Removal of organic matter and nutrients from slaughterhouse wastewater by using Eichhornia crassipes and evaluation of the generated biomass composting

The objective of this research was to evaluate the performance of the aquatic macrophyte Eichhornia crassipes applied in situ in a slaughter house treatment system, located in the west of the Paraná state, Brazil, regarding the nutrients removal and organic matter. Moreover, it aimed to obtain data from the production, management and composting practices of the biomass generated in the system. During 11 months of macrophytes development, physic and chemical parameters were monitored and plant density was controlled by periodical removal of excess biomass, which was weekly monitored and it is expressed in kg of aquatic plant per m² covered area. The degradation of the macrophytes removed from the treatment system was evaluated at the pilot scale in eight composting piles of 0.60 m³ that underwent four different treatments and two repetitions: T1 - water hyacinth (Eichhornia crassipes); T2 - water hyacinth and swine excrement (7:1), T3 - water hyacinth, swine excrement and earth (7:1:0,67), and T4 - water hyacinth, swine excrement and cellulosic gut (7:1:0,67), for a period of 90 days. The results indicated maximum removal efficiencies of 77.2% for COD; 77.8% for BOD, 87.9% for total nitrogen, 47.5% for ammonia nitrogen and 38.9% for total phosphorus for a five-day retention time. For biomass stabilization by composting, considering the C:N ratio as an indicator of compost maturity, it was observed that treatment T4 resulted in the shortest stabilization period (60 days). No difference was verified in the biostabilization rates at 5% level by the F test.

Simulation and optimization of IGCC technique for power generation and hydrogen production by using lignite Thar coal and cotton stalk

The purpose of this study was to simulate and to optimize integrated gasification for combine cycle (IGCC) for power generation and hydrogen (H2) production by using low grade Thar lignite coal and cotton stalk. Lignite coal is abundant of moisture and ash content, the idea of addition of cotton stalk is to increase the mass of combustible material per mass of feed use for the process, to reduce the consumption of coal and to increase the cotton stalk efficiently for IGCC process. Aspen plus software is used to simulate the process with different mass ratios of coal to cotton stalk and for optimization: process efficiencies, net power generation and H2 production etc. are considered while environmental hazard emissions are optimized to acceptance level. With the addition of cotton stalk in feed, process efficiencies started to decline along with the net power production. But for H2 production, it gave positive result at start but after 40% cotton stalk addition, H2 production also started to decline. It also affects negatively on environmental hazard emissions and mass of emissions/ net power production increases linearly with the addition of cotton stalk in feed mixture. In summation with the addition of cotton stalk, overall affects seemed to negative. But the effect is more negative after 40% cotton stalk addition so it is concluded that to get maximum process efficiencies and high production less amount of cotton stalk addition in feed is preferable and the maximum level of addition is estimated to 40%. Gasification temperature should keep lower around 1140 °C and prefer technique for studied feed in IGCC is fluidized bed (ash in dry form) rather than ash slagging gasifier

Use of data mining and spectral profiles to differentiate condition after harvest of coffee plants

This study aimed at identifying different conditions of coffee plants after harvesting period, using data mining and spectral behavior profiles from Hyperion/EO1 sensor. The Hyperion image, with spatial resolution of 30 m, was acquired in August 28th, 2008, at the end of the coffee harvest season in the studied area. For pre-processing imaging, atmospheric and signal/noise effect corrections were carried out using Flaash and MNF (Minimum Noise Fraction Transform) algorithms, respectively. Spectral behavior profiles (38) of different coffee varieties were generated from 150 Hyperion bands. The spectral behavior profiles were analyzed by Expectation-Maximization (EM) algorithm considering 2; 3; 4 and 5 clusters. T-test with 5% of significance was used to verify the similarity among the wavelength cluster means. The results demonstrated that it is possible to separate five different clusters, which were comprised by different coffee crop conditions making possible to improve future intervention actions.

Efficiency of distinct data mining algorithms for classifying stress level in piglets from their vocalization

Among the challenges of pig farming in today's competitive market, there is factor of the product traceability that ensures, among many points, animal welfare. Vocalization is a valuable tool to identify situations of stress in pigs, and it can be used in welfare records for traceability. The objective of this work was to identify stress in piglets using vocalization, calling this stress on three levels: no stress, moderate stress, and acute stress. An experiment was conducted on a commercial farm in the municipality of Holambra, São Paulo State , where vocalizations of twenty piglets were recorded during the castration procedure, and separated into two groups: without anesthesia and local anesthesia with lidocaine base. For the recording of acoustic signals, a unidirectional microphone was connected to a digital recorder, in which signals were digitized at a frequency of 44,100 Hz. For evaluation of sound signals, Praat® software was used, and different data mining algorithms were applied using Weka® software. The selection of attributes improved model accuracy, and the best attribute selection was used by applying Wrapper method, while the best classification algorithms were the k-NN and Naive Bayes. According to the results, it was possible to classify the level of stress in pigs through their vocalization.

