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This work considers an industrial production site partially powered by a decentralised energy system based on intermittent renewable energy sources. Our objective is to simultaneous plan the industrial production and the energy supply in this site so as to minimise the total cost. A new way of modelling this combinatorial optimisation problem is proposed: it relies on the extension of a multi-product single-resource small-bucket lot-sizing model called the proportional lot-sizing and scheduling problem. This extension involves among others sequence-dependent changeover times overlapping multiple periods and energy-related constraints. Our numerical results show that the resulting mixed-integer linear programming model enables to obtain good-quality production and energy supply plans with a computational effort much smaller than the one required by a previously published large-bucket lot-sizing model. [ABSTRACT FROM AUTHOR]

Although wireless devices continuously gain communication capabilities, even state-of-the-art Industrial Internet of Things (IIoT) architectures, such as Internet Protocol version 6 over the Time-Slotted Channel Hopping (TSCH) mode of IEEE 802.15.4 (6TiSCH), continue to use network-wide, fixed link configurations. This presents a missed opportunity to (1) forego the need for rigorous manual setup of new deployments; and (2) provide full coverage of particularly heterogeneous and/or dynamic industrial sites. As such, we devised the Multi-Modal Minimal Scheduling Function (3MSF) for the TSCH link layer, which, combined with previous work on the routing layer, results in a 6TiSCH architecture able to dynamically exploit modern multi-modal hardware on a per-link basis through variable-duration timeslots, simultaneous transmission, and routing metric normalization. This paper describes, in great detail, its design and discusses the rationale behind every choice made. Finally, we evaluate three basic scenarios through simulations, showcasing both the functionality and flexibility of our 6TiSCH implementation. [ABSTRACT FROM AUTHOR]

Safety incidents have always been a crucial risk in work spaces, especially industrial sites. In the last few decades, significant efforts have been dedicated to incident control measures to reduce the rate of safety incidents. Despite all these efforts, the rate of decline in serious injuries and fatalities (SIFs) has been considerably lower than the rate of decline for non-critical incidents. This observation has led to a change of risk reduction paradigm for safety incidents. Under the new paradigm, more focus has been allocated to reducing the rate of critical/SIF incidents, as opposed to reducing the count of all incidents. One of the challenges in reducing the number of SIF incidents is the proper identification of the risk prior to materialization. One of the reasons for risk identification being a challenge is that companies usually only focus on incidents where SIF did occur reactively, and incidents that did not cause SIF but had the potential to do so go unnoticed. Identifying these potentially significant incidents, referred to as potential serious injuries and fatalities (PSIF), would enable companies to work on identifying critical risk and taking steps to prevent them preemptively. However, flagging PSIF incidents requires all incident reports to be analyzed individually by experts and hence significant investment, which is often not affordable, especially for small and medium sized companies. This study is aimed at addressing this problem through machine learning powered automation. We propose a novel approach based on binary classification for the identification of such incidents involving PSIF (potential serious injuries and fatalities). This is the first work towards automatic risk identification from incident reports. Our approach combines a pre-trained transformer model with XGBoost. We utilize advanced natural language processing techniques to encode an incident record comprising heterogeneous fields into a vector representation fed to XGBoost for classification. Moreover, given the scarcity of manually labeled incident records available for training, we leverage weak labeling to augment the label coverage of the training data. We utilize the F2 metric for hyperparameter tuning using Tree-structured Parzen Estimator to prioritize the detection of PSIF records over the avoidance of non-PSIF records being mis-classified as PSIF. The proposed methods outperform several baselines from other studies on a significantly large test dataset. [ABSTRACT FROM AUTHOR]

This paper presents the findings of fifteen energy audits conducted on industrial sites in Canada's Greater Toronto Area (GTA). The audits covered a range of industries including food processing, packaged goods, and finishing processes (powder-coating). The primary focus of the audits was to analyze the natural gas consumption and the performance of major-gas-consuming equipment. The audits identified natural-gas-consuming equipment that could be optimized to yield energy and operational cost savings and greenhouse gas (GHG) reduction opportunities. Food production plants' energy intensity ranges from 5.59 m3/ft2 to 17.73 m3/ft2. Therefore, there is a significant opportunity to improve energy consumption through better technology integration. The results of the audits indicate a trend of an increase in the percentage of non-productive consumption with non-productive time. The proposed energy-saving measures include reducing non-productive natural gas consumption, gas-fired equipment tune-up, optimizing boiler loads, and reducing oven exhaust by using variable frequency drives (VFDs). The findings of this study could be used to develop a demand-side management program specifically for small- and medium-sized industrial facilities in the Greater Toronto Area and other parts of Canada. [ABSTRACT FROM AUTHOR]

In industry, the task of defect classification and defect localization is an important part of defect detection system. However, existing studies only focus on one task and it is difficult to ensure the accuracy of both tasks. This paper proposes a defect detection system based on improved Yolo_v4, which greatly improves the detection ability of minor defects. For K_Means algorithm clustering prianchors question with strong subjectivity, the paper proposes the Density Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm to determine the number of Anchors. To solve the problem of low detection rate of small targets caused by insufficient reuse rate of low-level features in CSPDarknet53 feature extraction network, this paper proposes an ECA-DenseNet-BC-121 feature extraction network to improve it. And the Dual Channel Feature Enhancement (DCFE) module is proposed to improve the local information loss and gradient propagation obstruction caused by quad chain convolution in PANet networks to improve the robustness of the model. The experimental results on the fabric surface defect detection datasets show that the mAP of the improved Yolo_v4 is 98.97%, which is 7.67% higher than SSD, 3.75% higher than Faster_RCNN, 10.82% higher than Yolo_v4 tiny, and 5.35% higher than Yolo_v4, and the detection speed reaches 39.4 fps. It can meet the real-time monitoring needs of industrial sites. [ABSTRACT FROM AUTHOR]

