Impact of port emissions on EU-regulated and non-regulated air quality indicators: The case of Civitavecchia (Italy)

Identification of Neighborhood Hotspots via the Cumulative Hazard Index: Results From a Community-Partnered Low-Cost Sensor Deployment

The Strathcona neighborhood in Vancouver is particularly vulnerable to environmental injustice due to its close proximity to the Port of Vancouver, and a high proportion of Indigenous and low-income households. Furthermore, local sources of air pollutants (e.g., roadways) can contribute to small-scale variations within communities. The aim of this study was to assess hyperlocal air quality patterns (intra-neighborhood variability) and compare them to average Vancouver concentrations (inter-neighborhood variability) to identify possible disparities in air pollution exposure for the Strathcona community. Between April and August 2022, 11 low-cost sensors (LCS) were deployed within the neighborhood to measure PM2.5, NO2, and O3 concentrations. The collected 15-min concentrations were down-averaged to daily concentrations and compared to greater Vancouver region concentrations to quantify the exposures faced by the community relative to the rest of the region. Concentrations were also estimated at every 25 m grid within the neighborhood to quantify the distribution of air pollution within the community. Using population information from census data, cumulative hazard indices (CHIs) were computed for every dissemination block. We found that although PM2.5 concentrations in the neighborhood were lower than regional Vancouver averages, daily NO2 concentrations and summer O3 concentrations were consistently higher. Additionally, although CHIs varied daily, we found that CHIs were consistently higher in areas with high commercial activity. As such, estimating CHI for dissemination blocks was useful in identifying hotspots and potential areas of concern within the neighborhood. This information can collectively assist the community in their advocacy efforts.

Effect of time-activity patterns and microenvironments on the personal exposure of undergraduate students to black carbon

In this study, the personal exposure to and potential dose of black carbon (BC) of undergraduate students (22-27 years old, nonsmokers) were determined. BC was continuously measured by a portable device (microAeth^® AE51) for four consecutive days in Istanbul between April and May 2019. The time-activity diaries filled out by each volunteer were assessed to define the activities and microenvironments (home, school, transportation and entertainment) that contributed to daily BC exposure. The overall mean concentration of BC was 2.0 μg/m³, and the mean concentrations on weekdays and weekends were 3.0 μg/m³ and 1.1 μg/m³, respectively. Transportation made the highest contribution to mean BC exposure (42%) and dose (45.8%) on weekdays, while the contributions of home-based activities to BC exposure (66.1%) and dose (63.2%) were higher on weekends. Students had the most intense exposure to (2.8% and 4.6%) and dose (3.1% and 5.8%) of BC in transportation both on weekdays and on weekends, respectively. Between transportation modes, the mean BC concentration was the highest for minibuses (14.8 μg/m³), while walking made the largest contribution to BC exposure (16.8%) on weekdays. Students spent 12.8% of their weekdays at school, and the contributions of the school environment to BC exposure and dose were 8.5% and 7%, respectively. Exposure to BC increased during cooking and eating activities in microenvironments such as the kitchen, cafe and dining hall.

Promoting Sustainability through Assessment and Measurement of Port Externalities: A Systematic Literature Review and Future Research Paths

In an attempt to mitigate and balance economic, environmental, and societal externalities that ports exert, port sustainability is becoming increasingly important as a key priority. This work embarks on an effort to explore the boundaries, provide a holistic view, and establish a knowledge map of contemporary research in the field of port externalities and impacts, by conducting a systematic literature review (SLR) by carrying out a three-stage procedure (planning, execution, and reporting), enhancing objectivity, while limiting errors and bias. The literature under study pertains to research domains focusing on: (a) identifying port externalities and impacts, (b) utilizing metrics and indicators to measure and quantify the positive or negative impact of port externalities, and (c) promoting an inclusive framework for sustainable port development. Our results include, among others, the classification of methodologies and particularly, of indicators established per type of externality to measure and monitor sustainable port performance, as well as identification of trends and gaps within the contemporary literature. We find considerable room for exploring new concepts and research paths within the domain of port impacts and externalities, both within individual dimensions of sustainability (economic, social, environmental), and on a multidisciplinary level.

