Search Results (150)

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. Full article

This research discusses the application of Sentinel satellite data for monitoring air pollution in port areas. The Scopus and Web of Science databases were comprehensively analysed to identify relevant peer-reviewed literature and assess research publications. The systematic literature review was conducted using the PRISMA methodology for inclusion and exclusion criteria. A total of 519 articles were identified from which 70 relevant articles were finally selected and discussed in detail for their relevancy to the maritime environment. Sentinel-5P was found to have several use cases in the literature that are useful for measuring maritime air pollution, while Sentinel 1 and 2 were mainly used for other applications like oil spills and water quality, respectively. Although aerial surveys, like those conducted using unmanned aerial vehicles (UAVs), offer more precise estimates of greenhouse gases (GHGs), they are only useful for certain applications because the technology is costly and impractical for daily monitoring. Satellite-based sensors are the state of the art for obtaining remote observations of emissions in open sea. Sentinel-5P measurements offer daily data for air quality monitoring, which supports ground surveys to identify and penalize major emission sources and consequently support environmental management in accordance with contemporary policies. Pollutant concentration levels for the maritime sector can be analysed both spatially and temporally using Sentinel-5P data. In the future, addressing the limitations of the Sentinel-5P data, such as underestimation and source separation, could improve air pollution assessments. Full article

Due to increased container traffic, the problems of congestion at terminal gates generate serious air pollution and decrease terminal efficiency. To address this issue, many terminals are implementing a truck appointment system (TAS) based on several concepts. Our work addresses gate congestion at a container terminal. A conceptual model was developed to identify system components and interactions, analyzing container flow from both static and dynamic perspectives. A truck appointment system (TAS) was modeled to optimize waiting times using a non-stationary approach. Compared to existing methods, our TAS introduces a more adaptive scheduling mechanism that dynamically adjusts to fluctuating truck arrivals, reducing peak congestion and improving resource utilization. Unlike traditional static appointment systems, our approach helps reduce truckers’ dissatisfaction caused by the deviation between the preferred time and the assigned one, leading to smoother operations. Various genetic algorithms were tested, with a hybrid genetic–tabu search approach yielding better results by improving solution stability and reducing computational time. The model was applied and adapted to the Port of Casablanca using real-world data. The results clearly highlight a significant potential to enhance sustainability, with an annual reduction of 785 tons of CO₂ emissions from a total of 1281 tons. Regarding trucker dissatisfaction, measured by the percentage of trucks rescheduled from their preferred times, only 7.8% of arrivals were affected. This improvement, coupled with a 62% decrease in the maximum queue length, further promotes efficient and sustainable operations. Full article

Under the “Dual Carbon” strategy, collaborative governance of port atmospheric pollutants and carbon emissions is critical for low-carbon transformation. Focusing on Ningbo-Zhoushan Port (48% regional ship emissions), this study examines government, port enterprises, and public interactions. A tripartite evolutionary game model with numerical simulation reveals dynamic patterns and key factors. The results show the following: (1) A substitution effect exists between government incentive costs and penalty intensity—increased environmental governance budgets reduce the probability of government incentives, whereas higher public reporting rewards accelerate corporate emission reduction convergence. (2) Public supervision exhibits cyclical fluctuations due to conflicts between individual rationality and collective interests, with excessive reporting rewards potentially triggering free-rider behavior. (3) The system exhibits two stable equilibria: a low-efficiency equilibrium (0,0,0) and a high-efficiency equilibrium (1,1,1). The latter requires policy cost compensation, corporate emission reduction gains exceeding investments, and a supervision benefit–cost ratio greater than 1. Accordingly, the study proposes a three-dimensional “Incentive–Constraint–Collaboration” governance strategy, recommending floating penalty mechanisms, green financial instrument innovation, and community supervision network optimization to balance environmental benefits with fiscal sustainability. This research provides a dynamic decision-making framework for multi-agent collaborative emission reduction in ports, offering both methodological innovation and practical guidance value. Full article

