Characteristics of PM10, PM2.5, CO2 and CO monitored in interiors and platforms of subway train in Seoul, Korea

This study was performed to investigate the concentration of PM₁₀ and PM_2.5 inside trains and platforms on subway lines 1, 2, 4 and 5 in Seoul, KOREA. PM₁₀, PM_2.5, carbon dioxide (CO₂) and carbon monoxide (CO) were monitored using real-time monitoring instruments in the afternoons (between 13:00 and 16:00). The concentrations of PM₁₀ and PM_2.5 inside trains were significantly higher than those measured on platforms and in ambient air reported by the Korea Ministry of Environment (Korea MOE). This study found that PM₁₀ levels inside subway lines 1, 2 and 4 exceeded the Korea indoor air quality (Korea IAQ) standard of 150 μg/m³. The average percentage that exceeded the PM₁₀ standard was 83.3% on line 1, 37.9% on line 2 and 63.1% on line 4, respectively. PM_2.5 concentration ranged from 77.7 μg/m³ to 158.2 μg/m³, which were found to be much higher than the ambient air PM_2.5 standard promulgated by United States Environmental Protection Agency (US-EPA) (24 h arithmetic mean: 65 μg/m³). The reason for interior PM₁₀ and PM_2.5 being higher than those on platforms is due to subway trains in Korea not having mechanical ventilation systems to supply fresh air inside the train. This assumption was supported by the CO₂ concentration results monitored in tube of subway that ranged from 1153 ppm to 3377 ppm. The percentage of PM_2.5 in PM₁₀ was 86.2% on platforms, 81.7% inside trains, 80.2% underground and 90.2% at ground track. These results indicated that fine particles (PM_2.5) accounted for most of PM₁₀ and polluted subway air. GLM statistical analysis indicated that two factors related to monitoring locations (underground and ground or inside trains and on platforms) significantly influence PM₁₀ (p < 0.001, R² = 0.230) and PM_2.5 concentrations (p < 0.001, R² = 0.172). Correlation analysis indicated that PM₁₀, PM_2.5, CO₂ and CO were significantly correlated at p < 0.01 although correlation coefficients were different. The highest coefficient was 0.884 for the relationship between PM₁₀ and PM_2.5.     

Particulate air pollution in Lanzhou China

Concentrations of total suspended particles (TSP) and PM(10) in Lanzhou China have been kept high for the past two decades. Data collected during the intensive observational period from October 1999 to April 2001 show high TSP and PM(10) concentrations. Starting from November, the PM(10) pollution intensifies, and reaches mid to high alert level of air pollution, continues until April next year, and is at low alert level in the summer. In the winter and spring, the TSP concentration is 2-10 times higher than the third-level criterion of air quality (severe pollution). Effects of intrinsic factors (sources of pollution) and remote preconditions (propagation of dust storms) for severe PM(10) and TSP pollution in Lanzhou are analyzed.     

Levels and major sources of PM2.5 and PM10 in Bangkok Metropolitan Region

This research was the first long-term attempt to concurrently measure and identify major sources of both PM₁₀ and PM_2.5 in Bangkok Metropolitan Region (BMR). Ambient PM₁₀ and PM_2.5 were evaluated at four monitoring stations and analyzed for elemental compositions, water-soluble ions, and total carbon during February 2002–January 2003. Fifteen chemical elements, four water-soluble ions, and total carbon were analyzed to assist major source identification by a receptor model approach, known as chemical mass balance. PM₁₀ and PM_2.5 were significantly different (p < 0.05) at all sites and 24 h averages were high at traffic location while two separated residential sites were similar. Seasonal difference of PM₁₀ and PM_2.5 concentrations was distinct between dry and wet seasons. Major source of PM₁₀ at the traffic site indicated that automobile emissions and biomass burning-related sources contributed approximately 33% each. Automobiles contributed approximately 39 and 22% of PM₁₀ mass at two residential sites while biomass burning contributed about 36 and 28%. PM₁₀ from re-suspended soil and cooking sources accounted for 10 to 15% at a residential site. Major sources of PM_2.5 at traffic site were automobile and biomass burning, contributing approximately 32 and 26%, respectively. Biomass burning was the major source of PM_2.5 mass concentrations at residential sites. Meat cooking also accounted for 31% of PM_2.5 mass at a low impact site. Automobile, biomass burning, and road dust were less significant, contributed 10, 6, and 5%, respectively. Major sources identification at some location had difficulty to achieve performance criteria due to limited source profiles. Improved in characterize other sources profiles will help local authority to better air quality.     

