No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Chemical composition and source apportionment of PM10 at an urban background site in a high–altitude Latin American megacity (Bogota, Colombia)
Abstract
Bogota registers frequent episodes of poor air quality from high PM10 concentrations. It is one of the main Latin American megacities, located at 2600 m in the tropical Andes, but there is insufficient data on PM10 source contribution. A characterization of the chemical composition and the source apportionment of PM10 at an urban background site in Bogota was carried out in this study. Daily samples were collected from June 2015 to May 2016 (a total of 311 samples). Organic carbon (OC), elemental carbon (EC), water soluble compounds (SO42−, Cl−, NO3−, NH4+), major elements (Al, Fe, Mg, Ca, Na, K, P) and trace metals (V, Cd, Pb, Sr, Ba, among others) were analyzed. The results were interpreted in terms of their variability during the rainy season (RS) and the dry season (DS). The data obtained revealed that the carbonaceous fraction (∼51%) and mineral dust (23%) were the main PM10 components, followed by others (15%), Secondary Inorganic Compounds (SIC) (11%) and sea salt (0.4%). The average concentrations of soil, SIC and OC were higher during RS than DS. However, peak values were observed during the DS due to photochemical activity and forest fires. Although trace metals represented <1% of PM10, high concentrations of toxic elements such as Pb and Sb on RS, and Cu on DS, were obtained. By using a PMF model, six factors were identified (∼96% PM10) including fugitive dust, road dust, metal processing, secondary PM, vehicles exhaust and industrial emissions. Traffic (exhaust emissions + road dust) was the major PM10 source, accounting for ∼50% of the PM10. The results provided novel data about PM10 chemical composition, its sources and its seasonal variability during the year, which can help the local government to define control strategies for the main emission sources during the most critical periods.
... F2 explains 25% of the variance. Studies conducted using RMs have associated these chemical species with the source BB. [31,59,78,79] For the PC3 was found a mixed contribution of SD/SA, explaining 12% of the variance of the sample, linking iron and aluminum with ammonium. SD/SA was also identified as a source in the PMF analysis (F3) linking chloride, nitrate and ammonium with magnesium and calcium. ...
... Different studies have concluded that the presence of these species have common origin. [68,78,79] For the MRVA: magnesium, calcium, potassium, aluminum, and iron were found to coming from re-suspended powder and quarries. [38] Zn and Clcompose the PC5 (6.5% of the total variance), identified as VE for their characteristics, as Zn is an important marker of VE it's also relevant in the PMF analysis in which Zn is the main component of the source (F5 with the 8% of the total variance). ...
... [22,28,59] Chloride is also associated with that source. [5,78,81] In the local context, presence of Zn has been associated with tire wear. [38] It's important to note that through the PMF all the emission sources proposed for the MRAV were detected, while PCA did not identified a source that could be enterally associated with industrial emissions. ...
The Metropolitan Region of the Aburrá Valley (MRAV) is an urbanized valley located in the central mountain range of the Andes of Colombia, with Medellin as the most important city of the region. Due to geography, economic trends, industrialization, and demography, air pollution has become one of the main problems in terms of health and the environment. The characterization of the ionic and metallic fraction of Particulate Matter (PM10) was carried out following the standard procedures, using Ionic chromatography for the anions (F-, Cl-, NO2-, NO3-, PO4-3 and SO4-2) and for cations (K + , Na + , Li + , Mg +2 , Ca +2 and NH4 +), as well as atomic absorption spectroscopy for the metals (Ni, Ba, Mn, Cu, Al, Cr, Zn, Fe). A total of 94 samples were collected in 10 different stations of the air quality network of the MRAV between December 2018 and October 2021. The results were statistically analyzed using receptor models: Principal Component Analysis (PCA) and the EPA Positive Matrix Factorization (PMF) to identify the main source of the pollutant. It was found that the average PM10 concentration of the collected samples was 40.65 µg/m 3 , 43% of the data was over the standard established by the WHO (45µg/m 3). The contribution of ions was approximately 26% of the PM10 mass, with SO4-2 occupying the largest fraction (approximately 12%), and Na + , having the highest concentration among the cations. The metals corresponded to 3% of the total mass of PM10, with Fe having the highest concentration. Through the statistical analysis, it was found that the results of both models have important similarities, identifying that the main emission sources of the pollutant in the MRAV are secondary aerosols (SA), biomass/waste burning (BB), soil/road dust (SD), vehicular emissions (VE), industrial emissions (IE), and mixed type contributions. The methods and results used in this case study for the particular geography of the valley are an important tool for understanding the effects of PM pollution in the local context and many regions worldwide.
... In the last years, the air quality monitoring network implemented in Colombia, managed by the Subsistema de Información Sobre Calidad del Aire -SISAIRE, and validated by the Instituto de Hidrología, Meteorología y Estudios Ambientales -IDEAM (IDEAM, 2018) has provided data to study the behavior, mechanisms, and air quality events where monitoring stations are available (e.g., Mogollón-Sotelo et al., 2021;Celis et al., 2022). However, the majority of the studies have focused on only one or two of the main cities (e.g., Ramírez et al., 2018;Franco et al., 2019;Gómez et al., 2020) due to a lack of validated data in some areas of the country (e.g., Amazonas, Llanos Orientales). This is why it is essential to complement the surface measurements with alternative sources of information such as the Copernicus Atmosphere Monitoring Service (CAMS) Reanalysis (Inness et al., 2019), which will allow a more robust spatial coverage. ...
... Some studies around NWSA have been carried out to accomplish this aim (e.g., Franco et al., 2019;Gómez et al., 2020). Ramírez et al. (2018) show that the traffic emissions were found as one of the greatest sources of PM 10 in Bogotá, being responsible for nearly 50 % of the pollutant concentration, followed by industrial emissions. Mateus-Fontecha et al. (2022), revealed how biomass burning is a persistent source of PM 2.5 in the Cauca River Valley region, because of the sugarcane and derivatives production, which is one of their main economic activities. ...
... A. Casallas et al. Science of the Total Environment 852 (2022) 158504 Aburrá, something very important, since the majority of the research (e.g., Ramírez et al., 2018;La Colla et al., 2021;Celis et al., 2022) and plans have been focusing on the capital city. This is evidence of the need for further research on the whole region, rather than only on the largest urban and industrial areas, as also shown in the previous section. ...
This paper analyzes the spatio-temporal variations, and exceedances of the PM2.5 concentrations in Northwestern South America at different scales to assess the implemented policies and identify the involved phenomena. Through reanalysis and ground-based data, we found that high PM2.5 levels in most cities of the region are caused by wildfires and local emissions, including the capital cities of Venezuela, Ecuador, Colombia, and Panamá. In-situ measurements suggest that the majority of the cities comply with the local but not with the WHO guidelines, indicating that local annual limits should be more restrictive. Two peaks in the daily variations of PM2.5 (related to vehicle emissions) and also a steeper decrease around noon (associated with an increase in wind speed and in the boundary layer height) were identified. The trend-analysis shows that Bogotá and Medellín have a decreasing PM2.5 annual-trend (between −0.8μgm⁻³ and −1.7μgm⁻³) that corresponds to effective policies. In contrast, Cali has a positive annual-trend (0.8μgm⁻³) most likely because of Short-Range Transport produced by a northerly-flow from a highly polluted neighboring city, which also affects Cali's PM2.5 diurnal cycle, or by local-dynamics. The exceedances show that the policies are working on an annual but not at a daily time-scale. These results serve as a first input for additional studies, with the aim of gaining a better understanding of the contaminant before adapting current policies or implementing new policies and measures that need to include a joint international, regional, and inter-city efforts regarding pollution transport.
... Besides, PM composition is oftentimes too complex and its elements impact the human ecosystem in a diverse way, with heavy metals (HMs) being one of the greatest concerns (Dockery, 2009;Nguyen et al., 2021a). Sources of HMs in PM comprise both anthropogenic and natural origins, examples of which include As, Pb, Cr as known carcinogenic HMs derived from industrial and anthropogenic sources and Fe, Mn and Si as typical elements found in the Earth's crust (Mulware, 2013;Ramírez et al., 2018). Despite its low abundance relative to the PM total mass, HMs pollution has attracted more attention due to their public health risks (Kumar et al., 2021). ...
... Several studies have been conducted worldwide concerning several HMs at a wide range of particle sizes (Sahu and Basti, 2021). For instance, PM10 studies have been conducted widely in North America, South America, and Europe (Zajusz-Zubek et al., 2015;Di Vaio et al., 2018;Ramírez et al., 2018;Alves et al., 2021;Li et al., 2021;Oroumiyeh et al., 2022). In these studies, spatiotemporal profiles of PM 10 -HMs (i.e., heavy metals in PM 10 ) in combination with either source apportionment or health risk assessment were described as primary methodologies. ...
... Such a pattern could be either a result of planetary boundary height (PBL) modulation or increased emission rates at nighttime (Maletto et al., 2003;Chandra et al., 2017). The reduction of PBL height during soil and dust re-suspension process could elevate mineral elements (Al, Sr) concentration (Ramírez et al., 2018;Rai et al., 2021) which was also observed in studies surrounding Tibetan Plateau where fugitive dust might influence crustal elements concentration and PM10 pattern (Tripathee et al., 2014;Guo et al., 2017). Besides, statistically insignificant daytime-nighttime differences between V (p = 0.056) and Sr (p = 0.58) concentration showed their lack of a diurnal cycle (Fig. 2(c)). ...
Airborne particulate matter (PM) pollution is a global concern, in which partitioned heavy metals (HMs) could impose great risks to residents living in metropolitan areas. In this study, PM10 samples were collected in Ho Chi Minh City (HCMC) – a megacity in southern Vietnam – and analyzed for 11 HMs to investigate their concentration profiles, perform source apportionment and estimate their risk factors. Results showed that atmospheric HMs concentration decreased following the order of Al > Fe > Sr > Mn> Pb > Cu > Cr > V > Ni > Sb > As. Traffic activities were likely the major cause of rush-hour peaks for most HMs in which Cr, As, and Cu showed > 20% increases in their relative proportions. For seasonal variation, most HMs showed a dry > rainy pattern as a result of washout by higher rainfall in the rainy season while crustal elements (Al, Sr, Mn) showed a rainy > dry pattern and might be explained by the difference in air mass transport modulating by monsoon activities. The positive-matrix factorization (PMF) model revealed 5 primary sources for HMs, including traffic emission, shipping activity and combustion activity, fugitive dust re-suspension and waste incineration. Combustion activity might enrich As, Sb, Pb levels at HCMC, and As contributed half (50.8%) to the potential ecological risk (PER) in the city. Besides, the current Cr level could impose a carcinogenic effect towards children in HCMC (total carcinogenic index > 10-4) while Mn might impose intolerable non-carcinogenic risk (hazard index > 1). This study provides information on local air quality status for scientific and regulatory perspectives as well as helps fill the information gap and update the understanding of air pollution in South and Southeast Asia.
... In the case of ions these values were 5 ng m − 3 and 15 %. Ion chromatography is routinely used worldwide for atmospheric aerosol samples analysis in recent source apportionment studies [17][18][19]. ...
... -Estimate of premature mortality -Annual number of hospitalizations at the emergency department for cardiac patients per 100 000 exposed individuals of all ages -Annual rate of emergency respiratory hospitalizations per 100 000 exposed individuals of all ages -Number of days per year using bronchodilators per 1000 children aged 5 to 14 -Number of days per year using bronchodilators per 1000 adults aged 20 to 64 -Attributable risk of days with respiratory symptoms (LRS) per 1 child aged 5-14 -Postneonatal (age 1-12 months) infant mortality, all causes -Prevalence of bronchitis in children aged 6-12 (or 6-18) years -Occurrence of chronic bronchitis in adults (age 18+) -Incidence of asthmatic symptoms in asthmatic children (5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19) years) ...
While car exhaust emissions in the EU are clearly decreasing, the future of non-exhaust emissions looks more pessimistic. The relative importance of the latter is thus expected to increase in terms of air quality and human health. The aim of the study was to assess regional and seasonal differences in the chemical composition of road dust across the Czech Republic and the health impact of its resuspension, with special respect to polycyclic aromatic hydrocarbons and metals. The road dust samples across all regions and seasons were collected. Based on subsequent laboratory and statistical processing, the spatiotemporal distribution of elements and PAHs was evaluated. Next, the contribution of road dust resuspension to air concentrations was estimated and related health impacts were assessed. A significant regional and seasonal variations in PAHs and metals were discovered. Air quality, leading to atmospheric deposition, was the most important factor contributing to these variations. In contrast, road traffic intensity played only a minor role in influencing the concentrations of metals and PAHs in road dust. Exposure to the PM10 fraction of road dust led to an increase in premature mortality, postneonatal infant mortality, and the prevalence, occurrence, and incidence of bronchitis by several percent. It also significantly raises the annual rate of emergency respiratory hospitalizations and the number of days per year using bronchodilators. Exposure to PAHs and heavy metals in road dust causes cancer incidence on the order of a few cases per 10 million people. Air quality protection measures that lead to a decrease in atmospheric deposition rates are required for the effective reduction of health risks associated with particle resuspension by traffic.
