Considering Variations in Waste Composition during Waste Input‐Output Modeling

Concentrations of pollutants vary in wastes from different sources. However, existing waste input‐output (WIO) models do not take these differing concentrations into account. This article proposes a new category of model, which we are calling a waste input‐output model at the substance level (WIOS model). The WIOS model considers variations in waste composition. These variations potentially affect the life cycle inventory of the waste treatment stage. The proposed model is expected to produce more accurate results than existing WIO models that do not consider variations in the composition of wastes. In addition, the proposed model provides a method to trace substances undergoing waste treatment. In this article, use of the WIOS model is illustrated by simulating the overall environmental loads of total organic carbon from wastewater treatment at a facility in Germany. The results show that variations in the composition of wastes entering treatment significantly affect the modeled estimates of total environmental loads caused by wastewater treatment. In addition, the results of the proposed model are different from results given by existing hybrid input‐output WIO models that do not consider variations in the composition of wastewater as it undergoes treatment.     

Input‐Output‐based Life Cycle Inventory

An input‐output‐based life cycle inventory (IO‐based LCI) is grounded on economic environmental input‐output analysis (IO analysis). It is a fast and low‐budget method for generating LCI data sets, and is used to close data gaps in life cycle assessment (LCA). Due to the fact that its methodological basis differs from that of process‐based inventory, its application in LCA is a matter of controversy. We developed a German IO‐based approach to derive IO‐based LCI data sets that is based on the German IO accounts and on the German environmental accounts, which provide data for the sector‐specific direct emissions of seven airborne compounds. The method to calculate German IO‐based LCI data sets for building products is explained in detail. The appropriateness of employing IO‐based LCI for German buildings is analyzed by using process‐based LCI data from the Swiss Ecoinvent database to validate the calculated IO‐based LCI data. The extent of the deviations between process‐based LCI and IO‐based LCI varies considerably for the airborne emissions we investigated. We carried out a systematic evaluation of the possible reasons for this deviation. This analysis shows that the sector‐specific effects (aggregation of sectors) and the quality of primary data for emissions from national inventory reporting (NIR) are the main reasons for the deviations. As a rule, IO‐based LCI data sets seem to underestimate specific emissions while overestimating sector‐specific aspects.     

An Input‐Output Model of Extended Producer Responsibility

Under an extended producer responsibility (EPR) system, when a producer delivers a product to the market it must also pay a takeback fee, which is used to cover the costs of end‐of‐life disposal. EPR systems are currently used in Europe and beyond to manage a variety of products, including packaging and used tires. In this article we develop an input‐output (IO) model that is able to assess the impacts of an EPR system, and is based on the waste IO (WIO) model. The WIO model is itself a hybrid‐unit model extension of the Leontief model that is able to capture the substitution effect between recycled/recovered material/energy from waste treatment and their non‐waste cognates. The resulting EPRIO model, besides the conventional direct and indirect effects of the Leontief model and the substitution effects of the WIO model, is able to capture the opportunity costs of financing the EPR system, and additionally requires the specification of an alternative waste management policy, with its own opportunity costs. The impact of an EPR policy is thus the difference between the impacts of the reference EPR and the alternative waste treament policies. The resulting model is illustrated with a simple example of a used tire management EPR system.     

Combined Two‐Stage Xanthate Processes for the Treatment of Copper‐Containing Wastewater

