Coarse and fine particulates, Hg(p)-bound particulate concentrations and compositions study at Sha-Lu, central Taiwan

Ambient air and coarse, fine and particulate-bound mercury (Hg(p)) pollutants were collected and analyzed from March 17 to May 22 and September 3, 2009 to March 5, 2010 at a highway traffic site located in Sha-Lu, central Taiwan. This study has the following objectives: (1) to measure the coarse and fine particulates concentrations and the particulate-bound mercury Hg(p) which was attached to these particulate; (2) to determine the average Hg(p) compositions in coarse and fine particulates and (3) to compare the Hg(p) concentrations and compositions particulate in this study to the those obtained in other studies. The results obtained in this study indicated that the average ambient air PM_2.5, PM_2.5–10 and PM₁₀ were 18.79 ± 6.71, 11.22 ± 4.93 and 30.01 ± 10.27 μg/m³, respectively. The ranges of concentrations for Hg(p) in PM_2.5 were from 0.0016 to 0.0557 ng/m³, from 0.0006 to 0.0364 ng/m³ in PM_2.5–10 and from 0.0022 to 0.0862 ng/m³ in PM₁₀. In addition, the highest particle-bound mercury compositions in PM_2.5 were 16.85 ng/g and the lowest particle-bound mercury concentrations were 0.55 ng/g. The highest particle-bound mercury compositions in PM_2.5–10 were 13.88 ng/g and the lowest particle-bound mercury in PM_2.5–10 were 0.22 ng/g.     

Spatio-temporal variations of respirable particles at residential areas located in the vicinity of opencast coal projects,India: a case study

The objective of the study is to investigate spatio-temporal variations of PM₁₀, PM_2.5, and PM₁ concentrations at seven residential sites, located in the vicinity of opencast coal projects, Basundhara Garjanbahal Area (BGA), India. Meteorological parameters such as wind speed, wind direction, relative humidity, and temperature were collected simultaneously with PM concentrations. Mean concentrations of PM₁₀ in the range 215 ± 169–526 ± 412 μg m^?3, PM_2.5 in the range of 91 ± 79–297 ± 107 μg m^?3, PM₁ in the range of 68 ± 60–247 ± 84 μg m^?3 were obtained. Coarse fractions (PM_2.5–10) varied from 27 to 58% whereas fine fractions (PM_1–2.5 and PM₁) varied in the range of 51–73%. PM_2.5 concentration was 41–74% of PM₁₀ concentration, PM₁ concentration was 31–62% of PM₁₀ concentration, and PM₁ concentration was 73–83% of PM_2.5 concentration. Role of meteorology on PM concentrations was assessed using correlation analysis. Linear relationships were established among PM concentrations using least square regression analysis. With the aid of principal component analysis, two components were drawn out of eight variables, which represent more than 75% of variance. The results indicated that major sources of air pollutants (PM₁₀, PM_2.5, PM₁, CO, CO₂) at the residential sites are road dust raised by vehicular movement, spillage of coal generated during transportation, spontaneous combustion of coal, and biomass burning in village area.     

Geochemical features of aerosols in Santiago de Chile from time series analysis

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 (PM_2.5 and PM_10–2.5) 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 PM_2.5 (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.     

A new method for measurement of air change rate based on indoor PM<Subscript>2.5</Subscript> removal

Outdoor PM_2.5 easily flows into indoor and seriously influences indoor air quality due to its characteristics of flow, diffusion and penetration. It is a proper ‘gas’ tracer similar to CO₂ to study building ventilation. Therefore, in this paper, a model for calculating air change rates by removing indoor PM_2.5 was deduced. Also, some factors influencing the air change rate were qualitatively analyzed and the expression of possible air change rate error was given. The comparison between the results from PM_2.5 removal method and the data from CO₂ decay method validated the model. The relative error between the results of the two methods is less than 10%. On the basis of validating the model, this paper presented the research of air change rates in ten naturally ventilated house rooms in three Chinese cities. It is found that the rooms with the ventilation rates of 1.15–6.75 m³/h/person have inadequate ventilation.     

