Scientific and technological revolutions and industrial transformations have accelerated the rate of innovation in environmental engineering technologies. However, few researchers have evaluated the current status and future trends of technologies. This paper summarizes the current research status in eight major subfields of environmental engineering—water treatment, air pollution control, soil/solid waste management, environmental biotechnology, environmental engineering equipment, emerging contaminants, synergistic reduction of pollution and carbon emissions, and environmental risk and intelligent management—based on bibliometric analysis and future trends in greenization, low carbonization, and intelligentization. Disruptive technologies are further identified based on discontinuous transformation, and ten such technologies are proposed, covering general and specific fields, technical links, and value sources. Additionally, the background and key innovations in disruptive technologies are elucidated in detail. This study not only provides a scientific basis for strategic decision-making, planning, and implementation in the environmental engineering field but also offers methodological guidance for the research and determination of breakthrough technologies in other areas.
Environmental engineering serves as a foundation for supporting the harmonious coexistence of humans and nature. The report of the 20th National Congress of the Communist Party of China emphasizes the necessity of promoting green development based on the notion that clear waters and green mountains are as good as mountains of gold and silver. Environmental complexity, transferability, and systematicity determine the cross integration of environmental engineering technologies. Therefore, future disruptive innovations in environmental engineering will require the integration of interdisciplinary theories, methods, and technologies to form new theoretical and methodological systems.
Scientific advances and industrial upgrades have expedited the transformation of environmental engineering technologies. The new generation of information technologies—represented by artificial intelligence (AI), the Internet of Things (IOT), and big data—offer crucial support for the accurate identification, control, and prediction of pollutants [1]. Biotechnologies, such as synthetic biology and gene editing, provide essential support for the design and construction of efficient and intelligent biodegradation and bioremediation systems [2], [3]. Advanced material technologies, represented by materials genomics, offer vital support for the “on-demand design” of pollution control methods [4]. Additionally, advanced manufacturing technologies, such as digital twins and virtual reality, have accelerated intelligent and sustainable transformations in environmental protection manufacturing [5].
Owing to the scientific revolution, integration of multiple disciplines, and global climate change, the field of environmental engineering has developed rapidly. However, few researchers have summarized the future directions and potential disruptive innovations in this field, especially in the context of the rapid development of environmental research. Here, the environmental engineering discipline was divided into eight subfields and a bibliometric analysis was conducted on the research status of each subfield. Greenization, low carbonization, and intelligentization are the main trends in the development of environmental engineering technologies. In addition, by focusing on discontinuous transformation, ten disruptive technologies were proposed from the perspective of technological processes and types, as well as their backgrounds and key innovations. These technologies are directional design of advanced materials, intelligent pollutant-degradation microbiota, digital twin equipment, normalized indicators of water toxicity, membrane materials based on the physical properties of water molecules, mainstream anammox processes for urban sewage treatment, zero byproduct disinfection processes, micro/nanoreactors, synchronous processing of carbon and pollutants, and the targeted transformation of pollutants. This study aimed to provide directions for future innovations in environmental engineering technology and methodological guidance for the research and evaluation of disruptive technologies.
2. Theoretical framework
Christensen [6] first proposed the theory of disruptive innovation in his seminal book, The Innovator’s Dilemma, in which disruptive technology is defined as that which provides a source of value different from the original technology. Disruptive technology has changed the performance characteristics of existing technologies, resulting in discontinuous transformation. In environmental engineering, green innovation—improving economic and social benefits while respecting natural resources, thereby generating positive societal impacts [7]—is considered potentially disruptive. The driving forces for green innovation technology are mainly environmental-level factors, such as public policies and market demands [8]. However, compared with traditional innovation, green innovation requires a closer cooperative relationship between external and internal actors [9]. Disruptive innovation can be achieved when internal managers adopt radical changes in concert with external organizations, particularly in cooperation with family businesses [10].