Estimation of Pollutant Emissions and Environmental Costs Caused by Ships at Port: A Case Study of Busan Port

To reduce air pollutants, the International Maritime Organisation and port authorities use ship emissions regulations, such as MARPOL Annex VI and green port policies. To measure the effectiveness of these air emissions regulatory policies, accurate calculations of pollutant emissions and estimations of the social environmental costs of emissions are important. However, Busan Port still suffers from a lack of research on continuous monitoring and easy access to data-based emission calculation methods and estimation of the social environmental costs. Therefore, the purpose of this study is to present quantitative emission calculations based on an open source and social environmental cost estimation method. To this end, the discharge of pollutants (NOx, SO2, CO2, VOC, PM2.5, and PM10) from ships in Busan Port was calculated using Port-MIS open data from 2015–2019. Subsequently, when the original study on estimating the social and environmental impact of air pollution from ships in Busan Port was difficult, the international benefit transfer method (an economic valuation method) was applied to estimate the social environmental costs. Our results can provide a basis for verifying the effectiveness of Busan Port’s air quality improvement policy in the future.

Applying and Comparing LSTM and ARIMA to Predict CO Levels for a Time-Series Measurements in a Port Area

Air pollution is a major problem in the everyday life of citizens, especially air pollution in the transport domain. Ships play a significant role in coastal air pollution, in conjunction with transport mobility in the broader area of ports. As such, ports should be monitored in order to assess air pollution levels and act accordingly. In this paper, we obtain CO values from environmental sensors that were installed in the broader area of the port of Igoumenitsa in Greece. Initially, we analysed the CO values and we have identified some extreme values in the dataset that showed a potential event. Thereafter, we separated the dataset into 6-h intervals and showed that we have an extremely high rise in certain hours. We transformed the dataset to a moving average dataset, with the objective being the reduction of the extremely high values. We utilised a machine-learning algorithm, namely the univariate long short-term memory (LSTM) algorithm to provide the predicted outcome of the time series from the port that has been collected. We performed experiments by using 100, 1000, and 7000 batches of data. We provided results on the model loss and the root-mean-square error as well as the mean absolute error. We showed that with the case with batch number equals to 7000, the LSTM we achieved a good prediction outcome. The proposed method was compared with the ARIMA model and the comparison results prove the merit of the approach.

Electrification of Inland Waterway Ships Considering Power System Lifetime Emissions and Costs

This paper deals with the applicability of alternative power system configurations to reduce the environmental footprint of inland waterway ships. Its original contribution includes: models for assessment of the lifetime emissions and associated lifetime costs of alternative power system configurations for different types of inland waterway vessels, identification of the most cost-effective options for these vessels, and an estimation of the impact of emission policies on the profitability of each option. The case study considers the Croatian inland waterway sector, where three types of vessel with significantly different purposes, designs, and operative profiles are considered (cargo ship, passenger ship, and dredger). The technical and operational features of these ships are analyzed with an emphasis on their energy needs. Then, life-cycle assessments (LCAs) of a diesel engine-powered ship configuration and two battery-powered ship configurations (with and without a photovoltaic system) are performed by means of GREET 2020 software. These configurations are compared from the economical viewpoint, by the life-cycle cost assessment (LCCA), where potential carbon credit scenarios are investigated, while relevant quantities are converted into monetary units. Although the LCA identified the photovoltaic cells’ battery-powered ship configuration as the most environmentally friendly, according to the LCCA, its life-cycle costs are rather high, except for passenger ships, for which the battery-powered ship configuration is a feasible option. If a set of required specific input data is known, the presented procedure is applicable to reduce the environmental footprint of any other inland waterway fleet.

