This research addresses a gap in localized air quality assessments by measuring pollution levels in Klaipeda, a Baltic port city, using passive solid particle collectors and nitrogen dioxide (NO₂) diffusion tubes. Passive sampling techniques were employed due to their cost-effectiveness and ease of deployment, allowing for practical monitoring over short-term periods. By targeting diverse functional zones, this study aims to provide a comprehensive analysis of air pollution patterns and seasonal variations in the region. Air pollution, primarily from NO₂ and particulate matter (PM), poses significant risks to public health, especially in densely populated urban areas. Air quality was assessed by measuring total suspended particulates (TSP) and NO₂ concentrations across 19 strategically chosen sites, covering key functional zones, such as industrial areas, green spaces, residential neighborhoods, transport hubs, and the port. Results show elevated pollution levels near major roads and the port area, likely driven by heavy traffic, industrial emissions, and port activities. These patterns correlate with areas of higher population density, highlighting the intersection of air quality challenges with human health risks in urbanized zones. Seasonal data reveal a notable peak in NO₂ concentrations during winter, likely due to increased heating demand and reduced atmospheric dispersion. These findings suggest that air quality management strategies should be adaptive to seasonal fluctuations, particularly by addressing emissions from heating sources in colder months. The study underscores the necessity of integrating sustainable urban planning with targeted air quality interventions. Expanding green spaces, enhancing traffic regulation, and establishing protective zones near industrial areas are critical strategies for mitigating pollution. These insights are essential for guiding both urban development and public health policies in Klaipeda and other coastal cities facing similar environmental challenges.

This study examines the spatial distribution of chemical elements in the urban environment of Klaipėda Seaport City, assessing their concentrations in industrial, residential, and port zones. Particulate matter (PM) samples were collected using passive sampling methods and analyzed for their chemical composition to identify pollution patterns. Beyond spatial pollution analysis, a detailed correlation analysis of pollutants was conducted to determine potential emission sources across different functional city zones. The results indicate significantly elevated concentrations of heavy metals in port and transport zones, highlighting the necessity for targeted air quality improvement measures and innovative pollution mitigation strategies.

Nitrogen dioxide (NO₂) is a short-lived atmospheric pollutant primarily emitted by road traffic, maritime shipping, and industrial combustion. It is a key indicator of anthropogenic air pollution due to its harmful health effects, its role in the formation of secondary particulate matter, and its strong association with other traffic-related pollutants. Elevated NO₂ concentrations are closely linked to respiratory and cardiovascular diseases, with children and elderly populations being particularly vulnerable due to physiological susceptibility and exposure patterns. This study uses satellite-based remote sensing data to assess the spatial and temporal variability of NO₂ concentrations in the Lithuanian coastal zone and adjacent marine areas. The analysis focuses on identifying spatial patterns of NO₂ concentration distribution, localized pollution hotspots, and their relationships with population distribution. Correlation analysis for the 2022–2024 period revealed a statistically significant negative relationship between NO₂ concentrations and distance from the coastline in inland areas, whereas no statistically significant relationship was observed offshore. NO₂ concentrations at 0 m and 50 m were strongly positively correlated across all spatial domains and seasons (r > 0.98, p < 0.001), indicating consistent vertical spatial patterns. Annual mean NO₂ concentrations were also strongly positively associated with population density (r = 0.81).

Extreme hydrometeorological events are occurring more often under climate change, increasing the risk for cities in coastal zones and lower river reaches. Such areas are prone to compound flooding (CF), where flood duration and magnitude are amplified by the combined effects of storm surges, onshore winds, long-term sea-level rise, and increasingly frequent rainfall-driven floods. This study assesses the socio-economic risk of residential neighbourhoods (RNs) along the lower reach of the Danė River in the city of Klaipėda, Lithuania, using a composite socio-economic risk index (CSERI) developed in this study under an extreme flood scenario, if the sea level in the south-eastern Baltic Sea rises by 1 m by the end of the century. The results show a strong relationship between water levels in the Klaipėda Strait and the lower reach of the Danė River, confirming a CF regime, where flood magnitude is driven by the interaction between strait water level and river discharge. The CSERI is based on five risk sub-indices (SIs): the building risk SI, road infrastructure risk SI, population risk SI, economic entities risk SI, and cultural heritage risk SI. The assessment identifies RNs at greatest risk under climate change and anthropogenic pressure and indicates priority areas for adaptation measures to reduce potential socio-economic losses. The proposed CSERI provides a practical decision-support tool for sustainable and climate-resilient urban development in coastal cities.

Urban air pollution remains a significant environmental and public health issue, especially in European coastal cities such as Klaipėda. However, there is still a lack of local-scale knowledge on how land use structure influences pollutant distribution, highlighting the need to address this gap. This study addresses this by examining the spatial distribution of nitrogen dioxide (NO₂) concentrations in Klaipėda’s seaport city and several inland and coastal resort towns in Lithuania. The research specifically asks how different land cover types and demographic factors affect NO₂ variability and population exposure risk. Data were collected using passive sampling methods and analyzed within a GIS environment. The results revealed clear air quality differences between industrial/port zones and greener resort areas, confirmed by statistically significant associations between land cover types and pollutant levels. Based on these findings, a Land Use Pollution Pressure index (LUPP) and its population-weighted variant (PLUPP) were developed to capture demographic sensitivity. These indices provide a practical decision-support tool for sustainable urban planning, enabling the assessment of pollution risks and the forecasting of air quality changes under different land use scenarios, while contributing to local climate adaptation and urban environmental governance.