Bibliometric analysis, proposed by Pritchard (1969) [11], is an objective statistical method that enables researchers to quickly understand the research status in related fields and provide predictions for future research directions. Currently, bibliometric analysis is employed by researchers in multiple fields, such as AI [12], semiconductors [13], information management [14], and biomedical science [15]. In the field of environmental engineering, it has only been used to analyze the current status of specific technologies—chemical technology [16] and biotechnology [17]. This study was based on Christensen’s disruptive innovation theory and bibliometric analysis, and aimed to evaluate disruptive technologies in environmental engineering through the following methods and steps (Fig. 1):
(1) Environmental engineering research is divided into eight major subfields according to environmental disciplines: water treatment, air pollution control, soil/solid waste management, environmental biotechnology, environmental engineering equipment, emerging contaminants, synergistic reduction of pollution and carbon emissions, and environmental risk and intelligent management. The Web of Science core collection database was selected as the data source, and research data were extracted from relevant articles published over the past six years (2018-2023) from “Article” and “Review Article” document types [18]. The specific retrieval strategies are listed in Table 1. The retrieved information was saved in plain text format, with recorded content consisting of “Full Record” [19]. Then, COOC software was used to clean and merge keywords, and the research results were visualized through bubble charts constructed in a Python matplotlib pyplot to determine the direction of major subfields in environmental engineering. To simplify the keyword trends over time, a trend factor (T) was used for evaluation [20]. The specific calculation formula was as follows:
where fi and are the appearance of article target keywords and the total number of articles published in year i, respectively; and are the frequency of target keywords from 2021–2023 and 2018–2020, respectively
(2) Basic principles, technical methods, and reaction paths were defined as the value sources of disruptive innovation in the environmental engineering field. By focusing on discontinuous transformation characteristics, analyzing the original technologies from the perspective of different technical links (monitoring, separation, and reaction) in general and specific fields, and combining this information with expert opinions, ten potential disruptive technologies in the field of environmental engineering were identified.
3. Current status and future trends in environmental engineering technologies
Based on the changes in keyword frequency over six years of research in the subfields of environmental engineering, the current status and future trends were revealed (Fig. 2 [21]). The bubble sizes represent the keyword frequency, and the bubble positions represent the year in which the keyword appeared.
Removal efficiency, energy consumption, membrane technology, and nanotechnology received high attention in the water treatment field (Fig. 2(a)) [22], and air quality, emissions, sensors, and atmospheric modeling were hot topics in air pollution control (Fig. 2(b)) [23]. In the field of soil/solid waste management (Fig. 2(c)), researchers focused on waste management, heavy metals, and life cycle assessment [24]. Biodegradation, remediation, and waste resource utilization are the focus of research in environmental engineering biotechnology (Fig. 2(d)), which is reflected in the keyword environmental mediation [25]. In the environmental engineering equipment field (Fig. 2(e)), biological treatment, IOT, and simulation were high-frequency keywords. Research hotspots for emerging contaminants (Fig. 2(f)) can be divided into pollutants, characteristics, and technologies. Microplastics, antibiotics, and endocrine disruptors were pollutant hotspots, hot research characteristics included toxicity, exposure, and risk assessment and key technology studies were focused on absorption, advanced oxidation processes), and microbial communities [26], [27]. The current research status of the synergistic reduction of pollutants and carbon is shown in Fig. 2(g), with photoreduction, electrical reduction, and biodegradation being mainstream technologies. In the environmental risk and intelligent management fields (Fig. 2(h)), risk assessment, heavy metals, human health risk, and environmental health were hot keywords and remediation, monitoring, and IOT were common techniques [28].
In all subfields, machine learning and AI appeared with high popularity. Sustainability, renewable energy, and remediation have attracted considerable attention in subfields such as soil/solid waste management, environmental engineering equipment, and synergistic reduction of pollution and carbon emissions, while emerging pollutants, microplastics, and emerging contaminants have received more attention in the fields of water treatment, emerging contaminants, and environmental risk and intelligent management. Greenization [29], low carbonization [30], and intelligentization [31] are predicted to be the main trends in the future development of environmental engineering technologies.
