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.
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•Annual average PM10 levels in Bogota were twice as high as the WHO guidelines.•PM10 levels were maximum during the RS while the highest peaks occurred during the DS.•OM + EC was the major chemical compound of PM10 in Bogota (∼51%).•Vehicle-related emissions were the chief source of PM10 (∼50%).•Significant industrial sources of Pb and Cu were identified.
Research on chemical composition and source apportionment of PM10 in a high–altitude (2600 m above sea level) and tropical megacity during one year of sampling.
Hydrogen fluoride (HF) is one of the most toxic gaseous compounds in air, the primary anthropogenic source of which is industrial activity, specifically fertilizer and waste. HF concentrations in an ...urban area (Huelva, SW Spain) related to a nearby major phosphogypsum (PG) deposit were measured by passive sampling during summer and winter months from 2014 to 2017 and high-resolution sampling during 2017 and 2017–2018 using an HF analyser. An HF geochemical anomaly was found in the PG pond with average concentrations of up to 19.1 μg/m3, and concentrations of up to 1.6 μg/m3 were exhibited in the nearest urban area. The concentrations were associated with the HF emissions from the PG deposit. Emission factors were calculated by field and laboratory experiments, and the brines exhibited the highest emission factor (2.7 kg/ha day). Several impacts of HF (>0.1 μg/m3) in the city were recorded throughout the year, occurring at noon in the summer and during fog events in the winter. Consequently, the PG system should be restored to protect the population living in Huelva from the impacts of HF emission.
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•Several HF impacts have been recorded and associated to the PG deposit.•Impacts are more numerous in winter but more concentrated in the warm season.•PG deposit is susceptible to emit HF through its solid and liquid phases.•The emission factors of the brines, settled in 2.7 kg/ha day, is the most important.
We demonstrate that there is great variation in the size range and chemical composition of metalliferous particulate matter (PM) present within petrochemical complex chimney stacks. Cascade impactor ...PM samples from seven size ranges (17, 14, 5, 2.5, 1.3, 0.67, and 0.33
μm) were collected from inside stacks within the San Roque complex which includes the largest oil refinery in Spain. SEM analysis demonstrates the PM to be mostly carbonaceous and aluminous fly ash and abundant fine metalliferous particles. The metals with the most extreme concentrations averaged over all size ranges were Ni (up to 3295
μg
m
−3), Cr (962
μg
m
−3), V (638
μg
m
−3), Zn (225
μg
m
−3), Mo (91
μg
m
−3), La (865
μg
m
−3), and Co (94
μg
m
−3). Most metal PM are strongly concentrated into the finest fraction (<0.33
μm), although emissions from some processes, such as purified terephthallic acid (PTA) production, show coarser size ranges. The fluid catalytic cracking stack shows high concentrations of La (>200
μg
m
−3 in PM
0.67–1.3), Cr and Ni in a relatively coarse PM size range (0.7–14
μm). Our unique database, directly sampled from chimney stacks, confirms that oil refinery complexes such as San Roque are a potent source of a variety of fine, deeply inhalable metalliferous atmospheric PM emissions.
Air pollution coming from industrial activities is a matter of interest since their emissions can seriously affect to the human health of nearby populations. A more detailed study about industrial ...emissions is required in order to discriminate different activities contributing to pollutant sources. In this sense, gaseous pollutants (NO2, SO2 and O3) and PM10 levels has been studied in a complex industrial area in the southwest of Spain (La Rabida and the nearby city of Huelva) during the period 1996–2017. Hourly, daily, monthly and annual variations of PM10 and gaseous pollutants concentrations point to the industrial activity as the main SO2 source. Furthermore, traffic and resuspension emissions contribute to the NO2 and PM10 levels, respectively. Results from chemical composition of PM10 at both sites during the period 2015–2017 are characterized by high concentrations of the crustal components derived from natural and local resuspension. Arsenic is found to be the main geochemical anomaly at La Rabida (annual mean of 7 ng m−3), exceeding the European annual target of 6 ng m−3, which supposes a risk for the nearby population. An emission source from Cu-smelter has been identified in La Rabida and Huelva. A second source corresponding to emissions from polymetallic sulfides handling in a port area has been described for the first time in La Rabida. In addition, arsenic speciation results have identified three different As impacts scenarios as a function of the dominant wind direction, the SO2 episodes and the As extraction efficiency: impact of the Cu-smelter, impact of the bulk polymetallic sulfides and a mixed impact of both sources.
