Surface Ozone Pollution: Trends, Meteorological Influences, and Chemical Precursors in Portugal

Surface ozone (O-3) is a secondary air pollutant, harmful to human health and vegetation. To provide a long-term study of O-3 concentrations in Portugal (study period: 2009-2019), a statistical analysis of ozone trends in rural stations (where the highest concentrations can be found) was first performed. Additionally, the effect of nitrogen oxides (NOx) and meteorological variables on O-3 concentrations were evaluated in different environments in northern Portugal. A decreasing trend of O-3 concentrations was observed in almost all monitoring stations. However, several exceedances to the standard values legislated for human health and vegetation protection were recorded. Daily and seasonal O-3 profiles showed high concentrations in the afternoon and summer (for all inland rural stations) or spring (for Portuguese islands). The high number of groups obtained from the cluster analysis showed the difference of ozone behaviour amongst the existent rural stations, highlighting the effectiveness of the current geographical distribution of monitoring stations. Stronger correlations between O-3, NO, and NO2 were detected at the urban site, indicating that the O-3 concentration was more NOx-sensitive in urban environments. Solar radiation showed a higher correlation with O-3 concentration regarding the meteorological influence. The wind and pollutants transport must also be considered in air quality studies. The presented results enable the definition of air quality policies to prevent and/or mitigate unfavourable outcomes from O-3 pollution

HAZOP Analysis in Terms of Safety Operations Processes for Oil Production Units: A Case Study

The Hazard and Operability Study (HAZOP) methodology is considered one of the most effective techniques for risk analysis, developed fundamentally to provide regular processes with reduced risks that aim to guarantee the safety of activities and the operability of the production units. The study aims to apply the HAZOP methodology in process and safety operations in the oil production industry. A crude oil production unit was divided into smaller sections that were analysed. By applying the HAZOP methodology, 71 possibilities of relevant risks were identified. The environmental, health and economic impacts were estimated to establish safeguard priorities for them. The application of this methodology and the defined safeguards generated 47 recommendations to mitigate the detected problems. The study contributions were to demonstrate the efficacies of HAZOP methodology to identify potential hazards and evaluate the potential hazards obtained for malfunctioning of equipment and property in terms of the resultant impacts either new or existing process facilities, and as a useful tool to provide essential knowledge for the companies' leaders, decision-maker, and operations managers

Analysis and Modelling of PM2.5 Temporal and Spatial Behaviors in European Cities

Particulate matter with an aerodynamic diameter of less than 2.5 mu m (PM2.5) is associated with adverse effects on human health (e.g., fatal cardiovascular and respiratory diseases), and environmental concerns (e.g., visibility impairment and damage in ecosystems). This study aimed to evaluate temporal and spatial trends and behaviors of PM2.5 concentrations in different European locations. Statistical threshold models using Artificial Neural Networks (ANN) defined by Genetic Algorithms (GA) were also applied for an urban centre site in Istanbul, to evaluate the influence of meteorological variables and PM10 concentrations on PM2.5 concentrations. Lower PM2.5 concentrations were observed in northern Europe. The highest values were found at traffic-related sites. PM2.5 concentrations were usually higher during the winter and tended to present strong increases during rush hours. PM2.5/PM10 ratios were slightly higher at background sites and the lower values were found in northern Europe (Helsinki and Stockholm). Ratios were usually higher during cold months and during the night. The statistical model (ANN + GA) allowed evaluating the combined effect of different explanatory variables (temperature, wind speed, relative humidity, air pressure and PM10 concentrations) on PM2.5 concentrations, under different regimes defined by relative humidity (threshold value of 79.1%). Important information about the temporal and spatial trends and behaviors related to PM2.5 concentrations in different European locations was developed

Microalgae Cultures: Environmental Tool and Bioenergy

[No abstract available

Recent Advances in Microalgal Biorefineries

[No abstract available

Optimization of Microalgal Harvesting with Inorganic and Organic Flocculants Using Factorial Design of Experiments