Logistics services are integral to urban economic activity, and delving into the spatial distribution traits and evolutionary pathways of various kinds of logistics service node facilities (LSNF) is markedly valuable for understanding a city's functional spatial makeup and refining the spatial layout of logistics services. This study quantitatively and qualitatively analyzes the spatial congregation and spreading characteristics of diverse LSNFs in Wuhan in 2011, 2014, 2017, and 2020, employing kernel density analysis, average nearest neighbor index, mean center, and distance distribution frequency, seeking to characterize the spatial evolution characteristics of LSNF, alongside examining the trends in distances to city cores, principal adjoining roads, and production and consumption sites. The following conclusions were made: (1) Between 2011 and 2020, various types of LSNFs in Wuhan experienced a pattern characterized by the noticeable coexistence of spatial expansion and agglomeration, particularly visible after 2014. The degree of agglomeration is classified in a descending order as follows: CWC, STN, PSN, and PDN. (2) An "absolute diffusion" phenomenon characterizes the distribution of distances between various kinds of LSNFs and city cores or neighboring roads, with the lion's share of high-frequency distribution zones spreading beyond city cores by 5–10 km, and a majority of the LSNFs being situated within 1 km from adjacent roads. (3) While the LSNF collective exhibits a stronger tendency towards the consumption facet, it reflects a surrounding of industrial production sites on the production facet and locations of manufactured goods consumption on the consumption facet, followed by locations of agricultural product consumption and comprehensive consumption sites. [ABSTRACT FROM AUTHOR]

• A choice experiment was used to assess the preferences and willingness to pay for tangible and intangible industrial heritage. • The case study is the Baosteel steel factory, an industrial brownfield in Shanghai planned to be transformed into an arts and entertainment hub. • The results show that individuals tend to support selective rather than extensive preservation of physical attributes of the industrial sites. • Findings show there exist a demand for preserving and transmitting the intangible heritage of industrial culture along with adaptive reuse of the industrial sites. Industrial heritage has in recent years become an important component in land use and urban development policies. Yet, assessing the economic value associated with the preservation and reuse of industrial complexes remains an open question. In this paper, we apply a discrete choice experiment (DCE) method to assess the economic valuation of the Baosteel steel factory, an industrial brownfield in Shanghai planned to be transformed into an arts and entertainment hub. By eliciting the preferences of locals for the preservation and reuse of distinct attributes of the site, our findings suggest that the preservation of significant landmarks and the intangible component of the industrial site are the two most relevant attributes worth protection. Moreover, we add evidence on the relationship between respondents' economic preferences and their attitude toward the cultural value conveyed by industrial heritage by showing how distinct groups of respondents express different preferences for single attributes of the industrial heritage. The paper contributes to the heritage valuation literature by illustrating the implications and challenges of assessing the demand for industrial heritage rehabilitation projects. [ABSTRACT FROM AUTHOR]

In today's competitive landscape, manufacturing companies must embrace digital transformation. This study asserts that integrating Internet of Things (IoT) technologies for the deployment of real-time location systems (RTLS) is crucial for better monitoring of critical assets. Despite the challenge of selecting the right technology for specific needs from a wide range of indoor RTLS options, this study provides a solution to assist manufacturing companies in exploring and implementing IoT technologies for their RTLS needs. The current academic literature has not adequately addressed this industrial reality. This paper assesses the potential of Passive UHF RFID-RTLS in Industry 5.0, addressing the confusion caused by the emergence of new 'passive' RFID solutions that compete with established 'active' solutions. Our research aims to clarify the real-world performance of passive RTLS solutions and propose an updated classification of RTLS systems in the academic literature. We have thoroughly reviewed both the academic and industry literature to remain up to date with the latest market advancements. Passive UHF RFID has been proven to be a valuable addition to the RTLS domain, capable of addressing certain challenges. This has been demonstrated through the successful implementation in two industrial sites, each with different types of tagged objects. [ABSTRACT FROM AUTHOR]

Industry 4.0 is a revolution of the operations in the industrial manufacturing for increased productivity, trade and commerce. It is heavily reliant on the automation of the processes and equipment along with complex interconnectivity and insightful analysis using machine learning. The interconnectivity of the manufacturing devices from various industrial sites brings with it several security issues related to communication. This article focuses on solving the security issue of access control between such devices and enable seamless secure communication for the proper functioning of the industry. An access control scheme has been proposed that achieves the necessary security features of anonymity, traceability, and forward secrecy. It is also shown that the proposed scheme takes less communication and computational costs, and is strongly resilient against various attacks such as impersonation attack, replay attack, and denial‐of‐service attack as compared to other relevant schemes. [ABSTRACT FROM AUTHOR]

In recent years, the debate over the need to address ecological and social concerns has grown substantially. Phenomena such as the Gilets Jaunes in France or the ecological versus social disputes in industrial sites (such as, for example, the ILVA steel plant in Taranto) have constituted a trade-off in terms of potentially conflicting policies, making the understanding of the various underlying preferences very important. Furthermore, growing environmental concerns have challenged more traditional views anchored on the predominance of social and employment concerns. The article, in line with the research questions raised in the introduction of the Symposium, intends to contribute to the above-mentioned debate addressing the following questions: did the European Union take an 'eco-social' path? If so, how and why? The article illustrates the growing intertwining of social and environmental policies at the EU level and tries to explain its genesis by focusing on the role of the various actors involved. The main argument is that the European Commission, and in particular the President of the Commission, developed an eco-social agenda in order to obtain further institutional (i.e. internal) and socio-political (i.e. external) legitimation. [ABSTRACT FROM AUTHOR]

