Urban air pollution: a representative survey of PM2.5 mass concentrations in six Brazilian cities

In urban areas of Brazil, vehicle emissions are the principal source of fine particulate matter (PM_2.5). The World Health Organization air quality guidelines state that the annual mean concentration of PM_2.5 should be below 10 μg m⁻³. In a collaboration of Brazilian institutions, coordinated by the University of S?o Paulo School of Medicine and conducted from June 2007 to August 2008, PM_2.5 mass was monitored at sites with high traffic volumes in six Brazilian state capitals. We employed gravimetry to determine PM_2.5 mass concentrations, reflectance to quantify black carbon concentrations, X-ray fluorescence to characterize elemental composition, and ion chromatography to determine the composition and concentrations of anions and cations. Mean PM_2.5 concentrations and proportions of black carbon (BC) in the cities of S?o Paulo, Rio de Janeiro, Belo Horizonte, Curitiba, Recife, and Porto Alegre were 28.1 ± 13.6 μg m⁻³ (38% BC), 17.2 ± 11.2 μg m⁻³ (20% BC), 14.7 ± 7.7 μg m⁻³ (31% BC), 14.4 ± 9.5 μg m⁻³ (30% BC), 7.3 ± 3.1 μg m⁻³ (26% BC), and 13.4 ± 9.9 μg m⁻³ (26% BC), respectively. Sulfur and minerals (Al, Si, Ca, and Fe), derived from fuel combustion and soil resuspension, respectively, were the principal elements of the PM_2.5 mass. We discuss the long-term health effects for each metropolitan region in terms of excess mortality risk, which translates to greater health care expenditures. This information could prove useful to decision makers at local environmental agencies.     

The effect of outdoor air and indoor human activity on mass concentrations of PM(10), PM(2.5), and PM(1) in a classroom

The 12-h mass concentration of PM₁₀, PM_2.5, and PM₁ was measured in a lecturing room by means of three co-located Harvard impactors. The filters were changed at 8 AM and at 8 PM to cover the periods of presence and absence of students. Concentrations were assessed by gravimetry. Ambient PM₁₀ data were available for corresponding 12-h intervals from the nearest state air-quality-monitoring network station. The data were pooled into four periods according to the presence and absence of students—Monday-Thursday day (workday daytime), Monday-Thursday night (workday night), Friday-Sunday day (weekend daytime), and Friday-Sunday night (weekend night). Average indoor workday daytime concentrations were 42.3, 21.9 and 13.7 μg m⁻³, workday night were 20.9, 19.1 and 15.2 μg m⁻³, weekend daytime were 21.9, 18.1 and 11.4 μg m⁻³, and weekend night were 24.5, 21.3, and 15.6 μg m⁻³ for PM₁₀, PM_2.5, and PM₁, respectively. The highest 12-h mean, median, and maximum (42.3, 43.0, and 76.2 μg m⁻³, respectively) indoor concentrations were recorded on workdays during the daytime for PM₁₀. The statistically significant (r=0.68,P<0.0009) correlation between the number of students per hour per day and the indoor coarse fraction calculated as PM_10−2.5 during daytime on workdays indicates that the presence of people is an important source of coarse particles indoor. On workdays, the daytime PM₁₀ indoor/outdoor ratio was positively associated (r=0.93) with an increasing indoor coarse fraction (PM_10-2.5), also indicating that an important portion of indoor PM₁₀ had its source inside the classroom. With the exception of the calculated coarse fraction (PM_10-2.5), all of the measured indoor particulate matter fractions were significantly highly correlated with outdoor PM₁₀ and negatively correlated with wind velocity, showing that outdoor levels of particles influence their indoor concentrations.     

