New multi-source waste co-incineration and clustering park operating model for small- and medium-sized city: A case study in China.

With improvements in urban waste management to promote sustainable development, an increasing number of waste types need to be sorted and treated separately. Due to the relatively low amount of waste generated in small- and medium-sized cities, separate treatment facilities for each waste type lack scale, waste is treated at a high cost and low efficiency. Therefore, industrial symbiosis principles are suggested to be used to guide collaborative waste treatment system of multi-source solid wastes, and co-incineration is the most commonly used technology. Most existing studies have focused on co-incineration of one certain waste type (such as sludge or medical waste) with municipal solid waste (MSW), but the systematic design and the comprehensive benefits on a whole city and park level have not been widely studied. Taking the actual operation of a multi-source waste co-incineration park in south-central China as an example, this study conducted a detailed analysis of the waste-energy-water metabolism process of MSW, sludge, food waste, and medical waste co-incineration. The environmental and economic benefits were evaluated and compared with the single decentralized waste treatment mode. The results showed that the multi-source waste co-incineration and clustering park operating model was comprehensively superior to the single treatment mode, greenhouse gases and human toxicity indicators were decreased by 11.87% and 295.74%, respectively, and the internal rate of return of the project was increased by 29.35%. This mainly benefits from the synergy of technical system and the economies of scale. Finally, this research proposed policy suggestions from systematic planning and design, technical route selection, and an innovative management mode in view of the potential challenges.

Cross-media transfer of nitrogen pollution in the fast-urbanized Greater Bay Area of China: Trends and essential control paths.

For urban agglomerations in the bay area, which concentrate multiple environmental elements and intense anthropogenic activities, comprehensive control of nitrogen pollution is particularly challenging due to diverse cross-media migration and transformation forms of nitrogen pollutants. Existing studies on urban nitrogen metabolism mainly focused on quantification of nitrogen flux, without systematic consideration of physiochemical changes of nitrogen between environmental media. This study conducted a dynamic simulation of nitrogen cross-media metabolism in urban agglomeration over 30 consecutive years, and recognized the types, quantities, and trends of cross-media transfer of nitrogen pollution as well as pollution control paths based on ecological network analysis and scenario analysis. Taking the Guangdong-Hong Kong-Macao Greater Bay Area as the case, results show that during its fast-urbanized stage in 1989-2018, more than 25% of the total nitrogen pollution emissions were transferred from other media. The higher degree of imbalance between the socioeconomic system and the soil in the nitrogen metabolic network emphasizes the increased pressure and necessity of pollution control of nitrogen in the solid state with urban development. Promoting fertilizer reduction and sludge land use are priority paths for collaborative control of cross-media nitrogen pollution. The study provides methods to systematically analyze the features of cross-media transfer of nitrogen pollution at the city level, and accordingly propose paths aiming at sustainable urban nitrogen management with multi-media integrity and synergy.

Industrial-environmental management in China's iron and steel industry under multiple objectives and uncertainties.

Industrial-environmental management is a multi-objective optimization problem plagued with multiple uncertainties. Most studies only optimize few objectives and often neglect these uncertainties. This study builds a 6-objective optimization problem to quantify energy conservation and emission reduction (ECER) potentials in China's iron and steel industry. First, uncertainties are simulated through 100,000-time random sampling, NSGA-II and the mean-effective objective mechanism are applied to calculate optimal solutions. Finally, a global sensitivity analysis is performed to classify uncertainty parameters based on their impacts on objectives' performance. Results show: (1) There exist significant discrepancies between objectives' performance under certainty and uncertainty. For example, the deterministic CO2 intensity is 1148 kg/t, which is 11.93% lower than its value under uncertainty. Therefore, neglecting uncertainty increases the risk of noncompliance with policy targets as they might be too strict; (2) Two critical uncertainty parameters (steel ratios and technology penetration rates) have the most severe impacts on objectives' performance, hence, reducing their fluctuation can minimize uncertainties when estimating ECER potentials; (3) By-product recycling and energy efficiency measures have good performance in all objectives, thus, should be prioritized. Moreover, from 77-strategies assessed, 11 are identified as key-strategies due to their large ECER effects, hence, should be strongly promoted.

