Ecotoxicological studies of soil metal toxicity conventionally rely on the use of uncontaminated soils gradually enriched with metals in the form of soluble salts. Although this method is very useful in many ways, it is continually complicated by the difficulty of extrapolating laboratory results to actual field-collected soils exposed to decades of contamination. Although many studies emphasize the importance of using field-contaminated soils for toxicity bioassays, the number of studies actually conducted based on this premise is relatively small. This review provides an in-depth recompilation of data on metal toxicity thresholds in field-contaminated soils. We have summarized the EC₁₀, EC₂₅, and EC₅₀ values for metals, i.e., values of metal concentrations that reduce the response of specific organisms by 10%, 25%, and 50% of the value in uncontaminated soils. In our summary, most studies show that total metal content can predict organismal responses as well as bioavailable fractions. These results are consistent with the intensity/capacity/quantity concept proposed for plant nutrient uptake. In addition, microorganisms are thought to be more sensitive to metals than plants and invertebrates. However, our analysis shows that there is no statistically significant difference between the sensitivity of microorganisms and other organisms (plants and invertebrates) to any metal or metal pool. We expect that this information will be useful for environmental assessment and soil quality decisions. Finally, we encourage future studies to analyze dose-effect relationships in native field-collected soils with varying degrees of metal contamination from long-term anthropogenic pollution.

Chlorophyll-a (Chl-a) is a type of pigment is most common and predominant in all oxygen-evolving photosynthetic organisms such as higher plants, red and green algae. The concentrations of high chlorophyll-a (Chl-a) in coastal waters tend to be lower offshore due to land through river water runoff. The Madura Strait is one of the Indonesian basins that is widely used for fisheries activity, which directly impacts and puts quite high pressure on the aquatic resources. In addition, the development of urban areas and changes of land use in the hinterland areas of East Java Province due to increasing population are also intensive. The objectives of this research were: (1) to map the distribution of chlorophyll-a, its concentration and dynamics in the Madura Strait near the Pasuruan coastal area using remote sensing for both dry and rainy seasons, (2) figure out the influence of rivers or other oceanographic factors that may occur, and (3) calculate the accuracy of the estimation compared to the field data. The Landsat 8 OLI imagery was used to determine the concentration of Chl-a and analyze its seasonal spatial distribution pattern. The results show that (1) spatial distribution of chlorophyll-a (Chl-a), its concentration and dynamics in the Madura Strait waters near the Pasuruan coastal area varies between dry and rainy months or seasons, (2) input from rivers, waves, tidal level, and eddy circulation constitute the oceanographic parameters that influence the spatial distribution pattern of chlorophyll-a (Chl-a) in the Madura Strait waters near the Pasuruan coastal area, and (3) validation of the estimated Chl-a concentrations from Landsat 8 OLI using field data has shown RMSE value of 0.49.

Human intervention on vegetation cover has always had a negative impact on the environment, directly affecting the quality of life in urban areas. Therefore, this study aimed to develop a methodology for the construction of an urban environmental quality indicator (UEQI) that could reflect the environmental quality of urban areas considering the vegetation conditions to which the resident population is exposed. For this, the method sought to integrate data on demographic density (Dd), leaf area index (LAI), normalized difference vegetation index (NDVI), and surface temperature (St). The Mamdani fuzzy inference system was used to generate a rule base containing 108 variations and a defuzzed output with five condition classes, ranging from very bad to excellent. The results showed that the studied area is characterized by a very bad to good UEQI, with most neighbourhoods having poor conditions (64.51%) and only two with good conditions. It was found that in general the studied area has unsatisfactory environmental quality, showing the need for initiatives aimed at urban afforestation in order to improve the quality of life for the studied population. It can be concluded that UEQI proved to be an efficient tool to identify priority areas for the planning and management of vegetation cover in urbanized areas, enabling the improvement of people's living conditions.

Russia has often been seen in a negative light and as a difficult place for foreigners to operate, both currently and in the past. To a large extent, this is also true for Finland, which has fought several wars against its eastern neighbor and whose border with Russia has been closed for years. However, Finland, and in particular North Karelia, also has a long history of cross-border cooperation with Russian partners.

This paper seeks to analyze why North Karelian governmental and NGO actors choose to engage in cross-border cooperation with Russian counterparts and explain why they have been so successful.

The answers are sought via a historical review of the relationship between Finland and Russia, in particular the role and importance of Karelia as a source of both conflict and consolidation. Furthermore, semi-structured interviews with Finnish cross-border cooperation actors are utilized in the analysis. The theoretical approach is grounded in (un)familiarity, which is used to explain the pull-push effects of the border.

In conclusion, it was found that the Finnish actors harbor a historical feeling of connectedness and nostalgia towards the Karelian area which pulls them across the border. Because of the proximity they see cross-border cooperation as a natural extension of their work. Finally, the success is connected to the increased familiarity and close personal relations that have been build up over the years.

Emiliania huxleyi (Lohmann) evolved from the genus Gephyrocapsa Kamptner (Prymneosiophyceae) of the coccolithophore family Naёlaerhadaceae. Over the past 100 thousand years E. huxleyi has acquired the status of the most ecologically predominant coccolithophore due to its remarkable adaptability to a variety of environmental conditions and interspecific competitiveness. E. huxleyi plays an important role in both the marine carbon system and carbon cycling between the atmosphere and ocean due to its ability to produce organic and inorganic carbon as well as to form massive blooms throughout the world ocean. This study examines both older information and recent findings to shed light on the current tendencies in the two-way interactions between E. huxleyi blooms and the immediate and global environment under conditions of climate change. The assembled knowledge has emerged from laboratory and mesocosm instrumental investigations, retrievals of satellite remote sensing data, machine learning/statistical analyses, and numerical simulations. Special attention is given to both the quantitative data reported over the last two decades on such interactions, and the only very recently appearing mid-term projections of E. huxleyi bloom dynamics across the world ocean. These blooms strongly affect the atmosphere and ocean carbon cycles. They reduce CO₂ fluxes from by ~50% to ~150% as is documented for the North Atlantic, and on the global scale release particulate inorganic carbon as calcium calcite in the amounts assessed at 0.4 to 4.8 PgC/yr. At the same time, they are also sensitive to the atmospheric and oceanic state. This results in E. huxleyi blooms having an increased impact on the environment in response to ongoing global warming.