Heavy metal removal is mainly conducted by adjusting the wastewater pH to form metal hydroxide precipitates. However, in recent years, the xanthate process with a high metal removal efficiency, attracted attention due to its use of sorption/desorption of heavy metals from aqueous solutions. In this study, two kinds of agricultural xanthates, insoluble peanut‐shell xanthate (IPX) and insoluble starch xanthate (ISX), were used as sorbents to treat the copper‐containing wastewater (Cu concentration from 50 to 1,000 mg/L). The experimental results showed that the maximum Cu removal efficiency by IPX was 93.5 % in the case of high Cu concentrations, whereby 81.1 % of copper could rapidly be removed within one minute. Moreover, copper‐containing wastewater could also be treated by ISX over a wide range (50 to 1,000 mg/L) to a level that meets the Taiwan EPA's effluent regulations (3 mg/L) within 20 minutes. Whereas IPX had a maximum binding capacity for copper of 185 mg/g IPX, the capacity for ISX was 120 mg/g ISX. IPX is cheaper than ISX, and has the benefits of a rapid reaction and a high copper binding capacity, however, it exhibits a lower copper removal efficiency. A sequential IPX and ISX treatment (i.e., two‐stage xanthate processes) could therefore be an excellent alternative. The results obtained using the two‐stage xanthate process revealed an effective copper treatment. The effluent (C_e) was below 0.6 mg/L, compared to the influent (C₀) of 1,001 mg/L at pH = 4 and a dilution rate of 0.6 h^–1. Furthermore, the Cu‐ISX complex formed could meet the Taiwan TCLP regulations, and be classified as non‐hazardous waste. The xanthatilization of agricultural wastes offers a comprehensive strategy for solving both agricultural waste disposal and metal‐containing wastewater treatment problems.     

Life cycle sustainability assessment of autonomous heavy‐duty trucks

Connected and automated vehicles (CAVs) are emerging technologies expected to bring important environmental, social, and economic improvements in transportation systems. Given their implications in terms of air quality and sustainable and safer movement of goods, heavy‐duty trucks (HDTs), carrying the majority of U.S. freight, are considered an ideal domain for the application of CAV technology. An input–output (IO) model is developed based on the Eora database—a detailed IO database that consists of national IO tables, covering almost the entire global economy. Using the Eora‐based IO model, this study quantifies and assesses the environmental, economic, and social impacts of automated diesel and battery electric HDTs based on 20 macro‐level indicators. The life cycle sustainability performances of these HDTs are then compared to that of a conventional diesel HDT. The study finds an automated diesel HDT to cause 18% more fatalities than an automated electric HDT. The global warming potential (GWP) of automated diesel HDTs is estimated to be 4.7 thousand metric tons CO₂‐eq. higher than that of automated electric HDTs. The health impact costs resulting from an automated diesel HDT are two times higher than that of an automated electric HDT. Overall, the results also show that automation brings important improvements to the selected sustainability indicators of HDTs such as global warming potential, life cycle cost, GDP, decrease in import, and increase in income. The findings also show that there are significant trade‐offs particularly between mineral and fossil resource losses and environmental gains, which are likely to complicate decision‐making processes regarding the further development and commercialization of the technology.     

Life Cycle Assessment of Urban Wastewater Reclamation and Reuse Alternatives

Continuous population growth is causing increased water contamination. Uneven distribution of water resources and periodic droughts have forced governments to seek new water sources: reclaimed and desalinated water. Wastewater recovery is a tool for better management of the water resources that are diverted from the natural water cycle to the anthropic one. The main objective of this work is to assess the stages of operation of a Spanish Mediterranean wastewater treatment plant to identify the stages with the highest environmental impact, to establish the environmental loads associated with wastewater reuse, and to evaluate alternative final destinations for wastewater. Tertiary treatment does not represent a significant increment in the impact of the total treatment at the plant. The impact of reclaiming 1 cubic meter (m³) of wastewater represents 0.16 kilograms of carbon dioxide per cubic meter (kg CO₂/m³), compared to 0.83 kg CO₂/m³ associated with basic wastewater treatment (primary, secondary, and sludge treatment). From a comparison of the alternatives for wastewater final destination, we observe that replacing potable water means a freshwater savings of 1.1 m³, whereas replacing desalinated water means important energy savings, reflected in all of the indicators. To ensure the availability of potable water to all of the population—especially in areas where water is scarce—governments should promote reusing wastewater under safe conditions as much as possible.     

New Aspects of Microbial Nitrogen Transformations in the Context of Wastewater Treatment – A Review

Over the past few years, new technologies for nitrogen removal have been developed mainly because of the increasing financial costs of the traditional wastewater treatment technologies. Newly discovered pathways, like the anaerobic oxidation of ammonium (ANAMMOX), and uses for nitrogen removal technologies are under discussion. Processes and technologies such as: Partial nitrification; Single reactor systems for High Ammonium Removal Over Nitrite (SHARON); Anammox; Aerobic/anoxic deammonification; Oxygen Limited Autotrophic Nitrification‐Denitrification (OLAND); Completely Autotrophic Nitrogen Removal Over Nitrite (CANON); wetland based systems, all have a high potential for nitrogen removal. However, the pathways of nitrogen transformation processes are very complex. An understanding of how various environmental factors affect these processes and a sound knowledge of existing, worldwide experience pertaining to these novel technologies are the key if the nitrogen removal rates are to be improved and success is to be realized in full‐scale applications. This review describes the present knowledge of the new treatment technologies for wastewater with high nitrogen loads. Special emphasis is given to the influence of environmental factors and the reactor configuration on the nitrogen transformation process and microbial activity.     