Water-energy-nutrient nexus: Multi-sectoral metabolism analysis and technical path optimization for eco-towns.

The multi-sectoral metabolisms of substance and energy in rural areas are complex, whose optimization is the key to realize resource recycling and energy cascade utilization. Through Substance Flow Analysis (SFA), we establish a Multi-sectoral Metabolism Analysis Model specific to rural areas (MMAM-rural), and investigated the multi-sectoral metabolisms of Liujiadian Town in Beijing city. We simulate the water, energy and nutrients (carbon, nitrogen and phosphorus) metabolisms of a total of five sectors (water, waste management, livestock husbandry, forestry, and residential sectors), and identify the key metabolic flows significant for improving regional metabolism performance of Liujiadian Town. For further technical path optimization, we construct an index system made up of resource utilization efficiency, environmental burden of production and recycling efficiency, and adopt Scenario Analysis to evaluate the water-energy-nutrient metabolism performance under multiple technical scenarios different from disposals of agricultural waste, livestock and poultry manure, and domestic waste. Results show that, for agricultural wastes disposal, the combination scenario of edible fungi cultivation, anaerobic fermentation and aerobic composting is optimal. For livestock and poultry manure, all pig manure should be composted after anaerobic fermentation. For domestic wastes, food wastes require anaerobic fermentation and composting for optimization. Our study provides a model to evaluate metabolism performance of water-energy-nutrient nexus in rural areas, and raises solutions for optimization in the process of eco-town construction.

Quantitative analysis of the precise energy conservation and emission reduction path in China's iron and steel industry.

A precise energy conservation and emission reduction (ECER) path in industrial sector contains two aspects: applying effective ECER measures and focusing on processes with significant ECER potential. However, most studies have investigated the ECER effects of an individual measure or only evaluated industrial-level ECER potential. Therefore, the objective of this study is to find a precise ECER path in China's iron and steel industry through quantitative analysis methods. First, this article adopts scenario analysis to simulate situations where different ECER measures are adopted and designs calculation methods to quantitatively evaluate the ECER effects in each scenario in 2020 and 2025. Second, through analysis of the application of ECER measures to certain processes, we calculate the ECER potential of different individual processes in the iron and steel industry. In addition, the conservation supply curve method and the quadrant method are used to measure the level of advanced technology application. The results show that: (1) for four types of ECER measures, the limitation of production output measure is most effective, contributing to 6.98% and 12.50% decreases in total industrial energy consumption and pollutant emissions in 2020 and 2025; moreover, the contribution of the adjustment of scale structure measure is comparatively low. (2) The sintering and ironmaking processes have strong ECER potential in 2020, while the steel making process also has high ECER potential in 2025. (3) 21 technologies are divided into 4 quadrants based on energy, popularity, and economic performance. In addition, we provide some suggestions for future ECER policies. In sum, this article provides an in-depth example of determining a precise ECER path in an important industry.

Uncertainty analysis of industrial energy conservation management in China's iron and steel industry.

There are remarkable uncertainty factors in the industrial sector that enhance the difficulties of setting energy conservation strategies, such as the macro economy, industrial structures, and technical uncertainties. However, current studies simply predict the possible trends or conduct scenario analyses, and neglect uncertainty factors in the management of industrial energy conservation. In response, this article considers China's iron and steel industry as an example and builds the Industrial Energy Conservation Uncertainty Analysis (IECUA) model to recognize and analyze the uncertainty factors via a 200-thousand-time Latin hypercube sampling. Then, we propose some management measures, including setting energy conservation targets and energy conservation strategies. The results show that energy conservation targets should be more flexible than just the predicted values, to enhance the feasibility of their realization. In addition, energy conservation strategies are set at industrial and technique levels. On the one hand, such key parameters as production output, the coke/steel ratio, and pig iron/steel ratio, should be strictly controlled to avoid non-compliance risks. On the other hand, energy conservation technologies can be considered under four quadrants depending on their sensitivity to energy conservation and economic efficiency. Finally, some differentiated technologies promotion suggestions are made, such as economic stimulation, market entry standards and technical application guidelines.