4. Disruptive technologies in the field of environmental engineering
Disruptive innovation in environmental engineering technologies depends on changes in the values of basic principles, technical methods, and reaction paths. Both general—material, microbiota, and equipment—and specific fields—water treatment, air pollution control, and soil/solid waste management—together with the technical links involved in monitoring, separation, and reaction, are essential. Therefore, based on the aforementioned analysis of the major subfields, further attention was paid to the discontinuous transformation characteristics of value sources, and original technologies were evaluated from the perspectives of general and specific fields, technical links, and value sources. Ultimately, ten disruptive technologies in environmental engineering were proposed (Table 2).
4.1. Disruptive technologies in the general field of environmental engineering
4.1.1. Directional design of advanced materials
In current research on advanced materials in the environmental engineering field, design and innovation still result in resource wastage and high expenditure [32]. Through material genomics—the integration of high-throughput material design and experiments, and material databases containing components, structures and performance—the design of required structures and optimization of compositions and processes must be improved to realize the “on-demand design” of materials (Fig. 3) [33]. This principle has been applied in the preparation of new high-efficiency catalysts and adsorbents. Jiang et al. [34] achieved the controllable preparation of straw-activated carbon materials while reducing environmental pollution using machine learning models such as linear regression, support vector machines, and random forests to study the performance of straw pyrolysis-activated carbon. Recently, we accurately predicted the performance of metal organic frameworks in the treatment of different pollutants from theoretical databases using the XGBoost model [35]. Data interconnections and the interoperability of components and structures, and the performance of pollution control materials—together with machine learning models and traditional mechanism models for material data—are key innovations in achieving scientific material design.
Environmental biotechnology is an important part of environmental engineering and microorganisms are the cornerstone of environmental biotechnology. However, the ability of these microorganisms to degrade typical pollutants remains unclear. With improvements in genomics, synthetic biology, and microecology, targeted regulation of microbiota has gradually become a research hotspot (Fig. 3). Regulation methods include component creation for pollution degradation, construction of efficient degradation pathways for typical pollutants, and design of intelligent degradation systems for these pollutants [36]. Yang et al. [37] constructed potential degradation pathways for benzo[a]pyrene and phenanthrene through the genomic analysis of strains for PHA degradation, providing new insights into intelligent pollutant degradation. In the future, the rapid evolution and high-throughput screening of pollutant-degradation microbiota, as well as the efficient transformation and regulation of degradation microbial communities for degrading complex pollutants, will become key innovations in this technology to realize “bottom to top” designs.
4.1.3. Digital twin equipment
Environmental engineering equipment provides powerful support for environmental protection and pollution control; however, the development and manufacturing of environmental engineering equipment are still at an early stage in China. The integration of information and physical principles, as well as digital twins of physical equipment, is necessary for the transition from digitization to intelligentization [38]. The development of digital twin equipment depends on data platforms—process, energy consumption, and digital twin data—that can perform structural and strength design, and virtual simulations that enable self-perception, self-cognition, self-learning, self-decision-making, self-execution, and self-optimization to promote the digital upgrading of equipment and achieve intelligent production (Fig. 3) [39]. At present, digital twin equipment has been applied in fields such as electrical, vehicle engineering, machinery, steel, and pharmaceuticals; for example, in vehicle health monitoring, battery management systems, power electronic converters, and power drive systems [40]. However, this approach has not been widely applied in the environmental engineering field. Modeling methods based on spatiotemporal heterogeneity and multiscale digital twin equipment—together with digital model linkages, virtual real mapping, and consistency interaction mechanisms—are expected to be key future innovations.
