Assessing water quality index and health risk using deterministic and probabilistic approaches in Darab County, Iran; A machine learning for fluoride prediction.

The present study employed deterministic and probabilistic approaches to determine the Water Quality Index (WQI) and assess health risks associated with water consumption in Darab County, Iran. Additionally, pollution levels were predicted using a machine-learning algorithm. The study's findings indicate that certain physicochemical parameters of water in some locations exceeded permissible limits (WHO or EPA), with 79.00 % of total hardness (TH) and 21.74 % of Total dissolved solids (TDS) levels exceeding standard values. The WQI for drinking water was determined to be 94.56 % using the deterministic approach, and 98.4 % of samples included the excellent and good categories according to the WQI classification system using the probabilistic approach. Fluoride (F) exhibited the most substantial impact on WQI values. The Artificial Neural Network (ANN) analysis findings suggest that the pH, nitrate (NO3), and TDS are the most significant factors affecting the prediction of F concentration in water. Multivariate analysis demonstrated that anthropogenic, especially agriculture and geogenic factors, contributed to the water quality in this area. The health risk assessment (HRA) using deterministic methods revealed that water consumption posed a relatively high risk in certain areas. However, Monte Carlo simulation demonstrated that the 5th and 95th percentiles of Hazard Index (HI) for children, teenagers, and adults were within limits of (0.14-2.38), (0.09-1.29), and (0.10-1.00) respectively, with a certainty level of 70 %, 91 %, and 95 %. Interactive indices revealed that the intake of IR and NO3-IR in children, BW and F-BW in teenagers, and NO3 and NO3-IR in adults significantly impacted health risks. Based on these findings, augmenting water treatment processes, regulating fluoride concentrations, and advocating for sustainable agricultural practices complemented by continuous monitoring is imperative.

Nitrate concentrations and health risks in cow milk from Iran: Insights from deterministic, probabilistic, and AI modeling.

Excessive nitrate consumption has been linked to potential health risks in humans. Thus, understanding nitrate levels in staple foods such as cow milk can provide insights into their health implications. This study meticulously examined nitrate concentrations in 70 cow milk samples from traditional and industrialized cattle farming systems in Fars province, Iran. A combination of deterministic modeling, a probabilistic approach, and six artificial intelligence algorithms was employed to determine health risk assessments. The data disclosed average nitrate concentrations of 32.63 mg/L in traditional farming and 34.95 mg/L in industrialized systems, presenting no statistically significant difference (p > 0.05). The Hazard Quotient (HQ) was deployed to gauge potential health threats, underscoring heightened vulnerability in children, who exhibited HQ values ranging from 0.05 to 0.58 (mean = 0.19) in contrast to adults, whose values spanned 0.01 to 0.16 (mean = 0.05). Monte Carlo simulations enriched the risk assessment, demarcating the 5th and 95th percentile nitrate concentrations for children at 0.07 and 0.39, respectively. In children, pivotal interactions that influenced HQ encompassed those between nitrate concentration and consumption rate, as well as nitrate concentration and body weight. The interplay between nitrate concentration and consumption rate was most consequential for the adult cohort. Among the algorithms assessed for HQ prediction, Gaussian Naive Bayes (GNB) was optimal for children and eXtreme Gradient Boosting (XGB) for adults, with nitrate concentration being a key determinant. The results underscore the imperative for rigorous oversight of milk nitrate concentrations, highlighting the enhanced susceptibility of children and emphasizing the need for preventive strategies and enlightened consumption.

Modeling, quality assessment, and Sobol sensitivity of water resources and distribution system in Shiraz: A probabilistic human health risk assessment.