Air Quality Status During Diwali Festival of India: A Case Study

The PM_2.5 and PM₁₀ samples were collected during Diwali celebration from study area and characterized for ionic concentration of four anions (NO₃ ⁻, NO₂ ⁻, Cl⁻, SO₄ ²⁻) and five cations (K⁺, Mg²⁺, NH₄ ⁺, Ca²⁺, Na⁺). The results showed that the ionic concentrations were three times compared to those on pre and post Diwali days. Predominant ions for PM_2.5 were K⁺ 33.7 μg/m³, Mg⁺ 31.6 μg/m³, SO₄ ²⁻ 22.1 μg/m³, NH₄ ⁺ 17.5 μg/m³ and NO₃ ⁻ 18 μg/m³ and for PM₁₀ the ionic concentrations were Mg⁺ 29.6 μg/m³, K⁺ 26 μg/m³, SO₄ ²⁻ 19.9 μg/m³, NH₄ ⁺ 16.8 μg/m³ and NO₃ ⁻ 16 μg/m³. While concentration of SO₂ and NO₂ were 17.23, 70.33 μg/m³ respectively.     

The study of TSP and PM10 concentration and their heavy metal content in central area of Tehran, Iran

Atmospheric particulate matter may exert serious health hazards because of its chemical characteristics. The main objective of this study is to assess the concentrations of total suspended particles (TSP), particulate matter (PM) with an aerodynamic diameter ≤10 μm (PM₁₀), and air-transmitted particulate trace metals in Tehran University (a central location in Tehran, capital of Iran) ambient air, for the period of 5 months viz. February–June 2007. Furthermore, the present work examines the daily levels of fine particles in comparison with the proposed limiting values from the U.S. Environmental Protection Agency (65 μg m⁻³ for PM₁₀). The sampling for TSP and PM₁₀ was performed using a high-volume sampler. The TSP and PM₁₀ levels were determined by gravimetry and the metals by flame atomic absorption spectrometry. Arithmetic means of 151 ± 44 μg m⁻³ and 90 ± 38 μg m⁻³ were determined for TSP and PM₁₀, respectively. Comparing with EPA primary and secondary air quality standards, only PM₁₀ concentrations in 3 days were higher than the standard values. Heavy metal content of both TSP and PM₁₀, such as chromium (Cr), cadmium (Cd), and lead (Pb), were also analyzed separately during the same period using atomic absorption spectrometry. The average concentrations of heavy metal in TSP were Pb: 183.63 ± 147.81 ng m⁻³; Cr: 13.72 ± 2.40 ng m⁻³; and Cd: 6.80 ± 1.97 ng m⁻³ and for PM₁₀ were: 150.36 ± 157.01 ng m⁻³; Cr: 9.12 ± 2.14 ng m⁻³ and Cd: 6.87 ± 2.22 ng m⁻³.

Characteristics and Sources of Water-Soluble Ionic Species Associated with PM10 Particles in the Ambient Air of Central India

PM₁₀ aerosol samples were collected in Durg City, India from July 2009 to June 2010 using an Andersen aerosol sampler and analyzed for eight water-soluble ionic species, namely, Na⁺, NH₄ ⁺, K⁺, Mg²⁺, Ca²⁺, Cl⁻, NO₃ ⁻ and SO₄ ²⁻ by ion chromatography. The annual average concentration of PM₁₀ (253.5 ± 99.4 μg/m³) was four times higher than the Indian National Ambient Air Quality Standard of 60 μg/m³ prescribed by the Central Pollution Control Board, India. The three most abundant ions were SO₄ ²⁻, NO₃ ⁻, and NH₄ ⁺, with average concentrations of 8.88 ± 4.81, 5.63 ± 2.22, and 5.18 ± 1.76 μg/m³, respectively, and in turn accounting for 27.1 %, 16.5 %, and 15.5 % of the total water-soluble ions analyzed. Seasonal variation was similar for all secondary ions i.e., SO₄ ²⁻, NO₃ ⁻, and NH₄ ⁺, with high concentrations during winter and low concentrations during monsoon. Varimax Rotated Component Matrix principal component analysis identified secondary aerosols, crustal resuspension, and coal and biomass burning as common sources of PM₁₀ in Durg City, India.     