Using the example of an industrial site in Edmonton, Alberta, this paper argues that industrial ruins represent instantiations of abstract abandonment, a kind of real abstraction that directly articulates to the logic of capital. Drawing from excavations of the industrial ruins of Mill Creek Ravine, one of the first industrial areas in Edmonton, this paper reveals how sites of abstract abandonment congeal critical histories of both abandonment and its afterlives. The history of these ruins, and the communities that emerged after they were abandoned materialize the failures of capitalist fantasies, as well as the sprouts that grow in its cracks. [ABSTRACT FROM AUTHOR]

Pipelines are embedded in industrial sites and residential environments, and maintaining these pipes is crucial to prevent leakage. Given that most pipelines are buried, the development of robots capable of exploring their interiors is essential. In this work, we introduce a novel in-pipe robot utilizing Continuously Variable Transmission (CVT) mechanisms for navigating various pipes, including vertical and curved pipes. The robot comprises one air motor, three CVT mechanisms, and six wheels at the end of six slider-crank mechanisms, including three active and three idler ones. The slider crank and spring mechanism generate a wall press force through the wheel to prevent slipping inside the pipe. This capability allows the robot to climb vertical pipes and adapt to various pipe diameters. Moreover, by combining CVT mechanisms, whose speed ratios between the driver and driven pulleys are passively adjusted by the position of the slider, the robot achieves independent and continuous speed control for each wheel. This enables it to navigate pipes with various geometries, such as straight–curved–straight pipes, using only one motor. Since active control of each wheel is not needed, the complexities of the robot controller can be significantly reduced. To validate the proposed mechanism, MATLAB simulations were conducted, and in-pipe driving experiments were executed. Both simulation and experimental results have shown that the robot can effectively navigate curved pipes with a maximum speed of 17.5 mm/s and a maximum traction force of 56.84 N. [ABSTRACT FROM AUTHOR]

Chile, abundant in solar and wind energy resources, presents significant potential for the production of green hydrogen, a promising renewable energy vector. However, realizing this potential requires an understanding of the most suitable locations for the installation of green hydrogen industries. This study proposes a quantitative methodology that identifies and ranks potential public lands for industrial use, based on a range of technical parameters (such as solar and wind availability) and socio-environmental considerations (including land use restrictions and population density). The results reveal optimal locations that can facilitate informed, sustainable decision-making for large-scale green hydrogen implementation in Chile. While this methodology does not replace project-specific technical or environmental impact studies, it provides a flexible, general classification to guide initial site selection. Notably, this approach can be applied to other regions worldwide with abundant solar and wind resources, such as Australia and Northern Africa, promoting more effective and sustainable global decision-making for green hydrogen production. • Innovative spatial area scoring methodology for green hydrogen industrial site selection. • Novel quantitative approach for multi-criteria decision-making for Chile. • Integrating socio-environmental considerations, and technical factors in GH2 site prioritization. • Quantitative Scoring Framework for Identifying Optimal Green Hydrogen Deployment Sites. • Solar scenario shows 100 % of the GH2 industrial sites with scoring above 9.0. [ABSTRACT FROM AUTHOR]

Polycyclic aromatic compounds (PAHs) have been noted to generate a high risk for human health. Their presence and concentration have not been equally distributed in the environment and various anthropic activities favored the environmental presence of specific pollution components. The economic sector of bakery, as well as intensive animal breeding, are well spread worldwide and they represent a priority economic sector due to their direct link to the food industry. In this study, particulate matter (PM) and PAH pollutant compounds were monitored and their presence and concentration were correlated with specific anthropic activities such as bakery and animal husbandry. For the first time, the data analysis established correlations between PM10 or PM2.5 sizes and concentrations with a specific anthropic activity (bakery vs. animal husbandry). PM10 seemed to be more present at sites of animal husbandry activities than bakery ones. The vast majority of high PAH concentrations were detected in industrial sites such as bakeries. Spearman statistical correlation tests of intensive breeding of animals and bakery fields showed a moderate correlation between dimensional fractions of particulate matters, which indicated several emission sources, with different characteristics. [ABSTRACT FROM AUTHOR]

Industrial activities such as metallurgy, coal and oil combustion, cement production, and petrochemistry release aerosol particles into the atmosphere. We propose analyzing the aerosol composition of plumes emitted by different industrial stacks using PRISMA (PRecursore IperSpettrale della Missione Applicativa) satellite hyperspectral observations. Three industrial sites have been observed: a coal-fired power plant in Matla, South Africa (imaged on 25 September 2021); a steel plant in Wuhan, China (24 March 2021); and gas flaring at an oil extraction site in Hassi Messaoud, Algeria (9 July 2021). Below-plume surface reflectances are constrained using a combination of PRISMA and Sentinel-2/MSI images. Radiative transfer simulations are performed for each scene including the surface, background atmosphere, and plume optical properties. The plume aerosol optical thickness (AOT), particle radius, volume of coarse-mode aerosol, and soot are then retrieved within the plumes following an optimal estimation framework. The mean plume retrieved AOT at 500 nm ranges between 0.27 and 1.27 and the median radius between 0.10 and 0.12 µ m. We found a volume fraction of soot of 3.6 % and 10.4 % in the sinter plant and coal-fired plant plumes, respectively. The mass flow rate of particulate matter at a point source estimated by an integrated mass enhancement method varies from 840 ± 155 g s -1 for the flaring emission to 1348 ± 570 g s -1 at the coal-fired plant. [ABSTRACT FROM AUTHOR]

