A systematic methodology for the robust quantification of energy efficiency at wastewater treatment plants featuring Data Envelopment Analysis

Sustainable efficiency in cities in China-An interaction model among water, energy, and industry

With the inclusion of "Building Inclusive, safe, Resilient and Sustainable Cities and human Settlements" (SDG11) in the United Nations Sustainable Development Goals (SDGS), the movement to promote sustainable development from an urban perspective is growing globally. Many studies examine urban sustainability efficiency from multiple dimensions, but scant attention targets the interaction among various dimensions. This research combines the water-energy-industry subsystem to evaluate the sustainable development performance of 29 provinces in China from 2018 to 2020. The results show that 1) a water system plays an important role in promoting a city's overall sustainable performance. 2) Urban sustainable efficiency has the characteristics of low value aggregation and high value dispersion in space. 3) Regional and sub-system sustainability efficiencies exhibit clear heterogeneity. 4) Rainfall improves the sustainable efficiency of cities, mainly through water systems. 5) The coupling between water and industrial subsystems is better than that between energy and industrial subsystems, and the coupling between the central region subsystem is the best. This paper offers a new perspective for understanding the current state of sustainability in China's provinces and provides more specific suggestions for improving regional sustainability efficiency in the future.

Energy efficiency in wastewater treatment plants: A framework for benchmarking method selection and application

Utilities produce and store vast amount of data related to urban wastewater management. Not yet fully exploited, proper data analysis would provide relevant process information and represents a great opportunity to improve the process performance. In the last years, several statistical tools and benchmarking methods that can extract useful information from data have been described to analyse wastewater treatment plant (WWTP) energy efficiency. Improving energy efficiency at WWTPs is however a complex task which involves several actors (both internal and external to the water utility), requires an exchange of different types of information which can be analysed by a broad selection of methods. Benchmarking method therefore must not only be selected based on whether they provide a clear identification of inefficient processes; it must also match the available data and the skills of those performing the assessment and objectives of stakeholders interpreting the results. Here, we have identified the requirements of the most common benchmarking methods in terms of data, resources, complexity of use, and information provided. To do that, inefficiency is decomposed so that the analyst, considering the objective of the study and the available data, can link each element to the appropriate method for quantification and benchmarking, and relate inefficiency components with root-causes in wastewater treatment. Finally, a framework for selecting the most suitable benchmarking method to improve energy efficiency in WWTPs is proposed to assist water sector stakeholders. By offering guidelines on how integrates and links data, methods and actors in the water sector, the outcomes of this article are expected to move WWTPs towards increasing energy efficiency.

A comprehensive assessment of energy efficiency of wastewater treatment plants: An efficiency analysis tree approach

Wastewater treatment plants (WWTPs) are energy intensive facilities. Controlling energy use in WWTPs could bring substantial benefits to people and environment. Understanding how energy efficient the wastewater treatment process is and what drives efficiency would allow treating wastewater in a more sustainable way. In this study, we employed the efficiency analysis trees approach, that combines machine learning and linear programming techniques, to estimate energy efficiency of wastewater treatment process. The findings indicated that considerable energy inefficiency among WWTPs in Chile existed. The mean energy efficiency was 0.287 suggesting that energy use should cut reduce by 71.3 % to treat the same volume of wastewater. This was equivalent to a reduction in energy use by 0.40 kWh/m³ on average. Moreover, only 4 out of 203 assessed WWTPs (1.97 %) were identified as energy efficient. It was also found that the age of treatment plant and type of secondary technology played an important role in explaining energy efficiency variations among WWTPs.

Comprehensive efficiency evaluation of wastewater treatment plants in northeast Qinghai-Tibet Plateau using slack-based data envelopment analysis

Comprehensive efficiency analysis of wastewater treatment plants (WWPTs) in the alpine region with harsh environment and poor techniques as well as managing experience could provide targeted and effective improvement evidences for local wastewater treatment industry and help to improve the water quality of downstream reaches. In this paper, slack-based data envelopment analysis (SBM-DEA) was adopted to assess the operating efficiencies of WWPTs in northeast Qinghai-Tibet Plateau (QTP). Results showed that the average efficiency score for all WWPTs was 0.608, and 32.5% of WWPTs were efficient. Some WWPTs had large improvement potentials in operating costs and pollutant removal rates. Lowering expenditures and promoting facility construction for WWPTs to overcome the climate difficulties and improve management level was necessary according to their improvement potentials. In addition, the relative importance of the quantitative influential factors to efficiencies scores calculated by random forest regression (RFR) indicated that design capacity and temperature were important quantitative factors affecting the performance of WWPTs. Furthermore, geographical location and design capacity also had significant influence on the comprehensive efficiency of WWPTs verified by Kruskal-Wallis test. Our results highlight the importance of facilities upgrading, scientific management for WWPTs. And the relative improvement suggestions on overcoming the high and cold environment should also be considered for the efficient operations of WWTPs as well as the protection the aquatic environment.

