Industrial Park Research Articles

Analysis of the occurrence of heavy metals in the landfills at the former dye industry plant "Boruta" in Zgierz

The paper aims to analyse the occurrence of heavy metals (HMs) in the vicinity of a post-production waste landfill. The detection of HMs was based on the analysis of soil samples collected around the waste landfill in the Zgierz municipality. The research included soil analysis for HMs content using the atomic absorption spectrometry (AAS) method. Samples were collected in summer and winter. Soil samples were tested for physico-chemical properties. All soil samples were collected from locations accessible to residents near the former "Boruta" Dye Industry Plant in Zgierz, currently located in the Zgierz Boruta Industrial Park. The plant's activities greatly impacted the current landscape, leaving behind landfills that were a ‘ticking bomb’ in Zgierz. Products manufactured include dyes, acids, chemicals for the military, textile, pharmaceutical and food industries, furniture and agriculture.

Evasión tributaria y cumplimiento de obligaciones tributarias en el Parque Industrial de Huaycán de Ate Vitarte

The objective of the investigation was to determine the relationship between tax evasion and compliance with tax obligations in the Huaycán de Ate Vitarte Industrial Park. For this, a basic quantitative methodology was used, of a non-experimental and transversal type, using the survey technique through two questionnaires administered to 30 members of the industrial park association. The results revealed that the two-sided significance values were 0.000, below the threshold of 0.05. This indicates a significant and high relationship between tax evasion and compliance with tax obligations in the Huaycán Industrial Park, with a Rho correlation coefficient of 0.728. In conclusion, it was evident that there is a significant relationship between tax evasion and compliance with tax obligations in the Huaycán Industrial Park in Ate Vitarte. This suggests that partners who evade taxes have a tendency to be less compliant with their tax obligations, indicating a lack of tax ethics and a perception of impunity in compliance with tax laws.

Occurrence, distribution and risk assessment of phthalate esters in dust deposited in the outdoor environment of Yazd industrial park using Monte Carlo simulation

In this study, the distribution of eight phthalate esters (PAEs), namely (dimethyl phthalate (DMP), diethyl phthalate (DEP), di-n-butyl phthalate (DBP), butyl benzyl phthalate (BBP), bis (2-ethylhexyl) phthalate (DEHP), and di-n-octyl phthalate (DnOP)) were examined across fifteen sampling stations in Yazd industrial Park. All the PAEs in dust deposited in the outdoor environment were analyzed using a Gas-mass chromatography (GC-MS/MS) device. Both probabilistic and deterministic approaches were utilized to assess the non-carcinogenic and carcinogenic health risks for adult occupational population groups. These risks were associated with three exposure pathways: inhalation, ingestion, and dermal exposure to six phthalates in the dust samples. The findings revealed, among the fifteen sampling stations, highest and lowest concentrations of the PAEs in dust deposited in the outdoor environment were observed in S8 and S6, with BEHP (326.21 ± 4.35) μg/g and DMP (0.00 ± 0.02) μg/g, respectively. The total hazard index (HI) values were below one in all samples, indicating that the combined non-carcinogenic health risk from exposure to phthalates via inhalation, ingestion, and dermal pathways is within acceptable levels in each studied area. The total cancer risk (CR) values for BBP across all exposure routes were consistently low, with magnitudes ranging from 10- x 10−15to 10 x 10−11. The order of cancer risk from phthalate exposure in outdoor environments was ingestion > dermal > inhalation. The sensitivity analysis (SA) results indicated that the influential parameters in the carcinogenic risk in adult occupational population groups were concentration for inhalation and dermal pathways, as well as ingestion rate for the ingestion pathway. The result of this study provides new insight in to PAEs pollution and risk assessments related to the dust deposited in the outdoor environment of industrial Park. Furthermore, this finding is beneficial to the controlling the exposure and promoting steps to reduce PAEs contamination and manage health in the industrial area.