The seismic performance and safety of major European industrial facilities have a global interest for the whole of Europe and its citizens. However, the seismic design of these facilities is based on national, sometimes outdated seismic hazard analyses. The results of the commonly developed, fully harmonized newly released European Seismic Hazard Model ESHM20 provide a pertinent reference for seismic hazard at European scale and have been officially adopted as an "acceptable representation of the seismic hazard in Europe" in the ongoing revision of Eurocode 8. This study presents a large-scale investigation of the impact of the potential adoption of ESHM20 on the design of new industrial facilities as well as on the potential seismic risk of existing facilities at European level with respect to the current seismic codes. The horizontal elastic response spectra using ESHM20 in combination with the revised Eurocode 8 for selected industrial sites are compared with the respective response spectra of the national regulations for return periods of 475, 2500 and 5000 years. In addition, a single containment LNG tank is analysed for an industrial site in Germany using the design approach for liquid filled tanks according to the revised Eurocode 8. Furthermore, a deterministic and probabilistic seismic risk assessment of a vessel installed in a five-storey frame is performed for industrial sites in Greece and Germany. The examples show that a consistent procedure all over Europe would be desirable and a benefit for engineers in terms of comparability and achievement of the same safety targets. Based on the conducted illustrative studies, the consequences of a potential adoption of the revised Eurocode 8 and ESHM20 hazard maps are discussed and summarized with respect to the standard harmonisation process in Europe. [ABSTRACT FROM AUTHOR]

Furfuryl alcohol (FA) and other furanic compounds have garnered considerable attention in the quest for sustainable alternatives. FA-based resins have been used in various sectors that entail the release of FA into the environment. Hence, to ensure sustainability in this scenario, devising a dependable approach to its degradation is imperative. Given the crucial role of bacterial strains in the biodegradation of various organic pollutants, this study investigates the microbial degradation of FA, using bacterial strains isolated from sites that are constantly exposed to industrial waste. Three potential isolates were identified as B. paramycoides, B. cereus, and B. tequilensis by 16S rRNA gene sequencing. At a concentration of 300 µg/ml, these isolates demonstrated efficient FA degradation; 60–70% (at 300 µg/ml FA) and 50–60%, (at 500 µg/ml FA). Fourier-transform infrared (FTIR) spectroscopy and High-Performance Liquid Chromatography (HPLC) analysis further supported the result that the bacterial isolates consumed FA as the carbon source. Liquid chromatography-mass spectrometry (LC–MS) facilitates the detection of the major metabolic intermediate product in which FA gets transformed. The prominent peaks at 113 and 119 m/z obtained in the MS spectra of the degraded FA samples indicated the possibility of the conversion of FA into furoic acid or levulinic acid. The phytotoxicity bioassay findings revealed the non-toxic nature of the bio-transformed products as compared to pure FA. This investigation presents the initial documentation of the FA degradative potential of Bacillus strains, thereby augmenting the understanding of the prospective implementation of Bacillus species in industrial waste treatment projects. [ABSTRACT FROM AUTHOR]

The Canadian Federal Government promulgated new and lower NO2 Ambient Air Quality Standards (CAAQS) that went into effect in 2020 with additional decreases scheduled for 2025. The new hourly and annual NO2 CAAQS are 60 and 17 ppb, respectively, and the 2025 hourly and annual CAAQS are 42 and 12 ppb, respectively. The province of Alberta has also promulgated Ambient Air Quality Objectives (AAAQO) for NO2 currently set to 159 and 24 ppb on an hourly and annual basis, respectively. The Wood Buffalo Environmental Association (WBEA) in northeastern Alberta, Canada monitors NO2 at 21 community and industrial sites throughout the Athabasca Oil Sands Region (AOSR), for regulatory compliance using Thermo-Environmental (TEI) Model 42i Federal Reference Method (FRM) designated NO-NO2-NOx analyzers. The 42i measures NO directly via NO-O3 chemiluminescence, and NOx following the reduction of oxidized nitrogen to NO by a heated internal molybdenum converter. The difference between the NOx and NO channels is reported as NO2. This study presents the results of a three-year (2018–2021) WBEA comparison of four continuous NO2 analyzers: TEI 42i FRM; the API Model T500U cavity attenuated phase shift (CAPS) Federal Equivalent Method (FEM); a total reactive odd nitrogen analyzer (TEI Model 42i-Y); and a TEI 42i equipped with an external photolytic converter. The study showed that NO2 data from all analyzers were highly correlated and in general agreement, with r2 values (vs. the CAPS) ranging from 0.990–0.997 and slopes ranging from 0.933–0.992. Mean NO2 concentrations over the study period ranged from 7.2–7.5 ppb. Differences between the TEI 42i, TEI 42i-Y, and PhoNO, relative to the CAPS were all positive and highly significant (p < 0.0001), based upon nonparametric tests. The potential impact from the selection of different FRM/FEM measurement methods on current and future Canadian 2025 regulatory compliance in the region is evaluated. Implications: The study objective was to compare/evaluate different regulatory NO2 measurement techniques from a regional monitoring authority in a routine network operational context. Relatively small NO2 differences resulted in significant differences with respect to regulatory compliance triggers, particularly hourly standards based on daily extreme value statistics (e.g., 99th percentiles). For example, mean hourly NO2 △ differences ranged from 0.02–0.26 ppb over the study period but resulted in 2–3 ppb differences in the 3-year hourly CAAQS metrics. These differences could affect regulatory CAAQS and LARP compliance (management level) at monitoring sites observed during 2019 annual and 2020 hourly LARP trigger exceedances. [ABSTRACT FROM AUTHOR]

Aimed at the problems of complex industrial site environment, difficult identification of assembly features and low positioning accuracy, a new visual identification and positioning method is proposed, which can well identify and locate parts and products with different characteristics. First, combined filtering is used in preprocessing to repair low-quality images. Then, edge detection and contour finding are performed on the preprocessed image. Finally, the internal and external parameters of the camera are calculated through the camera calibration, and the acquired pixel coordinates are converted into world coordinates. The results show that the combined filtering algorithm has good noise reduction effect and can remove image surface noise, which improves the recognition accuracy for the identification and positioning of different feature parts by the subsequent contour search method, and the algorithm can meet the requirements of the actual positioning accuracy of the assembly. [ABSTRACT FROM AUTHOR]

