Source apportionment of PM(2.5) in the harbour-industrial area of Brindisi (Italy): identification and estimation of the contribution of in-port ship emissions

Spatial and seasonal variability of the contribution of sources to PM2.5, PM10 and their oxidative potential in different sites in a central Mediterranean area

Oxidative potential (OP) is a potential indicator of negative health effects of particulate matter (PM). To address mitigation strategies, there is need of understanding how natural and anthropogenic sources influence OP at different sites. This work investigates spatial and seasonal variabilities of PM2.5 and PM10 concentrations, composition, and oxidative potential (OPDTTV, obtained with DTT assay), simultaneously at 22 sites in a central Mediterranean area in south Italy. Source apportionment using PMF5 allowed to evaluate the contributions of eight sources: traffic, biomass burning (BB), nitrate, sulphate-rich, marine, crustal, carbonates/construction, and industrial (only for PM2.5). Nitrate, traffic, and BB had larger contributions during the cold season and presented spatial variability with exclusion of nitrate. Industrial contributions did not have relevant seasonal or spatial variability. The other sources had an opposite trend with larger values during the warm season but only sulphate-rich had non-negligible spatial variability. OPDTTV had relevant spatial variability only during the cold season. Four sources had statistically significant contributions to OPDTTV: traffic, BB, sulphate-rich, and crustal (in descending order). The use of soluble and insoluble fractions of OC and Ca in PMF5 allowed a better separation between traffic and BB sources and allowed to determine the role of local construction works. The results may have implications in future policies for mitigation strategies of OP targeting specific sources categories.

Profiling aerosol Polycyclic Aromatic Compounds (PACs) in a severely polluted European city: A comprehensive assessment of the residential biomass burning impact on atmospheric toxicity

Fine aerosol Polycyclic Aromatic Hydrocarbons (PAHs), Oxygenated Polycyclic Aromatic Hydrocarbons (OPAHs) and other PM2.5 components were quantified in Ioannina, a Southeastern European city facing severe air quality degradation due to residential biomass burning (BB). Polycyclic Aromatic Compound (PAC) seasonal means were extremely enhanced in winter compared to summer (by 98 and 88 times for PAHs and OPAHs, respectively). Benzo(a)pyrene (BaP) registered a 347-fold winter increase, and its estimated annual mean was 2.4 times higher than the EU standard. Medium- and high-molecular weight PAC species correlated well with PM2.5 DTTv activity (R2: 0.48 and 0.54, respectively), suggesting also their significant non-carcinogenic potential. These PAC groups were strongly associated with methanol- and water-soluble Brown Carbon absorption (R2 > 0.7). Source apportionment by Positive Matrix Factorization (PMF) on the speciation dataset indicated BB as the major aerosol source, contributing > 80 % to average Σ-PAC concentrations and their carcinogenic potential during the study period. The PAC carcinogenic risk assessment highlighted the importance of considering the inclusion of not only legacy PAHs but also emerging species with very high estimated toxicity, such as Benzo(c)fluorene and Dibenzo-pyrenes. Observed concentrations were alarming, posing substantial short- and especially long-term risks. Therefore, there is an urgent need to regulate residential BB in Ioannina and similar urban environments in SE Europe.

Source analysis of the particle-associated oxidative potential and polycyclic aromatic compounds in Shenyang, China

In this study, a dithiothreitol (DTT) assay was performed to assess the oxidative potential (OP) induced by atmospheric particulate matter in Shenyang, China, in the winter and summer of 2015. OP sources were identified by using the positive matrix factorization (PMF) model, and the relationships between components of the total suspended particulate (TSP), including different types of polycyclic aromatic compounds, and the OP were investigated. The volume-based DTT consumption rate (DTTv) was used as an OP indicator. During sampling, the average daily TSP concentration and DTTv in Shenyang City were 142 µg/m3 and 1304 pmol/min/m3, respectively, and they markedly increased in the winter compared with the summer. The PMF model identified the following sources for the OP induced by TSP: automobile exhaust and road dust (5.0%), biomass burning (31.0%), coal combustion (10.6%), soil (21.1%), diesel combustion (13.4%), and secondary pollution (19.0%). Furthermore, the source analysis revealed that biomass burning was the largest source of oxygenated and nitrated polycyclic aromatic hydrocarbons and that coal combustion was the largest source of polycyclic aromatic hydrocarbons.

Hourly PM2.5 concentration prediction for dry bulk port clusters considering spatiotemporal correlation: A novel deep learning blending ensemble model

Accurate prediction of PM2.5 concentrations in ports is crucial for authorities to combat ambient air pollution effectively and protect the health of port staff. However, in port clusters formed by multiple neighboring ports, we encountered several challenges owing to the impact of unique meteorological conditions, potential correlation between PM2.5 levels in neighboring ports, and coupling influence of background pollutants in city zones. Therefore, considering the spatiotemporal correlation among the factors influencing PM2.5 concentration variations within the harbor cluster, we developed a novel blending ensemble deep learning model. The proposed model combined the strengths of four deep learning architectures: graph convolutional networks (GCN), long short-term memory networks (LSTM), residual neural networks (ResNet), and convolutional neural networks (CNN). GCN, LSTM, and ResNet served as the base models aimed at capturing the spatial correlation of PM2.5 concentrations in neighboring ports, the potential long-term dependence of meteorological factors and PM2.5 concentrations, and the effects of urban ambient air pollutants, respectively. Following the blending ensemble technique, the prediction outcomes of three base models were used as the input data for the meta-model CNN, which employs the blending ensemble technique to produce the final prediction results. Based on actual data obtained from 18 ports in Nanjing, the proposed model was compared and analyzed for its prediction performance against six state-of-the-art models. The findings revealed that the proposed model provided more accurate predictions. It reduced mean absolute error (MAE) by 10.59 %-20.00 %, reduced root mean square error (RMSE) by 13.22 %-17.11 %, improved coefficient of determination (R2) by 10 %-35.38 %, and improved accuracy (ACC) by 3.48 %-7.08 %. Additionally, the contribution of each component to the prediction performance of the proposed model was measured using a systematic ablation study. The results demonstrated that the GCN model exerted the most substantial influence on the prediction performance of the GCN-LSTM-ResNet model, followed by the LSTM model. The influence of urban background pollutants can significantly enhance the generalizability of the complete model. Moreover, a comparison with three blended ensemble models incorporating any two base models demonstrated that the GCN-LSTM-ResNet model exhibited superior prediction performance and was particularly excellent in predicting the occurrence of high-concentration events. Specifically, the GCN-LSTM-ResNet model improved MAE and RMSE by at least 12.3% and 9.2%, respectively, but reduced R2 and ACC by 26.1% and 6.8%, respectively. The proposed model provided reliable PM2.5 concentration prediction outcomes and decision support for air quality management strategies in dry bulk port clusters.

Effects of seasonal management programs on PM2.5 in Seoul and Beijing using DN-PMF: Collaborative efforts from the Korea-China joint research

South Korea and China have implemented increasingly stringent mitigation measures to reduce the health risks from PM2.5 exposure, jointly conducting a ground-based air quality observation study in Northeast Asia. Dispersion normalized positive matrix factorization (DN-PMF) was used to identify PM2.5 sources in Seoul and Beijing and assess the effectiveness of the seasonal management programs (SMPs) through a comparative study. Samples were collected during three periods: January-December 2019, September 2020-May 2021, and July 2021-March 2022. In Seoul, ten sources were resolved (Secondary nitrate: 8.67 μg/m3, 34 %, Secondary sulfate: 5.67 μg/m3, 22 %, Motor vehicle: 1.83 μg/m3, 7.2 %, Biomass burning: 2.30 μg/m3, 9.1 %, Residual oil combustion: 1.66 μg/m3, 6.5 %, Industry: 2.15 μg/m3, 8.5 %, Incinerator: 1.39 μg/m3, 5.5 %, Coal combustion: 0.363 μg/m3, 1.4 %, Road dust/soil: 0.941 μg/m3, 3.7 %, Aged sea salt: 0.356 μg/m3, 1.4 %). The SMP significantly decreased PM2.5 mass concentrations and source contributions of motor vehicle, residual oil combustion, industry, coal combustion, and biomass burning sources (p-value < 0.05). For Seoul, the reduction effects of the SMPs were evident even considering the influence of the natural meteorological variations and the responses to COVID-19. In Beijing, nine sources were resolved (Secondary nitrate: 12.6 μg/m3, 28 %, Sulfate: 8.27 μg/m3, 18 %, Motor vehicle: 3.77 μg/m3, 8.4 %, Biomass burning: 2.70 μg/m3, 6.0 %, Incinerator: 4.50 μg/m3, 10 %, Coal combustion: 3.52 μg/m3, 7.8 %, Industry: 5.01 μg/m3, 11 %, Road dust/soil: 2.92 μg/m3, 6.5 %, Aged sea salt: 1.63 μg/m3, 3.6 %). Significant reductions in PM2.5 mass concentrations and source contributions of industry, coal combustion, and incinerator (p-value < 0.05) were observed, attributed to the SMP and additional measures enforced before the 2022 Beijing Winter Olympics. Unlike comparing PM2.5 mass concentration variations using conventional methods, investigation of the source contribution variations of PM2.5 by using DN-PMF can provide a deeper understanding of the effectiveness of the air quality management policies.