Distribution and Risk Assessment of VOCs in Road Dust Across Different Urban Areas

ABSTRACT Volatile organic compounds (VOCs) are significant pollutants in urban road dust, but their distribution and associated health risks remain unclear. VOC distribution in road dust from six distinct urban areas in Beijing Daxing District, China was systematically investigated. Eighteen VOCs were detected, with the highest load in commercial areas (7.73 μg/g), followed by industrial parks (6.38 μg/g), residential areas (3.35 μg/g), leisure areas (2.79 μg/g), traffic areas (2.01 μg/g) and urban-rural fringe (1.85 μg/g), much lower than in air and water phases. Typical VOCs in road dust include methyl tertiary butyl ether (MTBE) (0.82–1.24 μg/g), benzene series compounds (0.02–4.19 μg/g) and volatile halogenated alkanes (0.002-0.095 μg/g). Incomplete combustion of road vehicle fuels is the key source of VOCs. Particular attention was given to VOCs in typical sites within the urban-rural fringe, known for their unique pollution characteristics. The VOCs loads were ranked as follows: Gas Stations (2.61–2.62 μg/g) > Intersection (1.41 μg/g) > Main Road (1.34 μg/g) > University Gate (1.27 μg/g). Increased vehicle activity and frequent stalling contribute to higher VOCs accumulation in road dust. Health risk assessment indicates there is no appreciable non-carcinogenic risk associated with exposure to road dust VOCs. Further research should consider VOCs in the broader environmental context, including air and water.

Business performance of various products of self-help groups under Mahatma Gandhi rural industrial park in Sankra, Durg district of Chhattisgarh

Business performance of various products of self-help groups under Mahatma Gandhi rural industrial park in Sankra, Durg district of Chhattisgarh

Industrial park wastewater treatment using a combined sono-pulsed electrochemical-coagulation process

Maintaining sustainable water management practices, preserving ecosystems, and safeguarding public health has depend on the treatment of wastewater. It has a significant impact on reducing water pollution and protecting the water supplies. Sono-pulsed electrochemical oxidation (S-PEO) process is a wastewater treatment method that uses ultrasound (US) waves and electrochemistry to enhance the pollutant removal efficiency. This study aim is to investigate the mineralization of industrial park wastewater by using pulsed electrochemical oxidation (PEO) and a combination of sonolysis and pulsed electrochemical oxidation (S-PEO) processes. The research focuses on the percentage elimination of chemical oxygen demand (COD) and color, as well as the assessment of power consumption. The study considers the influence of experimental parameters like initial pH, electrolysis time, and current to find the optimum conditions for maximum percentage removal efficiency with minimization of power consumption. According to the study, the optimum values of responses for the S-PEO process were obtained at pH=7, electrolysis time=40 min, and current =0.5 Amp. The optimum values for the maximum removal percentages of the responses COD and color were 97.04 %, and 99.70 %, respectively. The minimum of power consumption for S-PEO was 0.19 kWh/m3. These results demonstrate that, the superior efficiency of the S-PEO process and its feasibility in the removal of industrial wastewater pollutants. Optimizing parameters like pH, time, and current intensity is crucial for optimal performance, reducing energy consumption and operational costs. The S-PEO technique eliminates pollutants from wastewater efficiently and effectively, making it the suitable process when compared to the others.

A superstructure-based model for the evolution of park-wide water infrastructure

Industrial parks are crucial to improve material efficiency, economic growth, as well as environmental protection. The increasing demand of freshwater poses a significant challenge for the sustainable development for industrial parks. This work reviews the evolution process of park-wide water infrastructure. A superstructure-based model was used to address the trade-off between water reuse and its impact on the wastewater treatment for the evolutionary state of water infrastructure. In the evolution process of park-wide water infrastructure, five scenarios were defined based on the evolution process of water infrastructure. For wastewater treatment system, centralized or decentralized wastewater treatment plants were deployed according to the evolutionary process of park-wide water infrastructure. The relationship among freshwater consumption, wastewater treatment, and discharge quality were investigated by optimizing the configuration of park-wide water infrastructure. The results indicate that the cost of park-wide water infrastructure with centralized wastewater treatment plant is lower than that with decentralized wastewater treatment plants. Improving the effluent standards for centralized wastewater treatment increases the total cost. For regeneration and reuse, improving the effluent standard for centralized wastewater treatment does not necessarily increase the total cost. The findings indicate that improvement in the discharge standard of centralized wastewater treatment depends on the specifications of the centralized wastewater treatment.

