Water-soluble ions measured in fine particulate matter next to cement works

2011 ◽  
Vol 45 (12) ◽  
pp. 2043-2049 ◽  
Author(s):  
N. Galindo ◽  
E. Yubero ◽  
J.F. Nicolás ◽  
J. Crespo ◽  
C. Pastor ◽  
...  
2018 ◽  
Vol 18 (4) ◽  
pp. 2585-2600 ◽  
Author(s):  
Thilina Jayarathne ◽  
Chelsea E. Stockwell ◽  
Ashley A. Gilbert ◽  
Kaitlyn Daugherty ◽  
Mark A. Cochrane ◽  
...  

Abstract. Fine particulate matter (PM2.5) was collected in situ from peat smoke during the 2015 El Niño peat fire episode in Central Kalimantan, Indonesia. Twenty-one PM samples were collected from 18 peat fire plumes that were primarily smoldering with modified combustion efficiency (MCE) values of 0.725–0.833. PM emissions were determined and chemically characterized for elemental carbon (EC), organic carbon (OC), water-soluble OC, water-soluble ions, metals, and organic species. Fuel-based PM2.5 mass emission factors (EFs) ranged from 6.0 to 29.6 g kg−1 with an average of 17.3 ± 6.0 g kg−1. EC was detected only in 15 plumes and comprised  ∼ 1 % of PM mass. Together, OC (72 %), EC (1 %), water-soluble ions (1 %), and metal oxides (0.1 %) comprised 74 ± 11 % of gravimetrically measured PM mass. Assuming that the remaining mass is due to elements that form organic matter (OM; i.e., elements O, H, N) an OM-to-OC conversion factor of 1.26 was estimated by linear regression. Overall, chemical speciation revealed the following characteristics of peat-burning emissions: high OC mass fractions (72 %), primarily water-insoluble OC (84 ± 11 %C), low EC mass fractions (1 %), vanillic to syringic acid ratios of 1.9, and relatively high n-alkane contributions to OC (6.2 %C) with a carbon preference index of 1.2–1.6. Comparison to laboratory studies of peat combustion revealed similarities in the relative composition of PM but greater differences in the absolute EF values. The EFs developed herein, combined with estimates of the mass of peat burned, are used to estimate that 3.2–11 Tg of PM2.5 was emitted to atmosphere during the 2015 El Niño peatland fire event in Indonesia. Combined with gas-phase measurements of CO2, CO, CH4, and volatile organic carbon from Stockwell et al. (2016), it is determined that OC and EC accounted for 2.1 and 0.04 % of total carbon emissions, respectively. These in situ EFs can be used to improve the accuracy of the representation of Indonesian peat burning in emission inventories and receptor-based models.


2017 ◽  
Author(s):  
Thilina Jayarathne ◽  
Chelsea E. Stockwell ◽  
Ashley A. Gilbert ◽  
Kaitlyn Daugherty ◽  
Mark A. Cochrane ◽  
...  

Abstract. Fine particulate matter (PM2.5) was collected in situ from peat smoke during the 2015 El Niño peat fire episode in Central Kalimantan, Indonesia. Twenty-one PM samples were collected from 18 peat fire plumes that were primarily smoldering with modified combustion efficiency (MCE) values of 0.725–0.833. PM emissions were determined and chemically characterized for elemental carbon (EC), organic carbon (OC), water-soluble OC, water-soluble ions, metals, and organic species. Fuel-based PM2.5 mass emission factors (EF) ranged from 6.0–29.6 g kg−1 with an average of 17.3 ± 6.0 g kg−1. EC was detected only in 15 plumes and comprised ~ 1 % of PM mass. Together, OC (72 %), EC (1 %), water-soluble ions (1 %) and metal oxides (0.1 %) comprised 74 ± 11 % of gravimetrically-measured PM mass. Assuming that the remaining mass is due to elements that form organic matter (OM; i.e. elements O, H, N) an OM to OC conversion factor of 1.26 was estimated by linear regression. Overall, chemical speciation revealed the following characteristics of peat burning emissions: high OC mass fractions (72 %), primarily water-insoluble OC (84 ± 11 % C), low EC mass fractions (1 %), vanillic to syringic acid ratios of 1.9, and relatively high n-alkane contributions to OC (6.2 % C) with a carbon preference index of 1.2–1.6. Comparison to laboratory studies of peat combustion revealed similarities in the relative composition of PM, but greater differences in the absolute EF values. The EF developed herein, combined with estimates of the mass of peat burned, are used to estimate that 3.2–11 Tg of PM2.5 was emitted to atmosphere during the 2015 El Niño peatland fire event in Indonesia. Combined with gas-phase measurements of CO2, CO, CH4 and VOC from Stockwell et al. (2016), it is determined that OC and EC account for 2.1 % and 0.04 % of total carbon emissions, respectively. These in situ EFs can be used to improve the accuracy of the representation of Indonesian peat burning in emission inventories and receptor-based models.


