Synergistic algal/bacterial interaction in membrane bioreactor for detoxification of 1,2-dichloroethane-rich petroleum wastewater.

The study addressed the challenge of treating petroleum industry wastewater with high concentrations of 1,2-dichloroethane (1,2-DCA) ranging from 384 to 1654 mg/L, which poses a challenge for bacterial biodegradation and algal photodegradation. To overcome this, a collaborative approach using membrane bioreactors (MBRs) that combine algae and bacteria was employed. This synergistic method effectively mitigated the toxicity of 1,2-DCA and curbed MBR fouling. Two types of MBRs were tested: one (B-MBR) used bacterial cultures and the other (AB-MBR) incorporated a mix of algal and bacterial cultures. The AB-MBR significantly contributed to 1,2-DCA removal, with algae accounting for over 20% and bacteria for approximately 49.5% of the dechlorination process. 1,2-DCA metabolites, including 2-chloroethanol, 2-chloro-acetaldehyde, 2-chloroacetic acid, and acetic acid, were partially consumed as carbon sources by algae. Operational efficiency peaked at a 12-hour hydraulic retention time (HRT) in AB-MBR, enhancing enzyme activities crucial for 1,2-DCA degradation such as dehydrogenase (DH), alcohol dehydrogenase (ADH), and acetaldehyde dehydrogenase (ALDH). The microbial diversity in AB-MBR surpassed that in B-MBR, with a notable increase in Proteobacteria, Bacteroidota, Planctomycetota, and Verrucomicrobiota. Furthermore, AB-MBR showed a significant rise in the dominance of 1,2-DCA-degrading genus such as Pseudomonas and Acinetobacter. Additionally, algal-degrading phyla (e.g., Nematoda, Rotifera, and Streptophyta) were more prevalent in AB-MBR, substantially reducing the issue of membrane fouling.

Quantifying the impact of urban road traffic on air quality: activity pre-pandemic and during partial and full lockdowns.

The impact of partial and full COVID lockdowns in 2020 on vehicle miles traveled (VMT) in Kuwait was estimated using data extracted from the Directions API of Google Maps and a Python script running as a cronjob. This approach was validated by comparing the predictions based on the app to measuring traffic flows for 1 week across four road segments considered in this study. VMT during lockdown periods were compared to VMT for the same calendar weeks before the pandemic. NOx emissions were estimated based on VMT and were used to simulate the spatial patterns of NOx concentrations using an air quality model (AERMOD). Compared to pre-pandemic periods, VMT was reduced by up to 25.5% and 42.6% during the 2-week partial and full lockdown episodes, respectively. The largest reduction in the traffic flow rate occurred during the middle of these 2-week periods, when the traffic flow rate decreased by 35% and 49% during the partial and full lockdown periods, respectively. The AERMOD simulation results predicted a reduction in the average maximum concentration of emissions directly related to VMT across the region by up to 38%, with the maximum concentration shifting to less populous residential areas as a result of the lockdown.

An integrated framework for exploring the tradeoffs between cost-optimized fuel allocation and regional air quality impacts in a water-energy nexus infrastructure.

This paper presents an integrated framework in which an air quality dispersion model is combined with an economic dispatch model to address the environmental tradeoffs of a cost-optimized fuel allocation strategy. A unit commitment dispatch model was developed to re-allocate fuel between power generation and desalination plants. Then, an air quality dispersion model was run for a 1-year period to simulate the spatiotemporal transport of pollutants and the possible formation of air pollution hotspots. The results showed that optimizing fuel allocation can reduce the associated fuel cost by as much as 16.5% of the total cost (1.08 billion USD). The optimized fuel allocation approach resulted in reducing the base case emissions of NOx, SO2, CO, and PM10 by 25%, 4.6%, 3.1%, and 7.6%, respectively. However, the air quality impact of the optimized fuel allocation scheme was not as favorable. The 1-h-averaged maximum concentration of SO2 increased, and NOx concentrations were slightly above the allowable limits. Although fewer pollutants were emitted over the study period in the optimized fuel allocation case, the variability in how fuel was allocated between power and desalination plants concentrated emissions near residential areas. As a result of this trend, the maximum 1-h concentrations of all pollutants increased, with increases ranging from 1% for CO to 29% for PM10. In addition, the total number of hourly SO2 concentration violations increased dramatically, leading to additional hotspot areas. Therefore, the effectiveness of any environmental-economic fuel dispatch strategy should be tested based on additional indicators such as the allowable limits of pollutant concentrations and not exclusively the overall emissions of the system. This approach could promote the selection of the most economic fuel dispatch method while simultaneously considering regional air quality impacts.

The impact of power plant emission variability and fuel switching on the air quality of Kuwait.

Power plant emissions have a significant impact on air quality, and a frequent assumption made in estimating impacts is to assume annual or monthly average emission rates. This study investigates the impact, on predicted ambient concentrations, of assuming annual average emissions, compared to resolving emissions on an hourly basis (base case). A case study of emissions from power plants in Kuwait, for the year 2014, is presented. In Kuwait, power plants operate on a mix of natural gas, gas oil, crude oil, and heavy fuel oil, and the type of fuel used varies on an hourly basis. Because of this fuel variability, a fuel switching strategy was also simulated in this work, replacing high sulfur fuels with natural gas during hours with high predicted SO2 concentrations. Emissions estimates were combined with an air quality dispersion model to simulate the temporal variability and spatial dispersion of sulfur dioxide (SO2) and nitrogen dioxide (NO2) in Kuwait, for a one-year episode. The results indicate that emission averaging and fuel switching operations result in lower area-wide annual maximum SO2 concentrations compared to the base case (1747 µg/m3, 1063 µg/m3, 616 µg/m3 for base case, annual average emissions and fuel switching scenarios, respectively). The number of receptor sites recording daily exceedances of the SO2 standard for annual average emissions were one seventh of those predicted for hourly averaged emissions and 92% lower for the fuel switching scenario. For NO2, while the overall number of exceedances of air quality criteria was much lower than for SO2, the numbers of exceedances were also predicted to be lower using annual averaged emissions compared to the base case. These results document the importance of using emission estimates that capture hourly variability over annually averaged emissions, particularly in locations such as Kuwait where multiple fuels are used in power production.