Seaports, as major transportation hubs, generate significant air pollution due to intensive ship traffic, directly affecting local air quality. While emission inventories are commonly used to manage ship-based air pollution, they reflect only the emission-related aspect of a specified period and area, limiting the broader interpretability and comparability of the results. To overcome the mentioned challenges, this research presents the PrE-PARE model, which enables the prediction, analysis, and risk evaluation of ship-sourced air pollution in port areas. The model comprises three interconnected modules. The first is applied for quantifying emissions using detailed technical and movement datasets, which are combined into individual voyage trajectories to enable a high-resolution analysis of ship-based air pollutants. In the second module, the Multivariate Adaptive Regression Splines (MARS) machine learning method is adapted to predict emissions in varying operational scenarios. In the third module, novel metric methods are introduced, enabling a standardised efficiency comparison between ships. These methods are supported by a unique classification system to determine the emission risk in different periods, evaluate the intensity of various ship types, and rank individual ships based on their operational efficiency and emission optimisation potential. By combining new methods with technical and operational shipping data, the model provides a transparent, comparable, and adaptable system for emissions monitoring. The results demonstrate that the PrE-PARE model has the potential to improve strategic planning and air quality management in ports while remaining flexible enough to be applied in different contexts and future scenarios. Full article

Under increasingly stringent global policies aimed at reducing emissions from shipping, the impact of maritime activities on air quality has garnered significant attention. However, the absence of comprehensive macro-evaluation methods and a limited understanding of regional-scale pollutant emissions introduce substantial uncertainties in assessing emission reduction effectiveness and identifying pollution sources. In this study, we utilized Sentinel-5P satellite data from 2019 to 2024 to examine the spatiotemporal characteristics of six air pollutants (SO₂, NO₂, HCHO, O₃, CO, and CH₄) in China’s coastal areas. We further investigated the correlation between ship density and pollutant concentrations and analyzed the distribution of pollutant concentrations in major coastal ports across China. The results indicate the following: (1) The concentrations of SO₂, HCHO, and CH₄ exhibited a continuous increasing trend, whereas NO₂, CO, and O₃ remained relatively stable or showed a slight decline. All six pollutants demonstrated obvious seasonal variations, with NO₂ and HCHO following a double-peak pattern and O₃, SO₂, CH₄, and CO exhibiting a single-peak pattern. (2) Pollutant concentrations were higher along the northern coast (Yellow Sea and Bohai Sea) and relatively lower in the South China Sea region. Specifically, NO₂, SO₂, and O₃ were higher in the Bohai Sea region; HCHO and CO were more concentrated in the northern coastal area; and CH₄ was elevated in the north and certain ports of the Yangtze River Delta. (3) Ship density displayed a significant positive correlation with NO₂, SO₂, HCHO, CO, and CH₄, indicating that ship emissions are an important source of these pollutants. Although O₃ is not directly emitted by ships, a positive correlation was observed in certain ship-dense areas, primarily due to photochemical reactions involving NO₂ and volatile organic compounds (VOCs). (4) Higher concentrations of NO₂, SO₂, HCHO, CO, and CH₄ were observed in northern ports (e.g., Tianjin Xingang, Qinhuangdao, Tangshan, and Dalian), whereas southern Chinese ports (e.g., Shenzhen, Xiamen, and Haikou) exhibited lower pollution levels. These findings provide a scientific foundation for coastal air pollution control and highlight the necessity of ship emission regulation and integrated multi-pollutant management. Full article

This paper presents a review of current developments in port pollution prevention and mitigation. A systematic categorization of the sources of pollution in the development and operation phases of ports and terminals is first presented. The paper then considers in detail technological and regulatory measures currently being applied to limit port pollution in the operation phase. This review is combined with that of relevant academic research and aims to fill a research gap by identifying the current and emerging port pollution themes and the latest trends in measures for pollution prevention and mitigation. A comprehensive approach is taken in this review by including not only academic research but also the industry’s research and development initiatives and the regulatory authority’s legislation. This paper identifies more than thirty different technological, regulatory, or organizational measures to limit pollution, although details on company-based research and development were found to be scarce. Mitigation of greenhouse gases and air-polluting emissions is identified as the most important field of research, but it is affected by regulatory uncertainties. Further research is needed on topics such as increased alternative fuel provision, digitalization potential for sustainability enhancement, and strategies for engaging stakeholders in greening ports. Full article

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. Full article

In response to the International Maritime Organization’s (IMO) 2020 sulfur cap and China’s stricter emission control policies, this study investigates the strategic interaction between port authorities and shipowners concerning air pollution emissions from ships in port areas. Using supervisory game theory, we construct a model that captures the cost–benefit trade-offs between inspection efforts by regulators and compliance behavior by ship operators. Empirical data from Guangzhou Port in 2020—including government inspection costs, fuel substitution costs, subsidy schemes, and fine levels—are incorporated into the model to simulate equilibrium outcomes. Results indicate that while the current level of inspection has a significant deterrent effect, the probability of full compliance remains low at 34.36%, highlighting the importance of a balanced regulatory approach combining inspection, fines, and subsidies. Policy implications suggest that increased financial incentives and stronger penalties can reduce both regulatory costs and non-compliance risks. This study contributes to the literature on maritime environmental governance by providing a quantitative supervisory framework grounded in real-world port data. Full article

