Photochemical oxidation of VOCs and their source impact assessment on ozone under de-weather conditions in Western Taiwan.

The application of statistical models has excellent potential to provide crucial information for mitigating the challenging issue of ozone (O3) pollution by capturing its associations with explanatory variables, including reactive precursors (VOCs and NOX) and meteorology. Considering the large contribution of O3 in degrading the air quality of western Taiwan, three-year (2019-2021) hourly concentration data of VOC, NOX and O3 from 4 monitoring stations of western Taiwan: Tucheng (TC), Zhongming (ZM), Taixi (TX) and Xiaogang (XG), was evaluated to identify the effect of anthropogenic emissions on O3 formation. Owing to the high-ambient reactivity of VOCs on the underestimation of sources, photochemical oxidation was assessed to calculate the consumed VOC (VOCcons) which was followed by the source identification of their initial concentrations. VOCcons was observed to be highest in the summer season (16.7 and 22.7 ppbC) at north (TC and ZM) and in the autumn season (17.8 and 11.4 ppbC) in southward-located stations (TX and XG, respectively). Results showed that VOCs from solvents (25-27%) were the major source at northward stations whereas VOCs-industrial emissions (30%) dominated in south. Furthermore, machine learning (ML): eXtreme Gradient Boost (XGBoost) model based de-weather analysis identified that meteorological factors favor to reduce ambient O3 levels at TC, ZM and XG stations (-67%, -47% and -21%, respectively) but they have a major role in accumulating the O3 (+38%) at the TX station which is primarily transported from the upwind region of south-central Taiwan. Crucial insights using ML outputs showed that the finding of the study can be utilized for region-specific data-driven control of emission from VOCs-sources and prioritized to limit the O3-pollution at the study location-ns as well as their accumulation in distant regions.

Exploration of characteristics and synthesis gas suitability for heat generation of coffee biomass pellets produced by single and co-pelletization.

Production of coffee beans generates various types of biomass that can be applied as bioenergy for drying and roasting the beans. Thus, the aims of this study were to explore the characteristics of coffee biomass pellets (CBPs) produced from coffee cherry pulp (CCP), coffee parchment (CPM), and expired green coffee beans (ECB) by single and co-pelletization. The CBPs were then used to produce the synthesis gas in a downdraft gasifier, and the syngas properties were investigated for further heat applications. The results showed that single and co-pelletization of CCP and CPM performed well. The CBPs had good physiochemical properties in shape, size, and atomic ratios. The higher heating value and energy density of CBPs were 19.25-24.29 MJ/kg and 12.09-14.87 GJ/m3. The ash from CBPs was rich in K2O, CaO and MgO oxides, and the CPM ash had the lowest initial deformation temperature at 1136 °C. The ash samples from CBPs also had different slagging and fouling indexes. The syngas from CBPs mainly contained H2 (6.85-9.30%), CO (12.15-18.85%), and CO2 (10.85-13.75%). The heating value and tar concentration of syngas from CBPs were 3.24-4.32 MJ/m3 and 21.75-30.92 g/m3. The main chemical compounds in tar were styrene, phenol, caffeine, and pyrrole according to GC-MS. These results indicate that CCP and CPM have potential for pelletization and gasification to generate heat needed for coffee bean processing.

Fine and ultrafine particle emission factors and new diagnostic ratios of PAHs for peat swamp forest fires.

Peatland fires are one of the major global sources of atmospheric particles. Emission factors for fine (PM1 and PM2.5) and ultrafine (PM0.1) particles and particle-bound polycyclic aromatic hydrocarbons (PAHs) from plants in the peat swamp forest (PSF), including Melaleuca cajuputi leaves, M. cajuputi branches, M. cajuputi bark, Lepironia articulata (Retz.) Domin, forest leaf litter and peat were measured in a laboratory combustion chamber. From these measurements, new PAH diagnostic ratios for fine and ultrafine particles were proposed for identifying the forest burning source. The new emission factors for PM were PM0.1: 0.03-0.33, PM1: 0.69-2.11 and PM2.5: 1.12-4.18 g/kg; for PM-bound PAHs, the factors were PM0.1: 5.7-166.0, PM1: 31.5-1338.9 and PM2.5: 36.3-3641.1 µg/kg. The predominant PAHs for PSF burning were Pyr, BbF, DBA (in PM0.1), Flu, DBA, BghiPe (in PM1), and BbF, DBA and BghiPe (in PM2.5). We also presented new diagnostic ratios for PSF burning, including BaP/(BaP + Chr): 0.39-0.75, BaP/(BaP + BbF): 0.21-0.47 and BaA/(BaA + Chr): 0.36-0.53. Moreover, the physical and chemical characteristics of ambient fine and ultrafine particles in the Kuan Kreng forest during the 2019 forest fire (FF) and 2021 non-forest fire (NFF) periods were investigated. The mean PM0.1, PM1 and PM2.5 concentrations during the FF period were approximately 3.5-4.4 times as high as those during the 2021 NFF period. New PAH diagnostic ratios of BaP/(BaP + BbF) versus BaP/(BaP + Chr) were able to identify PAH burning sources in PM1 and PM2.5 but were less clear for PM0.1, which was dominated by a single source - M. cajuputi. Chemical mass balance studies identified peat forest burning emissions as the main source of fine and ultrafine particles during the FF period. This study suggests that the new PAH diagnostic ratios can be used to identify the burning source for more precise source apportionment.

