This study investigates the impact of toll road construction on 59 micro, small, and medium enterprises in Kampar, Pekanbaru, and Dumai cities. The research aims to analyze the economic and environmental effects of infrastructure expansion on businesses’ profitability and sustainability, providing insights for policymakers and stakeholders to develop mitigation strategies to support MSMEs amidst ongoing infrastructure development. Structural equation modeling, spatial environmental impact analysis, and qualitative data analysis using five-level qualitative data analysis (FL-QDA) were all used together in a mixed-methods approach. Data collection involved observations, interviews, questionnaires, and geospatial analysis, including the use of a Geo-Information System (GIS) supported by drone reconnaissance to map affected areas. The study revealed that the toll roads significantly enhanced connectivity and economic growth but also negatively impacted local economies (β = 0.32, R² = 0.60, P-value ≤ 0.05). and the environment (β = 0.34, P-value ≤ 0.05), as 49% of respondents experienced a 50% decrease in profitability. To mitigate the risk of impact, policymakers should prioritize the principle of prudence to evaluate the significance of mitigation policy implementation (β = 0.144, P-value ≥ 0.05). In a nutshell, toll road construction significantly impacts MSMEs’ business continuity, necessitating an innovative strategy involving monitoring and participatory approaches to mitigate risk.

The article considers an actual problem of organizing a safe and sustainable urban transport system. We have examined the existing positive global experience in both infrastructural and managerial decisions. Then to assess possible solutions at the stage of infrastructure design, we have developed the simulation micromodels of transport network sections of the medium-sized city (Naberezhnye Chelny) with a rectangular building type. The models make it possible to determine the optimal parameters of the traffic flow, under which pollutant emissions from cars would not lead to high concentrations of pollutants. Also, the model allows to obtain the calculated values of the volume of emissions of pollutants and the parameters of the traffic flow (speed, time of passage of the section, etc.). On specific examples, the proposed method’s effectiveness is shown. Case studies of cities of different sizes and layouts are implementation examples and possible uses proposed by the models. This study has shown the rationality of the suggested solution at the stage of assessing infrastructure projects and choosing the best option for sustainable transport development. The proposed research method is universal and can be applied in any city.

The study is devoted to the problem of processing the organic waste that is generated as a result of paper, textiles and other industries production as well as food waste. The growth of economic activity in Kazakhstan has resulted in a significant challenge with regard to industrial waste management. The accumulation of waste on the territory of the country has reached 31.72 billion tonnes, comprising approximately 2.5 billion tonnes of hazardous waste, 50 million tonnes of phosphorus-containing waste, over 2.5 million tonnes of lead-zinc waste and more than 120 million tonnes of solid domestic waste. The study object was the Shymkent-Kokys polygons. According to the research carried out, it was determined that the titer of microorganisms of the studied groups is 1–10 CFU/g in the soils selected around the garbage in the area of the Shymkent landfill. The titer of microorganisms in the soil horizons was high at a depth of 20–30 cm and the titer were 10⁹ cells/mL. The structure of the soil microbiome obtained around the Shymkent Waste Landfill consists of actinomycetes, micromycetes, heterotrophic bacteria, nitrifying, nitrogen-fixing bacteria, enterobacteria, as well as algae and protozoa. It was found that strains KPA1, KPA2 Pseudomonas sp. strains KPA3, KPA4, KPA5 Bacillus sp. isolated from the soils of the Shymkent-Kokys landfill are able to recycle domestic waste with a high content of cellulose and organic substances up to 95%–97%. The findings can be used to develop more effective organic cellulosic waste management strategies and improve the environmental sustainability of various industries.

This research focuses on addressing critical driving safety issues on university campuses, particularly vehicular congestion, inadequate parking, and hazards arising from the interaction between vehicles and pedestrians. These challenges are common across campuses and demand effective solutions to ensure safe and efficient mobility. To address these issues, the study developed detailed microsimulation models tailored to the Victor Levi Sasso campus of the Technological University of Panama. The primary function of these models is to evaluate the effectiveness of various safety interventions, such as speed reducers and parking reorganization, by simulating their impact on traffic flow and accident risk. The models provide calculations of traffic parameters, including speed and travel time, under different safety scenarios, allowing for a comprehensive assessment of potential improvements. The results demonstrate that the proposed measures significantly enhance safety and traffic efficiency, proving the model’s effectiveness in optimizing campus mobility. Although the model is designed to tackle specific safety concerns, it also offers broader applicability for addressing general driving safety issues on university campuses. This versatility makes it a valuable tool for campus planners and administrators seeking to create safer and more efficient traffic environments. Future research could expand the model’s application to include a wider range of safety concerns, further enhancing its utility in promoting safer campus mobility.

The intensification of urbanization worldwide, particularly in China, has led to significant challenges in maintaining sustainable urban environments, primarily due to the Urban Heat Island (UHI) effect. This effect exacerbates urban thermal stress, leading to increased energy consumption, poor air quality, and heightened health risks. In response, urban green spaces are recognized for their role in ameliorating urban heat and enhancing environmental resilience. This paper has studied the microclimate regulation effects of three representative classical gardens in Suzhou—the Humble Administrator’s Garden, the Lingering Garden and the Canglang Pavilion. It aims to explore the specific impacts of water bodies, vegetation and architectural features on the air temperature and relative humidity within the gardens. With the help of Geographic Information System (GIS) technology and the Inverse Distance Weighted (IDW) spatial interpolation method, this study has analyzed the microclimate regulation mechanisms in the designs of these traditional gardens. The results show that water bodies and lush vegetation have significant effects on reducing temperature and increasing humidity, while the architectural structures and rocks have affected the distribution and retention of heat to some extent. These findings not only enrich our understanding of the role of the design principles of classical gardens in climate adaptability but also provide important theoretical basis and practical guidance for the design of modern urban parks and the planning of sustainable urban environments. In addition, the study highlights GIS-based spatial interpolation as a valuable tool for visualizing and optimizing thermal comfort in urban landscapes, providing insights for developing resilient urban green spaces.

Identify and diagnosis of homogenous units and separating them and eventually planning separately for each unit are considered the most principled way to manage units of forests and creating these trustable maps of forest’s types, plays important role in making optimum decisions for managing forest ecosystems in wide areas. Field method of circulation forest and Parcel explore to determine type of forest require to spend cost and much time. In recent years, providing these maps by using digital classification of remote sensing’s data has been noticed. The important tip to create these units is scale of map. To manage more accurate, it needs larger scale and more accurate maps. Purpose of this research is comparing observed classification of methods to recognize and determine type of forest by using data of Land Cover of Modis satellite with 1 kilometer resolution and on images of OLI sensor of LANDSAT satellite with 30 kilometers resolution by using vegetation indicators and also timely PCA and to create larger scale, better and more accurate resolution maps of homogenous units of forest. Eventually by using of verification, the best method was obtained to classify forest in Golestan province’s forest located on north-east of country.