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Socioeconomic factors and mitigation potentials are essential drivers of the dynamics of nutrient emissions, yet these drivers are rarely examined at broad spatiotemporal scales. Here, we combine material flow analysis and geospatial analysis to examine the past and future changes of nitrogen and phosphorus emissions in China. Results show that anthropogenic nitrogen and phosphorus emissions increased by 17% and 32% during 2000–2019, respectively. Meanwhile, many regions witnessed decreasing nitrogen emissions but rising phosphorus discharged to waterbody, leading to a 20% decrease in the nitrogen/phosphorus ratio. In addition to many prominent factors like fertilizer use, the increasing impervious land area around cities is a notable factor driving the emissions, indicating the urgency to limit building expansion, especially in North China Plain and other less-developed regions. Improving land-use efficiency and consuming behaviors could reduce nitrogen and phosphorus emissions by 65–77% in 2030, but the nitrogen/phosphorus ratio will increase unintendedly due to larger reduction potentials for phosphorus, which may deteriorate the aquatic ecosystem. We highlight that nitrogen and phosphorus emissions should be reduced with coordinated but differentiated measures by prioritizing nitrogen reduction through cropland and food-system management.

Pulse inductor coils can generate pulsed strong magnetic fields, which can be used in electromagnetic emission, electromagnetic molding, pulse power supply, and many other fields. Coils usually work in extreme physical environments with strong magnetic fields, high temperature rises, and large impact forces. When the temperature exceeds the glass transition temperature of the insulating material, it will accelerate the aging of the insulating material and shorten the service life of the coil, so the coil temperature needs to be accurately measured. The wire inside the coil is a heat source, and the surface temperature of the wire needs to be measured directly. However, the interface is difficult to access and requires any sensor to tolerate electromagnetic interference, extreme temperatures, and high currents. The development of fiber Bragg gratings (FBGs) offers a potential solution to this requirement. Since FBG is sensitive to temperature and stress, in order to eliminate the influence of electromagnetic force, a steady-state temperature test platform is first built, and the change law of optical fiber wavelength change with temperature is obtained. Then, a 2-D coupled heat transfer model of a pulsed inductor coil is established, and the temperature change of the coil under continuous discharge conditions is calculated and compared with the measurement results. The results show that the error between the simulation data and the test data under different discharge times is small, which proves the feasibility of the proposed method, and the sensor can be used for coil continuous discharge test.

Multistage synchronous induction coilgun (MSSICG) has higher launch efficiency than other electromagnetic guns due to excellent noncontact propulsion characteristics. However, the feeding of the coil array must be synchronized with the movement of the projectile to accelerate the load smoothly. Researchers usually adopt tedious step-by-step debugging to achieve the matching of trigger timing and other structural parameters, but lack of detailed derivation and demonstration of critical trigger criterion. Therefore, starting from the optimal coupling position of single-stage launcher, this article proposes the critical trigger criterion. Then, the extended trigger criterion is modified by analyzing the simplified conditions and adjustable parameters of MSSICG with different structural forms. The research aims to provide reference for the parameter design of MSSICG.

Nowadays, decision support systems and recommendation systems are emerging methodologies in the internet of things (IoT) environments for optimising smart electronic services such as smart tourist, smart logistics, smart transportation and smart home services. This paper proposes a smart recommendation system in the smart tourism application. Then, a content-based filtering method is proposed for improving search-based attributes in clustering. In addition, fuzzy C-means clustering is used to cluster the existing data in terms of the users' requests and recommend the optimised choice. Also, bat optimisation algorithm (BOA), which is a well-known meta-heuristic algorithm, is provided to improve the accuracy of the clustering to 98%, which is better than other state-of-the-art case studies. In addition, precision and recall are evaluated for predicting decision-making aspects in smart tourist applications. The results achieved are compared with those of the similar research studies and is superiority is shown.

The internet of medical things (IoMT) is considered as a middle platform between medical systems and communication systems. Machine learning (ML) is used as a new innovation prediction method for supporting stress monitoring factors in safety-critical information in IoMT environments. Therefore, ML approaches can support safety, accuracy and security for sensitive personal information in medical systems and healthcare applications. This paper presents a new literature management for main concept of ML methodologies on the IoMT ecosystem. Hence, the optimality of Stress monitoring is the primary research area in wearable sensors. Several contemporary papers exist on this important subject. The research gap in reviewing all these ML algorithms has motivated us for their presentation in the form of a detailed technical analysis in this paper. Architectures of IoMT are introduced prior to the development of the factors governing the stress monitoring decision making process and their reviews.

Urban agglomerations are a primary spatial focus of socioeconomic activity and inherently include large volumes of embodied water. We have applied the concept of water metabolism health to comprehensively evaluate the overall operation of water systems in urban agglomerations and propose an innovative assessment framework. In particular, we constructed a water metabolism network (WMN) model to simulate a water system in which different cities and sectors are integrated, combining a newly compiled multiregional input–output (MRIO) table of water flow with ecological network analysis (ENA). A case study considering the Pearl River Delta (PRD) urban agglomeration in 2015 demonstrates that its network is well synergic but highly dependent, with considerable negative effects. Highly developed cities in southeastern of the PRD exhibit higher embodied water productivity and robustness but impose considerable negative effects on the water system. We found the agricultural sector to be a dominant controller of the network; the construction and service sectors represent the primary beneficiaries with strong competition. We suggest measures at various scales to improve water utilization efficiency and promote positive interactions between components, thus improving water metabolism system health for urban agglomerations.