Given water's vital role in supporting life and ecosystems, global climate change and human activities have significantly diminished its availability and quality. This study explores the health risks of drinking water consumption in the shiraz county water resources and distribution system. The result showed that the water was slightly alkaline. However, the average pH values during the study were within the permissible range. The area's abundance of total hardness and calcium was due to the high concentration of minerals in rocks and soils. The nitrate and fluoride concentrations in drinking groundwater varied from 0.02 to 116.70 mg/L and 0.10-1.85 mg/L, respectively. Although the water quality index indicated that 52.63, 45.03, and 20.3 percent of samples were of excellent, good, and poor quality in 2020, those percentages obtained 46.05, 52.09, and 14.0 percent in 2021. The regression values of training, testing, validation, and the proposed artificial neural network model were 0.93, 0.92, 0.85, and 0.92. The maximum levels of hazard quotient of nitrate and fluoride (except for adults) were higher than 1 in all age groups, indicating a high non-carcinogenic risk by exposure to nitrate. Furthermore, according to the Monte Carlo simulation, the 95th percentile hazard index in all groups was more than 1. Children and infants were more inclined towards risk than teens and adults based on the intake of nitrate and fluoride from drinking water. The Sobol sensitivity reflected that the nitrate concentration and ingestion rate are vital parameters that influence the outcome of the oral exposure model for all age groups. The interaction of ingestion rate with a concentration of nitrate and fluoride is an important parameter affecting the health risk assessment. In conclusion, these findings suggest that precise measures can reduce health risks and guarantee safe drinking water for residents of Shiraz County.

Magnetic Levitation System Isolates and Purifies Airborne Viruses.

Detection of viable viruses in the air is critical in order to determine the level of risk associated with the airborne diffusion of viruses. Different methods have been developed for the isolation, purification, and detection of viable airborne viruses, but they require an extensive processing time and often present limitations including low physical efficiency (i.e., the amount of collected viruses), low biological efficiency (i.e., the number of viable viruses), or a combination of all. To mitigate such limitations, we have employed an efficient technique based on the magnetic levitation (Maglev) technique with a paramagnetic solution and successfully identified distinct variations in levitation and density characteristics among bacteria (Escherichia coli), phages (MS2), and human viruses (SARS-CoV-2 and influenza H1N1). Notably, the Maglev approach enabled a significant enrichment of viable airborne viruses in air samples. Furthermore, the enriched viruses obtained through Maglev exhibited high purity, rendering them suitable for direct utilization in subsequent analyses such as reverse transcription-polymerase chain reaction (RT-PCR) or colorimetric assays. The system is portable, easy to use, and cost-efficient and can potentially provide proactive surveillance data for monitoring future outbreaks of airborne infectious diseases and allow for the induction of various preventative and mitigative measures.

Placental plastics in young women from general population correlate with reduced foetal growth in IUGR pregnancies.

Constant exposure to plastics particulates has raised concerns against human health, particularly when it comes to birth outcomes. The present study explores the first appraisal of plastic particles in fresh human placenta and its association with foetal growth in neonates. Specifically, 43 pregnant women from general population were selected and their placentas were analyzed by digital microscopy and Raman microspectroscopy for microplastics (MPs <5 mm). We used regression analysis to estimate associations between MPs count in placenta and neonatal anthropometric measurements. MPs were found in all (13 out of 13) intrauterine growth restriction (IUGR) pregnancies and their average abundance ranged from 2 to 38 particles per placenta, but were less than limit of detection (LOD) in normal pregnancies except three out of 30 subjects. This study is one of very few that detected MPs in human placenta in which particles <10 µm were the most abundant in both IUGR and normal pregnancies, accounting for up to 64%. Fragments clearly prevailed at normal pregnancies and fragments together with fibers predominated at IUGR placentas. Despite four different polymers forming the MPs being identified, the majority of MPs comprised of PE (polyethylene) and PS (polystyrene). Inverse associations between MPs exposure and birth outcomes were observed in terms of birth weight (r = - 0.82, p < 0.001), length (r = - 0.56, p < 0.001), head circumference (r = - 0.50, p = 0.001), and 1-min Apgar score (r = - 0.75, p < 0.001) among those with IUGR, compared to those that were nominated as normal pregnancies. While it seems plastic particles may affect placental-foetal interrelationship, the pattern of associations between their content in placenta and birth outcomes, however, shows evidence of a nonlinear or nonmonotonic dose response possibly through perturbation of gas and nutrients exchange which is worth future investigation.

