Different Types Of Regions Research Articles

Will land transfer affect agricultural carbon emission efficiency? An empirical study based on provinces in China.

Studying the carbon emission efficiency of the agricultural sector plays an important role in achieving the goal of global carbon neutrality. As a common economic behavior in agricultural production, it is still unclear about that how land transfer affects agricultural carbon emission efficiency (ACEE). Therefore, according to panel data of 30 provinces (including autonomous regions and municipalities at the same level) from 2005 to 2019 in the Chinese mainland, this work adopts the panel Ordinary Least Square (OLS) to reveal the influential mechanism of land transfer on ACEE. Subsequently, the panel quantile regression and sub-sample regression are applied to divide the provinces into different types of regions, so as to explore what kind of heterogeneity effect would occur, if land transfer acts upon ACEE. Finally, this work discovers the influential mechanism of land transfer to ACEE by agricultural industrial agglomeration and agricultural land management scale. The research results support the view that the land transfer significantly inhibits the improvement of ACEE, and also prove that there is regional heterogeneity in the impact of land transfer on ACEE, and this heterogeneity is mainly reflected in the impact intensity of land transfer on ACEE in different regions. The more important and deeper discovery is that agricultural industrial agglomeration and agricultural land management scale intensify the inhibition of land transfer on ACEE. Considering that both agricultural industrial agglomeration and agricultural land management scale have a regulatory effect on the influence of the land transfer on ACEE, this work suggests that the government improve the land transfer market system, implement differentiated agricultural management measures, and reasonably promote agricultural industrial agglomeration to gradually realize economies of scale.

Multicomponent signals interference detection exploiting HP-splines frequency parameter

Multicomponent signals play a key role in many application fields, such as biology, audio processing, seismology, air traffic control and security. They are well represented in the time-frequency plane where they are mainly characterized by special curves, called ridges, which carry information about the instantaneous frequency (IF) of each signal component. However, ridges identification usually is a difficult task for signals having interfering components and requires the automatic localization of time-frequency interference regions (IRs). This paper presents a study on the use of the frequency parameter of a hyperbolic-polynomial penalized spline (HP-spline) to predict the presence of interference regions. Since HP-splines are suitably designed for signal regression, it is proved that their frequency parameter can capture the change caused by the interaction between signal components in the time-frequency representation. In addition, the same parameter allows us to define a data-driven approach for IR localization, namely HP-spline Signal Interference Detection (HP-SID) method. Numerical experiments show that the proposed HP-SID can identify specific interference regions for different types of multicomponent signals by means of an efficient algorithm that does not require explicit data regression.

The association between pasture systems, dung removal and colonization by a local Australian temperate dung beetle assemblage

Abstract Herbivore dung quality (physical and chemical parameters) varies between animal species and animal diet which is influenced by seasonal fluctuations and farm management practices. Subsequently, this influences the reproductive success of dung beetles. In Australian pasture systems, how the introduced dung beetle assemblage interacts in the field with cattle dung derived from different resources is unknown. This study quantifies the colonization by dung beetles (abundance, species richness and evenness) and removal of cattle dung derived from three common temperate pasture systems (improved native, forage oat and rye/clover pasture, henceforth dung type) over 24 h for 12 months. From the three dung types, 13 species of dung beetle were captured. Abundance and species richness were influenced by month and transect, with weak evidence for differences between dung types influencing overall abundance: Onthophagus binodis (49.7%), Aphodius fimetarius (24.4%) and Labarrus lividus (17.1%) were the most abundant species. Dung removal (organic matter) was influenced by month and dung type, with more dung buried in improved native (23.9 g) and rye/clover (24.7 g) derived dung compared with forage oat (12.3 g) dung. Dung beetle abundance was positively correlated with removal of all dung types, with O. binodis biomass significantly influencing dung removal. This study showed that diet of bovine animals weakly influences the abundance of a local dung beetle assemblage, warranting further investigation on the influence of other dung types in different regions. Improvements to reporting of pasture species and growth stage is recommended for comparisons between dung derived sources.