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•Trends of PM10 and gaseous pollutants were studied in SW Spain in a 21-year period.•High As concentrations were observed for the period 2015–2017 at the sampling site.•Cu smelter and polymetallic sulfides were identified as the As emissions sources.•As speciation analysis allowed to discriminate two industrial emission sources.
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.
Urban air quality impairment by ultrafine particles has become a matter of concern due to the adverse effects on human health. Most of the studies of ultrafine particles in urban air quality have ...focused on vehicle exhaust emissions. We studied how industrial emissions contribute to ultrafine particle concentrations in downwind urban ambient air. This research is based on experimental data collected in the ambient air of the industrial city of Huelva (SW Spain) over April 2008–December 2009 period (particle number, gaseous pollutants and black carbon concentrations and levels and chemical composition of PM10 and PM2.5 with daily and hourly resolution). This city is affected by emissions from the second largest Cu-smelter in Europe, phosphoric acid and fertilizer production plants and an oil refinery and petrochemical plant. Industrial emissions are the main cause of ultrafine particle episodes. When vehicle exhaust emissions are the main source, ultrafine particles typically show (24-h mean) concentrations within the range 14,700–5000 cm−3 (50th–1st), with 60% of these linked to this source and 30% to industrial emissions. In contrast, when daily mean levels of N are within the range 50,000–25,500 cm−3 (100th–70th), industrial and vehicle exhaust emissions accounted for 49 and 30%, respectively. High concentrations of toxic trace metals (As, Cu, Cd, Zn and Pb) were recorded when the study city suffered fumigations of the Cu-smelter plumes (e.g. 10–25 ng m−3 As, 1–2 ng m−3 Cd and >105 cm−3 of ultrafine particles). Because of these industrial emissions, ultrafine particle concentrations during daylight are about two times higher than those observed in other European cities. Recently, ultrafine particle emissions in vehicle exhausts have been subject to limit values in a recent stage of the EURO standards. Industrial emissions should also be considered.
► We studied how industrial emissions contribute to ultrafine particles (UP). ► Traffic and industrial UP episodes are identified from the relation of UP and PM2.5. ► Road traffic emissions, in the morning rush hours, are associated with OM and BC. ► Industrial plumes, during daylight, are related with heavy metals. ► Industrial emissions are the first cause of high UP in Huelva city.
The chemical evolution of brines resulting from an inactive phosphogypsum pond derived of fertilizer industry located in Huelva (Spain, SW Europe) has been studied based on a weekly sampling from ...2014 to 2017. Long-range time variation of metals and ions concentrations in brines are expected to depend on environmental parameters such as rainfall and evaporation. The results show that brines are enriched in F− (1.7–2.0 g/l), Cl− (13–24 g/l), SO42− (7.2–9.3 g/l), V (70–128 mg/l) and U (55–98 mg/l). A great variation of chemical concentrations has been found, due to dilution, recharge and evaporation processes. Most of the elements show peak concentrations in summer, coinciding with the lowest pH values (<1), high conductivity (>133 mS/cm), and high evaporation rates as expected. Nonetheless, F− shows an opposite behaviour, varying its concentrations between 0.9 g/l in summer and 3.7 g/l in the rainy season. According to the results, a future restoration plan for PG ponds should include the removal of brines and layered salts during summer in order to avoid the annual generation of brines and their impact on the environment.
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•Geochemical variations of brines depend on dilution and evaporation.•The recharge with brines generated in the PG stack produces dilution.•Highest concentrations are shown in summer, except for F−.•The removal of layered salts and brines in summer should be considered.
Despite their significant role in source apportionment analysis, studies dedicated to the identification of tracer elements of emission sources of atmospheric particulate matter based on air quality ...data are relatively scarce. The studies describing tracer elements of specific sources currently available in the literature mostly focus on emissions from traffic or large-scale combustion processes (e.g. power plants), but not on specific industrial processes. Furthermore, marker elements are not usually determined at receptor sites, but during emission. In our study, trace element concentrations in PM
10 and PM
2.5 were determined at 33 monitoring stations in Spain throughout the period 1995–2006. Industrial emissions from different forms of metallurgy (steel, stainless steel, copper, zinc), ceramic and petrochemical industries were evaluated. Results obtained at sites with no significant industrial development allowed us to define usual concentration ranges for a number of trace elements in rural and urban background environments. At industrial and traffic hotspots, average trace metal concentrations were highest, exceeding rural background levels by even one order of magnitude in the cases of Cr, Mn, Cu, Zn, As, Sn, W, V, Ni, Cs and Pb. Steel production emissions were linked to high levels of Cr, Mn, Ni, Zn, Mo, Cd, Se and Sn (and probably Pb). Copper metallurgy areas showed high levels of As, Bi, Ga and Cu. Zinc metallurgy was characterised by high levels of Zn and Cd. Glazed ceramic production areas were linked to high levels of Zn, As, Se, Zr, Cs, Tl, Li, Co and Pb. High levels of Ni and V (in association) were tracers of petrochemical plants and/or fuel-oil combustion. At one site under the influence of heavy vessel traffic these elements could be considered tracers (although not exclusively) of shipping emissions. Levels of Zn–Ba and Cu–Sb were relatively high in urban areas when compared with industrialised regions due to tyre and brake abrasion, respectively.
