Application of positive matrix factorization in characterization of PM(10) and PM(2.5) emission sources at urban roadside

The 24-h average coarse (PM₁₀) and fine (PM_2.5) fraction of airborne particulate matter (PM) samples were collected for winter, summer and monsoon seasons during November 2008-April 2009 at an busy roadside in Chennai city, India. Results showed that the 24-h average ambient PM₁₀ and PM_2.5 concentrations were significantly higher in winter and monsoon seasons than in summer season. The 24-h average PM₁₀ concentration of weekdays was significantly higher (12-30%) than weekends of winter and monsoon seasons. On weekends, the PM_2.5 concentration was found to slightly higher (4-15%) in monsoon and summer seasons. The chemical composition of PM₁₀ and PM_2.5 masses showed a high concentration in winter followed by monsoon and summer seasons.The U.S.EPA-PMF (positive matrix factorization) version 3 was applied to identify the source contribution of ambient PM₁₀ and PM_2.5 concentrations at the study area. Results indicated that marine aerosol (40.4% in PM₁₀ and 21.5% in PM_2.5) and secondary PM (22.9% in PM₁₀ and 42.1% in PM_2.5) were found to be the major source contributors at the study site followed by the motor vehicles (16% in PM₁₀ and 6% in PM_2.5), biomass burning (0.7% in PM₁₀ and 14% in PM_2.5), tire and brake wear (4.1% in PM₁₀ and 5.4% in PM_2.5), soil (3.4% in PM₁₀ and 4.3% in PM_2.5) and other sources (12.7% in PM₁₀ and 6.8% in PM_2.5).     

Spatial and seasonal variation of PM10 mass concentrations in Taiwan

Hourly data of PM10 concentration collected from an air quality-monitoring network has been analyzed over Taiwan from 1994 to 1999. Fourteen sites from 72 monitoring stations were selected to evaluate the spatial and seasonal variations in the regions of north, southwest, south, east and National Park. The selected monitoring sites are located in a suburban environment, except Nantz and Linyuan that are located in industrial areas. Moreover, Yangming and Hengchuen are located in National Park. Spatial and seasonal variations of PM10 concentrations are rather large over Taiwan. Annual average in south is approximately six times higher than in National parks. In northern sites, the highest concentration occurs in March–May, which is attributed to the occurrence of dust storms in arid regions of central Asia and the transport of dust by northeasterly monsoon. A marked seasonal variation of PM10 concentrations can be observed both in southwestern and southern regions. The pattern is characterized by high concentrations in winter and low in summer. Appearance of the highest monthly PM10 concentration in winter of south may be in part due to the lowest number of monthly precipitation days and low temperature, both of which occurred in winter. The frequency of PM10 daily mean concentration for exceeded 150 μg m⁻³ is 15% during winter in south, which reflects the serious pollution problem there. Monitoring sites in National Park are representatives of remote environments, but the PM10 concentrations are still affected by the dust storms and human activities.     

Size distribution and source identification of total suspended particulate matter and associated heavy metals in the urban atmosphere of Delhi

A study of the atmospheric particulate size distribution of total suspended particulate matter (TSPM) and associated heavy metal concentrations has been carried out for the city of Delhi. Urban particles were collected using a five-stage impactor at six sites in three different seasons, viz. winter, summer and monsoon in the year 2001. Five samples from each site in each season were collected. Each sample (filter paper) was extracted with a mixture of nitric acid, hydrochloric acid and hydrofluoric acid. The acid solutions of the samples were analysed in five-particle fractions by atomic absorption spectrometry (AAS). The impactor stage fractionation of particles shows that a major portion of TSPM concentration is in the form of PM0.7 (i.e. <0.7microm). Similarly, the most of the metal mass viz. Mn, Cr, Cd, Pb, Ni, and Fe are also concentrated in the PM0.7 mode. The only exceptions are size distributions pertaining to Cu and Ca. Though, Cu is more in PM0.7 mode, its presence in size intervals 5.4-1.6microm and 1.6-0.7microm is also significant, whilst in case of Ca there is no definite pattern in its distribution with size of particles. The average PM10.9 (i.e. <10.9microm) concentrations are approximately 90.2%+/-4.5%, 81.4%+/-1.4% and 86.4%+/-9.6% of TSPM for winter, summer and monsoon seasons, respectively. Source apportionment reveals that there are two sources of TSPM and PM10.9, while three and four sources were observed for PM1.6 (i.e. <1.6microm) and PM0.7, respectively. Results of regression analyses show definite correlations between PM10.9 and other fine size fractions, suggesting PM10.9 may adequately act as a surrogate for both PM1.6 and PM0.7, while PM1.6 may adequately act as a surrogate for PM0.7.     