The paper describes a continuous numerical model of polluted groundwater plumes near the LRW storage reservoirs Lake Karachay and Staroye Boloto of Mayak Production Association. This model, developed by Gidrospetsgeologiya, is based on the long-term monitoring of data obtained by Facility-Focused Monitoring System (FFMS). The model is regularly updated as the FFMS database is augmented, new data of engineering-geological and hydrogeological surveys are obtained, and new tasks are set to assess the hydrogeological safety of nuclear facilities at the industrial site of Mayak Production Association. [ABSTRACT FROM AUTHOR]

Highly accurate bending force presetting is a prerequisite to ensure the well flatness of the strip head, however, there are limitations in the preset model used in industrial sites. According to the flatness control characteristics of work roll and intermediate roll bending forces, this paper integrates the historical production data of a 1420 mm 6-high tandem cold rolling mill and establishes a chain model of bending force preset based on symbolic regression, which implements with age-layered population structure genetic programming (ALPS-GPSR). The advantage of symbolic regression models is the ability to obtain explicit mathematical expressions, which is very important in complex industrial production environments. With the application of ALPS-GPSR based bending force preset model in the industrial site, the hit rate of flatness within 6IU in the strip head for three specifications of the strip has increased by 2.86%, 1.61%, and 2.19% respectively on average, achieving a satisfactory result. [ABSTRACT FROM AUTHOR]

The industrial heritage in Spain, despite important advancements in the past decades, remains under-recognized, vulnerable, and inadequately appreciated. Its potential for contributing to local resilience and sustainability in the face of deindustrialization challenges is one of the best assets it has. This paper highlights the analysis of two case studies focused on the restoration of industrial heritage sites, namely the Sugar Mill "El Tarajal" in Malaga and the Trapiche del Prado in Marbella, conducted in collaboration between the University G. d'Annunzio of Chieti and Pescara and the University of Malaga. Four key concepts are identified: historical analysis and its impact on industrial evolution, production system transformations and their influence on buildings, the relationship between industry and its surroundings, and the impact of rehabilitation on the urban context. The recovery of industrial heritage goes beyond architectural preservation, emphasizing the importance of adapting these spaces for contemporary purposes and integrating modern technologies and sustainability approaches to drive socioeconomic revitalization. To address the vulnerabilities and lack of recognition faced by industrial heritage, a connection between research and education is discussed to disseminate knowledge among students and professionals in training. This approach aims to provide a more comprehensive and informed restoration process that considers the territorial scale, thereby translating assessment indicators into the design and preservation of industrial heritage sites. [ABSTRACT FROM AUTHOR]

Following the transnational flow of industrial heritage conservation, urban China has adopted a cultural strategy – adaptive reuse of industrial heritage – for the transformation of the inner-city industrial landscape. However, a wide gap exists between the concepts and outcomes of conservation practices in most urban regeneration projects. Taking Shanghai and Chongqing as cases, this study traces the origin, process, and outcomes of industrial heritage reuse ideas. The analysis unravels the rationale for the making of discourse on heritage in local urban policies or projects. The territorialization of an idea of adaptively reusing heritage for urban regeneration merely commenced on a poetic imagination but closed on a real estate dimension, which responds to local institutional contextual constraints. This study relates the relationality – territoriality approach to heritage studies, reveals industrial heritage reuse ideas on the move in China, and argues that the reshaping of industrial heritage reuse ideas entails territoriality and relationality. [ABSTRACT FROM AUTHOR]

Soil contamination is a significant environmental issue, and a cost-effective and environmentally friendly remediation method is essential for effective management. This paper has presented a cost analysis of the hybrid ultrasonication/ozonation (HUO) technology for the remediation of industrial sites contaminated with polycyclic aromatic hydrocarbons (PAHs). The economic feasibility of this HUO technology was evaluated and then compared to other soil remediation methods proposed by the EPA. Using the experimental and mathematical optimization, 98 optimal modes of the proposed technology, achieving a removal efficiency of 71 ± 1%, in terms of both capital expenses (CAPEX) and operational expenses (OPEX), were identified. It turned out that the average annual costs for the HUO technology were divided into 33% for OPEX and 67% for CAPEX. The most expensive component in the CAPEX was ultrasound units at 45%, followed by uncertainty, exclusive equipment, installation engineering, contractor, and site work. Regarding the OPEX, components replacement was the most contributor at 39%, followed by electrical energy, labor costs, and laboratory analysis at 36%, 23%, and 2%, respectively. The study found that the proposed method was less costly than soil washing and comparable to thermal desorption at $160/ton. It was concluded that the proposed technology was cost-effective and environmentally friendly for the remediation of industrial sites contaminated with PAHs. The paper provides valuable insights into the economic feasibility of the proposed technology, which can be significant for researchers, managers, and governmental authorities, who are responsible for selecting appropriate remediation methods for contaminated industrial sites. [ABSTRACT FROM AUTHOR]

This article examines a novel approach to visual methods that artist Ben Davis has developed based on sociologist Kevin Walby's research into decommissioned industrial sites, which is referred to here as tracing. Disrupting the over-reliance on photographic representation in visual methods in the social sciences, the authors integrate audio recordings of interviews, as well as photos, maps, and building plans for pop-up mining communities into visual art works to provide a counter-visual analysis of the landscapes depicted in Kevin Walby's photographs of Uranium City. After reviewing literature on environmental degradation and on visual methods, the article elaborates on Ben Davis's practice of tracing as a technique representing the feeling of decomposition and decay generated by the harms of industrial resource extraction. The authors argue that the technique of tracing excavates layered histories of place, providing a way of creating new interpretations of social and environmental issues. They then discuss how this counter-visual analysis and approach to tracing enables a trans-disciplinary and dialogical space for engagement with academics, artists, and activists to explore issues centered on land, contamination, and justice. [ABSTRACT FROM AUTHOR]