4.2. Disruptive technologies in the water treatment field
4.2.1. Normalized indicators of water toxicity
Currently, there are many complex water quality toxicity indicators based on different biological properties—at the molecular, cellular, or individual level—which result in limitations such as low information content and low scientific value of toxicity thresholds. In addition, because of the complex composition of wastewater, comprehensive biological toxicity studies are more practical for ensuring water quality and safety. Therefore, normalized indicators of water toxicity are necessary to guide the development of new technologies, equipment, and processes for water toxicity control in industries (Fig. 4). There are two key innovations: a big data-driven method for the development of comprehensive toxicity indicators for water quality, and a method for determining the comprehensive toxicity matrix index and simple quick response code to meet the requirements for information transfer, adaptability, and scalability of water quality toxicity indicators.
4.2.2. Membrane materials based on physical properties of water molecules
Membrane separation is a thriving green technology used in water treatment. At present, commonly used membrane materials include zeolites, graphene, metal-organic frameworks, covalent organic frameworks, and graphite-phase carbon nitride. Recently, emerging carbon nanofluid technologies have provided new insights into membrane materials. For example, aquaporins have been gradually applied in fields such as seawater desalination, wastewater treatment, and medical research, owing to their high selectivity, ease of operation, and environmental friendliness [41]. However, low structural stability and susceptibility to scaling have limited the large-scale industrial application of aquaporins [42]. The precise construction of sub-nanochannels at the molecular scale and the structural regulation of water molecule transport in sub-nanochannels will be key advances in this technology (Fig. 4).
4.2.3. Mainstream anammox processes for urban sewage treatment
The anammox process, rather than the traditional nitrification-denitrification process, is globally accepted as the most promising sewage treatment process (energy consumption for aeration is reduced by 60%, organic carbon by 100%, and sludge production by 90% [43]). However, its application in mainstream urban sewage treatment is still challenged by obstacles such as the unstable inflow of urban sewage and directional control of competing microorganisms; additionally, the process has failed to achieve satisfactory denitrification results in long-term operation [44]. Further expansion of the anammox process from sidestream to mainstream to adapt to the low concentrations of ammonia nitrogen present in urban sewage is the primary technical requirement of the field (Fig. 4) [45]. Because anammox bacteria are susceptible to environmental conditions and are deficient in nitrite supply, in-situ selective enrichment of anammox bacteria and functional regulation of autotrophic denitrifying bacteria have become key innovations in the mainstream anammox process for urban sewage treatment.
4.2.4. Zero byproduct disinfection processes
Disinfection processes are widely used in the treatment of drinking water and hospital wastewater. However, because of hydrolysis, exchange, and redox reactions, traditional disinfection processes produce disinfection byproducts that pose potential risks to human health and the environment [46]. Therefore, targeted disinfection processes for pollutants and zero byproduct disinfection processes have broad application prospects (Fig. 4). Breakthroughs have been made in the utilization of clean energy (e.g., physical energy) and nonchemical disinfection. For example, hydrodynamics has been utilized to disrupt the integrity of bacteria through a high dispersive force between a nanotip surface and cell envelopes to achieve sustainable and green water disinfection [47]. The key innovations in this technology lie in the precise construction and standardized preparation of the geometric features of the surface and interface materials, along with principles and new processes for selective disinfection and sterilization of target bacteria and pathogens.
4.2.5. Micro/nanoreactors
A series of shortcomings, such as difficulties in fluid flow, mixing, reaction control, and low mass transfer efficiency, are commonly encountered in environmentally engineered reactors. With the rapid development of precision machining and microchemical technologies, micro/nanoreactors have received increasing attention. Recently, many efforts have been made to understand microscale interface behavior, multiphase interface regulation, and microchannel manufacturing in micro/nanoreactors based on interface characteristic analysis, real-time monitoring, and dynamic observations of wastewater and waste gas treatment. The key innovations in the field of micro/nanoreactors lie in the dynamic regulation of microscale multiphase interfaces and high-precision, low-cost microchannel manufacturing to ensure appropriate scaling and achieve efficient, fast-responding, and controllable green processes (Fig. 4).
