Many of municipal wastewater treatment plants (WWTPs) are operated by biological process with their excellent performances. However, the early warning system in the influent line is required to avoid the process malfunction because the biological wastewater treatment system has serious drawback to toxic chemicals in the influent. In order to develop a new type of biosensor using anaerobic granules in an online device for rapid detection of toxic inhibitory to the biological process, a porous pot reactor and an anaerobic granule biosensor (AGB) were demonstrated as an upset early warning device (UEWD) in this study. In the first group of toxic loading tests, the prepared cupric chloride solutions were separately injected into both the porous pot and AGB systems at six different concentrations, and phenol solutions were used at three different concentrations in the second group of tests. The results showed the chemical oxygen demand (COD) and ammonia nitrogen (ammonia-N) removal efficiency from porous pot reactor decreased dramatically in response to the addition of Cu²⁺and phenol with the variation of the oxidation-reduction potential (ORP) in AGB. The response of AGB system was 6 to 20 h in advance of porous pot reactor performance response, which suggests that the AGB could potentially be used as an online UEWD.

In an effort to customize biochars for soil amendments, multiple feedstocks have been combined in various ratios prior to pyrolysis. The resulting variation in the chemistry and structure can affect a biochar’s adsorption capacity, which influences the bioavailability of many chemical compounds in the soil system including phenolic acids. This study characterizes the sorption of 14C-labeled ferulic acid, syringic acid, and chlorocatechol to four biochars prepared from individual feedstocks and four from mixed feedstocks using batch equilibration. Pure feedstock biochar sorption followed switchgrass< swine solids< poultry litter< pine chip for both ferulic (Kd= 1.4-75) and syringic acid (Kd= 0.07-6.03), and appeared to be influenced by the properties of the biochars as well as the chemicals themselves. All biochar Kd values, except pine chip, were lower than that of the reference soil (Waukegan silt loam). The sorptive properties of the combined feedstock biochars could not be predicted from their pure feedstock components and sorption coefficients were both unexpectedly higher and lower than the individual parent materials’ biochars. Further research is necessary to understand the characteristics of these combination biochars, particularly their sorption, which this study has shown is not merely an intermediary of its components.

Bauxsol is a chemico-physically modified product of red mud and is a promising material for the removal and recovery of phosphorus from wastewater. In this study, response surface methodology (RSM) and artificial neural network (ANN) were employed to develop prediction models and also to investigate the interactions of independent experimental factors for phosphorus adsorption onto acid-activated Bauxsol. The experimental results indicated that HCl activation was effective to improve the adsorption capacity of Bauxsol. The maximum adsorption capacity of acid-activated Bauxsol was 55.72 mg/g (as P) with HCl concentration of 10.20 mol/L, temperature of 41.00 °C, and time of 5.60 h, which increased by 10.53 and 6.62 times compared with the raw red mud and Bauxsol before acid activation, respectively. The relative importance of HCl concentration in RSM and ANN models was 51.78 and 54.25 %, respectively, which illustrated that HCl concentration played the predominant role on improving the adsorption capacity of Bauxsol. The predictive capability of RSM and ANN models was compared, and the results showed that both models provided excellent predictions with R² > 0.93. However, the ANN model showed the superiority over RSM for estimation capability.

This paper reports about the modification of sand and fumed silica with titania in order to obtain a photocatalytic active material for the degradation of pollutants. The coating process was performed based on the sol–gel method. Tetrapropylorthotitanate was used as the titania precursor to apply a nanoscaled layer on sand grains. For silica fume, the coating process was varied. Various amounts of tetrapropylorthotitanate were used to obtain different coating thicknesses and to identify the maximum amount of titania that could be loaded on the material. All samples showed high photonic efficiencies in the degradation of nitrogen monoxide despite their low titania quantities, which were identified via x-ray fluorescence analysis. Some samples showed higher photonic efficiencies than commercial Degussa P25. Due to the preparation method, calcination of the sand composites was not necessary to yield a crystalline coating which was responsible for the high photocatalytic activity. However, silica fume composites had to be calcined possibly due to variation in the preparation method. Scanning electron micrographs revealed the structured morphology of all specimens. Energy dispersive x-ray analysis identified nanoscaled titania particles on the sand surface that could not be observed only via SEM. The results of this research are especially interesting for large scale applications of photocatalysts. As industrial sand and silica fume used are low cost materials, this new kind of photocatalyst can be applied in higher quantities and distributed onto larger areas, while saving costs at the same time.

The issue of air pollution has become the focus of the world because of its significant influence to the economic development and public health. This paper proposes an interval dual stochastic-mixed integer programming (IDSIP) approach for regional air quality management. The IDSIP approach can be effectively communicated into the optimization processes and resulting solutions, which is formulated through integrating interval-parameter integer programming (IIP) within a two-stage stochastic programming (TSP) joint chance-constrained programming (CCP) and could deal with uncertainties expressed as not only probability distributions but also interval values. Moreover, the left-hand-side (LHS) constraints with stochastic variables could be handled at different risk levels with varied reliability scenarios. In the modeling formulation, penalties are imposed when expected policies are violated. The results indicate that reasonable solutions for air quality management system have been generated, which can help decision makers draw up productive strategies taking into account the trade-off between system economy and air quality under uncertainty.

