Water-Energy-Carbon Nexus: Greenhouse Gas Emissions from Integrated Urban Drainage Systems in China

Water quality prediction and carbon reduction mechanisms in wastewater treatment in Northwest cities using Random Forest Regression model

With the accelerated urbanization and economic development in Northwest China, the efficiency of urban wastewater treatment and the importance of water quality management have become increasingly significant. This work aims to explore urban wastewater treatment and carbon reduction mechanisms in Northwest China to alleviate water resource pressure. By utilizing online monitoring data from pilot systems, it conducts an in-depth analysis of the impacts of different wastewater treatment processes on water quality parameters. This work pays particular attention to their impact on key indicators such as Chemical Oxygen Demand (COD), NH4+-N, Total Phosphorus (TP), and Total Nitrogen (TN), and the application of predictive models. The work first establishes a Random Forest Regression (RFR) model. The RFR algorithm integrates Bagging ensemble learning and random subspace theory to construct multiple decision trees and aggregate their predictions, thereby enhancing the model's prediction accuracy and stability. Using bootstrap sampling, the RFR model generates multiple training subsets from the original data and randomly selects subsets of variables to construct regression trees. Its performance in predicting various water quality indicators is then evaluated. The results show that the RFR model exhibits excellent performance, achieving high levels of prediction accuracy and stability for all indicators. For example, the R2 for COD prediction is 0.99954, while the R2 values for NH4+-N, TP, and TN predictions reach 0.99989. Compared to five other models, the RFR model demonstrates the best performance across all water quality indicator predictions. This work provides critical support for optimizing wastewater treatment technologies and developing water resource management policies. These findings also offer essential theoretical and empirical insights for the future improvement of urban wastewater treatment technologies and water resource management decision-making.

Investigation of the interactions and influencing factors of the Water-Land-Energy-Carbon system in the Yellow River Basin

The survival and advancement of human society are fundamentally dependent on the availability and sustainable management of water, land, and energy resources. The development and utilisation of various energy sources and a considerable number of natural resources lead to carbon emissions. A complex interplay exists between water, land, energy, and carbon, and their correlation lies at the core of the regional "natural-social-economic" system, which is crucial for human existence and advancement. Despite its importance, research on the water-land-energy‑carbon (WLEC) nexus is limited. In this study, we employed an innovative combination of the comprehensive assessment index, coupled coordination degree, panel vector autoregressive, and random forest models to investigate the spatiotemporal evolution, internal dynamic interactions, and external influencing factors of the WLEC system in the Yellow River Basin (YRB) from 2007 to 2021. The findings revealed that the degree of coupled coordination in the WLEC system of the YRB exhibited an overall steady upward trend. The spatial agglomeration effect was continuously enhanced, and regional disparities increased. Complex interaction mechanisms exist within the water, land, energy, and carbon subsystems in the YRB. Population size, land relief, and sunshine are the prevailing factors influencing the degree of coupling coordination in the WLEC. Addressing the trade-off relationship among the subsystems of the WLEC system is a key aspect of optimising its correlation relationship. This study provides a scientific basis and relevant suggestions for achieving the Double-Carbon Goal, promoting ecological protection and high-quality development in the YRB.

Carbon metabolism mechanisms and evolution characteristics analysis of the food-water-energy nexus system under blue-green infrastructure changes

Food, water, and energy comprise a complex system (FWE nexus) that generates much carbon emissions during operation. At the same time, urban blue-green infrastructure (BGI) has a critical carbon sequestration function. This paper combines the functions of the FWE nexus and BGI and uses ecological network analysis (ENA) and the Markov model to measure the carbon metabolism (CM) mechanisms and evolutionary characteristics of BGI and FWE nexus (BGI-FWE nexus) complex systems. The results show that Guangzhou has high carbon emissions, and Zhaoqing and Huizhou have high carbon sequestration. Resident land and industrial and transportation land transfers to different land uses are more likely to produce positive carbon flows, while BGI transfers to other types are more likely to produce negative carbon flows. The study of CM mechanisms reveals a high proportion of competition relationships and a low proportion of mutualism relationships. The ecological utility index (EUI) tends to fall initially and then increase, peaking at 0.84 in 2015-2020, the highest value for the study period. The CM network has less system robustness (SR) and is in an unsustainable state of high redundancy and low efficiency. The mechanism evolution characterization study's findings show a decreased likelihood of remaining original and less stability in the spatial transfer probability matrices of EUI and SR. In this study, we constructed a BGI-FWE nexus research framework based on the different CM functions of BGI and FWE nexus. The research framework contributes to the realization of carbon reduction in the FWE nexus system and is essential for the planning and management of urban BGI.