Size-segregated characteristics of water-soluble oxidative potential in urban Xiamen: Potential driving factors and implications for human health

Oxidative potential (OP), defined as the ability of particulate matter (PM) to generate reactive oxygen species (ROS), has been considered as a potential health-related metric for PM. Particles with different sizes have different OP and deposition efficiencies in the respiratory tract and pose different health risks. In this study, size-segregated PM samples were collected at a coastal urban site in Xiamen, a port city in southeastern China, between August 2020 and September 2021. The water-soluble constituents, including inorganic ions, elements and organic carbon, were determined. Total volume-normalized OP based on the dithiothreitol assay was highest in spring (0.241 ± 0.033 nmol min-1 m-3) and lowest in summer (0.073 ± 0.006 nmol min-1 m-3). OP had a biomodal distribution with peaks at 0.25-0.44 μm and 1.0-1.4 μm in spring, summer, and winter and a unimodal pattern with peak at 0.25-0.44 μm in fall, which were different from the patterns of redox-active species. Variations in the seasonality of fine and coarse mode OP and their correlations with water-soluble constituents showed that the size distribution patterns of OP could be attributed to the combined effects of the size distributions of transition metals and redox-active organics and the interactions between them which varied with emissions, meteorological conditions and atmospheric processes. Respiratory tract deposition model indicated that the deposited OP and the toxic elements accounted for 47.9 % and 36.8 % of their measured concentrations, respectively. The highest OP doses and the excess lifetime carcinogenic risk (ELCR) were found in the head airway (>70 %). However, the size distributions of OP deposition and ELCR in the respiratory tract were different, with 63.9 % and 49.4 % of deposited ELCR and OP, respectively, coming from PM2.5. Therefore, attention must be paid to coarse particles from non-exhaust emissions and road dust resuspension.

A PM10 chemically characterized nation-wide dataset for Italy. Geographical influence on urban air pollution and source apportionment

Urban textures of the Italian cities are peculiarly shaped by the local geography generating similarities among cities placed in different regions but comparable topographical districts. This suggested the following scientific question: can different topographies generate significant differences on the PM10 chemical composition at Italian urban sites that share similar geography despite being in different regions? To investigate whether such communalities can be found and are applicable at Country-scale, we propose here a novel methodological approach. A dataset comprising season-averages of PM10 mass concentration and chemical composition data was built, covering the decade 2005-2016 and referring to urban sites only (21 cities). Statistical analyses, estimation of missing data, identification of latent clusters and source apportionment modeling by Positive Matrix Factorization (PMF) were performed on this unique dataset. The first original result is the demonstration that a dataset with atypical time resolution can be successfully exploited as an input matrix for PMF obtaining Country-scale representative chemical profiles, whose physical consistency has been assessed by different tests of modeling performance. Secondly, this dataset can be considered a reference repository of season averages of chemical species over the Italian territory and the chemical profiles obtained by PMF for urban Italian agglomerations could contribute to emission repositories. These findings indicate that our approach is powerful, and it could be further employed with datasets typically available in the air pollution monitoring networks.

Reduction of Outdoor and Indoor PM2.5 Source Contributions via Portable Air Filtration Systems in a Senior Residential Facility in Detroit, Michigan

Background: The Reducing Air Pollution in Detroit Intervention Study (RAPIDS) was designed to evaluate cardiovascular health benefits and personal fine particulate matter (particulate matter < 2.5 μm in diameter, PM2.5) exposure reductions via portable air filtration units (PAFs) among older adults in Detroit, Michigan. This double-blind randomized crossover intervention study has shown that, compared to sham, air filtration for 3 days decreased 3-day average brachial systolic blood pressure by 3.2 mmHg. The results also showed that commercially available HEPA-type and true HEPA PAFs mitigated median indoor PM2.5 concentrations by 58% and 65%, respectively. However, to our knowledge, no health intervention study in which a significant positive health effect was observed has also evaluated how outdoor and indoor PM2.5 sources impacted the subjects. With that in mind, detailed characterization of outdoor and indoor PM2.5 samples collected during this study and a source apportionment analysis of those samples using a positive matrix factorization model were completed. The aims of this most recent work were to characterize the indoor and outdoor sources of the PM2.5 this community was exposed to and to assess how effectively commercially available HEPA-type and true HEPA PAFs were able to reduce indoor and outdoor PM2.5 source contributions. Methods: Approximately 24 h daily indoor and outdoor PM2.5 samples were collected on Teflon and Quartz filters from the apartments of 40 study subjects during each 3-day intervention period. These filters were analyzed for mass, carbon, and trace elements. Environmental Protection Agency Positive Matrix Factorization (PMF) 5.0 was utilized to determine major emission sources that contributed to the outdoor and indoor PM2.5 levels during this study. Results: The major sources of outdoor PM2.5 were secondary aerosols (28%), traffic/urban dust (24%), iron/steel industries (15%), sewage/municipal incineration (10%), and oil combustion/refinery (6%). The major sources of indoor PM2.5 were organic compounds (45%), traffic + sewage/municipal incineration (14%), secondary aerosols (13%), smoking (7%), and urban dust (2%). Infiltration of outdoor PM2.5 for sham, HEPA-type, and true HEPA air filtration was 79 ± 24%, 61 ± 32%, and 51 ± 34%, respectively. Conclusions: The results from our study showed that intervention with PAFs was able to significantly decrease indoor PM2.5 derived from outdoor and indoor PM2.5 sources. The PAFs were also able to significantly reduce the infiltration of outdoor PM2.5. The results of this study provide insights into what types of major PM2.5 sources this community is exposed to and what degree of air quality and systolic blood pressure improvements are possible through the use of commercially available PAFs in a real-world setting.

An unneglected source to ambient brown carbon and VOCs at harbor area: LNG tractor truck

The ambient air quality of harbors area in Asia is commonly more polluted compared to other continents. The airborne pollutant is directly or indirectly related to a significant impact of traffic emissions. This study for the first time assessed the impacts on brown carbon (BrC) and volatile organic compounds (VOCs) from in-port liquid natural gas (LNG) tractor truck at harbor areas, via conducting real-time monitoring of VOCs characteristic and sampling for ambient air at a harbor (named as W harbor) in Shanghai, China, collecting emissions of in-port LNG tractor truck and miniCast in laboratory, as well as statistics of external container diesel trucks in the port for further validation. HPLC/DAD/Q-Tof MS was adopted for sample analysis. Results showed that many CHO compounds were associated with vehicle exhausts. Among of them, aliphatic CHO compounds with low degree of unsaturation were identified as fatty acids and fatty acid methyl esters extensively existing in fuel combustion emissions. And non-aliphatic CHO compounds characterized by low O/C ratios (<0.17) identified for the harbor air came from the emissions of in-port LNG power trucks with low-speed driving and idling. The ambient average non-methane total hydrocarbons (NMHC) concentration (0.59 ppm) at W harbor was much greater than that for other areas in Shanghai. The higher ratios of toluene/benzene (3.30) and m/p-xylene/ethylbenzene (3.11) observed at W harbor implied instead of external container diesel trucks, the dominating contributing of internal LNG tractor trucks to ambient VOCs cannot be neglected. This study concluded that LNG is not as clean as it was expected. The LNG-fueled vehicles can produce strong light-absorption chromophores as well as high concentration of VOCs.

Heavy vehicles' non-exhaust exhibits competitive contribution to PM2.5 compared with exhaust in port and nearby areas

Heavy port transportation networks are increasingly considered as significant contributors of PM2.5 pollution compared to vessels in recent decades. In addition, evidence points to the non-exhaust emission of port traffic as the real driver. This study linked PM2.5 concentrations to varied locations and traffic fleet characteristics in port area through filter sampling. The coupled emission ratio-positive matrix factorisation (ER-PMF) method resolves source factors by avoiding direct overlap from collinear sources. In the port central and entrance areas, freight delivery activity emissions including vehicle exhaust and non-exhaust particles, as well as induced road dust resuspension, accounted for nearly half of the total contribution (42.5%-49.9%). In particular, the contribution of non-exhaust from denser traffic with high proportion of trucks was competitive and equivalent to 52.3% of that from exhaust. Backward trajectory statistical models further interpreted the notably larger-scale coverage of non-exhaust emissions in the port's central area. The distribution of PM2.5 were interpolated within the scope of the port and nearby urban areas, displaying the potential contribution of non-exhaust within 1.15 μg/m3-4.68 μg/m3, slightly higher than the urban detections reported nearby. This study may provide useful insights into the increasing percentage of non-exhaust from trucks in ports and nearby urban areas and facilitate supplementary data collection on Euro-VII type-approval limit settings.

Impact of shipping emissions regulation on urban aerosol composition changes revealed by receptor and numerical modelling

Various shipping emissions controls have recently been implemented at both local and national scales. However, it is difficult to track the effect of these on PM2.5 levels, owing to the non-linear relationship that exists between changes in precursor emissions and PM components. Positive Matrix Factorisation (PMF) identifies that a switch to cleaner fuels since January 2020 results in considerable reductions in shipping-source-related PM2.5, especially sulphate aerosols and metals (V and Ni), not only at a port site but also at an urban background site. CMAQ sensitivity analysis reveals that the reduction of secondary inorganic aerosols (SIA) further extends to inland areas downwind from ports. In addition, mitigation of secondary organic aerosols (SOA) in coastal urban areas can be anticipated either from the results of receptor modelling or from CMAQ simulations. The results in this study show the possibility of obtaining human health benefits in coastal cities through shipping emission controls.