Assessment of air quality during 19th Common Wealth Games at Delhi, India

The 19th Common Wealth Games was organized at Delhi, India, during October 3 to 14, 2010, where more than 8,000 athletes from 71 Commonwealth Nations have participated. In order to give them better environment information for proper preparedness, mass concentrations of particulate matters below 10 microns (PM₁₀) and 2.5 microns (PM_2.5), black carbon (BC) particles and gaseous pollutants such as carbon monoxide (CO) and nitrogen oxide (NO) were monitored and displayed online for ten different locations around Delhi, including inside and outside the stadiums. This extensive information system for air quality has been set up for the period from September 24 to October 21, 2010, and data have been archived at 5-min interval for further research. During the study period, average concentration of PM₁₀ and PM_2.5 was observed to be 229.7 ± 85.5 and 112.1 ± 56.0 μg m^?3, respectively, which is far in excess of the corresponding annual averages, stipulated by the national ambient air quality standards. Significant large and positive correlation (r = 0.93) between PM₁₀ and PM_2.5 implies that variations in PM₁₀ mass are governed by the variations in PM_2.5 mass. The mass concentrations of PM_2.5 inside the stadium were found to be ~18 % lower than those outside; however, no large variations were observed in PM₁₀. Mean concentrations of BC, CO and NO for the observation period were 10.9 μg m^?3 (Min, 02 μg m^?3; Max, 31 μg m^?3), 1.83 ± 0.89 ppm (Min, 0.48 ppm; Max, 4.55 ppm) and 37.82 ppb (Min, 2.4 ppb; Max, 206.05 ppb), respectively. BC showed positive correlation (r = 0.73) with CO suggests unified source for both of them, mainly from combustion emissions. All the measured parameters, however, show a significant diurnal variation with enhanced peaks in the morning and late night hours and lower values during daytime.     

Mass-size distribution of PM10 and its characterization of ionic species in fine (PM2.5) and coarse (PM10−2.5) mode, New Delhi, India

Size distribution of PM₁₀ mass aerosols and its ionic characteristics were studied for 2 years from January 2006 to December 2007 at central Delhi by employing an 8-stage Andersen Cascade Impactor sampler. The mass of fine (PM_2.5) and coarse (PM_10?2.5) mode particles were integrated from particle mass determined in different stages. Average concentrations of mass PM₁₀ and PM_2.5 were observed to be 306 ± 182 and 136 ± 84 μg m^?3, respectively, which are far in excess of annual averages stipulated by the Indian National Ambient Air Quality Standards (PM₁₀: 60 μg m^?3 and PM_2.5: 40 μg m^?3). The highest concentrations of PM_10?2.5 (coarse) and PM_2.5 (fine) were observed 505 ± 44 and 368 ± 61 μg m^?3, respectively, during summer (June 2006) period, whereas the lower concentrations of PM_10?2.5 (35 ± 9 μg m^?3) and PM_2.5 (29 ± 13 μg m^?3) were observed during monsoon (September 2007). In summer, because of frequent dust storms, coarse particles are more dominant than fine particles during study period. However, during winter, the PM_2.5 contribution became more pronounced as compared to summer probably due to enhanced emissions from anthropogenic activities, burning of biofuels/biomass and other human activities. A high ratio (0.58) of PM_2.5/PM₁₀ was observed during winter and low (0.24) during monsoon. A strong correlation between PM₁₀ and PM_2.5 (r ² = 0.93) was observed, indicating that variation in PM₁₀ mass is governed by the variation in PM_2.5. Major cations (NH₄ ⁺, Na⁺, K⁺, Ca²⁺ and Mg²⁺) and anions (F^?, Cl^?, SO₄ ^2? and NO₃ ^?) were analyzed along with pH. Average concentrations of SO₄ ^2? and NO₃ ^? were observed to be 12.93 ± 0.98 and 10.33 ± 1.10 μg m^?3, respectively. Significant correlation between SO₄ ^2? and NO₃ ^? in PM_1.0 was observed indicating the major sources of secondary aerosol which may be from thermal power plants located in the southeast and incomplete combustion by vehicular exhaust. A good correlation among secondary species (NH⁺, NO₃ ^? and SO₄ ^2?) suggests that most of NH₄ ⁺ is in the form of ammonium sulfate and ammonium nitrate in the atmosphere. During winter, the concentration of Ca²⁺ was also higher; it may be due to entrainment of roadside dust particles, traffic activities and low temperature. The molar ratio (1.39) between Cl^? and Na⁺ was observed to be close to that of seawater (1.16). The presence of higher Cl^? during winter is due to western disturbances and probably local emission of Cl^? due to fabric bleaching activity in a number of export garment factories in the proximity of the sampling site.     