MicrobiomeCensus estimates human population sizes from wastewater samples based on inter-individual variability in gut microbiomes.

The metagenome embedded in urban sewage is an attractive new data source to understand urban ecology and assess human health status at scales beyond a single host. Analyzing the viral fraction of wastewater in the ongoing COVID-19 pandemic has shown the potential of wastewater as aggregated samples for early detection, prevalence monitoring, and variant identification of human diseases in large populations. However, using census-based population size instead of real-time population estimates can mislead the interpretation of data acquired from sewage, hindering assessment of representativeness, inference of prevalence, or comparisons of taxa across sites. Here, we show that taxon abundance and sub-species diversisty in gut-associated microbiomes are new feature space to utilize for human population estimation. Using a population-scale human gut microbiome sample of over 1,100 people, we found that taxon-abundance distributions of gut-associated multi-person microbiomes exhibited generalizable relationships with respect to human population size. Here and throughout this paper, the human population size is essentially the sample size from the wastewater sample. We present a new algorithm, MicrobiomeCensus, for estimating human population size from sewage samples. MicrobiomeCensus harnesses the inter-individual variability in human gut microbiomes and performs maximum likelihood estimation based on simultaneous deviation of multiple taxa's relative abundances from their population means. MicrobiomeCensus outperformed generic algorithms in data-driven simulation benchmarks and detected population size differences in field data. New theorems are provided to justify our approach. This research provides a mathematical framework for inferring population sizes in real time from sewage samples, paving the way for more accurate ecological and public health studies utilizing the sewage metagenome.

Sewage Systems Surveillance for SARS-CoV-2: Identification of Knowledge Gaps, Emerging Threats, and Future Research Needs.

The etiological agent for novel coronavirus (COVID-19, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), not only affects the human respiratory system, but also the gastrointestinal tract resulting in gastrointestinal manifestations. The high rate of asymptomatic infected individuals has challenged the estimation of infection spread based on patients' surveillance, and thus alternative approaches such as wastewater-based epidemiology (WBE) have been proposed. Accordingly, the number of publications on this topic has increased substantially. The present systematic review thus aimed at providing state-of-the-knowledge on the occurrence and existing methods for sampling procedures, detection/quantification of SARS-CoV-2 in sewage samples, as well as anticipating challenges and providing future research direction to improve the current scientific knowledge. Articles were collected from three scientific databases. Only studies reporting measurements of virus in stool, urine, and wastewater samples were included. Results showed that improving the scientific community's understanding in these avenues is essential if we are to develop appropriate policy and management tools to address this pandemic pointing particularly towards WBE as a new paradigm in public health. It was also evident that standardized protocols are needed to ensure reproducibility and comparability of outcomes. Areas that require the most improvements are sampling procedures, concentration/enrichment, detection, and quantification of virus in wastewater, as well as positive controls. Results also showed that selecting the most accurate population estimation method for WBE studies is still a challenge. While the number of people infected in an area could be approximately estimated based on quantities of virus found in wastewater, these estimates should be cross-checked by other sources of information to draw a more comprehensive conclusion. Finally, wastewater surveillance can be useful as an early warning tool, a management tool, and/or a way for investigating vaccination efficacy and spread of new variants.

Environmental risk assessments of multiclass pharmaceutical active compounds: selection of high priority concern pharmaceuticals using entropy-utility functions.