Source apportionment of PM2.5 before and after COVID-19 lockdown in an urban-industrial area of the Lisbon metropolitan area, Portugal

The lockdowns held due to the COVID-19 pandemic conducted to changes in air quality. This study aimed to understand the variability of PM_2.5 levels and composition in an urban-industrial area of the Lisbon Metropolitan Area and to identify the contribution of the different sources. The composition of PM_2.5 was assessed for 24 elements (by PIXE), secondary inorganic ions and black carbon. The PM_2.5 mean concentration for the period (December 2019 to November 2020) was 13 ± 11 μg.m^-3. The most abundant species in PM_2.5 were BC (19.9%), SO₄ ^2- (15.4%), NO₃ ^- (11.6%) and NH₄ ⁺ (5.3%). The impact of the restrictions imposed by the COVID-19 pandemic on the PM levels was found by comparison with the previous six years. The concentrations of all the PM_2.5 components, except Al, Ba, Ca, Si and SO₄ ^2-, were significantly higher in the winter/pre-confinement than in post-confinement period. A total of seven sources were identified by Positive Matrix Factorisation (PMF): soil, secondary sulphate, fuel-oil combustion, sea, vehicle non-exhaust, vehicle exhaust, and industry. Sources were greatly influenced by the restrictions imposed by the COVID-19 pandemic, with vehicle exhaust showing the sharpest decrease. Secondary sulphate predominated in summer/post-confinement. PM_2.5 levels and composition also varied with the types of air mass trajectories.

Overview of PM2.5 and health outcomes: Focusing on components, sources, and pollutant mixture co-exposure

PM_2.5 varies in source and composition over time and space as a complicated mixture. Consequently, the health effects caused by PM_2.5 varies significantly over time and generally exhibit significant regional variations. According to numerous studies, a notable relationship exists between PM_2.5 and the occurrence of many diseases, such as respiratory, cardiovascular, and nervous system diseases, as well as cancer. Therefore, a comprehensive understanding of the effect of PM_2.5 on human health is critical. The toxic effects of various PM_2.5 components, as well as the overall toxicity of PM_2.5 are discussed in this review to provide a foundation for precise PM_2.5 emission control. Furthermore, this review summarizes the synergistic effect of PM_2.5 and other pollutants, which can be used to draft effective policies.

Chemical fingerprints and source resolution of atmospheric fine particles in an industrial harbor based on one-year intermittent field sampling data

This study investigated the spatiotemporal variation, chemical characteristics, and source resolution of PM_2.5 in an East Asian seaport adjacent to industrial complex and urban area. Three representative harbor sites were selected to simultaneously sample 24-h PM_2.5 once every 13 days in four seasons. A significant seasonal variation was observed with the highest and the lowest PM_2.5 concentration in February (winter) and May (summer), respectively. High contribution of secondary inorganic aerosols (SIAs) showed that SO₂ and NO_x emitted from neighboring combustion sources burning coal and heavy fuel oil (HFO) were the major precursors forming secondary inorganic PM_2.5. High ratios of V/Ni and V/Cu were observed in summer (June~August) since the prevailing west and southwest winds from outer port carried ship emissions to inter port. The correlation of chemical fingerprints (V, Ni, V/Ni, Zn, nss-SO₄^2-, OC) and the number of ships were high at the Zhung-He Site and moderate at the Qi-Ho Site. The Cl^-, Na⁺, V, Ni, nss-SO₄^2-, OC, and V/Ni of PM_2.5 were co-influenced by ship missions and oceanic spray in the Kaohsiung Harbor. The influences were relatively higher for winds blown from the harbor areas than those blown from the industrial areas. Oppositely, the Fe, Mn, Cr, Cu, Ca, Zn, and Al in PM_2.5 were higher for winds blown from the industrial areas than those from the harbor areas. The CMB receptor modelling resolved that the major sources of PM_2.5 were industrial missions, secondary aerosols, mobile sources, ship emissions, oceanic spray, fugitive dust, biomass burning, and organic carbon. Similar to Busan (South Korea), Brindisi (Italy), Lampedusa (Italy), and Barcelona (Spain), the contributions of ship emissions in the Kaohsiung Harbor were in the range of 7.4-7.8 %. Meanwhile, Kaohsiung Harbor was highly influenced by emissions from industrial areas and urban areas.

Long-Term Observation of Mixing States and Sources of Vanadium-Containing Single Particles from 2020 to 2021 in Guangzhou, China

The distribution of vanadium (V) in aerosols is commonly used to track ship exhaust emissions, yet the atmospheric abundance of V has been greatly reduced due to the implementation of a clean fuel policy. Recent research mainly discussed the chemical compositions of ship-related particles during specific events, yet few studies focus on the long-term changes of V in the atmosphere. In this study, a single-particle aerosol mass spectrometer was used to measure V-containing particles from 2020 to 2021 in Huangpu Port in Guangzhou, China. The long-term trend of the particle counts of V-containing particles declined annually, but the relative abundance of V-containing particles in the total single particles increased in summer due to the influence of ship emissions. Positive matrix factorization revealed that in June and July 2020, 35.7% of the V-containing particles were from ship emissions, followed by dust and industrial emissions. Furthermore, more than 80% of the V-containing particles were found mixing with sulfate and 60% of the V-containing particles were found mixing with nitrate, suggesting that the majority of the V-containing particles were secondary particles processed during the transport of ship emissions to urban areas. Compared with the small changes in the relative abundance of sulfate in the V-containing particles, the relative abundance of nitrate exhibited clear seasonal variations, with a high abundance in winter. This may have been due to the increased production of nitrate from high concentrations of precursors and a suitable chemical environment. For the first time, the long-term trends of V-containing particles in two years are investigated to demonstrate changes in their mixing states and sources after the clean fuel policy, and to suggest the cautious application of V as an indicator of ship emissions.

The variation of PM2.5 from ship emission under low-sulfur regulation: A case study in the coastal suburbs of Kitakyushu, Japan

From January 1, 2020, the International Maritime Organization (IMO) regulation about the limit of fuel sulfur content to 0.5 % become effective, and ships commonly install sulfur scrubbers or use low-sulfur fuel or liquefied natural gas to replace sulfur-rich heavy fuel oil. In this study, the 4-year PM_2.5 sampling in the coastal suburbs of Kitakyushu, Japan clearly indicated the significant effects of relevant regulation and countermeasures on particle emissions in this receptor site. From the perspective of air quality, an obvious decrease in the mass concentration of ship-emitted particles was observed in 2020, and the contribution of sulfate could reach 60 %. The ammonium concentration was mainly controlled by sulfate and nitrate, and its reduction also could not be ignored, accounting for about 17 %. In terms of public health, the particle exposure risk also changed greatly, mainly due to the reduction of risk levels for As, W, Sb, V, Ni, and Cd; the lowest non-carcinogenic risk and carcinogenic risk for both adults (HI = 1.2 and CR = 5.7 × 10^-5) and children (HI = 9.9 and CR = 1.1 × 10^-4) all occurred in 2020. However, these reduced health risks were still not within the safe level (except for the carcinogenic risk for adults), a fact that requires continued attention. This result exposed the deficiency of current countermeasures regarding the IMO's fuel sulfur content limit in Kitakyushu City, and increasing the proportion of ships using clean fuels (liquefied natural gas, methanol, etc.) would surely alleviate the particle pollution caused by ship emissions.

Exhaust and non-exhaust contributions from road transport to PM10 at a Southern European traffic site

It is a well - established fact that road traffic is one of the main contributors to ambient levels of airborne particulate matter (APM). This study was carried out at a traffic site in which the PM₁₀ levels are monitored all year round. A trend analysis of these levels revealed that over a decade there was no discernible trend, with the PM₁₀ concentrations normally hovering around the EU limit values. In 2018, one of these limit values was exceeded. The contribution of traffic at the site was therefore investigated through a chemical speciation of 209 PM₁₀ samples collected throughout this year. The speciation data were used in a source apportionment exercise in which the output of the PMF model was further refined using the lesser-known, constraint weighted non - negative matrix factorization (CW - NMF) model. This technique enabled the isolation of two factors clearly related to traffic, which were labelled as "exhaust contribution" (responsible for 3.4% of the PM₁₀), "tire/brake wear contribution" (contributing 17% of the PM₁₀). Additionally, a factor including both traffic resuspended dust and crustal material was also isolated and labelled "road dust/crustal" factor. The two contributors to the factor jointly contribute 18% to the PM₁₀ and the contribution of the traffic resuspended dust was estimated at 7.3%. The traffic resuspended component of this factor together with the "tire/brake wear contribution" jointly make up the non-exhaust contribution of traffic - derived dust. Consonant with what has been known for quite some time, the exhaust fraction is the minor component of traffic PM₁₀. It is therefore, clear that policies aimed at controlling traffic derived PM₁₀ pollution at the receptor will have a minimal effect unless the non - exhaust emissions are adequately controlled.

The Impact of Meteorological Conditions and Agricultural Waste Burning on PM Levels: A Case Study of Avellino (Southern Italy)

In this work, the effect of the meteorological conditions and the agricultural waste burning on PM air pollution levels has been investigated in the city of Avellino, located in the Sabato Valley (southern Italy). Avellino has been described among the most polluted towns in Italy in terms of particulate matter (PM) during the last 10 years. The main aim of this study was to analyze the air quality data collected in Avellino and its surroundings during September 2021. In this period, the air quality in the Sabato Valley has been adversely affected by agricultural practices, which represent a significant source of PM. The impact of agricultural waste burning on PM levels in Avellino has been determined through an integrated monitoring network, consisting of two fixed urban reference stations and by several low-cost sensors distributed in the Sabato Valley. In the considered period, the two reference stations recorded several exceedances of the daily average PM₁₀ legislative limit value (50 µg m^-3) in addition to high concentrations of PM_2.5. Moreover, we provide a detailed description of the event that took place on 25 September 2021, when the combined effect of massive agricultural practices and very stable atmospheric conditions produced a severe pollution episode. Results show PM exceedances in Avellino concurrent with high PM values in the areas bordering the city due to agricultural waste burning and adverse meteorological conditions, which inhibit PM dispersion in the atmosphere.