Study of aerosol transport through precipitation chemistry over Arabian Sea during winter and summer monsoons

Precipitation samples over the Arabian Sea collected during Arabian Sea Monsoon Experiment (ARMEX) in 2002–2003 were examined for major water soluble components and acidity of aerosols during the period of winter and summer monsoon seasons. The pH of rain water was alkaline during summer monsoon and acidic during winter monsoon. Summer monsoon precipitation showed dominance of sea-salt components (∼90%) and significant amounts of non-sea salt (nss) Ca²⁺ and SO₄²⁻. Winter monsoon precipitation samples showed higher concentration of NO₃⁻ and NH₄⁺ compared to that of summer monsoon, indicating more influence of anthropogenic sources. The rain water data is interpreted in terms of long-range transport and background pollution. In summer monsoon, air masses passing over the north African and Gulf continents which may be carrying nss components are advected towards the observational location. Also, prevailing strong southwesterly winds at surface level produced sea-salt aerosols which led to high sea-salt contribution in precipitation. While in winter monsoon, it was observed that, air masses coming from Asian region towards observational location carry more pollutants like NO₃⁻and nss SO₄²⁻ that acidify the precipitation.     

Ions species size distribution in particulate matter associated with VOCs and meteorological conditions over an urban region

Airborne particulate matter (PM10, PM2.5, PM1) and volatile organic compounds (benzene, toluene, m,p-xylene, o-xylene) samples were collected during winter and summer seasons of 2005 at two sites, representing an urban and a suburban region of the Greater Athens Area. Urban site traffic emissions were the major contributor to the concentration of PM2.5, PM10, toluene, and xylenes, while benzene and PM1 concentrations were presented in significant spatial variations. K+, Na+, Mg2+, Ca2+, NO3-, Cl- and SO42- ions were analyzed for the chemical characterization of the collected PM samples. The results showed that Na+ cations and SO42- anions were the dominant species, during winter and summer, respectively, in both sites. The analysis of the synoptic scale and mesoscale atmospheric circulation during the experimental periods demonstrated that the meteorological conditions play a key role, not only in the variation but also in the distribution of the ionic concentrations at the three fractions of particulates and the dominant character (alkaline/acidic/neutral) of the particulates at the two sampling sites.     

Seasonal variations of monosaccharide anhydrides in PM1 and PM2.5 aerosol in urban areas