... Table 2 specifies that at the urban site the highest PM 10 average concentrations are registered during the wet season days without rain events, as also most of the elements. This result agrees with other studies 58 . This increase in the concentrations of PM 10 and elements during the wet season may be due to an increase in relative humidity (see Table 4), which causes worsened combustion efficiency 37 ; urban dynamics, such as an increase in the acceleration and braking rates, which can raise the pollutant emission rate 25,58 ; and a higher intensity of anthropogenic activity during school period (September-June). ...
... This result agrees with other studies 58 . This increase in the concentrations of PM 10 and elements during the wet season may be due to an increase in relative humidity (see Table 4), which causes worsened combustion efficiency 37 ; urban dynamics, such as an increase in the acceleration and braking rates, which can raise the pollutant emission rate 25,58 ; and a higher intensity of anthropogenic activity during school period (September-June). The latter causes an increase in the use of highly contaminating diesel-powered school buses 39 . ...
... The most polluted substances include particulate matter (PM 2.5 and PM 10 ) and gaseous species (sulfur dioxide; SO 2 , nitrogen dioxides; NO 2 , carbon monoxide; CO, hydrocarbon, etc.). Among air pollutants, air particulate matter (APM), PM 2.5 (fine particles with a diameter <2.5 µm), and PM 10 (coarse particles with a diameter between 2.5 and 10 µm) draw considerable attention because of their high contribution to air pollution and the detrimental health effects such as respiratory and cardiovascular disease [5,6], visibility effects [4,7] and climate change [1,2]. The levels of PM 2.5 and PM 10 are monitored by Thailand's Pollution Control Department (PCD). ...
... Factor 2 explained 29.6% of the total variance and was dominated by S, K, Ca, Ti and Zn. Elements such as K, Ca, Ti and Zn could be attributed to crustal dust [6]. The presence of S and K indicated the contribution of biomass burning [44]. ...
This study reports the mass concentrations, elemental characterization and identification of the possible sources of PM2.5 and PM10 at a suburban site in Pathum Thani, Thailand. The sampling was done from 18 February 2021 to 14 September 2021. PM2.5 concentrations were between 0.39 μg/m3 and 174.26 μg/m3, while PM10 concentration ranged from 12.75 μg/m3 to 242.02 μg/m3. The average concentration of PM2.5 in the wet season (61.96 μg/m3) in the study area exceeded the national ambient air quality standards (NAAQS). Particle-induced X-ray emission (PIXE) was used to measure the element concentrations. The main elements, namely Fe, K, Cr and Ca, in both PM2.5 and PM10 showed significantly higher concentrations in the summer season. A qualitative inter-elemental correlation analysis, principal component analysis (PCA) and cluster analysis (CA) were applied for source identification of PM2.5 and PM10. The results for the three procedures were in good agreement. Four and three factors of sources were isolated by the PCA for PM2.5 and PM10, respectively. The main sources identified by PCA were, for PM2.5, soil dust and biomass burning (32%), road dust and industrial emission (25%), vehicle and industrial emission (10%) and soil dust (9%); for PM10, road dust and industrial emission (36%), crustal and biomass burning (30%) and industrial sources (10%).
... Observational campaigns in Bogotá, Colombia show a persistent OA fraction over the city (e.g. Vargas et al., 2012;Ramírez et al., 2018;Rincón-Riveros et al., 2020). Vargas et al. (2012) suggested that OA was mainly of secondary origin based on EC to OC ratios. ...
... Recently, Rincón-Riveros et al. (2020) showed a strong association between OC and the BB tracer levoglucosan, during the dry season, and a strong correlation of Brown Carbon with the number of fires in the region. Ramírez et al. (2018) characterized PM 10 chemical composition during 1 year at an urban background site in Bogotá. The authors found that carbonaceous material constitutes 51% of PM 10 at the site, with a large OA fraction persistent throughout the year, i.e., not only during the high BB period of January to April. ...
Organic aerosol (OA) is one of the major components of fine atmospheric aerosol particles. Recent field campaigns and modeling studies in Colombia have demonstrated the presence of a large OA fraction in urban and rural aerosols. In this work we focus on constraining the sources associated with OA and its precursors over the city of Bogotá, Colombia. We used PM2.5 chemical speciation data from field campaigns carried out during 2018 to evaluate the ability of a regional transport model to reproduce and explain the observed OA. The samples were collected at three sites during high- and low-aerosol concentration seasons in the region. We used The Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) with two different chemical mechanisms and aerosol schemes, RACM/MADE-VBS and MOZART/MOSAIC, in conjunction with the detailed in-situ aerosol chemical speciation observations to analyze the seasonality of OA in the city of Bogotá, and to establish the most relevant sources. Simulations were carried out for the same periods for which data is available, spanning a high biomass burning (BB) season (February 2018) and a low biomass burning season (September 2018). We demonstrated that long-range transport of BB emissions from Northern Amazonia can episodically increase aerosol loading during September, while BB activity in the Grasslands of the Orinoco River Basin are the main source during February. The two aerosol schemes utilized in this work reproduce the observed seasonal variations in total fine aerosol concentration, with a difference between February and September of 10 μg m⁻³. The comparison between aerosol schemes demonstrated that MOZART/MOSAIC consistently predicted more OA with a larger SOA:OA ratio than in the RACM/MADE-VBS experiment. SOA dominates the OA fraction by 66% for RACM/MADE-VBS and 74% for MOZART/MOSAIC during February and 69% for RACM/MADE-VBS and 71% for MOZART/MOSAIC during September. These differences between organic aerosol burden between the mechanisms used in this study may be attributed to the different treatment of SOA gas/particle partitioning in the schemes.
... In São Paulo, 330 PM 2.5 levels are larger in July (18 µgm −3 ) than January (15 µgm −3 ), due to the impact of wildfires from the Amazon basis and sugarcane burning (de Fatima Andrade et al., 2017). In Bogotá, PM 2.5 concentrations are the lowest in July (13 µgm −3 ) due to the influence of the trade winds but with larger values in January (18 µgm −3 ) due to biomass burning events and frequent thermal inversions (Ramírez et al., 2018). ...
A multi-scale modeling ensemble chain has been assembled as a first step towards an Air Quality forecasting system for Latin America. Two global and three regional models were tested and compared over a shared domain (120W–28W, 60S–30N) to simulate January and July of 2015. Observations from local air quality monitoring networks in Colombia, Chile, Brazil, México, Ecuador and Peru were used for model evaluation. The models generally agreed with observations in large cities such as México City and São Paulo, whereas representing smaller urban areas, such as Bogotá and Santiago, was more challenging. For instance, in Santiago, during wintertime, the simulations showed large discrepancies with observations. No single model had the best performance among pollutants and sites available. Ozone and NO2 were reproduced better than other pollutants across sites whereas SO2 was the most difficult. The ensemble, created from the median value of the individual models, was evaluated as well. In some cases, the ensemble showed better results over the individual models and mitigated the extreme over- or underestimation of certain models, demonstrating the potential to establish an analysis and forecast system for Latin America. This study identified certain limitations in the models and global emissions inventories, which should be addressed with the involvement and experience of local researchers.
... Similar trends are observed when comparing EC and PM (Fig. S3 in the Supplement), with contributions of roughly 5 and 6% to total PM10 and PM2.5, respectively. Comparing the fraction of PM that corresponds to eBC and EC in other high-altitude cities we observe that according to Ramírez et al., 2018b in Bogotá is almost 1.3 times higher (8.2%-9%) than in La Paz-El Alto. In contrast, in Mexico City, eBC contributions to PM2.5 reported by Peralta et al. (2019), were almost 5 times higher than the ones observed in LP-EA (16%, calculated from average concentrations of eBC and PM2.5). ...
Black carbon (BC) is a major component of sub-micron particulate matter (PM) with significant health and climate impacts. Many cities in emerging countries lack comprehensive knowledge about BC emissions and exposure levels. This study investigates BC concentration levels, identify its emission sources, and characterize the optical properties of BC at urban background sites of the two largest high-altitude Bolivian cities: La Paz (LP) (3600 m above sea level) and El Alto (EA) (4050 m a.s.l.) where atmospheric oxygen levels and intense radiation may affect BC production. The study relies on concurrent measurements of equivalent black carbon (eBC), elemental carbon (EC), and refractory black carbon (rBC), and their comparison with analogous data collected at the nearby Global Atmosphere Watch-Chacaltaya station (5240 m a.s.l). The performance of two independent source-apportionment techniques was compared: a bilinear model and a least squares multilinear regression (MLR). Maximum eBC concentrations were observed during the local dry season (LP: eBC=1.5±1.6 μg m-3; EA: 1.9±2.0 μg m-3). While eBC concentrations are lower at the mountain station, daily transport from urban areas is evident. Average mass absorption cross sections of 6.6-8.2 m2 g-1 were found in the urban area at 637 nm. Both source apportionment methods exhibited a reasonable level of agreement in the contribution of biomass burning (BB) to absorption. The MLR method allowed the estimation of the contribution and the source-specific optical properties for multiple sources including open waste burning.
... El tamaño de las partículas en la atmósfera puede variar en cuatro órdenes de magnitud, desde10-3 μm hasta algunas decenas de micrones. A las partículas cuyo diámetro aerodinámico es inferior a 10 μm se la denomina PM 10 y a las de diámetro aerodinámico inferior a 2.5 μm, PM 2.5 ., (Semarnat, 2013(Semarnat, , 2015Ramírez, 2018). ...
In this work the inventory of atmospheric emissions of the 306 fixed sources is shown distributed in the seven coastal municipalities of the county of Villa Clara in the year 2018. The general objective was to quantify the emissions from the PM10 to the atmosphere taken place by these fixed sources. The calculation method was used based on the emission factor to determine the rate of the pollutant for sources. The main results were, to modernize the inventory of emissions of the fixed sources in this area of the provincial territory, removed by municipalities, Oaces and according to the classification of these sources keeping in mind the impact about the quality of the air. It was possible to determine that 80% of the fixed sources is well located and they emit 2% of the total of this pollutant, 17% is partially well located and they emit 96% and lastly 3% is not well located and they emit 2% of the load. The total emission of the PM10 was of 2 191,5 t/year, representing 75% of the provincial total, of it the well located fixed sources emitted 42,7 t/year, those partially well located 2 105,8 t/year and the not well located 43 t/year. These results provide the necessary and indispensable information for the proposals of actions that they contribute to reduce emissions, to minimize critical episodes of atmospheric contamination and to carry out the modelation of the dispersion of the pollutant and its evaluation.
... With the progress of urbanization, the particulate air pollution in high-altitude areas is gradually worsening [11][12][13]. Moreover, cooking, incense burning, and other activities in high-altitude areas significantly impact indoor air quality [14][15][16]. ...
... The high performance of the LUR models for PM 2.5 in Medellín compared to other cities might be explained by the wide range of estimated concentrations in the city and the influence of the topography and meteorology in the Valley of Aburrá where Medellín is located, as well as the important contribution of vehicular emissions to local concentrations as have been described in studies of PM 2.5 characterization in the city (Area Metropolitana del Valle de Aburrá and Politecnico Colombiano Jaime Isaza Cadavid 2021). In contrast, the low performance of the LUR models for PM 2.5 in Bogotá compared to other cities might be explained partially by the lower contribution of vehicular emissions and the increased contribution of enriched fugitive dust (resuspension of crustal material and soil dust) and secondary PM (Ramírez et al. 2018). A similar profile has also been documented for Barranquilla with an important contribution of ocean aerosols (Nuñez Blanco 2019), secondary organic aerosols and the effect of exposed land resuspension and road dust (Gómez-Plata et al. 2022), which was represented in the developed LUR model for this city. ...
Rapidly urbanizing cities in Latin America experience high levels of air pollution which are known risk factors for population health. However, the estimates of long-term exposure to air pollution are scarce in the region. We developed intraurban land use regression (LUR) models to map long-term exposure to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) in the five largest cities in Colombia. We conducted air pollution measurement campaigns using gravimetric PM2.5 and passive NO2 sensors for 2 weeks during both the dry and rainy seasons in 2021 in the cities of Barranquilla, Bucaramanga, Bogotá, Cali, and Medellín, and combined these data with geospatial and meteorological variables. Annual models were developed using multivariable spatial regression models. The city annual PM2.5 mean concentrations measured ranged between 12.32 and 15.99 µg/m³ while NO2 concentrations ranged between 24.92 and 49.15 µg/m³. The PM2.5 annual models explained 82% of the variance (R²) in Medellín, 77% in Bucaramanga, 73% in Barranquilla, 70% in Cali, and 44% in Bogotá. The NO2 models explained 65% of the variance in Bucaramanga, 57% in Medellín, 44% in Cali, 40% in Bogotá, and 30% in Barranquilla. Most of the predictor variables included in the models were a combination of specific land use characteristics and roadway variables. Cross-validation suggests that PM2.5 outperformed NO2 models. The developed models can be used as exposure estimate in epidemiological studies, as input in hybrid models to improve personal exposure assessment, and for policy evaluation.
