Conditional Bivariate Probability Function Research Articles

Source apportionment of PM2.5 using DN-PMF in three megacities in South Korea

AbstractPM2.5 pollution is problematic in megacities on the western coast in South Korea (Seoul, Incheon, and Gwangju). As these megacities are located downwind of China, their air quality is easily affected by local and long-range transport sources. PM2.5 samples collected in Seoul (n = 222), Incheon (n = 221), and Gwangju (n = 224) from September 2020 to March 2022, were chemically characterized. Dispersion normalized positive matrix factorization was applied to these PM2.5 speciated data to provide source apportionments. Nine common sources (including secondary nitrate, secondary sulfate, biomass burning, mobile, and waste incinerator) were identified at all sites. The conditional bivariate probability function helped to identify each site’s local sources. Joint potential source contribution function analysis identified northeast China and Inner Mongolia as potential source areas of long-range transport pollutants affecting all sites. Forced lifestyle changes due to the pandemic such as limited gatherings while increased recreational activities may have caused different patterns on the biomass burning source. The constraints on old vehicles during the policy implementation periods likely reduced the mobile source contributions in cities that adopted the policy. Secondary nitrate accounted for 40% of the PM2.5 mass at all sites, implying a significant impact from NOX sources. While the current policy focuses primarily on controlling primary emission sources, it should include secondary sources as well which may include precursor emissions control. Healthier air quality would be achieved if the policy effects are not limited to local, but also to foreign sources in regions upwind of Korea by intergovernmental collaboration.

Particulate black carbon mass concentrations and the episodic source identification driven by atmospheric blocking effects in Astana, Kazakhstan

Black carbon (BC) is a component of fine particulate matter (PM2.5) that is a key contributor to adverse human health effects and climate forcing. To date, BC mass concentrations and possible sources in Kazakhstan have not been studied. Thus, understanding the temporal variations of BC for a large developing region with a complex climate is useful. In this study, measurements of fine particulate BC mass concentrations in Astana were made from June 2020 to October 2021 by measuring light absorption of PM2.5 on filters. The mean BC concentration was 2.56 ± 1.29 μg m−3 with maximum and minimum monthly mean BC concentrations being 4.56 ± 2.03 μg m−3 and 1.12 ± 0.42 μg m−3 in January 2021 and June 2020, respectively. Temporal analyses of BC, SO2, PM10, NOx, CO, meteorological and atmospheric stability parameters were performed. Aggregated pollutant ‘episodic loadings’ during the heating and non-heating periods were identified. Their relationships with blocking anticyclones and cyclones were investigated by examining the reversal of meridional gradients at 500 hPa geopotential height (GPH) maps and identifying Omega (Ω) and Rex blocking types. Astana has some of the highest BC concentrations of cities worldwide. Seasonal BC source location identification using Conditional Bivariate Probability Function (CBPF) analysis implicated combined heat and power (CHP) plant emissions as the major BC source in Astana. Significant increases in BC concentrations were observed during the cold season due to numerous sources, generally poorer atmospheric dispersion and blocking events. The Concentration Weighted Trajectory (CWT) analysis results showed that the distribution of the 75th percentile of BC during episodic periods actively controlled by blockings exceeding than the entire measurement period, which may reflect cross-border transport and adjacent countries.

Source identification of ultrafine particulate matter and ammonia emissions in the metropolitan area

Previous studies have estimated the sources of particulate matter in the atmosphere. Among these, studying the sources of secondary aerosols harmful to human health is important. However, there is a lack of research on ammonia (NH3), a precursor to secondary aerosol formation. This study uses positive matrix factorization (PMF) model and conditional bivariate probability function (CBPF) model to estimate the sources of particulate matter and ammonia. The results showed that about 40% of the PM2.5 mass at both sites was attributable to secondary aerosol. To estimate the emission sources of ammonia that contribute to the generation of secondary aerosols, CBPF was utilized to model and compare the emission characteristics of categorized pollution sources and ammonia, and it was found that SMA had similar emission trends to industry, road dust, oil combustion, and biomass combustion, while GRA had similar emission trends to oil combustion and vehicle (diesel). Considering the results from these two regions, ammonia in the metropolitan area is more likely to be emitted from daily activities than from long distances. The study results demonstrate the major role of secondary aerosols on ambient PM2.5 concentrations and can help develop effective management strategies and policies for air pollution mitigation.