The concentrations of monosaccharide anhydrides (levoglucosan, mannosan, galactosan) in PM1 and PM2.5 aerosol samples were measured in Brno and ?lapanice in the Czech Republic in winter and summer 2009. 56 aerosol samples were collected together at both sites to investigate the different sources that contribute to aerosol composition in studied localities. Daily PM1 and PM2.5 aerosol samples were collected on pre-fired quartz fibre filters.The sum of average atmospheric concentration of levoglucosan, mannosan and galactosan in PM1 aerosol in ?lapanice and Brno during winter was 513 and 273 ng m^?3, while in summer the sum of average atmospheric concentration of monosaccharide anhydrides (MAs) was 42 and 38 ng m^?3, respectively. The sum of average atmospheric concentration of MAs in PM1 aerosol formed 71 and 63% of the sum of MA concentration in PM2.5 aerosol collected in winter in ?lapanice and Brno, whereas in summer the sum of average atmospheric concentration of MAs in PM1 aerosol formed 45 and 43% of the sum of MA concentration in PM2.5 aerosol in ?lapanice and Brno, respectively.In winter, the sum of MAs contributed significantly to PM1 mass ranging between 1.37% and 2.67% of PM1 mass (Brno – ?lapanice), while in summer the contribution of the sum of MAs was smaller (0.28–0.32%). Contribution of the sum of MAs to PM2.5 mass is similar both in winter (1.37–2.71%) and summer (0.44–0.55%).The higher concentrations of monosaccharide anhydrides in aerosols in ?lapanice indicate higher biomass combustion in this location than in Brno during winter season. The comparison of levoglucosan concentration in PM1 and PM2.5 aerosol shows prevailing presence of levoglucosan in PM1 aerosol both in winter (72% on average) and summer (60% on average).The aerosol samples collected in ?lapanice and Brno in winter and summer show comparable contributions of levoglucosan, mannosan and galactosan to the total amount of monosaccharide anhydrides in both aerosol size fractions. Levoglucosan was the most abundant monosaccharide anhydride with a relative average contribution to the total amount of MAs in the range of 71–82% for PM1 aerosols and 52–79% for PM2.5 aerosols.     

Source analysis of high particulate matter days in Hong Kong

This study identifies major contributing sources of high particulate matter (PM) days in Hong Kong and conducive meteorological conditions leading to high PM. The PM₁₀ chemical composition of 3393 ambient samples collected at ten monitoring stations in Hong Kong during 1998–2005 were used as input for positive matrix factorization (PMF) modeling to identify and quantify the aerosol sources in Hong Kong. Days with PM₁₀ levels exceeding 56 μg m^?3, the average plus one standard deviation of the mass concentration of all samples, are defined as high PM days. A total of 401 samples fell in the high PM category during the study period. Biomass burning, secondary sulfate and secondary nitrate were found to be the major contributors leading to high PM, responsible for 68–73% of PM₁₀ mass on high PM days. The contributions by these sources on high PM days were 140–180% higher than their respective average concentration contributions. These sources were identified to be regional sources on the grounds of little spatial variation in their concentrations among the monitoring stations and a temporal pattern of higher in the winter and lower in the summer. Sampling days of high PM in 2004 and 2005 were individually examined for weather charts and regional surface wind maps. Weak high pressures over mainland China were the most important synoptic event leading to high PM days in the fall and winter, while typhoon episodes were responsible for most summer cases. Approximately 80% of the high PM days were in the fall and winter months (September–February). Almost all the high PM days were associated with northwesterly, northerly or northeasterly regional transport. Anthropogenic primary sources (coal combustion, vehicular exhaust, and residue oil combustion) showed the highest contributions associated with northwesterly wind, indicating the strong influence of the more urbanized areas to the northwest of Hong Kong in the Pearl River Delta region.     

Analysis of rainfall and fine aerosol data using clustered trajectory analysis for National Park sites in the Western US

We calculated daily back-trajectories using the NOAA-HYSPLIT model to analyze 7 years of precipitation and PM2.5 data from three National Park sites in the Western US. Using a k-means clustering algorithm, the trajectories were segregated into six main transport patterns. At each site, we calculated trajectory clusters for 1, 5, and 10 days to represent short, medium and long-range flow patterns. Most clusters show marked seasonality. Faster flow patterns are more prevalent in winter, and slower/stagnant patterns are more prevalent in summer. The analyses between the 1, 5, and 10-day clusters revealed that the clusters of different duration show very different predictive power for rainfall and PM2.5. We found that the 1-day clusters are a better predictor for precipitation and PM2.5 concentrations, followed by the 5-day clusters. The 10-day clusters did a poorer job of differentiating precipitation and PM2.5. This is because the 10-day clusters show the greatest variability during the first day or two of transport.     

