Abstract: Complete removal of estrogens such as estrone (E1), estradiol (E2), estriol (E3) and ethinylestradiol (EE2) in wastewater treatment is essential since their release and accumulation in natural water bodies are giving rise to environment and health issues. To improve our understanding towards the estrogen bioremediation process, a mathematical model was proposed for describing estrogen removal by nitrifying activated sludge. Four pathways were involved in the developed model: i) biosorption by activated sludge flocs; ii) cometabolic biodegradation linked to ammonia oxidizing bacteria (AOB) growth; iii) non growth biodegradation by AOB; and iv) biodegradation by heterotrophic bacteria (HB). The degradation kinetics was implemented into activated sludge model (ASM) framework with consideration of interactions between substrate update and microorganism growth as well as endogenous respiration. The model was calibrated and validated by fitting model predictions against two sets of batch experimental data under different conditions. The model could satisfactorily capture all the dynamics of nitrogen, organic matters (COD), and estrogens. Modeling results suggest that for El, E2 and EE2, AOB-linked biodegradation is dominant over biodegradation by HB at all investigated COD dosing levels. However, for E3, the increase of COD dosage triggers a shift of dominant pathway from AOB biodegradation to HB biodegradation. Adsorption becomes the main contributor to estrogen removal at high biomass concentrations. (C) 2018 Elsevier Ltd. All rights reserved.

Abstract: Hydrogenotrophic denitrification is a novel and sustainable process for nitrogen removal, which utilizes hydrogen as electron donor, and carbon dioxide as carbon source. Recent studies have shown that nitrous oxide (N2O), a highly undesirable intermediate and potent greenhouse gas, can accumulate during this process. In this work, a new mathematical model is developed to describe nitrogen oxides dynamics, especially N2O, during hydrogenotrophic denitrification for the first time. The model describes electron competition among the four steps of hydrogenotrophic denitrification through decoupling hydrogen oxidation and nitrogen reduction processes using electron carriers, in contrast to the existing models that couple these two processes and also do not consider N2O accumulation. The developed model satisfactorily describes experimental data on nitrogen oxides dynamics obtained from two independent hydrogenotrophic denitrifying cultures under various hydrogen and nitrogen oxides supplying conditions, suggesting the validity and applicability of the model. The results indicated that N2O accumulation would not be intensified under hydrogen limiting conditions, due to the higher electron competition capacity of N2O reduction in comparison to nitrate and nitrite reduction during hydrogenotrophic denitrification. The model is expected to enhance our understanding of the process during hydrogenotrophic denitrification and the ability to predict N2O accumulation.

Abstract: Even though nitrification/denitrification is a robust technology to remove nitrogen from sewage, economic incentives drive its future replacement by shortcut nitrogen removal processes. The latter necessitates high potential activity ratios of ammonia oxidizing to nitrite oxidizing bacteria (rAOB/rNOB). The goal of this study was to identify which wastewater and process parameters can govern this in reality. Two sewage treatment plants (STP) were chosen based on their inverse rAOB/rNOB values (at 20 °C): 0.6 for Blue Plains (BP, Washington DC, US) and 1.6 for Nieuwveer (NV, Breda, NL). Disproportional and dissimilar relationships between AOB or NOB relative abundances and respective activities pointed towards differences in community and growth/activity limiting parameters. The AOB communities showed to be particularly different. Temperature had no discriminatory effect on the nitrifiers' activities, with similar Arrhenius temperature dependences (ΘAOB = 1.10, ΘNOB = 1.061.07). To uncouple the temperature effect from potential limitations like inorganic carbon, phosphorus and nitrogen, an add-on mechanistic methodology based on kinetic modelling was developed. Results suggest that BP's AOB activity was limited by the concentration of inorganic carbon (not by residual N and P), while NOB experienced less limitation from this. For NV, the sludge-specific nitrogen loading rate seemed to be the most prevalent factor limiting AOB and NOB activities. Altogether, this study shows that bottom-up mechanistic modelling can identify parameters that influence the nitrification performance. Increasing inorganic carbon in BP could invert its rAOB/rNOB value, facilitating its transition to shortcut nitrogen removal.