Identification of urban drinking water supply patterns across 627 cities in China based on supervised and unsupervised statistical learning.

Urbanization, one of the predominant trends of the 21st century, places great stress on urban water supply networks. This paper aimed to identify the most important variables driving urban water supply patterns in China, a region which has seen rapid urban growth in the last few decades. In addition, a principal component analysis-informed urban water sustainability index was developed in order to benchmark cities. The research involved applying statistical learning and other analytical methods to 12 years of urban water supply data for 627 cities across China. The findings were as follows: (1) PCA showed that approximately 46.8% of variability in the data could be explained by two principal components. Component 1 (37.26%) was more closely associated with variables related to water supply and sale, supply pipelines, and water supply finance. C2 (9.51%) was clearly related to urban water prices and average per capita water use. (2) Random forest and XGBoost algorithms were effective in classifying cities according to their region, with model testing accuracies of 87.69% and 88.32% respectively. (3) Chinese cities have consistently suffered water loss/leakage rates above 20% since 2001, and water prices are closely associated with leakage. (4) China's urban water sustainability has increased by just 3.56% between 2001 and 2013; Southwest China saw the highest growth rate in urban water supply sustainability. The implications of our research effort will be useful for decision makers in water-stressed urban areas around the world who are seeking novel insights in how to leverage statistical learning techniques to gain insights into urban drinking water supply patterns.

Performance evaluation of restaurant food waste and biowaste to biogas pilot projects in China and implications for national policy.

The objective of this research was to conduct a performance evaluation of three food waste/biowaste-to-biogas pilot projects across 7 scenarios in China based on multi-criteria decision analysis (MCDA) methodology. The projects ranked included a food waste-biogas project in Beijing, a food waste-biogas project in Suzhou and a co-digestion project producing biomethane in Hainan. The projects were ranked from best to worst based on technical, economic and environmental criteria under the MCDA framework. The results demonstrated that some projects are encountering operational problems. Based on these findings, six national policy recommendations were provided: (1) shift away from capital investment subsidies to performance-based subsidies; (2) re-design feed in tariffs; (3) promote bio-methane and project clustering; (4) improve collection efficiency by incentivizing FW producers to direct waste to biogas projects; (5) incentivize biogas projects to produce multiple outputs; (6) incentivize food waste-based projects to co-digest food waste with other substrates for higher gas output.

Uncertainty analysis of primary water pollutant control in China's pulp and paper industry.

The total emission control target of water pollutants (e.g., COD and NH4-N) for a certain industrial sector can be predicted and analysed using the popular technology-based bottom-up modelling. However, this methodology has obvious uncertainty regarding the attainment of mitigation targets. The primary uncertainty comes from macro-production, pollutant reduction roadmap, and technical parameters. This research takes the paper and pulp industry in China as an example, and builds 5 mitigation scenarios via different combinations of raw material structure, scale structure, procedure mitigation technology, and end-of-pipe treatment technology. Using the methodology of uncertainty analysis via Monte Carlo, random sampling was conducted over a hundred thousand times. According to key parameters, sensitive parameters that impact total emission control targets such as industrial output, technique structure, cleaner production technology, and end-of-pipe treatment technology are discussed in this article. It appears that scenario uncertainty has a larger influence on COD emission than NH4-N, hence it is recommended that a looser total emission control target for COD is necessary to increase its feasibility and availability while maintaining the status quo of NH4-N. Consequently, from uncertainty analysis, this research recognizes the sensitive products, techniques, and technologies affecting industrial water pollution.

Integrated control of emission reductions, energy-saving, and cost-benefit using a multi-objective optimization technique in the pulp and paper industry.