Attribution of aerosol particle number size distributions to main sources using an 11-year urban dataset

Abstract. Source apportionment was performed using size-segregated atmospheric particle number concentrations (PNCs) in 27 size channels over a diameter range of 6–1000 nm augmented by air pollutants with a time resolution of 1 h in Budapest for 11 full years. The input dataset was treated for the effect of the local meteorology using dispersion correction. Both the uncorrected dataset and corrected dataset were evaluated using positive matrix factorization for separate seasons. Six source types including nucleation, two road vehicle emission sources separated into a semi-volatile fraction and a solid-core fraction, a diffuse urban source, a secondary inorganic aerosol (SIA) source, and an ozone-associated secondary aerosol source were identified, characterized and quantified. The dispersion correction did not considerably change the profiles, diel variations or patterns of the sources, while it substantially modified the relative shares of the nucleation source in all seasons. The mean relative contributions of the traffic emissions (60 %) indicate that on-road motor vehicles were the leading source of particle numbers. The nucleation was responsible for 24 % of the PNC annually as a lower estimate. It exhibited a compound character consisting of photochemically induced nucleation and traffic-related nucleation. Its contributions were the highest in spring and the lowest in winter. The shares of the urban diffuse and SIA source types were the largest in autumn and winter and in spring and summer, respectively, but they were typically ⪅ 10 %. The O3-associated secondary aerosol made up the smallest (⪅ 3 %) contributions. The conditional bivariate probability function analysis showed considerable spatial variations in the source origin. The combination of the size-segregated particle number concentrations, wide overall range of the size channels, considerably long dataset, dispersion correction and modelling over separate seasons led jointly to a unique adaptation of the source apportionment and yielded novel and valuable insights into the urban aerosol sources and processes both for Budapest and in general.

Day–night variation, size distribution, source identification, and health risk of polycyclic aromatic hydrocarbons in particulate matter in Ulsan, South Korea

Particulate matter (PM) in 11 different sizes was collected at a semi-rural site in Ulsan, a multi-industrial city in South Korea, over one year from 2019 to 2020 to investigate the temporal patterns in size distribution and potential sources of polycyclic aromatic hydrocarbons (PAHs). The mean concentration of Σ21 PAHs was higher in winter (0.29 and 0.45 ng/m3 for coarse and fine PM, respectively) than in summer (0.06 and 0.07 ng/m3). Although there was no statistically significant difference between day and night for the concentration of individual PAHs in both coarse and fine PM, the concentrations were generally higher during the day than at night. During the day, Σ21 PAHs had two distinct peaks (0.056–0.10 μm and 3.20–5.60 μm) in winter, but they tended to partition to larger particles (1.00–1.80 μm and >18.0 μm) in summer. This result suggests that the volatilization of PAHs in smaller particles was enhanced by high-temperature conditions in summer, followed by their condensation onto larger particles. At night, Σ21 PAH peaks were mainly around the size of 0.7 μm (droplet mode), suggesting the importance of heterogeneous-aqueous reactions. The results of the conditional bivariate probability function and concentration-weighted trajectory indicate that the high concentrations of PAHs in summer and winter were more affected by local pollution and long-range atmospheric transport, respectively. The results of the health risk assessment demonstrate that PAHs in fine PM contributed significantly to cancer risk compared to those in coarse PM. In conclusion, investigating the size distribution of PAHs in particles is necessary to understand their environmental behaviors and evaluate potential health risks.

Chemical characteristics, morphology and source apportionment of PM10 over National Capital Region (NCR) of India.