Using data mining to identify factors that influence the degree of leg injuries in broilers

Locomotor problems prevent the bird to move freely, jeopardizing the welfare and productivity, besides generating injuries on the legs of chickens. The objective of this study was to evaluate the influence of age, use of vitamin D, the asymmetry of limbs and gait score, the degree of leg injuries in broilers, using data mining. The analysis was performed on a data set obtained from a field experiment in which it was used two groups of birds with 30 birds each, a control group and one treated with vitamin D. It was evaluated the gait score, the asymmetry between the right and left toes, and the degree of leg injuries. The Weka ® software was used in data mining. In particular, C4.5 algorithm (also known as J48 in Weka environment) was used for the generation of a decision tree. The results showed that age is the factor that most influences the degree of leg injuries and that the data from assessments of gait score were not reliable to estimate leg weakness in broilers.

Selection of microorganisms producer of lipase for fat removal from biodiesel purification water

The objective this study has been the selection of lipase productor microorganism, for removal of oils and grease, in the pre-treatment of biodiesel wastewater washing. For this, analyses of the physicist-chemistries characteristics had been made with the wastewater of the biodiesel washing, and then it had been isolated and chosen, by means of determinations of the lipase activity. Following, it was made a test of fat biodegradation, in the conditions: pH (5.95), temperature (35 ºC), rotation (180 rpm) and ammonium sulfate as nitrogen source (3 g L-1) and establishing as variable the two microorganism preselected and the time (24; 48; 72; 96 and 120 h). The biodiesel purification wastewater had presented high potential of environmental impact, presenting a concentration of O of 6.76 g L-1. From the six isolated microbiological cultures, two microorganisms (A and B) had been selected, with enzymatic index of 0.56 and 0.57, respectively. The treatment of the wastewater using the isolated microorganism (Klebsiella oxytoca) had 80% of the fatty removal in 48 h.

Isolation of microorganisms of cheese whey with lipolytic activity for removal of COD

The aim of this study was to isolate microorganisms that produce lipase and to assess the efficiency of COD removal intreatment of cheese whey under different operating conditions. The microorganisms were isolated from cheese whey and a commercial product; it was selectedthreemicroorganisms that obtained the best response to the lipolytic activity test through the enzyme index. Then, the microorganisms were inoculated in sterilized cheese whey samples, for two pH values (6.2 and 7.0), incubated at 35 °C and 150 rpm in shaker and the lipolityc activity and the efficiency of COD removal were measured in two time periods (24 and 48h). After incubation, it was observed that the treatments showed a good removal efficiency of COD for the pre-treatment and the isolated microorganism (S1) from the cheese whey showed the highest lipase production. Regarding the pH and time variables, there was not significant effect between the two evaluated factors. Among all treatments, T2 (S1, pH 7.0 and 24h) obtained more enzyme production (4.87 U mL-1).

Data mining techniques for identification of spectrally homogeneous areas using NDVI temporal profiles of soybean crop

The aim of this study was to group temporal profiles of 10-day composites NDVI product by similarity, which was obtained by the SPOT Vegetation sensor, for municipalities with high soybean production in the state of Paraná, Brazil, in the 2005/2006 cropping season. Data mining is a valuable tool that allows extracting knowledge from a database, identifying valid, new, potentially useful and understandable patterns. Therefore, it was used the methods for clusters generation by means of the algorithms K-Means, MAXVER and DBSCAN, implemented in the WEKA software package. Clusters were created based on the average temporal profiles of NDVI of the 277 municipalities with high soybean production in the state and the best results were found with the K-Means algorithm, grouping the municipalities into six clusters, considering the period from the beginning of October until the end of March, which is equivalent to the crop vegetative cycle. Half of the generated clusters presented spectro-temporal pattern, a characteristic of soybeans and were mostly under the soybean belt in the state of Paraná, which shows good results that were obtained with the proposed methodology as for identification of homogeneous areas. These results will be useful for the creation of regional soybean "masks" to estimate the planted area for this crop.