Size mass distribution of water-soluble ionic species and gas conversion to sulfate and nitrate in particulate matter in southern Taiwan

A Micro-Orifice Uniform Deposition Impactor (MOUDI) and a Nano-MOUDI were employed to determine the size-segregated mass distributions of ambient particulate matter (PM) and water-soluble ionic species for particulate constituents. In addition, gas precursors, including HCl, HONO, HNO₃, SO₂, and NH₃ gases, were analyzed by an annular denuder system. PM size mass distribution, mass concentration, and ionic species concentration were measured during the day and at night during episode and non-episode periods in winter and summer. Average total suspended particle (TSP) concentrations during episode days in winter were as high as 153?±?33 μg/m³, and PM mass concentrations in summer were as low as one-third of that in winter. Generally, PM concentration at night was higher than that in the daytime in southern Taiwan during the sampling periods. In winter during the episode periods, the size-segregated mass distribution of PM mass concentration was mostly in the 0.32–3.2-μm range, and the PM concentration increased significantly in the range of 0.32–3.2 μm at night. Ammonium, nitrate, and sulfate were the dominant water-soluble ionic species in PM, contributing 34–48 % of TSP mass. High concentrations of ammonia (12.9–49 μg/m³) and SO₂ (2.6–27 μg/m³) were observed in the gas precursors. The conversion ratio was high in the PM size range of 0.18–3.2 μm both during the day and at night in winter, and the conversion ratio of episode days was 20 % higher than that of non-episode days. The conversion factor was high for both nitrogen and sulfur species at nighttime, especially on episode days.     

Source characterization of fine and coarse particles at the East Mediterranean coast

Fine and coarse atmospheric particles were collected in Ashdod—a midsize industrial city on the southeastern Mediterranean coast, and in Gedera—a rural site, to characterize ambient particles and to determine their long-range transport during two major seasons—winter and summer. Manual PM2.5 and PM10 samplers, dichotomous samplers, continuous automated PM10 samplers, and denuders were used to sample particulate and gaseous pollutants.Fine and coarse concentrations in Ashdod were 21.2 and 39.6 μg m⁻³, and 23.9 and 30.5 μg m⁻³ in the fall–winter and summer campaigns, respectively. Crustal material, as calcites or dolomites mixed with silicates, dominated the coarse fraction and also the fine fraction on dusty days. In the fall–winter, S, P, and Ni were coupled with minerals. Coarse Ni was associated with crustal material during dust storms, while P originated from shipping and deposition of phosphates in the urban area around.Sulfates dominated the fine fractions in the summer season averaging 12 μg m⁻³. Multivariate analysis indicated that S was associated with As and Se, V and Ni, both associated with heavy fuel combustion, and Zn and Pb. In winter, those mixed sources were local, but in summer they were part of long-range transport. In the fall–winter, Zn and Pb were strongly associated with Mn, Ga, and Cu—elements emitted from either traffic or metal processing plants.Although the influence of crustal material on both size fractions was significant, most heavy metals were associated with PM2.5. Higher concentrations were linked to a larger number of particles in this fraction, to a larger surface area available for biochemical reaction [Harrison, R., Shi, J., Xi, S., Khan, A., Mark, D., Kinnersley, R., Yin, J., Philos, T., 2000. Measurement of number, mass and size distribution of particles in the atmosphere. Philosophical Transactions of the Royal Society 358, 2567–2579], and finally to a larger concern in regards to health effects.     

Time trends in the concentrations of lead in wet precipitation from rural and urban sites in Austria

Trend and time series analysis of concentrations of lead in wet precipitation at different rural and urban sampling sites in Austria, collected during intervals of 6-12 years (between 1984 and 1995) is performed. A substantial decrease of the lead concentrations for all sites in consideration is observed similar to observations in Germany, Sweden and North sea and western Atlantic regions. Reductions in rural sites between 60 and 80% in 10 years and around 90% in 10 years in urban areas are found. This trend correlates with the reduction of lead emissions from combustion of gasoline. The seasonal deconvolution model of the data set reveals a typical seasonality with lead concentration peaks in summer and spring for the rural sites and winter peaks for urban sites. The average annual lead concentration in the rural region for 1995 was 1.25 micrograms/l, in the urban region 2.25 micrograms/l.     