Food supply has been the central issue of human development for millennia and has become increasingly critical in an urbanizing world. However, the environmental footprints and associated mitigation strategies of food consumption have rarely been comprehensively characterized at urban or regional scales. Here, we analyze the water, carbon, reactive nitrogen, and phosphorus footprints of food consumption in Chinese urban regions and demonstrate how such information can help to formulate tailored mitigation strategies. The results show that in three of the largest urban regions of China, 44–93% of the four footprints are embodied in transboundary food supply. The size of the footprints and the effectiveness of mitigation measures in food supply chain vary across the environmental footprints and urban regions. However, targeting agriculture and food processing sectors in Hebei, Shandong, and Henan provinces can reduce these footprints by up to 47%. Our findings show that the analysis of the environmental footprints along the transboundary food supply chains could inform individualized and effective mitigation targets and strategies.

Carbon accounting results for the same city can differ due to differences in protocols, methods, and data sources. A critical review of these differences and the connection among them can help to bridge our knowledge between university-based researchers and protocol practitioners in accounting and taking further mitigation actions. The purpose of this study is to provide a review of published research and protocols related to city carbon accounting, paying attention to both their science and practical actions. To begin with, the most cited articles in this field are identified and analyzed by employing a citation network analysis to illustrate the development of city-level carbon accounting from three perspectives. We also reveal the relationship between research methods and accounting protocols. Furthermore, a timeline of relevant organizations, protocols, and projects is provided to demonstrate the applications of city carbon accounting in practice. The citation networks indicate that the field is dominated by pure-geographic production-based and community infrastructure-based accounting; however, emerging models that combine economic system analysis from a consumption-based perspective are leading to new trends in the field. The emissions accounted for by various research methods consist essentially of the scope 1–3, as defined in accounting protocols. The latest accounting protocols include consumption-based accounting, but most cities still limit their accounting and reporting from pure-geographic production-based and community infrastructure-based perspectives. In conclusion, we argue that protocol practitioners require support in conducting carbon accounting, so as to explore the potential in mitigation and adaptation from a number of perspectives. This should also be a priority for future studies.

Urban agriculture, including peri-urban farming, can nourish around one billion city dwellers and provide multiple social, economic, and environmental benefits. However, these benefits depend on various factors and are debated. Therefore, we used machine learning to semi-automate a systematic review of the existing literature on urban agriculture. It started with around 76,000 records for initial screening based on a broad keyword search strategy. We applied the topic modeling approach to systematically understand various aspects of urban agriculture based on the full text of around 1,450 relevant publications. Urban agriculture literature covers 14 topics, clustered into 11 themes related to urban agriculture forms, their multi-functionalities, and their underlying challenges. These forms are small-scale ground-based and building-integrated systems. The multi-functionalities include food, livelihoods, health benefits, social space, green infrastructure, biodiversity, and ecosystem services. Therefore, promoting urban agriculture requires accounting for its multi-functionalities, besides food provisioning, and encouraging efficient and sustainable practices.

China’s population–income structure has undergone significant changes. However, the impact of population expansion and changes in consumption patterns of specific income groups on regional water withdrawal has not been quantitatively assessed. Here we incorporate multiregional input–output (MRIO) tables with national survey data to capture the water footprint (WF) in the consumption of each income group in China by considering each group’s consumption patterns and population changes. The results show that the middle and rich classes contributed 83% (2012) and 89% (2015) of embodied water withdrawal, respectively. Among the driving factors leading to changes in water withdrawal, changes in consumption patterns and the population–income structure led to increases of approximately 15.4 billion m3and 12.4 billion m3, respectively. Households on the East Coast (EC), and South Coast (SC), as well as in Central China (CC), and Southwest (SW) were the key contributors to the increase. Our findings highlight essential water conservation policies to consider to meet the needs of transforming society.

The effective control of cropland soil erosion is urgent for all countries because of its threat to global food security. Cropland soil erosion is caused by agricultural production and driven indirectly by consumption. Analyzing the causes and preventive strategies from the consumption side is essential for soil erosion control. However, there is not yet sufficient research or practice. In this study, we estimated global cropland soil erosion with the revised universal soil loss equation, allocated it to specific types of crops, and quantified the cropland soil erosion footprint of the economies with a multiregional input–output analysis model. Our results showed that developed economies, usually importing cropland soil erosion from developing or agriculturally developed economies, are the beneficiaries in the current crop trading system. The European Union is the largest net importer, while Brazil is the largest exporter. The indirect and induced sectors are the main contributors, consuming approximately 70.48% of the total cropland soil erosion. Our results revealed the region- and product-specific contributors that could inform the reduction of global cropland soil erosion for sustainable food production and consumption.