Choice of Allocations and Constructs for Attributional or Consequential Life Cycle Assessment and Input‐Output Analysis

The divide between attributional and consequential research perspectives partly overlaps with the long‐standing methodological discussions in the life cycle assessment (LCA) and input‐output analysis (IO) research communities on the choice of techniques and models for dealing with situations of coproduction. The recent harmonization of LCA allocations and IO constructs revealed a more diverse set of coproduction models than had previously been understood. This increased flexibility and transparency in inventory modeling warrants a re‐evaluation of the treatment of coproduction in analyses with attributional and consequential perspectives. In the present article, the main types of coproductions situations and of coproduction models are reviewed, along with key desirable characteristics of attributional and consequential studies. A concordance analysis leads to clear recommendations, which call for important refinements to current guidelines for both LCA/IO practitioners and database developers. We notably challenge the simple association between, on the one hand, attributional LCA and partition allocation, and on the one hand, consequential LCA and substitution modeling.     

The ‘truck‐driver’ effect in leaf‐cutting ants: how individual load influences the walking speed of nest‐mates

The foraging behaviour of social insects is highly flexible because it depends on the interplay between individual and collective decisions. In ants that use foraging trails, high ant flow may entail traffic problems if different workers vary widely in their walking speed. Slow ants carrying extra‐large loads in the leaf‐cutting ant Atta cephalotes L. (Hymenoptera: Formicidae) are characterized as ‘highly‐laden’ ants, and their effect on delaying other laden ants is analyzed. Highly‐laden ants carry loads that are 100% larger and show a 50% greater load‐carrying capacity (i.e. load size/body size) than ‘ordinary‐laden’ ants. Field manipulations reveal that these slow ants carrying extra‐large loads can reduce the walking speed of the laden ants behind them by up to 50%. Moreover, the percentage of highly‐laden ants decreases at high ant flow. Because the delaying effect of highly‐laden ants on nest‐mates is enhanced at high traffic levels, these results suggest that load size might be adjusted to reduce the negative effect on the rate of foraging input to the colony. Several causes have been proposed to explain why leaf‐cutting ants cut and carry leaf fragments of sizes below their individual capacities. The avoidance of delay in laden nest‐mates is suggested as another novel factor related to traffic flow that also might affect load size selection The results of the presennt study illustrate how leaf‐cutting ants are able to reduce their individual carrying performance to maximize the overall colony performance.     

Triboelectric Nanogenerator for Sustainable Wastewater Treatment via a Self‐Powered Electrochemical Process

By harvesting the flowing kinetic energy of water using a rotating triboelectric nanogenerator (R‐TENG), this study demonstrates a self‐powered wastewater treatment system that simultaneously removes rhodamine B (RhB) and copper ions through an advanced electrochemical unit. With the electricity generated by R‐TENG, the removal efficiency (RE) of RhB can reach the vicinity of 100% within just 15 min when the initial concentration of RhB is around 100 ppm at optimized conditions. The removal efficiency of copper ions can reach 97.3% after 3 h within an initial concentration of 150 ppm at an optimized condition. Importantly, a better performance and higher treating efficiency are found by using the pulsed output of R‐TENG than those using direct current (DC) supply for pollutant removal when consuming equal amount of energy. The recovered copper layer on the cathode through R‐TENG is much denser, more uniform, and with smaller grain size (d = 20 nm) than those produced by DC process, which also hints at very promising applications of the R‐TENG in electroplating industry. In light of the merits such as easy portability, low cost, and effectiveness, this R‐TENG‐based self‐powered electrochemical system holds great potential in wastewater treatment and electroplating industry.     

