Deborah L. Sills

Quantitative Uncertainty Analysis of Life Cycle Assessment for Algal Biofuel Production

As a result of algaes promise as a renewable energy feedstock, numerous studies have used Life Cycle Assessment (LCA) to quantify the environmental performance of algal biofuels, yet there is no consensus of results among them. Our work, motivated by the lack of comprehensive uncertainty analysis in previous studies, uses a Monte Carlo approach to estimate ranges of expected values of LCA metrics by incorporating parameter variability with empirically specified distribution functions. Results show that large uncertainties exist at virtually all steps of the biofuel production process. Although our findings agree with a number of earlier studies on matters such as the need for wet lipid extraction, nutrients recovered from waste streams, and high energy coproducts, the ranges of reported LCA metrics show that uncertainty analysis is crucial for developing technologies, such as algal biofuels. In addition, the ranges of energy return on (energy) invested (EROI) values resulting from our analysis help explain the high variability in EROI values from earlier studies. Reporting results from LCA models as ranges, and not single values, will more reliably inform industry and policy makers on expected energetic and environmental performance of biofuels produced from microalgae.

Using FTIR to predict saccharification from enzymatic hydrolysis of alkali‐pretreated biomasses

Fourier transform infrared, attenuated total reflectance (FTIR‐ATR) spectroscopy combined with partial least squares (PLS) regression accurately predicted 72‐h glucose and xylose conversions (g sugars/100 g potential sugars) and yields (g sugars/100 g dry solids) from cellulase‐mediated hydrolysis of alkali‐pretreated lignocellulose. Six plant biomasses that represent a variety of potential biofuel feedstocks—two switchgrass cultivars, big bluestem grass, a low‐impact, high‐diversity mixture of 32 species of prairie biomasses, mixed hardwood, and corn stover—were subjected to four levels of low‐temperature NaOH pretreatment to produce 24 samples with a wide range of potential digestibility. PLS models were constructed by correlating FTIR spectra of pretreated samples to measured values of gluose and xylose conversions and yields. Variable selection, based on 90% confidence intervals of regression‐coefficient matrices, improved the predictive ability of the models, while simplifying them considerably. Final models predicted sugar conversions with coefficient of determination for cross‐validation (Q2) values of 0.90 for glucose and 0.89 for xylose, and sugar yields with Q2 values of 0.92 for glucose and 0.91 for xylose. The sugar‐yield models are noteworthy for their ability to predict enzymatic saccharification per mass dry solids without a priori knowledge of the composition of the solids. All peaks retained in the final regression coefficient matrices were previously assigned to chemical bonds and functional groups in lignocellulose, demonstrating that the models were based on real chemical information. This study demonstrates that FTIR spectroscopy combined with PLS regression can be used to rapidly estimate sugar conversions and yields from enzymatic hydrolysis of pretreated plant biomass. Biotechnol. Bioeng. 2012; 109:353–362.

Assessment of commercial hemicellulases for saccharification of alkaline pretreated perennial biomass.

The objective of this research was to measure the effects of different cellulase and hemicellulase mixtures on fermentable sugar production from two different perennial biomasses--switchgrass and a low-impact, high-diversity prairie biomass mixture (LIHD). Each was subjected to NaOH pretreatment, followed by hydrolysis with a commercial cellulase and β-glucosidase mixture [CB] supplemented with either of two hemicellulases. For both biomasses, there was little gain in sugar yield when using CB alone beyond 20-25 mg/g TS; further gain in yield was possible only through hemicellulase supplementation. An equation that modeled CB and hemicellulase effects as occurring independently fit the data reasonably well, except at the lowest of cellulase loadings with hemicellulase, where synergistic interactions were evident. Examination of the marginal effectiveness of enzyme loadings (incremental grams sugar per incremental mg enzyme) over a broad range of loadings suggests that there is no need to customize enzymatic hydrolysis for NaOH-pretreated switchgrass and LIHD.

Using FTIR spectroscopy to model alkaline pretreatment and enzymatic saccharification of six lignocellulosic biomasses.

Fourier transform infrared, attenuated total reflectance (FTIR‐ATR) spectroscopy, combined with partial least squares (PLS) regression, accurately predicted solubilization of plant cell wall constituents and NaOH consumption through pretreatment, and overall sugar productions from combined pretreatment and enzymatic hydrolysis. PLS regression models were constructed by correlating FTIR spectra of six raw biomasses (two switchgrass cultivars, big bluestem grass, a low‐impact, high‐diversity mixture of prairie biomasses, mixed hardwood, and corn stover), plus alkali loading in pretreatment, to nine dependent variables: glucose, xylose, lignin, and total solids solubilized in pretreatment; NaOH consumed in pretreatment; and overall glucose and xylose conversions and yields from combined pretreatment and enzymatic hydrolysis. PLS models predicted the dependent variables with the following values of coefficient of determination for cross‐validation (Q2): 0.86 for glucose, 0.90 for xylose, 0.79 for lignin, and 0.85 for total solids solubilized in pretreatment; 0.83 for alkali consumption; 0.93 for glucose conversion, 0.94 for xylose conversion, and 0.88 for glucose and xylose yields. The sugar yield models are noteworthy for their ability to predict overall saccharification through combined pretreatment and enzymatic hydrolysis per mass dry untreated solids without a priori knowledge of the composition of solids. All wavenumbers with significant variable‐important‐for‐projection (VIP) scores have been attributed to chemical features of lignocellulose, demonstrating the models were based on real chemical information. These models suggest that PLS regression can be applied to FTIR‐ATR spectra of raw biomasses to rapidly predict effects of pretreatment on solids and on subsequent enzymatic hydrolysis. Biotechnol. Bioeng. 2012; 109:894–903.

