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Foodwaste (hereinafter, FW) is the most voluminous solid waste and its amount is growing rapidly all over the world. The turning of FW into biogas via anaerobic fermentation is widely recognized as an environmentally responsible and economically reasonable option. Based on the knowledge obtained from agricultural biogas stations, the current methods of FW fermentation management are based on balancing the ratio of total carbon and nitrogen. However, it was repeatedly and independently reported that the stability of this process is low, resulting in many concessions in terms of prolonged hydraulic retention time or reduced biogas yield. Hence, biochemical as well as economic performance of the process is balanced by mixing of FW with agricultural residues. FW samples of various origin were collected and biochemically analyzed. The data indicate that FW originating from homes and luxury restaurants tends to be lignocellulose-based, whereas the levels of crude fiber (25% up to 27%) are higher than those from agricultural feedstock (18%). In contrast, FW from school canteens and inexpensive restaurants tends to be starch-based with high levels of amyloids (21% up to 23%) and fat (5% up to 7%). A novel method better reflecting the bioavailability of carbon and nitrogen to anaerobic consortia is proposed. It is demonstrated that the previous optimization methods could somehow reflect the availability of nutrients in agricultural feedstock, as carbonaceous and nitrogen sources are relatively equally biodegradable. Nevertheless, the biodegradability of FW is considerably different, which is why higher amounts of proteins and lipids lead to increased levels of ammonia and sulfide, resulting in an inhibitory effect on the metabolism of anaerobic consortia. Optimizing the anaerobic fermentation of FW by the new method outperforms the previous technique and makes it possible to process FW more intensively, or, more precisely, with higher profitability and lower proportion of ballast agricultural feedstock.

Research background: Covid-19 has affected the global economy and has had an inevitable impact on capital markets. In the week of February 24?28, 2020, stock markets crashed. The index FTSE 100 decreased 13%, while the indices DJIA and S&P 500 fell 11?12%, the biggest drop since the 2007?2008 financial and economic crisis. It is therefore of interest to test the random walk hypothesis in developed capital markets, European and also non-European, in order to understand the different predictabilities between them. Purpose of the article: The aim is to analyze capital market efficiency, in its weak form, through the stock market indices of Belgium (index BEL 20), France (index CAC 40), Germany (index DAX 30), USA (index DOW JONES), Greece (index FTSE Athex 20), Spain (index IBEX 35), Ireland (index ISEQ), Portugal (index PSI 20) and China (index SSE) for the period from December 2019 to May 2020. Methods: Panel unit root tests of Breitung (2000), Levin et al. (2002) and Hadri (2002) were used to assess the time series stationarity. The test of Clemente et al. (1998) is used to detect structural breaks. The tests for the random walk hypothesis follows the variance ratio methodology proposed by Lo and MacKinlay (1988). Findings & Value added: In general, we found mixed confirmation about the EMH (efficient market hypothesis). Taking into account the conclusions of the rank variance test, the random walk hypothesis was rejected in the case of stock indices: Dow Jones, SSE and PSI 20, partially rejected in the case indices: BEL 20, CAC 40, FTSTE Athex 20 and DEX 30, but accepted for indices: IBEX 35 and ISEQ. The results also show that prices do not fully reflect the information available and that changes in prices are not independent and identically distributed. This situation has consequences for investors, since some returns can be expected, creating opportunities for arbitrage and for abnormal returns, contrary to the assumptions of random walk and information efficiency.

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