... Por otra parte, se han hecho estudios que relacionan la emisión contaminante con PM10 y la salud como es el caso de Morales y Arias [3], donde se evidenciaron dos comportamientos relevantes: El primero de ellos es la relación entre morbilidad y emisión, y el segundo la relación entre morbilidad y concentración. También, Ramírez y otros [4], realizaron un estudio en Bogotá (Colombia) sobre el PM10 sugieren que "teniendo en cuenta que la fracción carbonosa de PM se ha relacionado principalmente con PM2.5, así como con los niveles de trazas de metales, se deben realizar más investigaciones sobre la distribución de PM2.5" ...
El problema de dispersión atmosférica de un contaminante es un tema complejo, donde variables como la velocidad del viento, la temperatura, la época del año, entre otros, contribuyen en mayor o menor grado al incremento o decremento de la concentración de las especies químicas. El objetivo de la investigación fue identificar la correlación entre variables climatológicas y la contaminación por los automotores (PM2,5 Y COV) en un punto de acceso a una institución ubicada al oriente de Bucaramanga (Colombia). Con relación a los datos del estudio, se utilizó un medidor manual y se registraron datos de PM2,5, Compuestos Orgánicos Volátiles (COV) y variables climatológicas de temperatura y humedad relativa para 26 días en la zona de interés durante 3 franjas horarias específicas del día, cada 5 minutos; además, se utilizaron los datos relacionados con la dirección y velocidad del viento de la estación Neomundo, según el documento del Instituto de Hidrología, Meteorología y Estudios Ambientales (IDEAM) para los años (2005-2009), por ser una zona similar en cuanto a la topografía. El análisis se realizó usando el software libre R (versión 3.5.3) y su librería OpenAir. Los resultados obtenidos muestran las correlaciones correspondientes del PM2,5, los COV, y las variables ambientales corroborando por una parte la influencia del tráfico vehicular en la concentración de PM2,5 principalmente debido a las motocicletas, y por otra parte la relación del PM2.5 con respecto a la Humedad relativa y la temperatura.
... Many research works presented the metal elements in PM 10 , but only a few studies have offered the concentrations of all carcinogenic metal elements in PM 10 , including As, Cd, Co, Cr, Ni, and Pb. Table 2 shows the mass concentrations of such carcinogenic metal elements in PM 10 and the total ECRs compared with previous studies (Limbeck et al. 2009;Alleman et al. 2010;von Schneidemesser et al. 2010;Contini et al. 2012;Gugamsetty et al. 2012;Alghamdi 2016;Cheng et al. 2018;Elhadi et al. 2018;Ramírez et al. 2018;Mai et al. 2021). The total ECR in this study was the lowest one among these monitored locations. ...
This study aimed to investigate the spatial distribution of metal elements in PM10 and their potential sources and associated health risks over a period of two years in eight locations in the central part of western Taiwan. The study revealed that the mass concentration of PM10 and the total mass concentration of 20 metal elements in PM10 were 39.0 μg m⁻³ and 4.74 μg m⁻³, respectively, with total metal elements accounting for approximately 13.0% of PM10. Of the total metal elements, 95.6% were crustal elements (Al, Ca, Fe, K, Mg, and Na), with trace elements (As, Ba, Cd, Cr, Co, Cu, Ga, Mn, Ni, Pb, Sb, Se, V, and Zn) contributing only 4.4%. Spatially, the inland areas exhibited higher PM10 concentrations due to lee-side topography and low wind speeds. In contrast, the coastal regions exhibited higher total metal concentrations because of the dominance of crustal elements from sea salt and crustal soil. Four primary sources of metal elements in PM10 were identified as sea salt (58%), re-suspended dust (32%), vehicle emissions and waste incineration (8%), and industrial emissions and power plants (2%). The positive matrix factorization (PMF) analysis results indicated that natural sources like sea salt and road dust contributed up to 90% of the total metal elements in PM10, while only 10% was attributed to human activities. The excess cancer risks (ECRs) associated with As, Co, and Cr(VI) were greater than 1 × 10⁻⁶, and the total ECR was 6.42 × 10⁻⁵. Although only 10% of total metal elements in PM10 came from human activities, they contributed to 82% of the total ECR.
Graphical Abstract
... The first is associated with mining activities, especially in open-pit coal or ferronickel mines, some of the largest in the world [102]. The second is related to industrial or semi-industrial facilities with high emissions and poor source controls [103], such as brick kilns, lime kilns, foundries, poultry farms, among others [104]. The third is open biomass burning in agricultural activities (i.e., sugarcane crop burning before harvest) [105], as well as forest fires for agricultural expansion and cattle production in the Amazon rainforest, and peat fires, particularly in the eastern plains shared with Venezuela [106][107][108][109][110][111][112]. ...
... Despite scarce studies concerning PM chemical characterisation in tropical sites have been reported, metal(oid)s levels found is this research were compared to studies conducted in other tropical areas. Results obtained were lower than those recently reported at Quito city (Ecuador) by Zalakeviciute et al. (Zalakeviciute et al. 2020) and similar to those reported in Bogotá city (Colombia) (Ramírez et al. 2018;Vargas et al. 2012). ...
This study investigates spatio-temporal variations of PM10 mass concentrations and associated metal(oid)s, δ¹³C carbon isotope ratios, polycyclic aromatic hydrocarbons (PAHs), total organic carbon (TOC) and equivalent black carbon (eBC) concentrations over a half year period (from March 2017 to October 2017) in two residential areas of Medellín (MED-1 and MED-2) and Itagüí municipality (ITA-1 and ITA-2) at a tropical narrow valley (Aburrá Valley, Colombia), where few data are available. A total of 104 samples were analysed by using validated analytical methodologies, providing valuable data for PM10 chemical characterisation. Metal(oid)s concentrations were measured by inductively coupled plasma mass spectrometry (ICP-MS) after acid digestion, and PAHs concentrations were measured by Gas Chromatography-Mass Spectrometry (GC–MS) after Pressurised Hot Water Extraction (PHWE) and Membrane Assisted Solvent Extraction (MASE). Mean PM10 mass concentration ranged from 37.0 µg m⁻³ to 45.7 µg m⁻³ in ITA-2 and MED-2 sites, respectively. Al, Ca, Mg and Na (from 6249 ng m⁻³ for Mg at MED-1 site to 10,506 ng m⁻³ for Ca at MED-2 site) were the major elements in PM10 samples, whilst As, Be, Bi, Co, Cs, Li, Ni, Sb, Se, Tl and V were found at trace levels (< 5.4 ng m⁻³). Benzo[g,h,i] perylene (BghiP), benzo[b + j]fluoranthene (BbjF) and indene(1,2,3-c,d)pyrene (IcdP) were the most profuse PAHs in PM10 samples, with average concentrations of 0.82–0.86, 0.60–0.78 and 0.47–0.58 ng m⁻³, respectively. Results observed in the four sampling sites showed a similar dispersion pattern of pollutants, with temporal fluctuations which seems to be associated to the meteorology of the valley. A PM source apportionment study were carried out by using the positive matrix factorization (PMF) model, pointing to re-suspended dust, combustion processes, quarry activity and secondary aerosols as PM10 sources in the study area. Among them, combustion was the major PM10 contribution (accounting from 32.1 to 32.9% in ITA-1 and ITA-2, respectively), followed by secondary aerosols (accounting for 13.2% and 23.3% ITA-1 and MED-1, respectively). Finally, a moderate carcinogenic risk was observed for PM10-bound PAHs exposure via inhalation, whereas significant carcinogenic risk was estimated for carcinogenic metal(oid)s exposure in the area during the sampling period.
... In addition, O, H, S, and N are relatively low compared to carbon content. Specifically, the low N and S content in the PM10 sample points towards primary pollutants such as OC as the principal source of organic matter, indicating that secondary pollutants such as sulfate and nitrate are not abundant as primary pollutants in Medellin air as it has been reported in other Colombian cities (Ramírez et al., 2018;Vargas et al., 2012). Additionally, a thermogravimetric analysis was performed to determine the volatile organic fraction (VOF), nonvolatile organic fraction (NVOF), and ash present in the PM10 sample; in this analysis, two important results draw our attention, the OC/EC ratio and the high ash content in the PM10. ...
Particulate matter arising from different sources affects air quality, representing a risk for human health and the environment. The Valle de Aburrá, Colombia, is facing serious air pollution conditions due to its geographical location and the continuous vehicle fleet growth. In this study, the chemical composition and morphology of the PM10 (particulate matter with aerodynamic diameter < 10 μm) collected at monitoring stations across the Valle de Aburrá, were studied by using thermogravimetric analysis (TGA), elemental analysis, scanning electron microscope/energy-dispersive X-ray spectrometer (SEM/EDS), and gas chromatography-mass spectrometry (GC–MS). Additionally, the potential of PM10-induced cytotoxic and oxidative effects was evaluated using peripheral blood mononuclear cells (PBMCs).
The PM10 from Valle de Aburrá has a chain morphology and particles of irregular shape; it is mainly composed of ashes (54.8%), followed by volatiles and fixed carbon. Furthermore, different metals were found in PM10, including Si, Fe, K, Na, Al, Cr, and Pt. On the other hand, the polycyclic aromatic hydrocarbon (PAH) analysis showed benz[a]anthracene levels at 6.71 ng cm−2 which may act as a potent carcinogen by generating various reactive metabolic intermediates leading to oxidative stress. These results are consistent with the cytotoxic effect and the production of ROS observed in PBMCs.
Finally, the results suggest that the PM10 of the Valle de Aburrá is mainly arising from construction waste transport, coal combustion to generate energy, and vehicles, representing a potential health risk for the citizens.
... An increase in PM 10 may be associated with urban dynamics and meteorological variables (Ramírez et al., 2018;Nogarotto and Pozza, 2020). It can include the reduction of the boundary layer height (Singh et al., 2020), variability in humidity conditions (Singh et al., 2020), and the horizontal movement of air masses (Nogarotto et al., 2021). ...
High particulate matter (PM) emissions from vehicular traffic impact air quality in urban areas. In 2018, a truckers’ strike interrupted some of the services in Brazil, leading to a fuel outage in several cities that significantly reduced the flow of vehicles. This study evaluated air quality during the strike in two cities (Limeira and Campinas) in Southeastern Brazil. PM10 concentration was analyzed in the periods before (BTS — 05/01/2018 to 05/22/2018), during (DTS — 05/23/2018 to 05/30/2018), and after (ATS — 05/31/2018 to 06/30/2018) the strike using the Theil-Sen method and the Autoregressive Integrated Moving Average model with Exogenous Variables (ARIMAX). A reduction in the PM daily mean concentration in both cities occurred during the strike. Considering the daily peak time of vehicular flow (6:00 p.m.), the PM10 concentration was 20% higher in the BTS period compared to the DTS period for both cities. In comparison, the ATS period showed concentrations 17% (Limeira) and 7% (Campinas) higher when compared with the DTS period. The variations were statistically significant based on the time series models, and the influences of wind speed, rainfall on the sampling day and the day before sampling, and weekends were also evaluated. It was also possible to verify the contribution of the truckers’ strike to the PM10 concentration in the two cities evaluated. In Limeira, truck traffic had a greater influence on the concentration of PM10, while in Campinas, the contribution of trucks was like that of light vehicles. Based on the variation of the PM10 concentration, the influence of changes in vehicle emission dynamics, one of the main sources of emission in the regions studied, was observed. The results indicate that restricting vehicular traffic had an immediate impact on improving air quality. Therefore, public investment in other types of transport and traffic control policies are suggested.
... shows the variation in the daily concentration of PM10 at the sampling site with changes in the meteorological environment including temperature, wind speed, relative humidity and precipitation. Considerable seasonal changes have been observed in earlier studies also[16,17,18]. Seasonal PM2.5 and PM10 correlation shows significant relationship among them in all the seasons. The gravimetric concentration level of PM2.5 and PM10 changed in a similar way throughout time. ...
While significant efforts have been made to mitigate the negative health impacts of particulate matter, there are limited statistics on particle exposure in Raipur. A study was conducted to look at the short-term relationships between particulate matter (PM 2.5 and PM 10 ) and meteorological variables in Raipur. The current research was based on an experimental study conducted at Chhattisgarh’s NIT Raipur. During the pre-monsoon, monsoon, post-monsoon, and winter seasons of 2021, a total of 125 air specimens were gathered from the campus. A respirable dust sampler and a fine particulate sampler were used to detect PM10 and PM 2.5 on the building’s terrace. To assess the associations between PM 2.5 and PM10 particulates and both sampling season and site, Pearson’s correlation study was used. The monthly mean mass concentrations of PM 2.5 and PM 10 in Raipur ranged from 28.0-334.0 μg/m ³ to 56.0-448.0 μg/m ³ , respectively. Post-monsoon PM concentrations were highest, followed by pre-monsoon, winter, and post-monsoon. On more than 92 percent of days, PM 2.5 concentrations exceeded NAAQS standards, while PM 10 concentrations exceeded restrictions on 90 percent of days. There were seasonal changes identified in the relationships between PM concentrations and meteorological variables.