Author(s):  
Shuang Wang ◽  
Mandeep Kaur ◽  
Tengfei Li ◽  
Feng Pan

The present study was planned to explore the pollution characteristics, health risks, and influence of atmospheric fine particulate matter (PM2.5) and its components on blood routine parameters in a typical industrial city (Xinxiang City) in China. In this study, 102 effective samples 28 (April–May), 19 (July–August), 27 (September–October), 28 (December–January) of PM2.5 were collected during different seasons from 2017 to 2018. The water-soluble ions and metal elements in PM2.5 were analyzed via ion chromatography and inductively coupled plasma–mass spectrometry. The blood routine physical examination parameters under different polluted weather conditions from January to December 2017 and 2018, the corresponding PM2.5 concentration, temperature, and relative humidity during the same period were collected from Second People’s Hospital of Xinxiang during 2017–2018. Risk assessment was carried out using the generalized additive time series model (GAM). It was used to analyze the influence of PM2.5 concentration and its components on blood routine indicators of the physical examination population. The “mgcv” package in R.3.5.3 statistical software was used for modeling and analysis and used to perform nonparametric smoothing on meteorological indicators such as temperature and humidity. When Akaike’s information criterion (AIC) value is the smallest, the goodness of fit of the model is the highest. Additionally, the US EPA exposure model was used to evaluate the health risks caused by different heavy metals in PM2.5 to the human body through the respiratory pathway, including carcinogenic risk and non-carcinogenic risk. The result showed that the air particulate matter and its chemical components in Xinxiang City were higher in winter as compared to other seasons with an overall trend of winter > spring > autumn > summer. The content of nitrate (NO3−) and sulfate (SO42−) ions in the atmosphere were higher in winter, which, together with ammonium, constitute the main components of water-soluble ions in PM2.5 in Xinxiang City. Source analysis reported that mobile pollution sources (coal combustion emissions, automobile exhaust emissions, and industrial emissions) in Xinxiang City during the winter season contributed more to atmospheric pollution as compared to fixed sources. The results of the risk assessment showed that the non-carcinogenic health risk of heavy metals in fine particulate matter is acceptable to the human body, while among the carcinogenic elements, the order of lifetime carcinogenic risk is arsenic (As) > chromium(Cr) > cadmium (Cd) > cobalt(Co) > nickel (Ni). During periods of haze pollution, the exposure concentration of PM2.5 has a certain lag effect on blood routine parameters. On the day when haze pollution occurs, when the daily average concentration of PM2.5 rises by 10 μg·m−3, hemoglobin (HGB) and platelet count (PLT) increase, respectively, by 9.923% (95% CI, 8.741–11.264) and 0.068% (95% CI, 0.067–0.069). GAM model analysis predicted the maximum effect of PM2.5 exposure concentration on red blood cell count (RBC) and PLT was reached when the hysteresis accumulates for 1d (Lag0). The maximum effect of exposure concentration ofPM2.5 on MONO is reached when the lag accumulation is 3d (Lag2). When the hysteresis accumulates for 6d (Lag5), the exposure concentration of PM2.5 has the greatest effect on HGB. The maximum cumulative effect of PM2.5 on neutrophil count (NEUT) and lymphocyte (LMY) was strongest when the lag was 2d (Lag1). During periods of moderate to severe pollution, the concentration of water-soluble ions and heavy metal elements in PM2.5 increases significantly and has a significant correlation with some blood routine indicators.


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