Economic Assessment of Energy Consumption in Wastewater Treatment Plants: Applicability of Alternative Nature-Based Technologies in Portugal

Understanding how to address today’s global challenges is critical to improving corporate performance in terms of economic and environmental sustainability. In wastewater treatment systems, such an approach implies integrating efficient treatment technologies with aspects of the circular economy. In this business field, energy costs represent a large share of operating costs. This work discusses technological and management aspects leading to greater energy savings in Portuguese wastewater treatment companies. A mixed methodology, involving qualitative and quantitative aspects, for collecting and analysing data from wastewater treatment plants was used. The qualitative aspects consisted of a narrative analysis of the information available on reports and websites for 11 wastewater management companies in Portugal (e.g., technologies, treated wastewater volumes and operating costs) followed by a review of several international studies. The quantitative approach involved calculating the specific energy consumption (kWh/m3), energy operating costs (EUR/m3) and energy operating costs per population equivalent (EUR/inhabitants) using data from the literature and from Portuguese companies collected from the SABI database. The results suggested that the most environmentally and economically sustainable solution is algae-based technology which might allow a reduction in energy operating costs between 0.05–0.41 EUR/m3 and 15.4–180.8 EUR/inhabitants compared to activated sludge and other conventional methods. This technology, in addition to being financially advantageous, provides the ability to eliminate the carbon footprint and the valorisation of algae biomass, suggesting that this biotechnology is starting to position itself as a mandatory future solution in the wastewater treatment sector.

Water pollutant discharge permit allocation based on DEA and non-cooperative game theory

Against the background of the ecological civilization system reform in the new era, the appropriate allocation of water pollutant discharge permits is an important policy for controlling the amount of wastewater discharge. Traditional allocation methods have disadvantages, such as high additional costs, an unfair allocation scheme, and market distortion. In the present study, a fixed-cost allocation model based on data envelopment analysis (DEA) and the Nash non-cooperative game theory is employed to allocate water pollutant discharge permits of totally 31 provinces in China from 2008 to 2017. The allocation scheme considers environmental efficiency. The results demonstrate regional differences in the allocation of water pollutant discharge permits. The eastern region has abundant allocations. The northeastern and central regions have insufficient allocations. Besides, the western region has a significant shortage of allocations. It indicates the higher the utilization efficiency of the water pollutant discharge permits, the higher the region's sustainable development is. Based on the analysis, we propose guidelines for industrial wastewater discharge reduction.

Sustainable water and sanitation for all: Are we there yet?

The lack of access to water and sanitation services (WSS) of a considerable share of the world population has been challenging the international community for decades. The proposal of the Millennium Development Goals and, later on, the Sustainable Development Goals (SDGs) by the United Nations (UN) intended to act as a blueprint to achieve a more equitable future for all and, in the case of WSS, "Ensure the availability and sustainable management of water and sanitation for all" (SDG 6). However, the current global pandemic further emphasised the importance of WSS, given the increasing asymmetries faced by billions worldwide, and the gaps between high-income and low- and middle-income nations. For this reason, understanding whether low- and middle-income countries have been approximating towards or deviating from the SDG 6 is crucial to derive and communicate key information for the sake of improved public governance and political decision-making. In this paper, we extend a state-of-the-art methodology based on data envelopment analysis for assessing the convergence of the low- and middle-income UN Member States regarding the SDG 6 between 2016 and 2017. We find that, on average, not only did the Member States converge by decreasing the performance spread and the gap between the best and worst practice frontiers, but also the Level of water stress: freshwater withdrawal as a proportion of available freshwater resources was the indicator in which the majority exhibited the worst performances. In the end, we derive possible policy implications, which, as our results show, are aligned with the recent UN reports on the subject.

Energy Self-Sufficiency Aiming for Sustainable Wastewater Systems: Are All Options Being Explored?

In upcoming years, water demand is expected to boost worldwide, and with that, wastewater generation and the required energy for treatment. Provided that efficiency measures should be implemented at first instance, developments of renewable energy technologies are needed to improve sustainability at wastewater treatment plants (WWTPs). Based on theoretical analyses of literature data, this article presents a novel perspective of the role that hydropower could play in that energy framework. This research applied a new approach compared to previous studies, considering the introduction of sustainability aspects in the decision-making process, other than economic feasibility. With that aim, a broad search of real case studies was conducted, and suitable Key Performance Indicators based on the energy self-sufficiency concept were selected and applied to the identified cases. The findings suggest that there is not a rule of thumb to determine feasibility for hydropower installation and this technology might deserve more attention. This new perspective can help to raise awareness among policy makers, decision managers, or plant operators, of the possibilities hydropower could offer to the wastewater industry in the pathway towards more sustainable systems.