Microalgae have a lot of potential as a source of several compounds of interest to various industries. However, developing a sustainable and efficient harvesting process on a large scale is still a major challenge. This is particularly a problem when the production of low-value products is intended. Chemical flocculation, followed by sedimentation, is seen as an alternative method to improve the energetic and economic balance of the harvesting step. In this study, inorganic (aluminum sulfate, ferric sulfate, ferric chloride) and organic (Zetag 8185, chitosan, Tanfloc SG) flocculants were tested to harvest Chlorella vulgaris in batch mode. Preliminary assays were conducted to determine the minimum dosages of each flocculant that generates primary flocs at different pH. Except for chitosan, the organic flocculants required small dosages to initiate floc formation. Additional studies were performed for the flocculants with a better performance in the preliminary assays. Zetag 8185 had the best results, reaching 98.8% and 97.9% efficiencies with dosages of 50 and 100 mg L-1, respectively. Lastly, a 2(4) full factorial design experiment was performed to determine the effects of the flocculant dosage, settling time, and mixing time on the Zetag 8185 harvesting efficiency. The harvesting efficiency of C. vulgaris was optimal at a dosage of 100 mg L-1 and 3 min of rapid mixing

Microalgal cultures for the remediation of wastewaters with different nitrogen to phosphorus ratios: Process modelling using artificial neural networks

Microalgae have remarkable potential for wastewater bioremediation since they can efficiently uptake nitrogen and phosphorus in a sustainable and environmentally friendly treatment system. However, wastewater composition greatly depends on its source and has a significant seasonal variability. This study aimed to evaluate the impact of different N:P molar ratios on the growth of Chlorella vulgaris and nutrient removal from synthetic wastewater. Furthermore, artificial neural network (ANN) threshold models, optimised by genetic algorithms (GAs), were used to model biomass productivity (BP) and nitrogen/phosphorus removal rates (RRN/RRP). The impact of various inputs culture variables on these parameters was evaluated. Microalgal growth was not nutrient limited since the average biomass productivities and specific growth rates were similar between the experiments. Nutrient removal efficiencies/rates reached 92.0 +/- 0.6%/6.15 +/- 0.01 mgN L-1 d-1 for nitrogen and 98.2 +/- 0.2%/0.92 +/- 0.03 mgP L-1 d-1 for phosphorus. Low nitrogen concentration limited phosphorus uptake for low N:P ratios (e.g., 2 and 3, yielding 36 +/- 2 mgDW mgP-1 and 39 +/- 3 mgDW mgP-1, respectively), while low phosphorus concentration limited nitrogen uptake with high ratios (e.g., 66 and 67, yielding 9.0 +/- 0.4 mgDW mgN-1 and 8.8 +/- 0.3 mgDW mgN-1, respectively). ANN models showed a high fitting performance, with coefficients of determination of 0.951, 0.800, and 0.793 for BP, RRN, and RRP, respectively. In summary, this study demonstrated that microalgae could successfully grow and adapt to N:P molar ratios between 2 and 67, but the nutrient uptake was impacted by these variations, especially for the lowest and highest N:P molar ratios. Furthermore, GA-ANN models demonstrated to be relevant tools for microalgal growth modelling and control. Their high fitting performance in characterising this biological system can contribute to reducing the experi-mental effort for culture monitoring (human resources and consumables), thus decreasing the costs of microalgae production

Characterization of Surface Ozone Behavior at Different Regimes

Previous studies showed that the influence of meteorological variables and concentrations of other air pollutants on O-3 concentrations changes at different O-3 concentration levels. In this study, threshold models with artificial neural networks (ANNs) were applied to characterize the O-3 behavior at an urban site (Porto, Portugal), describing the effect of environmental and meteorological variables on O-3 concentrations. ANN characteristics, and the threshold variable and value, were defined by genetic algorithms (GAs). The considered predictors were hourly average concentrations of NO, NO2, and O-3, and meteorological variables (temperature, relative humidity, and wind speed) measured from January 2012 to December 2013. Seven simulations were performed and the achieved models considered wind speed (at 4.9 m.s(-1)), temperature (at 17.5 degrees C) and NO2 (at 26.6 mu g.m(-3)) as the variables that determine the change of O-3 behavior. All the achieved models presented a similar fitting performance: R-2 = 0.71-0.72, RMSE = 14.5-14.7 mu g.m(-3), and the index of agreement of the second order of 0.91. The combined effect of these variables on O-3 concentration was also analyzed. This statistical model was shown to be a powerful tool for interpreting O-3 behavior, which is useful for defining policy strategies for human health protection concerning this air pollutant

