Chemical pollutants are mobilized during rainfall episodes in urban and industrial areas. As a result, complex mixtures of pollutants may enter freshwater ecosystems, potentially exacerbating the individual pollutant effects on aquatic organisms and on ecosystems functioning. We investigated the ecological impacts of five runoff episodes on an urban stream (Girona, Spain) by assessing the effects on the structure and function of river biofilms, and on the community composition of macroinvertebrate assemblages. Each of the five rainfall events was evaluated independently using a Control (upstream) vs Impact (downstream of the urban runoff entrance) design. Urban runoff transported high concentrations of dissolved organic carbon, and a suite of organic (1,3-diphenylguanidine) and inorganic pollutants (zinc, copper). These added to other pollutants which were already present in the urban stream. Small-scale flood events following rainfall episodes caused biofilm detachment, confounding the effects of hydrological disturbance with those of urban runoff pollutants. Urban runoff caused peaks in nutrient, DOC and pollutant concentrations, consistently adding to an increase in chlorophyll-a content, phosphatase activity and bacterial densities in river biofilms. Macroinvertebrate composition variations mostly reflected temporal dynamics. Overall, pollutant impacts associated with urban runoff became masked by environmental factors, and effects on biofilm communities were most evident after events of moderate rainfall, which allowed pollutant-driven responses to emerge. These findings indicate that recurrent urban runoff episodes can increase ecological risks in urban streams, particularly under scenarios of increasing urbanisation and climate-driven extremes.

Daily and spatial variation of particulate matter air pollution in industrial, urban and rural areas from central Burkina Faso

Public risk perception and behavioral responses to flood-triggered Natech Events: A field investigation in industrial areas of Luzhou, China

Plastic waste has reached a major environmental crisis level. Human exposure to microplastics (MPs)- particles <5mm - is linked to toxicity, oxidative stress, inflammatory responses, neoplastic change, and numerous chronic health effects. Effective mitigation requires a thorough understanding of factors that govern MP accumulation and transport. While quantitative analyses at the polymer level remain limited, the role of land use patterns in shaping polymer abundance and movement is especially underexplored. This study addresses this knowledge gap by characterising and quantifying polymer-specific MP abundance (polyethylene (PE), polypropylene (PP), polystyrene (PS), polyethylene terephthalate (PET) and polyvinyl chloride (PVC)) in freshwater across four urban land uses (industrial, commercial, residential, and natural). Bayesian Network models were developed for two urban catchments, and a pooled model generated generalised estimates across both basins. PET and PP dominate industrial areas, while commercial areas show high PE, PVC, and PS levels. Residential areas contain elevated levels of all five polymers, and the natural regions are characterised by PE, PVC, and PS. These distinct polymer signatures reflect local activities associated with each land use. Regression outputs from the pooled model enabled quantification of individual polymer loads and prediction of concentrations at unsampled sites based on known land use profiles. Strong relationships were found between abundance and commercial/industrial land uses than with residential and natural settings. Consequently, mitigation strategies targeting industrial and commercial sectors will yield the greatest reductions in MP emissions. Study outcomes support targeted source control and efficient monitoring designs, and robust policy development for curbing microplastic pollution.

Urban expansion in areas adjacent to industrial areas presents serious safety challenges, especially in fast developing areas. Nearly between residential and industrial activities increases the risk of accidents, environmental pollution and massive disasters. In response, industrial countries have adopted advanced management systems to reduce these risks. Of these, the Geographical Information System (GIS) provides a powerful tool for analyzing and mapping the areas coming in contact with industrial threats. The purpose of this study is to assess the role of GI in reducing industrial risks and focusing a specific focus on the Algerian context, reducing industrial risks and supporting permanent urban planning. Research adopts a spatial analysis approach using topological maps, geographical datasets and GIS software. Industrial areas and surrounding urban settlements were studied through layered spatial modeling. Supplementary area observation and case studies were included to validate the accuracy of GIS output. The analysis focused on identifying weak areas, assessing industrial threats and assessing the effectiveness of existing land-use and reaction strategies. Conclusions highlight the important weaknesses in current urban risk management systems, especially in terms of preparations and integration with spatial plan. The GIS proved to be effective in detecting high-risk areas, imagining dangerous areas and providing strategic support for the decisions of land-use. The device also featured landscape simulation, which improved the understanding of potential industrial accidents and their impact on nearby communities. The interpretation of these results suggests that GI increases urban flexibility, reduces exposure to industrial threa.