Characteristics of atmospheric trace gases, particulate matter, and heavy metal pollution in Dhaka, Bangladesh

Aerosol particulate matter (PM₁₀ and PM_2.5) and trace gases (SO₂, NO₂, CO and O₃) were sampled at five locations in greater Dhaka, Bangladesh, between January and April 2006. Particulate matter was collected on micro-fiber filters with a low-volume sampler, and trace gases (SO₂, NO₂, and O₃) were collected with an impinger equipped with PM samplers. Carbon monoxide was determined using the Indicator Tube method. The total average concentrations of SO₂, NO₂, CO, and O₃ were 48.3, 21.0, 166.0 and 28 μg m^–3, respectively. The total average concentrations of SO₂ and NO₂ were much lower than the annual average guideline values of the World Health Organization (WHO). The total average O₃ concentration was also much lower than the daily maximum values established by WHO (average of 100 μg m^–3 for an 8-h sample). The total average concentrations of five sites were 263, 75.5 and 66.2 μg m^–3 for SPM, PM₁₀ and PM_2.5, respectively. The mass of PM_2.5 is approximately 88% of the PM₁₀ mass, indicating that fossil fuel is the main source of PM in Dhaka. An atomic absorption spectrophotometer was used to determine the heavy metal concentrations in the PM_2.5 size fraction. The total average concentrations of As, Cd, Cu, Fe, Pb, and Zn in PM_2.5 were 6.3, 13, 94, 433, 204, and 381 ng m^–3, respectively. The Pb concentration in Dhaka shows a decreasing tendency, presumably due to the ban on the use of leaded fuel. The overall trace metal concentrations in Dhaka are higher than those in European (e.g., Spain, Norway) and East Asian (e.g., Taiwan) locations, but lower than those measured in Southeast Asian (Kanpur, Delhi, Mumbai, India; Lahore, Pakistan) cities.     

Measurements and Characteristics of Nitrogen-Containing Compounds in Atmospheric Particulate Matter in Beijing, China

The total nitrogen (TN) and water-soluble nitrogenous ions were determined by using CHN Elemental Analyzer and ion chromatography method, respectively, from November 24, 1998 to February 12, 1999 in Beijing. The average concentrations of TN, NH₄ ⁺ and NO₃ ⁻ were 10.62 μg N m⁻³, 6.67 μg m⁻³ and 10.01 μg m⁻³, respectively. The total inorganic nitrogen (IN) calculated from NH₄ ⁺ and NO₃ ⁻ was 7.45 μg N m⁻³, accounting for 70% of TN, i.e., 30% of TN existed as organic nitrogen form (ON). The correlation between ON and other pollution tracers showed that, coal combustion, biomass burning, soil humic matter and secondary formation were the important sources of ON in particulate matter in Beijing.     

Particle Size Distribution of Ambient Aerosols in an Industrial Area

Aerosol samples of PM₁₀ and PM_2.5 were collected from 38 sampling locations in and around the industrial area. The 24 h average mass concentration of PM₁₀ and PM_2.5 was 137.5 and 61.5 μg/m³ respectively during summer, 122 and 97.5 μg/m³ respectively in winter and 70 and 54 μg/m³ respectively during post monsoon season. The relative contribution of coarse, fine and ultrafine particle to ambient air was analyzed for its temporal and seasonal variability in an industrialized area. This paper aims to establish baseline between PM₁₀ and PM_2.5 mass concentration levels.     

Concentrations and Source Assessment of Some Atmospheric Trace Elements in Northwestern Region of Tehran, Iran

Outdoor concentrations of some elements such as iron, aluminum, magnesium, titanium, copper, zinc, lead, manganese, sulfur, chromium and arsenic in PM₁₀ and PM_2.5, was evaluated at four points in north-western part of Tehran in winter 2007. The total concentration of the elements in PM₁₀ and PM_2.5 at the north Karegar avenue found to be as high as 82.05 and 60.64 μg/m³, respectively, while at the Arjantin square it was measured to be 34.30 and 28.03 μg/m³. The emission sources of the trace elements were attributed to the adjoining local industries in the west parts of Tehran.     