Prospects for energy recovery during hydrothermal and biological processing of waste biomass.

Thermochemical and biological processes represent promising technologies for converting wet biomasses, such as animal manure, organic waste, or algae, to energy. To convert biomass to energy and bio-chemicals in an economical manner, internal energy recovery should be maximized to reduce the use of external heat and power. In this study, two conversion pathways that couple hydrothermal liquefaction with anaerobic digestion or catalytic hydrothermal gasification were compared. Each of these platforms is followed by two alternative processes for gas utilization: 1) combined heat and power; and 2) combustion in a boiler. Pinch analysis was applied to integrate thermal streams among unit processes and improve the overall system efficiency. A techno-economic analysis was conducted to compare the feasibility of the four modeled scenarios under different market conditions. Our results show that a systems approach designed to recover internal heat and power can reduce external energy demands and increase the overall process sustainability.

Algal food and fuel coproduction can mitigate greenhouse gas emissions while improving land and water-use efficiency

The goals of ensuring energy, water, food, and climate security can often conflict. Microalgae (algae) are being pursued as a feedstock for both food and fuels—primarily due to algaes high areal yield and ability to grow on non-arable land, thus avoiding common bioenergy-food tradeoffs. However, algal cultivation requires significant energy inputs that may limit potential emission reductions. We examine the tradeoffs associated with producing fuel and food from algae at the energy–food–water–climate nexus. We use the GCAM integrated assessment model to demonstrate that algal food production can promote reductions in land-use change emissions through the offset of conventional agriculture. However, fuel production, either via co-production of algal food and fuel or complete biomass conversion to fuel, is necessary to ensure long-term emission reductions, due to the high energy costs of cultivation. Cultivation of salt–water algae for food products may lead to substantial freshwater savings; but, nutrients for algae cultivation will need to be sourced from waste streams to ensure sustainability. By reducing the land demand of food production, while simultaneously enhancing food and energy security, algae can further enable the development of terrestrial bioenergy technologies including those utilizing carbon capture and storage. Our results demonstrate that large-scale algae research and commercialization efforts should focus on developing both food and energy products to achieve environmental goals.

Geoengineering, marine microalgae, and climate stabilization in the 21st century

Society has set ambitious targets for stabilizing mean global temperature. To attain these targets, it will have to reduce CO2 emissions to near zero by mid-century and subsequently remove CO2 from the atmosphere during the latter half of the century. There is a recognized need to develop technologies for CO2 removal; however, attempts to develop direct air capture systems have faced both energetic and financial constraints. Recently, BioEnergy with Carbon Capture and Storage (BECCS) has emerged as a leading candidate for removing CO2 from the atmosphere. However, BECCS can have negative consequences on land, nutrient, and water use as well as biodiversity and food production. Here, we describe an alternative approach based on the large-scale industrial production of marine microalgae. When cultivated with proper attention to power, carbon, and nutrient sources, microalgae can be processed to produce a variety of biopetroleum products, including carbon neutral biofuels for the transportation sector and long-lived, potentially carbon-negative construction materials for the built environment. In addition to these direct roles in mitigating and potentially reversing the effects of fossil CO2 emissions, microalgae can also play an important indirect role. Because microalgae exhibit much higher primary production rates than terrestrial plants, they require much less land area to produce an equivalent amount of bioenergy and/or food. On a global scale, the avoided emissions resulting from displacement of conventional agriculture may exceed the benefits of microalgae biofuels in achieving climate stabilization goals.

Residential proximity to high-density poultry operations associated with campylobacteriosis and infectious diarrhea

Poultry carry zoonotic bacteria that can cause gastroenteritis in humans. Environmental transmission of pathogens from poultry operations may increase gastrointestinal infection risk in surrounding communities. To evaluate associations between residential proximity to high-density poultry operations and individual-level diarrheal illnesses, we conducted a nested case-control study among 514,488 patients in Pennsylvania (2006-2015). Using electronic health records, we identified cases of five gastrointestinal outcomes: three pathogen-specific infections, including Escherichia coli (n = 1425), Campylobacter (n = 567), and Salmonella (n = 781); infectious diarrhea (n = 781); and non-specific diarrhea (2012-2015; n = 28,201). We estimated an inverse-distance squared activity metric for poultry operations based on farm and patient addresses. Patients in the second and fourth (versus first) quartiles of the poultry operation activity metric had increased odds of Campylobacter (AOR [CI], Q2: 1.36 [1.01, 1.82]; Q3: 1.38 [0.98, 1.96]; Q4: 1.75 [1.31, 2.33]). Patients in the second, third, and fourth quartiles had increased odds of infectious diarrhea (Q2: 1.76 [1.29, 2.39]; Q3: 1.76 [1.09, 2.85]; Q4: 1.60 [1.12, 2.30]). Stratification revealed stronger relations of fourth quartile and both Campylobacter and infectious diarrhea in townships, the most rural community type in the study geography. Increasing extreme rainfall in the week prior to diagnosis strengthened fourth quartile Campylobacter associations. The poultry operation activity metric was largely unassociated with E. coli, Salmonella, and non-specific diarrhea. Findings suggest high-density poultry operations may be associated with campylobacteriosis and infectious diarrhea in nearby communities, highlighting additional public health concerns of industrial agriculture.