This article examines the demographic development in Ekaterinburg from 1861 to 1900. The work provides a comprehensive analysis of the population composition and growth dynamics in the economic capital of Perm province, including an examination of gender composition and an assessment of both absolute and relative indicators of natural population change. The author refers to of published state and zemstvo statistics, published administrative documentation, and periodicals. The methods used include the calculation of general demographic coefficients, descriptive statistics, graphical and comparative analysis. As a result of the study of demographic processes in Ekaterinburg in the second half of the nineteenth century, it is possible to trace the gradual evolution of the city’s demographic order. Thus, the 1860s and 1870s were characterised by rapid population growth due to migration, a gender imbalance in favour of men, high variability in the number of demographic events, and natural population decline. In the 1880s, there was a significant reduction in migration, a decrease in mortality, primarily among infants, a return to a balanced gender composition, and the emergence of stable natural growth. By the 1890s, migration and mortality had declined even further, steady natural growth became an important source of population growth, and a serious gender imbalance in favour of women had developed. During the 1880s and 1890s, mortality exceeded fertility only three times: during the famine years (1883–1884, 1891–1892) and during the year of the “Russian flu” pandemic (1889). The transformation of Ekaterinburg’s demographic order from the 1860s to the 1890s actively involved the population of the surrounding rural and industrial areas through urbanisation and waves of migration resulting from agricultural and industrial crises. In addition, the modernisation of the reproduction regime played an important and gradually increasing role.

Polysulfone (PSF)-based membranes have been widely studied for various applications, particularly in wastewater treatment, heavy metal extraction, and other environmental and industrial areas. In this work, nanofiltration membranes based on PSF were prepared using the evaporation method. To enhance the performance of PSF membranes, polyethylene glycol (PEG) with two different molecular weights was used as a plasticizing additive in the PSF matrix. This study investigates the effect of doping with titanium dioxide (TiO2) nanoparticles on the stiffness, hydrophilicity, and porosity of the membranes. To characterize our membranes, several analytical techniques were used, such as, differential scanning calorimetry (DSC), rheometer, thermogravimetric analysis (TGA), contact angle measurements, and scanning electron microscopy (SEM). A photodegradation study was conducted under UV radiation for 12 weeks. UV-visible spectroscopy was used to characterize the membranes before and after aging. The results showed that adding 0.1 wt.% TiO2 nanoparticles increased the stiffness of the developed membranes, improved their thermal degradation resistance, and enhanced the contact angle and porosity of the fabricated membranes. The results of the aging study showed that the nanoparticles improve the membranes’ resistance to photodegradation.

Many studies indicate that microalgae and cyanobacteria, widely used in cosmetics, medicine, various industrial areas, and as food sources for humans and animals, have potential applications in alternative treatments. These species have high nutritional value due to their high protein, carbohydrate, and fatty acid content. Microalgae display diverse morphological and physiological features, and their biological properties vary according to the metabolites they produce. The therapeutic properties of microalgae have been investigated in numerous scientific studies. The literature reports that microalgae possess anticancer, cholesterol-lowering, anti-inflammatory, antioxidant, and antiviral activities, as well as the ability to stimulate the immune system. Interest in compounds with antiviral activity against SARS-CoV-2, which emerged in China and spread worldwide, is currently at its peak. The discovery and isolation of bioactive compounds with antiviral effects is of great importance. In this study, the antiviral effects of Arthrospira platensis, Prasinococcus sp., Nanofrustulum shiloi, Phaeodactylum tricornutum, Scenedesmus sp., and Pseudanabaena sp. were investigated. The antiviral effects of extracts from these microalgae/cyanobacteria species were assessed by in ovo experiments in the embryonated chicken egg system using the Infectious Bronchitis Virus (IBV) D274 strain, which agglutinates erythrocytes. Among the microalgae/cyanobacteria species, Pseudanabaena sp., which exhibits the lowest hemagglutination activity (log2HA=4 at 5 mg/kg and log2HA=5 at 10 mg/kg), shows the strongest and most potent antiviral activity and is more effective at 5 mg/kg than at 10 mg/kg.