This research aimed to identify high-risk pharmaceutically active compounds (PhACs) by analyzing occurrence (O), persistence (P), bioaccumulation (B), and toxicity (T) of 62 drugs which are widely used in Iran. A comprehensive approach was taken in risk assessment of the selected PhACs and in their prioritization using multiple-criteria decision analysis (MCDA) such as utility functions and principal component analysis (PCA). In practice, assigning weight to each criterion (i.e., O, P, B, and T) for risk assessment of PhACs is a challenge. In this research, the impact of giving both equal and unequal weight to each criterion by using a quantitative entropy method was studied. For risk assessment, two exposure approaches (consumption rate and occurrence of PhACs) and three MCDA approaches (PCA and utility functions with and without equal weights for each criterion) were compared. The utility function using equal weights for all O, P, B, and T criteria showed that thioridazine, pimozide, chlorpromazine, sertraline, clomipramine, and aripiprazole were at the highest level of risk, with concern score of 0.75, 0.75, 0.67, 0.58, 0.58, and 0.58, respectively. Unequal weight approach included additional compounds such as fluoxetine, citalopram, and methadone as a priority. All three MCDA approaches showed that sedatives and antidepressants were prevalent PhACs in the risk-based priority lists. However, the exposure-based approaches showed antibiotics and analgesics as the pharmaceutical of the highest priority. Overall, selection of the high priority concern pharmaceuticals depends on the prioritization approach employed. However, the utility function using unequal weights is a more conservative and effective approach for prioritization.

Moore swab performs equal to composite and outperforms grab sampling for SARS-CoV-2 monitoring in wastewater.

Wastewater-based epidemiology (WBE) approaches to detect SARS-CoV-2 in municipal wastewater can provide unique information on the incidence or prevalence of COVID-19 in community. However, there are several technical challenges coupled with sewage sampling for SARS-CoV-2, including intermittent shedding of viruses, sampling time, volume, and frequency. Sampling schemes thus may need to be tailored to reach out highly sensitive, accurate, and reliable results. Herein, we compared the accuracy and threshold cycle (Ct) profiles of SARS-CoV-2 in Moore swabs, composite (16-h), and grab samples taken from sewage manholes (n = 17) at the Middle Eastern city of Tehran, Iran, on two occasions (November 2020 and May 2021). Samples were concentrated by polyethylene glycol precipitation and the corresponding Ct values for CDC 'N' and 'ORF1ab' assays were derived by means of real time RT-qPCR. Overall, the Moore swabs performed equal to samples composited over 16 h for qualitative monitoring, and 34/34 (100%) were positive for SARS-CoV-2. The 'N' assay showed the highest detection frequency as compared to 'ORF1ab'. The mean Moore swab Ct profiles were more consistent with 16 h composite sampling as compared with corresponding grab samples, providing hints as to the best sampling protocol to adopt when planning a sewage monitoring campaign particularly under WBE. Furthermore, our analyses on local differences showed somewhat higher virus copy numbers in the southern areas. The experimental design of this study revealed that the Moore swab and composite samples are more sensitive than grab samples, suggesting that the collection of grab samples may be inappropriate for characterizing total number of viral RNA copies in sewage samples. Given the transiently presence of human host-restricted infections such as SARS-CoV-2 and the simplicity and affordability of Moore swab, the method is well suited for disease surveillance in resource poor regions struggling with limited capacity for clinical testing.

Longitudinal wastewater sampling in buildings reveals temporal dynamics of metabolites.

Direct sampling of building wastewater has the potential to enable "precision public health" observations and interventions. Temporal sampling offers additional dynamic information that can be used to increase the informational content of individual metabolic "features", but few studies have focused on high-resolution sampling. Here, we sampled three spatially close buildings, revealing individual metabolomics features, retention time (rt) and mass-to-charge ratio (mz) pairs, that often possess similar stationary statistical properties, as expected from aggregate sampling. However, the temporal profiles of features-providing orthogonal information to physicochemical properties-illustrate that many possess different feature temporal dynamics (fTDs) across buildings, with large and unpredictable single day deviations from the mean. Internal to a building, numerous and seemingly unrelated features, with mz and rt differences up to hundreds of Daltons and seconds, display highly correlated fTDs, suggesting non-obvious feature relationships. Data-driven building classification achieves high sensitivity and specificity, and extracts building-identifying features found to possess unique dynamics. Analysis of fTDs from many short-duration samples allows for tailored community monitoring with applicability in public health studies.