Reduction of water pollutant emissions and energy consumption is regarded as a key environmental objective for the pulp and paper industry. The paper develops a bottom-up model called the Industrial Water Pollutant Control and Technology Policy (IWPCTP) based on an industrial technology simulation system and multiconstraint technological optimization. Five policy scenarios covering the business as usual (BAU) scenario, the structural adjustment (SA) scenario, the cleaner technology promotion (CT) scenario, the end-treatment of pollutants (EOP) scenario, and the coupling measures (CM) scenario have been set to describe future policy measures related to the development of the pulp and paper industry from 2010-2020. The outcome of this study indicates that the energy saving amount under the CT scenario is the largest, while that under the SA scenario is the smallest. Under the CT scenario, savings by 2020 include 70 kt/year of chemical oxygen demand (COD) emission reductions and savings of 7443 kt of standard coal, 539.7 ton/year of ammonia nitrogen (NH4-N) emission reductions, and savings of 7444 kt of standard coal. Taking emission reductions, energy savings, and cost-benefit into consideration, cleaner technologies like highly efficient pulp washing, dry and wet feedstock preparation, and horizontal continuous cooking, medium and high consistency pulping and wood dry feedstock preparation are recommended.

Performance evaluation model of a pilot food waste collection system in Suzhou City, China.

This paper analyses the food waste collection and transportation (C&T) system in a pilot project in Suzhou by using a novel performance evaluation method. The method employed to conduct this analysis involves a unified performance evaluation index containing qualitative and quantitative indicators applied to data from Suzhou City. Two major inefficiencies were identified: a) low system efficiency due to insufficient processing capacity of commercial food waste facilities; and b) low waste resource utilization due to low efficiency of manual sorting. The performance evaluation indicated that the pilot project collection system's strong points included strong economics, low environmental impact and low social impact. This study also shows that Suzhou's integrated system has developed a comprehensive body of laws and clarified regulatory responsibilities for each of the various government departments to solve the problems of commercial food waste management. Based on Suzhou's experience, perspectives and lessons can be drawn for other cities and areas where food waste management systems are in the planning stage, or are encountering operational problems.

Uneven agricultural contraction within fast-urbanizing urban agglomeration decreases the nitrogen use efficiency of crop production.

Diverse development paths among cities within an urban agglomeration can lead to uneven changes in their agricultural production scale, which reshape the inter-city food supply patterns and the spatiotemporal characteristics of nitrogen (N) pollution from the food system. Here, using Guangdong-Hong Kong-Macao Greater Bay Area of China as a case, we found a substantial decrease in N use efficiency of crop production from 45.2% to 29.3% during 1989-2007, along with a growing level of concentration of food N production in less-urbanized cities. From 1989 to 2018, 12.3% to 42.2% of total N pollution in food production became embedded in inter-city trade, leading to aggregation of N pollution in peripheral cities with relatively low levels of economic development. We suggest that protection and intensification of cropland from urban encroachment, as well as enhancing the economic and technical synergies among cities, can serve the sustainable transition of the food system with coordinated N pollution mitigation.

A fine-grained dataset for sewage outfalls objective detection in natural environments.

Pollution sources release contaminants into water bodies via sewage outfalls (SOs). Using high-resolution images to interpret SOs is laborious and expensive because it needs specific knowledge and must be done by hand. Integrating unmanned aerial vehicles (UAVs) and deep learning technology could assist in constructing an automated effluent SOs detection tool by gaining specialized knowledge. Achieving this objective requires high-quality image datasets for model training and testing. However, there is no satisfactory dataset of SOs. This study presents a high-quality dataset named the images for sewage outfalls objective detection (iSOOD). The 10481 images in iSOOD were captured using UAVs and handheld cameras by individuals from the river basin in China. This study has carefully annotated these images to ensure accuracy and consistency. The iSOOD has undergone technical validation utilizing the YOLOv10 series objective detection model. Our study could provide high-quality SOs datasets for enhancing deep-learning models with UAVs to achieve efficient and intelligent river basin management.

The eco-efficiency evaluation in China's cement industry: A city-level study.

To implement strict environmental targets in China's cement industry into small regions, one should evaluate the city-level eco-efficiency that provides comprehensive instruction. This study establishes a plant-level database with 4000+ production lines located in 341 cities, calculates the energy consumption and CO2, SO2, NOx, and PM emissions, evaluates the eco-efficiency in each city via Slacks-based Measure, and verifies the spatial features of these indicators. Results show that the energy consumption and emissions of the industry are highly concentrated, with ~10 % of the land area contributing to 28.4 %-34.6 % of the total amounts in 2019. The average eco-efficiency value of the clinker calcination and cement grinding processes are 0.761 and 0.714, but the city clusters having low eco-efficiency values are inconsistent with the ones having large energy consumption and emission amounts. The results can contribute to the implementation of the targets such as carbon peaking and pollution cap in China's cement industry.