Chemical characterization and sources of PM2.5 at 12-h resolution in Guiyang,China

The increasing emission of primary and gaseous precursors of secondarily formed atmospheric particulate matter due to continuing industrial development and urbanization are leading to an increased public awareness of environmental issues and human health risks in China. As part of a pilot study, 12-h integrated fine fraction particulate matter (PM_2.5) filter samples were collected to chemically characterize and investigate the sources of ambient particulate matter in Guiyang City, Guizhou Province, southwestern China. Results showed that the 12-h integrated PM_2.5 concentrations exhibited a daytime average of 51 ± 22 µg m^?3 (mean ± standard deviation) with a range of 17–128 µg m^?3 and a nighttime average of 55 ± 32 µg m^?3 with a range of 4–186 µg m^?3. The 24-h integrated PM_2.5 concentrations varied from 15 to 157 µg m^?3, with a mean value of 53 ± 25 µg m^?3, which exceeded the 24-h PM_2.5 standard of 35 µg m^?3 set by USEPA, but was below the standard of 75 µg m^?3, set by China Ministry of Environmental Protection. Energy-dispersive X-ray fluorescence spectrometry (XRF) was applied to determine PM_2.5 chemical element concentrations. The order of concentrations of heavy metals in PM_2.5 were iron (Fe) > zinc (Zn) > manganese (Mn) > lead (Pb) > arsenic (As) > chromium (Cr). The total concentration of 18 chemical elements was 13 ± 2 µg m^?3, accounting for 25% in PM_2.5, which is comparable to other major cities in China, but much higher than cities outside of China.     

The characteristics of air pollutants during different seasons in the urban area of Lanzhou,Northwest China

Based on data from ground-based air quality stations, space–time variations of six principal atmospheric pollutants, such as particulate matter (PM_2.5 and PM₁₀) and gas pollutants (SO₂, NO₂, СО, and O₃), obtained from January 1, 2014 to December 31, 2017 in the city of Lanzhou, have been studied. Average total concentrations of PM_2.5 and PM₁₀ were 53.2?±?26.91 and 124.54?±?82.33 µg/m³, respectively; however, the results showed that in 75.53% and 84.85% days, concentrations of these pollutants exceeded Chinese National Ambient Air Quality Standard and in 100% days exceeded World Health Organization guidelines standards. Daily mean values of aerosol optical depth and Ångström exponent based on data, received by satellite Moderate Resolution Imaging Spectroradiometer, show a broad range of values for aerosol optical depth (from 0.018 to 1.954) and Ångström exponent (from 0.003 to 1.8). Results of principal components analysis revealed three factor loadings. Thus, Factor 1 has the relevant loadings for PM_2.5, PM₁₀, CO, SO₂, and NO₂ (36%) and closely associated with transport emissions and industrial sources, which contribute to air pollution in Lanzhou. Factor 2 was heavily loaded with temperature and visibility (16.94%). Factor 3 consisted of relative humidity (14.11%). Cluster analysis revealed four subgroups: cluster 1 (PM_2.5, NO₂, SO₂), cluster 2 (CO), cluster 3 (PM₁₀) and cluster 4 (relative humidity, visibility, temperature, O₃, wind speed), which were compliant with results, obtained from principal components analysis. Positive correlation was found among all pollutants, other than O₃. According to processed backward trajectories obtained by Hybrid Single-Particle Lagrangian Integrated Trajectory model, it was found that movement of air masses occur from north, northwest, and west directions—the location of principal natural sources of aerosols.     