Pollutant Emissions in Ports: A Comprehensive Review

In recent decades, maritime transport demand has increased along with world population and global trades. This is associated with higher pollution levels, including the emissions of GHG and other polluting gases. Ports are important elements within maritime transport and contribute themselves to pollutant emissions. This paper aims to offer a comprehensive yet technical review of the latest related technologies, explaining and covering aspects that link ports with emissions, i.e., analyzing, monitoring, assessing, and mitigating emissions in ports. This has been achieved through a robust scientific analysis of very recent and significant research studies, to offer an up-to-date and reliable overview. Results show the correlation between emissions and port infrastructures, and demonstrate how proper interventions can help with reducing pollutant emissions and financial costs as well, in ports and for maritime transportation in general. Besides, this review also wishes to propose new ideas for future research: new future experimental studies might spin-off from it, and perhaps port Authorities might be inspired to experiment and implement dedicated technologies to improve their impact on environment and sustainability.

Selecting Suitable, Green Port Crane Equipment for International Commercial Ports

Responding to the increasing global need for environmental protection, a green port balances economic vibrancy with environmental protection. However, because exhaust emissions (e.g., CO2 or sulfide) are difficult to monitor around ports, data on such emissions are often incomplete, which hinders research on this topic. The present study aimed to fill this gap in this topic. To remedy this problem, this study formulated a new data envelopment analysis (DEA) method for collecting CO2 emissions data at their source. This method was applied to collect real-world operating data from a large container-handling company in Taiwan. Specifically, we provide a real example using a novel green energy index to account for undesirable outputs. Our main objective was to formulate two methods that combine: (1) data envelopment analysis based on a modified slack-based measure, and (2) a multi-choice goal programming approach. The contributions of this paper included the finding that rubber-tired gantry cranes are the greenest and should be used in ports. Finally, our findings aid port managers in selecting port equipment that provides the best balance between environmental protection and profitability.

Estimating greenhouse gas emissions from ships on four ports of Georgia from 2010 to 2018

This study is a comprehensive inventory of the greenhouse gas emissions from ships in the Georgian ports and aims to analyse the level of exhaust gas emissions in ports. Georgia has four main ports (the Poti Sea Port, the Batumi Port, the Port of Kulevi, and the Port of Supsa) which are a vital link in Georgia's economy and transfer point for handling oil and oil products. The ship activity-based method is used to calculate the emissions of NO_X, CO₂, VOC, PM, and SO₂ from ships between 2010 to 2018 years. The analysis is executed according to the type of ships (container, bulk dry, general cargo, tanker, chemical, liquified gas, and others) and operational modes (cruising, manoeuvring, and hoteling). The total emissions from ports are 54.640, 44.030, 11.910, and 9.206 tonnes per year for Batumi, Poti, Kulevi, and Supsa, respectively. The study indicates that the Batumi Port is the main source of atmospheric pollution in the region followed by the Poti Sea Port. Tanker, general cargo, and container ships are the main polluters at all ports and emit almost 82% of all emissions in the Georgian ports. The greenhouse gas emissions emitted from vessels during the mode of cruising were 82% of the total amount; manoeuvring emissions were 5% and hoteling 13% in operational modes. The environmental costs of ports can reach to €19.1 million or €14.288 per ship call in 2018. The uncertainties of the pollutant emission estimates were measured, with lower bounds of - 12.3 to - 33.9% and upper bound of 10.8 to 30.0% at 95% confidence intervals. The lower uncertainties in the study emphasised the importance of the ship activity-based method in improving ship emission estimates.

Shipping and Air Quality in Italian Port Cities: State-of-the-Art Analysis of Available Results of Estimated Impacts

Populated coastal areas are exposed to emissions from harbour-related activities (ship traffic, loading/unloading, and internal vehicular traffic), posing public health issues and environmental pressures on climate. Due to the strategic geographical position of Italy and the high number of ports along coastlines, an increasing concern about maritime emissions from Italian harbours has been made explicit in the EU and IMO (International Maritime Organization, London, UK) agenda, also supporting the inclusion in a potential Mediterranean emission control area (MedECA). This work reviews the main available outcomes concerning shipping (and harbours’) contributions to local air quality, particularly in terms of concentration of particulate matter (PM) and gaseous pollutants (mainly nitrogen and sulphur oxides), in the main Italian hubs. Maritime emissions from literature and disaggregated emission inventories are discussed. Furthermore, estimated impacts to air quality, obtained with dispersion and receptor modeling approaches, which are the most commonly applied methodologies, are discussed. Results show a certain variability that suggests the necessity of harmonization among methods and input data in order to compare results. The analysis gives a picture of the effects of this pollution source, which could be useful for implementing effective mitigation strategies at a national level.