EVALUATING WASTEWATER TREATMENT EFFICIENCY OF MEDICAL CENTERS IN BINH DUONG PROVINCE

This paper presents a comprehensive analysis of the wastewater management system implemented at a medical center located within the Bau Bang Industrial Park in Binh Duong province, Vietnam. With a staff of 166 and 60 beds, the facility operates in accordance with TCVN 4470:2012 General Hospital design standards, serving a diverse range of water demands including domestic, medical, and auxiliary requirements. The wastewater management system is meticulously designed to handle both rainwater and wastewater separately. Rainwater is efficiently collected through surface and roof drainage networks, while domestic and medical wastewater undergo discrete collection processes. The medical center's wastewater treatment facility, operating at a capacity of 100 m³/day, employs a multistage treatment process to ensure compliance with stringent regulatory standards (QCVN 28:2010/BTNMT, column B, K = 1). This process includes preliminary treatment, anaerobic and aerobic biological treatment, membrane filtration, and disinfection. The facility consistently meets quality parameters outlined in QCVN 28:2010/BTNMT, exhibiting effective removal rates for organic pollutants, suspended solids, ammonia, phosphates, and pathogens. Furthermore, the medical center demonstrates commendable environmental stewardship through its stormwater drainage infrastructure, which integrates seamlessly with the local drainage network, safeguarding against environmental contamination. Overall, the wastewater management practices at the medical center exemplify best practices in environmental management within the healthcare sector. This study provides valuable insights into the design, implementation, and performance evaluation of wastewater treatment systems in industrial settings, contributing to the global discourse on sustainable wastewater management practices.

Low‐carbon optimal scheduling strategy for multi‐agent integrated energy system of the park based on Stackelberg–Nash game

AbstractUnder the background of achieving the dual‐carbon goal, the park is a natural experimental field for practicing the dual‐carbon goal. A low‐carbon optimal scheduling strategy for a multi‐agent park‐integrated energy system (P‐IES) based on the Stackelberg–Nash game is proposed. Firstly, a low‐carbon P‐IES scheduling model is established, considering the two‐stage operation of power‐to‐gas (P2G) technology and reward–punishment stepwise carbon trading mechanism. Then, a two‐layer game optimisation model is proposed with a park‐integrated energy system operator (P‐IESO) as the leader and multiple low‐carbon P‐IESs as followers. Among them, the parks are connected with each other through the power trading channels. Then, the Nash equilibrium solution is obtained by the iterative search method, and the uniqueness of the equilibrium solution of the game is proven, so as to determine the optimal pricing strategy of the operator. Finally, a typical industrial park is taken as an example for simulation verification. The example analysis verifies that the model can effectively reduce the system's carbon emissions and improve the park's economic benefits and low‐carbon levels, thereby achieving the coordinated development of low‐carbon and economic performance in the park.

PROMOTION OF SMES ESTABLISHMENT AS PART OF THE INDUSTRIAL PARKS TRANSFORMATION

This study examines the role of small and medium-sized enterprises in transforming industrial parks into eco-industrial parks and focuses on strategies for small and medium-sized enterprises’ engagement. The relevance of the topic stems from the growing need to implement sustainable development principles, which are increasingly demanded by companies with international investments. These principles require industrial sites to balance economic and environmental indicators through the creation of eco-friendly industrial systems. SMEs are crucial to this process due to their flexibility, capacity for innovation, and efficient resource use. However, their integration into industrial parks faces significant barriers, such as limited financial resources, technical expertise, and infrastructure, making this issue critical for investigation. The study employs inductive analysis of scientific literature, case studies, and reports on eco-industrial parks development and small and medium-sized enterprises’ support. Findings indicate that small and medium-sized enterprises significantly enhance the economic vitality of industrial parks by creating jobs, fostering innovation, and expanding production capacity. However, in countries like Ukraine, the involvement of small and medium-sized enterprises is hindered by financial, regulatory, and technical challenges. The article proposes a methodology for developing strategies to attract small and medium-sized enterprises to industrial parks, which will enhance their alignment with eco-industrial standards and promote sustainable regional development.