Distribution of PBDEs in air particles from an electronic waste recycling site compared with Guangzhou and Hong Kong, South China

Air samples of total suspended particles (TSP, particles less than 30-60 microm), and particles with aerodynamic diameter smaller than 2.5 microm (PM(2.5)) were collected simultaneously at Guiyu (an electronic waste recycling site), three urban sites in Hong Kong and two urban sites in Guangzhou, South China from 16 August to 17 September 2004. Twenty-two PBDE congeners (BDE-3, -7, -15, -17, -28, -49, -71, -47, -66, -77, -100, -119, -99, -85, -126, -154, -153, -138, -156, -184, -183, -191) in TSP and PM(2.5) were measured. The results showed that the overall average concentrations of TSP and PM(2.5) collected at Guiyu were 124 and 62.1 microg m(-3), respectively. The monthly concentrations of the sum of 22 BDE congeners contained in TSP and PM(2.5) at Guiyu were 21.5 and 16.6 ng m(-3), with 74.5 and 84.3%, contributed by nine congeners (BDE-28, -47, -66, -100, -99, -154, -153, -183 and -191 respectively). This pattern was similar to Tsuen Wan site of Hong Kong. Two urban sites of Guangzhou had the same congener pattern, but were different from Yuen Long and Hok Tsui sites of Hong Kong. The results also showed that the amount of mono to penta brominated congeners, which are more toxic, accounted for 79.4-95.6% of Sigma(22)PBDEs from all sites. All congeners tested in Guiyu were up to 58-691 times higher than the other urban sites and more than 100 times higher than other studies reported elsewhere. The higher concentration in the air was due to heating or opening burning of electronic waste since PBDEs are formed when plastics containing brominated flame retardants are heated.     

Source apportionment of fine carbonaceous particles by positive matrix factorization at Gosan background site in East Asia

Fine particle (aerodynamic diameter <2.5 microm) samples were collected during six intensive measurement periods from November 2001 to August 2003 at Gosan, Jeju Island, Korea, which is one of the representative background sites in East Asia. Chemical composition of these aerosol samples including major ion components, trace elements, organic and elemental carbon (OC and EC), and particulate polycyclic aromatic hydrocarbons (PAHs) were analyzed to study the impact of long-range transport of anthropogenic aerosol. Aerosol chemical composition data were then analyzed using the positive matrix factorization (PMF) technique in order to identify the possible sources and estimate their contribution to particulate matter mass. Fourteen sources were then resolved including soil dust, fresh sea salt, transformed natural source, ammonium sulfate, ammonium nitrate, secondary organic carbon, diesel vehicle, gasoline vehicle, fuel oil combustion, biomass burning, coal combustion, municipal incineration, metallurgical emission source, and volcanic emission. The PMF analysis results of source contributions showed that the natural sources including soil dust, fresh and aged sea salt, and volcanic emission contributed to about 20% of the measured PM(2.5) mass. Other primary anthropogenic sources such as diesel and gasoline vehicle, coal and fuel oil combustion, biomass burning, municipal incineration, metallurgical source contributed about 34% of PM(2.5) mass. Especially, the secondary aerosol mainly involved with sulfate, nitrate, ammonium, and organic carbon contributed to about 39% of the PM(2.5) mass.     

Contribution of (222)Rn-bearing water to indoor radon and indoor air quality assessment in hot spring hotels of Guangdong, China

This study investigates the contribution of radon (²²²Rn)-bearing water to indoor ²²²Rn in thermal baths. The ²²²Rn concentrations in air were monitored in the bathroom and the bedroom. Particulate matter (PM, both PM₁₀ and PM_2.5) and carbon dioxide (CO₂) were also monitored with portable analyzers. The bathrooms were supplied with hot spring water containing 66-260 kBq m⁻³ of ²²²Rn. The results show that the spray of hot spring water from the bath spouts is the dominant mechanism by which ²²²Rn is released into the air of the bathroom, and then it diffuses into the bedroom. Average ²²²Rn level was 110-410% higher in the bedrooms and 510-1200% higher in the bathrooms compared to the corresponding average levels when there was no use of hot spring water. The indoor ²²²Rn levels were influenced by the ²²²Rn concentrations in the hot spring water and the bathing times. The average ²²²Rn transfer coefficients from water to air were 6.2 × 10⁻⁴-4.1 × 10⁻³. The 24-h average levels of CO₂ and PM₁₀ in the hotel rooms were 89% and 22% higher than the present Indoor Air Quality (IAQ) standard of China. The main particle pollutant in the hotel rooms was PM_2.5. Radon and PM₁₀ levels in some hotel rooms were at much higher concentrations than guideline levels, and thus the potential health risks to tourists and especially to the hotel workers should be of great concern, and measures should be taken to lower inhalation exposure to these air pollutants.     

Economic Valuation of Health Impact of PM10 Pollution in Beijing from 2001 to 2006

Abstract

In light of the practical need for research to inform policy in Beijing, this study evaluates the economic cost of the impact of PM₁₀ pollution in Beijing from 2001 to 2006, taking health as the main impact, and mortality as the main outcome. Based on the literature review, this study adopts relatively conservative parameters as the basis for calculating the health impacts. It concludes that nearly 30% of mortality among registered residents above age 30 in Beijing can be attributed to PM₁₀ pollution, and that the economic cost equals 0.8%–1.2% of the city’s GDP over the same period. This is lower than the results of previous studies, but still high enough to warrant a commitment to solve the city’s air pollution problem.