... The chemical composition and size distribution of PM 10 vary greatly depending on the origin and the formation processes in the atmosphere. Chemical analyses of the components constituting PM 10 indicate a large variety of different substances, including elemental carbon (EC), organic carbon (OC), water soluble compounds, such as sulfate (SO 4 2− ), chloride (Cl − ), nitrate (NO 3 − ), ammonium (NH 4 + ), and also minerals and metals [6][7][8][9]. ...
The old Swedish city Visby, located on the island Gotland, has, for several years, reported higher PM10 concentrations than any other city in Sweden. In Visby, local limestone is used, both in road paving and as sand used for anti-slip measures, resulting in a clear annual pattern of PM10 with the highest concentrations during winter/spring when studded tires are allowed. This study analyzes the short-term associations between PM10 and daily number of patients with acute respiratory problems (ICD-10 diagnoses: J00-J99) seeking care at the hospital or primary healthcare units in Visby during the period of 2013-2019. The daily mean of PM10 was on average 45 µg m-3 during winter/spring and 18 µg m-3 during summer/autumn. Four outcome categories were analyzed using quasi-Poisson regression models, stratifying for period and adjusting for calendar variables and weather. An increase in respiratory visits was associated with increasing concentrations in PM10 during the summer/autumn period, most prominent among children, where asthma visits increased by 5% (95% CI: 2-9%) per 10 µg m-3 increase in PM10. For the winter/spring period, no significant effects were observed, except for the diagnose group 'upper airways' in adults, where respiratory visits increased by 1% (95% CI: 0.1-1.9%) per 10 µg m-3 increase. According to the results, limestone in particles seem to be relatively harmless at the exposure concentrations observed in Visby, and this is in line with the results from a few experimental and occupational studies.
... This sector has an intensive use of fossil fuels for goods production and transportation. The industries are located both within the urban area and at nearby municipalities, generating land-use and environmental conflicts [28]. Frequently, PM exceeds national air quality standards in the southern and western areas of the city, given the emission sources, and local and meteorological conditions [24]. ...
Road dust (RD) is one of the most important sources of particles in the atmosphere,
especially in industrial areas and cities. In this special issue, we collected 16 original articles that describe field, experimental, and modeling studies related to RD and its various size fractions as a key issue in understanding the relationships between several urban and industrial environments and in the identification of pollution sources. Articles in the special issue focus primarily on the following main topics: (1) study of the chemical composition and speciation of RD and its source attribution; (2) assessment of RD and aerosol pollution levels (including express technique), environmental hazards and public health risks; (3) distribution of stable and radioactive isotopes in RD; (4) determination of
factors affecting the level of dust accumulation on roads and the intensity of its pollution; and (5) study of the effect of RD on the atmosphere and other environments. Based on the results presented in this special issue, but not limited to, some of the current challenges in studying RD are formulated, including the need for further geographically wider and analytically deeper work on various aspects of the formation, transport pathways, and accumulation of RD in urban, industrial and other areas.
... Otro factor de riesgo para alteración de los niveles de vitamina D en regiones del trópico es la contaminación ambiental, la cual afecta la cantidad de radiación solar, generando una disminución en el porcentaje de luz UVB captado por la piel (20,21). En Bogotá, se han reportado niveles elevados de partículas con diámetro menor a 10 µm (PM10), indicador de contaminación ambiental con subsecuente efecto en la disminución de exposición a radiación solar (21)(22)(23). ...
Objetivo: Determinar la prevalencia de hipovitaminosis D en gestantes y sus neonatos en un hospital de Bogotá, Colombia.
Métodos: Estudio de corte transversal a través de la medición de 25-hidroxivitamina D (25(OH)D) en sangre materna y sangre de cordón, empleando técnica de quimioluminiscencia. Se obtuvieron muestras periféricas de sangre neonatal si la muestra de cordón era < 30 ng/mL.
Resultados: Se incluyeron 88 muestras maternas, 90 muestras de cordón (dos gestaciones gemelares) y 43 muestras periféricas neonatales. Según los rangos establecidos en el Consenso Global de la European Society for Pediatric Endocrinology (ESPE), la prevalencia de hipovitaminosis D fue de 26%, 34% y 67% en gestantes, cordón umbilical y muestra neonatal periférica, respectivamente. De acuerdo con la Endocrine Society, la prevalencia encontrada fue de 66%, 83% y 100%, respectivamente. Se evidenció correlación positiva entre niveles maternos de 25(OH) D y niveles de sangre de cordón (Spearman's Rho 0.67, p < 0.001). En las madres con valores de suficiencia un 12.3% de los neonatos bajo criterios ESPE y 56.7% bajo Endocrine society presentaron hipovitaminosis.
Conclusiones: Se evidencia alta prevalencia de hipovitaminosis D en neonatos y gestantes en la población a estudio. Los niveles de suficiencia maternos no garantizan niveles neonatales adecuados. La estimación de prevalencia varía significativamente según las guías diagnósticas empleadas.
... Recently, Safai et al. (2014) proposed the concept of ECR to obtain a better association between atmospheric carbonaceous aerosols and climate change. This approach has been widely used in previous studies (Safai et al., 2014;Singh et al., 2016;Pipal and Satsangi, 2015;Ramírez et al., 2018a;Pani et al., 2019). Fig. 7 shows the monthly ECR values, which were calculated using Eq. ...
Carbonaceous material is an important component of atmospheric aerosol particles, which plays a significant role in air quality and climate, and also has potentially negative impacts on human health. There is a lack of data reported in the literature regarding the carbonaceous fraction of aerosol in the North-West European ‘air pollution hotspot’ and this work reports a comprehensive one-year intensive measurement campaign, where organic carbon (OC) and elemental carbon (EC) fractions of PM10 (particulate matter of diameter ≤ 10 μm) were measured. Owing to the importance of carbonaceous aerosols in understanding particulate pollution sources, ~2000 PM10 samples were simultaneously collected across North-West Europe at four urban background sites located in Amsterdam (AD), Antwerp (AP), Leicester (LE) and Lille (LL), and one industrial site at Wijk aan Zee (WZ). PM10 samples were chemically analysed by OC-EC analyser for carbonaceous species (OC, and EC) and trends were identified. OC accounted for 12.8%, 13.9%, 15.3%, 15.1% and 9.8%, and EC accounted for 2.4%, 4.9%, 4.4%, 4.0%, and 2.4% of total PM10 mass for AD, AP, LE, LL and WZ, respectively. Secondary organic carbon (SOC) contributions were higher in warmer months compared to colder months, and SOC concentration levels were similar at all five locations, with SOC contributing more than primary organic aerosol (POC) in each city. The lower effective carbon ratio (ECR) values (≤0.3) at all five sites in October, November, and February can be attributed to higher combined POC and EC concentrations and lesser contributions from SOC, meaning that SOC with a greater relative formation has a greater tendency to disperse solar radiation. Higher ECR values in April, May, and July, on the other hand, indicate that more absorbing types of carbonaceous aerosols are also present. More than 90% of the air-mass trajectories were from the north and northeast. This paper details atmospheric processes and sources influencing the seasonal variability of the carbonaceous components of PM10.
... Zn could be released to the environment by iron/steel industry emissions (Bourliva et al., 2018). The significant amount of Zn and Cu appearing in this factor were associated with industrial sources at high temperatures, such as metallurgical activities, especially galvanization industry for Zn (Begum et al., 2011;Ramírez et al., 2018). Cu is one of the most widely used metallic materials (Jin et al., 2019b). ...
A total of 32 atmospheric depositions (ADs) samples were collected from eight sampling sites from April 2018 to March 2019 in the Tehran megacity. Elemental concentration, pollution characteristics, ecological and human health risks, and source apportionment of ADs in the < 63 μm fraction were investigated. Descriptive statistical analysis revealed that the average concentration of Zn, Cd, Pb, and Cu had the highest values over the upper continental crust (UCC). The influence of anthropogenic activities on the level of elements pollution was determined using the Geo-accumulation index (Igeo), Enrichment factor (EF), and Pollution index (PI). The findings revealed the highest Igeo values for Cd at the “extremely contaminated” level due to great influence from Cd emission sources, especially in spring. The extremely high EF values for Zn in 18.8% of samples could be attributed to the low distance of these sampling sites from the nearby industrial areas and adjacent road traffic density. PI values in the range of “considerable to extremely high” pollution were in the order of Zn > Cd > Pb > Cu > Ni > Cr. Eventually, The pollution load index (PLI) indicated the higher than unity of PLI values for all sampling sites reflecting considerable polluted sites across the study area. The ecological risk index (RI) indicated a considerable ecological risk, with the highest monomial risk values for Cd and Pb. The cumulative hazard index (HI) results showed that children encounter higher non-carcinogenic (NCR) risks than adults. However, the cumulative carcinogenic risk (CCR) of adults was 2.25 times higher than for children. The positive matrix factorization (PMF) model extracted four factors, including traffic-related sources (29.7%), local soils and crustal dust resuspension sources (24.8%), demolition and construction activities (23.5%), and industry-related emissions (22%). Among the identified sources, traffic-related sources showed the largest contribution to elements and ecological risks.
... Por otra parte, se han hecho estudios que relacionan la emisión contaminante con PM10 y la salud como es el caso de Morales y Arias [3], donde se evidenciaron dos comportamientos relevantes: El primero de ellos es la relación entre morbilidad y emisión, y el segundo la relación entre morbilidad y concentración. También, Ramírez y otros [4], realizaron un estudio en Bogotá (Colombia) sobre el PM10 sugieren que "teniendo en cuenta que la fracción carbonosa de PM se ha relacionado principalmente con PM2.5, así como con los niveles de trazas de metales, se deben realizar más investigaciones sobre la distribución de PM2.5" ...
El problema de dispersión atmosférica de un contaminante es un tema complejo, donde variables como la velocidad del viento, la temperatura, la época del año, entre otros, contribuyen en mayor o menor grado al incremento o decremento de la concentración de las especies químicas. El objetivo de la investigación fue identificar la correlación entre variables climatológicas y la contaminación por los automotores (PM2,5 Y COV) en un punto de acceso a una institución ubicada al oriente de Bucaramanga (Colombia). Con relación a los datos del estudio, se utilizó un medidor manual y se registraron datos de PM2,5, Compuestos Orgánicos Volátiles (COV) y variables climatológicas de temperatura y humedad relativa para 26 días en la zona de interés durante 3 franjas horarias específicas del día, cada 5 minutos; además, se utilizaron los datos relacionados con la dirección y velocidad del viento de la estación Neomundo, según el documento del Instituto de Hidrología, Meteorología y Estudios Ambientales (IDEAM) para los años (2005-2009), por ser una zona similar en cuanto a la topografía. El análisis se realizó usando el software libre R (versión 3.5.3) y su librería OpenAir. Los resultados obtenidos muestran las correlaciones correspondientes del PM2,5, los COV, y las variables ambientales corroborando por una parte la influencia del tráfico vehicular en la concentración de PM2,5 principalmente debido a las motocicletas, y por otra parte la relación del PM2.5 con respecto a la Humedad relativa y la temperatura.
... In relation to the PM2.5 concentrations, the following spatial distribution was detected: north (1,1,10), center (1,1,4), and south-west (1,1,9). This spatial distribution was possibly related to wind direction and speed, and land use [12]. The results showed the following spatial distribution for O3: northwest (1,1,4), center (1,1,9), and south (1,1,5). ...
The objective of this paper is to show the development of Box-Jenkins stochastic models to study the behavior of air pollutants concentrations in the megacity of Bogotá, Colombia. Information was collected from 10 stations in the city’s air quality monitoring network over a ten-year period. The temporal relationship between air pollutants, their spatial variation, and the occurrence of extreme pollution episodes was studied using Box-Jenkins models. The results showed that the moving average term of the models developed was the main indicator of spatial distribution for the daily pollutant concentrations. In the case of atmospheric particulate matter < 10 μm, the following spatial distribution was identified in the megacity: northwestern, center-southwest, and southeast. For atmospheric particulate matter < 2.5 μm: north, center, and southwest. For ozone: northwest, center, and south. Maximum hourly particulate matter concentrations were observed between 6-10 a.m., and between 11 a.m. - 4 p.m. for ozone. Monthly, the highest particulate matter concentrations were observed in February (14.1%), January (13.5%), and March (12.2%). In the context of atmospheric physics, this study was relevant for the following findings: The usefulness of Box-Jenkins models in simulating the temporal behavior of air pollutants, and for their adequate performance in detecting urban spatial trends.