Challenge-oriented regional innovation systems

In this letter, we reflect on recent modifications of the regional innovation system (RIS) approach that have been prompted by persistent environmental, social, and economic problems. Scholars have begun to advocate a reorientation of the RIS framework towards addressing territorial sustainability challenges and have introduced the notion of challenge-oriented regional innovation systems (CORIS). While the CORIS approach holds promise given the challenges of our time, several unresolved issues remain. We elaborate on and discuss three themes that demand further research. Firstly, there is a need for in-depth studies of the geographies of problems. Systematic analyses of the origins and interrelations of territorial challenges are high in demand. Secondly, the geographies of challenge-oriented innovation-exnovation dynamics warrant more attention. We argue that future research should delve into questions around the development, testing and upscaling of innovative solutions, as well as the unlocking and destabilisation of unsustainable practices in various spatial contexts. Lastly, we contend that a better understanding of the geographies of RIS reconfiguration is necessary. This entails shedding light on various forms of system-level agency involved in reorienting or transforming historically-grown real-world RIS in different types of regions.

What Are the Variation Patterns of Vegetation and Its Influencing Factors in China from 2000–2020 from the Partition Perspective?

China’s vegetation ecosystem has undergone profound changes, and there is an urgent need to explore the mechanisms behind vegetation changes in different ecological sub-regions and historical periods across China. Based on NDVI (normalized difference vegetation index) data, this study analyzed the spatial and temporal evolution patterns and driving mechanisms of six ecological sub-regions in China. The results showed that: (1) over the past 20 years, the vegetation coverage in mainland China showed a decreasing trend from east to west. (2) Over the past 20 years, the vegetation coverage of the six ecological sub-regions showed an increasing trend, with the highest increase in Central Southern China (0.0039) and the lowest increase in East China (0.002). (3) The gravity center of Northeast China showed a trend of migration to the northwest. The gravity center of North China, East China, and Central South China showed a trend of migration to the southwest, while that of Northwest and Southwest China showed a trend of migration to the southeast. (4) During the period from 2000 to 2020, vegetation cover levels showed an upward trend. (5) The lag time of vegetation types in different regions was different. (6) Precipitation was the dominant influencing factor in the evolution of vegetation in Northeast China, North China, Northwest China, and Southwest China. The dominant influencing factors of vegetation evolution in East China were land use and GDP (gross domestic product), while the dominant influencing factors of vegetation evolution in Central South China were precipitation and land use.

Divergent paths for green transition: regional disparities in technology diversification

ABSTRACT This study explores the regional diversification processes into green technologies (2000–17) for different types of regions. Utilising patent and Eurostat data, we analyse these processes along the economic strength of regions and the nature of their knowledge base. Our findings reveal that both structurally strong and weak regions can successfully diversify into green technologies if they possess related technological capabilities. However, brown regions cannot do so, but regions specialised in both technologies can. While green relatedness density is important for green diversification on average, it becomes less effective in regions with strong specialisation in brown or both technologies.

Machine learning approach to predict flow fields induced by internal solitary waves acting on mid-water structures based on particle image velocimetry experiments