4.3. Disruptive technology in the air pollution control field
China’s “dual carbon” goals involve the coupling of carbon emission and pollution reduction in the air pollution control field, in which the synergistic conversion of carbon and other air pollutants into high-value chemicals is considered an effective way to address this issue (Fig. 5). Researchers have utilized the “Wood-Ljungdahl metabolic pathway of acetogens to effectively transform CO2 and CO present in industrial waste gases [48]. However, existing research seldom involves the synergistic transformation of carbon and pollutants, and issues related to energy supply and conversion efficiency exist [49]. In the future, more attention should be given to developing a closed-loop catalytic conversion system for high-value chemicals in one-step reactions. Key innovations will lie in the design of catalysts with high reactivity and target product yields, and in-situ and real-time monitoring of reaction intermediates and catalytic conversion mechanisms.
4.4. Disruptive technology in the field of soil/solid waste management
Pollutant detoxification and multiple side reactions are problems encountered in environmental engineering and treatment technologies. In addition, the emergence of new pollutants further increases pollutant removal complexities. Therefore, targeted pollutant transformation is urgently needed to achieve greenization and low-carbon technologies. Recently, progress has been made in this transformation, including the design of electron transfer paths (Fig. 5). Chen et al. [50] developed a multiscale molecular simulation method specifically for complex pollutants and identified potential mechanisms for electron transfer at micro interfaces, providing technical support for direct targeted transformation of pollutants. The detoxification of pollutants mediated by microorganisms and targeted transformation—together with interfacial electron transfer mechanisms for complex pollutant transformation—will become key innovations in this technology to achieve controllable transformation pathways, resource utilization, and low-carbon goals in soil/solid waste management.
5. Conclusions
This article summarizes the current research status in eight major subfields of environmental engineering based on bibliometric analysis and illustrates future trends toward greenization, low carbonization, and intelligentization. Disruptive technologies were then identified through discontinuous transformation, and ten disruptive technologies were proposed from the perspectives of general and specific fields, technical links, and innovation types. Furthermore, the background of and key innovations in disruptive technologies were elucidated in detail. However, this study had some limitations. First, owing to length limitations, only research articles were summarized, and the analysis and discussion of patents were neglected; therefore, attention should be paid to the role of patents in disruptive innovation. In addition, theoretical research on disruptive technologies in the environmental engineering field is limited, and the definition of disruptive concepts is somewhat unclear. Therefore, in this study, we defined three types of disruptive technologies through expert consultation and discussion. However, these do not include all possible categories. In the future, more comprehensive theories and evaluation standards should be developed to determine disruptive technologies in the environmental engineering field.
In summary, this research can serve as a reference for future innovation directions in environmental engineering technology; provide a scientific basis for strategic decision-making, planning, and implementation in the environmental engineering field; and offer methodological research guidance for breakthrough technologies in other fields.
Acknowledgments
This work was supported by National Natural Science Foundation of China (52388101 and 52242004), National Key Research and Development Program of China (2023YFC320760301), Jiangsu Provincial Department of Science and Technology (BK20220012), and Excellent Research Program of Nanjing University (ZYJH005). We also thank Professor Jiuhui Qu from Tsinghua University and Professor Jun Bi from Nanjing University for their helpful guidance on the method of disruptive technology judgement.
Compliance with ethics guidelines
Hui Huang, Junjie Lu, Lili Jin, and Hongqiang Ren declare that they have no conflict of interest or financial conflicts to disclose.
S.F.Zhong, K.Zhang, M.Bagheri, J.G.Burken, A.Gu, B.K.Li, et al. Machine learning: new ideas and tools in environmental science and engineering. Environ Sci Tec, 55 (19) (2021), pp. 12741-12754.
