Green water footprint distribution of the CSS case

<p><strong>Figure 3.</strong> Green water footprint distribution of the CSS case. The maps represent water footprint under the scenarios of refinery size 2000 DMTD, with 7% and 30% of feedstock ash and moisture content, respectively.</p> <p><strong>Abstract</strong></p> <p>Forest residue has been proposed as a feasible candidate for cellulosic biofuels. However, the number of studies assessing its water use remains limited. This work aims to analyze the impacts of forest-based biofuel on water resources and quality by using a water footprint approach. A method established here is tailored to the production system, which includes softwood, hardwood, and short-rotation woody crops. The method is then applied to selected areas in the southeastern region of the United States to quantify the county-level water footprint of the biofuel produced via a mixed alcohol gasification process, under several logistic systems, and at various refinery scales. The results indicate that the blue water sourced from surface or groundwater is minimal, at 2.4 liters per liter of biofuel (l/l). The regional-average green water (rainfall) footprint falls between 400 and 443 l/l. The biofuel pathway appears to have a low nitrogen grey water footprint averaging 25 l/l at the regional level, indicating minimal impacts on water quality. Feedstock mix plays a key role in determining the magnitude and the spatial distribution of the water footprint in these regions. Compared with other potential feedstock, forest wood residue shows promise with its low blue and grey water footprint.</p

Calculation steps and key data sources

<p><strong>Figure 1.</strong> Calculation steps and key data sources. Sources of data or models used to obtain each variable are marked in parentheses, which are detailed in section <a href="http://iopscience.iop.org/1748-9326/8/3/035015/article#erl470159s2" target="_blank">2</a>.</p> <p><strong>Abstract</strong></p> <p>Forest residue has been proposed as a feasible candidate for cellulosic biofuels. However, the number of studies assessing its water use remains limited. This work aims to analyze the impacts of forest-based biofuel on water resources and quality by using a water footprint approach. A method established here is tailored to the production system, which includes softwood, hardwood, and short-rotation woody crops. The method is then applied to selected areas in the southeastern region of the United States to quantify the county-level water footprint of the biofuel produced via a mixed alcohol gasification process, under several logistic systems, and at various refinery scales. The results indicate that the blue water sourced from surface or groundwater is minimal, at 2.4 liters per liter of biofuel (l/l). The regional-average green water (rainfall) footprint falls between 400 and 443 l/l. The biofuel pathway appears to have a low nitrogen grey water footprint averaging 25 l/l at the regional level, indicating minimal impacts on water quality. Feedstock mix plays a key role in determining the magnitude and the spatial distribution of the water footprint in these regions. Compared with other potential feedstock, forest wood residue shows promise with its low blue and grey water footprint.</p

Green and grey water spatial distribution of the DPSS case under the combination of 30% and 7% moist and ash contents, respectively

<p><strong>Figure 4.</strong> Green and grey water spatial distribution of the DPSS case under the combination of 30% and 7% moist and ash contents, respectively.</p> <p><strong>Abstract</strong></p> <p>Forest residue has been proposed as a feasible candidate for cellulosic biofuels. However, the number of studies assessing its water use remains limited. This work aims to analyze the impacts of forest-based biofuel on water resources and quality by using a water footprint approach. A method established here is tailored to the production system, which includes softwood, hardwood, and short-rotation woody crops. The method is then applied to selected areas in the southeastern region of the United States to quantify the county-level water footprint of the biofuel produced via a mixed alcohol gasification process, under several logistic systems, and at various refinery scales. The results indicate that the blue water sourced from surface or groundwater is minimal, at 2.4 liters per liter of biofuel (l/l). The regional-average green water (rainfall) footprint falls between 400 and 443 l/l. The biofuel pathway appears to have a low nitrogen grey water footprint averaging 25 l/l at the regional level, indicating minimal impacts on water quality. Feedstock mix plays a key role in determining the magnitude and the spatial distribution of the water footprint in these regions. Compared with other potential feedstock, forest wood residue shows promise with its low blue and grey water footprint.</p

Assessing County-Level Water Footprints of Different Cellulosic-Biofuel Feedstock Pathways