Mid-water structures (MWSs) have important applications in the ocean to minimize the effects of environmental factors in the surface ocean and to avoid the effects of high pressure on the seabed. However, their operational positions are vulnerable to internal solitary waves (ISWs), which poses a significant challenge to the safe functioning of MWSs. Consequently, there is a pressing need to explore the flow field characteristics surrounding MWSs under the action of ISWs to establish a reliable foundation for structural design. In this study, experimental investigations were conducted to analyze the flow fields induced by ISWs acting on MWSs, employing the particle image velocimetry (PIV) method. The intricate details of the flow fields around the structure were thoroughly analyzed, and the impact of the structure's submerged depth on the ISW-induced flow fields was discussed. A machine learning approach is utilized to develop an Artificial Neural Network (ANN) model aimed at predicting the flow fields of ISWs. The experimental results are compared and analyzed alongside the predicted outcomes, focusing on the anomaly region, the tail field region, and the occluded region. The results show that the presence of the structure complicates the flow characteristics in the tail flow regions, and the flow patterns are constantly changing. The characteristics of the ISW flow fields around the structure vary with the different submerged depths of the MWS. Positioning the MWS above the wave trough results in an ascending trend followed by a descending trend in the strength of the surrounding flow field with increasing submerged depth. The ANN predictions for different types of regions of the flow fields show satisfactory accuracy. The model closely matches the PIV results in predicting the extremes and positions of horizontal velocities in the tail flow fields at different stages of ISW trough propagation. The ANN model can be recommended for predicting the flow fields of ISWs acting on MWSs. This study offers comprehensive insights into the characteristics of the flow fields induced by ISWs acting on MWSs, emphasizing the valuable contribution of machine learning methods to the field of fluid dynamics.

Spatial and Temporal Dynamics of Ecological Parameters in Various Land Use Types in China during the First 20 Years of the 21st Century

Ecological quality in China has experienced significant improvements due to the interplay of climate change and human activities. Nevertheless, previous studies exploring the trend of ecological parameters have always overlooked the effects of land use types. Therefore, in this study, we explored the spatiotemporal variation in ecological parameters in various land use types and discussed the relationship between ecological parameters and climatic factors in China during the first 20 years of the 21st century. The results show that: (1) The area of grassland and unutilized land decreased, and the area of other land use types increased. (2) Distinct variations in the average, slope, and interval distribution of ecological parameters across various land use types were evident. Particularly significant increases in ecological parameters were observed in cultivated land and forest. (3) The influence of land use and land cover change on ecological parameters was evident. The conversion of cultivated land, forest, and grassland into water bodies, constructive land, and unutilized land resulted in a significant decrease in ecological parameters. (4) The distinct climatic conditions resulted in heightened monthly variations in the ecological parameters. Significant monthly fluctuations in ecological parameters were observed for cultivated land, forest, grassland, and constructed land, while water bodies and unutilized land did not exhibit such variations. (5) The correlation between ecological parameters and climatic factors varied considerably in various land use types in different regions.

Acquisitions, spatial heterogeneity and economic impacts in Central European non-metro-politan regions

ABSTRACT This paper aims to make a conceptual and empirical contribution to our understanding of the effects of extra-regional assets and knowledge inflow, through mergers and acquisitions (M&A), in different types of regions. We revealed that the M&A market is not geographically homogeneous, and regions differ in all aspects of the M&A market: relative position, local density and foreign attractiveness, the same as in the M&A intensity. This heterogeneity is not random but follows a spatial pattern and differences in economic fundamentals of regions, but at the same time, there is no linear relationship between economic performance and M&A performance. The regional M&A market characteristics can explain differences in the impacts of M&A transactions on the economy, especially in the exit rate of companies after acquisition and in the change of employment. The impacts of M&A on the regional economy generally do not differ by sector of the acquired company. However, some patterns show that the negative effects are more present after acquisitions of firms in tradeable sectors in the less developed regions, whereas in the stronger regions, the most vulnerable sectors belong to the part of the economy which offers mundane, but occasionally purchased (and thus substitutable) goods.

Regional innovations influence on the ecological footprint of the Russian Federation territories: case of the Siberia and Volga regions