Wastewater treatment by the HCR‐process

The increasing requirements in wastewater treatment have led to the development of new wastewater treatment processes based on the know‐how and experience in reaction and process engineering of the chemical industry. Due to their compactness, closed operation and high flexibility, these new processes show a large potential for process integration and significant cost reduction in particular for highly polluted industrial wastewaters. This paper discusses the HCR (h igh‐performance c ompact r eactor) ‐ process, developed at the Mass Transfer Laboratory of the Technical University of Clausthal within the last decade. This process has been realized in more than 30 technical applications with a volume loading of up to 70 kg COD/m³ d and an energy consumption of about 0.4 kWh per kg COD_elim.     

Environmental Evaluation of Different Treatment Processes for Sludge from Urban Wastewater Treatments: Anaerobic Digestion versus Thermal Processes (10 pp)

Background, Aims and Scope Huge amounts of sewage sludge, that need to be handled, are generated all around the world from wastewater treatment plants and its management in an economically and environmentally acceptable way has become a matter of increasing importance during the last few years. In this paper, we make use of Life Cycle Assessment (LCA) to compare biological and thermal processes, that is to say, anaerobic digestion versus pyrolysis and incineration. This paper will complete the analysis performed in a wastewater treatment plant, where sludge post-treatment was identified as one of the main contributors to the environmental impact on the global system. Methods LCA is a tool for evaluating the environmental performance of goods as well as processes or services (collectively termed products). ISO 14040 defines LCA as a compilation and evaluation of the inputs, outputs and the potential environmental impacts of a system throughout its life cycle: from the production of raw materials to the disposal of the waste generated. In this study, data relating to the actual scenario from an existent wastewater treatment plant were considered. Both bibliographical and real data from existing facilities were used for the thermal processes proposed. The Centre of Environmental Science (CML) of Leiden University's methodology was chosen to quantify the potential environmental impacts associated with the different scenarios under study. The software SimaPro 5.1 was used and CML factors (updated in 2002) were chosen for characterisation and normalisation stages. Results and Discussion In a previous study, sewage sludge was found to be a critical point in the environmental performance of a wastewater treatment plant, so different alternatives have been tackled here. Anaerobic digestion followed by land application of pasty sludge comprises both energy recovery and nutrient recovery. Other thermal processes, such as incineration or pyrolysis, allow energy recovery (both electrical and thermal) and, although nutrients are lost, new co-products are produced (tar and char at pyrolysis). Here, the most adverse case (that is to say, the total amount of heavy metals is supposed to be released from the sludge and reach the environment) was applied to consider the most negative impact due to sludge spreading in agricultural soils; so more research is required in order to establish the precise amount of heavy metals that is effectively uptaken by the plants and crops as well as the amount that is transferred to another phase as a leachate. Thermal processes are presented here as a good option to recover energy from the sludge; although the value of nutrients is lost. Tar and char, co-products from pyrolysis, are good examples that were evaluated here, recycling of bottom ashes from sludge incineration or manufacture of ceramic materials from sludge are other options to be studied in the near future. Conclusion During the last few years, several opinions have been declared in favour of land application, incineration or pyrolysis, but many voices have also spoken out against each one. To obtain general conclusions for an overall comparison of different post-treatment of urban wastewater sludge is not easy as there are many contradictory aspects. The most effective utilisation of sewage sludge implies both energy and material re-use, but this is not always possible. Nevertheless, we think that land application of digested sludge is an acceptable option, probably not the best but at least a good one, for sludge treatment as long as efforts are focused on the minimisation of heavy metal content in the final cake.     

Effects of Using Heterogeneous Prices on the Allocation of Impacts from Electricity Use: A Mixed‐Unit Input‐Output Approach