Possible influence of shipping emissions on metals in size-segregated particulate matter in Guanabara Bay (Rio de Janeiro, Brazil)

In the world of growing maritime fleets, ships powered by fossil fuels are being widely used that are responsible for atmospheric emissions such as particulate matter (PM). When inhaled, these can cause serious injury to the body and affect internal organs, because the particle size is on a tiny scale. The International Convention for the Prevention of Pollution from Ships (MARPOL) regulates the standards for emissions from marine diesel engines. However, although they pose risks to human health and the environment, the metals present in PM are not covered by Brazilian national current legislation. This study is based on the results of sampling of PM in the atmosphere of Guanabara Bay, Rio de Janeiro, Brazil, by means of the MOUDI cascade impactor, followed by acid opening of the collected PM and subsequent chemical analysis by ICP-MS for the determination of Ba, Ca, Cd, Co, Cu, Cr, Fe, Mg, Mn, Ni, Pb, V, and Zn. In coarse particles, the mean values ranged from 0.11 ng m^-3 for Ba to 24.9 ng m^-3 for Fe; in fine particles, from 0.07 ng m^-3 for Co to 25.0 ng m^-3 for Fe; and in ultrafine particles, from 0.11 ng m^-3 for Ba to 9.71 ng m^-3 for Fe. Finally, the nanoparticles (Ba and Ca) were not detected and the maximum value obtained was 5.32 ng m^-3 for Mn.

Chemical characterisation of PM10 from ship emissions: a study on samples from hydrofoil exhaust stacks

A chemical characterization of PM10 collected at hydrofoil exhaust stacks was performed conducting two on-board measuring campaigns, with the aim of assessing the ship emission impact on PM10 collected in the coastal area of Naples (Southern Italy) and providing information about the characteristics of this important PM emission source.Samples were analysed determining the contribution of different chemical parameters to PM10's mass, which consisted of polycyclic aromatic hydrocarbons (PAHs) (0.10 ± 0.12%), total carbon (61.9% ± 20.0%, with 40.4% of organic carbon, OC, and 21.5% of elemental carbon, EC) and elemental fraction (0.44% ± 1.00%). Differences in terms of composition and chemical parameter profiles were observed between samples collected during offshore navigation (Off) and samples collected during shunting operations (SO), the latter of higher concern on a local scale. For SO samples, lower contributions of OC and EC were observed (39.7% and 19.6% respectively) compared to Off samples (41.5% and 24.2%), and an increase in terms of elements (from 0.32 to 0.51%) and PAHs (from 0.06 to 0.12%) concentrations was observed. In addition, enrichment factors (EFs) for some elements such as V, Zn, Cd, Cu, Ag and Hg as well as PAHs profile varied significantly between SO and Off. Data presented here were compared with data on chemical composition of PM10 sampled in a tunnel, in a background site and in an urban site in the city of Naples. Results indicated that shipping activities contributed significantly to the emission of V and, in some extent, Zn and Cd; in addition, PAH profiles indicated a greater contribution to urban PM10 from vehicular traffic than shipping emissions. These results can significantly contribute to the correct evaluation of the influence of shipping emission on PM10 generation in urban coastal areas and can be a useful reference for similar studies. The coastal area of Naples is an important example of the coexistence of residential, touristic and natural areas with pollutants emission sources including, among the others, shipping emissions. In this and similar contexts, it is important to distinguish the contribution of each emission source to clearly define environmental control policies.

Spatiotemporal Variation and Influencing Factors of TSP and Anions in Coastal Atmosphere of Zhanjiang City, China

Water-soluble anions and suspended fine particles have negative impacts on ecosystems and human health, which is a current research hotspot. In this study, coastal suburb, coastal urban area, coastal tourist area, and coastal industrial area were explored to study the spatiotemporal variation and influencing factors of water-soluble anions and total suspended particles (TSP) in Zhanjiang atmosphere. In addition, on-site monitoring, laboratory testing, and analysis were used to identify the difference of each pollutant component at the sampling stations. The results showed that the average concentrations of Cl⁻, NO₃⁻, SO₄²⁻, PO₄³⁻, and TSP were 29.8 μg/m³, 19.6 μg/m³, 45.6 μg/m³, 13.5 μg/m³, and 0.28 mg/m³, respectively. The concentration of Cl⁻, NO₃⁻, PO₄³⁻, and atmospheric TSP were the highest in coastal urban area, while the concentration of SO₄²⁻ was the highest in coastal industrial area. Moreover, there were significantly seasonal differences in the concentration of various pollutants (p < 0.05). Cl⁻ and SO₄²⁻ were high in summer, and NO₃⁻ and TSP were high in winter. Cl⁻, SO₄²⁻, PO₄³⁻, and TSP had significant correlations with meteorological elements (temperature, relative humidity, atmospheric pressure, and wind speed). Besides, the results showed the areas with the most serious air pollution were coastal urban area and coastal industrial area. Moreover, the exhaust emissions from vehicles, urban enterprise emissions, and seawater evaporation were responsible for the serious air pollution in coastal urban area. It provided baseline information for the coastal atmospheric environment quality in Zhanjiang coastal city, which was critical to the mitigation strategies for the emission sources of air pollutants in the future.

Source attribution and quantification of atmospheric nickel concentrations in an industrial area in the United Kingdom (UK)

Pontardawe in South Wales, United Kingdom (UK), consistently has the highest concentrations of nickel (Ni) in PM₁₀ in the UK and repeatedly breaches the 20 ng m^-3 annual mean EU target value. Several local industries use Ni in their processes. To assist policy makers and regulators in quantifying the relative Ni contributions of these industries and developing appropriate emission reduction approaches, the hourly concentrations of 23 elements were measured using X-ray fluorescence alongside meteorological variables and black carbon during a four-week campaign in November-December 2015. Concentrations of Ni ranged between 0 and 2480 ng m^-3 as hourly means. Positive Matrix Factorization (PMF) was used to identify sources contributing to measured elements. Cluster analysis of bivariate polar plots of those factors containing Ni in their profile was further used to quantify the industrial processes contributing to ambient PM₁₀ concentrations. Two sources were identified to contribute to Ni concentrations, stainless-steel (which contributed to 10% of the Ni burden) and the Ni refinery (contributing 90%). From the stainless-steel process, melting activities were responsible for 66% of the stainless-steel factor contribution.

Particle release from refit operations in shipyards: Exposure, toxicity and environmental implications

European harbours are known to contribute to air quality degradation. While most of the literature focuses on emissions from stacks or logistics operations, ship refit and repair activities are also relevant aerosol sources in EU harbour areas. Main activities include abrasive removal of filler and spray painting with antifouling coatings/primers/topcoats. This work aimed to assess ultrafine particle (UFP) emissions from ship maintenance activities and their links with exposure, toxicity and health risks for humans and the aquatic environment. Aerosol emissions were monitored during mechanical abrasion of surface coatings under real-world operating conditions in two scenarios in the Mallorca harbour (Spain). Different types of UFPs were observed: (1) highly regular (triangular, hexagonal) engineered nanoparticles (Ti-, Zr-, Fe-based), embedded as nano-additives in the coatings, and (2) irregular, incidental particles emitted directly or formed during abrasion. Particle number concentrations monitored were in the range of industrial activities such as drilling or welding (up to 5 ∗ 10⁵/cm³, mean diameters <30 nm). The chemical composition of PM₄ aerosols was dominated by metallic tracers in the coatings (Ti, Al, Ba, Zn). In vitro toxicity of PM₂ aerosols evidenced reduced cell viability and a moderate potential for cytotoxic effects. While best practices (exhaust ventilation, personal protective equipment, dust removal) were in place, it is unlikely that exposures and environmental release can be fully avoided at all times. Thus, it is advisable that health and safety protocols should be comprehensive to minimise exposures in all types of locations (near- and far-field) and periods (activity and non-activity). Potential release to coastal surface waters of metallic engineered and incidental nanomaterials, as well as fine and coarse particles (in the case of settled dust), should be assessed and avoided.

Sources of airborne particulates (PM10) in the port city of Rijeka, Croatia

The air quality monitoring in Rijeka started in the early 1970s and has been oriented to air pollution caused by the big industrial sources (new petroleum refinery, oil burning power plant, coke plant), while maritime traffic was neglected. First emission inventory comprising port emission was done only in 2008 indicating similar level of emissions as road traffic. Further analyses on maritime impact were done within MED project POSEIDON. This was the good opportunity to perform positive matrix factorization (PMF) analysis on airborne particulate data and identify principal sources of pollution within the Rijeka urban area. PMF analyses of PM₁₀ collected from the urban background site in the period 2008-2010 identified 5 factors: biomass burning, secondary sulphates, sea spray, road/soil dust and metal industry/traffic. Condition probability functions (CPF) obtained from PMF factors of dust and secondary sulphates indicate that Ca, Fe, Zn and Cu originate from harbour area due to reloading of fertilizers and metal waste, as well as SO₄^2- and NH₄⁺ pointing to maritime corridor leading to the Rijeka harbour. These data could not quantify the maritime impact on the air quality, but gave the first estimation of contribution of various sources to air pollution within the Rijeka Bay area. The maritime contribution to air quality was estimated in other part of the same project, as primary PM_2.5 emission obtained from vanadium. Both primary PM_2.5 emission and polynuclear aromatic hydrocarbon profiles indicated reduced economic activity, including maritime traffic, during economic crisis in the period 2008-2012.

