Factors affecting the concentrations of PM10 in central Taiwan

A comprehensive examination of temporal-seasonal variations of PM1.0 and PM2.5 in taiwan before and during the COVID-19 lockdown

COVID-19 has been a significant global concern due to its contagious nature. In May 2021, Taiwan experienced a severe outbreak, leading the government to enforce strict Pandemic Alert Level 3 restrictions in order to curtail its spread. Although previous studies in Taiwan have examined the effects of these measures on air quality, further research is required to compare different time periods and assess the health implications of reducing particulate matter during the Level 3 lockdown. Herein, we analyzed the mass concentrations, chemical compositions, seasonal variations, sources, and potential health risks of PM1.0 and PM2.5 in Central Taiwan before and during the Level 3 lockdown. As a result, coal-fired boilers (47%) and traffic emissions (53%) were identified as the predominant sources of polycyclic aromatic hydrocarbons (PAHs) in PM1.0, while in PM2.5, the dominant sources of PAHs were coal-fired boilers (28%), traffic emissions (50%), and iron and steel sinter plants (22.1%). Before the pandemic, a greater value of 20.9 ± 6.92 μg/m3 was observed for PM2.5, which decreased to 15.3 ± 2.51 μg/m3 during the pandemic due to a reduction in industrial and anthropogenic emissions. Additionally, prior to the pandemic, PM1.0 had a contribution rate of 79% to PM2.5, which changed to 89% during the pandemic. Similarly, BaPeq values in PM2.5 exhibited a comparable trend, with PM1.0 contributing 86% and 65% respectively. In both periods, the OC/EC ratios for PM1.0 and PM2.5 were above 2, due to secondary organic compounds. The incremental lifetime cancer risk (ILCR) of PAHs in PM2.5 decreased by 4.03 × 10-5 during the pandemic, with PM1.0 contributing 73% due to reduced anthropogenic activities.

Spatial distributions of PM10-bound metal elements in the central part of western Taiwan and their potential emission sources and the carcinogenic health risks

This study aimed to investigate the spatial distribution of metal elements in PM10 and their potential sources and associated health risks over a period of two years in eight locations in the central part of western Taiwan. The study revealed that the mass concentration of PM10 and the total mass concentration of 20 metal elements in PM10 were 39.0 μg m-3 and 4.74 μg m-3, respectively, with total metal elements accounting for approximately 13.0% of PM10. Of the total metal elements, 95.6% were crustal elements (Al, Ca, Fe, K, Mg, and Na), with trace elements (As, Ba, Cd, Cr, Co, Cu, Ga, Mn, Ni, Pb, Sb, Se, V, and Zn) contributing only 4.4%. Spatially, the inland areas exhibited higher PM10 concentrations due to lee-side topography and low wind speeds. In contrast, the coastal regions exhibited higher total metal concentrations because of the dominance of crustal elements from sea salt and crustal soil. Four primary sources of metal elements in PM10 were identified as sea salt (58%), re-suspended dust (32%), vehicle emissions and waste incineration (8%), and industrial emissions and power plants (2%). The positive matrix factorization (PMF) analysis results indicated that natural sources like sea salt and road dust contributed up to 90% of the total metal elements in PM10, while only 10% was attributed to human activities. The excess cancer risks (ECRs) associated with As, Co, and Cr(VI) were greater than 1 × 10-6, and the total ECR was 6.42 × 10-5. Although only 10% of total metal elements in PM10 came from human activities, they contributed to 82% of the total ECR.