The present study frames the physico-chemical characteristics and the source apportionment of PM10 over National Capital Region(NCR) of India using the receptor model's Positive Matrix Factorization (PMF) and Principal Momponent Mnalysis/Absolute Principal Component Score-Multilinear Regression (PCA/APCS-MLR). The annual average mass concentration of PM10 over the urban siteof Faridabad, IGDTUW-Delhi and CSIR-NPL of NCR-Delhi were observed to be 195 ± 121, 275 ± 141 and 209 ± 81µgm-3, respectively. Carbonaceous species (organic carbon (OC), elemental carbon (EC) and water-soluble organic carbon (WSOC)), elemental constituents (Al, Ti, Na, Mg, Cr, Mn, Fe, Cu, Zn, Br, Ba, Mo Pb) and water-soluble ionic components (F-, Cl-, SO42-, NO3-, NH4+, Na+, K+, Mg2+, Ca2+) of PM10were entrenched to the receptor models to comprehend the possible sourcesof PM10. The PMF assorted sources over Faridabad were soil dust (SD 15%), industrial emission (IE 14%), vehicular emission (VE 19%), secondary aerosol (SA 23%) and sodium magnesium salt (SMS 17%). For IGDTUW-Delhi, the sources were SD (16%), VE (19%), SMS (18%), IE (11%), SA (27%) and VE + IE (9%). Emission sources like SD (24%), IE (8%), SMS (20%), VE + IE (12%), VE (15%) and SA + BB (21%) were extracted over CSIR-NPL, New Delhi, which are quite obvious towards the sites. PCA/APCS-MLR quantified the similar sources with varied percentage contribution. Additionally, catalogue the Conditional Bivariate Probability Function (CBPF) for directionality of the local source regions and morphology as spherical, flocculent and irregular were imaged using a Field Emission-Scanning Electron Microscope (FE-SEM).

Identifying source apportionment of atmospheric particulate matter and gaseous pollutants using receptor models : A case study of Bengaluru, India

The data of Particulate matter PMs (PM2.5, PM10) and Gaseous Pollutants such as carbon monoxide (CO), methane (CH4), oxides of nitrogen (NOx: NO and NO2), non-methane hydrocarbons (NMHCs), sulfur dioxide (SO2), along with ammonia (NH3) at five different locations across Bengaluru from 1st January, 2017 to 20th March, 2018 were collected. The primary objective of this research work is to identify the sources of atmospheric particulate matter and gaseous pollutants using receptor models in Bengaluru, India. To execute this, receptor models, namely Conditional Bivariate Probability Function (CBPF) and Concentrated Weighted Trajectory (CWT) Analysis, are applied. Conditional Bivariate Probability Function (CBPF) shows that, annually, the maximum concentrations of PMs over receptor sites were detected during low wind speed (< 2 knots) along the north-east direction specifying that the long-range transport does not play an essential role in the transportation of higher concentrations of PM and their primary source region may be localized. Concentrated Weighted Trajectory (CWT) analysis shows that, seasonally, the highest air mass contribution of about 37% was noticed in summer, whereas the lowest was in the post-monsoon season (13%). The significant contribution of PM2.5 transported from long distances was during monsoon, and in the case of PM10, it was in summer. The study suggests that the long-range transport of PMs and gaseous Pollutants was not vital and was observed to be localized.

Evaluation of PM2.5 spatio-temporal variability and hotspot formation using low-cost sensors across urban-rural landscape in lucknow, India

The high-resolution spatio-temporal monitoring through low-cost sensors (LCS) provides important insights into the dynamics of localized pollution patterns and in conceptualizing effective environmental management and public health interventions. We assessed the role of meteorology and local sources on spatially distributed PM2.5 pollutants measured from a unique urban-rural scaled network of LCS in Lucknow, India. The city-wide average PM2.5 annual cycle ranged between 29 ± 7 μg/m3 during the monsoon to 64 ± 30 μg/m3 during the rest of the year. During non-monsoon seasons, >60% of air mass trajectories indicated regional level transportations primarily from the north-western plains of the Indo-Gangetic basin, with peak weighted concentration weighted trajectory (WCWT, scale: 0–100) value estimated at >70. To analyze the impact of local sources, we designed a statistical classification method to divide each seasonal distribution into five incremental concentration groups ranging from no risk zone to hotspots. The hotspots were identified both within urban and rural regions with their average concentration measured as 23 μg/m3 and 26 μg/m3 higher than the rest of the regions in pre-monsoon (2 hotspots) and post-monsoon (4 hotspots) season, respectively. Further analysis shows that the nighttime concentrations were much higher in several locations (up to 40% in pre-monsoon and 54% in post-monsoon compared to their daytime levels), indicating the greater impact of local sources in the presence of low boundary layer height. A diurnal trend analysis along with conditional bivariate probability function (CBPF) was performed to interpret the characteristics and locations of the dominant sources. The study highlights the importance of a dense network of LCS to scale air quality monitoring in spatially heterogeneous environments and as a futuristic tool for PM2.5 exposure-based studies.

