An index directly indicates land-based pollutant load contributions of domestic wastewater to the water pollution and its application

Study on load allocation of land-based total nitrogen in the Bohai Sea

Total nitrogen (TN) is one of the terrigenous pollutants in the Bohai Sea. A reasonable releasing scheme can effectively improve the seawater quality. Based on the observed TN concentrations and the national pollution control requirements, the TN load ratios of four major rivers around the Bohai Sea are adjusted in multiple levels within the range of 50 %-200 % in the frame of total control. Then, a pollutant transport model is used to evaluate each load allocation scheme by calculating the area of different seawater qualities. The optimum scheme is loads of the Yellow River and Luan River are set to 50 % and 200 % of the levels in 2018, and thus the area of heavily polluted seawater can be decreased by 33.14 %. Additionally, the reasonable TN reduction amounts of four major rivers in 2018-2020 are calculated according to the optimum scheme, which can be provided as a decision-making basis of marine managements.

Biomarkers selection for population normalization in SARS-CoV-2 wastewater-based epidemiology

Wastewater-based epidemiology (WBE) has been one of the most cost-effective approaches to track the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) levels in the communities since the coronavirus disease 2019 (COVID-19) outbreak in 2020. Normalizing SARS-CoV-2 concentrations by the population biomarkers in wastewater is critical for interpreting the viral loads, comparing the epidemiological trends among the sewersheds, and identifying the vulnerable communities. In this study, five population biomarkers, pepper mild mottle virus (PMMoV), creatinine (CRE), 5-hydroxyindoleacetic acid (5-HIAA), caffeine (CAF) and its metabolite paraxanthine (PARA) were investigated and validated for their utility in normalizing the SARS-CoV-2 loads through two normalizing approaches using the data from 64 wastewater treatment plants (WWTPs) in Missouri. Their utility in assessing the real-time population contributing to the wastewater was also evaluated. The best performing candidate was further tested for its capacity for improving correlation between normalized SARS-CoV-2 loads and the clinical cases reported in the City of Columbia, Missouri, a university town with a constantly fluctuating population. Our results showed that, except CRE, the direct and indirect normalization approaches using biomarkers allow accounting for the changes in wastewater dilution and differences in relative human waste input over time regardless flow volume and population of the given WWTP. Among selected biomarkers, PARA is the most reliable population biomarker in determining the SARS-CoV-2 load per capita due to its high accuracy, low variability, and high temporal consistency to reflect the change in population dynamics and dilution in wastewater. It also demonstrated its excellent utility for real-time assessment of the population contributing to the wastewater. In addition, the viral loads normalized by the PARA-estimated population significantly improved the correlation (rho=0.5878, p < 0.05) between SARS-CoV-2 load per capita and case numbers per capita. This chemical biomarker complements the current normalization scheme recommended by CDC and helps us understand the size, distribution, and dynamics of local populations for forecasting the prevalence of SARS-CoV2 within each sewershed.

Interpreting per capita loads of organic matter and nutrients in municipal wastewater: A study on 168 Italian agglomerations

The size of an agglomeration is expressed in population equivalent, referring to the maximum average weekly load during the year according to the European Directive 271/91. This quantity, multiplied by the daily biochemical oxygen demand (BOD) produced by one population equivalent (which is 60 g d^-1 PE^-1, by definition), yields the design biodegradable organic load of the wastewater treatment plant. The same agglomeration size is compared against the capacity of the wastewater treatment plant (WWTP) for plant conformity verification by the European Commission. However, field observations show remarkable fluctuations of the daily mass flows entering a WWTP, often considerably below or above the expected load calculated according to the Directive prescriptions. A wrong estimation of the real influent load adversely affects the plant design and operation, and may lead to a misleading verification of its conformity to the agglomeration. In this work, a statistical data analysis on 168 agglomerations was performed, aiming at verifying the consistency between the expected loads of BOD, chemical oxygen demand (COD), nitrogen and phosphorus and the mass flows measured at the treatment plant inlet. Only 30-40% of the total analysed cases were found having an actual load compatible with the expected one. In these cases, the average per capita daily loads of BOD, COD, nitrogen and phosphorus, calculated over 2-3 years data pools, resulted: 44.6 ± 5.9, 82.4 ± 11, 9.4 ± 1.1, and 1.08 ± 0.13 g d^-1, respectively, while the daily BOD per capita production of 60 g represented a value in between the 70th and the 90th percentiles of the actual daily load distributions. For the remaining 60-70% of the total cases, variably-remarkable positive or negative discrepancies between the nominal pollutant loads generated by the agglomeration and those measured at the plant inlet could be detected and possible causes were pointed out.