[2]
H.Liu, L.G.Zhang, W.W.Wang, H.Y.Hu, X.Y.Ouyang, P.Xu, et al. An Intelligent synthetic bacterium for chronological toxicant detection, biodegradation, and its subsequent suicide. Adv Sci, 10 (2023), p. 31.
[3]
S.Jaiswal, D.K.Singh, P.Shukla. Gene editing and systems biology tools for pesticide bioremediation: a review. Front Microbiol, 10 (2019), p. 87.
[4]
K.M.Jablonka, D.Ongari, S.M.Moosavi, B.Smit. Big-data science in porous materials: materials genomics and machine learning. Chem Rev, 120 (16) (2020), pp. 8066-8129.
[5]
J.Bolorinos, M.S.Mauter, R. Rajagopal. Integrated energy flexibility management at wastewater treatment facilities. Environ Sci Tec, 57 (46) (2023), pp. 18362-18371.
[6]
ChristensenCM. The innovator's dilemma:when new technologies cause great firms to fail. Boston, MA: Harvard Business School Press; 1997.
[7]
V.Cillo, A.M.Petruzzelli, L.Ardito, M. DelGiudice. Understanding sustainable innovation: a systematic literature review. Corp Soc Resp Env Ma, 26 (5) (2019), pp. 1012-1025.
[8]
L.Ardito, A.M.Petruzzelli, F.Pascucci, E.Peruffo. Inter-firm R&D collaborations and green innovation value: the role of family firms’ involvement and the moderating effects of proximity dimensions. Bus Strateg Environ, 28 (1) (2019), pp. 185-197.
[9]
A.M.Petruzzelli, R.M.Dangelico, D.Rotolo, V.Albino. Organizational factors and technological features in the development of green innovations: evidence from patent analysis. Innov Organ Manag, 13 (3) (2011), pp. 291-310.
[10]
A.Urbinati, Z.S.Esfandabadi, A.M.Petruzzelli. Assessing the interplay between open innovation and sustainability-oriented innovation: a systematic literature review and a research agenda. Bus Ethics Environ Resp, 32 (3) (2023), pp. 1078-1095.
[11]
PritchardA. Statistical bibliography or bibliometrics. J Doc1969; 25(4):348.
[12]
S.F.Wamba, R.E.Bawack, C.Guthrie, M.M.Queiroz, K.D.A.Carillo. Are we preparing for a good AI society? A bibliometric review and research agenda. Technol Forecast Soc Chang, 164 (2021), Article 120482.
[13]
I.Kang, J.Yang, W.Lee, E.Y.Seo, D.H.Lee. Delineating development trends of nanotechnology in the semiconductor industry: focusing on the relationship between science and technology by employing structural topic model. Technol Soc, 74 (2023), Article 102326.
[14]
H.Yalcin, T.Daim. A scientometric review of technology capability research. J Eng Technol Manag, 62 (2021), Article 101658.
[15]
J.D.O’Leary, M.W.Crawford, E.Jurczyk, A.Buchan. Benchmarking bibliometrics in biomedical research: research performance of the University of Toronto’s faculty of medicine,2008-2012. Scientometrics, 105 (1) (2015), pp. 311-321.
[16]
X.Z.Sun, L.L.Jin, F.Y.Zhou, K.Jin, L.C.Wang, X.X.Zhang, et al. Patent analysis of chemical treatment technology for wastewater: status and future trends. Chemosphere, 307 (4) (2022), Article 135802.
[17]
L.L.Jin, X.Z.Sun, H.Q.Ren, H.Huang. Hotspots and trends of biological water treatment based on bibliometric review and patents analysis. J Environ Sci, 125 (2022), pp. 774-785.
[18]
L.L.Jin, X.Z.Sun, H.Q.Ren, H.Huang. Biological filtration for wastewater treatment in the 21st century: a data-driven analysis of hotspots, challenges and prospects. Sci Total Environ, 855 (2022), Article 158951.