Physicochemical characteristics and seasonal variations of PM2.5 in urban, industrial, and suburban areas in South Korea

Among countries that are a part of the Organization for Economic Co-operation and Development, South Korea is the most exposed to PM2.5. Despite the country having implemented various strategies to limit PM2.5 emissions, its concentrations are still high enough to pose serious environmental and health concerns. Herein, we monitored various physiochemical properties of PM2.5 across different regions in South Korea from January 1 to December 31, 2021. Specifically, the study area consisted of the city center, industrial complexes, and suburban areas. Before analyzing dynamics of emissions specific to each site, the Clean Air Policy Support System data for the three areas were compared to elucidate their respective primary emission sources. The particle concentrations for the three areas were 21.8–26.44 µg/m3, with the highest concentrations being observed in March. All the three areas exhibited high ratios of NO3− across all seasons. The particle number concentrations in the three sites were 1.3–1.5 × 107, and the peak points of the concentrations were different in every site: city center (40 nm), industrial complexes (60 nm), and suburban areas (80 nm). We also conducted potential source contribution function and conditional bivariate probability function analyses. These analyses were conducted to determine the inflow direction of the pollution sources for high PM2.5 episodes. For the episodes that occurred in spring and winter, there were no differences in the PM2.5 concentrations between the three sites. Overall, the insights gained from this study offer a framework for developing air-quality management policies in South Korea, specifically in the context of PM2.5 emissions.

Annual and Periodic Variations of Particulates and Selected Gaseous Pollutants in Astana, Kazakhstan: Source Identification via Conditional Bivariate Probability Function

Annual and Periodic Variations of Particulates and Selected Gaseous Pollutants in Astana, Kazakhstan: Source Identification via Conditional Bivariate Probability Function

Spatiotemporal distribution of pollutants and impact of local meteorology on source influence on pollutants' level in a traffic air-shed in Lagos megacity, Nigeria.

Pollution from vehicular emissions is a major cause of poor air quality observed in many urban and semi-urban towns and cities. As such, this study was conducted to assess air quality and the spatiotemporal distribution of vehicular and traffic-related pollutants in several air sheds of Lagos megacity, the economic nerve centre of Nigeria. A setup of low-cost air quality sensors comprising five (5) units was deployed between November 2018 and February 2019 within traffic corridors in the heart of the city. Diurnal variation of pollutants indicated that carbon dioxide (CO2) peaked during the early hours of the day, total oxide (Ox = NO2+O3) peaked at mid-day while carbon monoxide (CO) had two distinct peaks which correspond to morning and evening rush hours. Nitrogen dioxide (NO2) concentration peaked during evening hours. Average concentrations are NO2 (97.1 ± 9.7) ppb, Ox (78.6 ± 27.2) ppb, CO2 (450.1 ± 31.2) ppm, and CO (2285.63 ± 743.7) ppb. Average concentrations of pollutants were above thresholds set by the World Health Organization (WHO) except for NO2 which was within the range permissible limits. The implication of this is that the atmosphere is polluted due to elevated concentrations of airborne pollutants, an indication which is of both health and environmental concern. The air quality index (AQI) indicates that the quality of ambient air varies from good to very unhealthy for Ox, and unhealthy to very unhealthy for CO, while AQI for PM2.5 and PM10 showed hazardous at all the sampling locations except at UNILAG where it is unhealthy for the sensitive group. For all of the sampling sites, conditional bivariate probability function (CBPF) plots show a significant agreement with the location of known pollution sources.