Maritime transportation significantly contributes to air pollution, especially in coastal cities. Air pollution represents the greatest health risk related to the environment in the European Union. Therefore, the European Commission published the European Green Deal, which introduces the rule of zero-emission requirements for ships at berths with the mandatory use of power supply from shore or alternative technologies without emissions. The electrification of ferries has proven to be a key approach in reducing the negative impact on the environment; hence, it is necessary to provide adequate infrastructure for charging electric ferries. To determine the energy needs of the shore connection, a daily energy profile of the ferry fleet was created. Due to the sailing schedule, daily energy needs may be non-periodic. By optimizing the charging process, a reduction in peak charging power can be achieved. The charging process was optimized using particle swarm optimization. To improve the function goal, the parameters of the model were analyzed and optimized. It was found that the correct selection of population size and inertia weight factor can significantly enhance the optimization effect. The proposed model can be applied to other ports of interest, considering the specifics of the exploitation of the fleet of ships. Full article

Air pollution, particularly from coarse particulate matter (PM₁₀), is a major public health concern, significantly contributing to respiratory and cardiovascular diseases, especially among vulnerable populations. In 2024, Brazil introduced a new air quality resolution (CONAMA Resolution No. 506/2024), aligning its ultimate goal with the World Health Organization’s 2021 guidelines while establishing specific timelines for the interim targets. However, these interim targets, set for 2025, 2033, and 2044, along with the absence of a deadline for the final target of 15 µg/m³, raise concerns about their adequacy in addressing the urgent health impacts of air pollution. This study evaluates the economic and public health benefits of accelerating these targets in the city of Rio Grande, a region characterized by an industrial and port-driven economy and an aging population particularly vulnerable to air pollution. Using health impact assessments, economic cost analyses, and mortality estimates, we modeled three scenarios with PM₁₀ concentration limits of 30 µg/m³, 20 µg/m³, and 15 µg/m³, corresponding to the resolution’s 2033 and 2044 goals and the undated final target. Our findings indicate that achieving the 15 µg/m³ target by 2025 could prevent 2568 respiratory hospitalizations, 1551 cardiac hospitalizations, and 1128 air pollution-related deaths in Rio Grande, resulting in approximately BRL 7.3 million in healthcare savings. When extrapolated to cities with similar pollution profiles across Brazil, these results suggest substantial potential for reducing the health burdens and economic costs nationwide. This study underscores the urgent need to establish more ambitious timelines in Brazil’s air quality policies to maximize public health benefits and mitigate the economic impacts of air pollution. Full article

Ship emissions significantly impact air quality, particularly in coastal and port regions, contributing to elevated concentrations of PM_2.5, and PM₁₀, with varying effects observed across different locations. This study investigates the effectiveness of emission control policies, inland and port-specific contributions to air pollution, and the health risks posed by particulate matter (PM). A regression discontinuity model at Ningbo Port revealed that ship activities show moderate PM_2.5 and PM₁₀ variations. In Busan Port, container ships accounted for the majority of emissions, with social costs from pollutants estimated at USD 31.55 million annually. Inland shipping near the Yangtze River demonstrated significant PM contributions, emphasizing regional impacts. Health risks from PM_2.5, a major global toxic pollutant, were highlighted, with links to respiratory, cardiovascular, and cognitive disorders. Advances in air purification technologies, including hybrid electrostatic filtration systems, have shown promising efficiency in removing submicron particles and toxic gases, reducing energy costs. In this paper, a random forest machine learning model developed to predict particulate concentrations post-cleaning demonstrated robust performance (MAE = 0.49 P/cm³, R² = 0.97). These findings underscore the critical need for stringent emission controls, innovative filtration systems, and comprehensive monitoring to mitigate the environmental and health impacts of ship emissions. Full article