Biomarkers Selection for Population Normalization in SARS-CoV-2 Wastewater-based Epidemiology

Wastewater-based epidemiology (WBE) has been one of the most cost-effective approaches to track the SARS-CoV-2 levels in the communities since the COVID-19 outbreak in 2020. Normalizing SARS-CoV-2 concentrations by the population biomarkers in wastewater can be critical for interpreting the viral loads, comparing the epidemiological trends among the sewersheds, and identifying the vulnerable communities. In this study, five population biomarkers, pepper mild mottle virus (pMMoV), creatinine (CRE), 5-hydroxyindoleacetic acid (5-HIAA), caffeine (CAF) and its metabolite paraxanthine (PARA) were investigated for their utility in normalizing the SARS-CoV-2 loads through developed direct and indirect approaches. Their utility in assessing the real-time population contributing to the wastewater was also evaluated. The best performed candidate was further tested for its capacity for improving correlation between normalized SARS-CoV-2 loads and the clinical cases reported in the City of Columbia, Missouri, a university town with a constantly fluctuated population. Our results showed that, except CRE, the direct and indirect normalization approaches using biomarkers allow accounting for the changes in wastewater dilution and differences in relative human waste input over time regardless flow volume and population at any given WWTP. Among selected biomarkers, PARA is the most reliable population biomarker in determining the SARS-CoV-2 load per capita due to its high accuracy, low variability, and high temporal consistency to reflect the change in population dynamics and dilution in wastewater. It also demonstrated its excellent utility for real-time assessment of the population contributing to the wastewater. In addition, the viral loads normalized by the PARA-estimated population significantly improved the correlation ( rho =0.5878, p <0.05) between SARS-CoV-2 load per capita and case numbers per capita. This chemical biomarker offers an excellent alternative to the currently CDC-recommended pMMoV genetic biomarker to help us understand the size, distribution, and dynamics of local populations for forecasting the prevalence of SARS-CoV2 within each sewershed.

HIGHLIGHT bullet points

The paraxanthine (PARA), the metabolite of the caffeine, is a more reliable population biomarker in SARS-CoV-2 wastewater-based epidemiology studies than the currently recommended pMMoV genetic marker.SARS-CoV-2 load per capita could be directly normalized using the regression functions derived from correlation between paraxanthine and population without flowrate and population data.Normalizing SARS-CoV-2 levels with the chemical marker PARA significantly improved the correlation between viral loads per capita and case numbers per capita.The chemical marker PARA demonstrated its excellent utility for real-time assessment of the population contributing to the wastewater.

Water quality and climate variability of urban and tourism areas in Thailand and northern Vietnam: correlations and possible influences on nearby coastal shrimp farms

This research explored the long-term relationships of climate parameters and coastal water quality nearby shrimp farms in two countries. In Thailand, two sampling points in canals located in Bangkok and Trang provinces were selected as the urban and tourism areas, respectively. In northern Vietnam, the canals located in Thai Binh and Quang Ninh provinces were used as the urban and tourism areas, respectively. The diurnal monitoring of water quality and weather was performed at each site to evaluate the relationships between climate and water quality, pollution load, and risk analysis. A questionnaire was also used to assess the climate and water exposure, vulnerability, and adaptability of each site. All data were ranked on a scale of 1 to 5 to integrate each factor. It was determined that the main water quality problem was fecal pollution. Notably, aquaculture farming in northern Vietnam is more vulnerable than in Thailand; however, Vietnam farmers were adaptable for climate variability.

City-level SARS-CoV-2 sewage surveillance

The COVID-19 pandemic created a global crisis impacting not only healthcare systems, but also economics and society. Therefore, it is important to find novel methods for monitoring disease activity. Recent data have indicated that fecal shedding of SARS-CoV-2 is common, and that viral RNA can be detected in wastewater. This suggests that wastewater monitoring is a potentially efficient tool for both epidemiological surveillance, and early warning for SARS-CoV-2 circulation at the population level. In this study we sampled an urban wastewater infrastructure in the city of Ashkelon (̴ 150,000 population), Israel, during the end of the first COVID-19 wave in May 2020 when the number of infections seemed to be waning. We were able to show varying presence of SARS-CoV-2 RNA in wastewater from several locations in the city during two sampling periods, before the resurgence was clinically apparent. This was expressed with a new index, Normalized Viral Load (NVL) which can be used in different area scales to define levels of virus activity such as red (high) or green (no), and to follow morbidity in the population at the tested area. The rise in viral load between the two sampling periods (one week apart) indicated an increase in morbidity that was evident two weeks to a month later in the population. Thus, this methodology may provide an early indication for SARS-CoV-2 infection outbreak in a population before an outbreak is clinically apparent.