The effects of Typhoon Morakot on concentration of airborne particulates derived from unvegetated riverbanks

Landslides frequently occur during large earthquakes and storms in Taiwan, supplying large volumes of sediment to downslope areas. When coupled with the intense northeast monsoon over Taiwan in the dry winter season, this can lead to high concentrations of airborne particulates that are hazardous to human health. Air quality monitoring stations near unvegetated riverbanks recorded high concentrations of particulate matter less than 10 μm (PM₁₀) after Typhoon Morakot in 2009. The objective of this study was, therefore, to analyze the effects on air quality of sediment caused by the typhoon. A deflation module was simulated, and the resulting estimates were compared with observed data from the Taitung monitoring station for 2004 and 2005. The relationship of dust flux to average atmospheric dust concentration was analyzed for October to December 2001–2010. Analysis showed that the 2001–2008 data are highly correlated (0.78) with the average concentration. The intercept of 28.07 represented the background concentration with no dust emission, from October to December of 2001–2008. Based on the dust flux potential in 2009, the average yearly PM₁₀ concentration would be 37.98 µg/m³; however, the measured concentration was 61.67 µg/m³ from October to December. This suggests the strong influence of dust re-suspended from unvegetated riverbanks by Typhoon Morakot.     

Assessment of carbonaceous aerosol over Delhi in the Indo-Gangetic Basin: characterization, sources and temporal variability

Semi-continuous measurements of organic carbon (OC) and elemental carbon (EC) and continuous measurements of black carbon (BC) and PM_2.5 aerosols were conducted simultaneously during the winter period of 2010–2011 at Delhi, one of the polluted urban megacities in western part of the Indo-Gangetic Basin region. The average mass concentrations of OC, EC, BC and PM_2.5 were about 54 ± 39, 10 ± 5, 12 ± 5 and 210 ± 146 μg m^?3, respectively. Contribution of total carbonaceous aerosol mass to PM_2.5 mass was found to be ~46 %. Average OC/EC ratio was found to be 5 ± 2 during the study period, suggesting the presence of secondary organic aerosols in the atmosphere over Delhi. Estimated mean secondary organic aerosol mass concentration was found to be 25 μg m^?3 and varied between 14.6 (February) and 37.0 μg m^?3 (December). A diurnal variation of OC and EC shows lower values during the day time and higher during the morning and night, which are highly associated with the corresponding variability in mixing layer heights. OC and EC were also found to be significantly correlated (r = 0.71) to each other, indicating their common sources. Concentrations of OC and EC were about 45 and 13 % higher during weekdays than weekends, respectively. Higher OC (67 %) and EC (53 %) were observed in the late evening during weekdays than those on weekends, which could be due to different emission sources during these two periods. The night/day ratio of EC and OC was found to be larger than 1.0, suggesting the relative accumulation of EC and OC near the surface at night hours.     

Radon distributions in the Hail Region of Northern Saudi Arabia

Indoor radon measurements were carried out in a total of 420 dwellings and 17 schools in Hail region of Saudi Arabia, using NTDs based radon dosimeters. The duration of the measurements was one year, from April 2008 to April 2009. The indoor radon concentrations varied from 4 to 513 Bq/m³ with an overall average of 45 Bq/m³ for all surveyed dwellings. These passive measurements were confirmed by the active measurements. The anomalous concentrations above 200 Bq/m³ were observed in 13 dwellings, representing 3.1 % of the total surveyed dwellings. In Inbowan village alone, it was found that 7.6 % of the dwellings have indoor radon concentration above 200 Bq/m³. The highest average indoor radon concentration of 64 Bq/m³ was found in Inbowan village while the lowest average of 24 Bq/m³ was found in Majasah village. The city of Hail showed an average indoor radon concentration of 49 Bq/m³. The average indoor radon concentration in one area located at the edge of the Aja Mountain in Hail city was 111 Bq/m³. The elevated indoor radon concentrations in many dwellings in the Hail region, prompted us to measure outdoor ground radon in such locations using gas monitor. It was found that radon concentrations at a depth of 0.5 m varied significantly from place to place ranging from 1.2 to 177 kBq/m³. The outdoor radon concentrations are generally correlated with the indoor radon measurements. Radon exhalations from construction materials and soil samples from the Hail region were also measured. It was found that radon exhalations from soil samples are higher than that of construction materials by a factor of at least 3 and reaching up to 11. These results indicate that soil is the main source of indoor radon. Geological interpretations of the results are also given.     