Seasonal variations in the chemical composition of particulate matter: a case study in the Po Valley. Part I: macro-components and mass closure

The seasonal variability in the mass concentration and chemical composition of atmospheric particulate matter (PM₁₀ and PM_2.5) was studied during a 2-year field study carried out between 2010 and 2012. The site of the study was the area of Ferrara (Po Valley, Northern Italy), which is characterized by frequent episodes of very stable atmospheric conditions in winter. Chemical analyses carried out during the study allowed the determination of the main components of atmospheric PM (macro-elements, ions, elemental carbon, organic matter) and a satisfactory mass closure was obtained. Accordingly, chemical components could be grouped into the main macro-sources of PM: soil, sea spray, inorganic compounds from secondary reactions, vehicular emission, organics from domestic heating, organics from secondary formation, and other sources. The more significant seasonal variations were observed for secondary inorganic species in the fine fraction of PM; these species were very sensitive to air mass age and thus to the frequency of stable atmospheric conditions. During the winter ammonium nitrate, the single species with the highest concentration, reached concentrations as high as 30 μg/m³. The intensity of natural sources was fairly constant during the year; increases in natural aerosols were linked to medium and long-range transport episodes. The ratio of winter to summer concentrations was roughly 2 for combustion product, close to 3 for secondary inorganic species, and between 2 and 3 for organics. The winter increase of organics was due to poorer atmospheric dispersion and to the addition of the emission from domestic heating. A similar winter to summer ratio (around 3) was observed for the fine fraction of PM.     

西安市及周边地区MODIS气溶胶光学厚度与PM10浓度关系模型研究

西安是空气污染监控和防治有代表性的西部大型城市。研究了西安市及周边地区上空气溶胶光学厚度与PM10浓度的关系模型。利用2011—2012年MODIS卫星气溶胶光学厚度（AOD）遥感产品，通过数据匹配，利用地面气象观测站点的能见度数据和相对湿度数据对AOD产品进行垂直标高订正和湿度订正，2项订正显著提高了AOD和地面PM10浓度的相关性，相关系数从0．36提高到0．65，按季节分类统计和订正春至冬四季的相关系数分别为0．57、0．71、0．62和0．87，夏季和冬季的订正更为有效，可用性更高，这可能由于受到不同季节气溶胶来源和特征的影响。为研究中国西部大型城市，特别是西安市空气环境监测和区域联防联控提供了一种有效方法。     

Sources of Atmospheric Carbonaceous Particulate Matter in Pittsburgh,Pennsylvania

Abstract

The organic carbon (OC)/elemental carbon (EC) tracer method is applied to the Pittsburgh, PA, area to estimate the contribution of secondary organic aerosol (SOA) to the monthly average concentration of organic particu-late matter (PM) during 1995. An emissions inventory is constructed for the primary emissions of OC and EC in the area of interest. The ratio of primary emissions of OC to those of EC ranges between 2.4 in the winter months and 1.0 in the summer months. A mass balance model and ambient measurements were used to assess the accuracy of the emissions inventory. It is estimated to be accurate to within 50%. The results from this analysis show a strong monthly dependence on SOA contribution to the total organic PM concentration, varying from near zero during winter months to 50% or more of the total OC concentration in the summer.     

Particulate matter source apportionment in a village situated in industrial region of Central Europe

The bilinear receptor model positive matrix factorization (PMF) was used to apportion particulate matter with an aerodynamic diameter of 1–10 μm (PM_1–10) sources in a village, B?ezno, situated in an industrial region of northern Bohemia in Central Europe. The receptor model analyzed the data sets of 90- and 60-min integrations of PM_1–10 mass concentrations and elemental composition for 27 elements. The 14-day sampling campaigns were conducted in the village in summer 2008 and winter 2010. Also, to ensure seasonal and regional representativeness of the data sets recorded in the village, the spatial-temporal variability of the 24-hr PM₁₀ and PM_1–10 within 2008–2010 in winter and summer across the multiple sites was evaluated. There were statistically significant interseasonal differences of the 24-hr PM data, but not intrasummer or intrawinter differences of the 24-hr PM_1–10 data across the multiple sites. PMF resolved seven sources of PM_1–10. They were high-temperature coal combustion; combustion in local heating boilers; marine aerosol; mineral dust; primary biological/wood burning; road dust, car brakes; and gypsum. The main summer factors were assigned to mineral dust (38.2%) and primary biological/wood burning (33.1%). In winter, combustion factors dominated (80%) contribution to PM_1–10. The conditional probability function (CPF) helped to identified local sources of PM_1–10. The source of marine aerosol from the North Sea and English Channel was indicated by the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT).