While agricultural residue is considered as a near-term feedstock option for cellulosic biofuels, its sustainability must be evaluated by taking water into account. This study aims to analyze the county-level water footprint for four biofuel pathways in the United States, including bioethanol generated from corn grain, stover, wheat straw, and biodiesel from soybean. The county-level blue water footprint of ethanol from corn grain, stover, and wheat straw shows extremely wide variances with a national average of 31, 132, and 139 L of water per liter biofuel (L_w/L_bf), and standard deviation of 133, 323, and 297 L_w/L_bf, respectively. Soybean biodiesel production results in a blue water footprint of 313 L_w/L_bf on the national average with standard deviation of 894 L_w/L_bf. All biofuels show a greater green water footprint than the blue one. This work elucidates how diverse spatial resolutions affect biofuel water footprints, which can provide detailed insights into biofuels’ implications on local water sustainability

Distribution of biofuel blue water and green water footprint under different sizing (in DMTD) with feedstock containing 7% ash and 30% moist content

<p><strong>Figure 2.</strong> Distribution of biofuel blue water and green water footprint under different sizing (in DMTD) with feedstock containing 7% ash and 30% moist content. Green water is composed of water associated with thinning residue (LOGT), logging residue (LOGR), short-rotation woody crop (SRWC), and pulpwood from softwood (SW) and hardwood (HW). The values of the conventional case are averaged between Aiken and Rankin by using ethanol production as a weighting factor.</p> <p><strong>Abstract</strong></p> <p>Forest residue has been proposed as a feasible candidate for cellulosic biofuels. However, the number of studies assessing its water use remains limited. This work aims to analyze the impacts of forest-based biofuel on water resources and quality by using a water footprint approach. A method established here is tailored to the production system, which includes softwood, hardwood, and short-rotation woody crops. The method is then applied to selected areas in the southeastern region of the United States to quantify the county-level water footprint of the biofuel produced via a mixed alcohol gasification process, under several logistic systems, and at various refinery scales. The results indicate that the blue water sourced from surface or groundwater is minimal, at 2.4 liters per liter of biofuel (l/l). The regional-average green water (rainfall) footprint falls between 400 and 443 l/l. The biofuel pathway appears to have a low nitrogen grey water footprint averaging 25 l/l at the regional level, indicating minimal impacts on water quality. Feedstock mix plays a key role in determining the magnitude and the spatial distribution of the water footprint in these regions. Compared with other potential feedstock, forest wood residue shows promise with its low blue and grey water footprint.</p

Formation of Hexabranched GeO₂ Nanoparticles via a Reverse Micelle System

We report the first synthesis of GeO2 nanoparticles with six symmetrically arranged branches running along the long axis of each particle. The nanoparticles have a shape resembling that of a star fruit. A reverse micelle system with Triton X-100 serving as the capping surfactant for the aqueous phase and n-hexanol as the cosurfactant was adopted. Ge(OEt)4 was selected as the germanium source. Using the optimal synthesis procedure by reacting the mixture at room temperature for 3 h, hexabranched GeO2 particles with an average length of 185 nm were produced. The products have been examined by FE-SEM, TEM, X-ray diffraction, and FT-IR techniques. GeO2 nanoparticles with structually well-developed branches were gnereated only with solution pH values in the range of 0.9−1.1. At a low [H2O]/[Ge(OEt)4] molar ratio of 45, particles having a hexagonal bipyramidal shape but without branch formation were observed. Increasing this ratio to 90, branches begin to appear from the six side edges of the particles. By simply varying the reaction time, the sizes of the branched GeO2 nanoparticles can be adjusted from around 100 nm in length to as large as 300 nm in length

Water Embodied in Bioethanol in the United States

Prior studies have estimated that a liter of bioethanol requires 263−784 L of water from corn farm to fuel pump, but these estimates have failed to account for the widely varied regional irrigation practices. By using regional time-series agricultural and ethanol production data in the U.S., this paper estimates the state-level field-to-pump water requirement of bioethanol across the nation. The results indicate that bioethanol’s water requirements can range from 5 to 2138 L per liter of ethanol depending on regional irrigation practices. The results also show that as the ethanol industry expands to areas that apply more irrigated water than others, consumptive water appropriation by bioethanol in the U.S. has increased 246% from 1.9 to 6.1 trillion liters between 2005 and 2008, whereas U.S. bioethanol production has increased only 133% from 15 to 34 billion liters during the same period. The results highlight the need to take regional specifics into account when implementing biofuel mandates

Data_Sheet_1_Dialysis Duration and Glucose Exposure Amount Do Not Increase Mortality Risk in Peritoneal Dialysis Patients: A Population-Based Cohort Study From 2004 to 2012.pdf