Abstract: Urban environments typically exhibit large atmospheric pollution variation, in both space and time. In contrast to traditional monitoring networks suffering from a limited spatial coverage, mobile platforms enable personalized high-resolution monitoring, providing valuable insights into personal atmospheric pollution exposure, and the identification of potential pollution hotspots. This study evaluated personal cyclist exposure to UFPs, BC and heavy metals whilst commuting near Antwerp, Belgium, by performing mobile measurements with wearable black carbon (BC) and ultrafine particle (UFP) instruments. Loaded micro-aethalometer filterstrips were chemically analysed and the inhaled pollutant dose determined from the exhibited heart rate. Considerable spatial pollutant variation was observed along the travelled routes, with distinct contributions from spatial factors (e.g. traffic intersections, urban park and market) and temporary events. On average 300% higher BC, 20% higher UFP and changing elemental concentrations are observed along the road traffic route (RT), when compared to the bicycle highway route (BH). Although the overall background pollution determines a large portion of the experienced personal exposure (in this case 53% for BC and 40% for UFP), cyclists can influence their personal atmospheric pollution exposure, by selecting less exposed commuting routes. Our results, hereby, strengthen the body of evidence in favour of further policy investments in isolated bicycle infrastructure.

Abstract: This work is focused on an in-depth experimental characterization of multi-tube reactors for indoor air purification integrated in ventilation systems. Glass tubes were selected as an excellent photocatalyst substrate to meet the challenging requirements of the operating conditions in a ventilation system in which high flow rates are typical. Glass tubes show a low-pressure drop which reduces the energy demand of the ventilator, and additionally, they provide a large exposed surface area to allow interaction between indoor air contaminants and the photocatalyst. Furthermore, the performance of a range of P25-loaded sol-gel coatings was investigated, based on their adhesion properties and photocatalytic activities. Moreover, the UV light transmission and photocatalytic reactor performance under various operating conditions were studied. These results provide vital insights for the further development and scaling up of multi-tube reactors in ventilation systems which can provide a better comfort, improved air quality in indoor environments, and reduced human exposure to harmful pollutants.

Abstract: The principle of similarity (Thompson, 1917) states that the weight of an organism follows the 3/2-power law of its surface area and is proportional to its volume on the condition that the density is constant. However, the allometric relationship between leaf weight and leaf area has been reported to greatly deviate from the 3/2-power law, with the irregularity of leaf density largely ignored for explaining this deviation. Here, we choose 11 bamboo species to explore the allometric relationships among leaf area (A), density (ρ), length (L), thickness (T), and weight (W). Because the edge of a bamboo leaf follows a simplified two-parameter Gielis equation, we could show that A ∝ L2 and that A ∝ T2. This then allowed us to derive the density-thickness allometry ρ ∝ Tb and the weight-area allometry W ∝ A(b+3)/2 ≈ A9/8, where b approximates −3/4. Leaf density is strikingly negatively associated with leaf thickness, and it is this inverse relationship that results in the weight-area allometry to deviate from the 3/2-power law. In conclusion, although plants are prone to invest less dry mass and thus produce thinner leaves when the leaf area is sufficient for photosynthesis, such leaf thinning needs to be accompanied with elevated density to ensure structural stability. The findings provide the insights on the evolutionary clue about the biomass investment and output of photosynthetic organs of plants. Because of the importance of leaves, plants could have enhanced the ratio of dry material per unit area of leaf in order to increase the efficiency of photosynthesis, relative the other parts of plants. Although the conclusion is drawn only based on 11 bamboo species, it should also be applicable to the other plants, especially considering previous works on the exponent of the weight-area relationship being less than 3/2 in plants.