Investigating the androgenic activity of ozonation transformation products of testosterone and androstenedione.

This study investigates the impact of ozonation on the concentration of two androgen steroid hormones, testosterone and androstenedione, and on androgenic activity as measured using the YAS assay. While these compounds are remarkably similar in chemical structure and showed comparable removal profiles in the presence and absence of a hydroxyl scavenger (isopropanol), large differences between percent removal of target compounds using chemical analysis and percent removal of bioactivity was observed when small ozone doses were applied. The dynamic change and initial increase in bioactivity during ozonation can be attributed to transformation products. These results demonstrate the importance of combining chemical analysis and bioanalytical techniques not only to perform a comprehensive assessment of environmental risks but also as a tool to optimize treatment technologies proposed as a mean to mitigate the impact of contaminants of emerging concern.

Toxicity of extracts from municipal wastewater to early life stages of Japanese medaka (Oryzias latipes) to evaluate removals of micropollutants by wastewater treatment.

Treatment of municipal wastewater reduces the concentrations of some pharmaceuticals and personal care products (PPCPs), hormones, and drugs of abuse. However, reduced concentrations of these micropollutants in wastewater may not correlate with reduced toxicity because transformations of micropollutants and/or the formation of disinfection by-products may generate toxic compounds. In the present study, we prepared extracts by solid phase extraction of samples collected from wastewater treatment plants (WWTPs) at various stages of treatment and tested these extracts for toxicity to early life stages of Japanese medaka (Oryzias latipes). Toxicity data for extracts prepared from a WWTP with secondary treatment showed that the numbers of exposed embryos (n = 12 per treatment) that did not hatch increased from 1 of 12 for the treatment with untreated effluent to 5 of 12 for the treatment with final treated effluent. For extracts prepared from a WWTP with tertiary treatment, toxicity among exposed embryos (n = 12 per treatment) also increased with each step of wastewater treatment, as shown by mortalities of 2 of 12 and 8 of 12 in treatments with extracts from untreated and final treated effluent, respectively, as well as an increase in the numbers of embryos that did not hatch from 2 of 12 to 9 of 12 in treatments with untreated and final treated effluent, respectively. Ozonation of treated wastewater collected from a third WWTP caused a high incidence of delayed hatch in exposed embryos (n = 24 per treatment). However, hatching success and the numbers of developmental abnormalities in embryos from this ozonation treatment were not different from controls. The present study shows the value of including toxicity testing to assess the effectiveness of technologies for treatment of municipal wastewater. Environ Toxicol Chem 2018;37:136-144. © 2017 SETAC.

Evaluation of wastewater treatment by ozonation for reducing the toxicity of contaminants of emerging concern to rainbow trout (Oncorhynchus mykiss).

Although conventional wastewater treatment technologies are effective at removing many contaminants of emerging concern (CECs) from municipal wastewater, some contaminants are not removed efficiently. Ozonation may be a treatment option for reducing the concentrations of recalcitrant CECs in wastewater, but this process may generate toxic transformation products. In the present study, we conducted semibatch experiments to ozonate municipal wastewater effluent spiked with 5 commonly detected CECs. The purpose of the present study was to evaluate whether ozonation increased or decreased biological responses indicative of sublethal toxicity in juvenile rainbow trout (Oncorhynchus mykiss) injected intraperitoneally (i.p.) with extracts prepared from ozonated and nonozonated wastewater effluent. Blood, liver, and brain tissues were collected from the fish at 72 h post injection for analysis of a battery of biomarkers. In fish i.p. injected with the extracts from nonozonated wastewater effluent, significant induction of plasma vitellogenin (VTG) was observed, but ozonation of the municipal wastewater effluent spiked with CECs significantly reduced this estrogenic response. However, in fish injected with extracts from spiked municipal wastewater effluent after ozonation, the balance of hepatic glutathione in its oxidized (glutathione disulfide [GSSG]) form was altered, indicating oxidative stress. Levels of the neurotransmitter serotonin were significantly elevated in brain tissue from trout injected with the extracts from ozonated spiked municipal wastewater effluent, a biological response that has not been previously reported in fish. Other in vivo biomarkers showed no significant changes across treatments. These results indicate that ozonation reduces the estrogenicity of wastewater, but may increase other sublethal responses. The increase in biomarker responses after ozonation may be because of the formation of biologically active products of transformation of CECs, but further work is needed to confirm this conclusion. Environ Toxicol Chem 2018;37:274-284. © 2017 SETAC.