Source Apportionment of Ambient Fine Particle Size Distribution Using Positive Matrix Factorisation and Conditional Bivariate Probability Function in a Coastal Urban Area

Source Apportionment of Ambient Fine Particle Size Distribution Using Positive Matrix Factorisation and Conditional Bivariate Probability Function in a Coastal Urban Area

PM2.5 carbonaceous components and mineral dust at a COALESCE network site - Bhopal, India: Assessing the impacts of COVID-19 lockdowns on site-specific optical properties

Thermal elemental carbon (EC), optical black carbon (BC), organic carbon (OC), mineral dust (MD), and 7-wavelength optical attenuation of 24-hour ambient PM2.5 samples were measured/estimated at a regionally representative site (Bhopal, central India) during a business-as-usual year (2019) and the COVID-19 lockdowns year (2020). This dataset was used to estimate the influence of emissions source reductions on the optical properties of light-absorbing aerosols. During the lockdown period, the concentration of EC, OC, BC880 nm, and PM2.5 increased by 70 % ± 25 %, 74 % ± 20 %, 91 % ± 6 %, and 34 % ± 24 %, respectively, while MD concentration decreased by 32 % ± 30 %, compared to the same time period in 2019. Also, during the lockdown period, the estimated absorption coefficient (babs) and mass absorption cross-section (MAC) values of Brown Carbon (BrC) at 405 nm were higher (42 % ± 20 % and 16 % ± 7 %, respectively), while these quantities for MD, i.e., babs-MD and MACMD values were lower (19 % ± 9 % and 16 % ± 10 %), compared to the corresponding period during 2019. Also, babs-BC-808 (115 % ± 6 %) and MACBC-808 (69 % ± 45 %) values increased during the lockdown period compared with the corresponding period during 2019. It is hypothesized that although anthropogenic emissions (chiefly industrial and vehicular) reduced drastically during the lockdown period compared to the business-as-usual period, an increase in the values of optical properties (babs and MAC) and concentrations of BC and BrC, were likely due to the increased local and regional biomass burning emissions during this period. This hypothesis is supported by the CBPF (Conditional Bivariate Probability Function) and PSCF (Potential Source Contribution Function) analyses for BC and BrC.

Emission Source Areas of Fine Particulate Matter (PM2.5) in Ho Chi Minh City, Vietnam

This study aims to determine emission source areas of fine particulate matter (PM2.5) in Ho Chi Minh (HCM) City, Vietnam, using a conditional bivariate probability function (CBPF) and hybrid receptor models, including three-dimensional potential source contribution function (3D-PSCF) and concentration-weighted trajectory (3D-CWT), considering latitudes, longitudes, and height of trajectory segments. Uncertainties of the CBPF and 3D-PSCF/3D-CWT were evaluated based on the 95th confidence intervals and 95% confidence levels, respectively. For the local scale, PM2.5 in HCM City was primarily emitted from shallow or common ground sources (e.g., vehicle emissions) throughout the year. Regarding non-local source areas, PM2.5 in HCM City is contributed by those originated from the East Sea (e.g., shipping emissions) and southeastern Vietnam (e.g., Binh Duong and Dong Nai provinces) having several industrial zones with PM2.5 emission sources, especially in the dry season (December to April of the following year). In the rainy season (May–November), PM2.5 derived from emission sources in the Mekong Delta (e.g., biomass burning) might be transported to HCM City. However, contribution of the non-local sources to PM2.5 pollution in HCM City during the rainy season is less important because of PM2.5 deposition stemmed from the high rainfall amount in this season.

Temporal variation and source identification of carbonaceous aerosols in Monrovia, Liberia

This study examined the atmospheric Black Carbon (BC) and Organic Carbon (OC) data for two years from January 2019 to December 2020 in Monrovia, Liberia. This study is the first of its kind in Monrovia, Liberia and the Mano River Union region. The objective is to evaluate the temporal variation in BC and OC over Monrovia and locate the probable local and regional source locations contributing to BC and OC therein. We also presented here the relationship of BC and OC with meteorological parameters. The highest BC (∼1.4 µg m−3) and OC (∼14 µg m−3) concentrations were observed in January 2019 and 2020. A clear seasonal effect was found in both years, with high mean BC (∼4.9 µg m−3) and OC (∼10 µg m−3) during the dry season (November to April). Diurnal variation suggested high BC and OC during 5:00–7:00 AM, 12 noon, 2:00 PM, and 4:00–7:00 PM. Long-range transportation and local emission sources were studied using Conditional Bivariate Probability Function (CBPF), and Concentration Weighted Trajectory (CWT). CBPF indicated that higher BC and OC concentrations were experienced when the wind was blowing from the South (at >2 ms−1) and North-West (1–2 ms−1) where a lot of shipping activities are carried out. CWT for BC showed that the air mass passes over Senegal through Guinea Bissau via the Atlantic Ocean while for OC, on the Atlantic Ocean and Freeport of Monrovia, indicating shipping emissions as probable sources. The results of this study can help policymakers devise appropriate strategies to control the BC and OC emissions over Monrovia, Liberia.