Spatial Distribution and Location Determinants of High-Tech Firms in Shenzhen, a Chinese National Innovative City

The development of high-tech firms is a vital driver for the economic growth of a city but their distribution and location determinants at the intra-urban level are still unclear. We aim to deepen the understanding of location determinants of high-tech firms, so we construct an analytical framework and use GeoDetector to investigate high-tech firms in Shenzhen based on firms and POI open data in 2023. We find that high-tech firms are distributed in a spatial pattern of ‘one core and six clusters’ with high density in the western area despite industrial heterogeneity. Agglomeration economies and amenity-based factors play a significant role in the distribution of high-tech firms. Institutional factors and classical locational factors have more significant effects on the location of high-tech service and manufacturing firms, respectively. This study contributes to the literature on study spatial units, the influence of amenities, and industrial specificities. These findings highlight public policies on industrial park planning, transportation systems, and public services.

Exploring ecological compensation standards in the urbanization process: An ecosystem service value-based perspective

Understanding the spatiotemporal changes in ecosystem service value (ESV) under urbanization, as well as the supply–demand relationship between different regions, can provide a consultation for ecological compensation (EC) standards. Taking Suzhou, a typical city experiencing rapid urbanization in the Yangtze River Delta, as a case study, this paper analyzes the spatiotemporal changes in land use and ESV from 2000 to 2020. To quantify the ecosystem service flow (ESF), we apply the breakpoint formula and field strength model. Additionally, an EC standard is established, taking population, area and GDP into account while specifying compensation. The findings reveal that urbanization has led to a substantial increase in built-up land in Suzhou, accompanied by continuous reductions in farmland and water bodies. As a result, ESV decreased from 153.07 billion CNY to 138.81 billion CNY. Furthermore, the research identifies a spatial pattern where ESV increases with distance from the city center but decreases with distance from the lake center. This pattern suggests a directional flow of ESV from lakes to cities. Notably, ESF mainly occurs in the southwestern and central areas of Suzhou, with areas closer to Taihu Lake experiencing greater ESV transfer. The transfer value ranges from 5.11 and 32.57 billion CNY. There is an imbalance between the supply and demand of ecosystem services. Therefore, specific county-level cities in Suzhou, namely, the Kunshan District and Industrial Park, emerge as contributors of EC and should contribute 71.94 and 80.74 billion CNY, respectively, to other cities. By formulating a novel EC policy for Suzhou, this paper provides a scientifically informed reference for promoting sustainable development.

An evolutionary game analysis of incentive of industrial parks, government support and enterprise innovation willingness in China

Industrial parks are the important carriers to promote regional innovation and economic development. The policy preferences of the government, the support orientation of the industrial park and the innovation willingness of the enterprises in the park play a significant role in promoting the high-quality development of the industrial parks. In order to clarify the decision-making process of each subject, this paper constructs a triple evolutionary game model between the government, industrial park and enterprises in the park, Matlab software is used to conduct simulation research, and the strategy selection of each subject in the process of promoting high-quality development of the park is analyzed, as well as the influence of variables on the evolutionary game. Through numerical simulation, this study finds that the strategy choice of the government and the industrial park is influenced by the cost of innovation management for enterprises. In addition, the innovation willingness of enterprises is affected by the policy preference of the government and the support orientation of the industrial park, the excessive tax preference of the government will lead to negative innovation behaviors of the enterprises, the “inward incentives” support orientation of the industrial park can stimulate the enterprises’ innovation willingness on “active innovation”, the enterprises behavior of “active innovation” will strengthen the “inward incentives” support orientation of the industrial park in turn. The difference of the benefits and the costs between the two support orientations by the industrial park will lead to the equilibrium points stabilized at different strategy combinations. Based on these findings, countermeasures and suggestions are proposed in this study.

