399,400 research outputs found

    Microalgae recycling improves biomass recovery from wastewater treatment high rate algal ponds

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    Microalgal biomass harvesting by inducing spontaneous flocculation (bioflocculation) sets an attractive approach, since neither chemicals nor energy are needed. Indeed, bioflocculation may be promoted by recycling part of the harvested microalgal biomass to the photobioreactor in order to increase the predominance of rapidly settling microalgae species. The aim of the present study was to improve the recovery of microalgal biomass produced in wastewater treatment high rate algal ponds (HRAPs) by recycling part of the harvested microalgal biomass. The recirculation of 2% and 10% (dry weight) of the HRAPs microalgal biomass was tested over one year in an experimental HRAP treating real urban wastewater. Results indicated that biomass recycling had a positive effect on the harvesting efficiency, obtaining higher biomass recovery in the HRAP with recycling (R-HRAP) (92–94%) than in the control HRAP without recycling (C-HRAP) (75–89%). Microalgal biomass production was similar in both systems, ranging between 3.3 and 25.8 g TSS/m2d, depending on the weather conditions. Concerning the microalgae species, Chlorella sp. was dominant overall the experimental period in both HRAPs (abundance >60%). However, when the recycling rate was increased to 10%, Chlorella sp. dominance decreased from 97.6 to 88.1%; while increasing the abundance of rapidly settling species such as Stigeoclonium sp. (16.8%, only present in the HRAP with biomass recycling) and diatoms (from 0.7 to 7.3%). Concerning the secondary treatment of the HRAPs, high removals of COD (80%) and N-NH4+ (97%) were found in both HRAPs. Moreover, by increasing the biomass recovery in the R-HRAP the effluent total suspended solids (TSS) concentration was decreased to less than 35 mg/L, meeting effluent quality requirements for discharge. This study shows that microalgal biomass recycling (10% dry weight) increases biomass recovery up to 94% by selecting the most rapidly settling microalgae species without compromising the biomass production and improving the wastewater treatment in terms of TSS removal.Peer ReviewedPostprint (author's final draft

    Logistics issues of biomass : the storage problem and the multi-biomass supply chain

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    Biomass is a renewable energy source with increasing importance. The larger fraction of cost in biomass energy generation originates from the logistics operations. A major issue concerning biomass logistics is its storage, especially when it is characterized by seasonal availability. The biomass energy exploitation literature has rarely investigated the issue of biomass storage. Rather, researchers usually choose arbitrarily the lowest cost storage method available, ignoring the effects this choice may have on the total system efficiency. In this work, the three most frequently used biomass storage methods are analyzed and are applied to a case study to come up with tangible comparative results. Furthermore, the issue of combining multiple biomass supply chains, aiming at reducing the storage space requirements, is introduced. An application of this innovative concept is also performed for the case study examined. The most important results of the case study are that the lowest cost storage method indeed constitutes the system-wide most efficient solution, and that the multi-biomass approach is more advantageous when combined with relatively expensive storage methods. However, low cost biomass storage methods bear increased health, safety and technological risks that should always be taken into account. (C) 2008 Elsevier Ltd. All rights reserved

    Comparing Aboveground Biomass Predictions for an Uneven-Aged Pine-Dominated Stand Using Local, Regional, and National Models

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    Sequestration by Arkansas forests removes carbon dioxide from the atmosphere, storing this carbon in biomass that fills a number of critical ecological and socioeconomic functions. We need a better understanding of the contribution of forests to the carbon cycle, including the accurate quantification of tree biomass. Models have long been developed to predict aboveground live tree biomass, but few of these have been derived from Arkansas forests. Since there is geographic variability in the growth and yield of pine as a function of genetics, site conditions, growth rate, stand stocking, and other factors, we decided to compare aboveground tree biomass estimates for a naturally regenerated, uneven-aged loblolly pine (Pinus taeda)-dominated stand on the Crossett Experimental Forest (CEF) in southeastern Arkansas. These predictions were made using a new locally derived biomass equation, five regional biomass equations, and the pine model from the National Biomass Estimators. With the local model as the baseline, considerable biomass variation appeared across a range of diameters—at the greatest diameter considered, the minimum value was only 69% of the maximum. Using a recent inventory from the CEF’s Good Farm Forty to compare each model, stand-level biomass estimates ranged from a low of 76.9 Mg/ha (a different Arkansas model) to as much as 96.1 Mg/ha (an Alabama model); the local CEF equation predicted 82.5 Mg/ha. A number of different factors contributed to this variability, including differences in model form and derivation procedures, geographic origins, and utilization standards. Regardless of the source of the departures, their magnitude suggests that care be used when making large-scale biomass estimates
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