BackgroundAlthough the bio-incompatibility of glucose-based peritoneal dialysis (PD) solution is well documented, it is used worldwide. How PD duration and the amount of dialyzate glucose exposure affect survival in patients with end-stage renal disease remain inconclusive due to improper study designs in the extant literature.MethodsAll incident patients with PD from 2004 to 2007 who were older than 18 years in Taiwan were included. Patients were censored when they received a transplant or at the end of 2012. Glucose exposure through PD solution was calculated by the mean glucose contained per liter when receiving PD. For those who had already shifted to hemodialysis (HD) and survived longer than 2, 3, and 4 years (the index dates), the cause-specific Cox regression model was used to make the survival comparison by PD duration and mean glucose concentration in these three cohorts, respectively. The model was adjusted by demographics, case-mix, time cohort (2004–2005 vs. 2006–2007), peritonitis episode (none vs. ≥once), and mean PD solution glucose exposure (tertile).ResultsA total of 3,226 patients were included, with a mean age of 53.4 ± 15.2 years, 44.6% being male, and 34.2% having diabetes mellitus. The 1, 2, 3, and 4-year survival rates were 94, 87, 80, and 74%, while technical survival rates were 86, 70, 56, and 45%, respectively. The overall transplant events were 309 (9.6%) only. There were 389, 495, and 553 incident patients with PD shifting to HD included in 2-, 3-, and 4-year cohort, respectively. The population with moderate glucose concentration exposure had the highest mortality, and the high glucose concentration exposure had non-significant lower mortality in each cohort. In various fixed time-window cohorts, the duration of PD treatment did not increase mortality risk after adjustments. In addition, glucose exposure did not affect the mortality rate.ConclusionFor incident PD patients with PD duration no longer than 4 years, neither PD duration nor glucose exposure amount increases the long-term mortality risk.</p

Association of bacterial genotypes and epidemiological features with treatment failure in hemodialysis patients with methicillin-resistant <i>Staphylococcus aureus</i> bacteremia - Fig 1

(A) The proportions of healthcare-associated community onset (CO)- and healthcare-associated hospital onset (HO)-MRSA bacteremia in hemodialysis cases in a Taiwanese medical center from 2009 to 2014. A linear trend toward an increasing proportion of CO-MRSA during 2009 to 2014 was observed (R2 = 0.662, p = 0.062). (B) The proportions of CA genotypes (SCCmec type IV, V) and HA genotypes (SCCmec type I, II or III strains) in hemodialysis cases in a Taiwanese medical center from 2009 to 2014. A linear trend toward an increasing proportion of CA genotypes during 2009 to 2014 was observed (R2 = 0.791, p = 0.018).</p

Association of bacterial genotypes and epidemiological features with treatment failure in hemodialysis patients with methicillin-resistant <i>Staphylococcus aureus</i> bacteremia

<div><p>Objectives</p><p>Methicillin-resistant <i>Staphylococcus aureus</i> (MRSA) infections in the hemodialysis (HD) population are epidemiologically classified as healthcare-associated infections. The data about the clinical impact and bacterial characteristics of hospital-onset (HO)- and community-onset (CO)-MRSA in HD patients are scarce. The current study analyzed the difference in the clinical and molecular characteristics of HO-MRSA and CO-MRSA.</p><p>Methods</p><p>We performed a retrospective review and molecular analysis of clinical isolates from 106 HD patients with MRSA bacteremia from 2009 to 2014. CA genotypes were defined as isolates carrying the SCC<i>mec</i> type IV or V, and HA genotypes were defined as isolates harboring SCC<i>mec</i> type I, II, or III.</p><p>Results</p><p>CO-MRSA infections occurred in 76 patients, and 30 patients had HO-MRSA infections. There was no significant difference in the treatment failure rates between patients with CO-MRSA infections and those with HO-MRSA infections. CA genotypes were associated with less treatment failure (odds ratio [OR]: 0.18; 95% confidence interval [95% CI], 0.07–0.49; <i>p</i> = 0.001). For isolates with a vancomycin minimum inhibitory concentration (MIC) < 1.5 mg/L, the multivariate analysis revealed that HA genotypes and cuffed tunneled catheter use were associated with treatment failure. For isolates with a vancomycin MIC ≥1.5 mg/L, the only risk factor for treatment failure was a higher Pitt score (OR: 1.76; 95% CI, 1.02–3.05; <i>p</i> = 0.043).</p><p>Conclusion</p><p>CA genotypes, but not the epidemiological classification of CO-MRSA, impacted the clinical outcome of MRSA bacteremia in the HD population.</p></div