Long-term inhibition of chlortetracycline antibiotics on anaerobic digestion of swine manure.

This study aimed to identify whether chronic effects are present in the anaerobic digestion (AD) of swine manure (SM) containing chlortetracycline (CTC), which is one of the major broad-spectrum veterinary antibiotics, and to elucidate the long-term inhibitory effects and recovery from the inhibition based on AD performance and microbial community. Two continuous-stirred tank reactors treating SM with and without CTC spiking (3 mg/L) were operated for 900 days. Due to the degradation and transformation, the total concentration including CTC's epimer and isomer in the test reactor was 1.5 mg/L. The exposure level was determined according to probabilistically estimated concentrations with uncertainties in field conditions. Until the cessation of CTC exposure on day 585, the methane generation of test reactor continuously decreased to 55 ± 17 mL/g-VS/day, 53% that of control. The methane generation and organic removal were not recovered within 300 days after the CTC exposure was stopped. During the experiment, stability parameters such as pH, total ammonium nitrogen, the composition of methane and alkalinity were the same for both reactors. The concentration and composition of VFAs in the test reactor were different with those of control but not in inhibition level. Microbial profiles revealed that reduction in bacterial diversity and changed balance in microbial species resulted in the performance downgrade under the long-term antibiotic pressure. Since it is hard to recover from the inhibition and difficult to predict the inhibition using physicochemical indicators, continuous exposure to CTC needs to be avoided for the sustainable management of AD plants treating SM.

Incorporating interaction terms in multivariate linear regression for post-event flood waste estimation.

Multivariate linear regression methodology has been conceived as a viable technique in flood waste estimation. The fundamental assumption of the conventional flood waste model, independence between input variables, may not work in reality. As an alternative, we evaluated the effectiveness of including interaction terms in flood waste modeling. The secondary objectives include to suggest the strategy in flood waste mitigation and to explore a plausible explanation to the modeling results. In the scheme of model development and assessment, ninety flood cases in South Korea were statistically analyzed. Input variables for regression analysis were selected from available datasets in the national disaster information system and the selected variables were flood damage variables used to quantify the amount of flood waste. According to the results, incorporating the interaction terms improved the estimation accuracy of the model. The single-variable sensitivity analysis revealed that mitigating damage to rivers and croplands would most efficiently reduce potential flood waste generation. The interaction terms appeared to compensate for the over/underestimated waste amounts by single terms, and they explained the nonlinear response of waste generation. Observations made throughout the field survey revealed that the nonlinear and interactive pattern of flood waste generation corresponded to the results from the regression analysis. In a practical aspect, incorporating the interaction terms would be an effective method to enhance the flood waste estimation model without costly works for further variables exploration.

Data stratification toward advanced flood waste estimation: A case study in South Korea.

Flood waste management is important for reducing the damage and secondary environmental pollution caused by delays in disaster recovery. One key issue related to flood waste management concerns estimating the precise quantity of waste to plan recovery strategies and policies. In this study, an advanced flood waste estimation technique was devised using data stratification. In total 90 flood cases in South Korea were sorted by three strata characteristics: administrative region (AR; equivalent to special city or province), urbanization rate (UR), and disaster type and coastal accessibility (DC). According to the results, such data stratification led to flood waste prediction improvement not only by the single-stage stratification but also by successive stratifications. Data stratification was effective both for identifying groups with similar contexts and for eliminating disparities in the dataset that impede accurate waste prediction. Among the stratification sequences tested, the order resulted in the most improvement in flood waste prediction was UR, AR, and DC. This stratification order yielded enhanced waste prediction in 74 cases. Since this study deals with a strategy to resolve gaps in disaster data, which is a crucial issue in many countries, it is envisaged that this strategy can be transferred to other countries.

Estimation of emission of tire wear particles (TWPs) in Korea.