Economic input‐output life cycle assessment (IO‐LCA) models allow for quick estimation of economy‐wide greenhouse gas (GHG) emissions associated with goods and services. IO‐LCA models are usually built using economic accounts and differ from most process‐based models in their use of economic transactions, rather than physical flows, as the drivers of supply‐chain GHG emissions. GHG emissions estimates associated with input supply chains are influenced by the price paid by consumers when the relative prices between individual consumers are different. We investigate the significance of the allocation of GHG emissions based on monetary versus physical units by carrying out a case study of the U.S. electricity sector. We create parallel monetary and mixed‐unit IO‐LCA models using the 2007 Benchmark Accounts of the U.S. economy and sector specific prices for different end users of electricity. This approach is well suited for electricity generation because electricity consumption contributes a significant share of emissions for most processes, and the range of prices paid by electricity consumers allows us to explore the effects of price on allocation of emissions. We find that, in general, monetary input‐output models assign fewer emissions per kilowatt to electricity used by industrial sectors than to electricity used by households and service sectors, attributable to the relatively higher prices paid by households and service sectors. This fact introduces a challenging question of what is the best basis for allocating the emissions from electricity generation given the different uses of electricity by consumers and the wide variability of electricity pricing.     

Modeling of the evolution of bacterial densities in an eutrophic ecosystem (sewage lagoons)

The process of wastewater treatment was studied by modeling the relationships between physical, chemical, and biological (bacteria, phytoplankton, zooplankton) components of the sewage treatment lagoons of an urban wastewater center, based upon a two-year sampling program. The models of interactions between variables were tested by path analysis. The path coefficients were computed from the results of ridge regression, instead of linear multiple regression. The results show that fecal coliforms were effectively controlled by the environmental variables included in the model, which have a cyclic seasonal behavior. This control grew stronger with distance from the input (R ²=0.71) to the output (R ²=0.88) of the treatment plant, resulting in effective elimination of most enteric bacteria. Simultaneously, the ecosystem's community of aerobic heterotrophic bacteria became more independent from the model's predictive variables, with increased distance from the sewage input, thus demonstrating its maturation as an autonomous community in the lagoon ecosystem. Consequences of modeling are discussed, with respect to the understanding of biological wastewater treatment mechanisms and ecosystem dynamics and to plant management.     

Occurrence and reduction of human viruses,F‐specific RNA coliphage genogroups and microbial indicators at a full‐scale wastewater treatment plant in Japan

Aims

To evaluate and compare the reductions of human viruses and F‐specific coliphages in a full‐scale wastewater treatment plant based on the quantitative PCR (qPCR) and plate count assays.

Methods and Results

A total of 24 water samples were collected from four locations at the plant, and the relative abundance of human viruses and F‐RNA phage genogroups were determined by qPCR. Of the 10 types of viruses tested, enteric adenoviruses were the most prevalent in both influent and effluent wastewater samples. Of the different treatment steps, the activated sludge process was most effective in reducing the microbial loads. Viruses and F‐RNA phages showed variable reduction; among them, GI and GIII F‐RNA phages showed the lowest and the highest reduction, respectively.

Conclusions

Ten types of viruses were present in wastewater that is discharged into public water bodies after treatment. The variability in reduction for the different virus types demonstrates that selection of adequate viral indicators is important for evaluating the efficacy of wastewater treatment and ensuring the water safety.

Significance and Impact of the Study

Our comprehensive analyses of the occurrence and reduction of viruses and indicators can contribute to the future establishment of appropriate viral indicators to evaluate the efficacy of wastewater treatment.     

An Australian Multi‐Regional Waste Supply‐Use Framework

The production of waste creates both direct and indirect environmental impacts. A range of strategies are available to reduce the generation of waste by industry and households, and to select waste treatment approaches that minimize environmental harm. However, evaluating these strategies requires reliable and detailed data on waste production and treatment. Unfortunately, published Australian waste data are typically highly aggregated, published by a variety of entities in different formats, and do not form a complete time‐series. We demonstrate a technique for constructing a multi‐regional waste supply‐use (MRWSU) framework for Australia using information from numerous waste data sources. This is the first MRWSU framework to be constructed (to the authors' knowledge) and the first sub‐national waste input‐output framework to be constructed for Australia. We construct the framework using the Industrial Ecology Virtual Laboratory (IELab), a cloud‐hosted computational platform for building Australian multi‐regional input‐output tables. The structure of the framework complies with the System of Environmental‐Economic Accounting (SEEA). We demonstrate the use of the MRWSU framework by calculating waste footprints that enumerate the full supply chain waste production for Australian consumers.     