Inter-comparison of chemical characteristics and source apportionment of PM2.5 at two harbors in the Philippines and Taiwan

This study inter-compared the concentration and chemical characteristics of PM_2.5 at two harbors in East Asia, and identified the potential sources of PM_2.5 and their contribution. Two sites located at the Kaohsiung (Taiwan) and Manila (the Philippines) Harbors were selected for simultaneous sampling of PM_2.5 in four seasons. The sampling of 24-h PM_2.5 was conducted for continuous seven days in each season. Water-soluble ions, metallic elements, carbonaceous content, anhydrosugars, and organic acids in PM_2.5 were analyzed to characterize their chemical fingerprints. Receptor modeling and trajectory simulation were further applied to resolve the source apportionment of PM_2.5. The results indicated that the Kaohsiung Harbor was highly influenced by long-range transport (LRT) of polluted air masses from Northeast Asia, while the Manila Harbor was mainly influenced by local emissions. Secondary inorganic aerosols were the most abundant ions in PM_2.5. Crustal elements dominated the metallic content of PM_2.5, but trace elements were mainly originated from anthropogenic sources. Higher concentrations of organic carbon (OC) than elemental carbon (EC) was found in PM_2.5, with secondary OC (SOC) dominant to the former. Levoglucosan in PM_2.5 at the Manila Harbor were superior to those at the Kaohsiung Harbor due to biomass burning surrounding the Manila Harbor. Additionally, high mass ratios of malonic and succinic acids (M/S) in PM_2.5 indicated the formation of SOAs. Overall, the ambient air quality of Manila Harbor was more polluted than Kaohsiung Harbor. The Kaohsiung Harbor was more severely affected by LRT of polluted air masses from Northeast Asia, while those toward the Manila Harbor came from the oceans. The major sources resolved by CMB and PMF models at the Kaohsiung Harbor were secondary aerosols, ironworks, incinerators, oceanic spray, and ship emissions, while those at the Manila Harbor were secondary aerosols, soil dust, biomass burning, ship emissions, and oceanic spray.

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.

Source appointment of PM2.5 in Qingdao Port, East of China

Field measurements were conducted near Qingdao Port to characterize the particulate air pollutants, assess the spatial and seasonal characteristics of the pollutants, and identify the contribution from ship traffic emissions. By utilizing multiple statistical methods and data collected at two sites in Qingdao, we comprehensively explored the PM_2.5 seasonal characteristics and source apportionments of different PM_2.5 constituents, especially those originating from ship emissions, and identified potential source regions for samples collected in Qingdao. In this study, 118 concurrent daily PM_2.5 samples were collected from August 2018 to May 2019 at a port site (QH) and a coastal background site (BG). Vanadium (V) and Nickel (Ni) are the dominant metal elements from crude oil and crude oil combustion emissions. The significant correlations between V and Ni at both sampling sites, indicating that shipping emissions have a significant impact on the port and background area. Additionally, Ni and other metals showed significant correlations at the BG site, implying Ni also emission from the land-based oil at this site. The positive matrix factorization (PMF) model identified six main sources for the PM_2.5 samples in Qingdao, and they are coal combustion, industrial emissions/mineral dust, marine vessel emissions, secondary aerosols/biomass burning, sea salt/crustal emissions, and vehicle exhaust, respectively. Marine vessel emissions were the dominant contributor to PM_2.5 in Qingdao during the sampling periods (25.05%). The potential source contribution function (PSCF) analysis suggested that the Yellow Sea and Jiaodong Peninsula were the major sources regions for PM_2.5 in Qingdao. The Yellow Sea and Bohai Sea were the potential source regions for shipping emissions in Qingdao. Therefore, efforts to control shipping emissions should be strengthened not only at the Qingdao Port but also in surrounding ports.

Association of systemic inflammation and coagulation biomarkers with source-specific PM2.5 mass concentrations among young and elderly subjects in central Tehran

In this study, we investigated the association between short-term exposure to different sources of fine particulate matter (PM_2.5) and biomarkers of coagulation and inflammation in two different panels of elderly and healthy young individuals in central Tehran. Five biomarkers, including white blood cells (WBC), high sensitive C-reactive protein (hsCRP), tumor necrosis factor-soluble receptor-II (sTNF-RII), interleukin-6 (IL-6), and von Willebrand factor (vWF) were analyzed in the blood samples drawn every 8 weeks from the subjects between May 2012 and May 2013. The studied populations consisted of 44 elderly individuals at a retirement home as well as 40 young adults residing at a school dormitory. Positive Matrix Factorization (PMF)-resolved source-specific PM_2.5 mass concentrations and biomarker levels were used as the input to the linear mixed-effects regression model to evaluate the impact of exposure to previously identified PM sources at retirement home and school dormitory in two time lag configurations: lag 1-3 (1-3 days before the blood sampling), and lag 4-6 (4-6 days before the blood sampling). Our analysis of the elderly revealed positive associations of all biomarkers (except hsCRP) with particles of secondary origin in both time lags, further corroborating the toxicity of secondary aerosols formed by photochemical processing in central Tehran. Moreover, industrial emissions, and road dust particles were positively associated with WBC, sTNF-RII, and IL-6 among seniors, while vehicular emissions exhibited positive associations with all biomarkers in either first- or second-time lag. In contrast, most of the PM_2.5 sources showed insignificant associations with biomarkers of inflammation in the panel of healthy young subjects. Therefore, findings from this study indicated that various PM_2.5 sources increase the levels of inflammation and coagulation biomarkers, although the strength and significance of these associations vary depending on the type of PM sources, demographic characteristics, and differ across the different time lags. Implications: Tehran, the capital of Iran with a population of more than 9 million people, has been facing serious air pollution challenges as a result of extensive vehicular, and industrial activities in the previous years. Among various air pollutants in Tehran, fine particulate matters (PM_2.5, particles with aerodynamic diameters < 2.5 µm) are known as one of the most important critical pollutants, causing several adverse health impacts including lung cancer, respiratory, cardiovascular, and cardiopulmonary diseases. Therefore, a number of studies in the area have tried to investigate the adverse health impacts of exposure to PM_2.5. However, no studies have ever been conducted in Tehran to examine the association between specific PM_2.5 sources and biomarkers of coagulation and systemic inflammation as indicators of cardiovascular disorders. Indeed, this is the first study in the area investigating the association of source-specific PM_2.5 with biomarkers of inflammation including white blood cells (WBC), high sensitive C-reactive protein (hsCRP), tumor necrosis factor-soluble receptor-II (sTNF-RII), interleukin-6 (IL-6), and von Willebrand factor (vWF). Our results have important implications for policy makers in identifying the most toxic sources of PM_2.5, and in turn designing schemes for mitigating adverse health impacts of air pollution in Tehran.

Recent Advances in Studying Air Quality and Health Effects of Shipping Emissions

The increase of global commerce and tourism makes the shipping sector an important contributor of atmospheric particles and gaseous pollutants. These have impacts on both health and climate, especially in populated coastal areas. Maritime activities could be an important driver for economic and social development, however, they are also an environmental pressure. Several policies were implemented in the last decades, at local/regional or international levels, mainly focused on reducing the content of sulphur in marine fuels. The last international IMO-2020 regulation was enforced on 1 January 2020. This work reviews some recent studies on this topic delineating current knowledge of the impacts of maritime emissions on air quality and health and the future projections relative to the benefits of the implementation of the new IMO-2020 regulation. In addition, future perspectives for further mitigation strategies are discussed.

Chemical characterization and source apportionment of PM1 and PM2.5 in Tianjin, China: Impacts of biomass burning and primary biogenic sources

The submicron particulate matter (PM₁) and fine particulate matter (PM_2.5) are very important due to their greater adverse impacts on the natural environment and human health. In this study, the daily PM₁ and PM_2.5 samples were collected during early summer 2018 at a sub-urban site in the urban-industrial port city of Tianjin, China. The collected samples were analyzed for the carbonaceous fractions, inorganic ions, elemental species, and specific marker sugar species. The chemical characterization of PM₁ and PM_2.5 was based on their concentrations, compositions, and characteristic ratios (PM₁/PM_2.5, AE/CE, NO₃^-/SO₄^2-, OC/EC, SOC/OC, OM/TCA, K+/EC, levoglucosan/K⁺, V/Cu, and V/Ni). The average concentrations of PM₁ and PM_2.5 were 32.4 µg/m³ and 53.3 µg/m³, and PM₁ constituted 63% of PM_2.5 on average. The source apportionment of PM₁ and PM_2.5 by positive matrix factorization (PMF) model indicated the main sources of secondary aerosols (25% and 34%), biomass burning (17% and 20%), traffic emission (20% and 14%), and coal combustion (17% and 14%). The biomass burning factor involved agricultural fertilization and waste incineration. The biomass burning and primary biogenic contributions were determined by specific marker sugar species. The anthropogenic sources (combustion, secondary particle formation, etc) contributed significantly to PM₁ and PM_2.5, and the natural sources were more evident in PM_2.5. This work significantly contributes to the chemical characterization and source apportionment of PM₁ and PM_2.5 in near-port cities influenced by the diverse sources.