Evaluating the Eco-Efficiency of Wastewater Treatment Plants: Comparison of Optimistic and Pessimistic Approaches

The assessment of wastewater treatment plant (WWTP) performance has gained the interest of water utilities and water regulators. Eco-efficiency has been identified as a powerful indicator, as it integrates economic and environmental variables into a single index. Most previous studies have employed traditional data envelopment analysis (DEA) for the evaluation of WWTP eco-efficiency. However, DEA allows the selection of input and output weights for individual WWTPs for the calculation of eco-efficiency scores. To overcome this limitation, we employed the double-frontier and common set of weights methods to evaluate the eco-efficiency of a sample of 30 WWTPs in Spain. The WWTPs were ranked based on eco-efficiency scores derived under several scenarios including best- and worst-case scenarios; this approach to performance assessment is reliable and robust. Twenty-six of the 30 WWTPs were not classified as eco-efficient, even under the most favorable scenario, indicating that these facilities have substantial room for the reduction of costs and greenhouse gas emissions. The ranking of WWTPs varied according to the scenario used for evaluation, which has notable consequences when eco-efficiency scores are used for regulatory purposes. The findings of this study are relevant for water regulators and water utilities, as they demonstrate the importance of weight allocation for eco-efficiency score estimation.

Designing a robust index for WWTP energy efficiency: The ENERWATER water treatment energy index

The development and use of composite indexes has exploded in the last 15 years as a tool to summarise the large amount of information available nowadays. To ensure that composite indicators reflect faithfully the purpose of evaluation and are widely accepted and used, the users must understand the relationship between individual sub-indicators and the result (transparency) and the evaluation should not depend on weights, lack of information, etc. (robustness). It is proposed here for the first time a composite index to measure energy efficiency in a wastewater treatment plant, from the definition of the individual sub-indicators to the assignation of an energy label, easy to communicate to a broad public. Using as a demonstration real data from 44 wastewater treatment plants, the index robustness is tested and improved by uncertainty and sensitivity analysis results, finally achieving a robust algorithm which can be used by the large majority of wastewater treatment plants.

Application and Evaluation of Energy Conservation Technologies in Wastewater Treatment Plants

High energy consumption is an important issue affecting the operation and development of wastewater treatment plants (WWTPs). This paper seeks energy-saving opportunities from three aspects: energy application, process optimization, and performance evaluation. Moreover, effective energy-saving can be achieved from the perspective of energy supply and recovery by using green energy technologies, including wastewater and sludge energy recovery technologies. System optimization and control is used to reduce unnecessary energy consumption in operation. Reasonable indexes and methods can help researchers evaluate the application value of energy-saving technology. Some demonstration WWTPs even can achieve energy self-sufficiency by using these energy conservation technologies. Besides, this paper introduces the challenges faced by the wastewater treatment industry and some emerging energy-saving technologies. The work can give engineers some suggestions about reducing energy consumption from comprehensive perspectives.

Evaluation of anaerobic digestion post-treatment options using an integrated model-based approach

The objective of this paper is to present the main results of an engineering-research project dealing with model-based evaluation of waste streams treatment from a biotech company. This has been extensively done in domestic treatment systems, but is equally important, and with different challenges in industrial wastewater treatment. A new set of biological (activated sludge, anaerobic digestion), physicochemical (aqueous phase, precipitation, mass transfer) process models and model interfaces are required to describe removal of organics in an upflow anaerobic sludge blanket (UASB) reactor plus either traditional nitrification/denitrification (A₁) or partial nitritation (PN)/anammox (ANX) (A₂) processes. Model-based analysis shows that option A₁ requires a decrease in digestion energy recovery (E_recovery) in order to have enough organic substrate for subsequent post NO₃ reduction treatment (95 kWh.kg N^-1). In contrast, A₂ in an aerobic granular sludge reactor allows for higher UASB conversion since N removal is carried out autotrophically. The study also reveals that the addition of an aerated pre-treatment unit prior to the PN/ANX (A₂) reactor promotes COD and H₂S oxidation, CO₂ and CH₄ stripping, a pH increase (up to 8.5) and a reduction of the risk of intra-granular precipitation as well as sulfide inhibition. Simulations indicate clear differences regarding the microbial distribution/abundance within the biofilm in A₂ when comparing the two operational modes. Final results show the effects of different loading and operational conditions; dissolved oxygen (DO), Total Suspended Solids (TSS_op), energy recovery (E_recovery); on the overall process performance; N removal, aeration energy (E_aeration), net energy production (E_recovery); using response surfaces, highlighting the need of integrated approaches to avoid sub-optimal outcomes. The study shows the benefits of virtual plant simulation and demonstrates the potential of model-based evaluation when process engineers in industry have to decide between competing options.