Analysis of China's non-ferrous metals industry's path to peak carbon: A whole life cycle industry chain based on copper.

Copper is an essential nonferrous metal, and the adjustment of its whole industry chain structure is conducive to realizing a carbon peak in the nonferrous metal industry. We have performed a life cycle assessment to calculate the carbon emissions of the copper industry. Based on the carbon emissions scenarios of shared socioeconomic pathways (SSPs), we have utilized material flow analysis and system dynamics to analyze the structural changes in the copper industry chain from 2022 to 2060 in China. The results show that (1) the flows and in-use stocks of all types of copper resources will increase significantly. The overall copper supply may meet demand around 2040-2045 due to secondary copper production potentially replacing primary copper production to a large extent, and trade supply is the primary pathway for meeting copper demand. (2) The total carbon emissions from the regeneration system are the smallest (4 %), followed by the production and trade subsystems, accounting for 48 %. The embodied carbon emissions from copper product trade in China have expanded annually. (3) Under the SSP scenario, the copper chain carbon emission peak will be achieved by approximately 2040. Based on a balanced copper supply and demand scenario, the recycled copper recovery efficiency must reach 84.6 %, and the energy structure (the proportion of non-fossil energy in electricity) must reach 63.8 % by 2030 to achieve the carbon peak target for the copper industry chain in China. The above conclusions indicate that actively promoting adjustments in the energy structure and resource recovery processes may help encourage the carbon peak of nonferrous metals in China by realizing the carbon peak of the copper industry.

The economic and environmental impacts of shared collection service systems for retired electric vehicle batteries.

One of the impending consequences of the rapid penetration of electric vehicles (EVs) is that a substantial amount of expired EV batteries will present an increasing waste collection and management problem, particularly in the urban context. Motivated by a lack of research on this issue, this paper comprehensively evaluates the relative benefits of shared versus non-shared collection systems, where the service outlets are not exclusive to specified automakers. Using a mixed-integer optimization model, the analysis features spatiotemporal and multiple stakeholder complexities. Based on the historical monthly EV sales data from 2016 to 2021, a representative case study of Beijing, China is conducted, including 16 district centers, 32 major automobile manufacturers, 153 collection service outlets and 4 disposal centers. The results show that a shared collection service system leads to higher profitability, higher collection rates, increased environmental benefits and improved facility utilization. Consequently, this research contributes to supply chain liberalization to foster the efficient waste management of EV batteries. With a further model extension, it can also provide decision support for the policy-making of more countries.

Single-use plastic bag alternatives result in higher environmental impacts: Multi-regional analysis in country with uneven waste management.

Single-use plastics (SUPs) have been the focus of plastic pollution control, and limiting their use while shifting to other alternatives have been widely promoted in various countries. This study tries to verify the life cycle environmental performances of single-use plastic bag and its alternatives under different scenarios in real world. China is chosen as case study, where provincial variability is prominent in waste disposal, and strictest plastics ban has issued lately in this worldwide biggest market. The study found that HDPE plastic bags have relatively lowest environmental footprints regarding to Acidification Potential, Global Warming Potential, Chemical Oxygen Demand, Eutrophication Potential, Fossil Fuel Depletion Potential and Water Use. Sticking to current waste treatment, large-scale promotion of degradable products will increase environmental impacts by 1.4-22.6 times nationwide. Xinjiang has highest impact of using plastic bag at household level, due to its long-distance transport and high landfill ratio. Henan and Hebei will trigger the most significant changes in Global Warming Potential of 4.6 and 4.4 times if single-use plastic bags are all replaced with other alternatives. Uncertainty and sensitivity test further prove the robustness of results, and extends geographical implications of the findings. These suggest that introduction of new alternatives requires systematic deployment with full life cycle thinking, and SUPs pollution control should be a holistic transformation. Reducing bag weight while ensuring carrying capacity, purchasing local products to shorten transportation distances and shifting towards cleaner energy sources are synergetic ways to reduce the environmental impact of single-use plastic products.