Metal smelting and processing are highly polluting activities that have a strong influence on the levels of heavy metals in air, soil, and crops. We employ an atmospheric transport and dispersion ...model to predict the pollution levels originated from the second largest Cu-smelter in Europe. The model predicts that the concentrations of copper (Cu), zinc (Zn), and arsenic (As) in an urban area close to the Cu-smelter can reach 170, 70, and 30ngm−3, respectively. The model captures all the observed urban pollution events, but the magnitude of the elemental concentrations is predicted to be lower than that of the observed values; ~300, ~500, and ~100ngm−3 for Cu, Zn, and As, respectively. The comparison between model and observations showed an average correlation coefficient of 0.62±0.13. The simulation shows that the transport of heavy metals reaches a peak in the afternoon over the urban area. The under-prediction in the peak is explained by the simulated stronger winds compared with monitoring data. The stronger simulated winds enhance the transport and dispersion of heavy metals to the regional area, diminishing the impact of pollution events in the urban area. This model, driven by high resolution meteorology (2km in horizontal), predicts the hourly-interval evolutions of atmospheric heavy metal pollutions in the close by urban area of industrial hotspot.
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•Atmospheric heavy metals from a large Cu-smelter were predicted by the HYSPLIT.•The high-resolution predictions were evaluated with hourly measurement data.•The model captured all the urban pollution events during two measurement campaigns.•The transport of Cu-smelter pollutants peaked during the afternoon at the urban area.•The low-resolution global HYSPLIT predictions were further constrained.
A one-year black carbon (BC) experimental study was performed at three different locations (urban traffic, urban background, rural) in Spain with different equivalent BC (eBC) source characteristics ...by means of multi-wavelength Aethalometers. The Aethalometer model was used for the source apportionment study, based on the difference in absorption spectral dependence of emissions from biomass burning (bb) and fossil fuel (ff) combustion. Most studies use a single bb and ff absorption Ångström exponent (AAE) pair (AAEbb and AAEff), however in this work we use a range of AAE values associated with fossil fuel and biomass burning based on the available measurements, which represents more properly all conditions. A sensitivity analysis of the source specific AAE was carried out to determine the most appropriate AAE values, being site dependent and seasonally variable. Here we present a methodology for the determination of the ranges of AAEbb and AAEff by evaluating the correlations between the source apportionment of eBC using the Aethalometer model with four biomass burning tracers measured at the rural site. The best combination was AAEbb = 1.63–1.74 and AAEff = 0.97–1.12. Mean eBC values (±SD) obtained during the period of study were 3.70 ± 3.73 μg m−3 at the traffic urban site, 2.33 ± 2.96 μg m−3 at the urban background location, and 2.61 ± 5.04 μg m−3 in the rural area. High contributions of eBC to the PM10 mass were found (values up to 21% in winter), but with high eBC/PM10 variability. The hourly mean eBCff and eBCbb concentrations varied from 0 to 51 μg m−3 and from 0 to 50 μg m−3 at the three sites, respectively, exhibiting distinct seasonal and daily patterns. The fossil fuel combustion was the dominant eBC source at the urban sites, while biomass burning dominated during the cold season (88% of eBCbb) in the rural area. Daily PM2.5 and PM10 samples were collected using high-volume air samplers and analyzed for OC and EC. Analysis of biomass burning tracers and organic (OC) and elemental (EC) carbon in the rural area indicate that biomass combustion is the main source, while OC and EC indicate a lower influence of this source at the urban site.
•One-year black carbon (BC) experimental study at three different locations in Spain.•Estimation of fossil fuel and biomass burning absorption Ångström exponents.•Source apportionment of black carbon from fossil fuel and biomass burning.•Dominance of fossil fuel at urban sites and biomass burning in winter at rural area.•Relationship between BC with biomass burning tracers, organic and elemental carbon.
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