA (150 mg l?1) was completely degraded by chloroperoxidase (CPO)/H2O2 within 7 min at room temperature, atmospheric pressure with the enzyme at 6 μg CPO ml?1. The degradation products were identified by HPLC–MS, which suggested involvement of multiple steps. Enzymatic treatment followed by existing bioremediation technologies (activated sludge) enhanced removal of COD from 9 to 54 %. Using an ecotoxicity evaluation with Chlorella pyrenoidosa, the degradation products had a lower toxicity than BPA.

Conclusion

BPA can be degraded rapidly and efficiently under mild conditions with chloroperoxidase at 6 μg ml?1. The degradation products had a lower toxicity than BPA.
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12.

Objectives

To improve the production and activity of an alkaline zinc metalloprotease from Salinivibrio proteolyticus in response to ZnSO4 (ionic and nanoparticle forms) and low intensity direct electric current (LIDC).

Results

A DC of 50 µA for 10 min increased enzyme production from 35 to 53 U ml?1 when applied to the stationary phase bacterial cells. Zn2+ improved enzyme production better than zinc nanoparticles (52 vs. 43.5 U ml?1). Zinc nanoparticles (0.5 mM) added to an enzyme reaction mixture containing casein (0.65 %) and 20 mM Tris/HCl buffer (pH 8) improved enzyme activity more than Zn2+ (42 vs. 36 U ml?1).

Conclusion

LIDC exposure (50 µA, 10 min) to the stationary phase bacterial cells increases metalloprotease production in Salinivibrio. A low concentration of zinc nanoparticles (0.5 mM) increases maximum enzyme activity.
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13.

Purpose

The emission of greenhouse gases (GHG) is a key criterion in the environmental assessment of biofuels. Life cycle inventories taking into account the latest methodological developments are an essential prerequisite for this assessment. In the last years, substantial progresses in the modelling of nitrogen emissions relevant for the climate as well as in modelling the emissions from land use change (LUC) have been achieved. Therefore, the biomass production inventories in the ecoinvent database were revised to take into account these developments.

Methods

The IPCC method tier 1 has been used for the assessment of N2O emissions. Induced emissions from NH3 and NO3 were included as well. Due to the importance of the latter emissions for N2O formation, these emissions have also been updated and harmonised. The Agrammon model was used for the NH3 emissions. The SALCA-NO3 model has been applied in the European inventories to estimate nitrate leaching, whilst in non-European inventories the SQCB-NO3 model has been used. The quantification of the land use change areas has been based on annualized, retrospective data of the last 20 years. All carbon pools (from aboveground biomass to soil organic carbon) were considered and differentiated on a regional level for all of the natural vegetation categories affected. Whenever possible, default values and methods from the IPCC 2006 were applied.

Results and discussion

The changes for ammonia emissions were generally very small (?5 % on average). The nitrate emissions increased on average by +13 %, but this slight trend is the result of important downward and upward changes, whilst the average N2O emissions decreased by ?26 %. For the existing inventories of soybean, palm oil and sugarcane production, significant increases of GHG emissions resulted from LUC modelling. This was mainly due to the consistent inclusion of all carbon stocks according to the IPCC guidelines. The calculation method can also result in important C sequestration effects in certain cases like African Jatropha production.

Conclusions

The changes in greenhouse gas emissions due to the updated methodology were significant. This shows that life cycle assessment studies for biofuels using older methodological bases need to be revised and could lead to different conclusions. The implemented and cultivated superstructure for LUC modelling is modular and flexible and can be easily extended to other important crop activities. The new parameterisation functionality applied for the activities provides powerful means for the simple generation of site-specific activities.
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14.

Objectives

To improve the production of α-ketoglutaric acid (α-KG) from l-glutamate by whole-cell biocatalysis.

Results

A novel and highly active l-glutamate oxidase, SmlGOX, from Streptomyces mobaraensis was overexpressed and purified. The recombinant SmlGOX was approx. 64 kDa by SDS-PAGE. SmlGOX had a maximal activity of 125 ± 2.7 U mg?1 at pH 6.0, 35 oC. The apparent Km and Vmax values of SmlGOX were 9.3 ± 0.5 mM and 159 ± 3 U mg?1, respectively. Subsequently, a co-expression plasmid containing the SmlGOX and KatE genes was constructed to remove H2O2, and the protein levels of SmlGOX were improved by codon optimization. Finally, by optimizing the whole-cell transformation conditions, the production of α-KG reached 77.4 g l?1 with a conversion rate from l-glutamate of 98.5% after 12 h.