... PM10 is the most significant air pollutant in Bogotá [9]. Annual average PM10 levels for Bogotá range from 9.89 μg/m3 to 160 μg/m3 with peaks in the months of March and April. ...
Air pollution levels in the cities of Bogotá and Medellín (Colombia) are now reaching dangerous levels as measured by the few government monitoring stations available and operative. So far, government actions have focused on enforcing private car and industrial emission limits, prohibiting the circulation of vehicles for a few days during particularly polluted periods and vague promises of switching a percentage of public transport vehicles to alternative power. Official measurements are increasingly being reported in the national and local media, as well as through social media, but citizen distrust of their quality has mounted. Citizen collectives are starting to work designing low-cost mobile sensors, monitoring pollution in some areas and in public transport, sharing their georeferenced data over the internet and trying to raise awareness of the dangers of pollution and the necessity of radical actions to deal with the problem. This paper describes the current actions of some of these citizen collectives and their results in setting the media and public agenda on air pollution problems.
Black carbon (BC) is a major component of submicron particulate matter (PM), with significant health and climate impacts. Many cities in emerging countries lack comprehensive knowledge about BC emissions and exposure levels. This study investigates BC concentration levels, identifies its emission sources, and characterizes the optical properties of BC at urban background sites of the two largest high-altitude Bolivian cities: La Paz (LP) (3600 m above sea level) and El Alto (EA) (4050 m a.s.l.), where atmospheric oxygen levels and intense radiation may affect BC production. The study relies on concurrent measurements of equivalent black carbon (eBC), elemental carbon (EC), and refractory black carbon (rBC) and their comparison with analogous data collected at the nearby Chacaltaya Global Atmosphere Watch Station (5240 m a.s.l). The performance of two independent source apportionment techniques was compared: a bilinear model and a least-squares multilinear regression (MLR). Maximum eBC concentrations were observed during the local dry season (LP: eBC = 1.5 ± 1.6 µg m⁻³; EA: 1.9±2.0µg m⁻³). While eBC concentrations are lower at the mountain station, daily transport from urban areas is evident. Average mass absorption cross sections of 6.6–8.2 m² g⁻¹ were found in the urban area at 637 nm. Both source apportionment methods exhibited a reasonable level of agreement in the contribution of biomass burning (BB) to absorption. The MLR method allowed the estimation of the contribution and the source-specific optical properties for multiple sources, including open waste burning.
In recent years, air quality research in Colombia has gained momentum due to its critical impact on urban populations and vulnerable communities amidst escalating environmental and public health challenges. Despite growing awareness, a significant research gap persists in understanding the integrated dynamics of air pollution, particularly concerning particulate matter, urban development, and public health. This paper presents a comprehensive bibliometric analysis mapping the landscape of air quality research in Colombia over the past two decades. Employing advanced methods including keyword frequency analysis, Latent Dirichlet Allocation for topic modeling, and dynamic topic modeling, the study identifies dominant research themes, temporal trends, and emerging opportunities for intervention. Findings reveal an overwhelming focus on health impacts, while highlighting underexplored areas such as air quality modeling, urban transport emissions, and open data practices. The analysis underscores a critical need for participatory approaches and cross-domain data integration to enhance the effectiveness of air quality interventions. The study also emphasizes that implementing open science principles, particularly FAIR (Findable, Accessible, Interoperable, and Reusable) data practices, could catalyze innovation and foster collaborative, context-specific solutions for air quality management. By providing a strategic overview of the field's evolution and current state, this research aims to guide future studies and inform policy decisions, promoting a more holistic and sustainable approach to addressing urban air quality challenges in Colombia. The insights presented offer a roadmap for researchers, policymakers, and stakeholders to prioritize efforts and resources in tackling this pressing environmental issue.
Four hundred and sixty-six references with 625 data reports were included in our study. The high frequency of ratio OC/EC for PM0.1 was observed in 3.92-5.93; PM1 in 1.08-3.08; PM2.5, 2.08-4.08; PM10 in 2.70-4.70 and TSP in 2.66-4.66. The rank order of areas based on the pooled concentration of OC bound to PM2.5 was traffic (17.893 µg/m3) > industrial (10.58 µg/m3) > urban (7.696 µg/m3) > rural (4.08 µg/m3). The rank order of areas based on the pooled (mean) concentration of EC in PM2.5 was traffic (17.893 µg/m3) > industrial (2.65 µg/m3) > Urban (1.48 µg/m3) > rural (1.06 µg/m3). The pooled concentrations of OC and EC bound to PM2.5 in traffic areas were higher than in other areas. Therefore, it is recommended that monitoring and effectively reducing concentration plans are carried out, especially in traffic areas.
Atmospheric heavy metal (HMs) pollution that impacts the environment and human health is one of the increasingly concerning problems in developing countries. Southeast Asia (SEA) is now described as a dynamic and rapidly developing region and is facing problems of air pollution, including HMs in the atmosphere. According to the International Cancer Research Institute (IARC), some metals (e.g., Pb, As, Ni, Cd, Hg, Cd, Cr) are particularly harmful to human health. In this chapter, we focus on the knowledge of atmospheric HMs in the SEA region over the last 15 years, in which, the potential sources and spatio temporal distribution of atmospheric HMs in SEA were discussed in detail. Research on atmospheric HMs is unevenly distributed in the SEA region and most of the studies concentrated in countries such as Thailand, Malaysia, and Vietnam. By employing multivariable models, including PCA and PMF, studies show that both anthropogenic sources (e.g., transportation, biomass burning, and industrial processes) and natural sources (e.g., volcanic eruption and dust storms) can contribute to elevated atmospheric HMs. HMs concentrations in industrial areas are often higher than in urban/background locations. On a seasonal basis, HMs concentrations in the dry season are often higher than in the rainy season. Certain knowledge gaps pertaining to atmospheric HMs in the SEA region necessitate comprehensive investigation. Specifically, there is a need for rigorous research focused on elucidating the deposition of atmospheric HMs as well as research regarding atmospheric mercury (Hg). This chapter presents scientific information on atmospheric HMs pollution in SEA from both regulatory and research perspectives. It aims to enhance the understanding of HMs contaminations in the SEA region by providing updated and rigorous scientific analysis.
La Paz and El Alto are two fast-growing, high-altitude Bolivian cities forming the second-largest metropolitan area in the country. Located between 3200 and 4050 m a.s.l. (above sea level), these cities are home to a burgeoning population of approximately 1.8 million residents. The air quality in this conurbation is heavily influenced by urbanization; however, there are no comprehensive studies evaluating the sources of air pollution and their health impacts. Despite their proximity, the substantial variation in altitude, topography, and socioeconomic activities between La Paz and El Alto result in distinct sources, dynamics, and transport of particulate matter (PM). In this investigation, PM10 samples were collected at two urban background stations located in La Paz and El Alto between April 2016 and June 2017. The samples were later analyzed for a wide range of chemical species including numerous source tracers (OC, EC, water-soluble ions, sugar anhydrides, sugar alcohols, trace metals, and molecular organic species). The United States Environmental Protection Agency (U.S. EPA) Positive Matrix Factorization (PMF v.5.0) receptor model was employed for the source apportionment of PM10. This is one of the first source apportionment studies in South America that incorporates an extensive suite of organic markers, including levoglucosan, polycyclic aromatic hydrocarbons (PAHs), hopanes, and alkanes, alongside inorganic species. The multisite PMF resolved 11 main sources of PM. The largest annual contribution to PM10 came from the following two major sources: the ensemble of the four vehicular emissions sources (exhaust and non-exhaust), accountable for 35 % and 25 % of the measured PM in La Paz and El Alto, respectively; and dust, which contributed 20 % and 32 % to the total PM mass. Secondary aerosols accounted for 22 % (24 %) in La Paz (El Alto). Agricultural smoke resulting from biomass burning in the Bolivian lowlands and neighboring countries contributed to 9 % (8 %) of the total PM10 mass annually, increasing to 17 % (13 %) between August–October. Primary biogenic emissions were responsible for 13 % (7 %) of the measured PM10 mass. Additionally, a profile associated with open waste burning occurring from May to August was identified. Although this source contributed only to 2 % (5 %) of the total PM10 mass, it constitutes the second largest source of PAHs, which are compounds potentially hazardous to human health. Our analysis additionally resolved two different traffic-related factors, a lubricant source (not frequently identified), and a non-exhaust emissions source. Overall, this study demonstrates that PM10 concentrations in La Paz and El Alto region are predominantly influenced by a limited number of local sources. In conclusion, to improve air quality in both cities, efforts should primarily focus on addressing dust, traffic emissions, open waste burning, and biomass burning.
Rapidly urbanizing cities in Latin America experience high levels of air pollution which are known risk factors for population health. However, the estimates of long-term exposure to air pollution are scarce in the region. We developed intraurban land use regression (LUR) models to map long-term exposure to fine particulate matter (PM 2.5 ) and nitrogen dioxide (NO 2 ) in the five largest cities in Colombia. We conducted air pollution measurement campaigns using gravimetric PM 2.5 and passive NO 2 sensors for two weeks during both the dry and rainy seasons in 2021 in the cities of Barranquilla, Bucaramanga, Bogotá, Cali, and Medellín, and combined these data with geospatial and meteorological variables. Annual models were developed using multivariable spatial regression models. The city annual PM 2.5 mean concentrations measured ranged between 12.32 𝛍g/m ³ and 15.99 𝛍g/m ³ while NO 2 concentrations ranged between 24.92 𝛍/m3) and 49.15 𝛍g/m ³ . The PM 2.5 annual models explained 82% of the variance (R ² ) in Medellín, 77% in Bucaramanga, 73% in Barranquilla, 70% in Cali, and 44% in Bogotá. The NO 2 models explained 65% of the variance in Bucaramanga, 57% in Medellín, 44% in Cali, 40% in Bogotá, and 30% in Barranquilla. Most of the predictor variables included in the models were a combination of specific land use characteristics and roadway variables. Cross-validation suggest that PM 2.5 outperformed NO 2 models. The developed models can be used as exposure estimate in epidemiological studies, as input in hybrid models to improve personal exposure assessment, and for policy evaluation.
In this study, PM 10 daily samples were collected every day during approximately one month in winter and one month in summer, 2019. Sampling was performed simultaneously at two different locations: an urban traffic site (∼ 80 m a.s.l.) and a regional background station (∼ 1500 m a.s.l.) in the Western Mediterranean. The objective of this work was to investigate PM 10 sources at both sites in order to determine regional and urban contributions to aerosol levels. Seven factors were obtained at both sites using Positive Matrix Factorization (PMF): Saharan dust , Aged sea salt , Ammonium sulfate , Nitrate , Road traffic , Local dust and Fresh sea salt . At the urban site, the contribution of vehicle related-sources ( Road traffic, Nitrate and Local dust ) was significantly higher in winter (∼80%) than in summer (∼60%).
The carbonaceous particles represent a significant fraction in the particulate matter (PM) and are considered an environmental hazard due to their effects on climate and health. The main goal in this research is to identify and analyze the scope that have been achieved so far on the characterization and measurement of the carbonaceous fraction present in PM, a great contribution to global pollution and thus to the deterioration of public health. The ProKnow-C methodology was used to build a bibliographic portfolio and perform a bibliometric and systemic analysis of the information found in the chosen databases. The contribution of these carbonaceous compounds to PM is very significant, reaching values up to 50%. The most used methods for the determination of organic and elemental carbon are thermo-optical reflectance and transmittance. Positive Factorization models are used worldwide to determine potential sources of particulate matter emissions. Even though various studies have been developed to understand these carbonaceous substances, there are several limitations in the measurements and limited knowledge on the subject. The positive outcomes and future possibilities were analyzed as well.
Particulate matter (PM), particle pollution that can travel long distances, is a big concern because it contains liquid droplets or microscopic solids resulting in significant health issues such as respirational and cancer problems. Therefore, the characterization of these particles is very significant as a hazard to public health. PM can be identified by X-ray diffraction (XRD) and Raman spectroscopy (RS), both powerful and non-destructive technologies. RS, in particular, allows the identification of black carbon, considered one of the pollutants with the greatest influence on climate change. Another important technology for the evaluation of inorganic and organic functional groups present in PM compounds is the Fourier transform infrared spectroscopy (FTIR). X-ray fluorescence (XRF) provides elemental analysis, revealing, in many cases, the original source of the sample. In order to understand the current state of the art, the Proknow-C method was applied to track the most recent information on PM characterization. Aspects such as sample collection, filter material, characterization parameters, PM components, and the advantages and limitations of each technique are discussed. PM minerals are found to be composed of silicates, oxides, sulfates, and carbonates. The elemental components of PM are classified into five categories: marine aerosol, mineral material, anthropogenic elements, organic carbon, and elemental carbon. The XRD technique is a powerful, fast, and non-destructive tool to identify various minerals present in PM. On the other hand, the XRF technique requires minimal sample treatment, but its sensitivity is limited for the determination of trace metals and some relevant environmental elements. FTIR spectroscopy is able to identify and quantify all organic functional groups present in atmospheric PM. Despite its advantages, a proper choice of calibration method is crucial to ensure its effectiveness. RS is fast and simple, although it only detects Raman-active functional groups. These are some of the advantages and limitations of these techniques addressed in the following review article.