Research on Machine Learning-Based Method for Predicting Industrial Park Electric Vehicle Charging Load

To achieve global sustainability goals and meet the urgent demands of carbon neutrality, China is continuously transforming its energy structure. In this process, electric vehicles (EVs) are playing an increasingly important role in energy transition and have become one of the primary user groups in the electricity market. Traditional load prediction algorithms have difficulty in constructing mathematical models for predicting the charging load of electric vehicles, which is characterized by high randomness, high volatility, and high spatial heterogeneity. Moreover, the predicted results often exhibit a certain degree of lag. Therefore, this study approaches the analysis from two perspectives: the overall industrial park and individual charging stations. By analyzing specific load data, the overall framework for the training dataset was established. Additionally, based on the evaluation system proposed in this study and utilizing both Multilayer Perceptron (MLP) and Long Short-Term Memory (LSTM) algorithms, a framework for machine learning-based load prediction methods was constructed to forecast electric vehicle charging loads in industrial parks. Through a case analysis, it was found that the proposed solution for the short-term prediction of the charging load in industrial park electric vehicles can achieve accurate and stable forecasting results. Specifically, in terms of data prediction for normal working days and statutory holidays, the Long Short-Term Memory (LSTM) algorithm demonstrated high accuracy, with R2 coefficients of 0.9283 and 0.9154, respectively, indicating the good interpretability of the model. In terms of weekend holiday data prediction, the Multilayer Perceptron (MLP) algorithm achieved an R2 coefficient of as high as 0.9586, significantly surpassing the LSTM algorithm’s value of 0.9415, demonstrating superior performance.

Does self-containment of spatial scale and land use function contribute to mitigate urban heat island effects? Lessons from new towns in Shanghai

The concept of self-containment in new towns has been widely discussed from social and economic perspectives. However, localized interpretations within the context of China's development, particularly regarding climate adaptability and urban heat island (UHI) mitigation, are scarce. To fill this gap, our research analyzed self-containment from the perspectives of urban spatial scale and land use function. Focusing on Shanghai’s five new towns, we empirically demonstrated how self-containment influenced the UHI effects from 2005 to 2020, employing the Geodetector method. The findings reveal that during the daytime, the intensity of UHI in new towns decreased, serving as vital connectivity nodes of UHI within the region. Conversely, during the nighttime, both the intensity and area of UHI showed an increasing trend. The research confirmed that expanding the urban scale and functional diversity are effective strategies for mitigating the UHI. Based on these findings, we offer practical suggestions for the development of new towns: Increase population size while ensuring coordination with development scale; enhance mixed-use functions in large-scale development projects like university towns and industrial parks; and be vigilant of potential functional decline in central areas and increasing thermal impact due to new town development. Overall, this study enriches our understanding of self-containment in Chinese new towns and provides valuable insights for mitigating UHI in other similar contexts.

Research on the dangerous scenarios of propylene oxide leakage from tank in a chemical plant in an industrial park of Tongling City, China

ABSTRACT Propylene oxide (PO) is toxic, flammable and explosive. Accidents from the release of PO from large-scale storage tanks can have disastrous consequences associated with meteorological conditions. Therefore, this study explores the dangerous scenarios of PO leakage from a 1000 m3 spherical tank in a chemical plant located in an industrial park during various seasons using the Aerial Location of Hazardous Atmospheres software. Our results show that the maximum hazard distance of poisoning, flash fire and vapour cloud explosion caused by leakage and diffusion from the PO storage tank occur in the summer season and the affected distances were 2900, 372, and 374 m, respectively. In regard the thermal radiation resulting from a pool fire scenario, the longest threat distance was 110 m in the summer. For the boiling liquid expanding vapour explosion (BLEVE), the maximum thermal effect was 2100 m in winter. The BLEVE scenario has the largest impact area and its toxic vapour cloud is the primary accident. Adequate safety management and technical measures should be put in place for the prevention and emergency response of accidental PO release in the factory.

Construction of a Coal Chemical Industry Park with Zero Carbon Emission by Integrating Renewable Energy Based on Life Cycle Analysis

Construction of a Coal Chemical Industry Park with Zero Carbon Emission by Integrating Renewable Energy Based on Life Cycle Analysis

Intelligent road extraction from high resolution remote sensing images based on optimized SVM