Green transformation strategy of pallet logistics in China based on the life cycle analysis.

The Anthropocene is a new geologic epoch defined by the significant impact of human activity on the planet. Industrialisation and population growth have altered the natural environment. The logistics industry, which facilitates economic development and enhances human well-being, relies on logistic carriers as essential equipment. Pallets, the most representative tools of logistic carriers, transport more than 80 % of the world's trade. The conventional pallet market structure is largely determined by economic and convenience factors, but in light of the global environmental changes, the leading users of pallet products have raised their environmental standards, making environmental performance a key factor in the pallet industry. While China is the second largest pallet holder and accounts for 25 % of the global pallet holdings, it lacks an in-depth understanding on the pallet market structure, the environmental effects, and the barriers for developing pallet sharing system in China. This study conducts comprehensive field studies to reveal the pallet market structure in China, applies life cycle assessment to present a cradle to grave environmental evaluation of the five widely-used pallet material types that account for 99 % of market share, and compare various end-of-life treatment methods using scenario analysis. Results show that the current market structure does not align with the optimal environmental outcomes, but would be improved by establishing the circulation-sharing system. Therefore, there is an urgent need for the pallet industry to undergo a green transition. The focus for developing a sharing system should be on engaging the leading user enterprises in the supply chain, rather than merely relying on the pallet manufacturers who have limited bargaining power. Additionally, the environmental impacts can be reduced by 20 % to 300 % via choosing the appropriate end-of-life treatment method for each pallet material type.

Mapping the environmental impacts and policy effectiveness of takeaway food industry in China.

The takeaway food industry, involving more than 0.4 billion consumers in China, has brought mass of packaging waste and salient environmental burden. Here we mapped the distribution of takeaway food industry across China including the industry scale, diet structure and order time based on the analysis of more than 35 million takeaway food orders. The real use situation of various packaging materials in the takeaway food industry market has been clarified. The life cycle assessment of "a piece of takeaway food delivery order" has been carried out in different regions. Results show that in addition to plastic waste generation, takeaway food industry causes more types of environmental impacts. In terms of the national resource consumption, greenhouse gases emission, water pollution and health damage risk, the top 5 ranked provinces in each accounted for 44%, 48%, 43% and 49%, respectively. Under the latest Chinese plastic pollution control policy, the industry needs to reduce 1.12 million tons of non-degradable plastic packaging by the end of 2025, and 65% of the pressure is clustered in the metropolis and provincial capitals. However, without targeted and regionally differentiated plastic pollution control policies, the environmental impact control of takeaway food industry is still ineffective. It is urgent to explore the control measures applicable to different regions. Overall, packaging reduction is more effective than material substitution.

The driving effect of technological innovation on green development: dynamic efficiency spatial variation.

In order to further explore the internal transmission mechanism between technological innovation and green development in manufacturing industry under the background of obvious development characteristics in the new era, this paper constructed an integrated methodology system to evaluate the internal impact mechanism of technological innovation value chain efficiency on green development efficiency based on spatial perspective. First, the Network Slack-based model and Global Malmquist-Luenberger model are constructed to reveal the internal development law of technological innovation and green development of manufacturing industry. Secondly, the spatial Dubin model is employed to analyze the impact of current development characteristics and technological innovation on green development. The results show that innovation value chain efficiency is higher than technological innovation efficiency, and economic transformation efficiency is lower than that of technological innovation value chain. During the study period, the efficiency of technological innovation value chain in the four economic regions present fluctuant growth trend, and the eastern region has the highest value. The green development efficiency in the east, central, west, and northeast regions of manufacturing industry is higher than 1, and it shows an obvious spatial agglomeration effect. Besides, the efficiency of technological innovation, information and communication technology, urbanization, and the advanced industrial structure are all conducive to the improvement of green development in manufacturing industry. This paper studies the influence mechanism of technological innovation value chain efficiency on green development based on spatial perspective and puts forward relevant countermeasures and suggestions to effectively promote green development of manufacturing industry, providing relevant theoretical research for green and high-quality development.