La Paz and El Alto are two fast-growing high-altitude Bolivian cities forming the second largest metropolitan area in the country, located between 3200 and 4050 m a.s.l. Together they host a growing population of around 1.8 million people. The air quality in this conurbation is strongly influenced by urbanization. However, there are no comprehensive studies that have assessed the sources of air pollution and their impacts on health. Despite being neighboring cities, the drastic change in altitude and topography between La Paz and El Alto together with different socio-economic activities lead to different sources, dynamics and transport of particulate matter (PM). In this investigation, PM10 samples were collected at two urban background stations located in La Paz and El Alto between April 2016 and June 2017. The samples were later analyzed for a wide range of chemical species including numerous source tracers (OC, EC, water-soluble ions, sugar anhydrides, sugar alcohols, trace metals, and molecular organic species). The US-EPA Positive Matrix Factorization (PMF v.5.0) receptor model was then applied for source apportionment of PM10. This is the first source apportionment study in South America that incorporates a large set of organic markers (such as levoglucosan, polycyclic aromatic hydrocarbons – PAH, hopanes and alkanes) together with inorganic species. The multisite PMF resolved 11 main sources of PM. The largest annual contribution to PM10 came from two major sources: the ensemble of the four vehicular emissions sources (exhaust and non-exhaust), together responsible for 35 % and 25 % of the measured PM in La Paz and El Alto, respectively, and dust contributing 20 % and 32 % to the total. Secondary aerosols contributed 22 % (24 %) in La Paz (El Alto). Agriculture-related smoke from biomass burning originated in the Bolivian lowlands and neighboring countries contributed to 8 % (7 %) of the total PM10 mass annually. This contribution increased to 17 % (13 %) between August–October. Primary biogenic emissions were responsible for 13 % (7 %) of the measured PM10 mass. Finally, it was possible to identify a profile related to open waste burning occurring between the months of May and August. Despite the fact that this source contributed only to 2 % (5 %) of the total PM10 mass, it constitutes the second largest source of PAHs, compounds potentially hazardous to health. Our analysis resulted in the identification of two specific traffic-related sources. In addition, we also identified a lubricant source (not frequently identified) and a non-exhaust emissions source. This study shows that PM10 concentrations in La Paz and El Alto region are mostly impacted by a limited number of local sources. In conclusion, dust, traffic emissions, open waste burning and biomass burning are the main sources to target in order to improve air quality in both cities.
High urbanization and a consequent change in land cover can lead to a deterioration in air quality and generate impacts on public health. The objective of this paper is to provide a multitemporal analysis of the influence of particulate matter ≤ 10 μm (PM10) on human mortality from the land cover variation in a Latin American megacity. Six monitoring stations (monitoring daily PM10 concentration, increases in daily mortality (IDM), and land cover) were established throughout the megacity. The results suggest that for every 10% increase in vegetation cover, the daily PM10 concentration and IDM decreases by 7.5 μg/m3 and 0.34%, respectively. Moreover, it is evident that the monitoring station with the lowest vegetation cover (8.96 times) shows an increase of 1.56 times and 4.8 times in the daily PM10 concentration and IDM, respectively, compared with the monitoring station with the highest vegetation cover (46.7%). It is also suggested that for each increase of 100 inhabitants/hectare in population density, the daily PM10 concentration and IDM increases by 9.99 µg/m3 and 0.45%, respectively. Finally, the population densification of the megacity possibly implies a loss of vegetation cover and contributes to the increase in PM10 and IDM.
The monograph is devoted to the study of atmospheric aerosol and its dynamics in the urban environment of Moscow megacity. Based on the AeroRadCity 2018-2019 complex experiment, composed of measurement campaign and numerical experiments using the COSMO-ART chemical transport model, a number of new results were obtained, which contributed to a deeper understanding of the gas-aerosol composition of the urban atmosphere, wet aerosol deposition with accounting of geochemical processes and aerosol radiative effects. Aerosol pollution in the Moscow region and its dynamics in the 21st century were estimated according to the aerosol retrievals using the MAIAC algorithm developed for the MODIS satellite instrument, and long-term AERONET measurements. The effects of aerosol on meteorological and radiative characteristics of the atmosphere were obtained from the numerical experiments with the COSMO model and long-term observations. The indirect aerosol effects on cloud characteristics and weather forecast were estimated.
Agro-industrial areas are frequently affected by various sources of atmospheric pollutants that have a negative impact on public health and ecosystems. However, air quality in these areas is infrequently monitored because of their smaller population compared to large cities, especially in developing countries. The Cauca River valley (CRV) is an agro-industrial region in southwestern Colombia, where a large fraction of the area is devoted to sugarcane and livestock production. The CRV is also affected by road traffic and industrial emissions. This study aims to elucidate the chemical composition of particulate matter fine mode (PM2.5) and to identify the main pollutant sources before source attribution. A sampling campaign was carried out at a representative site in the CRV region, where daily averaged mass concentrations of PM2.5 and the concentrations of water-soluble ions, trace metals, organic and elemental carbon, and various fractions of organic compounds (carbohydrates, n alkanes, and polycyclic aromatic hydrocarbons – PAHs) were measured. The mean PM2.5 was 14.4±4.4 µg m-3, and the most abundant constituent was organic material (52.7 % ± 18.4 %), followed by sulfate (12.7 % ± 2.8 %), and elemental carbon (7.1 % ± 2.5 %), which indicates the presence of secondary aerosol formation and incomplete combustion. Levoglucosan was present in all samples, with a mean concentration of (113.8±147.2 ng m-3), revealing biomass burning as a persistent source. Mass closure using the elemental carbon (EC) tracer method explained 88.4 % on PM2.5, whereas the organic tracer method explained 70.9 % of PM2.5. We attribute this difference to the lack of information of specific organic tracers for some sources, both primary and secondary. Organic material and inorganic ions were the dominant groups of species (79 % of PM2.5). OMprim and OMsec contribute 24.2 % and 28.5 % to PM2.5. Inorganic ions as sulfate, nitrate, and ammonia constitute 19.0 %, EC 7.1 %, dust 3.5%, particle-bounded water (PBW) 5.3 %, and trace element oxides (TEOs), 0.9 % of PM2.5. The aerosol was acidic, with a pH of 2.5±0.4, mainly because of the abundance of organic and sulfur compounds. Diagnostic ratios and tracer concentrations indicate that most PM2.5 was emitted locally and had contributions of both pyrogenic and petrogenic sources, that biomass burning was ubiquitous during the sampling period and was the main source of PAHs, and that the relatively low PM2.5 concentrations and mutagenic potentials are consistent with low-intensity, year-long biomass burning (BB) and sugarcane pre-harvest burning in the CRV.
In this paper, the emission sources of PM10 are characterised by analysing its trace elements (TE) and ions contents. PM10 samples were collected for a year (2019-2020) at five sites and analysed. PM10 speciated data were analysed using graphical visualization, correlation analysis, generalised additive model (GAM), and positive matrix factorization (PMF). Annual average PM10 concentrations (µg/m3) were 304.68 ± 155.56 at Aziziyah, 219.59 ± 87.29 at Misfalah, 173.90 ± 103.08 at Abdeyah, 168.81 ± 82.50 at Askan, and 157.60 ± 80.10 at Sanaiyah in Makkah, which exceeded WHO (15 µg/m3), USEPA (50 µg/m3), and the Saudi Arabia national (80 µg/m3) annual air quality standards. A GAM model was developed using PM10 as a response and ions and TEs as predictors. Among the predictors Mg, Ca, Cr, Al, and Pb were highly significant (p < 0.01), Se, Cl, and NO2 were significant (p < 0.05), and PO4 and SO4 were significant (p < 0.1). The model showed R-squared (adj) 0.85 and deviance explained 88.1%. PMF identified four main emission sources of PM10 in Makkah: (1) Road traffic emissions (explained 51% variance); (2) Industrial emissions and mineral dust (explained 27.5% variance); (3) Restaurant and dwelling emissions (explained 13.6% variance); and (4) Fossil fuel combustion (explained 7.9% variance).
In this article, volatile organic compounds (VOC) were characterized in ambient air at three different monitoring sites within the urban perimeter of Bogotá, Colombia. On-line VOC measurements were conducted using a Synstech Spectras portable gas chromatograph with a temporal resolution of 30 min. Average VOC concentrations were higher at two of the sampling sites, which are characterized by intensive industrial and commercial activities, and high vehicular activity. Analyses of the diurnal behavior of total VOC showed that concentrations tend to be higher in the morning (at around 8:00 LT) and during the evening (around 22:00 LT). Such trends suggest the influence of road traffic activity in the surroundings of the measuring sites on VOC levels. According to our results, alkanes are the most abundant hydrocarbons in the ambient air in Bogotá (about 80% of the total VOC), while alkenes represent only 15% of the total VOC. We computed the ozone formation potential (OFP) using the maximum incremental reactivity (MIR) concept and evaluated the role of each VOC in the O3 formation. These results show that ethene, propene, n-butane, i-pentane and isoprene are the species with the highest OFP (noting that high concentrations are not necessarily linked with elevated O3 production). Finally, we used principal components analysis to identify the sources of different VOC. Our results showed that most of the compounds included in this study are emitted by road traffic. The receptor modeling also shows that the top-five compounds in terms of O3 production come mainly from the exhaust of gasoline vehicles.
London, like many major cities, has a noted air pollution problem, and a better understanding of the sources of airborne particles in the different size fractions will facilitate the implementation and effectiveness of control strategies to reduce air pollution. Thus, the trace elemental composition of the fine and coarse fraction were analysed at hourly time resolution at urban background (North Kensington, NK) and roadside (Marylebone Road, MR) sites within central London. Unlike previous work, the current study focuses on measurements during the summer providing a snapshot of contributing sources, utilising the high time resolution to improve source identification. Roadside enrichment was observed for a large number of elements associated with traffic emissions (Al, S, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, As, Rb and Zr), while those elements that are typically from more regional sources (e.g. Na, Cl, S and K) were not found to have an appreciable increment. Positive Matrix Factorization (PMF) was applied for the source apportionment of the particle mass at both sites with similar sources being identified, including sea salt, airborne soil, traffic emissions, secondary inorganic aerosols and a Zn-Pb source. In the fine fraction, traffic emissions was the largest contributing source at MR (31.9%), whereas it was incorporated within an "urban background" source at NK, which had contributions from wood smoke, vehicle emissions and secondary particles. Regional sources were the major contributors to the coarse fraction at both sites. Secondary inorganic aerosols (which contained influences from shipping emissions and coal combustion) source factors accounted for around 33% of the PM10 at NK and were found to have the highest contributions from regional sources, including from the European mainland. Exhaust and non-exhaust sources both contribute appreciably to PM10 levels at the MR site, highlighting the continuing importance of vehicle-related air pollutants at roadside.
Thermal-optical analysis is a conventional method for determining the
carbonaceous aerosol fraction and for classifying it into organic carbon,
OC, and elemental carbon, EC. Unfortunately, the different thermal evolution
protocols in use can result in a wide elemental carbon-to-total carbon
variation by up to a factor of five. In Europe, there is currently no
standard procedure for determining the carbonaceous aerosol fraction which
implies that data from different laboratories at various sites are of
unknown accuracy and cannot be considered comparable. In the framework of
the EU-project EUSAAR (European Supersites for Atmospheric Aerosol
Research), a comprehensive study has been carried out to identify the causes
of differences in the EC measured using different thermal evolution
protocols; thereby the major positive and negative biases affecting
thermal-optical analysis have been isolated and minimised to define an
optimised protocol suitable for European aerosols. Our approach to improve
the accuracy of the discrimination between OC and EC was essentially based
on four goals. Firstly, charring corrections rely on faulty assumptions –
e.g. pyrolytic carbon is considered to evolve completely before native EC
throughout the analysis –, thus we have reduced pyrolysis to a minimum by
favoring volatilisation of OC. Secondly, we have minimised the potential
negative bias in EC determination due to early evolution of light absorbing
carbon species at higher temperatures in the He-mode, including both native
EC and combinations of native EC and pyrolytic carbon potentially with
different specific attenuation cross section values. Thirdly, we have
minimised the potential positive bias in EC determination resulting from the
incomplete evolution of OC during the He-mode which then evolves during the
He/O2-mode, potentially after the split point. Finally, we have
minimised the uncertainty due to the position of the OC/EC split point on
the FID response profile by introducing multiple desorption steps in the
He/O2-mode. Based on different types of carbonaceous PM encountered
across Europe, we have defined an optimised thermal evolution protocol, the
EUSAAR_2 protocol, as follows: step 1 in He, 200 °C for 120 s; step 2
in He 300 °C for 150 s; step 3 in He 450 °C for 180 s; step 4 in He
650 °C for 180 s. For steps 1–4 in He/O2, the conditions are
500 °C for 120 s, 550 °C for 120 s, 700 ° C for 70 s,
and 850 °C for 80 s, respectively.