Variations in local, transported, and exposure risks of PM2.5 pollution: Insights from long-term monitoring data in mega coastal city

Urban air quality is influenced by both local and external sources of pollution. The outbreak of Coronavirus COVID-19 had led to implementation of stringent lockdowns at different levels of governance. National Level Lockdown (NLL) was imposed in 2020 and State Level Lockdown (SLL), in 2021 to curb the spread of disease. A direct consequence of lockdown is the dramatic improvement of air quality in various urban agglomerations. The present study investigated the effects of national and regional lockdown on PM2.5 levels at various urban morphological units in the Chennai Metropolitan Region, the fourth-largest urban conglomeration in India. Hourly measurements of PM2.5 over a 6-year period (2016–2021) at three monitoring sites in Chennai were segregated into Pre-lockdown Phase (PLP) (2016–2019), NLL, and SLL to analyze reductions in PM2.5 levels. Local PM2.5 sources were investigated using Conditional Bivariate Probability Function (CBPF) whereas transported PM2.5 was evaluated using Concentration Weighted Trajectory (CWT) and Cluster Analysis. The results showed that PM2.5 in Chennai Metropolitan Region reduced by 33.45% during NLL and 48.95% during SLL when compared to PLP. Mann Kendall Test showed a statistically significant (p < .001) decreasing PM2.5 trend at Manali Monitoring Site, Alandur Monitoring Site, and Velachery Monitoring Site. CBPF showed variations in local contributions for all sites during the selected time frames. CWT and Cluster analysis showed reductions in transported PM2.5 during NLL and SLL when compared to PLP. Health Risk Assessment using Integrated Exposure Response (IER) model function showed a decreasing trend of excess mortality for various health endpoints over 6-year period. Steep reductions in excess mortality cases were observed during NLL and SLL. The results show that lockdown implemented at the state level proved to be more effective than the national level in reducing PM2.5 levels over Chennai metropolitan Region.

Black carbon and particulate matter mass concentrations in the Metropolitan District of Caracas, Venezuela: An assessment of temporal variation and contributing sources

Atmospheric aerosols play an important role in atmospheric processes and human health. Characterizing atmospheric aerosols and identifying their sources in large cities is relevant to propose site-specific air pollution mitigation strategies. In this study, we measured the mass concentration of atmospheric aerosols with an aerodynamic diameter smaller than 2.5 µm (PM2.5) in the city of Caracas (urban) and in a tropical montane cloud forest (suburban site, located in a mountainous area 11 km far from Caracas) between June 2018 and October 2019. We also measured equivalent black carbon (eBC) mass concentration in PM2.5 in Caracas during the same period. Our goal is to assess PM2.5 and eBC temporal variation and identify their major sources in the area. eBC showed a pronounced diurnal cycle in the urban site, mainly modulated by traffic circulation and the diurnal changes of the mixing layer height. In contrast, PM2.5 showed stable median values during the day with slight variations like that of eBC. In the forest site, PM2.5 values were higher in the afternoons due to the convective transport of aerosols from Caracas and other surrounding urban areas located in adjacent valleys. The annual median for eBC and PM2.5 was 1.6 and 9.2 µg m–3, respectively, in the urban site, while PM2.5 in the forest site was 6.6 µg m–3. To our knowledge, these are the first measurements of this type in the northernmost area of South America. eBC and PM2.5 sources identification during wet and dry seasons was obtained by percentiles of the conditional bivariate probability function (CBPF). CBPF showed seasonal variations of eBC and PM2.5 sources and that their contributions are higher during the dry season. Biomass burning events are a relevant contributing source of aerosols for both sites of measurements inferred by fire pixels from satellite data, the national fire department’s statistics data, and backward trajectories. Our results indicate that biomass burning might affect the atmosphere on a regional scale, contribute to regional warming, and have implications for local and regional air quality and, therefore, human health.

Immission levels and identification of sulfur dioxide sources in La Oroya city, Peruvian Andes.