Impact of China's water pollution on agricultural economic growth: an empirical analysis based on a dynamic spatial panel lag model

The average annual growth rate of China's waste emissions from 2007 to 2017 was 2.3%. The main pollutants in the wastewater are chemical oxygen demand, ammonia nitrogen, total ammonia, total phosphorus, and so on which pollute groundwater and destroy ecosystems. Poor water quality reduces the edible value of agricultural products and has an impact on human health. Based on the panel data of 31 provinces in China from 2007 to 2017, this paper uses a dynamic spatial panel lag model to study the impact of China's water pollution on agricultural economic growth. The results show that the impact of China's water pollution on agricultural economic growth is significant. If the intensity of wastewater discharge is taken as an input factor in the process of agricultural production, the growth of agricultural economy tends to decline with the increase of water pollution. In the effect analysis, the short-term and long-term effects are significant. The absolute value of the long-term total effect is far greater than the short-term total effect, indicating that the inhibitory effect of water pollution on agricultural economic growth is more obvious. The cumulative effect of water pollution on agricultural economic growth continues to expand, resulting in more and more economic losses. The central and local governments should take various measures to reduce water pollution, guide the green development of agriculture, and increase farmers' income to realize the rural revitalization plan.

The utilization of reclaimed water: Possible risks arising from waterborne contaminants

Increasing interest of seeking substitutable water resources accrues from shortage of freshwater. One of the options considered is reclaimed water (also designated as recycled water) that has been widely used in daily life. Although reclaimed water can serve as a feasible reliever of water pressure, attention about its technologies and potential risks is growing in the meantime. Most established wastewater treatment plants (WWTPs) predate many new contaminants, which means treatment processes cannot ensure to dislodge certain contaminants completely from origin water. Furthermore, a wide range of factors, such as seasons and influent variations, affect occurrence and concentration of reclaimed water-borne contaminants, making research about quality of reclaimed water especially significant. Many reclaimed water-borne contaminants, including biological and chemical contaminants, are toxic to human health, and complex wastewater matrix may aggravate water quality of concern. The widespread use of reclaimed water continues to be a concern on agriculture, ecological environment and human health. This study aims to: 1) provide a critical review about occurrence and profiles of diverse contaminants in the treated reclaimed water, 2) discuss the possibility to avoid the secondary pollution in reuse of reclaimed water, and 3) reveal the prospective consequences of using reclaimed water on agriculture, ecological environment and human health.

A new approach to nationwide sanitation planning for developing countries: Case study of Indonesia

Many developing countries struggle to provide wastewater and solid waste services. The backlog in access has been partly attributed to the absence of a functional sanitation planning framework. Various planning tools are available; however a comprehensive framework that directly links a government policy to nationwide planning is missing. Therefore, we propose a framework to facilitate the nationwide planning process for the implementation of wastewater and solid waste services. The framework requires inputs from government planners and experts in the formulation of starting points and targets. Based on a limited number of indicators (population density, urban functions) three outputs are generated. The first output is a visualization of the spatial distribution of wastewater and solid waste systems to support regional priority setting in planning and create awareness. Secondly, the total number of people served, budget requirements and distribution of systems is determined. Thirdly, the required budget is allocated to the responsible institution to assure effective implementation. The determined budgets are specified by their beneficiaries, distinguishing urban, rural, poor and non-poor households. The framework was applied for Indonesia and outputs were adopted in the National Development Plan. The required budget to reach the Indonesian government's 2019 target was determined to be 25 billion US$ over 5years. The contribution from the national budget required a more than fivefold increase compared to the current budget allocation in Indonesia, corresponding to an increase from 0.5 to 2.7 billion US$ per year. The budget for campaigning, advocacy and institutional strengthening to enable implementation was determined to be 10% of the total budget. The proposed framework is not only suitable for Indonesia, but could also be applied to any developing country that aims to increase access to wastewater and solid waste facilities.

Wastewater analysis to monitor use of caffeine and nicotine and evaluation of their metabolites as biomarkers for population size assessment

The use of caffeine, nicotine and some major metabolites was investigated by wastewater analysis in 13 sewage treatment plants (STPs) across Italy, and their suitability was tested as qualitative and quantitative biomarkers for assessing population size and dynamics. A specific analytical method based on mass spectrometry was developed and validated in raw urban wastewater, and included two caffeine metabolites, 1-methylxanthine and 7-methylxanthine, never reported in wastewater before. All these compounds were found widely at the μg/L level. Mass loads, calculated by multiplying concentrations by the wastewater daily flow rate and normalized to the population served by each plant, were used to compare the profiles from different cities. Some regional differences were observed in the mass loads, especially for nicotine metabolites, which were significantly higher in the south than in the center and north of Italy, reflecting smoking prevalences from population surveys. There were no significant weekly trends, although the mean mass loads of caffeine and its metabolites were slightly lower during the weekend. Most caffeine and nicotine metabolites fulfilled the requirements for an ideal biomarker for the assessment of population size, i.e. being easily detectable in wastewater, stable in sewage and during sampling, and reflecting human metabolism. Nicotine metabolites were tested as quantitative biomarkers to estimate population size and the results agreed well with census data. Caffeine and its metabolites were confirmed as good qualitative biomarkers, but additional information is needed on the caffeine metabolism in relation to the multiple sources of its main metabolites. This exploratory study opens the way to the routine use of nicotine metabolites for estimating population size and dynamics.

