Digestate Evaporation Treatment in Biogas Plants: A Techno-economic Assessment by Monte Carlo, Neural Networks and Decision Trees

Biogas production is one of the most promising pathways toward fully utilizing green energy within a circular economy. The anaerobic digestion process is the industry standard technology for biogas production due to its lowered energy consumption and its reliance on microbiology. Even in such an environmental-friendly process, liquid digestate is still produced from the remains of digested bio-feedstock and will require treatment. With unsuitable treatment procedure for liquid digestate, the mass of bio-feedstock can potentially escape the circular supply chain within the economy. This paper recommends the implementation of evaporator systems to provide a sustainable liquid digestate treating mechanism within the economy. Studied evaporator systems are represented by vacuum evaporation in combination with ammonia scrubber, stripping and reverse osmosis. Nevertheless, complex multi-dimensional decisions should be made by stakeholders before implementing such systems. Our work utilizes a novel techno-economics model to study the techno-economics robustness in implementing recent state-of-art vacuum evaporation systems with exploitation of waste heat from combined heat and power (CHP) units in biogas plants (BGP). To take into the account the stochasticity of the real world and robustness of the analysis, we used the Monte-Carlo simulation technique to generate more than 20,000 of different possibilities for the implementation of the evaporation system. Favourable decision pathways are then selected using a novel methodology which utilizes the artificial neural network and a hyper-optimized decision tree classifier. Two pathways that give the highest probability of providing a fast payback period are identified. Descriptive statistics are also used to analyse the distributions of decision parameters that lead to success in implementing the evaporator system. The results highlighted that integration of evaporation system are favourable when transport costs and incentives for CHP units are large and while feed-in tariffs for electricity production and specific investment costs are low. The result of this work is expected to pave the way for BGP stakeholders and decision makers in implementing liquid digestate treating technologies within the currently existing infrastructure

Digestate Evaporation Treatment in Biogas Plants: A Techno-economic Assessment by Monte Carlo, Neural Networks and Decision Trees

Biogas production is one of the most promising pathways toward fully utilizing green energy within a circular economy. The anaerobic digestion process is the industry standard technology for biogas production due to its lowered energy consumption and its reliance on microbiology. Even in such an environmental-friendly process, liquid digestate is still produced from the remains of digested bio-feedstock and will require treatment. With unsuitable treatment procedure for liquid digestate, the mass of bio-feedstock can potentially escape the circular supply chain within the economy. This paper recommends the implementation of evaporator systems to provide a sustainable liquid digestate treating mechanism within the economy. Studied evaporator systems are represented by vacuum evaporation in combination with ammonia scrubber, stripping and reverse osmosis. Nevertheless, complex multi-dimensional decisions should be made by stakeholders before implementing such systems. Our work utilizes a novel techno-economics model to study the techno-economics robustness in implementing recent state-of-art vacuum evaporation systems with exploitation of waste heat from combined heat and power (CHP) units in biogas plants (BGP). To take into the account the stochasticity of the real world and robustness of the analysis, we used the Monte-Carlo simulation technique to generate more than 20,000 of different possibilities for the implementation of the evaporation system. Favourable decision pathways are then selected using a novel methodology which utilizes the artificial neural network and a hyper-optimized decision tree classifier. Two pathways that give the highest probability of providing a fast payback period are identified. Descriptive statistics are also used to analyse the distributions of decision parameters that lead to success in implementing the evaporator system. The results highlighted that integration of evaporation system are favourable when transport costs and incentives for CHP units are large and while feed-in tariffs for electricity production and specific investment costs are low. The result of this work is expected to pave the way for BGP stakeholders and decision makers in implementing liquid digestate treating technologies within the currently existing infrastructure

Finanční analýza podniku CLEANTEX a.s.

Fonanční analýza podniku CLEANTEX a.s. v letech 2002 až 2006. Obsahuje teoretickou část týkající se finanční analýzy a praktickou část hodnotící finanční řízení podniku

Finanční analýza podniku CLEANTEX a.s.