Relevance. Ensuring the development of the country regions on the principles of environmental and economic balance, taking into account the national development goals of Russia until 2030.This article models the relationship between economic development and environmental progress. The relationship between investment in innovation and uncontrolled emissions in certain regions of Russia in the period from 2010 to 2022 is explored. Aim. To study the intensity of innovation influence on the ecological footprint, as well as the efficiency of functioning of environmental-innovative activities, in regions of different types using the example of the Siberian Federal District and the Volga Federal District. Methods. Panel regression with fixed effects, correlation analysis, DEA method, cluster analysis, analysis of variance. Results and conclusions. Using the example of 24 Russian regions, it is shown that the intensity increase of the research and development of regional companies does not always lead to an increase in the environmental footprint and an increase in emissions intensity. The obtained results indicate that the economic and environmental dimensions of sustainable development contradict each other and suggest that regional governments should consider the negative environmental externalities of economic development when designing policies to promote regional growth. It is noted that the growth of investments in the research and development of more developed regions reduce the emissions intensity level. Large industrial centers of Siberia and the Volga regions are investing in innovation to increase the intensity of emissions. The hypothesis about the high degree of the economic space heterogeneity in terms of the influence of the research and development intensity of regional companies on the degree of environmental pollution in the regions of the Russian Federation is confirmed. The necessity is emphasized to take into account the regional specifics of the industrial structure of the economy. A highly significant heterogeneity was revealed in the efficiency of environmental-innovative activities functioning in the regions of the Siberian Federal District and Volga Federal District. Moreover, the effectiveness of environmental-innovative activities of the regions is insignificantly correlated with the identified imbalance of this activity.

Research and future directions of HPV-related vaccines

Human papillomavirus (HPV) infection is a major cause of cervical lesions such as cervical cancer in women. Prophylactic vaccines developed against HPV have been widely used, but these vaccines are only effective against certain types of HPV and do not work in people who are already infected. Therefore, the development of therapeutic vaccines is also particularly important. The use of the modified poxvirus (MVA) as a vector for HPV vaccinations has garnered attention in recent years. It has been found that modified poxvirus vaccines are able to combat human papillomavirus infection and have significant safety and efficacy profiles. Based on the study of the distribution of HPV types in different regions and populations, this paper finds that there are differences in the prevalence of high-risk HPV subtypes in different regions, and that a large number of infected people need more effective treatments. At the same time, by comparing the advantages and disadvantages of preventive and therapeutic vaccines, we recognize that both have roles that cannot be replaced by the other in the task of fighting HPV, and that the two vaccines need to be developed together and complement each other in order to minimize the harm of HPV. Based on these findings, this paper provides a constructive reference for future targeted prevention and treatment of HPV in different regions of the world with different HPV distributions.

What hampers research collaboration in a region?

Research collaboration is an important instrument for innovation and knowledge transfer. In this respect, barriers that prevent or impede research collaboration between research institutions and companies are of particular importance. In this paper, we elaborate on the importance of research collaboration barriers by conducting and analysing 77 expert interviews from ten German regions. We go beyond the existing literature by examining differences in the perception of different kinds of experts and by comparing different types of regions classified according to the presence of important actors, namely research institutions and large companies. Our results show that research collaboration barriers are perceived as very significant barriers to innovation across all region types. We find differences in the perception of research collaboration barriers between the experts. On the regional level, the presence of research institutions shifts the relevance from missing partners to other research collaboration barriers, while all research collaboration barriers are not perceived as significantly less important.

A framework for quantification and integration of green development of cultivated land in China: From the perspective of adaptability‐vitality‐resistance

AbstractExploring the green development of cultivated land (GDCL) and solving the problem of “high consumption and high pollution” caused by the traditional model are of great significance for achieving sustainable use of cultivated land and green agricultural growth. However, the existing consensus on action lacks theoretical support and quantitative analysis. To this end, the objective of this study was to develop a new multidimensional framework considering as an integrated capacity to adaptability‐vitality‐resistance (A‐V‐R) assess GDCL according to the essential requirement of green development. The analytical framework and evaluation system proposed in this study are expected to provide empirical support for the green transition of cultivated land use in China or worldwide. This study determines spatiotemporal differentiation and influencing mechanism of GDCL in China from 2000 to 2020. The results demonstrated that the GDCL level of China was low and characterized by a W‐shaped fluctuation. The regional difference in GDCL is greater than that within the regions and the evolution of different types of regions showed significant path dependence and spatiotemporal inertia. The reason behind this phenomenon is that agricultural technology and socioeconomic development factors such as agricultural mechanization level, urban–rural income equity index and extensively influenced GDCL in different regions. The interaction among driving factors forms a complex multi‐resultant force to construct a comprehensive action mechanism at the GDCL level driven by demand, economy, technology, and ecology. Therefore, this study suggests coordinating the relationship between technological progress, technological diffusion, agricultural total factor productivity, and the GDCL path, in order to effectively reduce the internal and external contradictions of GDCL.