Chemical characteristics and sources of ambient PM2.5 in a harbor area: Quantification of health risks to workers from source-specific selected toxic elements

Samples of ambient PM_2.5 were collected in the Qingdao harbor area between 21 March and May 25, 2016, and analyzed to investigate the compositions and sources of PM_2.5 and to assess source-specific selected toxic element health risks to workers via a combination of positive matrix factorization (PMF) and health risk (HR) assessment models. The mean concentration of PM_2.5 in harbor area was 48 μg m^-3 with organic matter (OM) dominating its mass. Zn and V concentrations were significantly higher than the other selected toxic elements. The hazard index (HI) and cancer risk (R_i) of all selected toxic elements were lower than the United States Environmental Protection Agency (USEPA) limits. There were no non-cancer and cancer risks for workers in harbor area. The contributions from industrial emissions (IE), ship emissions (SE), vehicle emissions (VE), and crustal dust and coal combustion (CDCC) to selected toxic elements were 39.0%, 12.8%, 24.0%, and 23.0%, respectively. The HI values of selected toxic elements from IE, CDCC, SE, and VE were 1.85 × 10^-1, 7.08 × 10^-2, 6.36 × 10^-2, and 3.37 × 10^-2, respectively; these are lower than the USEPA limits. The total cancer risk (R_t) value from selected toxic elements in CDCC was 2.04 × 10^-7, followed by IE (6.40 × 10^-8), SE (2.26 × 10^-8), and VE (2.18 × 10^-8). CDCC and IE were the likely sources of cancer risk in harbor area. The Bo Sea and coast were identified as the likely source areas for health risks from IE via potential source contribution function (PSCF) analysis based on the results of PMF-HR modelling. Although the source-specific health risks were below the recommended limit values, this work illustrates how toxic species in PM_2.5 health risks can be associated with sources such that control measures could be undertaken if the risks warranted it.

Atmospheric fine particles in a typical coastal port of Yangtze River Delta

In recent decades, coastal ports have experienced rapid development and become an important economic and ecological hub in China. Atmospheric particle is a research hotspot in atmospheric environmental sciences in inland regions. However, few studies on the atmospheric particle were conducted in coastal port areas in China, which indeed suffers atmospheric particle pollution. Lack of the physicochemical characteristics of fine particles serves as an obstacle toward the accurate control for air pollution in the coastal port area in China. Here, a field observation was conducted in an important coastal port city in Yangtze River Delta from March 6 to March 19, 2019. The average PM_2.5 concentration was 63.7 ± 27.8 μg/m³ and NO₃^-, SO₄^2-, NH₄⁺, and organic matter accounted for ~60% of PM_2.5. Fe was the most abundant trace metal element and V as the ship emission indicator was detected. Transmission electron microscopy images showed that SK-rich, soot, Fe, SK-soot and SK-Fe were the major individual particles in the coastal port. V and soluble Fe were detected in sulfate coating of SK-Fe particles. We found that anthropogenic emissions, marine sea salt, and secondary atmosphere process were the major sources of fine particles. Backward trajectory analysis indicated that the dominant air masses were marine air mass, inland air mass from northern Zhejiang and inland-marine mixed air mass from Shandong and Shanghai during the sampling period. The findings can help us better understand the physicochemical properties of atmospheric fine particles in the coastal port of Eastern China.

Water/Methanol-Insoluble Brown Carbon Can Dominate Aerosol-Enhanced Light Absorption in Port Cities

Light absorption enhancement (E_abs) of black carbon (BC) is a key factor in global climate models and is impacted by brown carbon (BrC) and the lensing effect of coatings. We conducted an in-depth field study on E_abs for ambient aerosols at a monitoring point in Shanghai, China, by real-time aerosol optical property monitoring and high-performance liquid chromatography/diode array detector/quadrupole-time-of-flight mass spectrometry (HPLC/DAD/Q-ToF-MS) analysis. The results showed E_abs at λ = 530 nm caused by the lensing effect was about 1.39 ± 027, accounting for 18.84% of the total light absorption. In this study, BrC is classified as soluble BrC (soluble in both water and methanol) or insoluble BrC (insoluble in both water and methanol). Soluble BrC accounted for 13.68 ± 11.15% of the total aerosol light absorption. For the first time, we concluded that insoluble BrC can contribute more than 60 and 97% of total aerosol and BrC light absorption in port cities, respectively. The molecular analysis of soluble BrC identified N-containing aromatic compounds (4-nitrophenol, 4-nitrocatechol, methyl nitrophenol, methyl nitrocatechols, and nitro-1-naphthol) commonly observed in biomass burning emissions or biomass burning-impacted atmospheres. A series of components (C₁₆H₂₆O₃S, C₁₇H₂₈O₃S, C₁₈H₃₀O₃S, and C₁₉H₃₂O₃S) were determined to be emissions from nearby cargo ships filled with heavy fuel oil (HFO), which further confirmed that insoluble BrC emitted from cargo ships could be the largest contributor to E_abs. This study confirms the global significance of evaluating HFO used in port cities in climate models. The control measures of cargo ship emission should be considered for the related environmental and health issues in port cities.

Protocol development for real-time ship fuel sulfur content determination using drone based plume sniffing microsensor system

Pollutants from navigation sector are key contributors to emission inventories of most coastal cities with heavy port activities. The use of high fuel sulfur content (FSC) bunker oil by ocean going vessels (OGVs) has been identified as a major source of sulfur dioxide (SO₂). Government authorities all over the world, including Hong Kong government, have implemented air pollution control regulations to cap FSC of fuel used by OGVs to 0.5%, from the existing 3.5%, to reduce SO₂ emissions. However, the lack of efficient screening tools to identify non-compliant OGVs has prevented effective enforcement. This study developed and evaluated an unmanned aerial vehicle (UAV)-borne lightweight (750 g) microsensor system (MSS), which is capable of measuring ship plume SO₂, NO₂, NO, CO₂, CO, and particulate matter in real-time. Extensive experiments were conducted on the sensor system to evaluate its performance during laboratory and field operations. The effects of cross-sensitivity and meteorological conditions were studied and incorporated to account for the measurement conditions in dispersed ship plumes. The SO₂ to CO₂ concentration ratio-based FSC expression was formulated as per the 2016 European Union Directive and Regulations. Furthermore, the impact of plume dilution on the accuracy of FSC measurement was investigated at different stages using the MSS, with and without the UAV in both simulated conditions and real-world scenarios, maintaining a safe distance from the OGV exhaust stacks. The study demonstrates the robustness of using UAV-borne sensor system for ship emission sniffing and FSC determination. The results will assist in development of a technological framework for effective enforcement of ship emission control regulations.

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).

Long-Term Assessment of Air Quality and Identification of Aerosol Sources at Setúbal, Portugal

Understanding air pollution in urban areas is crucial to identify mitigation actions that may improve air quality and, consequently, minimize human exposure to air pollutants and their impact. This study aimed to assess the temporal evolution of the air quality in the city of Setúbal (Portugal) during a time period of 10 years (2003–2012), by evaluating seasonal trends of air pollutants (PM₁₀, PM_2.5, O₃, NO, NO₂ and NO_x) measured in nine monitoring stations. In order to identify emission sources of particulate matter, PM_2.5 and PM_2.5–10 were characterized in two different areas (urban traffic and industrial) in winter and summer and, afterwards, source apportionment was performed by means of Positive Matrix Factorization. Overall, the air quality has been improving over the years with a decreasing trend of air pollutant concentration, with the exception of O₃. Despite this improvement, levels of PM₁₀, O₃ and nitrogen oxides still do not fully comply with the requirements of European legislation, as well as with the guideline values of the World Health Organization (WHO). The main anthropogenic sources contributing to local PM levels were traffic, industry and wood burning, which should be addressed by specific mitigation measures in order to minimize their impact on the local air quality.

Source apportionment of PM2.5 at two Seattle chemical speciation sites

Positive Matrix Factorization analysis of PM_2.5 chemical speciation data collected from 2015-2017 at Washington State Department of Ecology's urban NCore (Beacon Hill) and near-road (10th and Weller) sites found similar PM_2.5 sources at both sites. Identified factors were associated with gasoline exhaust, diesel exhaust, aged and fresh sea salt, crustal, nitrate-rich, sulfur-rich, unidentified urban, zinc-rich, residual fuel oil, and wood smoke. Factors associated with vehicle emissions were the highest contributing sources at both sites. Gasoline exhaust emissions comprised 26% and 21% of identified sources at Beacon Hill and 10th and Weller, respectively. Diesel exhaust emissions comprised 29% of identified sources at 10th and Weller but only 3% of identified sources at Beacon Hill. Correlation of the diesel exhaust factor with measured concentrations of black carbon and nitrogen oxides at 10th and Weller suggests a method to predict PM_2.5 from diesel exhaust without a full chemical speciation analysis. While most PM_2.5 sources exhibit minimal change over time, primary PM_2.5 from gasoline emissions is increasing on average 0.18 µg m^-3 per year in Seattle.

IMPLICATIONS

This study utilizes Positive Matrix Factorization to determine PM_2.5 sources from chemical speciation measurements at two urban Seattle sites from 2015-2017. The paper reports PM_2.5 source trends, and extends previous source apportionment analyses in Seattle to the present day. The study also quantifies diesel PM_2.5 at a near-road site, and describes a predictive model that allows estimation of the contribution of diesel PM_2.5 to the total measured PM_2.5 at near-road sites across the country without a full chemical speciation analysis.