Tire wear particles (TWPs) were one of the source categories of microplastics, and some countries consider it the largest. In the case of Korea, the number of vehicles per a kilometer of road is the highest among 30 OECD countries. Therefore, the concentration of TWPs is considered high. This study aims to estimate TWPs emission factor by using warranty period of tire, driving distance per vehicle per day, weight of tire, and ratio of weight loss of tire, and then, suggests TWPs emission amount by using annual driving distance and emission factor of TWPs of each type of vehicle. As a result, the emission factor of TWPs in Korea appeared as in the following: 45-57 mg/vehicle·km (average 51.1 mg/vehicle·km) for passenger cars, 224 mg/vehicle·km for lightweight trucks, 799 mg/vehicle·km for buses, and 949 mg/vehicle·km for heavyweight trucks. The total amount of TWPs to be generated in a year was calculated as 51,795-54,581 tonnes/year (average 53,188 tonnes/year). The amount of TWPs appeared in the order of heavyweight trucks, buses, passenger cars, and lightweight trucks; the contribution of tires of each type of vehicles, to the emitted amount of TWPs, appeared with insignificant differences.

Bayesian approach in estimating flood waste generation: A case study in South Korea.

Accurate estimations of flood waste generation are a crucial issue in disaster waste management. Multilinear regression of related parameters has been recognized as a promising technique for flood waste estimation. There are two types of flood waste estimation methods: pre-event predictions using factors related to regional properties and rainfall hazards, and post-event predictions using damage variables due to floods, such as the number of damaged buildings. Previous attempts to establish these models used deterministic approaches; however, probabilistic methods have never been applied. Considering the large degrees of uncertainty in waste generation from floods, a probabilistic approach can provide a more accurate model compared to models developed by the conventional deterministic approach. This study applied Bayesian inference to develop a flood waste regression model in South Korea. The aims of the study are as follows: (1) to analyze the characteristics of coefficients estimated by the Bayesian approach; (2) evaluate the performance of the prediction model by Bayesian inference; and (3) assess the effectiveness of Bayesian updating in a flood waste estimation. According to the results, the coefficients obtained via Bayesian inference showed a more significant p-value compared to those developed through the deterministic approach. Bayesian inference with a null prior distribution was effective in error reduction, specifically for post-event prediction. Bayesian updating did not effectively increase the accuracy of the model, while iterative updating required a complex calculation process. These results reveal the potential of the Bayesian approach in flood waste estimations, which can be transferred to other countries.

Fate of chlortetracycline antibiotics during anaerobic degradation of cattle manure.

As veterinary antibiotics (VAs) cause adverse effects on nature, anaerobic digestion (AD) of livestock manure has been receiving attention as an exposure route of VAs. This research evaluated the anaerobic degradation and phase distribution of chlortetracycline (CTC) with its epimer (4-epi-CTC, ECTC) and isomer (Iso-CTC, ICTC). In addition, whether CTC can inhibit not only AD of a substrate but also the degradation of CTC was assessed. Anaerobic batch assays were performed with cattle manure for 30 days by varying the initial concentration of CTC; 0, 10, 25, 50, and 100 mg/L. Approximately 25-43 % (w/w) of CTC was primarily degraded while 18-25 % and 20-26 % of CTC was transformed into ECTC and ICTC, respectively. Up to 88 % (w/w) of the remaining CTC, ECTC, and ICTC was present in the solid phase. In addition, CTC inhibited not only the mineralization of the cattle manure but also the degradation of CTC due to co-metabolism. In conclusion, significant quantities of CTC, ECTC, and ICTC can be exposed to nature by solid phase of anaerobic digestate. The inhibition on AD can reduce the degradation of CTC, ECTC, and ICTC during the AD.

Food loss rate in food supply chain using material flow analysis.

The food loss rate is a factor that represents food consumption efficiency. To improve food consumption efficiency, we need to fundamentally quantify food loss at national and global levels. This study examines food and food waste flow and calculates the food loss rate in the food supply chain by targeting Japan. We analyzed inedible food waste and avoidable food losses in wholesale, manufacturing, retail, food services, and households and considered different supply chain pathways, different food categories representing whole Japanese meals, and weight changes after cooking. The results are as follows: (1) Japan has an overall rate of avoidable food losses of approximately 15% for meals (excluding agricultural losses), (2) the supply sector with the highest food loss rate is food services, and (3) the food category with the highest food loss rate is vegetables. Finally, we proposed a model for calculating food loss rates that could be used for future analysis in Japan or other countries.