UAVs are widely used for all-weather, round-the-clock security inspections in urban and industrial areas. However, pure visible-light systems fail at night or in adverse weather conditions, while pure infrared methods are limited by thermal noise, low spatial resolutions, and high false alarm rates. Multispectral images render the task of object detection highly reliable and robust by providing complementary target feature information. This study suggests a frequency-based cross-attention transformer (FCAT) for multispectral object detection as a solution to this issue. This approach collects cross-modal complementary characteristics, effectively learns and integrates global contextual information via the cross-attention mechanism, and greatly increases multispectral object detection accuracy. At the same time, spatial-domain features are mapped to the frequency domain via the Fourier transform, and the scaled dot product attention is estimated via element-wise product operations, which break through the limitation of traditional spatial-domain matrix multiplication and effectively reduce the computational cost of the model. Additionally, this study independently builds a multi-scene multi-time climate visible–infrared dataset (OPVM-VIRD), which contains 20,025 target instances, to address the issue of the lack of all-weather cross-spectral data in object detection tasks from the perspective of UAVs. Experimental findings from the OPVM-VIRD, M3FD, and FLIR datasets demonstrate that our proposed approach outperforms prevailing state-of-the-art multispectral object detection algorithms on public benchmarks, while the FCAT model achieves an mAP50 score of 94.7% on our custom-built dataset—10.8% higher than ICAF. At the same time, the number of FCAT parameters is 85.26 M, which is significantly lower than that of mainstream models, such as ICAF. Therefore, the FCAT is a change detection strategy with strong model generalization abilities, and it has important application value in the all-day and all-weather security patrol of cities and industrial parks carried out by UAVs.

Modeling community hydrogen sulfide exposure in an urban industrial area during routine and extreme events.

Abstract In this study, a comparative analysis of Multiple Linear Regression (MLR) and Geographically Weighted Regression (GWR) models was applied within the scope of Land Use Regression (LUR) analysis in order to reveal the spatial distribution of sulfur dioxide (SO 2 ) concentration in Karabük city. Fivefold cross-validation and external data validation methods were used to test the accuracy of the models. The MLR model successfully represented the distribution of SO 2 concentrations in general. However, due to the application of fixed coefficients, spatial heterogeneity could not be fully revealed. In the GWR analysis, local differences were revealed more accurately thanks to the coefficient produced separately for each sample point. In the MLR model, the overall accuracy is R 2 :0.85, the fivefold cross-validation method accuracy is R 2 :0.85, and the external data validation method accuracy is R 2 :0.92. In the GWR model, the overall accuracy is R 2 :0.95, the fivefold cross-validation method accuracy is R 2 :0.95, and the external data validation method accuracy is R 2 :0.94. In both methods, high SO 2 concentrations were observed in the southern part of the city where industrial areas are dense. In the local R 2 distribution of the GWR model, high explanation values were again obtained in the southern regions. In the residual analysis of the GWR model, it was observed that the prediction errors of the model were in the range of ± 1 µg/m 3 and were randomly distributed except for a few small local regions. According to the results, the GWR model performed better than the MLR model in both predictive accuracy and spatial heterogeneity.