Empirical Model for Evaluating PM10 Concentration Caused by River Dust Episodes

Around the estuary of the Zhuo-Shui River in Taiwan, the waters recede during the winter, causing an increase in bare land area and exposing a large amount of fine earth and sand particles that were deposited on the riverbed. Observations at the site revealed that when northeastern monsoons blow over bare land without vegetation or water cover, the fine particles are readily lifted by the wind, forming river dust, which greatly endangers the health of nearby residents. Therefore, determining which factors affect river dust and constructing a model to predict river dust concentration are extremely important in the research and development of a prototype warning system for areas at risk of river dust emissions. In this study, the region around the estuary of the Zhuo-Shui River (from the Zi-Qiang Bridge to the Xi-Bin Bridge) was selected as the research area. Data from a nearby air quality monitoring station were used to screen for days with river dust episodes. The relationships between PM₁₀ concentration and meteorological factors or bare land area were analyzed at different temporal scales to explore the factors that affect river dust emissions. Study results showed that no single factor alone had adequate power to explain daily average or daily maximum PM₁₀ concentration. Stepwise regression analysis of multiple factors showed that the model could not effectively predict daily average PM₁₀ concentration, but daily maximum PM₁₀ concentration could be predicted by a combination of wind velocity, temperature, and bare land area; the coefficient of determination for this model was 0.67. It was inferred that river dust episodes are caused by the combined effect of multiple factors. In addition, research data also showed a time lag effect between meteorological factors and hourly PM₁₀ concentration. This characteristic was applied to the construction of a prediction model, and can be used in an early warning system for local residents.

Aerosol characteristics of different types of episode

Daily and hourly average data from nine air-quality monitoring stations distributed across central Taiwan, which include ten items (i.e., PM₁₀, PM₂.₅, wind direction, wind speed, temperature, relative humidity, SO₂, NO₂, NO, and CO), were collected from 2005 to 2009. Four episode types: long-range transport with dust storms (DS), long-range transport with frontal pollution (FP), river dust (RD), and stagnant weather (SW), and one mixed type of episode were identified. Of these four episode types, the SW was the dominant type, averaging about 70%. The mean ratio of PM₂.₅/PM₁₀ was the lowest during the RD episodes (0.42), while the mean ratio of PM₂.₅/PM₁₀ was the highest during the SW episodes (0.64). Fine aerosol (PM₂.₅) and coarse aerosol (PM₁₀-₂.₅) samples were collected by high-volume samplers for chemical composition analysis, from only three stations (Douliou, Lunbei, and Siansi) during the days of SW, RD, DS, and FP. The concentrations of PM₂.₅ and three ionic species (NH₄⁺, NO₃⁻, and SO₄²⁻) all showed significant differences among the four episode types. The highest levels of NO₃⁻ (12.1 μg/m(3)) and SO₄²⁻ (20.5 μg/m(3)) were found during the SW and FP episodes, respectively. A comparison on the spatial similarity of aerosol compositions among the episodes and/or non-episodes (control) was characterized by the coefficient of divergence (CD). The results showed higher CD values in PM₁₀-₂.₅ than in PM₂.₅, and the CD values between RD episodes and the other three episodes were higher than those between two types of episode for the other three episodes. The ratios of SOR (sulfur oxidation ratio), SO₄²⁻/EC (elemental carbon), NOR (nitrogen oxidation ratio), and NO₃⁻/EC showed that sulfate formation was most rapid during the FP, while nitrate formation was most rapid during the SW.

Analysis of the major factors affecting the visibility degradation in two stations

There are four types of PM10 (particulate matter with an aerodynamic diameter <10 microm) episodes that occur frequently in central Taiwan: long-range transport with dust storms (DS), long-range transport with frontal pollution (FP), river dust (RD), and stagnant weather (SW). During the periods of the four episodes, poor visibility usually results. Multiple linear regression was applied to visibility using eight potential influential variables (temperature, relative humidity, wind speed, PM2.5, PM2.5-10, SO2, NO2, and NO) as independent variables. Of the eight variables, PM2.5 showed the greatest explainable percentage of about 48.6% and 58.1% for Taichung and Wuchi stations, respectively. This suggested that PM2.5 was the most important contributor to reduced visibility. Compared with other type of episodes, the aerosols tended to be offine size during the SWepisodes. This is the main reason that the poorest visibility occurred during the SWepisodes. Good correlation between visibility and secondary inorganic salts (NH4+, NO3, and SO4(2-)) were found at Taichung station (r = 0.71) and Wuchi station (r = 0.81), suggesting that secondary inorganic salts did contribute significantly to the degradation ofvisibility. The visibility degradation due to the effects ofNO3- was much higher than that due to SO4(2-) and NH4+ in the urban area, whereas the visibility degradation due to the effects of NO3 , SO42-, and NH4+ did not show significant diference in the rural area.