High resolution aerosol data from MODIS satellite for urban air quality studies

The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not suitable for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM_2.5 as measured by the 27 EPA ground monitoring stations was investigated. These results were also compared to conventional MODIS 10 km AOD retrievals (MOD04) for the same days and locations. The coefficients of determination for MOD04 and for MAIAC are R² =0.45 and 0.50 respectively, suggested that AOD is a reasonably good proxy for PM_2.5 ground concentrations. Finally, we studied the relationship between PM_2.5 and AOD at the intra-urban scale (?10 km) in Boston. The fine resolution results indicated spatial variability in particle concentration at a sub-10 kilometer scale. A local analysis for the Boston area showed that the AOD-PM_2.5 relationship does not depend on relative humidity and air temperatures below ～7 °C. The correlation improves for temperatures above 7–16 °C. We found no dependence on the boundary layer height except when the former was in the range 250–500 m. Finally, we apply a mixed effects model approach to MAIAC aerosol optical depth (AOD) retrievals from MODIS to predict PM_2.5 concentrations within the greater Boston area. With this approach we can control for the inherent day-to-day variability in the AOD-PM_2.5 relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance. Our results show that the model-predicted PM_2.5 mass concentrations are highly correlated with the actual observations (out-of-sample R² of 0.86). Therefore, adjustment for the daily variability in the AOD-PM_2.5 relationship provides a means for obtaining spatially-resolved PM_2.5 concentrations.     

Levels, seasonal variations, and health risks assessment of ambient air pollutants in the residential areas

People living in the urban area and the surrounding suburban area have disparities in exposure and health risks due to different levels of ambient air pollutants. The main objective of this study is to investigate the concentrations, seasonal variations, and related health risks of ambient air pollutants (PM₁₀, NO₂, and SO₂) in urban and suburban areas of Ningbo, China. The results showed that the average PM₁₀, NO₂, and SO₂ concentrations in the urban area were 85.2, 49.3, and 37.4 μg/m³, which were 1.13, 1.25, and 1.41 times the values of the suburban area during the period of March 2009 to February 2010. For the potential health risk analysis, the residents have been divided into four age categories namely, infants, children (1 year), children (8–10 years), and adults. The analysis took into account age-specific breathing rates, body weights for different age categories. The results showed that the potential health risks to respiratory disease for all age categories living in urban area were higher than those in suburban area.     

Spatial heterogeneity in near surface aerosol characteristics across the Brahmaputra valley

In order to examine the spatial variability of the aerosol characteristics across the Brahmaputra valley, a land campaign was conducted during late winter (February 3–March 2) 2011. Measurements of particulate matter (PM, PM₁₀, PM_2.5) and black carbon (BC) concentrations were made onboard an interior redesigned vehicle. The length of the campaign trail stretched about 700 km, covering the longitude belt of 89.97°–95.55°E and latitude belt of 26.1°–27.6°N, comprising 13 measurement locations. The valley is divided into three sectors longitudinally: western sector (R1: 89.97°–91.75°E), middle sector (R2: 92.5°–94.01°E) and eastern sector (R3: 94.63°–95.55°E). Spatial heterogeneity in aerosol distribution has been observed with higher PM₁₀ and PM_2.5 concentrations at the western and middle sectors compared to the eastern sector. The locations in the western sector are found to be rich in BC compared to the other two sectors and there is a gradual decrease in BC concentrations from west to east of the Brahmaputra valley. Two hotspots within the western and middle sectors with high PM and BC concentrations have been identified. The associated physico-optical parameters of PM reveal abundance of PM_2.5 aerosols along the entire valley. High population density in the western and middle sectors, together with the contribution of remote aerosols, leads to higher anthropogenic aerosols over those regions. Spectral Radiation-Transport Model for Aerosol Species (SPRINTARS) slightly underestimates the measured PM₁₀ and PM_2.5 at the eastern sector while the model overestimates the measurements at a number of locations in the western sector. In general, BC is underestimated by the model. The variation of BC within the campaign trail has not been adequately captured by the model leading to higher variance in the western locations as compared to the middle and eastern locations.     