L.L.Jin, J.J.Lu, X.Z.Sun, H.Huang, H.Q.Ren. Data-driven insights into treatment of sulfur-containing organic wastewater. J Clean Prod, 433 (2023), Article 139878.
[21]
H.Huang, R.Ma, H.Q.Ren. Scientific and technological innovations of wastewater treatment in China. Front Environ Sci Eng, 18 (6) (2024), p. 72.
[22]
K.Xiao, S.Liang, X.M.Wang, C.S.Chen, X.Huang. Current state and challenges of full-scale membrane bioreactor applications: a critical review. Bioresour Technol, 271 (2018), pp. 473-481.
[23]
S.Rao, Z.Klimont, S.J.Smith, R. VanDingenen, F.Dentener, L.Bouwman, et al. Future air pollution in the shared socio-economic pathways. Global Environ Chang, 42 (2017), pp. 346-358.
[24]
H.Y.Wu, J.Zuo, G.Zillante, J.Y.Wang, H.P.Yuan. Status quo and future directions of construction and demolition waste research: a critical review. J Clean Prod, 240 (2019), Article 118163.
[25]
P.Xie, C.Chen, C.F.Zhang, G.Y.Su, N.Q.Ren, S.H.Ho. Revealing the role of adsorption in ciprofloxacin and sulfadiazine elimination routes in microalgae. Water Res, 172 (2020), Article 115475.
[26]
N.Morin-Crini, E.Lichtfouse, M.Fourmentin, A.R.L.Ribeiro, C.Noutsopoulos, F.Mapelli, et al. Removal of emerging contaminants from wastewater using advanced treatments: a review. Environ Chem Lett, 20 (2) (2022), pp. 1333-1375.
[27]
A.K.Ghattas, F.Fischer, A.Wick, T.A.Ternes. Anaerobic biodegradation of (emerging) organic contaminants in the aquatic environment. Water Res, 116 (2017), pp. 268-295.
[28]
Z.Wang, P.P.Luo, X.B.Zha, C.Y.Xu, S.X.Kang, M.M.Zhou, et al. Overview assessment of risk evaluation and treatment technologies for heavy metal pollution of water and soil. J Clean Prod, 379 (2) (2022), Article 134043.
[29]
Y.Qi, X.Q.Xie, X.X.Chen. Effects of environmental regulation and corporate environmental commitment: complementary or alternative?. Evidence from China. J Clean Prod, 423 (2023), Article 138641.
[30]
Y.M.Wei, K.Y.Chen, J.N.Kang, W.M.Chen, X.Y.Zhang, X.Y.Wang. Policy and management of carbon peaking and carbon neutrality: a literature review. Engineering, 14 (2022), pp. 52-63.
[31]
D.C.Tang, L.X.Wang, B.J.Bethel. An evaluation of the Yangtze River Economic Belt manufacturing industry level of intelligentization and influencing factors: evidence from China. Sustainability, 13 (16) (2021), p. 8913.
[32]
W.Q.Lai, K.Zhang, P.H.Shao, L.M.Yang, L.Ding, S.G.Pavlostathis, et al. Optimization of adsorption configuration by DFT calculation for design of adsorbent: a case study of palladium ion-imprinted polymers. J Hazard Mater, 379 (2019), Article 120791.
[33]
J.M.Cole. A Design-to-device pipeline for data-driven materials discovery. Acc Chem Res, 53 (3) (2020), pp. 599-610.
[34]
W.Jiang, X.J.Xing, S.Li, X.W.Zhang, W.Q.Wang. Synthesis, characterization and machine learning based performance prediction of straw activated carbon. J Clean Prod, 212 (2019), pp. 1210-1223.
[35]
J.H.Li, J.W.Wang, H.X.Mu, H.D.Hu, J.F.Wang, H.Q.Ren, et al. Prediction of adsorptive activities of MOFs for pollutants in aqueous phase based on machine learning. ACS EST Eng, 3 (9) (2023), pp. 1258-1266.