Conclusions

An efficient method for the production of α-KG was established in the recombinant Escherichia coli, and it has a potential prospect in industrial application.
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15.

Purpose

To evaluate the efficiency of corneal collagen cross-linking (CXL) in addition to topical voriconazole in cases with mycotic keratitis.

Design

Retrospective case series in a tertiary university hospital.

Participants

CXL was performed on 13 patients with mycotic keratitis who presented poor or no response to topical voriconazole treatment.

Methods

The clinical features, symptoms, treatment results and complications were recorded retrospectively. The corneal infection was graded according to the depth of infection into the stroma (from grade 1 to grade 3). The visual analogue scale was used to calculate the pain score before and 2 days after surgery.

Main Outcome Measures

Grade of the corneal infection.

Results

Mean age of 13 patients (6 female and 7 male) was 42.4 ± 17.7 years (20–74 years). Fungus was demonstrated in culture (eight patients) or cytological examination (five patients). Seven of the 13 patients (54%) were healed with topical voriconazole and CXL adjuvant treatment in 26 ± 10 days (15–40 days). The remaining six patients did not respond to CXL treatment; they initially presented with higher grade ulcers. Pre- and post-operative pain score values were 8 ± 0.8 and 3.5 ± 1, respectively (p < 0.05).

Conclusions

The current study suggests that adjunctive CXL treatment is effective in patients with small and superficial mycotic ulcers. These observations require further research by large randomized clinical trials.
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16.

Purpose

The purpose of the study was to outline and demonstrate a new geographic information system (GIS)-based approach for utilising spatial geological data in three dimensions (i.e. length, width and depth) to improve estimates on earthworks during early stages of road infrastructure planning.

Methods

This was undertaken by using three main methodological steps: mass balance calculation, life cycle inventory analysis and spatial mapping of greenhouse gas (GHG) emissions and energy use. The mass balance calculation was undertaken in a GIS environment using two assumptions of geological stratigraphy for two proposed alternative road corridors in Sweden. The estimated volumes of excavated soil, blasted rock and filling material were later multiplied with the GHG emission and energy use factors for these processes, to create spatial data and maps in order to show potential impacts of the studied road corridors. The proposed GIS-based approach was evaluated by comparing with actual values received after one alternative was constructed.

Results and discussion

The results showed that the estimate of filling material was the most accurate (about 9 % deviation from actual values), while the estimate for excavated soil and blasted rock resulted in about 38 and 80 % deviation, respectively, from the actual values. It was also found that the total volume of excavated and ripped soils did not change when accounting for stratigraphy.

Conclusions

The conclusion of this study was that more information regarding embankment height and actual soil thickness would further improve the model, but the proposed GIS-based approach shows promising results for usage in LCA at an early stage of road infrastructure planning. Thus, by providing better data quality, GIS in combination with LCA can enable planning for a more sustainable transport infrastructure.
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17.

Aims

Slow or failed tree regeneration after forest disturbance is increasingly observed in the central European Alps, potentially amplifying the carbon (C) loss from disturbance. We aimed at quantifying C dynamics of a poorly regenerating disturbance site with a special focus on the role of non-woody ground vegetation.

Methods

Soil CO2 efflux, fine root biomass, ground vegetation biomass, tree increment and litter input were assessed in (i) an undisturbed section of a ~ 110 years old Norway spruce stand, (ii) in a disturbed section which was clear-cut six years ago (no tree regeneration), and (iii) in a disturbed section which was clear-cut three years ago (no tree regeneration).

Results

Total soil CO2 efflux was similar across all stand sections (8.5 ± 0.2 to 8.9 ± 0.3 t C ha?1 yr.?1). The undisturbed forest served as atmospheric C sink (2.1 t C ha?1 yr.?1), whereas both clearings were C sources to the atmosphere. The source strength three years after disturbance (?5.5 t C ha?1 yr.?1) was almost twice as high as six years after disturbance (?2.9 t C ha?1 yr.?1), with declining heterotrophic soil respiration and the high productivity of dense graminoid ground vegetation mitigating C loss.