Land use and urbanization indirectly control riverine CH4 and CO2 emissions by altering nutrient input

Urban rivers are recognized as significant sources of methane (CH4) and carbon dioxide (CO2) emissions. Despite this, the influence of land use and urbanization on carbon emissions across rural-urban rivers at the watershed scale has been insufficiently explored. This study utilized in-situ surveys of the Liao River in northern China to investigate the spatial and temporal variations of CH4 and CO2 emissions and their relationship with urbanization and its potential controlling factors. The findings revealed that CH4 emissions peaked in fall, whereas CO2 emissions were highest in summer. The average fluxes of CH4 and CO2 at the water-gas interface were 1387.22 ± 2474.98 µmol·m-2·d-1 and 52.78 ± 54.44 mmol·m-2·d-1, respectively. Water quality parameters accounted for 80.49 % of the total variation in CH4 and CO2 concentrations and fluxes. Structural equation modeling indicated that TN, TP, DTC, and conductivity had direct effects on riverine CH4 and CO2 emissions, with standardized direct effects of 0.50 and 0.49, respectively. Nutrient input emerged as the primary driver, increasing CH4 and CO2 concentrations and fluxes, particularly in urban-adjacent river sections likely receiving higher nutrient loads. This study underscores that land use and urbanization indirectly influence riverine CH4 and CO2 emissions by modifying nutrient inputs. Effective land use management and nutrient input control are recommended strategies to mitigate riverine CH4 and CO2 emissions.

Analyzing the variation of greenhouse gas emissions from typical municipal wastewater treatment plants in Beijing during 2007-2021

With the proposal of dual carbon goals and stringent effluent standards, the path of mitigating greenhouse gas (GHG) emissions from wastewater treatment plants (WWTPs) has gained significant research attention. Here, we evaluate the impact of season, elevated standards, operating parameters, and using clean energy on GHG emissions from 8 typical WWTPs in Beijing based on 180 monthly monitoring data. Coupled with the increasing demand for wastewater treatment and 77% more chemical oxygen demand being removed in 2017, total GHG emissions from 5 WWTPs increased by 89% compared to the status quo in 2007, and after energy structure reform total GHG emissions decreased by 17% in 2021. Scenario analysis reveals that energy recovery and clean energy utilization provide 64% and 48% mitigation potential by 2050, respectively. We argue stricter effluent standard leads to GHG emissions growth in WWTPs; meanwhile, process optimization, proper temperature and targeted policies at WWTPs can reduce GHG emissions.

Tofu wastewater as a carbon source flowing into municipal wastewater treatment plants for reductions of costs and greenhouse gas emissions

Wastewater treatment processes significantly contribute to greenhouse gas (GHG) emissions. Municipal wastewater treatment also faces challenges related to low strength and a low carbon-to-nitrogen (C/N) ratio. This study investigates the high-carbon tofu wastewater flowing into municipal sewers for co-treatment at a wastewater treatment plant (WWTP) directly, with the goal of enhancing nitrogen removal and reduce GHG emissions. Within the framework of a circular economy for wastewater treatment, tofu wastewater serves as an external carbon source for sustainable solutions. The concentrated tofu wastewater had an average chemical oxygen demand (CODCr) of 21,894 ± 11,485 mg/L, total nitrogen (TN) of 591.8 ± 238.2 mg/L, and a C/N ratio of 36.9 ± 7.4. The denitrification rate reached 3.05 mg NO3--N/(g MLVSS·h). Therefore, tofu wastewater is a suitable alternative carbon source. A full-scale WWTP with a capacity of 20,000 m³/day was monitored from 2017 to 2022 to evaluate the co-treatment effects of municipal wastewater and tofu wastewater. The results showed an increase in 53.3% in the average CODCr concentration of the influent wastewater, while the total nitrogen and total phosphorus removal efficiencies were enhanced to 75.8% and 95.2%, respectively. In addition, the study quantified GHG emissions from tofu wastewater and municipal wastewater treatment. Compared to separate treatment processes, the co-treatment reduced GHG emissions by 337.9 t CO2-eq., approximately 15.8% of the total emissions of WWTP, and achieved a cost saving of 7-10% of the total operational costs. These findings demonstrate the environmental and economic advantages of integrating high-carbon industrial wastewater treatment directly into wastewater treatment plants.