Regional diversification in Brazil: The role of relatedness and complexity

AbstractThe paper contributes to the growing literature on the relationship between relatedness, complexity and regional diversification. It explores regional diversification in an emerging economy, focusing on diversification opportunities of regions with distinct levels of local capabilities. We investigate the importance of relatedness and economic complexity for sectoral and technological diversification in all regions of Brazil during the period 2006–2019. Regions tend to diversify in sectors/technologies requiring similar capabilities to those already available locally. In general, the higher the sector/technology complexity, the lower the probability of diversification. However, in high‐complex regions, complexity reverses into a positive force for diversification. Our analysis shows diversification prospects vary widely across different types of regions in Brazil.

Molecular characterization of Escherichia coli producing extended-spectrum β-lactamase CTX-M-14 and CTX-M-28 in Mexico.

The spread of ESBL-producing Escherichia coli has constantly increased in both clinical and community infections. Actually, the main ESBL reported is the CTX-M family, which is widely disseminated between the Enterobacteriaceae family. The epidemiology of the CTX-M family shows the CTX-M-15 variant dominating worldwide, followed by CTX-M-14 and CTX-M-27. The specific ESBL-producing E. coli clones included mainly the sequence types ST131, ST405, and ST648. In this report, we present the molecular characterization of ESBL-producing E. coli clinical isolates from eight hospitals in Mexico. From a collection of 66 isolates, 39 (59%) were identified as blaCTX-M-14 and blaCTX-M-27 belonging to the group CTX-M-9. We identified 25 (38%) isolates, producing blaCTX-M-28 belonging to the group CTX-M-1. blaCTX-M-2 and blaTEM-55 were identified in one isolate, respectively. Fourteen isolates (21%) were positive for blaCTX-M-14 (13%) and blaCTX-M-28 (7.3%) that were selected for further analyses; the antimicrobial susceptibility showed resistance to ampicillin (> 256µg/mL), cefotaxime (> 256µg/mL), cefepime (> 64µg/mL), and ceftazidime (16µg/mL). The ResFinder analysis showed the presence of the antimicrobial resistance genes aacA4, aadA5, aac(3)lla, sul1, dfrA17, tet(A), cmlA1, and blaTEM-1B. PlasmidFinder analysis identified in all the isolates the replicons IncFIB, which were confirmed by PCR replicon typing. The MLST analysis identified isolates belonging to ST131, ST167, ST405, and ST648. The ISEcp1B genetic element was found at 250 pb upstream of blaCTX-M-14 and flanked by the IS903 genetic element at 35 pb downstream. The IS1380-like element ISEc9 family transposase was identified at 250 pb upstream of blaCTX-M-14 and flanked downstream by the IS5/IS1182 at 80 pb. Our study highlights the significant prevalence of CTX-M-14 and CTX-M-28 enzymes as the second-most common ESBL-producing E. coli among isolates in Mexican hospitals. The identification of specific sequence types in different regions provides valuable insights into the correlation between ESBL and E. coli strains. This contribution to understanding their epidemiology and potential transmission routes is crucial for developing effective strategies to mitigate the spread of ESBL-producing E. coli in healthcare settings.