Air pollution is now becoming an independent risk factor for cardiovascular morbidity and mortality. Numerous epidemiological, biomedical and clinical studies indicate that ambient particulate matter (PM) in air pollution is strongly associated with increased cardiovascular disease such as myocardial infarction (MI), cardiac arrhythmias, ischemic stroke, vascular dysfunction, hypertension and atherosclerosis. The molecular mechanisms for PM-caused cardiovascular disease include directly toxicity to cardiovascular system or indirectly injury by inducing systemic inflammation and oxidative stress in peripheral circulation. Here, we review the linking between PM exposure and the occurrence of cardiovascular disease and discussed the possible underlying mechanisms for the observed PM induced increases in cardiovascular morbidity and mortality.
This study reports the results of field research into variability of the scavenging coefficient (Λ) of suspended dust comprising particles with aerodynamic diameters less than 10 mm. Registration of PM10 over 7 years in conditions of the occurrence of rainfall (convective light showers, large-scale precipitation and storms) was undertaken in an undeveloped rural area. The analysis involved 806 observations taken at constant time intervals of 0.5 hour. The measurements of the concentration of PM10 were performed by means of a reference method accompanied by concurrent registration of basic meteorological parameters. It was found that, for PM10, the scavenging efficiency is considerably influenced by rainfall intensity R and the type of precipitation. In the case of convective precipitation, data on Λ are only partially related to "classical approach" of rain scavenging. Within the range of comparable values of rainfall intensity, the type of wet deposition (except for storms) does not influence the effectiveness of scavenging PM10 from the ground-level zone. The large number of observations conducted in real-time conditions yielded a proposal of simple regression model, which can be deemed suitable for the description of variability Λ (DPM10), but only to a limited extent for large-scale precipitation. The collected results can be applied in air pollution dispersion models and deposition and were found to be generally representative for areas with similar climatic characteristics.
Major components of suspended particulate matter (PM) are inorganic ions, organic matter (OM), elemental carbon (EC), geological minerals, salt, non-mineral elements, and water. Since oxygen (O) and hydrogen (H) are not directly measured in chemical speciation networks, more than ten weighting equations have been applied to account for their presence, thereby approximating gravimetric mass. Assumptions for these weights are not the same under all circumstances. OM is estimated from an organic carbon (OC) multiplier (f) that ranges from 1.4 to 1.8 in most studies, but f can be larger for highly polar compounds from biomass burning and secondary organic aerosols. The mineral content of fugitive dust is estimated from elemental markers, while the water-soluble content is accounted for as inorganic ions or salt. Part of the discrepancy between measured and reconstructed PM mass is due to the measurement process, including: (1) organic vapors adsorbed on quartz-fiber filters; (2) evaporation of volatile ammonium nitrate and OM between the weighed Teflon-membrane filter and the nylon-membrane and/or quartz-fiber filters on which ions and carbon are measured; and (3) liquid water retained on soluble constituents during filter weighing. The widely used IMPROVE equations were developed to characterize particle light extinction in U.S. national parks, and variants of this approach have been tested in a large variety of environments. Important factors for improving agreement between measured and reconstructed PM mass are the f multiplier for converting OC to OM and accounting for OC sampling artifacts.
Electronic supplementary material
The online version of this article (doi:10.1007/s11869-015-0338-3) contains supplementary material, which is available to authorized users.
Objective:
To analyze the association between daily mortality from different causes and acute exposure to particulate matter less than 10 microns in aerodynamic diameter (PM10), in Bogota, Colombia.
Materials and methods:
A time-series ecological study was conducted from 1998 to 2006. The association between mortality (due to different causes) and exposure was analyzed using single and distributed lag models and adjusting for potential confounders.
Results:
For all ages, the cumulative effect of acute mortality from all causes and respiratory causes increased 0.71% (95%CI 0.46-0.96) and 1.43% (95%CI 0.85-2.00), respectively, per 10µg/m³ increment in daily average PM10 with a lag of three days before death. Cumulative effect of mortality from cardiovascular causes was -0.03% (95%CI -0.49-0.44%) with the same lag.
Conclusions:
The results suggest an association between an increase in PM10 concentrations and acute mortality from all causes and respiratory causes.
Urban air quality management plan (UAQMP) is an effective and efficient tool employed in managing acceptable urban air quality. However, the UAQM practices are specific to a country’s needs and requirements. Majority of the developed countries have full–fledged UAQMP with a regulatory management framework. However, developing countries are still working in formulating the effective and efficient UAQMPs to manage their deteriorating urban air environment. The first step in the process of formulation of UAQMP is to identify the air quality control regions based on ambient air quality status and second, initiate a time bound program involving all stakeholders to develop UAQMPs. The successful implementation of UAQMPs depends on the strength of its key components, e.g. goal/objective, monitoring network, emission inventory, air quality modeling, control strategies and public participation. This paper presents a comprehensive review on UAQMPs, being implemented worldwide at different scales e.g., national (macro), city (medium), and local (micro).
This study aimed to investigate the quantitative effects of outdoor air pollution, represented by 10 µg/m3 increment of PM10, on chronic obstructive pulmonary disease in China, United States and European Union through systematic review and meta-analysis.
Publications in English and Chinese from PubMed and EMBASE were selected. The Cochrane Review Handbook of Generic Inverse Variance was used to synthesize the pooled effects on incidence, prevalence, mortality and hospital admission.
Outdoor air pollution contributed to higher incidence and prevalence of COPD. Short-term exposure was associated with COPD mortality increased by 6%, 1% and 1% in the European Union, the United States and China, respectively (p < 0.05). Chronic PM exposure produced a 10% increase in mortality. In a short-term exposure to 10 µg/m3 PM10 increment COPD mortality was elevated by 1% in China (p < 0.05) and hospital admission enrollment was increased by 1% in China, 2% in United States and 1% in European Union (p < 0.05).
Outdoor air pollution contributes to the increasing burdens of COPD.10 µg/m3 increase of PM10 produced significant condition of COPD death and exacerbation in China, United States and European Union. Controlling air pollution will have substantial benefit to COPD morbidity and mortality.
A pilot study, in which we conducted inhalable particulate matter (PM10) measurements in four public elementary schools in Bogotá, is presented. Three of these schools are located alongside major urban roads with different types of public transportation. The remainder school is located alongside a rural road. PM10 measurements were carried out using both gravimetric and real time techniques. Average PM10 concentrations found in the schools ranged from 55 ug m-3 to 91 ug m-3. These pollutant concentrations are above the World Health Organization reference values. Significant differences in PM10 concentrations were observed between the schools located in urban roads and the school located in the semi-rural area. The present work corresponds to the base line results of a longitudinal study that is still being conducted. These results demonstrate the importance of continuing developing research aimed at characterizing the range of atmospheric pollutants at major city roads environs in Bogota.
Simultaneous monitoring of PM2.5 and PM10 was carried out during two-month periods at three air-quality monitoring stations in Bogotá. The data gathered were statistically analyzed looking for evidence of correlations between PM2.5 and PM10. Results show a positive linear correlation between the two parameters.
En el presente estudio se llevó a cabo la caracterización química del material particulado menor a 10 micrómetros (PM 10) recolectado en la Localidad de Puente Aranda de Bogotá. Durante el período de estudio (junio de 2005 a junio de 2006) se recolectaron 75 muestras de PM 10 en diferentes condiciones climáticas en tres puntos de monitoreo, dos en la zona industrial y el tercero en una zona remota. Se incluyen en el estudio los días del paro de transportes que tuvo lugar en la ciudad en el 2006. Se determinó la presencia de cadmio, cobre, cromo, plata, hierro, plomo, manganeso, cinc y níquel. Las concentraciones promedio diarias de PM 10 en Puente Aranda se encontraron entre 65 y 100 µg/m3, mientras que para el norte de la ciudad variaban entre 20 y 30 µg/m3. Los principales metales encontrados en la zona industrial fueron Fe y Pb, con concentraciones hasta de 4.000 ng/m3. El grupo de metales Cu, Cr, Zn, Ni, Mn presentaron un rango medio de concentración (50 a 700 ng/m3 en Puente Aranda, <100 ng/m3 en el norte de la ciudad). Los metales con las menores concentraciones en la atmósfera fueron Cd y Ag. A partir del analisis de material particulado y metales pesados se realizó una aproximación al aporte de las fuentes de emisión.
The impact of road dust emissions on PM10
and PM2.5 (atmospheric particulate matter with diameteer
<10 μm and 2.5 μm mass concentrations recorded from 2003
to 2010 at 11 locations (rural, urban and industrial) in southern
Spain was estimated based on the chemical characterization
of PM and the use of a constrained Positive Matrix
Factorization, where the chemical profile of local road dust
samples is used as a priori knowledge. Results indicate that
road dust increased PM10 levels on average by 21–35% at
traffic sites, 29–34% at urban background sites heavily affected
by road traffic emissions, 17–22% at urban-industrial
sites and 9–22%at rural sites. Road dust contributions to ambient
PM levels show a marked seasonality with maxima in
summer and minima in winter, likely due to the rainfall frequency.
Decreasing concentration trends over the sampling
years were found at some traffic and urban sites but in most
cases the decreases were less significant than for vehicle exhaust
emissions, while concentrations increased at industrial
sites, probably due to local peculiarities. Concerning PM2.5,
road dust contributions were lower than in PM10, as expected
but still important (21–31 %, 11–31 %, 6–16% and 7% for
traffic, urban background, urban-industrial and rural sites, respectively).
In addition the three main sources of road dust
(carbonaceous particles, brake wear and road wear/mineral)
were identified and their contributions to road dust mass
loadings estimated, supporting the idea that air quality managers
should drive measures aimed at preventing the build-up
of road dust particles on roads.
Particulate matter, measured as PM10, is the most concerning airborne pollutant in Bogotá. Determining its chemical composition is important for understanding its potential effects and to estimate various sources' contribution to such pollution. This paper gives the results of characterising the ionic species, carbonaceous material, metals and crustal elements present in airborne PM10 in Bogotá. An ion charge balance and mass reconstruction were done for determining consistency between chemical characterisation and gravimetric PM10. The composition was different in each area; however, the fractions contributing most to PM10 were crustal, 37% to 42% was related to fugitive and suspended dust, 12% to 11% was related to carbonaceus fractions, 43% to elemental carbon, 34% for organic matter and 5% to 8% for ionic fractions.
In this work, the source of ambient particulate matter (PM10)
collected over a one year period at an urban background site in Lens
(France) were determined and investigated using a~Positive Matrix
Factorization receptor model (US EPA PMF v3.0). In addition, a Potential
Source Contribution Function (PSCF) was performed by means of the
Hysplit v4.9 model to assess prevailing geographical origins of the
identified sources. A selective iteration process was followed for the
qualification of the more robust and meaningful PMF solution. Components
measured and used in the PMF include inorganic and organic species:
soluble ionic species, trace elements, elemental carbon (EC), sugars
alcohols, sugar anhydride, and organic carbon (OC). The mean
PM10 concentration measured from March 2011 to March 2012 was
about 21 μg m-3 with typically OM, nitrate and sulfate
contributing to most of the mass and accounting respectively for 5.8,
4.5 and 2.3 μg m-3 on a yearly basis. Accordingly, PMF
outputs showed that the main emission sources were (in a decreasing
order of contribution): secondary inorganic aerosols (28% of the total
PM10 mass), aged marine emissions (19%), with probably
predominant contribution of shipping activities, biomass burning (13%),
mineral dust (13%), primary biogenic emissions (9%), fresh sea salts
(8%), primary traffic emissions (6%) and heavy oil combustion (4%).
Significant temporal variations were observed for most of the identified
sources. In particular, biomass burning emissions were negligible in
summer but responsible for about 25% of total PM10 and 50% of
total OC at wintertime. Conversely, primary biogenic emissions were
found to be negligible in winter but to represent about 20% of total
PM10 and 40% of total OC in summer. The latter result calls
for more investigations of primary biogenic aerosols using source
apportionment studies, which quite usually disregards this type of
sources. This study furthermore underlines the major influence of
secondary processes during daily threshold exceedances. Finally,
apparent discrepancies that could be generally observed between
filter-based studies (such as the present one) and Aerosol Mass
Spectrometer-based PMF analyses (organic fractions) are also discussed
here.