Conclusions

C loss after disturbance decreases with time and ground vegetation growth. Dense non-woody ground vegetation cover can hamper tree regeneration but simultaneously decrease the ecosystem C loss. The role of ground vegetation should be more explicitly taken into account in forest C budgets assessing disturbance effects.
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18.

Purpose

Governments around the world encourage the use of biofuels through fuel standard policies that require the addition of renewable diesel in diesel fuel from fossil fuels. Environmental impact studies of the conversion of biomass to renewable diesel have been conducted, and life cycle assessments (LCA) of the conversion of lignocellulosic biomass to hydrogenation-derived renewable diesel (HDRD) are limited, especially for countries with cold climates like Canada.

Methods

In this study, an LCA was conducted on converting lignocellulosic biomass to HDRD by estimating the well-to-wheel greenhouse gas (GHG) emissions and fossil fuel energy input of the production of biomass and its conversion to HDRD. The approach to conduct this LCA includes defining the goal and scope, compiling a life cycle inventory, conducting a life cycle impact assessment, and executing a life cycle interpretation. All GHG emissions and fossil fuel energy inputs were based on a fast pyrolysis plant capacity of 2000 dry tonnes biomass/day. A functional unit of 1 MJ of HDRD produced was adopted as a common unit for data inputs of the life cycle inventory. To interpret the results, a sensitivity analysis was performed to measure the impact of variables involved, and an uncertainty analysis was performed to assess the confidence of the results.

Results and discussion

The GHG emissions of three feedstocks studied—whole tree (i.e., chips from cutting the whole tree), forest residues (i.e., chips from branches and tops generated from logging operations), and agricultural residues (i.e., straw from wheat and barley)—range from 35.4 to 42.3 g CO2,eq/MJ of HDRD (i.e., lowest for agricultural residue- and highest for forest residue-based HDRD); this is 53.4–61.1 % lower than fossil-based diesel. The net energy ratios range from 1.55 to 1.90 MJ/MJ (i.e., lowest for forest residue- and highest for agricultural residue-based HDRD) for HDRD production. The difference in results among feedstocks is due to differing energy requirements to harvest and pretreat biomass. The energy-intensive hydroprocessing stage is responsible for most of the GHG emissions produced for the entire conversion pathway.

Conclusions

Comparing feedstocks showed the significance of the efficiency in the equipment used and the physical properties of biomass in the production of HDRD. The overall results show the importance of efficiency at the hydroprocessing stage. These findings indicate significant GHG mitigation benefits for the oil refining industry using available lignocellulosic biomass to produce HDRD for transportation fuel.
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19.

Objective

To re-engineer the active site of proteins for non-natural substrates using a position-based prediction method (PBPM).

Results

The approach has been applied to re-engineer the E. coli glutamate dehydrogenase to alter its substrate from glutamate to homoserine for a de novo 1,3-propanediol biosynthetic pathway. After identification of key residues that determine the substrate specificity, residue K92 was selected as a candidate site for mutation. Among the three mutations (K92V, K92C, and K92M) suggested by PBPM, the specific activity of the best mutant (K92 V) was increased from 171 ± 35 to 1328 ± 71 μU mg?1.

Conclusion

The PBPM approach has a high efficiency for re-engineering the substrate specificity of natural enzymes for new substrates.
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20.

Objectives

To use permeabilized cells of the fission yeast, Schizosaccharomyces pombe, that expresses human UDP-glucose 6-dehydrogenase (UGDH, EC 1.1.1.22), for the production of UDP-glucuronic acid from UDP-glucose.

Results

In cell extracts no activity was detected. Therefore, cells were permeabilized with 0.3 % (v/v) Triton X-100. After washing away all low molecular weight metabolites, the permeabilized cells were directly used as whole cell biocatalyst. Substrates were 5 mM UDP-glucose and 10 mM NAD+. Divalent cations were not added to the reaction medium as they promoted UDP-glucose hydrolysis. With this reaction system 5 mM UDP-glucose were converted into 5 mM UDP-glucuronic acid within 3 h.

Conclusions

Recombinant permeabilized cells of S. pombe can be used to synthesize UDP-glucuronic acid with 100 % yield and selectivity.
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