Endocrine Activities of Pesticides During Ozonation of Waters.

Two yeast-based bioassays were used to assess the endocrine activity potential of transformation products formed during the ozonation of water containing a variety of pesticides (propiconazole, atrazine, 2,4-dichlorophenoxyacetic acid [2,4-D], tebuconazole, climbazole, myclobutanil, irgarol, terbutryn, dicamba, mecoprop and diuron). Ozone experiments were conducted first in reverse osmosis water to isolate the effects of the pesticides and then in synthetic wastewater and wastewater effluent to investigate whether the results translated to more complex matrices. The findings demonstrate the recalcitrant nature of most pesticides during ozonation, with removals below 50%, except for irgarol, terbutryn and climbazole with removals up to 70%. This study is the first one to investigate the removal of the fungicides myclobutanil and tebuconazole by ozonation and is one of the first studies to investigate the androgenic activity of ozonation transformation products of contaminants of emerging concern. These findings also demonstrated that during ozonation the initial anti-androgenic activity was removed while the estrogenic activity remained undetected and the androgenic activity increased to levels up to 60% of the anti-androgenic activity of the DHT control. These results indicate that bioactivity should be considered in the evaluation of treatment performance and risks assessment associated to wastewater discharges.

Investigation of Acute and Chronic Toxicity Trends of Pesticides Using High-Throughput Bioluminescence Assay Based on the Test Organism Vibrio fischeri.

High-throughput acute and chronic toxicity tests using Vibrio fischeri were used to assess the toxicity of a variety of fungicides, herbicides, and neonicotinoids. The use of time points beyond the traditional 30 min of an acute test highlighted the sensitivity and applicability of the chronic toxicity test and indicated that for some compounds toxicity is underestimated using only the acute test. The comparison of EC50 values obtained from acute and chronic tests provided insight regarding the toxicity mode of action, either being direct or indirect. Using a structure-activity relationship approach similar to the one used in hazard assessments, the relationship between toxicity and key physicochemical properties of pesticides was investigated and trends were identified. This study not only provides new information regarding acute toxicity of some pesticides but also is one of the first studies to investigate the chronic toxicity of pesticides using the test organism V. fischeri. The findings demonstrated that the initial bioluminescence has a large effect on the calculated effective concentrations for target compounds in both acute and chronic tests, providing a way to improve and standardize the test protocol. In addition, the findings emphasize the need for additional investigation regarding the relationship between a toxicant's physicochemical properties and mode of action in nontarget organisms.

Development of a Facile and High-Throughput Bioluminescence Assay Using Vibrio fischeri to Determine the Chronic Toxicity of Contaminated Samples.

Chronic toxicity testing using the luminescent bacterium, Vibrio fischeri, has recently been demonstrated to be a suitable bioassay for water quality monitoring. The toxicity evaluation is typically based on determining the EC50 at specific time points which may lead to overlooking the dynamic nature of luminescence response and limits information regarding the possible mechanisms of action of target compounds. This study investigated various approaches (standard, integral, and luminescence rate inhibition) to evaluate the chronic toxicity of three target compounds (atrazine, trimethoprim, and acetamiprid) using a 96-well plate based method. The chronic toxicity assay and the methods used for EC50 calculation provided in this work resulted in a high-throughput method of chronic toxicity testing and indicated lower EC50 than the values provided by the standard short term methods, indicating higher toxicity. This study emphasizes the need for additional chronic toxicity testing to further evaluate the toxicity of compounds or unknown samples.