Implications: This is the first application of PMF to highly time/size resolved PM data in Czech Republic. The coarse aerosol fraction, PM_1–10, was chosen with regard to industrial character of the region, sampling site near the coal strip mine and coal power stations. Contrary to expectation, source apportionment did not show dominance of emissions from the coal strip mine. The results will enable local authorities and state bodies responsible for air quality assessment to focus on sources most responsible for air pollution in this industrial region.

Supplemental Materials:?Supplemental materials are available for this paper. Go to the publisher's online edition of the Journal of the Air & Waste Management Association for (1) details of measurement campaigns; (2) CPF for each of the sources contributing to PM_1–10; (3) factors contribution to PM_1–10 resolved by PMF; (4) diurnal pattern of road dust, car brake factor in summer and winter; (5) trajectories during the marine aerosol episode in winter 2010; and (6) temporal temperature, concentration, and wind speed relationships during the summer 2008 campaign and winter 2010 campaign.     

Sources of atmospheric carbonaceous particulate matter in Pittsburgh,Pennsylvania

The organic carbon (OC)/elemental carbon (EC) tracer method is applied to the Pittsburgh, PA, area to estimate the contribution of secondary organic aerosol (SOA) to the monthly average concentration of organic particulate matter (PM) during 1995. An emissions inventory is constructed for the primary emissions of OC and EC in the area of interest. The ratio of primary emissions of OC to those of EC ranges between 2.4 in the winter months and 1.0 in the summer months. A mass balance model and ambient measurements were used to assess the accuracy of the emissions inventory. It is estimated to be accurate to within 50%. The results from this analysis show a strong monthly dependence of the SOA contribution to the total organic PM concentration, varying from near zero during winter months to as much as 50% of the total OC concentration in the summer.     

Light-Duty Motor Vehicle Exhaust Particulate Matter Measurement in the Denver,Colorado, Area

ABSTRACT

A study of particulate matter (PM) emissions from in-use, light-duty vehicles was conducted during the summer of 1996 and the winter of 1997 in the Denver, CO, region. Vehicles were tested as received on chassis dynamometers on the Federal Test Procedure Urban Dynamometer Driving Schedule (UDDS) and the IM240 driving schedule. Both PM10 and regulated emissions were measured for each phase of the UDDS. For the summer portion of the study, 92 gasoline vehicles, 10 diesel vehicles, and 9 gasoline vehicles with visible smoke emissions were tested once. For the winter, 56 gasoline vehicles, 12 diesel vehicles, and 15 gasoline vehicles with visible smoke were tested twice, once indoors at 60 °F and once outdoors at the prevailing temperature. Vehicle model year ranged from 1966 to 1996. Impactor particle size distributions were obtained on a subset of vehicles. Continuous estimates of the particle number emissions were obtained with an electrical aerosol analyzer. This data set is being provided to the Northern Front Range Air Quality Study program and to the State of Colorado and the U.S. Environmental Protection Agency for use in updating emissions inventories.     

Evaluation of multisectional and two-section particulate matter photochemical grid models in the Western United States