A study of PM<Subscript>2.5</Subscript> and PM<Subscript>10</Subscript> concentrations in the atmosphere of large cities in Gansu Province,China, in summer period

Due to rapid economic growth of the country in the last 25 years, particulate matter (PM) has become a topic of great interest in China. The rapid development of industry has led to an increase in the haze created by pollution, as well as by high levels of urbanization. In 2012, the Chinese National Ambient Air Quality Standard (NAAQS) imposed ‘more strict’ regulation on the PM concentrations, i.e., 35 and 70 μg/m³ for annual PM_2.5 and PM₁₀ in average, respectively (Grade-II, GB3095-2012). The Pearson’s correlation coefficient was used to determine the linear relationship of pollution between pollution levels and weather conditions as well as the temporal and spatial variability among neighbouring cities. The goal of this paper was to investigate hourly mass concentration of PM_2.5 and PM₁₀ from June 1 to August 31, 2015 collected in the 11 largest cities of Gansu Province. This study has shown that the overall average concentrations of PM_2.5 and PM₁₀ in the study area were 26 and 66 μg/m³. In PM_2.5 episode days (when concentration was more than 75 μg/m³ for 24 hrs), the average concentrations of PM_2.5 was 2–3 times higher as compared to non-episode days. There were no observed clear differences during the weekday/weekend PM and other air pollutants (SO₂, NO₂, CO and O₃) in all the investigated cities.     

Development of the models to estimate particulate matter from thermal infrared band of Landsat Enhanced Thematic Mapper

Particulate matter concentration and assessment of its movement pattern is crucial in air pollution studies. However, no study has been conducted to determine the PM₁₀ concentration using atmospheric correction of thermal band by temperature of nearest dark pixels group (TNDPG) of this band. For that purpose, 16 Landsat Enhanced Thematic Mapper plus ETM+ images for Sanandaj and Tehran in Iran were utilized to determine the amount of PM₁₀ concentration in the air. Thermal infrared (band 6) of all images was also used to determine the ground station temperature (GST b6) and temperature of nearest dark pixels group. Based on atmospheric correction of images using temperature retrieval from Landsat ETM+, three empirical models were established. Non-linear correlation coefficient with polynomial equation was used to analyze the correlations between particulate matter concentration and the ground station temperature for the three models. Similar analyses were also undertaken for three stations in Klang Valley, Malaysia, using 11 Landsat ETM+ images to show the effectiveness of the model in different region. The data analysis indicated a good correlation coefficient R = 0.89 and R = 0.91 between the trend of the result of temperature of nearest dark pixels group b6 ? (GST b6 ? GST) model and the trend of PM₁₀ concentration in Iran and Malaysia, respectively. This study reveals the applicability of the thermal band of Landsat TM and ETM+ to determine the PM₁₀ concentration over large areas.     

Temporal analysis of air pollution and its relationship with meteorological parameters in Bahrain, 2006–2012

The objective of this paper is to analyze temporal and seasonal trends of air pollution in Bahrain between 2006 and 2012 by utilizing datasets from five air quality monitoring stations. The non-parametric and robust Theil-Sen approach is employed to study quantitatively temporal variations of particulate matter (PM₁₀ and PM_2.5), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and ozone (O₃). The calculated annual concentrations for PM₁₀ and PM_2.5 in Bahrain were substantially higher than recommended World Health Organization (WHO) guideline standards. Results showed increasing trends for PM₁₀, PM_2.5, and SO₂ whereas O₃ and its precursor NO₂ showed decreasing behavior. The general increase in air pollution trends is in agreement with prediction of air pollution models for Middle East region due to economic growth, industrialization, and urbanization. The significances of long-term trends were examined. Additional to actual (unadjusted) trends, meteorological adjusted (deseasonalized) trends and seasonal trends were quantified. The box-plot analysis visually illustrated monthly variations of key air pollutants. It showed that only PM₁₀ and PM_2.5 exhibited seasonal pattern, and their concentrations increased during summer and decreased during winter. The effects of ambient air temperature, relative humidity, wind speed, and rainfall on particulate matter (PM) concentrations were further investigated. The Spearman correlation coefficient results demonstrated significant negative correlation between relative humidity and PM concentrations (??0.595 for PM₁₀ and ??0.526 for PM_2.5) while significant positive correlation was observed between temperature and PM concentrations (0.420 for PM₁₀ and 0.482 for PM_2.5).     