Estimating the burden of disease attributable to long-term exposure to fine particulate matter (PM2.5) in ambient air requires knowledge of both the shape and magnitude of the relative risk function (RR). However, there is inadequate direct evidence to identify the shape of the mortality RR functions at high ambient concentrations observed in many places in the world.
Develop relative risk (RR) functions over entire global exposure range for causes of mortality in adults: ischemic heart disease (IHD), cerebrovascular disease (stroke), chronic obstructive pulmonary disease (COPD), and lung cancer (LC). In addition, develop RR functions for the incidence of acute lower respiratory infection (ALRI) that can be used to estimate mortality and lost-years of healthy life in children less than 5 years old.
An Integrated Exposure-Response (IER) model was fit by integrating available RR information from studies of ambient air pollution (AAP), second hand tobacco smoke (SHS), household solid cooking fuel (HAP), and active smoking (AS). AS exposures were converted to estimated annual PM2.5 exposure equivalents using inhaled doses of particle mass. Population attributable fractions (PAF) were derived for every country based on estimated world-wide ambient PM2.5 concentrations.
The IER model was a superior predictor of RR compared to seven other forms previously used in burden assessments. The PAF (%) attributable to AAP exposure varied among countries from: 2-41 for IHD, 1-43 for stroke, < 1-21 for COPD, < 1-25 for LC, and < 1-38 for ALRI.
We developed a fine particulate mass-based RR model that covered the global range of exposure by integrating RR information from different combustion types that generate emissions of particulate matter. The model can be updated as new RR information becomes available.
Santiago, the capital of Chile, suffers from high air pollution levels, especially during winter. An extensive particulate matter (PM) monitoring and analysis program was conducted to quantify elemental concentrations of PM. Size-resolved PM samples (PM2.5 and PM10–2.5) from the La Paz and Las Condes stations in Santiago (2004–2005) were analyzed using ICP-MS. Most trace element concentrations (Cu, Pb, Zn, Mn, V, Sb, Pb and As) were higher during winter than during summer and were also higher at the La Paz station than at the Las Condes station. During the highest pollution events, As concentrations in PM2.5 (16 ng m−3) exceeded the annual average standard value (6 ng m−3). A 10-year time series showed decreasing Pb and As concentrations and slightly increasing Zn, Cu and Mn concentrations. Concentrations of Cr and Ni remained relatively constant. The implementation of new public policies in 1998 may explain the decreasing concentrations of Pb and As. Enrichment factor (EF) calculations identified two principal groups: elements with EF < 10 (Mg, Y, Zr, U Sr, Ca, Ti, and V) and EF > 10 (Rb, K, Cs, Fe, P, Ba, Mn, Ni, Cr, Co, Zn, Sn, Pb, Cu, Mo, Cd, As, Ag, and Sb), which were related to natural and anthropogenic PM sources, respectively. Three main PM sources were identified using factor analysis: a natural source (crustal matter and marine aerosol), combustion and copper smelting. Three other sources were identified using rare earth elements: fluid catalytic crackers, oil-fired power production and catalytic converters.
Particle-related pollution (PM10, PM2.5 and soot) was measured in both indoor and outdoor microenvironments at four public elementary schools in Bogota, Colombia. Three of these schools were located alongside major urban roads in w hich different types of public transit systems are used (bus rapid transit system and conventional transit buses). The fourth school was located on a non-congested road (background school). Pollutant levels at schools situated on major-roads were higher than those found at the low -congestionroad school. Outdoor black carbon daily mean concentrations at the schools located near major roads were up to six times higher than those recorded at the background school. Mean particulate matter concentrations at schools near major roads were above international standards, suggesting that school-age children in Bogota are exposed to pollution levels that are considered to be harmful by environmental and public health authorities. Elevated indoor and outdoor pollutant concentrations documented in this study suggested that traffic has a direct impact on air quality regarding the schools’ characterised microenvironments.
At urban traffic intersections, vehicles frequently stop with idling engines during the red-light period and speed up rapidly during the green-light period. The changes of driving patterns (i.e., idle, acceleration, deceleration and cruising patterns) generally produce uncertain emission. Additionally, the movement of pedestrians and the influence of wind further result in the random dispersion of pollutants. It is, therefore, too complex to simulate the effects of such dynamics on the resulting emission using conventional deterministic causal models.
Aerosol particle samples collected from Asia and the North Pacific were analyzed to investigate the relationships among atmospheric sea salt, mineral aerosol, biogenic emissions (methanesulfonate (MSA)), and several anthropogenic substances (sulfate, nitrate, and various trace elements). These studies specifically focused on the sources for aerosol SO=4 and on the long-range transport of continental materials to the North Pacific. Ground-based aerosol sampling was conducted at four coastal-continental sites: Hong Kong, Taiwan, Okinawa, and Cheju; and at three remote Pacific islands, Shemya, Midway, and Oahu. Non-sea-salt (nss) SO=4 and MSA were uncorrelated at the East Asian sites presumably because pollution sources overwhelm the biogenic emissions of nss SO=4. At the coastal-continental sites, marine biogenic emissions accounted for only 10 to
Heze city, a medium-size city in Shandong province, Eastern China. Ambient PM2.5 samples were collected in urban area of Heze from August 2015 to April 2016, and chemical species and sources of PM2.5 were investigated in this paper. The results indicated that the average concentration of PM2.5 was 100.9 μg/m³ during the sampling period, and the water-soluble ions, carbonaceous species included elemental carbon (EC) and organic carbon (OC), as well as elements contributed 32.7–51.7%, 16.3% and 12.5%, respectively, to PM2.5. Pearson's correlation analysis showed that the existing form of NH4⁺ was more complex and diverse in spring/summer, and ammonium nitrate, ammonium sulfate and ammonium hydrogen sulfate might be major form of NH4⁺ in autumn/winter. Correlation analysis between PM2.5 and SO4²⁻/NO3⁻, PM2.5 and OC/EC during different seasons suggested that mobile sources might make an important impact on the increase of PM2.5 concentrations in spring/summer, and stationary sources might play a critical role on the increase of PM2.5 concentrations in autumn/winter. Seven factors were selected in Positive Matrix Factorization (PMF) models analysis based on the Error Estimation (EE) diagnostics during different seasons. Secondary source had the highest contribution to PM2.5 in Heze for the whole year, and followed by coal combustion, vehicle exhaust, soil dust, construction dust, biomass burning and metal manufacturing, and their annual contributions to PM2.5 were 26.5%, 17.2%, 16.5%, 11.5%, 7.7%, 7.0% and 3.8%, respectively. The air masses that were originated from Mongolia reflected the features of large-scale and long-distance air transport; while the air masses that began in Jiangsu, Shandong and Henan showed the features of small-scale and short-distance. Shandong, Henan and Jiangsu were identified as the major potential sources-areas of PM2.5 by using potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) models.
Concentrations of sixteen rare earth elements (REEs) in PM2.5 and potential-source samples, collected in Nanchang city in mid-September 2013, were determined by inductively coupled plasma mass spectrometry (ICP-MS). The results showed that the concentrations of total REEs (∑REE) ranged from 78.76 to 1351 ng/mg. The order of REEs in PM2.5 samples showed the anthropogenic effects, Ce and Eu were affected more than the other REEs according to the enrichment factors. The results of chondrite-normalized REEs patterns and characteristic parameters showed evident light REEs fractionation, and positive anomalies of Ce and Eu in PM2.5. The other non-local pollution sources affected the PM2.5 samples, according to the triangular diagram of La, Ce and Sm compositions and plot of ∑REE vs δEu. Moreover, plot of (La/Sm)N vs (Gd/Yb)N revealed the effects of local sources. In conclusion, the REEs in potential-source samples were close to the background of local soil, while the REEs in PM2.5 samples in Nanchang city were jointly affected by the investigated local sources and other non-local sources.
From 1st June to 31st August 2015, the online datasets (the water soluble ions (WSIs), OC and EC in PM2.5, and SO2, NO2, NO) were measured continuously at Tianjin. Source apportionment of atmospheric pollutants was carried out by using PMF and ME2 models based on the online datasets. During summer in Tianjin, the ammonium sulfate/ammonium hydrogen sulfate might be major forms of sulfate in the atmospheric aerosol, while the ammonium nitrate might be major forms of nitrate. The poor correlation between OC and EC might be caused by the changes of emission sources and the production of secondary organic carbon (SOC). Five source-categories that contributed to atmospheric pollutants were extracted by PMF and ME2 models, respectively. The profiles calculated by PMF and ME2 models were consistent, and the source contributions estimated by the two models were also similar. The correlations (R² = 0.84–0.94) were better on the time series of the contributed concentrations for the same source-category calculated from PMF and ME2 models. The source-categories were identified as secondary sources (the contribution of 25.4–26.1%), vehicle exhaust (23.3–25.4%), coal combustion (16.5–18.2%), crustal dust (13.2–14.0%) and biomass burning (9.1–10.2%). For the same source-category identified from PMF and ME2 models, the differences of profiles might be attributed to the differences of calculated methods from the two models and the uncertainties of the online datasets.
With the objective of estimating the impact of harbour activities on ambient PM10 and PM2.5 levels at the urban area of Barcelona, a one year long monitoring campaign was carried out in the context of the European APICE project (MED-FEDER-EC). This campaign was simultaneously conducted at the port and a central urban background site. A detailed PM10 and PM2.5 chemical speciation analysis was carried out with samples from both sites. Subsequently, a source apportionment analysis by means of the PMF receptor model was performed. Six common factors were identified, explaining local to regional emission sources (fuel oil combustion, industrial emissions, mineral-road dust resuspension, and road traffic emissions) and aerosol formation/transformation processes (secondary aerosols including ammonium sulphate and organic aerosols, and a mixed source accounting for aged sea spray and secondary nitrate).
The atmospheric pollution created by coal-dominated industrial cities in China cannot be neglected. This study focuses on the atmospheric PM10 in the typical industrial city of Pingdingshan City in North China. A total of 44 PM10 samples were collected from three different sites (power plant, mining area, and roadside) in Pingdingshan City during the winter of 2013, and were analyzed gravimetrically and chemically. The Pingdingshan PM10 samples were composed of mineral matter (average of 118.0 ± 58.6 μg/m3, 20.6% of the total PM10 concentration), secondary crystalline particles (338.7 ± 122.0 μg/m3, 59.2%), organic matter (77.3 ± 48.5 μg/m3, 13.5%), and elemental carbon (38.0 ± 28.3 μg/m3, 6.6%). Different sources had different proportions of these components in PM10. The power plant pollutant source was characterized by secondary crystalline particles (377.1 μg/m3), elemental carbon (51.5 μg/m3), and organic matter (90.6 μg/m3) due to coal combustion. The mining area pollutant source was characterized by mineral matter (124.0 μg/m3) due to weathering of waste dumps. The roadside pollutant source was characterized by mineral matter (130.0 μg/m3) and organic matter (81.0 μg/m3) due to road dust and vehicle exhaust, respectively. A positive matrix factorization (PMF) analysis was performed for PM10 source apportionment to identify major anthropogenic sources of PM10 in Pingdingshan. Six factors—crustal matter, coal combustion, vehicle exhaust and abrasion, local burning, weathering of waste dumps, and industrial metal smelting—were identified and their contributions to Pingdingshan PM10 were 19.0%, 31.6%, 7.4%, 6.3%, 9.8%, and 25.9%, respectively. Compared to other major cities in China, the source of PM10 in Pingdingshan was characterized by coal combustion, weathering of waste dumps, and industrial metal smelting.
To determine the influence of regional and local sources of the fine and coarse fractions of airborne particulate matter (PM), samples were collected in 2006, 2007, 2010, and 2013 covering the 2 major seasons (wet and dry) at multiple locations in Ile-Ife, Nigeria. A total of 216 samples for each of the PM2.5 and PM2.5–10 were collected on polycarbonate filters using low volume Gent samplers. Elements and black carbon was measured using x-ray fluorescence (XRF) spectrometry and optical transmissometry, respectively. The average mass concentration for the PM2.5 and PM2.5–10 at Obafemi Awolowo University (OAU) in 2006, 2007, and 2010 exceeded the annual National Ambient Air Quality Standards (NAAQS) of 15 and 60 μg/m3 for PM2.5 and PM2.5–10, respectively. At the Obafemi Awolowo University Teaching Hospital Complex (OAUTHC) sites, the PM2.5 and PM2.5–10 mass fractions also exceeded the NAAQS standards except at the urban background site. Positive matrix factorization (PMF) was used to identify and apportion the PM sources for the combined data from these sampling sites. Four sources each were identified for both PM2.5 and PM2.5–10. The sources are soil (44%), savannah burning (26%), scrap processing (18%) and vehicular emissions (12%) for PM2.5 and soil plus biomass burning (71%), sea salt (22%), scrap processing (5%) and vehicle emissions (tire wear) (2%) for PM2.5–10. Most of the PM mass originated from anthropogenic contributions. The highest contributions were associated with northwesterly wind from the urbanized areas of Ile-Ife.