Road recognition and extraction based on high-resolution remote sensing images is currently a hot issue at the forefront of image processing and other disciplines, and its results not only help to enrich geographic information, but also have important application value in national defence construction and other aspects. For the intelligent extraction of roads in high-resolution remote sensing images, the study firstly preprocesses these images, and then extracts the roads by using variational function and support vector machine. As the extraction results are not satisfactory enough, the 3D wavelet transform technique is used to extract the spectral features of roads in the frequency domain, combined with the texture in the time domain, and optimized the support vector machine in order to extract the road images more accurately. The outcomes denote that in contrast with other methods, the optimized method can have optimal correctness and quality while guaranteeing higher integrity. The satellite road image of Chengdu A industrial park is rich in extracted information, having the highest completeness of 94.23%, correctness of 60.73%, and quality of 59.42%, and the satellite road image of Chengdu B industrial park is similarly rich in extracted information, having the highest completeness of 83.47%, correctness of 85.31%, and quality of 72.85%. The highest value of CPU usage for road extraction was 2000 kb at 37 s, and the average value of CPU usage for the whole 60 s was 500 kb. It shows that the research method has good results in high resolution remote sensing image road extraction.

Lab-Scale Treatment of Anaerobic Co-Digestion Liquor from Kitchen Waste, Human Feces, and Municipal Sludge Using Partial Nitritation-Anammox Process

Effective nitrogen removal from anaerobic co-digestion is a major challenge to achieving dual-carbon goals. This study explored the acclimatization process of a lab-scale two-stage partial nitritation and anammox process of a stepwise increase in the percentage of raw anaerobic co-digestion liquor from kitchen waste, human feces, and municipal sludge in a venous industrial park in China, which has not been reported yet. Under limited dissolved oxygen (below 0.5 mg/L) and high ammonia levels (200–1500 mg/L), based on adjusting aeration rates, partial nitritation rapidly started up in 50 days. After acclimatization, partial nitritation still performed efficiently and stably, with the final total nitrogen loading rate (TNLR) of 1.24 ± 0.09 gN/L/d, nitrite accumulation rate of 99 ± 4%, and ratio of eff. nitrite/ammonia of 1.32 ± 0.13. In the anammox process, the final total nitrogen removal efficiency, total nitrogen removal rate, and TNLR reached 94 ± 5%, 1.27 ± 0.03 gN/L/d, and 1.36 ± 0.05 gN/L/d, respectively. Chemical oxygen demand (COD) was also reduced in both reactors, with COD removal rates of 0.7 gCOD/L/d in the partial nitritation and 0.4 gCOD/L/d in the anammox process. Overall, the PNA system demonstrated its feasibility in adapting to high ammonia, salinity, and iron levels, when treating anaerobic co-digestion liquor, particularly regarding resource recovery in venous industrial parks.

The influence of two and three-dimensional spatial characteristics of industrial parks on the emotional well-being of employees: A case study of Shenzhen

Enhancing the emotions of the workers within industrial parks is crucial for achieving the sustainable development goal (SDG). However, evidence on the impact of industrial park environmental layouts on emotions is limited due to the low attention on the workers in the industrial park. Based on a framework of two-dimensional (2D) industrial park morphology indicators and three-dimensional (3D) spatial objective perception, this study aims to compare and analyze the effect of environmental characteristics in Shenzhen's industrial parks on workers' emotions by using emotional geography and social media data. The potential mechanism that environmental characteristic variables influence the positive emotion index (PEI) is also explored. Using the natural language processing (NLP) to analyze the Weibo check-in data, the study captures the daily emotions of workers in industrial parks. By adopting the linear and spatial regression models, this research reveals the complex relationship between the environmental layout of the total 425 industrial parks in Shenzhen city and the corresponding emotions of the workers. The conclusions are as follows: (1) There is a significant correlation between the environmental layout of the industrial parks and the emotions of the workers, with the correlation among 3D variables being higher than that among 2D variables considering spatial effects. (2) There is a certain degree of coordination and contradiction between the morphological indicators of the industrial parks and the spatial objective perception variables, necessitating the planners to consider both macro-scale and micro-perception environmental characteristics to enhance the workers' emotions. (3) In addition to higher accessibility and more public transportation options, the safer, wider, relatively more open streets, more perceivable green spaces, and richer street life can promote the positive emotions among the workers. On the contrary, the enclosed environments, the dense and overwhelming buildings, and the excessive road density may lead to negative emotions. This study contributes to establish the environmental layouts for the industrial parks that foster positive worker emotions and offer insights for the sustainable development of the industrial parks.