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

Current shipping activities employ about 3% of the world-delivered energy. Most of this energy is conveyed by diesel engines. In Europe, release of NO_x and particulate matter (PM) from shipping is expected to equal the road-transport one by the year 2020. This paper addresses a typical central Mediterranean city-port condition to evaluate the relative contribution of shipping activities to the local air quality. A 3-year long air quality dataset collected at the boundary between the port of Civitavecchia (the major port in central Italy) and the city itself was analyzed to evaluate the long-term, relative contribution of the port and of the city at determining the loads of EU-regulated pollutants (NO₂, PM₁₀ and SO₂). In addition, black carbon and ultrafine-to-coarse particles data collected along a short-term, intensive campaign were used to assess the port's role at emitting these unregulated pollutants. Cross-analysis of the measurements, allowed to assess which shipping-related activities and port's sectors represent the principal emitters. At the city-port boundary, the annual share of regulated pollutants originating in the port area by shipping and ground movements is of 33% for PM₁₀, 43% for NO₂, and 60% for SO₂. Analysis of non-regulated pollutants shows the in-port, high polluting potential of some ship categories, in particular those employing low-sulfur but poorly refined oils. These conditions appear to be more often associated with Ro-Ro passenger ships. Piers closest to the Civitavecchia urban settlements are also observed to host the largest emissions. Meteorology and location of the piers with respect to residential areas are confirmed to govern the port's share at impacting the city air quality. Even though air quality thresholds for regulated pollutants are not exceeded in Civitavecchia, constant consideration of an enlarged set of environmental variables should drive actions implemented to mitigate the port's impact onto the nearby city's air quality.

Characterisation of atmospheric pollution near an industrial site with a biogas production and combustion plant in southern Italy

Although biogas production can have some benefits, there is a research gap on potential influence of biogas plant emissions on local air quality, thus an accurate and comprehensive evaluation of impacts of this technology is needed. This study deals with this issue by means of a characterisation of air pollution near an industrial area including a biogas production (from biomass) and combustion plant located in South Italy. The methodology consists in advanced statistical analysis on concentration of gaseous pollutants, particles concentration and size distribution in number and mass, and PM_2.5 chemical composition. High-temporal resolution measurements, supported by ancillary meteorological parameters, and source apportionment of PM_2.5 using Positive Matrix Factorization (PMF) receptor model, are performed. The integrated approach provides the emissive picture consisting in different anthropogenic sources (i.e. traffic, biomass burning, and industrial facilities) with particular focus on biogas plant emissions. Results showed that CO and nitrogen oxides were influenced by vehicular traffic and biomass combustion, however, a contribution of the plant to NO was observed. SO₂ was influenced mainly by transport from the industrial zone, but a second local contribution compatible with the emissions of the biogas plant was detected. Number particle concentrations were analysed in four size ranges: nanoparticles (D < 0.05 μm), ultrafine particles (D < 0.3 μm), accumulation (0.3 < D < 1 μm) and coarse particles (D > 1 μm). Nanoparticles and ultrafine particles were mainly influenced by vehicular traffic and biomass burning, instead, a contribution of the plant was individuated in the accumulation mode. PMF5 identified the contribution of six sources: crustal (14.7% ± 2.1% of measured PM_2.5); marine aerosol (aged) (12.9% ± 2.3%); biomass burning (32.8% ± 1.4%); secondary sulphate (19.7% ± 2.4%); primary industrial emissions (5.4% ± 2.3%); traffic and secondary nitrate (17.0% ± 3.9%). The plant is likely to contribute to both sources, the industrial and the traffic plus secondary nitrate.

Chemical Composition of PM10 in 16 Urban, Industrial and Background Sites in Italy

Italy is characterized by a very variable configuration in terms of altitude, proximity to the sea, latitude and the presence of industrial plants. This paper summarizes the chemical characterization of PM10 obtained from 38 sampling campaigns carried out in 16 sites in Italy during the years 2008–2018. Chemical determinations include all macro-components (six macro-elements, eight ions, elemental carbon and organic carbon). The sum of the individual components agrees well with the PM10 mass. The chemical composition of the atmospheric aerosol clearly reflects the variety in the Italian territory and the pronounced seasonal variations in the meteoclimatic conditions that characterize the country. Macro-sources reconstruction allowed us to identify and evaluate the strength of the main PM10 sources in different areas. On 10 sampling sites, the soluble and insoluble fractions of 23 minor and trace elements were also determined. Principal Component Analysis was applied to these data to highlight the relationship between the elemental composition of PM10 and the characteristics of the sampling sites.

Physical Characteristics of Particle Emissions from a Medium Speed Ship Engine Fueled with Natural Gas and Low-Sulfur Liquid Fuels

Particle emissions from marine traffic affect significantly air quality in coastal areas and the climate. The particle emissions were studied from a 1.4 MW marine engine operating on low-sulfur fuels natural gas (NG; dual-fuel with diesel pilot), marine gas oil (MGO) and marine diesel oil (MDO). The emitted particles were characterized with respect to particle number (PN) emission factors, PN size distribution down to nanometer scale (1.2-414 nm), volatility, electric charge, morphology, and elemental composition. The size distribution of fresh exhaust particles was bimodal for all the fuels, the nucleation mode highly dominating the soot mode. Total PN emission factors were 2.7 × 10¹⁵-7.1 × 10¹⁵ #/kWh, the emission being the lowest with NG and the highest with MDO. Liquid fuel combustion generated 4-12 times higher soot mode particle emissions than the NG combustion, and the harbor-area-typical lower engine load (40%) caused higher total PN emissions than the higher load (85%). Nonvolatile particles consisted of nanosized fuel, and spherical lubricating oil core mode particles contained, e.g., calcium as well as agglomerated soot mode particles. Our results indicate the PN emissions from marine engines may remain relatively high regardless of fuel sulfur limits, mostly due to the nanosized particle emissions.

Study on Pollution Characterization and Source Apportionment of Daytime and Nighttime PM2.5 Samples in an Urban Residential Community in Different Weather Conditions

Daytime and nighttime PM_2.5 samples were collected from an urban community in Tianjin. The major chemical components in PM_2.5, including metal elements, polycyclic aromatic hydrocarbons and inorganic water-soluble ions, were monitored. A positive matrix factorization (PMF) model was used to apportion the potential sources of PM_2.5 under different weather conditions. When the Air Quality Index (AQI) was below 200, the concentrations of BaA, BbF, BkF, Na and NO₃^- during the nighttime were higher than those during the daytime. PMF analysis indicated that secondary aerosols (37.3%), biomass burning (26.7%) and coal combustion (26.0%) were important sources of PM_2.5 in the urban residential community when the AQI was greater than 200. When the AQI was less than 200 in the urban residential community, the main sources of PM_2.5 in the urban residential community were secondary aerosols (50.7%) and fossil fuel combustion (47.2%). The pollution status of PM_2.5 in the residential community of the urban area was serious, and the source apportionments of the PM_2.5 samples in the urban area were different under different weather conditions.

Estimated health impacts from maritime transport in the Mediterranean region and benefits from the use of cleaner fuels

Ship traffic emissions degrade air quality in coastal areas and contribute to climate impacts globally. The estimated health burden of exposure to shipping emissions in coastal areas may inform policy makers as they seek to reduce exposure and associated potential health impacts. This work estimates the PM2.5-attributable impacts in the form of premature mortality and cardiovascular and respiratory hospital admissions, from long-term exposure to shipping emissions. Health impact assessment (HIA) was performed in 8 Mediterranean coastal cities, using a baseline conditions from the literature and a policy case accounting for the MARPOL Annex VI rules requiring cleaner fuels in 2020. Input data were (a) shipping contributions to ambient PM2.5 concentrations based on receptor modelling studies found in the literature, (b) population and health incidence data from national statistical registries, and (c) geographically-relevant concentration-response functions from the literature. Long-term exposure to ship-sourced PM2.5 accounted for 430 (95% CI: 220-650) premature deaths per year, in the 8 cities, distributed between groups of cities: Barcelona and Athens, with >100 premature deaths/year, and Nicosia, Brindisi, Genoa, Venice, Msida and Melilla, with tens of premature deaths/year. The more stringent standards in 2020 would reduce the number of PM2.5-attributable premature deaths by 15% on average. HIA provided a comparative assessment of the health burden of shipping emissions across Mediterranean coastal cities, which may provide decision support for urban planning with a special focus on harbour areas, and in view of the reduction in sulphur content of marine fuels due to MARPOL Annex VI in 2020.

Study on the oxidation potential of the water-soluble components of ambient PM2.5 over Xi'an, China: Pollution levels, source apportionment and transport pathways

Reactive oxygen species (ROS) are a class of substances that are of general concern in terms of human health and are used to represent the oxidation potential (OP) of the atmosphere. In this study, the ROS levels in 116 daily fine particulate matter (PM_2.5) samples taken over Xi'an in 2017 were measured with the dithiothreitol (DTT) method. The sources of DTTv (volume-based DTT consumption) in PM_2.5 as well as their contributions were identified by both positive matrix factorization (PMF) and multiple linear regression (MLR) based on the measured chemical species in particulate matter (PM). The results showed that the yearly average DTTv over Xi'an was 0.53 nmol/min/m³ (0.19-1.10 nmol/min/m³). The highest DTTv level occurred in winter, followed by spring, summer and autumn. DTTv was the most strongly correlated with the water-soluble organic carbon (WSOC; r = 0.85), but the effects of WSOC on DTTv were very limited. SO₂, NO₂, CO, elemental carbon (EC) and K⁺ (r > 0.64) had moderate correlations with DTTv and were moderately related to environmentally persistent free radicals (EPFRs) (r = 0.56). The linear mixed-effects model showed that pollutants originating from incomplete combustion had greater effects on DTTv than those from complete combustion. Source apportionment results from PMF showed that motor vehicle emissions (27.4%), secondary sulfates (21.6%) and coal combustion sources (18.8%) were more important contributors to the DTTv in PM_2.5 than dust sources (8.4%), metal processing (4.9%), industrial emissions (11.3%) and secondary nitrates (7.5%). The PMF results for the DTTv were consistent with the MLR results, which verified that both PMF and MLR are feasible methods for source apportionment of PM_2.5 as well as specific species such as ROS and EPFRs. Backward trajectory clusters showed that the dominant cluster groups were local and regional transport, while the OP of the PM_2.5 over Xi'an was affected more by long-range transport than by local transport. As stated above, the improvement of atmospheric oxidation potential require not only regional efforts but also large-scale joint cooperation. Furthermore, this study on the OP of PM as well as the specific source information provides important guidance for health effect research.