Sulfur dioxide (SO₂) can be of natural and anthropogenic origin and is one of the sulfur compounds present in the atmosphere. Among natural sources, volcanoes contribute with relevant annual outputs, and major eruptions lead to spikes in these outputs. In the case of anthropogenic pollution, SO₂ emissions are mostly correlated with the sulfur content of fuels, which has been the focus of specific emission mitigation policies for decades. Following other examples of cyclic and multi-year evaluations, an analysis of SO₂ at the Lamezia Terme (code: LMT) WMO/GAW (World Meteorological Organization—Global Atmosphere Watch) station in Calabria, Southern Italy, was performed. The coastal site is characterized by wind circulation patterns that result in the detection of air masses with low or enhanced anthropic influences. The presence of the Aeolian Arc of active, quiescent, and extinct volcanoes, as well as Mount Etna in Sicily, may influence LMT observations with diffused SO₂ emissions. For the first time in the history of the LMT, a multi-year analysis of a parameter has been integrated with TROPOMI data gathered by Sentinel-5P and used to test total tropospheric column densities at the LMT itself and select coordinates in the Tyrrhenian and Ionian seas. Surface and satellite data indicate that SO₂ peaks at the LMT are generally linked to winds from the western–seaside wind corridor, a pattern that is compatible with active volcanism in the Tyrrhenian Sea and maritime shipping to and from the Gioia Tauro port located in the same region. The findings of this research provide the basis for enhanced source apportionment, which could further differentiate anthropogenic sources in the area from natural outputs. Full article

This study focuses on understanding the health impacts of hazardous air pollutant (HAP) emissions from the Kaohsiung Coastal Industrial Park and port areas in southern Taiwan on neighboring communities. Six important HAPs (formaldehyde, benzene, arsenic, vinyl chloride, 1,3-butadiene, and diesel particulate matter (DPM)) were identified in this area. By considering the impact of emissions from stationary sources, mobile sources, and port activities, the relative importance of each emission source was assessed. In addition, the AERMOD (AMS (American Meteorological Society)/EPA (U.S. Environmental Protection Agency)) diffusion model was employed to simulate the increases in target pollutant concentrations and to analyze the influence and spatial distribution of various emission sources on atmospheric HAP concentrations in nearby communities. This study further evaluated the exposure risks of composite HAP sources, to understand their impacts and to determine their control priorities. The findings revealed that emissions and carcinogenic weighting from composite sources, particularly DPM emissions from port activities, including from ocean-going vessels and heavy-duty vehicles, had a significant impact. The maximum incremental concentration for DPM in the study area occurred around the port area, whereas the maxima for formaldehyde, benzene, arsenic, vinyl chloride, and 1,3-butadiene were all observed within the industrial complex. DPM emissions from port activities, 1,3-butadiene emissions from mobile sources, and benzene emissions from stationary sources were the composite sources with the greatest potential impacts. Over 90% of health risks were due to DPM, and the remaining health risks were due to 1,3-butadiene (6%), benzene (2%), arsenic (1%), and other species (less than 1%). DPM emissions were primarily influenced by port activities (77%), 1,3-butadiene emissions by mobile sources (45%), and benzene emissions by stationary sources (41%). A total of 25% of the area had risk values greater than 10⁻³, and 75% of the area had risk values between 10⁻³ and 10⁻⁴. The risk values in the densely populated areas were all greater than 10⁻⁴. The potential risk hotspots with risk values greater than 10⁻³ were located on the northwest side of the port and downwind of the industrial park. The key pollutants contributing to these hotspots were, in order, DPM (up to 80% cancer risk), formaldehyde, and 1,3-butadiene, all of which were significantly influenced by port activities. This indicates that the control of, and reduction in, HAP emissions from port activities should be prioritized. Full article

Electromagnetic waves (EMWs) have become an integral part of our daily lives, but they are causing a new form of environmental pollution, manifesting as electromagnetic interference (EMI) and radio frequency signal leakage. As a result, the demand for innovative, eco-friendly materials capable of blocking EMWs has escalated in the past decade, underscoring the significance of our research. In the realm of modern science, the creation of new materials must consider the starting materials, production costs, energy usage, and the potential for air, water, and soil pollution. Herein, we utilized biowaste materials generated during the distillation of fruit schnapps. The biowaste from apple and quince schnapps distillation was used as starting material, mixed with KOH, and carbonized at 850 °C, in a nitrogen atmosphere. The structure of samples was investigated using various techniques (infrared, Raman, energy-dispersive X-ray, X-ray photoelectron spectroscopies, thermogravimetric analysis, BET surface area analyzer). Encouragingly, these materials demonstrated the ability to block EMWs within a frequency range of 8 to 12 GHz. Shielding efficiency was measured using waveguide adapters connected to ports (1 and 2) of the vector network analyzer using radio-frequency coaxial cables. At a frequency of 10 GHz, carbonized biowaste blocks 78.5% of the incident electromagnetic wave. Full article