The suitability of land for C. konishii was evaluated using the analytic hierarchy process (AHP) method, which included multiple criteria, such as elevation, soil, climate, and vegetation characteristics. 120 different sites of C. konishii were studied and the model approximations were verified by a confusion matrix. The subsistence of C. konishii was mainly affected by topographic features (elevation, slope) and soil (soil texture) conditions. 15 variables were selected for the ecological analysis and construction of the land suitability map. They were combined into four main groups for weights approximation. The weights obtained by AHP were calculated as follows: topographic features (65%), soil (21.3%), climate conditions (7.4%), and vegetation type (6.3%). The total area with the highest suitability was estimated at 4, 6, 2 and 8% of the province area in Son La, Ha Giang, Thanh Hoa, Nghe An, respectively. The suitable areas for planting were located in Mai Son, Muong La, Moc Chau, Sop Cop districts of Son La province; Hoang Su Phi, Xin Man districts of Ha Giang province; Muong Lat district of Thanh Hoa province; Que Phong, Ky Son, Tuong Duong, Con Cuong districts of Nghe An province. Nghe An province has the largest suitable area for planting. The estimated AHP accuracy was 91.6%, which indicates that the approach is reliable for forestry management. The current study will provide a ground to the local population for the selection of suitable lands, ensuring the sustainability of natural resources, sustainable use and quality forest production.

Wildfires affect the structure and distribution of vegetation all over the globe and have their own specifics in different regions. In this study, we considered the spatial and temporal distribution of fires in the Jewish Autonomous Region (JAR), which is the most fire-prone area of the Russian Far East. Using data from the Department of Natural Resources of the Jewish Autonomous Region, fires and burned areas for more than 40 years were analyzed. The average annual number of fires is near 100, and the average area of one fire is 134 hectares, which is significantly higher compared to other regions of Russia. The largest number of fires and fires with the greatest extent took place in 1975. The intra-annual distribution of fires is bimodal and depends on the climate characteristics of the region. Mapping of burning areas showed that most of the fires occurred near settlements and along roads. The main centers of fire ignition were areas with a large number of small fires (no more than 5 hectares), located within several types of locations: (1) asphalt and dirt roads, railroads and river valleys near settlements; (2) areas of former logging that have several large burned spots of more than 300 hectares; (3) plains with a high concentration of fires over a large region; and (4) small burned spots on the mountain slopes, along the field roads and small rivers. Regions with different degree of fire exposure were identified. Sedge-reed mixed grassy meadows and Agricultural land with shaded meadows are the plant formations most prone to wildfires. At the same time, more fires were detected in Cedar-deciduous forests as well as Oak and black birch forests. The findings are useful for environmental protection agencies in planning fire management strategies, optimizing the fire services and firefighting actions.

Identification of urban activity centers is among the most important components of the urban structure study, it is necessary for reasonable planning, regulation of traffic flows and other practical measures. The purpose of this paper is to design a complex method to identify urban activity centers based on different but universal data types. In this study, we used social media data (Twitter) since it guarantees regular updates and does not rely on administrative borders and points of interest database that was considered a 'hard' representation of multifunctional urban activities. A large amount of geotagged tweets was processed by means of statistical modelling (spatial autoregression) and combined with the distribution analysis of points of interest. This allowed to identify the local centers of urban activity within 23 special wards of Tokyo more objectively and precisely than when only based on the social media data. Thereafter, delimitated centers were classified in order to define and describe their main functional and spatial characteristics. As a result of the study, railway transport was identified as the main attraction factor of the urban activity; the modern urban structure of Tokyo was identified and mapped; a new comprehensive method for identification of urban activity centers was developed and five classes of urban activity centers were defined and described.

Most Arab countries are part of the Sunbelt where solar insolation is among the highest in the world (as high as 9.5 kWh/m² per day). At the same time, Arab countries have a high-risk of climate change. Of the 19 countries that set new temperature high in 2010, five were Arab countries. Temperature in Kuwait reached 54.3 °C in 2019. The aims of this study were fourfold: to discuss the current situation of renewable energy in the Arab countries, to analyses the regional patterns of climate change, to secure a certain amount of the future energy needs by establishing the suitability map for renewable energy exploitation, and to assess the Jacobson's «world plan», 100% Clean and Renewable Wind, Water, and Sunlight (WWS) All-Sector Energy Roadmaps for Arab Countries according to climate change impacts 2050. To achieve these aims, the current study depended on climatic data from web-based WorldClim utility and the global climate model ECHAM5-MPIQM that downscaled by the regional climate model RegCM and CQRDEX domain. A site suitability map has been developed using the Geographic Information System (GIS). We analyzed the results based on the IPCC A2 scenario for the periods 2011-2040 and 2041-2070. We found that transforming Arab countries to a 100% WWS system as suggested by Jacobson et al. (2016) will reduce the end-user demand in 2050 by about 32%. This difference can be attributed to the conversion of fossil fuel combustions to a more efficient sustainable renewable energy.