Life cycle assessment of animal feeds prepared from liquid food residues: a case study of rice-washing water

Life cycle assessment (LCA) was used to compare the greenhouse gas (GHG) emissions and energy consumption of three methods used to produce animal feed from concentrated rice-washing water (CRW) and disposing of the rice-washing water through wastewater treatment. Four scenarios were compared using LCA: (i) producing concentrated liquid feed by centrifugation (CC) of CRW with wastewater treatment and discharge of the supernatant, (ii) producing concentrated liquid feed by heating evaporation (HC) of CRW, (iii) producing dehydrated feed by dehydration (DH) of CRW, and (iv) wastewater treatment and discharge of nonconcentrated rice-washing water (WT). The functional unit (FU) was defined as 1 metric ton of rice washed for cooking or processing. Our results suggested that the energy consumptions of CC, HC, DH, and WT were 108, 322, 739, and 242 MJ per FU, respectively, and the amounts of GHG emissions from CC, HC, DH, and WT were 6.4, 15.8, 45.5, and 22.5 kg of CO equivalents per FU, respectively. When the produced feed prepared from CRW was assumed to be transported 200 km to farms, CC and HC still emitted smaller GHGs than the other scenarios, and CC consumed the smallest amount of energy among the scenarios. The present study indicates that liquid feed production from CRW by centrifugation has a remarkably reduced environmental impact compared with the wastewater treatment and discharge of rice-washing water.

Real-time estimation of small-area populations with human biomarkers in sewage

A new approach is conceptualized for measuring small-area human populations by using biomarkers in sewage. The basis for the concept (SCIM: Sewage Chemical-Information Mining) is supported by a comprehensive examination and synthesis of data published across several disciplines, including medicine, microbiology, clinical chemistry, and environmental science. Accurate measures of human populations are fundamental to numerous disciplines, including economics, marketing, politics, sociology, public health and safety (e.g., disease management; assessment of natural hazards; disaster prevention and response), quality of life, and the environment. Knowing the size, distribution, and flow of a small-area (local) population facilitates understanding the numerous and complex linkages and interactions between humans and the environment. Examples include material-flow (substance-flow) analysis, determining the magnitude of per capita contribution of pollutant loadings to watersheds, or forecasting future impacts of local populations on the environment or a population's demands on resources. While no definitive approach exists for measuring small-area populations, census-taking is a long-established convention. No approach exists, however, for gauging small-area populations in real-time, as none is able to capture population dynamics, which involve transient changes (e.g., daily influx and efflux) and lasting changes (e.g., births, deaths, change in residence). Accurate measurement of small-area populations in real time has never been possible but is essential for facilitating the design of more sustainable communities. Real-time measurement would provide communities the capability of testing what-if scenarios in design and policy decisions. After evaluation of a range of biomarkers (including the nitrogenous waste product creatinine, which has been long used in clinical chemistry as a parameter to normalize the concentrations of other urinary excretion products to account for urine dilution), the biomarker with the most potential for the SCIM concept for real-time measurement of population was determined to be coprostanol - the major sterol produced by microbial reduction of cholesterol in the colon.

Translational benchmark risk analysis

Translational development - in the sense of translating a mature methodology from one area of application to another, evolving area - is discussed for the use of benchmark doses in quantitative risk assessment. Illustrations are presented with traditional applications of the benchmark paradigm in biology and toxicology, and also with risk endpoints that differ from traditional toxicological archetypes. It is seen that the benchmark approach can apply to a diverse spectrum of risk management settings. This suggests a promising future for this important risk-analytic tool. Extensions of the method to a wider variety of applications represent a significant opportunity for enhancing environmental, biomedical, industrial, and socio-economic risk assessments.

Benchmark analysis for quantifying urban vulnerability to terrorist incidents

We describe a quantitative methodology to characterize the vulnerability of U.S. urban centers to terrorist attack, using a place-based vulnerability index and a database of terrorist incidents and related human casualties. Via generalized linear statistical models, we study the relationships between vulnerability and terrorist events, and find that our place-based vulnerability metric significantly describes both terrorist incidence and occurrence of human casualties from terrorist events in these urban centers. We also introduce benchmark analytic technologies from applications in toxicological risk assessment to this social risk/vulnerability paradigm, and use these to distinguish levels of high and low urban vulnerability to terrorism. It is seen that the benchmark approach translates quite flexibly from its biological roots to this social scientific archetype.