Comparison of the impact of ships to size-segregated particle concentrations in two harbour cities of northern Adriatic Sea

Detailed information on in-harbour shipping contribution to size segregated particles in coastal cities are scarce, especially in the busy Mediterranean basin. This poses issues for human exposure and air quality in urban harbour agglomerates, where only criteria pollutants (i.e. PM₁₀ and/or PM_2.5) are usually monitored. In this work, particle number and mass size distributions, in a large size range (0.01-31 μm), were obtained in two coastal cities of northern Adriatic Sea: Venice (Italy) and Rijeka (Croatia). Three size ranges were investigated: nanoparticles (diameter D < 0.25 μm); fine particles (0.25<D < 1 μm), and coarse particles (D > 1 μm). Absolute concentrations were larger in Venice for all size ranges showing, using analysis of daily trends, a large influence of local meteorology and boundary-layer dynamics. Contribution of road transport was larger (in relative terms) in Rijeka compared to Venice. The highest contributions of shipping were in Venice, mainly because of the larger ship traffic. Maximum impact was on nanoparticles 7.4% (Venice) and 1.8% (Rijeka), the minimum was on fine range 1.9% (Venice) and <0.2% (Rijeka) and intermediate values were found in the coarse fraction 1.8% (Venice) and 0.5% (Rijeka). Contribution of shipping to mass concentration was not distinguishable from uncertainty in Rijeka (<0.2% for PM₁, PM_2.5, and PM₁₀) and was about 2% in Venice. Relative contributions as function of particles size show remarkable similitudes: a maximum for nanoparticles, a quick decrease and a successive secondary maximum (2-3 times lower than the first) in the fine range. For larger diameters, the relative contributions reach a minimum at 1-1.5 μm and there is a successive increase in the coarse range. Size distributions showed a not negligible contribution of harbour emissions to nanoparticle and fine particle number concentrations, compared to PM_2.5 or PM₁₀, indicating them as a better metric to monitor shipping impacts compared to mass concentrations (PM_2.5 or PM₁₀).

Time-Frequency Analysis of Particulate Matter (PM10) Concentration in Dry Bulk Ports Using the Hilbert-Huang Transform

To analyze the time–frequency characteristics of the particulate matter (PM₁₀) concentration, data series measured at dry bulk ports were used to determine the contribution of various factors during different periods to the PM₁₀ concentration level so as to support the formulation of air quality improvement plans around port areas. In this study, the Hilbert–Huang transform (HHT) method was used to analyze the time–frequency characteristics of the PM₁₀ concentration data series measured at three different sites at the Xinglong Port of Zhenjiang, China, over three months. The HHT method consists of two main stages, namely, empirical mode decomposition (EMD) and Hilbert spectrum analysis (HSA), where the EMD technique is used to pre-process the HSA in order to determine the intrinsic mode function (IMF) components of the raw data series. The results show that the periods of the IMF components exhibit significant differences, and the short-period IMF component provides a modest contribution to all IMF components. Using HSA technology for these IMF components, we discovered that the variations in the amplitude of the PM₁₀ concentration over time and frequency are discrete, and the range of this variation is mainly concentrated in the low-frequency band. We inferred that long-term influencing factors determine the PM₁₀ concentration level in the port, and short-term influencing factors determine the difference in concentration data at different sites. Therefore, when formulating PM₁₀ emission mitigation strategies, targeted measures must be implemented according to the period of the different influencing factors. The results of this study can help guide recommendations for port authorities when formulating the optimal layout of measurement devices.