Mass size distribution and chemical composition of the surface layer of summer and winter airborne particles in Zabrze, Poland

Mass size distributions of ambient aerosol were measured in Zabrze, a heavily industrialized city of Poland, during a summer and a winter season. The chemical analyses of the surface layer of PM₁₀, PM_2.5 and PM₁ in this area were also performed by X-ray photoelectron spectroscopy (XPS). Results suggested that the influence of an atmospheric aerosol on the health condition of Zabrze residents can be distinctly stronger in winter than in summer because of both: higher concentration level of particulate matter (PM) and higher contribution of fine particles in winter season compared to summer. In Zabrze in June (summer) PM₁₀ and PM_2.5 reached about 20 and 14 μg/m³, respectively, while in December (winter) 57 and 51 μg/m³, respectively. The XPS analysis showed that elemental carbon is the major surface component of studied airborne particles representing about 78%–80% (atomic mass) of all detected elements.     

Measurement and modeling of respirable particulate (PM10) and lead pollution over Madurai, India

Samples of particulate matter less than or equal to 10 μm (PM₁₀) were collected round the clock duration by using a respirable dust sampler (APM 460 BL) in Madurai, the second largest and most densely populated city of Tamil Nadu, India. The Environmental Protection Agency (EPA)-recommended standard methods were adopted not only for sample collection but also for subsequent analysis of respirable particulate pollutants. The observed PM₁₀ concentrations varied from 88.1 to 226.9 μg/m³, and lead concentrations ranged between 0.21 to 1.18 μg/m³. The annual averages of the concentrations of the pollutants of current concern manifested that they were mostly below the Indian air quality standards and were generally comparable with those concentrations observed in most other Indian urban areas. The AERMOD model was validated simultaneously by comparing the predicted levels with the estimated levels of PM₁₀. The generated database of the present investigation on the degree of pollution may be used for further research investigation and pollution abatement in the city.     

Airborne particulate matter (PM2.5 and PM10) and associated metals in urban Turkey

Airborne particulate matter (PM) and associated metals were measured in a district of an industrial city in Western Turkey. We compared PM concentrations in Bursa, Turkey (Nilufer district) with international air quality standards. Turkish legislature adopted the EC Air Quality Framework in 2008, and compliance is required in the medium term. State-of-the-art reference methods were used for all measurements. A Partisol sampler measured urban background PM_2.5 and PM₁₀ between May 2007 and April 2008, and PM_2.5 samples were later analysed for selected metals using ICP-MS. Average PM_2.5 and PM₁₀ mass concentrations over the year were 53 and 83 μg/m³, respectively. The annual mean PM_2.5:PM₁₀ ratio in Bursa was 0.64. PM_2.5 and PM₁₀ were highly correlated at the site (R?=?0.91 overall), especially in winter. In the cold seasons, the coarse and fine fractions were strongly correlated R?=?0.67 (p?<?0.1), while in the warm seasons, they were not (R?=?0.01). Sampler results correlated well with a nearby Government sampler. Current PM₁₀ and PM_2.5 levels in Bursa breach current and prospective EU air quality standards, with significant implications in public health.     

Acidic Anions in PM<Subscript>10</Subscript> Particle Fraction in Zagreb Air,Croatia

This paper presents the results of 7 years continuous measurement of acidic anions chlorides, nitrates, and sulphates in PM₁₀ particle fraction in the city of Zagreb, Croatia. The mean annual mass concentrations of the investigated anions in PM₁₀ particle fraction varied from 0.28 to 0.95 μg/m³ for chlorides, from 3.21 to 7.87 μg/m³ for nitrates and from 3.98 to 9.71 μg/m³ for sulphates. The concentration levels of all measured anions showed significant seasonal differences. The most contributing to the PM₁₀ mass were sulphates, then nitrates, and then chlorides. The mobile source emission was an important contributor to particle mass.     