With the transformation and upgrading of industries, the environmental problems caused by industrial residual contaminated sites are becoming increasingly prominent. Based on actual investigation cases, this study analyzed the soil pollution status of a remaining sites of the copper and zinc rolling industry, and found that the pollutants exceeding the screening values included Cu, Ni, Zn, Pb, total petroleum hydrocarbons and 6 polycyclic aromatic hydrocarbon monomers. Based on traditional analysis methods such as the correlation coefficient and spatial distribution, combined with machine learning methods such as SOM + K-means, it is inferred that the heavy metal Zn/Pb may be mainly related to the production history of zinc rolling. Cu/Ni may be mainly originated from the production history of copper rolling. PAHs are mainly due to the incomplete combustion of fossil fuels in the melting equipment. TPH pollution is speculated to be related to oil leakage during the industrial use period and later period of vehicle parking. The results showed that traditional analysis methods can quickly identify the correlation between site pollutants, while SOM + K-means machine learning methods can further effectively extract complex hidden relationships in data and achieve in-depth mining of site monitoring data. [ABSTRACT FROM AUTHOR]

Industrial activities, through the human-induced release of Green House Gas (GHG) emissions, have been identified as the primary cause of global warming. Accurate and quantitative monitoring of these emissions is essential for a comprehensive understanding of their impact on the Earth's climate and for effectively enforcing emission regulations at a large scale. This work examines the feasibility of detecting and quantifying industrial smoke plumes using freely accessible geo-satellite imagery. The existing system has somany lagging factors such as limitations in accuracy, robustness, and efficiency and these factors hinder the effectiveness in supporting timely response to industrial fires. In this work, the utilization of grayscale images is done instead of traditional color images for smoke plume detection. The dataset was trained through a ResNet-50 model for classification and a U-Net model for segmentation. The dataset consists of images gathered by European Space Agency's Sentinel-2 satellite constellation from a selection of industrial sites. The acquired images predominantly capture scenes of industrial locations, some of which exhibit active smoke plume emissions. The performance of the abovementioned techniques and models is represented by their accuracy and IOU (Intersection-over-Union) metric. The images are first trained on the basic RGB images where their respective classification using the ResNet-50 model results in an accuracy of 94.4% and segmentation using the U-Net Model with an IOU metric of 0.5 and accuracy of 94% which leads to the detection of exact patches where the smoke plume has occurred. This work has trained the classification model on grayscale images achieving a good increase in accuracy of 96.4%. [ABSTRACT FROM AUTHOR]

Most research on air chemistry and human health has focused on negative consequences of air pollution from cities, rural dust, mining, or industrial sites. Research on nature tourism and nature therapy, in contrast, focuses on positive benefits of air quality for physical and mental health, e.g., via "clean air clean water" holidays. Aeroanions and terpenoids in forests have received particular attention, especially in China, Japan, and Korea. We review and analyse several hundred articles published in English and Chinese. With a few recent exceptions, English-language research has tested indoor negative ion generators, and concluded that they have no measurable health benefit. It has tested terpenoids in indoor aroma marketing. Chinese-language research, in contrast, has analysed fine-scale components of outdoor environments that affect concentrations of aeroanions and terpenoids: ecosystem, latitude, altitude, temperature, proximity to water, and individual plant species. Historically, health outcomes have been taken for granted, with little rigorous testing. Air quality research has shown that aeroanions can become attached to fine water droplets, e.g., after rain in forests, or in mists produced locally by waterfalls. We hypothesise that the health benefits of aeroanions in natural environments may arise through the scavenging of airborne particulates by negatively charged mists, creating especially clean, dust-free air. We propose that this particularly clean-tasting air, contrasting strongly with polluted urban air, creates positive effects on human mental health and perhaps, also on pulmonary physical health. Mechanisms and outcomes remain to be tested. We also propose testing psychological health effects of airborne terpenoid scents from forest trees. [ABSTRACT FROM AUTHOR]

Experiment and numerical simulation are combined to reveal the influence of the obstacle position on the combustion and explosion characteristics of methane–hydrogen–air mixture in a closed 90° bend pipe. The result shown that the synergistic effect of the obstacle and the hydrogen addition significantly enhances the explosion intensity of the mixed gas. Affected by the turbulent vortex near the obstacle, the flame is distorted significantly when it approaches the obstacles, thus enhancing the flame instability and accelerating the flame transition from layer to turbulence. The relative position between the obstacle and the elbow has an obvious influence on the excitation of flame propagation. When the distance between the obstacle and the elbow is more than 6 times the diameter of the pipe, the closer the obstacle is to the ignition end, the stronger the excitation effect. When the obstacle is located behind the elbow, the excitation effect of the obstacle on the flame propagation is weak. The maximum explosive overpressure in a 90° bend is influenced by the coupling of obstacles and elbows. The research results can provide theoretical guidance for the safety and explosion protection of hydrogen transportation in industrial sites. [ABSTRACT FROM AUTHOR]

This study presents a development plan for a vision AI system to enhance productivity in industrial environments, where environmental control is challenging, by using AI technology. An image pre-processing algorithm was developed using a mobile robot that can operate in complex environments alongside workers to obtain high-quality learning and inspection images. Additionally, the proposed architecture for sustainable AI system development included cropping the inspection part images to minimize the technology development time, investment costs, and the reuse of images. The algorithm was retrained using mixed learning data to maintain and improve its performance in industrial fields. This AI system development architecture effectively addresses the challenges faced in applying AI technology at industrial sites and was demonstrated through experimentation and application. [ABSTRACT FROM AUTHOR]