La Oroya is a city in the Peruvian Andes that has suffered a serious deterioration in its air quality, especially due to the high rate of sulfur dioxide (SO2) emissions, which underlines the importance of knowing its sources of contamination and variation over the years. In this sense, this study aimed to evaluate the immission levels and determine the sources of SO2 contamination in La Oroya. This analysis was performed using the hourly concentration data of SO2, and meteorological variables (wind speed and direction), which were analyzed for a period of three years (2018–2020). Graphs of time series, wind and pollutant roses, bivariate polar graphs, clustering k-means, nonparametric statistical tests, and the application of the conditional bivariate probability function were performed to analyze the data and identify the emission sources. The mean concentration of SO2 was 264.2 μg m−3 for the study period, where 55.66 and 2.37% of the evaluated days exceeded the guideline values recommended by the World Health Organization and the Peruvian Environmental Quality Standard for air for 24 h, respectively. The results showed a defined pattern for the daily and monthly variations, with peaks in the morning hours (0900–1000 h LT) and at the end of the year (December), respectively. The main sources of SO2 emissions identified were light and heavy vehicles that travel through the Central Highway, the La Oroya Metallurgical Complex, the transit of vehicles within the city, and the diesel–electric locomotives that provide cargo transportation services and tourism passenger transportation. The article attempts to contribute to the development of adequate air quality management policies.

Impact of ship emissions at a high receptor point in the port of Naples

The influence of in-port ship emissions of gases and particulate matter concentrations was studied in the port of Naples, the third port of Italy. The CO, NO, NO2, NOX, O3, SO2, PM10, and PM2.5 concentrations were continuously measured in May–June 2021 at a height of about 20 m from ground level to better monitor the plumes released by ship funnels. AIS data were used to obtain detailed calendars of ship activities. The impact of ship emissions in hotelling conditions was studied by splitting the port area into radial sectors, with the receptor point at the centre, grouping all docks belonging to the same sector and generating patterns of the conditional bivariate probability function. The results show the important contribution of passenger ships to NOX and SO2 concentrations at the receptor point and downwind urban area and their limited impact on PM10 and PM2.5. For PM10 and PM2.5, the results show a significant contribution of other sources external to the port and a possible contribution of commercial ships.

Characteristics of volatile organic compounds in the metropolitan city of Seoul, South Korea: Diurnal variation, source identification, secondary formation of organic aerosol, and health risk

Atmospheric volatile organic compounds (VOCs) in Seoul, the capital of South Korea, have attracted increased attention owing to their emission, secondary formation, and human health risk. In this study, we collected 24 hourly samples once a month at an urban site in Seoul for a year (a total of 288 samples) using a sequential tube sampler. Analysis results revealed that toluene (9.08 ± 8.99 μg/m3) exhibited the highest annual mean concentration, followed by ethyl acetate (5.55 ± 9.09 μg/m3), m,p-xylenes (2.79 ± 4.57 μg/m3), benzene (2.37 ± 1.55 μg/m3), ethylbenzene (1.81 ± 2.27 μg/m3), and o-xylene (0.91 ± 1.47 μg/m3), indicating that these compounds accounted for 77.8–85.6% of the seasonal mean concentrations of the total (Σ59) VOCs. The concentrations of the Σ59 VOCs were statistically higher in spring and winter than in summer and fall because of meteorological conditions, and the concentrations of individual VOCs were higher during the daytime than nighttime owing to higher human activities during the daytime. The conditional bivariate probability function and concentration weighted trajectory analysis results suggested that domestic effects (e.g., vehicular exhaust and solvents) exhibited a dominant effect on the presence of VOCs in Seoul, as well as long-range atmospheric transport of VOCs. Further, the most important secondary organic aerosol formation potential (SOAFP) compounds included benzene, toluene, ethylbenzene, and m,p,o-xylenes, and the total SOAFP of nine VOCs accounted for 5–29% of the seasonal mean PM2.5 concentrations. The cancer and non-cancer risks of the selected VOCs were below the tolerable (1 × 10−4) and acceptable (Hazard quotient: HQ < 1) levels, respectively. Overall, this study highlighted the feasibility of the sequential sampling of VOCs and hybrid receptor modeling to further understand the source–receptor relationship of VOCs.