The composition of zooplankton, benthic macroinvertebrate (BMI) and forage fish communities of 20 lakes in and near Kejimkujik National Park and National Historic Site were evaluated as part of Environment Canada’s Acid Rain Biomonitoring Program. The pH of study lakes ranged from 4.3 to 6.6. Lake pH was positively correlated with alkalinity, calcium and magnesium concentrations and negatively correlated with colour, aluminium, total organic carbon and nitrogen. Gradients in overall BMI community composition and total BMI richness were strongly related to the gradient in pH, but the composition of zooplankton and forage fish communities were more strongly related to other environmental parameters such as elevation. Potential indicator species for future acid rain monitoring included Daphnia catawba, the amphipod Hyalella azteca, pill/pea clams Pisidium casertanum and Pisidium ferrugineum and larval water scavenger beetle Berosus. These chemical and biological data provide a baseline for future evaluation of the continued effects of anthropogenic deposition to this acid-sensitive region of Atlantic Canada.

Wastewater treatment works can receive toxic substances that can kill microorganisms responsible for waste degradation. Implementation of toxicity monitors in-sewer, as part of an early warning system to help prevent toxic substances entering treatment works, is, however, very rare. This work presents results from a pilot-scale study using an in-sewer early warning system based on detection of nitrous oxide (N₂O) gas emitted by nitrifying bacteria naturally present in sewer biofilm. Nitrous oxide has potential to be an indicator of nitrification inhibition as it is typically emitted when nitrifiers are under stress. The biofilm was allowed to develop over 14 days under fixed wastewater flow and level. Presence of nitrifying bacteria was verified on day 13 followed by a 90 min toxic shock on day 14 by four different known nitrification inhibitors. Pre-shock nitrification rates averaged 0.78 mg-NH₄⁺-N mg-VS⁻¹ d⁻¹and were significantly reduced post shock to <0.2 mg-NH₄⁺-N mg-VS⁻¹ d⁻¹. Nitrous oxide emissions were found to vary with influent wastewater quality, suggesting a more complex data processing algorithm is needed instead of a simple threshold emission value. The extent of nitrification inhibition differed from the recorded response for suspended growth biomass with allylthiourea resulting in a 77 and 81 % nitrification inhibition for literature suspended growth EC₅₀and EC₇₅concentrations, respectively. Results from this study suggest nitrifying biofilms in closed pipes can be used as part of an early warning system but will likely require amplification of the response to be of practical use. Further research is required to better understand the biofilm response and calibrate the early warning system for differentiating its unique baseline from true toxicity events.

Accumulation of heavy metals due to pollution of the environment, particularly in agricultural ecosystems, can cause serious deterioration of crop yield and quality. In this study, we assessed the effect of silicon on physiological, photosynthetic and stress-related aspects of cadmium toxicity in hydroponically grown maize plants (Zea mays L., hybrid Valentina). One concentration of silicon (5 mM) and two concentrations of cadmium (5 and 50 μM) added to the cultivation medium were tested. Cadmium alone led to a significant growth inhibition and negatively affected the content of total chlorophylls and the efficiency of photosystem II. Especially in roots, application of cadmium resulted in the accumulation of reactive oxygen species and consequent membrane lipid peroxidation. The supplementation of silicon successfully ameliorated the toxic effect of cadmium on maize plants and enhanced growth, some of the photosynthetic parameters and reduced the level of oxidative stress. In plants exposed to higher concentrations of cadmium silicon also reduced its accumulation, especially in roots. Changes in the accumulation of phenolic compounds may indicate the influence of silicon on this aspect of secondary plant metabolism and its importance in the detoxification of heavy metals.

The main objective of the present study is to measure the levels of heavy metals in important fruit species such as apple, apricot, and nectarine and their nine, five, and six cultivars, respectively. This work investigates the accumulation of Fe, Cu, Zn, Ni, Cd, Pb, and Cr in flowers of above species, to measure the levels of heavy metal contamination. The obtained results revealed that amounts of heavy metals significantly varied among cultivars at the same species and were within the permissible amounts in general. The Cd was not detected in apricot, nectarine, and the most of apple cultivars. Results for floral Fe, and also for Cu and Zn, which are the most important micronutrients for fruit production, suggest that levels of these elements might be used for assessing the storage of these elements during the previous season. We assume that the production of apple, apricot, and nectarine is safe, and there is no risk of contamination with heavy metals.

A 3-year study was conducted to determine the effects of anaerobic digestion (AD), large particle solids, and manure additive (More Than Manure, MTM™) on ammonia (NH₃) and greenhouse gas (GHG; carbon dioxide, nitrous oxide, and methane) emissions when raw and treated manure were surface-applied. The presence of large particle solids resulted in greater NH₃ emissions, probably, due to reduced infiltration of liquid manure into soil (P < 0.05). Anaerobic digestion did not have a consistent effect on NH₃ emission. Manure with greater ammoniacal nitrogen (AN) concentrations had significantly greater NH₃ loss after manure application (P < 0.05). Anaerobic digestion of manure also did not have a significant effect on GHG flux (P > 0.05). Raw manure with large particle solids had significantly greater CO₂ flux than the other raw manure treatments on the day of manure application (P < 0.05). There was no significant manure treatment effects (P > 0.2) on methane flux over the 3-day period after manure application. The manure additive MTM™ did not have significant effects (P > 0.05) on NH₃ and GHG fluxes. The results of this study suggest that solids and AN concentrations in manure are the most important factors affecting NH₃ emissions after surface application.