Assessment of spatial variations of particulate matter (PM<Subscript>10</Subscript> and PM<Subscript>2.5</Subscript>) in Bahrain identified by air quality index (AQI)

The rapid urbanization, industrialization, modernization, and the frequent Middle Eastern dust storms have negatively impacted the ambient air quality in Bahrain. The objective of this study is to identify the most critical atmospheric air pollutants with emphasis on their potential risk to health based on calculated AQI (air quality index) values using EPA approach. The air quality datasets of particulate matters (PM₁₀ and PM_2.5), ozone (O₃), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and carbon monoxide (CO) were measured in January 2012 and August 2012 using five mobile air quality monitoring stations located at different governorates. The results of this study demonstrated that PM₁₀ and PM_2.5 are the most critical air pollutants in Bahrain with PM_2.5 prevailing during January 2012 and PM₁₀ prevailing during August 2012. The corresponding AQI categories were utilized to evaluate spatial variability of particulate matters in five governorates. The impact of meteorological factors such as ambient air temperature, wind speed, relative humidity, and total precipitation on ambient air quality were discussed. The analysis demonstrated that the highest PM₁₀ concentrations were observed in the Northern Governorate while the highest PM_2.5 concentrations were observed in the Capital, Central, and Northern Governorates during August 2012. It was observed that the levels of PM_2.5 pollution were higher within proximity of the industrial zone. The results suggested that the average PM_2.5/PM₁₀ ratio in August 2012 was lower than in January 2012 due to the Aeolian processes. This study concludes that higher wind speed, total precipitation, relative humidity rates, and lower ambient air temperature in January 2012 assisted with the dissipation of particulate matter thus lowering the pollution levels of both PM₁₀ and PM_2.5 in comparison to August 2012.     

Air quality and elemental enrichment factors of aerosol particulate matter in Riyadh City, Saudi Arabia

Air particulate matter (PM) samples were collected from June 2006 to May 2007 for determination of chemical elements. PM samples were taken in two size fractions (PM_2.5 and PM₁₀) with MiniVolume air samplers on rooftops of various buildings (15–25 m above ground) in the city of Riyadh. The samples were subjected to X-ray fluorescence analysis to measure major (Na, Mg, Al, K, Ca, Si, P, S, and Fe) and trace elements (Mn, Ni, Cu, Zn, and Ba). The results showed that the PM concentrations were higher for PM₁₀ compared to PM_2.5, indicating that the major PM source was local dust. Also the spatial distribution with high PM concentrations was observed in the south and southeast of the city and the lowest levels were in the center and northeast of the city. This spatial distribution was attributed to different factors such as wind direction and velocity, emission from cement factories, and the presence of buildings, trees, and paved streets that reduce the amount of dust resuspended into the atmosphere. The air quality of the city was found to range from good to hazardous based on PM_2.5, and from good to very hazardous based on PM₁₀. The element-enrichment factors revealed two element groups according to their changing spatial behavior. The first group showed no significant spatial changes indicating they have the same common source. The second group (mainly S and Ni) exhibited significant changes as expected from anthropogenic inputs. The origin of S is possibly a combination of minerals (CaSO₄) and fossil fuel combustion. The source of Ni is probably from fossil fuel combustion.     

Ambient indoor/outdoor gamma radiation dose rates in the city and at high altitudes of Muzaffarabad (Azad Kashmir)

Preliminary results of ambient indoor/outdoor gamma dose rates measured for Muzaffarabad city, the state capital of Azad Kashmir, are presented. Measurements of indoor/outdoor environmental exposures were carried out using a portable Ludlum Model 19 Micrometer. Effect of altitude on measured values of gamma dose rates has also been investigated. Besides measuring the gamma dose rates for indoor and open environment, measurements have also been taken within two coal mines. Effects of lithology on gamma dose rates have also been investigated. For outdoor measurements, minimum and maximum gamma dose rates were found as 533 ± 4.33 and 1,143 ± 2.96 μGy y^?1, while for indoor environment minimum and maximum gamma dose rate value were found as 533 ± 4.33 and 979 ± 3.2 μGy y^?1. Average values of indoor and outdoor gamma dose rates were found as 761 ± 3.62 and 710 ± 3.75 μGy y^?1. Gamma dose rates have also been calculated with altitude variations. Measured values of gamma dose rates show a weak positive correlation with altitude. For measurements made in coal mines, maximum gamma doses rate value was found as 3,490 ± 1.69 μGy y^?1, situated at a height of 1,098 m, located at Sangri Mera. Results obtained from the current study show that annual effective doses from gamma radiation exposure does not pose health threat to the population of district Muzaffarabad.