Bacterial community assembly in activated sludge: mapping beta diversity across environmental variables.

Effect of ecological variables on community assembly of heterotrophic bacteria at eight full-scale and two pilot-scale activated sludge wastewater treatment plants (AS-WWTPs) were explored by pyrosequencing of 16S rRNA gene amplicons. In total, 39 samples covering a range of abiotic factors spread over space and time were analyzed. A core bacterial community of 24 families detected in at least six of the eight AS-WWTPs was defined. In addition to the core families, plant-specific families (observed at <50% AS-WWTPs) were found to be also important in the community structure. Observed beta diversity was partitioned with respect to ecological variables. Specifically, the following variables were considered: influent wastewater characteristics, season (winter vs. summer), process operations (conventional, oxidation ditch, and sequence batch reactor), reactor sizes (pilot-scale vs. full-scale reactors), chemical stresses defined by ozonation of return activated sludge, interannual variation, and geographical locations. Among the assessed variables, influent wastewater characteristics and geographical locations contributed more in explaining the differences between AS-WWTP bacterial communities with a maximum of approximately 26% of the observed variations. Partitioning of beta diversity is necessary to interpret the inherent variability in microbial community assembly and identify the driving forces at play in engineered microbial ecosystem.

Heavy metal contamination in street dusts with various land uses in Zahedan, Iran.

A total of 78 street dust samples (75 within city and 3 from suburban) were collected from different areas with various land use within the city of Zahedan in November 2013 at the end of a long dry period. After digestion, the concentrations of Cd, Cr, Cu, Ni, Pb, and Zn were measured by using ICP-OES. The degree of pollution by heavy metals was assessed with respect to the background concentration by calculation and comparison of the pollution index, integrated pollution index (IPI) and enrichment factor (EF). The mean IPI values (aggregate of six heavy metals) in commercial, high traffic, industrial, urban park, and residential were 3.65, 2.76, 1.68, 1.53 and 1.25, respectively. The results of EF analysis showed almost all sampled urban land use types to be enriched in heavy metals compared with sampled background levels, suggesting heavy metals contamination of street dust in the urban center is from anthropogenic sources.

Should activated sludge models consider influent seeding of nitrifiers? Field characterization of nitrifying bacteria.

This study revealed the presence of nitrifying bacteria in influent municipal wastewaters reaching full-scale biological wastewater treatment plants. Respirometric assays showed that the influent nitrifiers were active following a 5- to 8-hour period of metabolic induction. Diversity analyses by pyrosequencing of functional gene PCR (polymerase chain reaction) amplicon suggested that the nitrifiers in the influent stream likely seeded activated sludge bioreactors since the most abundant operational taxonomic units in the influent and mixed liquor were the same. Based on the estimated seeding intensity of 0.3 g of nitrifiers per day per gram of nitrifiers already present, the absolute minimum solids retention time (SRT) was reduced by approximately 56% at 5 °C as compared to non-seeding conditions. This can have important repercussions on the design and sizing of bioreactors operating in cold climates and calls for a need to fine-tune process modelling by considering the contribution of autotrophic nitrifying biomass from municipal influent streams.

New mechanistically based model for predicting reduction of biosolids waste by ozonation of return activated sludge.

Two pilot-scale activated sludge reactors were operated for 98 days to provide the necessary data to develop and validate a new mathematical model predicting the reduction of biosolids production by ozonation of the return activated sludge (RAS). Three ozone doses were tested during the study. In addition to the pilot-scale study, laboratory-scale experiments were conducted with mixed liquor suspended solids and with pure cultures to parameterize the biomass inactivation process during exposure to ozone. The experiments revealed that biomass inactivation occurred even at the lowest doses, but that it was not associated with extensive COD solubilization. For validation, the model was used to simulate the temporal dynamics of the pilot-scale operational data. Increasing the description accuracy of the inactivation process improved the precision of the model in predicting the operational data.