Removal of nitrogen, phosphorus, copper and zinc from swine breeding waste water by bermudagrass and cattail in constructed wetland systems

This work aimed to study the agronomic performance and capacity of nutrient removal by bermudagrass (Cynodon spp.) and cattail (Typha sp.) when grown in constructed wetlands systems (CWSs) of vertical and horizontal flow, respectively, used in the post-treatment of swine breeding wastewater (ARS). The average yield of dry matter (DM) of bermudagrass in sections of 60-day interval ranged from 14 to 43 t ha-1, while the cultivated cattail produced in a single cut after 200 days of cultivation between 45 and 67 t ha-1 of DM. Bermudagrass extracted up to 17.65 kg ha-1 d-1 of nitrogen, 1.76 kg ha-1 d-1 of phosphorus, 6.67 g ha-1 d-1 of copper and 54.75 g ha-1 d-1 of zinc. Cattail extracted up to 5.10 kg ha-1 d-1 of nitrogen, 1.07 kg ha-1 d-1 of phosphorus, 1.41 g ha-1 d-1 of copper and 16.04 g ha-1 d-1 of zinc. Cattail and bermudagrass were able to remove, respectively, 5.0 and 4.6% of the nitrogen and 11.2 and 5.4% of the phosphorus applied via ARS, being less efficient in extracting N and P when the initial intake of these nutrients is evaluated.

Evaluation of the effect of the seed extract of Moringa oleifera Lam over the efficiency of organic filters in wastewater treatment of dairy cattle breeding

This study aimed to evaluate the effect of Moringa oleifera Lam extract on the removal of total solids (TS), total suspended solids (TSS) and chemical oxygen demand (COD), in different filter media for treating wastewater of dairy cattle breeding (DCW). The moringa seed extract was obtained by grinding 50 g of seeds in one liter of distilled water and, after passing the solution through a quantitative paper filter of 25 microns, 60 mL of the extract were added to wastewater from cattle breeding before the filtration process in organic filters made of thin coal, bamboo leaves, eucalyptus leaves, gliricidia branches and sawdust. This was followed by the completely randomized experimental design, adopting a factorial of 5 x 2. Aliquots of filtered effluent were collected and the total solids (TS) concentrations, total suspended solids (TSS) and chemical oxygen demand (COD) were determined. It was found that the increase in the efficiency of removal of COD and total solids can be attributed to the coagulating power of the moringa seed extract, wherein the filter medium with bamboo leaves presented the best performance, showing potential for use as alternative filter material in the primary treatment of DCW.

Performance of an anaerobic-aerobic reactor and kinetic study of organic matter removal of cattle slaughterhouse effluent

This paper sought to evaluate the behavior of an upflow Anaerobic-Aerobic Fixed Bed Reactor (AAFBR) in the treatment of cattle slaughterhouse effluent and determine apparent kinetic constants of the organic matter removal. The AAFBR was operated with no recirculation (Phase I) and with 50% of effluent recirculation (Phase II), with θ of 11h and 8h. In terms of pH, bicarbonate alkalinity and volatile acids, the results indicated the reactor ability to maintain favorable conditions for the biological processes involved in the organic matter removal in both operational phases. The average removal efficiencies of organic matter along the reactor height, expressed in terms of raw COD, were 49% and 68% in Phase I and 54% and 86% in Phase II for θ of 11h and 8h, respectively. The results of the filtered COD indicated removal efficiency of 52% and k = 0.0857h-1 to θ of 11h and 42% and k = 0.0880h-1 to θ of 8h in the Phase I. In Phase II, the removal efficiencies were 59% and 51% to θ of 11h and 8h, with k = 0.1238h-1 and k = 0.1075 h-1, respectively. The first order kinetic model showed good adjustment and described adequately the kinetics of organic matter removal for θ of 11h, with r² equal to 0.9734 and 0.9591 to the Phases I and II, respectively.

Application of response surface methodology to study the biological removal of nitrogen from effluent of cattle slaughterhouse in a sequencing batch reactor

The aim of this study was to evaluate the efficiency of a sequencing batch reactor (SBR) on biological removal of nitrogen from cattle slaughterhouse wastewater by nitrification/denitrification processes. The effects of initial concentration of ammoniacal nitrogen were investigated at 100; 150 and 200 mg L-1 and air flow rate at 0.125; 0.375 and 0.625 L min¹ Lreactor-1 on the nitrogen compounds removal, by a Central Composite Rotational Design (CCRD) configuration. There were variations from 9.2 to 94.9%, 4.0 to 19.6% and 20.8 to 92.0% in the conversion of ammoniacal nitrogen to nitrate and nitrite concentration and removal of total nitrogen, respectively. The increase of air flow rate and decrease of the initial concentration of ammoniacal nitrogen resulted in higher efficiencies of total nitrogen removal, as well as the conversion of ammoniacal nitrogen to nitrate. During the pre-established intervals of this study, the removal and conversion efficiencies of nitrogen compounds above 85% were achieved in air flow rate variations from 0.375 to 0.725 L min-1 Lreactor-1 and initial concentration of ammoniacal nitrogen from 80 to 200 mg L-1. On denitrification process, we obtained efficiencies from 91.5 to 96.9% on the removal of nitrite/nitrate and from 78.3 to 87.9% on the removal of organic matter.