Raising of the problem. Changing the original functional purpose of a building and continuing its use may be one of the promising directions for Ukraine's post-war reconstruction. The best option for revitalisation is multifunctionality, when different possibilities are combined in one building. The main questions that need to be answered when revitalising industrial buildings are: what should be the new function (or functions) of the building; how to obtain funds to finance the project; how to balance the interests of business, local authorities and the population. When carrying out work on the revitalisation of industrial buildings, a number of specific features that affect the duration and cost of the work must be taken into account: the external compactness of the construction site, the internal compactness of industrial buildings, the saturation of industrial areas with above-ground and underground engineering communications, and the complex configuration of industrial buildings. Currently, there is no single approach to the formation and selection of rational organisational and technological solutions for the revitalisation of industrial buildings, and there is no statistical information on the determining factors influencing performance indicators. Purpose of the aricle. Identifying dependencies between the duration of industrial building revitalisation and key organisational and technological factors. Conclusion. Revitalisation projects for abandoned industrial sites require: setting revitalisation priorities for both individual sites and entire areas; assessing the presence and extent of hazardous material contamination at the site and, if necessary, developing a clean-up plan to prepare industrial sites for reuse; identifying the list of necessary infrastructure facilities and the amount of investment required; analysing alternative options for revitalising industrial facilities; developing a strategy to achieve reuse goals; identifying sources of funding. The existence of statistically reliable dependencies between the duration of industrial building revitalisation and key organisational and technological factors will allow them to be used for forecasting purposes at the pre-investment stage.

Assessment of Sponge Iron Industries' Impact on Water Bodies and Total Hardness Levels in Barjora Industrial Area

The real estate market in the High Mountains region, particularly in the municipalities of Orizaba, Nogales, Río Blanco, Ixtaczoquitlán, Ciudad Mendoza, and Mariano Escobedo, has experienced remarkable growth in recent years. This growth stems from the boost in tourism, urban revitalization efforts in the historic center, the consolidation of commercial corridors, and metropolitan expansion into new residential and industrial areas. The region has become a point of interest for local and foreign investors seeking profitable opportunities in housing, commerce, services, and tourism projects. From an accounting and financial perspective, this growth does not necessarily create a favorable environment for investment. Despite the economic appeal, investors face a series of structural obstacles that hinder the accurate evaluation of project viability and limit the proper application of essential financial tools such as Net Present Value (NPV), Internal Rate of Return (IRR), and Return on Investment (ROI). One of the main problems is the lack of reliable and up-to-date information on market prices, appreciation indices, actual demand levels, construction costs, and the behavior of the real estate supply. This lack of transparent data generates a high level of uncertainty, prevents the formulation of realistic financial projections, and reduces the investor's ability to adequately estimate future cash flows, payback periods, and the level of risk associated with each project.

This research was aimed at determining the quality of groundwater by analyzing the physico-chemical parameters ‎and heavy metal content of samples from selected industrial areas (soap, food, vegetable oil and foam ‎manufacturing industries) in Jos metropolis in comparison to the contaminants in the industrial effluents. ‎Groundwater samples as well as waste-water effluents were collected from within Jos North and Jos south Local ‎Government Areas of Plateau State and analyzed using standard laboratory methods. Higher levels of ‎contamination were present in samples collected from the waste-water effluents. The pH of samples C (location) ‎and its corresponding groundwater (WC) were found to be 4.98 ± 0.04 and 5.93 ± 0.01 respectively. Concentrations ‎of anions in the various Sample, it was found that Sample B (location) and its corresponding Ground water sample ‎GB showed Nitrate ions concentration of 72mg/L and 6.5m/L respectively whereas ground water in some other ‎areas sampled were as low as 1.4mg/L. For the heavy metal concentrations, it was found that for all the samples ‎that showed the contamination of cadmium and nickel, their corresponding groundwater also showed even higher ‎levels of the heavy metal concentration. The cadmium concentrations of A and GA which are 0.003mg/kg and ‎‎0.005mg/kg respectively. The project concludes that urgent action is necessary to address this issue, including ‎establishment and enforcement of stringent regulations, advanced treatment technologies, and regular monitoring ‎of industrial effluent discharge to protect groundwater‎.

Integrated analysis of PM2.5 chemical characteristics and multi-pollutant health risks in Central Taiwan: Implications for optimizing the air quality health index (AQHI) during the COVID-19 pandemic.

Temporal trends and spatial distribution of organophosphate esters in Shanghai soils: Increasing presence of emerging OPE alternatives.

New insights into the dry deposition distribution of atmospheric microplastics in suburban, urban, and industrial areas: A focus on hawker stalls in the East Coast of Peninsular Malaysia

Improvement of indoor air quality and health effects in COPD patients in a heavy industrial area.

Numerical Simulation of Pollutant Dispersion of Industrial Area with Staggered Novel Cavity