Strategic carbon emission assessment in sludge treatment: A dynamic tool for low-carbon transformation

The carbon-neutral target presents a significant challenge for the sewage sludge treatment and disposal (SSTD) industry, necessitating strategic planning for a low-carbon transition. However, flexible and comprehensive carbon emission analysis tools to support this goal remain lacking. This study presents a carbon emission analysis tool to evaluate the carbon emission characteristics and future mitigation potentials of SSTD. The tool integrates life cycle inventory (LCI) modeling-based analysis, sensitivity analysis, regression analysis, and scenario analysis. Carbon emissions are dynamically calculated based on sludge properties, technological level, and industry external parameters, providing a foundation for adaptable evaluation tailored to local conditions. The framework considers the potential effects of multi-parameter and multi-aspect changes in scene design, both within and outside the industry, to achieve dynamic and comprehensive simulations. A case study conducted in Wuhan, China, demonstrated the usability and application processes of the framework. The results indicated that carbon emissions from SSTD are projected to more than double from 2021 to 2060 without interventions. Among the mitigation measures, energy and chemical savings would yield the largest reduction potential, followed by the technical layout adjustment and the promotion of energy efficiency. Operational optimization in the sludge industry and outside the industry would contribute the least. With all mitigation measures applied, emissions could decrease to -82.91 kt CO2-eq in 2060, equivalent to 13.03% compensation for emissions from the sewage treatment line. Among all the processes, incineration routes are recommended due to their current and future low carbon emissions. The cooperative resource route of anaerobic digestion and land use also shows promise as it progressively demonstrates superior performance with increasing organic matter and nutrient content of sludge. Critical factors, sub-processes, and emission types for different routes were identified and can be optimized accordingly. The developed method demonstrates sufficient flexibility to be applied to other cities and larger-scale regions, thereby offering technical and strategic support for SSTD towards carbon-neutral operation.

Advancing irrigation management: integrating technology and sustainability to address global food security

Irrigation management is essential for addressing global food security challenges under changing climate. This review discusses the integration of advanced irrigation technologies and their roles in enhancing water use efficiency and managing energy demands within agricultural systems. High-efficiency irrigation systems, such as drip and sprinkler systems, have significant potential to reduce water use and increase crop yields. However, their adoption varies worldwide, and the efficiency of existing irrigation practices often remains inadequate, resulting in substantial water losses due to outdated management practices. Emerging technologies and innovative irrigation strategies, including precision agriculture and advanced crop models, provide promising pathways for improving irrigation efficiency. Nonetheless, the widespread integration of these technologies is hindered by high costs, the need for technical expertise, and challenges in adapting existing agricultural systems to new methodologies. Irrigation systems can have substantial energy requirements, particularly those dependent on groundwater. The exploration of the water-environment-energy-food (WEEF) nexus illustrates the importance of a balanced approach to resource management, which is crucial for achieving sustainable agricultural outcomes. Future research should include lowering barriers to technology adoption, enhancing data utilization for precision irrigation, promoting integrated management strategies within the WEEF framework, and strengthening policy support for sustainable practices. This review proposes a multidisciplinary approach to irrigation management that includes technological innovation, strategic policy development, and global cooperation to secure sustainable agricultural practices and ensure global food supply resilience in the face of climate change.