Light guide plate (LGP) is a key component of liquid crystal display (LCD) display systems, so its quality directly affects the display effect of LCD. However, LGPs have complex background texture, low contrast, varying defect size and numerous defect types, which makes realizing efficient and accuracy-satisfactory surface defect automatic detection of LGPS still a big challenge. Therefore, combining its optical properties, dot distribution, defect imaging characteristics and detection requirements, a surface defect detection algorithm based on LGP-YOLO for practical industrial applications is proposed in this paper. To enhance the feature extraction ability of the network without dimensionality reduction, expand the effective receptive field and reduce the interference of invalid targets, we built the receptive field module (RFM) by combining the effective channel attention network (ECA-Net) and reviewing large kernel design in CNNs (RepLKNet). For the purpose of optimizing the performance of the network in downstream tasks, enhance the network's expression ability and improve the network's ability of detecting multi-scale targets, we construct the small detection module (SDM) by combining space-to-depth non-strided convolution (SPDConv) and omini-dimensional dynamic convolution (ODConv). Finally, an LGP defect dataset is constructed using a set of images collected from industrial sites, and a multi-round experiment is carried out to test the proposed method on the LGP detect dataset. The experimental results show that the proposed LGP-YOLO network can achieve high performance, with mAP and F1-score reaching 99.08% and 97.45% respectively, and inference speed reaching 81.15 FPS. This demonstrates that LGP-YOLO can strike a good balance between detection accuracy and inference speed, capable of meeting the requirements of high-precision and high-efficiency LGP defect detection in LGP manufacturing factories. [ABSTRACT FROM AUTHOR]

Dispersion modeling is a useful tool for reproducing the spatial–temporal distribution of pollutants emitted by industrial sites, particularly in the environmental odor field. One widely used tool, accepted by regulatory agencies for environmental impact assessments, is the CALPUFF model, which requires a large number of input variables, including meteorological and orographical variables. The reliability of model results depends on the accuracy of these input variables. The present research aims to discuss a comparative study of odor dispersion modeling by initializing the CALMET meteorological processor with different input data: surface and upper air observational meteorological data, 3D prognostic data, and a blend of prognostic and measured data. Two distinct sources (a point and an area source) and two different simulation domains in Cuba and Italy are considered. The analysis of results is based on odor impact criteria enforced in some Italian regions by computing the 98th percentile of odor peak concentrations on an annual basis. For the area source, simulation results reveal that the 'OBS' and 'HYBRID' modes are largely comparable, whereas prognostic data tend to underestimate the odor concentrations, likely due to a reduced percentage of wind calms. For point sources, different input meteorological settings provide comparable results, with no significant differences. [ABSTRACT FROM AUTHOR]

Tangshan is a typical heavy industrial city in North China. Evernia mesomorpha (EV) from a remote site was exposed at the non-industrial and industrial sites of Tangshan in the winter heating period of 2016-2017 for 4 months. Concentration of 50 elements in the samples before and after exposure was measured using ICP (Inductively Coupled Plasma). The results show that exposure concentrations of the 49 elements are significantly higher than the background concentrations, coinciding with the fact that the exposure area had higher pollutant contents than the background area. The results show that exposure concentrations are significantly higher than the background concentrations which had a low variability, confirming the applicability of this lichen in active biomonitoring of atmospheric deposition of 49 elements in China. The elements are classified into crustal (Ag, Al, As, Cs, K, P, Rb, Si, Th, U, Sc, and 15 Lanthanides), atmospheric-crustal (Be, Bi, Cd, Co, Cr, Cu, Fe, Ge, Li, Mg, Mn, Mo, Nb, Ni, Pb, Sb, Se, Sn, Sr, Ti, Tl, and V), and atmospheric groups (S and Zn). PLIsite and PLIzone often reveal one class of bioaccumulation higher at industrial sites than at non-industrial sites, regardless of element sources. After taking all groups together, the bioaccumulation is evaluated as heavy and moderate at the industrial and non-industrial sites, respectively. The bioaccumulation is the highest for the atmospheric elements (heavy to severe) and the lowest for the crustal elements (low to moderate). These results indicate that EV is a good biomonitor for all elements except P. Air quality of Tangshan in winter heating period is a concern due to industrial, transport and coal combustion emissions. [ABSTRACT FROM AUTHOR]

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The article aims to analyze the pollution with Volatile Organic Compounds (VOC) emitted from the biggest refinery in Romania, using the daily and monthly series registered for two years in two sites on the industrial platform, and the carcinogenic and noncarcinogenic risks for workers at the industrial plant. Since the values of the basic statistics (minimum, maximum, and average) and outliers indicate that most recorded values exceed the maximum admissible limits established by law, the Peaks Over Threshold (POT) method was utilized to model the maximum values of the series and determine the return levels for benzene and total VOC (TVOC). Given the high values obtained for relatively short return periods, indicating potential danger for the workers, we assessed the noncarcinogenic and carcinogenic risks to benzene and TVOC exposure by computing the hazard index (HI) and lifetime cancer risk (LCR). The results indicate that 43.75% of the HI values are above 1, indicating a relatively high noncarcinogenic risk for different categories of workers. LRC indicates a high LRC for 93.75% of the workers in all considered categories exposed to TVOC. [ABSTRACT FROM AUTHOR]

With the deceleration of urban expansion, the adaptive reuse of industrial heritage buildings has emerged as a novel area of research. In previous times, the majority of approaches to adapting industrial heritage buildings relied on experiential knowledge, which lacked the ability to objectively assess the relationship between spaces and engage in rational planning. However, the social network analysis method offers an objective and comprehensive means of perceiving the spatial structure and analyzing its issues from a detached perspective. This study presents a proposal for addressing three spatial challenges encountered during the conversion of industrial heritage buildings into public buildings. It also suggests spatial optimization strategies to overcome these challenges. The Sanlinqiao Thermal Bottle Factory is selected as the research subject, and a spatial network structure model is constructed to analyze the existing issues using the social network analysis method. The proposed spatial optimization strategies are then applied, and the optimized space is evaluated through a re-analysis of the spatial layout. The spatial utilization rate has been significantly improved, leading to an effective enhancement of the spatial vitality of the site. This study presents a spatial strategy aimed at converting industrial heritage buildings into public buildings, thereby offering valuable insights for similar projects involving the transformation of industrial heritage sites. [ABSTRACT FROM AUTHOR]