[36]
H.Liu, L.G.Zhang, W.W.Wang, H.Y.Hu, X.Y.Ouyang, P.Xu, et al. An intelligent synthetic bacterium for chronological toxicant detection, biodegradation, and its subsequent suicide. Adv Sci, 10 (31) (2023), Article e2304318.
[37]
H.C.Yang, Z.H.Qian, Y.J.Liu, F.Yu, T.W.Huang, B.Zhang, et al. Comparative genomics reveals evidence of polycyclic aromatic hydrocarbon degradation in the moderately halophilic genus Pontibacillus. J Hazard Mater, 462 (2023), Article 132724.
[38]
F.Tao, M.Zhang, Y.S.Liu, A.Y.C.Nee. Digital twin driven prognostics and health management for complex equipment. CIRP Ann Manuf Technol, 67 (1) (2018), pp. 169-172.
[39]
F.Tao, C.Y.Zhang, H.Zhang, J.F.Cheng, X.F.Zou, H.Xu, et al. Future equipment exploration: digital twin equipment. Comput Integr Manuf Syst, 28 (1) (2022), pp. 1-16.
[40]
G.Bhatti, H.Mohan, R.R.Singh. Towards the future of smart electric vehicles: digital twin technology. Renew Sustain Energy Rev, 141 (2021), Article 110801.
[41]
Y.J.Lim, K.Goh, R.Wang. The coming of age of water channels for separation membranes: from biological to biomimetic to synthetic. Chem Soc Rev, 51 (11) (2022), pp. 4537-4582.
[42]
Y.Yang, P.Dementyev, N.Biere, D.Emmrich, P.Stohmann, R.Korzetz, et al. Rapid water permeation through carbon nanomembranes with sub-nanometer channels. ACS Nano, 12 (5) (2018), pp. 4695-4701.
[43]
N.J.Mao, H.Q.Ren, J.J.Geng, L.L.Ding, K.Xu. Engineering application of anaerobic ammonium oxidation process in wastewater treatment. World J Microb Biot, 33 (8) (2017), p. 153.
[44]
H.P.Trinh, S.H.Lee, G.Jeong, H.Yoon, H.D.Park. Recent developments of the mainstream anammox processes: challenges and opportunities. J Environ Chem Eng, 9 (4) (2021), Article 105583.
[45]
L.Zhang, L.Jiang, J.T.Zhang, J.L.Li, Y.Z.Peng. Enhancing nitrogen removal through directly integrating anammox into mainstream wastewater treatment: advantageous, issues and future study. Bioresour Technol, 362 (2022), Article 127827.
[46]
X.F.Sun, M.Chen, D.Wei, Y.G.Du. Research progress of disinfection and disinfection by-products in China. J Environ Sci, 81 (2019), pp. 52-67.
[47]
L.Peng, H.J.Zhu, H.B.Wang, Z.B.Guo, Q.Y.Wu, C.Yang, et al. Hydrodynamic tearing of bacteria on nanotips for sustainable water disinfection. Nat Commun, 14 (2023), p. 5734.
[48]
Y.Song, J.S.Lee, J.Shin, G.M.Lee, S.Jin, S.Kang, et al. Functional cooperation of the glycine synthase-reductase and Wood-Ljungdahl pathways for autotrophic growth of Clostridium drakei. Proc Nat Acad Sci, 117 (13) (2020), pp. 7516-7523.
[49]
L.Z.Hu, S.Q.Guo, B.Wang, R.Z.Fu, D.D.Fan, M.Jiang, et al. Bio-valorization of C 1 gaseous substrates into bioalcohols: potentials and challenges in reducing carbon emissions. Biotechnol Adv, 59 (2022), Article 107954.
[50]
J.J.Chen. Interfacial electron transfer in chemical and biological transformation of pollutants in environmental catalysis. Environ Sci Technol, 57 (51) (2024), pp. 21540-21549.
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