Sergio C. Capareda

Biochar pyrolytically produced from municipal solid wastes for aqueous As(V) removal: Adsorption property and its improvement with KOH activation

Biochar converted from waste products is being considered as an alternative adsorbent for removal of aqueous heavy metal(loid)s. In this work, experimental and modeling investigations were conducted to examine the effect of biochars pyrolytically produced from municipal solid wastes on removing aqueous As(V) before and after activated by 2M KOH solution. Results showed that the highest adsorption capacity of pristine biochars was 24.49 mg/g. The pseudo-second-order model and Langmuir adsorption isotherm model can preferably describe the adsorption process. The activated biochar showed enhanced As(V) adsorption ability with an adsorption capacity of 30.98 mg/g, which was more than 1.3 times of pristine biochars, and 2-10 times of modified biochars reported by other literatures. Increase of surface area and changes of porous texture, especially the functional groups on the surface of activated biochars are the major contributors to its more efficient adsorption of As(V).

Ligninolytic enzymes: a biotechnological alternative for bioethanol production

Ligninolytic fungi and enzymes (i.e., laccase, manganese peroxidase, and lignin peroxidase) have been applied recently in the production of second-generation biofuels. This review contains the analysis of ligninolytic enzymes and their applications in second-generation biofuels. In here, each of the ligninolytic enzymes was described analyzing their structures, catalysis, and reaction mechanism. Additionally, delignification and detoxification, the two most important applications of ligninolytic enzymes, were reviewed and analyzed. The analysis includes an evaluation of the biochemical process, feedstocks, and the ethanol production. This review describes the current situation of the ligninolytic enzymes technology and its future applications in bioethanol industry.

Seasonal and spatial variations of ammonia emissions from an open-lot dairy operation.

Abstract There is a need for a robust and accurate technique to measure ammonia (NH3) emissions from animal feeding operations (AFOs) to obtain emission inventories and to develop abatement strategies. Two consecutive seasonal studies were conducted to measure NH3 emissions from an open-lot dairy in central Texas in July and December of 2005. Data including NH3 concentrations were collected and NH3 emission fluxes (EFls), emission rates (ERs), and emission factors (EFs) were calculated for the open-lot dairy. A protocol using flux chambers (FCs) was used to determine these NH3 emissions from the open-lot dairy. NH3 concentration measurements were made using chemiluminescence-based analyzers. The ground-level area sources (GLAS) including open lots (cows on earthen corrals), separated solids, primary and secondary lagoons, and milking parlors were sampled to estimate NH3 emissions. The seasonal NH3 EFs were 11.6 ± 7.1 kg-NH3 yr-1head-1 for the summer and 6.2 ± 3.7 kg-NH3 yr-1head-1 for the winter season. The estimated annual NH3 EF was 9.4 ± 5.7 kg-NH3 yr-1head-1 for this open-lot dairy. The estimated NH3 EF for winter was nearly 47% lower than summer EF. Primary and secondary lagoons (∼37) and open-lot corrals (∼63%) in summer, and open-lot corrals (∼95%) in winter were the highest contributors to NH3 emissions for the open-lot dairy. These EF estimates using the FC protocol and real-time analyzer were lower than many previously reported EFs estimated based on nitrogen mass balance and nitrogen content in manure. The difference between the overall emissions from each season was due to ambient temperature variations and loading rates of manure on GLAS. There was spatial variation of NH3 emission from the open-lot earthen corrals due to variable animal density within feeding and shaded and dry divisions of the open lot. This spatial variability was attributed to dispirit manure loading within these areas.

Evaluation of ligninolytic enzymes, ultrasonication and liquid hot water as pretreatments for bioethanol production from cotton gin trash

Cotton gin trash (CGT) is a ubiquitous cotton-production-waste resource which can be used for ethanol production. In this research, seven combinations of three pretreatments; ultrasonication, liquid hot water and ligninolytic enzymes were evaluated on CGT to select the best pretreatments combination that increased the cellulose conversion and the ethanol yield in the saccharification and fermentation processes, respectively. The structural changes in the cellulose, hemicellulose and lignin from CGT were followed using FT-IR after each pretreatment. All the pretreatment combinations modified the CGTs structure and composition compared with the unpretreated CGT, and the majority of them improved release of sugars originally present in the CGT. The best results were achieved by the sequential combination of ultrasonication, hot water, and ligninolytic enzymes with an improvement of 10% in the ethanol yield and cellulose conversion compared to the other pretreatments. These results are a contribution to develop a feasible bioethanol production from CGT.

Capacity of biochar application to maintain energy crop productivity: soil chemistry, sorghum growth, and runoff water quality effects.