Source identification of different size fraction of PM10 using factor analysis at residential cum commercial area of Nagpur city

Particulate size distribution of PM₁₀ and associated trace metal concentrations has been carried out in residential cum commercial area of Mahal at Nagpur city. Sampling for size fraction of particulate matter was performed during winter season using eight-stage cascade impactor with a pre-separator and toxic metals were analyzed using inductively coupled plasma-optical emission spectroscopy (ICP-OES). The average concentration of PM₁₀ and fine particulate matter (effective cut of aerodynamic diameter ≤2.2 μm) was found to be 300 and 136.7 μg/m³, respectively which was exceeding limit of Central Pollution Control Board. Maximum mass concentration of 41 μg/m³ in size range of 9.0–10.0 μm and minimum mass concentration of 19 μg/m³ in size range 2.2–3.3 μm was observed. Metals (Sr, Ni and Zn) were found to large proportions in below 0.7 μm particle size and could therefore pass directly into the alveoli region of human respiratory system. Factor analysis results indicated combustion and vehicular emission as the dominant source in fine mode and resuspended dust was dominant in medium mode while crustal along with vehicular source was major in coarse mode of particulate matter.     

Seasonal trends of PM2.5 and PM10 in ambient air and their correlation in ambient air of Lucknow city, India

The PM₁₀ concentration (μg/m³) in Lucknow city at 4 locations in three different seasons ranged between 148.6–210.8 (avg. 187.2 ± 17.1) during summer, 111.8–187.6 (avg. 155.7 ± 22.7) during monsoon and 199.3–308.8 (avg. 269.3 ± 42.9) during winter while PM_2.5 ranged between 32.4–67.2 (avg. 45.6 ± 10.9), 25.6–68.9 (avg. 39.8 ± 4.6) and 99.3–299.3 (avg. 212.4 ± 55.0) during respective seasons. The mass fraction ratio of PM_2.5 ranged between 0.22–0.92 (avg. 0.42 ± 0.26) and was significantly high during winter season indicating their composition.     

Carbonaceous Species of PM<Subscript>2.5</Subscript> in Megacity Delhi,India During 2012–2016

Organic carbon (OC) and elemental carbon (EC) in PM_2.5 were estimated to study the seasonal and inter-annual variability of atmospheric total carbonaceous aerosols (TCA) at an urban site of megacity Delhi, India for 5 years from January, 2012 to December, 2016. The annual average (±?standard deviation) concentrations of PM_2.5, OC, EC and TCA were 128?±?81, 16.6?±?12.2, 8.4?±?5.8 and 34.5?±?25.2 µg m^?3, respectively. During the study, significant seasonal variations in mass concentrations of PM_2.5, OC, EC and TCA were observed with maxima in winter and minima in monsoon seasons. Significant correlations between OC and EC, and OC/EC ratio suggested that vehicular emissions, fossil fuel combustion and biomass burning could be major sources of carbonaceous aerosols of PM_2.5 at the sampling site of Delhi, India.     

Monitoring of long-term personal exposure to fine particulate matter (PM<Subscript>2.5</Subscript>)

Personal monitoring is of a demanding nature; thus, it is very difficult to obtain personal data for periods longer than a few days or a maximum of a few weeks. To fill this gap, we have performed a study in which personal exposure to particulate matter of aerodynamic diameter under 2.5 μm (PM_2.5) was monitored for almost 1 year. One healthy, adult, non-smoking, female student living in Prague (Czech Republic) was involved in the study. A battery-operated, fast-responding nephelometer was worn by the individual for a period of 10 months, recording PM_2.5 concentration every 5 min. A written time activity diary was used to record the experimental person's movement and the microenvironments visited. The dataset was divided into 12 different (seven indoor and four outdoor and transit) microenvironments. The overall average of the year-long measurement was 14.9 ± 52.5 μg.m⁻³ (median, 8.0 μg.m⁻³). The highest PM_2.5 average concentration was detected in restaurant microenvironments (294.4 μg.m⁻³), while the second highest concentration was recorded in an indoor microenvironment heated by wood and coal stoves (112.2 μg.m⁻³). The lowest mean aerosol concentrations were detected outdoors in a rural/natural environment (7.0 μg.m⁻³) and indoors at the monitored person's home (9.3 μg.m⁻³). During the measurement period, isolated and brief, but very high concentration excursions over 500 μg.m⁻³ or even over 1,000 μg.m⁻³ were recorded. However, they accounted for less than 0.5% of the total time of personal exposure. We conclude that continuous long-term monitoring is a good tool capable of disclosing the frequency and severity of short-term peak events of high particulate concentrations, which may be associated with adverse health effects.     