Fonanční analýza podniku CLEANTEX a.s. v letech 2002 až 2006. Obsahuje teoretickou část týkající se finanční analýzy a praktickou část hodnotící finanční řízení podniku

Finanční analýza podniku CLEANTEX a.s.

Fonanční analýza podniku CLEANTEX a.s. v letech 2002 až 2006. Obsahuje teoretickou část týkající se finanční analýzy a praktickou část hodnotící finanční řízení podniku

Application of a method based on the measurement of radiation reflectance when estimating the sensitivity of selected grain maize hybrids to the herbicide CALLISTO 480 SC + ATPLUS 463

The application of methods based on measurements of photosynthesis efficiency is now more and more popular and used not only for the evaluation of the efficiency of herbicides but also for the estimation of their phytotoxicity to the cultivated crop. These methods enable to determine also dif­fe­ren­ces in the sensitivity of cultivars and/or hybrids to individual herbicides. The advantage of these methods consists above all in the speed and accuracy of measuring.In a field experiment, the sensitivity of several selected grain maize hybrids (EDENSTAR, NK AROBASE, NK LUGAN, LG 33.30 and NK THERMO) to the herbicide CALLISTO 480 SC + ATPLUS 463 was tested for a period of three years. The sensitivity to a registered dose of 0.25 l . ha−1 + 0.5 % was measured by means of the apparatus PS1 meter, which could measure the reflected radiation. Measurements of sensitivity of hybrids were performed on the 2nd, 3rd, 4th, 5th and 8th day after the application of the tested herbicide, i.e. in the growing stage of the 3rd–5th leaf. Plant material was harvested using a small-plot combine harvester SAMPO 2010. Samples were weighed and converted to the yield with 15 % of moisture in grain DM.The obtained three-year results did not demonstrate differences in sensitivity of tested hybrids to the registered dose of the herbicide CALLISTO 480 SC + ATPLUS 463 (i.e. 0.25 l . ha−1 + 0,5 %). Recorded results indicated that for the majority of tested hybrids the most critical were the 4th and the 5th day after the application; on these days the average PS1 values were the highest at all. In years 2005 and 2007, none of the tested hybrids exceeded the limit value 15 (which indicated a certain decrease in the efficiency of photosynthesis). Although in 2006 three of tested hybrids showed a certain decrease in photosynthetic activity (i.e. EDENSTAR and NK AROBASE on the 3rd day and NK LUGAN on the 2nd–4th day after the application), no visual symptoms of damage of plants were found out. It could be concluded that the herbicide CALLISTO 480 SC + ATPLUS 463 (when applied in the registered dose of 0.25 l . ha−1 + 0.5 %) did not damage hybrids under study and did not show any statistically significant effect on the grain yield. This means that the manufacturer’s statement that this herbicide, if applied in the registered dose of 0.25 l . ha−1 + 0.5 %, is very tolerant to grain maize seedlings in the growth stage of 3–5 leafs, was correct. The most suitable date of measurements of differences in sensitivity to and/or potential phytotoxicity of the preparation CALLISTO 480 SC + ATPLUS 463 seemed to be the fourth day after the application because the measured average PS1 values were the highest in all hybrids under study. When evaluating the pooled three-year yields of grain (converted to 15% of moisture content) by means of variance analysis, a statistically significant effect of the year and the hybrid on the grain yield was found out. On the other hand, however, there was no statistically significant difference in the grain yield between control and the variant treated with the registered dose of the herbicide CALLISTO 480 SC + ATPLUS 463, i.e. 12.08 t . ha‑1 and 11.50 t . ha−1, respectively (grain moisture content 15%). When comparing pooled three-year yields of all hybrids under study, there were statistically significant differences between yields of the hybrid NK THERMO on the one hand and hybrids EDENSTAR and NK AROBASE on the other