Deciphering carbon emissions in urban sewer networks: Bridging urban sewer networks with city-wide environmental dynamics

As urbanization accelerates, understanding and managing carbon emissions from urban sewer networks have become crucial for sustainable urban water cycles. This review examines the factors influencing greenhouse gas (GHG) emissions within urban sewage systems, analyzing the complex effects between water quality, hydrodynamics, and sewer infrastructure on GHG production and emission processes. It reveals significant spatiotemporal heterogeneity in GHG emissions, particularly under long-term scenarios where flow rates and temperatures exhibit strong impacts and correlations. Given the presence of fugitive and dissolved potential GHGs, standardized monitoring and accounting methods are deemed essential. Advanced modeling techniques emerge as crucial tools for large-scale carbon emission prediction and management. The review identifies that traditional definitions and computational frameworks for carbon emission boundaries fail to fully consider the inherent heterogeneity of sewers and the dynamic changes and impacts of multi-source pollution within the sewer system during the urban water cycle. This includes irregular fugitive emissions, the influence of stormwater systems, climate change, geographical features, sewer design, and the impacts of food waste and antibiotics. Key strategies for emission management are discussed, focusing on the need for careful consideration of approaches that might inadvertently increase global emissions, such as ventilation, chemical treatments, and water management practices. The review advocates for an overarching strategy that encompasses a holistic view of carbon emissions, stressing the importance of refined emission boundary definitions, novel accounting practices, and comprehensive management schemes in line with the water treatment sector's move towards carbon neutrality. It champions the adoption of interdisciplinary, technologically advanced solutions to mitigate pollution and reduce carbon emissions, emphasizing the importance of integrating cross-scale issues and other environmentally friendly measures in future research directions.

A simulation and risk assessment framework for water-energy-environment nexus: A case study in the city cluster along the middle reach of the Yangtze River, China

In the Anthropocene, there is a strong interlinkage among water, energy, and the environment. The water-energy-environment nexus (WEEN) has been vigorously advocated as an emerging development paradigm and a global research agenda. Based on the nexus concept, a framework for the WEEN complex system simulation and risk assessment is developed. The three metropolitan areas of the city cluster along the middle reaches of the Yangtze River (CCMRYR) are taken as the objects. Regional policies are combined with generic shared socio-economic pathways (SSPs) to form a localized SSPs suitable for the research region. The dynamic simulation of the WEEN complex system and the risk analysis are carried out with the combination of system dynamics models and copula functions. Results show that: There are obvious differences in water utilization, energy consumption, air pollutant emissions, and water pollutant emissions among the three metropolitan areas. The issue of high carbon intensity in the Wuhan Metropolitan Coordinating Region needs to be emphasized and solved from the perspective of optimizing the industrial structure. Adhering to current development patterns, there will be successive peaks in water utilization, energy consumption, and carbon emissions in Wuhan, Dongting Lake, and Poyang Lake Metropolitan Coordinating Region by 2030, leading to high synergy risks at the systemic level, with maximum values of 0.84, 0.85, 0.62, respectively. A development path based on conservation priorities indicates that future policymaking needs to prioritize a resource-saving and pollution-control development pattern directed by technological upgrading against the backdrop of scarce natural resource endowments. The localized SSPs are a beneficial extension that enriches the narrative of regional-scale SSPs. The evolutionary trajectories and risk assessments of WEEN complex systems under different localized SSPs provide a sweeping insight into the consequences of policy decisions, thus enabling policymakers to appraise policy rationality and implement appropriate corrective measures.

Modeling Indirect Greenhouse Gas Emissions Sources from Urban Wastewater Treatment Plants: Integrating Machine Learning Models to Compensate for Sparse Parameters with Abundant Observations

Electricity consumption and sludge yield (SY) are important indirect greenhouse gas (GHG) emission sources in wastewater treatment plants (WWTPs). Predicting these byproducts is crucial for tailoring technology-related policy decisions. However, it challenges balancing mass balance models and mechanistic models that respectively have limited intervariable nexus representation and excessive requirements on operational parameters. Herein, we propose integrating two machine learning models, namely, gradient boosting tree (GBT) and deep learning (DL), to precisely pointwise model electricity consumption intensity (ECI) and SY for WWTPs in China. Results indicate that GBT and DL are capable of mining massive data to compensate for the lack of available parameters, providing a comprehensive modeling focusing on operation conditions and designed parameters, respectively. The proposed model reveals that lower ECI and SY were associated with higher treated wastewater volumes, more lenient effluent standards, and newer equipment. Moreover, ECI and SY showed different patterns when influent biochemical oxygen demand is above or below 100 mg/L in the anaerobic-anoxic-oxic process. Therefore, managing ECI and SY requires quantifying the coupling relationships between biochemical reactions instead of isolating each variable. Furthermore, the proposed models demonstrate potential economic-related inequalities resulting from synergizing water pollution and GHG emissions management.