Microbial fuel cells (MFCs) that are bio-energy transducers capture bioelectricity produced from the oxidation of organic matter by using the electro-active bacteria grown on the biofilm attached on anode. Previous studies explored the effect of several limiting factors, such as electrode material, catalyst type, membrane structure, and electrolyte, on the electrochemical performance of MFCs. However, the effects of electrode position on Cr(VI) reduction and bioelectricity production remain unknown. https://www.selleckchem.com/products/ars-853.html In this study, MFCs with different electrode positions (i.e., 4 cm (MFC-4), 3 cm (MFC-3), 2 cm (MFC-2), and 1 cm (MFC-1)) were designed and fabricated to evaluate the overall performance of MFCs. The results of electrochemical analysis confirmed that MFC-2 exhibited low exchange transfer resistance (4.9 Ω) and strong conductivity, resulting in optimal electrochemical performance. In addition, Cr(VI) was completely removed within 11 h in MFC-2 with a large reduction rate of 0.91 g/m3·h. and COD removal efficiency of 78.25%. The overall performance of MFC-2 was comparatively higher than those of MFC-1 (0.80 g/m3·h and 68.82%), MFC-3 (0.64 g/m3·h and 61.67%), and MFC-4 (0.52 g/m3·h and 39.85%). Meanwhile, MFC-2 generated high open voltage (1.02 V) and power density (535.4 mW/m2), which are 1.4- and 3.1-fold larger than those of MFC-4 (0.72 V and 171.3 mW/m2). High COD removal and power density indicated the strong electrochemical activity of electroactive bacteria in the anode chamber of the MFCs, which was due to the low resistance in the MFCs could accelerate electron transfer and boost electrochemical reaction. Consequently, the optimal electrode spacing in MFCs was 2 cm. Further studies confirmed that Cr(VI) was removed and deposited in the form of Cr(III) on the electrode surface. High-throughput analysis suggested Pseudomonas species are the key electroactive bacteria for electricity generation.The COVID lockdown has affected food purchases and eating habits. In this regard, this short communication assesses the nutritional and environmental impacts of these changes during the COVID lockdown in Spain, by applying Life Cycle Assessment and an energy- and nutrient-corrected functional unit. Three environmental impacts were studied (Global Warming Potential, Blue Water Footprint and Land Use) and a total of seven weekly diet scenarios were designed two pre-COVID diets for March and April in 2019 (MAR19, APR19), one COVID diet (COVID) and two alternative diets, one based on the National Dietary Guidelines (NDG) and another one on the Planetary Health Diet (PHD). Results show that the COVID diet had larger energy intake and lower nutritional quality, as well as higher environmental impacts (between 30 and 36%) than the pre-COVID eating patterns. Further research is needed to account for food affordability within this assessment, as well as to analyze how eating patterns will evolve after the COVID lockdown. Finally, the definition of short guidelines for sustainable food behaviors for future possible lockdowns is suggested, as well as the introduction of sustainable indicators within NDGs.We model the impact of restricting socioeconomic activities (SA) on the transmission of COVID-19 globally. Countries initiate public health measures to slow virus transmission, ranging from stringent quarantines including city lockdown to simpler social distancing recommendations. We use satellite readings of NO2, a pollutant emitted from socioeconomic activities, as a proxy for the level of social-economic restrictions, and discuss the implications under the influences of weather. We found that restricting SA has a leading contribution to lowering the reproductive number of COVID-19 by 18.3% ± 3.5%, while air temperature, the highest contributor among all weather-related variables only contributes 8.0% ± 2.6%. The reduction effects by restricting SA becomes more pronounced (23% ± 3.0%) when we limited the data to China and developed countries where the indoor climate is mostly controlled. We computed the spared infectees by restricting SA until mid-April. Among all polities, China spared 40,964 (95% CI 31,463-51,470) infectees with 37,727 (95% CI, 28,925-47,488) in the Hubei Province, the epicenter of the outbreak. Europe spared 174,494 (95% CI 139,202-210,841) infectees, and the United States (US) spared 180,336 (95% CI 142,860-219,445) with 79,813 (95% CI 62,887-97,653) in New York State. In the same period, many regions except for China, Australia, and South Korea see a steep upward trend of spared infectees due to restricting SA with the US and Europe far steeper, signaling a greater risk of reopening the economy too soon. Latin America and Africa show less reduction of transmissivity through the region-by-time fixed effects than other regions, indicating a higher chance of becoming an epicenter soon.Low-cost sensors are useful tools for the collection of air quality data, augmenting the existing regulatory monitoring networks and providing an unprecedented opportunity to increase their spatial coverage. This study presents a calibration process of a low-cost PM sensor (PurpleAir PA-II, PAir) in ambient conditions in the city of Patras, Greece, during 18 months of 2017-2018. The hourly PM1 and PM2.5 measurements using the original sensor values were reasonably well correlated (R2 = 0.82 for PM1 and R2 = 0.56 for PM2.5) with the reference instrument, but with a high mean bias and root mean square error. There was a small improvement of around 10% for the daily averages. For PM1-2.5 (particles with diameters between 1 and 2.5 μm), PM2.5-10 (diameters between 2.5 and 10 μm) and PM10, the performance of the low-cost sensors was poor in this area with R2 less then 0.37 in all cases. The response of the PAir sensor for PM1 and PM2.5 changed significantly compared to the reference instrument during periods with high dust (or other coarse particle) concentrations. These periods were excluded and a simple linear calibration was then developed for the rest of the fine PM measurements. A method for the identification of these high dust periods based on regional model predictions is proposed. This calibration reduces the relative mean error for hourly PM1 to 19% (1.1 μg m-3) and for PM2.5 to 18% (1.1 μg m-3). The corresponding root mean square errors are 25% (1.4 μg m-3) for hourly PM1 and 25% (1.6 μg m-3) for PM2.5. The biases of the corrected values are, as expected, practically zero. Surprisingly, the relative humidity had a negligible effect on fine PM measurements of the PAir in this location and for the conditions of the study.