Version 4.10s of the comprehensive air-quality model with extensions (CAMx) photochemical grid model has been developed, which includes two options for representing particulate matter (PM) size distribution: (1) a two-section representation that consists of fine (PM2.5) and coarse (PM2.5-10) modes that has no interactions between the sections and assumes all of the secondary PM is fine; and (2) a multisectional representation that divides the PM size distribution into N sections (e.g., N = 10) and simulates the mass transfer between sections because of coagulation, accumulation, evaporation, and other processes. The model was applied to Southern California using the two-section and multisection representation of PM size distribution, and we found that allowing secondary PM to grow into the coarse mode had a substantial effect on PM concentration estimates. CAMx was then applied to the Western United States for the 1996 annual period with a 36-km grid resolution using both the two-section and multisection PM representation. The Community Multiscale Air Quality (CMAQ) and Regional Modeling for Aerosol and Deposition (REMSAD) models were also applied to the 1996 annual period. Similar model performance was exhibited by the four models across the Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network monitoring networks. All four of the models exhibited fairly low annual bias for secondary PM sulfate and nitrate but with a winter overestimation and summer underestimation bias. The CAMx multisectional model estimated that coarse mode secondary sulfate and nitrate typically contribute <10% of the total sulfate and nitrate when averaged across the more rural IMPROVE monitoring network.     

Seasonal distribution and contamination levels of total PHCs, PAHs and heavy metals in coastal waters of the Alang-Sosiya ship scrapping yard, Gulf of Cambay, India

Alang-Sosiya situated on the Gulf of Cambay is one of the largest ship breaking yard in the world. The seasonal distribution and contamination levels of dissolved and/or dispersed total petroleum hydrocarbons (PHCs), total polycyclic aromatic hydrocarbons (PAHs) and heavy metals in seawater during high tide are investigated. The concentrations of petroleum hydrocarbons and heavy metals are higher in the winter than in the monsoon and summer. The concentrations of total PHCs and PAHs are about three times higher in the winter and two times in the monsoon or summer at Along-Sosiya and about twice in all seasons at two stations one on either side 5 km away from it as compared to the reference station at Mahuva, 60 km away towards the south. Further, the levels of PHCs are correlated with salinity and compared with those of other regions. The concentration of all metals is the highest in the winter season followed by the monsoon and summer. We carried out the quantitative analysis of the possible relationships among 13 variables such as Al, Fe, Pb, Mn, Cu, Zn, Cd, Cr, Co, pH, NO3-, NO2 and PO4(3-).     

Spatiotemporal distribution and short-term trends of particulate matter concentration over China, 2006–2010

Air quality problems caused by atmospheric particulate have drawn broad public concern in the global scope. In the paper, the spatiotemporal distributions of fine particle (PM2.5) and inhalable particle (PM10) concentrations estimated with the artificial neural network (ANN) over China during 2006 to 2010 have been discussed. Most high PM10 concentration appears in Xinjiang, Qinghai, Gansu, Ningxia, Hubei, and parts of Inner Mongolia. The distribution of PM2.5 concentration is consistent with China’s three gradient terrains. The seasonal variations of PM2.5 and PM10 concentrations both indicate that they are higher in north China in spring and winter, lowest in summer. In autumn, most provinces in south China appear high value. In particular, high PM2.5 concentration appears in the southeast coastal cities while high PM10 concentration prefers the central regions in south China. On this basis, seasonal Mann–Kendall test method is utilized to analyze the short-term trends. The results also show significant changes of PM2.5 and PM10 concentrations of China in the past 5 years, and most provinces present the tendency of reduction (3–5 μg/m³ for PM2.5 and 10–20 μg/m³ for PM10 per year) while a fraction of provinces appear the increasing trend of 8–16 μg/m³ (PM2.5) and 16–30 μg/m³ (PM10). Simultaneously, PM2.5 population exposure is discussed with the combination of population density-gridded data. Municipalities get much higher exposure level than other provinces. Shanghai suffers the highest population exposure to PM2.5, followed by Beijing and then Tianjin, Jiangsu province. Most provincial capitals, such as Guangzhou, Nanjing, Chengdu, and Wuhan, face much higher exposure level than other regions of their province. Moreover, the PM2.5 exposure situation is more serious in southeast than northwest regions for Beijing-Tianjin-Hebei region. Also, per capita PM2.5 concentration and population-weighted PM2.5 concentration are calculated. The former shows that the high-level regions distribute in Guangdong, Shanghai, and Tianjin, while the latter in Hebei, Chongqing, and Shandong provinces. Further studies may consider optimizing concentration estimation model and use it to discuss the effects of particulate matters on human health.