Research on Florfenicol Residue in Coastal Area of Dalian (Northern China) and Analysis of Functional Diversity of the Microbial Community in Marine Sediment

An analytical method based on high performance liquid chromatography tandem mass spectrometry (HPLC–MS/MS) has been developed to investigate florfenicol residues. Among 11 stations, florfenicol was detected in six water samples. The concentrations of florfenicol in the six samples were 64.2 μg L⁻¹, 390.6 μg L⁻¹, 1.1 × 10⁴ μg L⁻¹, 29.8 μg L⁻¹, 61.6 μg L⁻¹, 34.9 μg L⁻¹, respectively. These results showed that high levels of florfenicol were observed in water samples collected from stations influenced by aquaculture discharges. However, no florfenicol residue was detected in the sediment samples. Furthermore, the functional diversities of microbial community in four marine sediment samples were analyzed by Biolog microplate. For the sediment samples from the stations where antibacterials had been used, the functional diversity of microbial community was much lower than those from the stations where antibacterials were not used.     

Differential oxidative stress response in young children and the elderly following exposure to PM2.5

Objectives  The mechanism of the adverse health effects of ambient particulate matter on humans has not been well-investigated despite many epidemiologic association studies. Measurement of personal exposure to particulate pollutants and relevant biological effect markers are necessary in order to investigate the mechanism of adverse health effects, particularly in fragile populations considered to be more susceptible to the effects of pollutants. Methods  We measured personal exposure to PM_2.5 and examined oxidative stress using urinary malondialdehyde three times in 51 preschoolers and 38 elderly subjects. A linear mixed-effects model was used to estimate PM_2.5 effects on urinary MDA levels. Results  Average personal exposure of the children and elderly to PM_2.5 was 80.5 ± 29.9 and 20.7 ± 12.7 μg/m³, respectively. Mean urinary MDA level in the children and the elderly was 3.6 ± 1.9 and 4.0 ± 1.6 μmol/g creatinine. For elderly subjects the PM_2.5 level was significantly associated with urinary MDA after adjusting for age, sex, BMI, passive smoking, day-care facility site, alcohol consumption, cigarette smoking, and medical history (heart disease, hypertension and bronchial asthma). However, there was no significant relationship for children. Conclusions  The elderly were more susceptible than young children to oxidative stress as a result of ambient exposure to PM_2.5. Identification of oxidative stress induced by PM_2.5 explains the mechanism of adverse health effects such as cardiovascular or respiratory diseases, particularly in the elderly.     

Vehicle emissions and PM2.5 mass concentrations in six Brazilian cities

In Brazil, the principal source of air pollution is the combustion of fuels (ethanol, gasohol, and diesel). In this study, we quantify the contributions that vehicle emissions make to the urban fine particulate matter (PM_2.5) mass in six state capitals in Brazil, collecting data for use in a larger project evaluating the impact of air pollution on human health. From winter 2007 to winter 2008, we collected 24-h PM_2.5 samples, employing gravimetry to determine PM_2.5 mass concentrations; reflectance to quantify black carbon concentrations; X-ray fluorescence to characterize elemental composition; and ion chromatography to determine the composition and concentrations of anions and cations. Mean PM_2.5 concentrations in the cities of S?o Paulo, Rio de Janeiro, Belo Horizonte, Curitiba, Porto Alegre, and Recife were 28, 17.2, 14.7, 14.4, 13.4, and 7.3 μg/m³, respectively. In S?o Paulo and Rio de Janeiro, black carbon explained approximately 30% of the PM_2.5 mass. We used receptor models to identify distinct source-related PM_2.5 fractions and correlate those fractions with daily mortality rates. Using specific rotation factor analysis, we identified the following principal contributing factors: soil and crustal material; vehicle emissions and biomass burning (black carbon factor); and fuel oil combustion in industries (sulfur factor). In all six cities, vehicle emissions explained at least 40% of the PM_2.5 mass. Elemental composition determination with receptor modeling proved an adequate strategy to identify air pollution sources and to evaluate their short- and long-term effects on human health. Our data could inform decisions regarding environmental policies vis-à-vis health care costs.