Impact of harbour activities on local air quality: A review

Several harbour activities cause negative environmental impacts in the harbours' surrounding areas, namely the degradation of air quality. This paper intends to comprehensively review the status of the air quality measured in harbour areas. The published studies show a limited number of available air quality monitoring data in harbours areas, mostly located in Europe (71%). Measured concentrations of the main air pollutants were compiled and intercompared, for different countries worldwide allowing a large spatial representativeness. The higher NO₂ and PM₁₀ concentrations were found in Europe - ranging between 12 and 107 μg/m³ and 2-50 μg/m³, respectively, while the higher concentrations of PM_2.5 were found in Asia (25-70 μg/m³). In addition, the lower levels of SO₂ monitored in recent years suggest that current mitigation strategies adopted across Europe were very efficient in promoting the reduction of SO₂ concentrations. Part of the reviewed studies also estimated the contributions from ship emissions to PM concentration through the application of source apportionment methods, with an average of 5-15%. In some specific harbour areas in Asia, ships can contribute up to 7-26% to the local fine particulate matter concentrations. This review confirms that emissions from the maritime transport sector should be considered as a significant source of particulate matter in harbour areas, since this pollutant concentrations are frequently exceeding the established standard legal limit values. Therefore, the results from this review boost the implementation of mitigation measures, aiming to reduce, in particular, particulate matter emissions.

Effect of air masses motion on the rapid change of aerosols in marine atmosphere

The impact of air masses motion on marine aerosol properties was investigated using an on-board single particle mass spectrometer (SPAMS) deployed for the determination of single particle size resolved chemical composition over Southeast China Sea. Two aerosol blooms (E1 and E2) were observed during the cruise. High average particle number count occurred in E1 (7320), followed by E2 (5850), which was more than 100-150 times of the average particle number count during normal periods. Particles were classified as four major sources, including continental source, shipping source, marine source, and transport source based on the mass spectral similarity. Transport source was identified as those particles with high particle number count occurred only during aerosol bloom period. Three sub-types of EC-Ca, OC-Ca, and Al-rich were classified as transport source. EC-Ca was the dominant particles of the transport source, accounting for more than 70% of the total particles in aerosol bloom events. A uni-modal size distribution in the size range of 0.1-2.0 μm was observed during normal period, while a bimodal distribution with a tiny mode (<0.3 μm) and a coarse mode between 0.4 and 0.6 μm was present during aerosol bloom. The variation of aerosol source is consistent with air masses back trajectories, for the reason that most of the long-range air trajectories are from the ocean, while short air trajectories originate in the continental regions, which means that air masses have a significant impact on the aerosol physical-chemical properties along their tracks.

Air pollution survey across the western Mediterranean Sea: overview on oxygenated volatile hydrocarbons (OVOCs) and other gaseous pollutants

Despite the Mediterranean Sea basin is among the most sensitive areas over the world for climate change and air quality issues, it still remains less studied than the oceanic regions. The domain investigated by the research ship Minerva Uno cruise in Summer 2015 was the Tyrrhenian Sea. An overview on the marine boundary layer (MBL) concentration levels of carbonyl compounds, ozone (O₃), and sulfur dioxide (SO₂) is reported. The north-western Tyrrhenian Sea samples showed a statistically significant difference in acetone and SO₂ concentrations when compared to the south-eastern ones. Acetone and SO₂ values were higher in the southern part of the basin; presumably, a blend of natural (including volcanism) and anthropogenic (shipping) sources caused this difference. The mean acetone concentration reached 5.4 μg/m³; formaldehyde and acetaldehyde means were equal to 1.1 μg/m³ and 0.38 μg/m³, respectively. Maximums of 3.0 μg/m³ for formaldehyde and 1.0 μg/m³ for acetaldehyde were detected along the route from Civitavecchia to Fiumicino. These two compounds were also present at levels above the average in proximity of petrol-refining plants on the coast; in fact, formaldehyde reached 1.56 μg/m³ and 1.60 μg/m³, respectively, near Milazzo and Augusta harbors; meanwhile, acetaldehyde was as high as 0.75 μg/m³ at both sites. The levels of formaldehyde agreed with previously reported measurements over Mediterranean Sea and elsewhere; besides, a day/night trend was observed, confirming the importance of photochemical formation for this pollutant. According to this study, Mediterranean Sea basin, which is a closed sea, was confirmed to suffer a high anthropic pressure impacting with diffuse emissions, while natural contribution to pollution could come from volcanic activity, particularly in the south-eastern Tyrrhenian Sea region.

Assessment of source contribution to air quality in an urban area close to a harbor: Case-study in Porto, Portugal

Several harbors, like the Port of Leixões (Porto, Portugal), are located near urban and industrial areas, places where residential urban areas, highways and the refinery industry coexist. The need for assessing the contribution of the port to the air quality in its vicinity around the port is the motivation for the present study. This contribution was investigated using a numerical modelling approach based on the web-based research screening tool C-PORT. The impact of the meteorological conditions (namely atmospheric stability and wind direction) was first evaluated, and the most critical conditions for pollutants dispersion were identified. The dominant wind direction, from WSW, was responsible for the transport of pollutants over the surrounding urban area, which was potentiated by the diurnal sea breeze circulation. Multiple scenario runs were then performed to quantify the contribution of each emission sector/activity (namely maritime emissions; port activities; road traffic and refinery) to the ambient air quality. The multiple scenario runs indicated that land-based emission sources at the Port (including trucks, railways, cargo handling equipment and bulk material stored) were the major contributors (approximately 80%) for the levels of surface PM₁₀ concentrations over the study area. Whereas, the main drivers of NO_X concentrations were docked ships, responsible for 55-73% of the total NO_X concentrations.

Characterization and quantification of PM2.5 emissions and PAHs concentration in PM2.5 from the exhausts of diesel vehicles with various accumulated mileages

Road traffic is one of the main sources of particulate matter in the atmospheric environment. Notwithstanding its significance, there are noteworthy challenges in quantitative assessment of its contribution to the concentrations of airborne. This study reports on the characterization and quantification of PM_2.5 emissions and PAHs concentration in PM_2.5 from the exhausts of on-road diesel vehicles with various accumulated mileages in Kaohsiung City, Taiwan. Urban areas could be a subject matter not just in connection to deprived air quality, but similarly to pollution of other significant environmental media by air contaminants. To that end, our study intends to estimate the PM_2.5 emissions from diesel vehicles using diesel fuels and to analyze the PM_2.5 emissions and PAHs concentration in PM_2.5. In this study, particulate matters (PM_2.5) were characterized and quantified from a place impacted by diesel vehicles fueled with diesel in Kaohsiung City, Taiwan. The tested diesel vehicles with various accumulated mileages overs the model year comprising of the vehicles registered from 1984 to 2012 from different manufacturers (or brands) ranging from 8733 to 965,026 km (average 445,433 km) accumulative mileages. Exhaust constituents include CO, NOx, PM_2.5 and particle phase PAHs. The concentrations of twenty-one (21) priority polycyclic aromatic hydrocarbons (PAHs) were studied in the samples by their relationship with atmospheric PM_2.5. However, in relations to cumulative mileages, lower cumulative mileage (mileage <20,000 km) has the lowest CO and NOx emission factors. The mileage ranged from 20,001 to 30,000 km had an increased CO and NOx emission factors, respectively. Interestingly, with the increased high number of mileages ranged from 30,001 to 50,000 km, CO and NOx emission factor was observed to be declining, respectively. This could be attributed to the technological changes on new diesel vehicle models. But nonetheless, the trend of CO emission factor was found to be higher with an increasing of cumulative mileages as compared to the mileage that reached lower than 30,000 km.

Assigning machinery power values for estimating ship exhaust emissions: Comparison of auxiliary power schemes

While ship exhaust emissions can be calculated at both large scales and fine resolutions due to the availability of activity data from the Automatic Identification System, there are still uncertainties in the assignment of ship engine and boiler power, which then leads to uncertainties in the estimated emissions. Reliable information is usually available for main engines, including engine type and installed power, and physical models exist for estimating propulsive power requirements. However, similar models are not available for estimating auxiliary power requirements. This study examines methods for calculating the actual operating power of auxiliary engines and auxiliary boilers. Earlier approaches assumed that installed auxiliary engine power increased in proportion to installed main engine power. Auxiliary-to-main engine power ratios were specified by ship type, and load factors were specified by ship type and operating mode. Auxiliary boiler power was generally not differentiated by ship size. More recent approaches are based on extensive ship survey data, and give tables of auxiliary engine and auxiliary boiler power binned against ship type, ship size and operating mode. These surveys show that auxiliary power does not necessarily increase with ship size or main engine power. A revised approach based on the recent data sources is adopted and applied to a case study of four ports in southeast Australia. The revised approach is informed by a local survey of ships to investigate auxiliary power demand. Comparisons are made of the impact of the different approaches on the magnitude and spatial distribution of the emissions.