Pyrolysis of crop biomass generates a by-product, biochar, which can be recycled to sustain nutrient and organic C concentrations in biomass production fields. We evaluated effects of biochar rate and application method on soil properties, nutrient balance, biomass production, and water quality. Three replications of eight sorghum [ (L.) Moench] treatments were installed in box lysimeters under greenhouse conditions. Treatments comprised increasing rates (0, 1.5, and 3.0 Mg ha) of topdressed or incorporated biochar supplemented with N fertilizer or N, P, and K fertilizer. Simulated rain was applied at 21 and 34 d after planting, and mass runoff loss of N, P, and K was measured. A mass balance of total N, P, and K was performed after 45 d. Returning 3.0 Mg ha of biochar did not affect sorghum biomass, soil total, or Mehlich-3-extractable nutrients compared to control soil. Yet, biochar contributed to increased concentration of dissolved reactive phosphorus (DRP) and mass loss of total phosphorus (TP) in simulated runoff, especially if topdressed. It was estimated that up to 20% of TP in topdressed biochar was lost in surface runoff after two rain events. Poor recovery of nutrients during pyrolysis and excessive runoff loss of nutrients for topdressed biochar, especially K, resulted in negative nutrient balances. Efforts to conserve nutrients during pyrolysis and incorporation of biochar at rates derived from annual biomass yields will be necessary for biochar use in sustainable energy crop production.

Variogram Analysis of Hyperspectral Data to Characterize the Impact of Biotic and Abiotic Stress of Maize Plants and to Estimate Biofuel Potential

A considerable challenge in applied agricultural use of reflection-based spectroscopy is that most analytical approaches are quite sensitive to radiometric noise and/or low radiometric repeatability. In this study, hyperspectral imaging data were acquired from individual maize leaves and the main objective was to evaluate a classification system for detection of drought stress levels and spider mite infestation levels across maize hybrids and vertical position of maize leaves. A second objective was to estimate biomass and biofuel potential (heating value) of growing maize plants. Stepwise discriminant analysis was used to identify the five spectral bands (440, 462, 652, 706, and 784 nm) that contributed most to the classification of three levels of drought stress (moderate, subtle, and none) across hybrids, leaf position, and spider mite infestation. Regarding the five selected spectral bands, average reflectance values and standard variogram parameters (“nugget”, “sill”, and “range” derived from variogram analysis) were examined as indicators of spider mite and/or drought stress. There was consistent significant effect of drought stress on average reflectance values, while only one spectral band responded significantly to spider mite infestations. Different variogram parameters provided reliable indications of spider mite infestation and drought stress. Based on independent validation, variogram parameters could be used to accurately predict spider mite density but were less effective as indicators of drought stress. In addition, variogram parameters were used as explanatory variables to predict biomass and biofuel potential of individual maize plants. The potential of using variogram analysis as part of hyperspectral imaging analysis is discussed.

Analysis of alkali ultrasonication pretreatment in bioethanol production from cotton gin trash using FT-IR spectroscopy and principal component analysis

BackgroundCotton gin trash (CGT) is a lignocellulosic residue that can be used in the production of cellulosic ethanol. In a previous research, the sequential use of ultrasonication, liquid hot water, and ligninolytic enzymes was selected as pretreatment for the production of ethanol from CGT. However, an increment in the ethanol production is necessary. To accomplish that, this research evaluated the effect of pretreating CGT using alkaline ultrasonication before a liquid hot water and ligninolytic enzymes pretreatments for ethanol production. Three NaOH concentrations (5%, 10%, and 15%) were employed for the alkaline ultrasonication. Additionally, this work is one of the first applications of Fourier transform infrared (FT-IR) spectrum and principal component analysis (PCA) as fast methodology to identify the differences in the biomass after different types of pretreatments.ResultsThe three concentrations employed for the alkaline ultrasonication pretreatment produced ethanol yields and cellulose conversions higher than the experiment without NaOH. Furthermore, 15% NaOH concentration achieved twofold increment yield versus the treatment without NaOH. The FT-IR spectrum confirmed modifications in the CGT structure in the different pretreatments. PCA was helpful to determine differences between the pretreated and un-pretreated biomass and to evaluate how the CGT structure changed after each treatment.ConclusionsThe combination of alkali ultrasonication hydrolysis, liquid hot water, and ligninolytic enzymes using 15% of NaOH improved 35% the ethanol yield compared with the original treatment. Additionally, we demonstrated the use of PCA to identify the modifications in the biomass structure after different types of pretreatments and conditions.

Particulate matter emission factors for almond harvest as a function of harvester speed.