SPATIO-TEMPORAL ANALYSIS OF THE EFFECTS OF URBAN GROWTH ON URBAN HEAT ISLAND: CASE OF KONYA, TURKIYE

Abstract. The increase in impermeable surfaces within the urban areas contributes to local and regional-scale climate changes. This phenomenon, called "Urban Heat Island," is observed as the temperature in urban areas is higher than rural areas and natural landscape areas on the urban fringe. In recent years, advances in remote sensing and geographic information system technologies have enabled the urban heat island effect to be determined more quickly, economically, and accurately. In this study, the rapidly increasing urbanization in Konya, Türkiye and the resulting urban heat island effect have been analyzed. The study consists of four steps. In the first step, land surface temperatures for 1990 and 2022 of Konya city center were determined using the thermal band of Landsat-5 TM and Landsat-8 OLI satellite images. Then, satellite images were classified using the maximum likelihood method to determine land use and land cover in Konya. The effects of land use types and urban growth on urban heat island were examined. The Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-Up Index (NDBI) analyses were examined the statistical relationships between land surface temperature. The last step, the urban heat island effects of different types of regions in the city center of Konya were determined based on their urban form, texture, structure, landscape, and planning strategy. As a result of the study, measures that can be taken especially in spatial planning and design policies have been identified to reduce and prevent the urban heat island in Konya.

Regionwise Generative Adversarial Image Inpainting for Large Missing Areas.

Recently, deep neural networks have achieved promising performance for in-filling large missing regions in image inpainting tasks. They have usually adopted the standard convolutional architecture over the corrupted image, leading to meaningless contents, such as color discrepancy, blur, and other artifacts. Moreover, most inpainting approaches cannot handle well the case of a large contiguous missing area. To address these problems, we propose a generic inpainting framework capable of handling incomplete images with both contiguous and discontiguous large missing areas. We pose this in an adversarial manner, deploying regionwise operations in both the generator and discriminator to separately handle the different types of regions, namely, existing regions and missing ones. Moreover, a correlation loss is introduced to capture the nonlocal correlations between different patches, and thus, guide the generator to obtain more information during inference. With the help of regionwise generative adversarial mechanism, our framework can restore semantically reasonable and visually realistic images for both discontiguous and contiguous large missing areas. Extensive experiments on three widely used datasets for image inpainting task have been conducted, and both qualitative and quantitative experimental results demonstrate that the proposed model significantly outperforms the state-of-the-art approaches, on the large contiguous and discontiguous missing areas.

Computed tomography radiomic features and clinical factors predicting the response to first transarterial chemoembolization in intermediate-stage hepatocellular carcinoma

BackgroundAccording to clinical practice guidelines, transarterial chemoembolization (TACE) is the standard treatment modality for patients with intermediate-stage hepatocellular carcinoma (HCC). Early prediction of treatment response can help patients choose a reasonable treatment plan. This study aimed to investigate the value of the radiomic-clinical model in predicting the efficacy of the first TACE treatment for HCC to prolong patient survival. MethodsA total of 164 patients with HCC who underwent the first TACE from January 2017 to September 2021 were analyzed. The tumor response was assessed by modified response evaluation criteria in solid tumors (mRECIST), and the response of the first TACE to each session and its correlation with overall survival were evaluated. The radiomic signatures associated with the treatment response were identified by the least absolute shrinkage and selection operator (LASSO), and four machine learning models were built with different types of regions of interest (ROIs) (tumor and corresponding tissues) and the model with the best performance was selected. The predictive performance was assessed with receiver operating characteristic (ROC) curves and calibration curves. ResultsOf all the models, the random forest (RF) model with peritumor (+10 mm) radiomic signatures had the best performance [area under ROC curve (AUC) = 0.964 in the training cohort, AUC = 0.949 in the validation cohort]. The RF model was used to calculate the radiomic score (Rad-score), and the optimal cutoff value (0.34) was calculated according to the Youden's index. Patients were then divided into a high-risk group (Rad-score > 0.34) and a low-risk group (Rad-score ≤ 0.34), and a nomogram model was successfully established to predict treatment response. The predicted treatment response also allowed for significant discrimination of Kaplan-Meier curves. Multivariate Cox regression identified six independent prognostic factors for overall survival, including male [hazard ratio (HR) = 0.500, 95% confidence interval (CI): 0.260–0.962, P = 0.038], alpha-fetoprotein (HR = 1.003, 95% CI: 1.002–1.004, P < 0.001), alanine aminotransferase (HR = 1.003, 95% CI: 1.001–1.005, P = 0.025), performance status (HR = 2.400, 95% CI: 1.200–4.800, P = 0.013), the number of TACE sessions (HR = 0.870, 95% CI: 0.780–0.970, P = 0.012) and Rad-score (HR = 3.480, 95% CI: 1.416–8.552, P = 0.007). ConclusionsThe radiomic signatures and clinical factors can be well-used to predict the response of HCC patients to the first TACE and may help identify the patients most likely to benefit from TACE.