Microalgae systems- environmental agents for wastewater treatment and further potential biomass valorisation

Water is the most valuable resource on the planet. However, massive anthropogenic activities generate threat-ening levels of biological, organic, and inorganic pollutants that are not efficiently removed in conventional wastewater treatment systems. High levels of conventional pollutants (carbon, nitrogen, and phosphorus), emerging chemical contaminants such as antibiotics, and pathogens (namely antibiotic-resistant ones and related genes) jeopardize ecosystems and human health. Conventional wastewater treatment systems entail several environmental issues: (i) high energy consumption; (ii) high CO2 emissions; and (iii) the use of chemicals or the generation of harmful by-products. Hence, the use of microalgal systems (entailing one or several microalgae species, and in consortium with bacteria) as environmental agents towards wastewater treatment has been seen as an environmentally friendly solution to remove conventional pollutants, antibiotics, coliforms and antibiotic resistance genes. In recent years, several authors have evaluated the use of microalgal systems for the treatment of different types of wastewater, such as agricultural, municipal, and industrial. Generally, microalgal systems can provide high removal efficiencies of: (i) conventional pollutants, up to 99%, 99%, and 90% of total nitrogen, total phosphorus, and/or organic carbon, respectively, through uptake mechanisms, and (ii) antibiotics frequently found in wastewaters, such as sulfamethoxazole, ciprofloxacin, trimethoprim and azithromycin at 86%, 65%, 42% and 93%, respectively, through the most desirable microalgal mechanism, biodegradation. Although pathogens removal by microalgal species is complex and very strain-specific, it is also possible to attain total coliform and Escherichia coli removal of 99.4% and 98.6%, respectively. However, microalgal systems' effectiveness strongly relies on biotic and abiotic conditions, thus the selection of operational conditions is critical. While the combination of selected species (microalgae and bacteria), ratios and inoculum concentration allow the efficient removal of conventional pollutants and generation of high amounts of biomass (that can be further converted into valuable products such as biofuels and biofertilisers), abiotic factors such as pH, hydraulic retention time, light intensity and CO2/O2 supply also have a crucial role in conventional pollutants and anti-biotics removal, and wastewater disinfection. However, some rationale must be considered according to the purpose. While alkaline pH induces the hydrolysis of some antibiotics and the removal of faecal coliforms, it also decreases phosphates solubility and induces the formation of ammonium from ammonia. Also, while CO2 supply increases the removal of E. coli and Pseudomonas aeruginosa, as well as the microalgal growth (and thus the conventional pollutants uptake), it decreases Enterococcus faecalis removal. Therefore, this review aims to pro-vide a critical review of recent studies towards the application of microalgal systems for the efficient removal of conventional pollutants, antibiotics, and pathogens; discussing the feasibility, highlighting the advantages and challenges of the implementation of such process, and presenting current case-studies of different applications of microalgal systems

Microalgal Systems, a Green Solution for Wastewater Conventional Pollutants Removal, Disinfection, and Reduction of Antibiotic Resistance Genes Prevalence?

The low-efficiency rate of urban wastewater (UWW) treatment generates tons of discharged water with a high concentration of pollutants, pathogens and antibiotic-resistance genes (ARGs). Microalgal systems may be a green alternative to be implemented as a UWW polishing treatment. This study assessed the ability of Chlorella vulgaris and UWW autochthonous microalgal species (AMS) to simultaneously remove PO4-P, and reduce the proliferation of coliforms and ARGs. AMS seems to be more promising due to: (i) the higher specific growth rate, mu(max) (0.687 +/- 0.065 d(-1)); (ii) efficient PO4-P removal (92.62 +/- 0.10%); (iii) faster reduction of coliforms proliferation achieving concentrations below the limits of quantification (6 d); (iv) the reduction of intl1 and the ARGs sul1 and blaTEM abundance in ca. of 70.4%, 69.2%, and 75.7%, respectively (9 d); and (v) the additional reduction of these genes in ca. of 97.1%, 94.2%, and 99.9%, respectively, after 5 d storage in the dark and at room temperature. Results also revealed that the high pH values in both microalgal systems (due to microalgal growth) were highly correlated with a reduction in the proliferation of coliforms, including Escherichia coli. In conclusion, using AMS as a final polishing treatment of UWW seems to be very promising