Vocalization data mining for estimating swine stress conditions

This study aimed to identify differences in swine vocalization pattern according to animal gender and different stress conditions. A total of 150 barrow males and 150 females (Dalland® genetic strain), aged 100 days, were used in the experiment. Pigs were exposed to different stressful situations: thirst (no access to water), hunger (no access to food), and thermal stress (THI exceeding 74). For the control treatment, animals were kept under a comfort situation (animals with full access to food and water, with environmental THI lower than 70). Acoustic signals were recorded every 30 minutes, totaling six samples for each stress situation. Afterwards, the audios were analyzed by Praat® 5.1.19 software, generating a sound spectrum. For determination of stress conditions, data were processed by WEKA® 3.5 software, using the decision tree algorithm C4.5, known as J48 in the software environment, considering cross-validation with samples of 10% (10-fold cross-validation). According to the Decision Tree, the acoustic most important attribute for the classification of stress conditions was sound Intensity (root node). It was not possible to identify, using the tested attributes, the animal gender by vocal register. A decision tree was generated for recognition of situations of swine hunger, thirst, and heat stress from records of sound intensity, Pitch frequency, and Formant 1.

Effect of cycle time and airflow in biological nitrogen removal from poultry slaughterhouse wastewater using sequencing batch reactor

This study aimed to evaluate the influence of airflow (0.25, 0.50 and 0.75 L.L-1.min-1) and cycle time (10.45 h, 14.25 h and 17.35 h) on a sequencing batch reactor (SBR) performance in promoting nitrification and denitrification of poultry slaughterhouse wastewater. The operational stages included feeding, aerobic and anoxic reactions, sedimentation and discharge. SBR was operated in a laboratory scale with a working volume of 4 L, keeping 25% of biomass retained inside the reactor as inoculum for the next batch. In the anoxic stage, C: N ratio was maintained between 5 and 6 by adding cassava starch wastewater. A factorial design (22) with five repetitions was designed at the central point to evaluate the influence of cycle time and airflow on total inorganic nitrogen removal (N-NH4++N-NO2-+N-NO3-) and in the whole process (nitrification and denitrification). The highest total inorganic nitrogen removal (93.3%) was observed for airflow of 0.25 L.L-1.min‑1 and a cycle time of 14.25 h. At the end of the experiment, the sludge inside the reactor was characterized by fluorescent in situ hybridization (FISH), indicating the presence of ammonia and nitrite oxidizing bacteria.

Assessing the Environmental Value of Water Treatment Solutions in the Mining Industry

Environmental accountability has become a major source of competitive advantage for industrial companies, because customers consider it as relevant buying criterion. However, in order to leverage their environmental responsibility, industrial suppliers have to be able to demonstrate the environmental value of their products and services, which is also the aim of Kemira, a global water chemistry company considered in this study. The aim of this thesis is to develop a tool which Kemira can use to assess the environmental value of their solutions for the customer companies in mining industry. This study answers to questions on what kinds of methods to assess environmental impacts exist, and what kind of tool could be used to assess the environmental value of Kemira’s water treatment solutions. The environmental impacts of mining activities vary greatly between different mines. Generally the major impacts include the water related issues and wastes. Energy consumption is also a significant environmental aspect. Water related issues include water consumption and impacts in water quality. There are several methods to assess environmental impacts, for example life cycle assessment, eco-efficiency tools, footprint calculations and process simulation. In addition the corresponding financial value may be estimated utilizing monetary assessment methods. Some of the industrial companies considered in the analysis of industry best practices use environmental and sustainability assessments. Based on the theoretical research and conducted interviews, an Excel based tool utilizing reference data on previous customer cases and customer specific test results was considered to be most suitable to assess the environmental value of Kemira’s solutions. The tool can be used to demonstrate the functionality of Kemira’s solutions in customers’ processes, their impacts in other process parameters and their environmental and financial aspects. In the future, the tool may be applied to fit also Kemira’s other segments, not only mining industry.