IMPLICATIONS

Of the eight potential influential variables, PM2.5 showed the greatest effects on reduced visibility. Compared with other type of episodes, the aerosols tend to be fine size during the episodes of stagnant weather. This is the main reason why the poorest visibility occurred during the SW episodes. Good correlations between visibility and secondary inorganic salts (NH4+, NO3-, and SO4(2-)) suggested that secondary inorganic salts did contribute significantly to the degradation of visibility. Among the three inorganic salts, nitrates played a leading role for visibility degradation in urban areas in central Taiwan.

Characteristics of major secondary ions in typical polluted atmospheric aerosols during autumn in central Taiwan

In autumn of 2008, the chemical characteristics of major secondary ionic aerosols at a suburban site in central Taiwan were measured during an annually occurring season of high pollution. The semicontinuous measurement system measured major soluble inorganic species, including NH(4)(+), NO(3)(-), and SO(4)(2-), in PM(10) with a 15 min resolution time. The atmospheric conditions, except for the influences of typhoons, were dominated by the local sea-land breeze with clear diurnal variations of meteorological parameters and air pollutant concentrations. To evaluate secondary aerosol formation at different ozone levels, daily ozone maximum concentration (O(3,daily max)) was used as an index of photochemical activity for dividing between the heavily polluted period (O(3,daily max) ≧80 ppb) and the lightly polluted period (O(3,daily max)<80 ppb). The concentrations of PM(10), NO(3)(-), SO(4)(2-), NH(4)(+) and total major ions during the heavily polluted period were 1.6, 1.9, 2.4, 2.7 and 2.3 times the concentrations during the lightly polluted period, respectively. Results showed that the daily maximum concentrations of PM(10) occurred around midnight and the daily maximum ozone concentration occurred during daytime. The average concentration of SO(2) was higher during daytime, which could be explained by the transportation of coastal industry emissions to the sampling site. In contrast, the high concentration of NO(2) at night was due to the land breeze flow that transport inland urban air masses toward this site. The simulations of breeze circulations and transitions were reflected in transports and distributions of these pollutants. During heavily polluted periods, NO(3)(-) and NH(4)(+) showed a clear diurnal variations with lower concentrations after midday, possibly due to the thermal volatilization of NH(4)NO(3) during daytime and transport of inland urban plume at night. The diurnal variation of PM(10) showed the similar pattern to that of NO(3)(-) and NH(4)(+) aerosols. This indicated that the formatted secondary aerosols in the inland urban area could be transported to the coastal area by the weak land breeze and deteriorated the air quality in the coastal area at night.

Time-resolved measurements of water-soluble ions and elements in atmospheric particulate matter for the characterization of local and long-range transport events

Chemical composition of atmospheric PM(10) was determined at 2-h resolution during a 10-d field study carried out in the urban area of Rome, Italy. Extractable and residual fractions of elements were determined on 2-h samples by inductively coupled plasma mass spectrometry, a rather widespread analytical technique; daily chemical characterization of macro- and micro-components was also carried out and the mass closure was obtained. Interpretation of the variations in PM(10) composition was carried out in the light of the meteorological conditions and, in particular, of the mixing properties of the lower atmosphere, evaluated by monitoring natural radioactivity due to radon 222 decay. The combination of time-resolved sampling, chemical fractionation and monitoring of the dilution properties of the atmosphere allowed a reliable identification of long-range transport events and of local phenomena, which could not be detected by daily samplings. This kind of study can be effective for gathering detailed information about tracers at local scale, which are really valuable for interpreting the results of traditional low-resolution monitoring studies.