The goal of the current study is to evaluate the heavy metal rainfall contamination in the vicinity brought on by the Erbil Steel Factory in Iraq during the study period. The study's findings revealed the concentration of all studied heavy metals in the precipitation near and around the factory is significantly higher than that of the rural area of Barzan village which is used as a control site. The average concentration of the metals is in descending order manganese (Mn) > lead (Pb) > iron (Fe) > arsenic (As) > cobalt (Co) > selenium (Se) > mercury (Hg) > and cadmium (Cd) for the polluted site. The geo-accumulation index (I-geo) of the heavy metal Mn in the rainfall around the steel factory site is 6.28 > 5 which indicates extreme contamination. While the Igeo values of Cd, As, and Fe are 4.87, 4.54, and 4.04 > 4 that indicate heavy to extreme contamination, for Pb, 3.80 > 3 indicates moderate to heavy contamination, Cd 1.68 > 1 indicates moderate contamination, Hg 0.46 > 0 indicates uncontaminated to moderate contamination, and Se − 0.36 < 0 indicates uncontaminated. The pollution load index (PLI) of the rainwater around the steel factory site is 13.46 > 1, demonstrating that the area is highly metal-contaminated. [ABSTRACT FROM AUTHOR]

IntroductionThe industrial activity constitutes one of the most driving sectors of a nation, as it is often considered at the center of public debate as the fulcrum of development policies. However, considering the climate impacts generated, many industries have necessarily changed, relocated, and/or interrupted their production. Due to the connection of industrial sites with the socio-economic, environmental, and health systems of cities, the real estate market dynamics can be differently affected by the presence of polluting industrial sites. With reference to the Italian context, the goal of the research is to, firstly, verify whether there is a functional relationship between the presence of polluting industrial sites and the residential real estate market dynamics, for then determining its type and the extent of purchase price affection.MethodThe proposed logical-evaluative model is based on the application of an econometric technique for investigating the significance of the industrial sites on the residential real estate dynamics through a set of technological, locational, and health variables.ResultsThe obtained results show that the total surface area of the polluting sites, the activity level and the industrial plant opening date are among the most relevant variables, instead the accessibility to the industrial site does not influence the real estate market dynamics.Discussion and practical implicationsThe main practical implication of the present research consists of the possibility to provide a support for the activation of strategies aimed at adopting sustainable development models in the industrial sector.

This study presents a development plan for a vision AI system to enhance productivity in industrial environments, where environmental control is challenging, by using AI technology. An image pre-processing algorithm was developed using a mobile robot that can operate in complex environments alongside workers to obtain high-quality learning and inspection images. Additionally, the proposed architecture for sustainable AI system development included cropping the inspection part images to minimize the technology development time, investment costs, and the reuse of images. The algorithm was retrained using mixed learning data to maintain and improve its performance in industrial fields. This AI system development architecture effectively addresses the challenges faced in applying AI technology at industrial sites and was demonstrated through experimentation and application.

Climate change and particulate matter air pollution present major threats to human well-being by causing impacts on human health. Both are connected to key air pollutants such as carbon dioxide (CO 2 ), primary fine particulate matter (PM 2.5 ), sulfur dioxide (SO 2 ), nitrogen oxides (NO x ) and ammonia (NH 3 ), which are primarily emitted from energy-intensive industrial sectors. We present the first study to consistently link a broad range of emission measurements for these substances with site-specific technical data, emission models, and atmospheric fate and effect models to quantify health impacts caused by nearly all global fossil power plants, steel mills, oil refineries and cement plants. The resulting health impact patterns differ substantially from far less detailed earlier studies due to the high resolution of included data, highlighting in particular the key role of emission abatement at individual coal-consuming industrial sites in densely populated areas of Asia (Northern and North-Eastern India, Java in Indonesia, Eastern China), Western Europe (Germany, Belgium, Netherlands) as well as in the US. Of greatest health concern are the high SO 2 emissions in India, which stand out due to missing flue gas treatment and cause a particularly high share of local health impacts despite a limited number of emission sites. At the same time, the massive infrastructure and export capacity build-up in China in recent years is taking a substantial toll on regional and global health and requires more stringent regulation than in the rest of the world due to unfavorable environmental conditions and high population densities. The current phase-out of highly emitting industries in Europe is found not to have started with sites having the greatest health impacts. Our detailed site-specific emission and impact inventory is able to highlight more effective alternatives and to track future progress. [ABSTRACT FROM AUTHOR]

Rapid establishment of closed canopy cover is a key goal in land reclamation. While re-establishment of understory vegetation is likely to positively contribute to this goal, native herbaceous species are not typically planted on reclaimed sites though it is an alternative to reliance on natural regeneration. The objective of the present study was to test the principle of hitchhiker production of a tree species with native herbaceous species on recently reclaimed industrial sites with the aim of (1) understanding growth tradeoffs when mixing these species in the same container and (2) if hitchhiking had negative growth and survival outcomes for white spruce (Picea glauca) seedlings compared with singly grown white spruce seedlings. White spruce seeds were sown in nursery containers of contrasting cavity sizes, followed by sowing a forb species (Eurybia conspicua or Chamerion angustifolium) at different time intervals or grown singly. Larger cavities and earlier sow dates were associated with higher persistence and growth of the forbs, while later sow dates were associated with larger white spruce seedlings. We observed no evidence to suggest that hitchhiked seedlings were at a competitive disadvantage in terms of growth or survival compared with singly grown seedlings that were initially similar in size. [ABSTRACT FROM AUTHOR]