An Approach to Integrating Environmental Considerations Within Managerial Decision‐Making

Recent environmental trends, including (1) an expansion of existing command and control directives, (2) the introduction of market‐based policy instruments, and (3) the adoption of extended producer responsibility, have created a need for new tools to help managerial decision‐making. To address this need, we develop a nonlinear mathematical programming model from a profit‐maximizing firm's perspective, which can be tailored as a decision‐support tool for firms facing environmental goals and constraints. We typify our approach using the specific context of diesel engine manufacturing and remanufacturing. Our model constructs are based on detailed interviews with top managers from two leading competitors in the medium and heavy‐duty diesel engine industry. The approach allows the incorporation of traditional operations‐planning considerations—in particular, capacity, production, and inventory—together with environmental considerations that range from product design through production to product end of life. A current hurdle to implementing such a model is the availability of input data. We therefore highlight the need not only to involve all departments within businesses but also for industrial ecologists and business managers to work together to implement meaningful decision models that are based on accurate and timely data and can have positive economic and environmental impact.     

Disaggregating the Power Generation Sector for Input‐Output Life Cycle Assessment

The electric power industry plays a critical role in the economy and the environment, and it is important to examine the economic, environmental, and policy implications of current and future power generation scenarios. However, the tools that exist to perform the life cycle assessments are either too complex or too aggregated to be useful for these types of activities. In this work, we build upon the framework of existing input‐output (I‐O) models by adding data about the electric power industry and disaggregating this single sector into additional sectors, each representing a specific portion of electric power industry operations. For each of these disaggregated sectors, we create a process‐specific supply chain and a set of emission factors that allow calculation of the environmental effects of that sector's output. This new model allows a much better fit for scenarios requiring more specificity than is possible with the current I‐O model.     

Modeling of an Aerobic Membrane Bioreactor for Wastewater Treatment

The goal of this work is to develop a mathematical model to describe a continuous aerobic membrane bioreactor (MBR) for the treatment of different kinds of wastewater. Firstly, the experimental setup and the materials and methods to obtain data for the model verification are described. Secondly, a black box model is developed and verified for size containing wastewater. The model calculates output streams and concentrations from input streams and compositions using distribution coefficients. These coefficients are derived from experimental data. In a third step, two shortcut models of different complexity are developed. Both shortcut models use the black box balancing as a basis. However, the component balances for carbon and oxygen are no longer modeled by constant distribution coefficients. The basic shortcut model introduces Monod kinetics to modify the carbon balance. The enhanced shortcut model introduces transport laws for dissolved oxygen supply and combines the Monod kinetics with an additional term for oxygen limitation to model biological growth. The models show an increasing degree of agreement.     

Early‐stage sustainability assessment of biotechnological processes: A case study of citric acid production

Sustainability assessment using a life‐cycle approach is indispensable to contemporary bioprocess development. This assessment is particularly important for early‐stage bioprocess development. As early‐stage investigations of bioprocesses involve the evaluation of their ecological and socioeconomic effects, they can be adjusted more effectively and improved towards sustainability, thereby reducing environmental risk and production costs. Early‐stage sustainability assessment is an important precautionary practice and, despite limited data, a unique opportunity to determine the primary impacts of bioprocess development. To this end, a simple and robust method was applied based on the standardized life‐cycle sustainability assessment methodology and commercially available datasets. In our study, we elaborated on the yeast‐based citric acid production process with Yarrowia lipolytica assessing 11 different substrates in different process modes. The focus of our analysis comprised both cultivation and down‐stream processing. According to our results, the repeated batch raw glycerol based bioprocess alternative showed the best environmental performance. The second‐ and third‐best options were also glycerol‐based. The least sustainable processes were those using molasses, chemically produced ethanol, and soy bean oil. The aggregated results of environmental, economic, and social impacts display waste frying oil as the best‐ranked alternative. The bioprocess with sunflower oil in the batch mode ranked second. The least favorable alternatives were the chemically produced ethanol‐, soy oil‐, refined glycerol‐, and molasses‐based citric acid production processes. The scenario analysis demonstrated that the environmental impact of nutrients and wastewater treatment is negligible, but energy demand of cultivation and down‐stream processing dominated the production process. However, without energy demand the omission of neutralizers almost halves the total impact, and neglecting pasteurization also considerably decreases the environmental impact.