Abstract Almond harvest accounts for substantial particulate matter less than 10 µm in aerodynamic diameter (PM10) emissions in California each harvest season. This paper addresses the reduction of harvester ground speed from a standard 8 km/hr (5 mph) to 4 km/hr (2.5 mph) as a possible mitigation measure for reducing PM10 emissions. Ambient total suspended particulate (TSP) and PM10 sampling was conducted during harvest with alternating control (8 km/hr [5 mph]) and experimental (4 km/hr [2.5 mph]) treatments. On-site meteorological data were used in conjunction with both Industrial Source Complex-Short Term version 3 (ISCST3) and the American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model (AERMOD) dispersion models to back-calculate emission rates from the measured concentrations. Baseline annual emission factors for nut pickup of 381 ± 122 and 361 ± 123 kg PM10/km2·yr were determined using ISCST3 and AERMOD, respectively. Both of these values are substantially lower than the current PM10 emission factor for almond pickup of 4120 kg PM10/km2·yr. The particulate matter less than 2.5 µm in aerodynamic diameter (PM2.5) emission factors for nut pickup developed from this study were 25 ± 8 kg PM2.5/km2·yr and 24 ± 8 kg PM10/km2·yr were determined using ISCST3 and AERMOD, respectively. Reducing harvester speed resulted in an emissions reduction of 42% for TSP, but no differences were detected in emissions of PM10 and PM2.5. Differences detected in the emission factors developed using ISCST3 and AERMOD were not statistically significant, indicating that almond harvest emission factors previously developed using ISCST3 may be applied appropriately in AERMOD.

COMPARISON OF CONTINUOUS MONITOR (TEOM) AND GRAVIMETRIC SAMPLER PARTICULATE MATTER CONCENTRATIONS

Tapered element oscillating microbalance (TEOM) samplers may offer significant advantages to state air pollution regulatory agencies and air quality researchers in terms of reduced labor and data processing requirements through an automated particulate matter (PM) monitoring system. However, previous research has shown that TEOM samplers may not report accurate PM concentrations due to the operating characteristics of the automated system. This article presents the results of a multiyear study using collocated TEOM and gravimetric samplers configured to measure TSP concentrations from a Texas cattle feedlot. The objective of this work was to define the relationship between PM concentrations measured by TEOM and gravimetric samplers and characterize the influence of concentration intensity and particle size on that relationship. The results show that there was a significant positive linear relationship between the concentrations measured by the TEOM and gravimetric TSP samplers (p-values < 0.001). It was observed that in general, the TEOM samplers reported lower TSP concentrations than the collocated gravimetric TSP sampler. Further investigation into these results indicated that the difference in the concentration measured by the TEOM sampler versus the gravimetric TSP sampler (known as the TEOM measurement error) is correlated with the concentration measured by the gravimetric TSP sampler, but the nature of that relationship varies by location. However, linear relationships were observed between the measurement error of the TEOM samplers and the mass median diameter and geometric standard deviation of the collocated gravimetric TSP sample.

Determining Seasonal Greenhouse Gas Emissions from Ground-Level Area Sources in a Dairy Operation in Central Texas

ABSTRACT Greenhouse gas (GHG) emissions from agricultural production operations are recognized as an important air quality issue. A new technique following the U.S. Environmental Protection Agency Method TO-14A was used to measure GHG emissions from ground-level area sources (GLAS) in a free-stall dairy operation in central Texas. The objective of this study was to quantify and report GHG emission rates (ERs) from the dairy during the summer and winter using this protocol. A weeklong sampling was performed during each season. A total of 75 and 66 chromatograms of air samples were acquired from six delineated GLAS (loafing pen, walkway, barn, silage pile, settling basin, and lagoon) of the same dairy during summer and winter, respectively. Three primary GHGs—methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O)—were identified from the dairy operation during the sampling periods. The estimated overall ERs for CH4, CO2, and N2O during the summer for this dairy were 274, 6005, and 7.96 g head−1day−1, respectively. During the winter, the estimated overall CH4, CO2, and N2O ERs were 52, 7471, and 3.59 g head−1day−1, respectively. The overall CH4 and N2O ERs during the summer were approximately 5.3 and 2.2 times higher than those in the winter for the free-stall dairy. These seasonal variations were likely due to fluctuations in ambient temperature, dairy manure loading rates, and manure microbial activity of GLAS. The annualized ERs for CH4, CO2, and N2O for this dairy were estimated to be 181, 6612, and 6.13 g head−1day−1, respectively. Total GHG emissions calculated for this dairy with 500 cows were 2250 t of carbon dioxide equivalent (CO2e) per year. IMPLICATIONS The agricultural sector, especially concentrated animal feeding operations (CAFOs) contribute a considerable amount of GHGs to the atmosphere. To develop abatement strategies to reduce GHG emissions, it is important to learn to collect, analyze, verify, and report real data on actual emissions. Therefore, there is a need for a robust and accurate technique/protocol to measure GHGs from CAFOs. It is important to obtain direct estimates of GHG emissions from different GLAS in CAFOs to compile emission inventories and to develop GLAS-specific abatement strategies.