Impact of climate and geological storage potential on feasibility of hydrogen fuels

Electrofuels, including hydrogen, methane and ammonia, have been suggested as one pathway in achieving net-zero greenhouse gas energy systems. They can play a role in providing an energy storage and fuel or feedstock to hard-to-abate sectors. In future energy systems their role is often studied in case studies adhering to specific region. In this study we study their role by defining multiple archetypal energy systems, which represent approximations of real systems in different regions. Comparing the role of electrofuels across the cost-optimized systems relying only on renewable energy in power generation, we found that hydrogen was a significant energy vector in all systems, with its annual quantity approaching the classic electricity demand. The role of renewable methane was very limited. Electrofuel storages were needed in all systems and their capacity was the highest in the northern Hemiboreal system. Absence of cavern storage potential did not hamper the significance of electrofuels but increased the role of ammonia and led to average 5.5% systemic cost increase. Systems where reservoir hydropower was scarce or level of electricity consumption was high, needed more fuel storages. The findings of this study can help for better understanding of what kind of storage and generation technologies will be most useful in future carbon-neutral systems in different types of regions.

ПРОСТРАНСТВЕННОЕ РАСПРЕДЕЛЕНИЕ И СЕЗОННАЯ ДИНАМИКА ГИДРОХИМИЧЕСКИХ УСЛОВИЙ В ВИСЛИНСКОМ ЗАЛИВЕ БАЛТИЙСКОГО МОРЯ В 2020–2022 гг.

To study current hydrochemical conditions in the Vistula Lagoon and the trend of their change under changing anthropogenic impact in 2020–2022 seasonal variability and spatial distribution of hydrochemical parameters (salinity, pH, dissolved oxygen, BOD5, mineral forms of phosphorus and nitrogen) were investigated. The water body is exposed to intense anthropogenic impact from the Kaliningrad agglomeration, the nature of which has undergone qualitative changes in recent years, therefore, a comparative analysis was carried out with the period 2007–2016, which preceded the launch of modern treatment facilities in Kaliningrad. The Vistula Lagoon is characterized by spatial variability of hydrological and hydrochemical conditions, which was considered for 4 different types of regions (eastern, near-Baltic, central and Primorskaya Bay). The impact of anthropogenic factors on the dynamics of hydrochemical conditions had the greatest impact on the eastern region and Primorskaya Bay. The eastern region of the lagoon accounts for the main inflow of nutrients from the catchment area (from the Pregola River), and since 2016 the wastewater outlet from Kaliningrad is located here. Compared to the period before 2016, in the eastern area a significant increase of BOD5, a decrease of dissolved oxygen concentrations, a multiple excess of nitrite and nitrate nitrogen in comparison with the all of the water area lagoon were recorded. In the Primorskaya Bay, where until 2016 low-purity wastewater was supplied from the city of Kaliningrad, in 2020–2022 pollution for most of the studied indicators (BOD5, phosphate phosphorus, ammonium nitrogen) decreased and corresponded to the average values for the water area. The near-Baltic and central regions are strongly affected by natural conditions (sea water inflows), where in 2020–2022, as in the previous period, lower concentrations of nutrients were observed due to the remoteness from the main sources of pollution. Despite the decrease in the intensity of local pollution in the Primorskaya Bay in 2020–2022, the concentrations of mineral forms of nutrients remained at high levels, providing intensive development of algae (including the growth of BOD5) and eutrophication of the Vistula Lagoon.