Source apportionment of PM2.5 in Thailand's deep south by principal component analysis and impact of transboundary haze.

Atmospheric particulate matter smaller than 2.5 micron (PM2.5) was evaluated at four sites in the lower southern part of Thailand during 2019-2020 to understand the impact of PM2.5 transport from peatland fires in Indonesia on air quality during the southwest monsoon season. Mass concentration and chemical bound-PM, including carbon composition, e.g., organic carbon (OC) and elemental carbon (EC), polycyclic aromatic hydrocarbons (PAHs), and inorganic elements, were analyzed. The PM2.5 emission sources were identified by principal components analysis (PCA). The average mass concentrations of PM2.5 in the normal period, which represents clean background air, from four sites was 3.5-5.1 µg/m3, whereas during the haze period, it rose to 5.4-13.5 µg/m3. During the haze period, both OC and EC were 3.5 times as high as in the normal period. The average total PAHs and BaP-TEQ of PM2.5 during the haze period were ~ 1.3-1.7 and ~ 1.2-1.9 times higher than those in the normal period. The K concentrations significantly increased during haze periods. SO42- dominated throughout the year. The effects of external sources, especially the transboundary haze from peatland fires, were significantly enhanced, because the background air in the study locations was generally clean. PCA indicated that vehicle emission, local biomass burning, and secondary particles played a key role during normal period, whereas open biomass burning dominated during the haze phenomena. This was consistent with the OC/EC and PAH diagnostic ratios. Backward trajectories confirmed that the sources of PM during the haze period were predominantly peatland fires in Sumatra, Indonesia, due to southwest wind.

Source-apportionment and spatial distribution analysis of VOCs and their role in ozone formation using machine learning in central-west Taiwan.

This study assessed the machine learning based sensitivity analysis coupled with source-apportionment of volatile organic carbons (VOCs) to look into new insights of O3 pollution in Yunlin County located in central-west region of Taiwan. One-year (Jan 1 to Dec 31, 2021) hourly mass concentrations data of 54 VOCs, NOX, and O3 from 10 photochemical assessment monitoring stations (PAMs) in and around the Yunlin County were analyzed. The novelty of the study lies in the utilization of artificial neural network (ANN) to evaluate the contribution of VOCs sources in O3 pollution in the region. Firstly, the station specific source-apportionment of VOCs were carried out using positive matrix factorization (PMF)-resolving six sources viz. AAM: aged air mass, CM: chemical manufacturing, IC: Industrial combustion, PP: petrochemical plants, SU: solvent use and VE: vehicular emissions. AAM, SU, and VE constituted cumulatively more than 65% of the total emission of VOCs across all 10 PAMs. Diurnal and spatial variability of source-segregated VOCs showed large variations across 10 PAMs, suggesting for distinctly different impact of contributing sources, photo-chemical reactivity, and/or dispersion due to land-sea breezes at the monitoring stations. Secondly, to understand the contribution of controllable factors governing the O3 pollution, the output of VOCs source-contributions from PMF model along with mass concentrations of NOX were standardized and first time used as input variables to ANN, a supervised machine learning algorithm. ANN analysis revealed following order of sensitivity in factors governing the O3 pollution: VOCs from IC > AAM > VE ≈ CM ≈ SU > PP ≈ NOX. The results indicated that VOCs associated with IC (VOCs-IC) being the most sensitive factor which need to be regulated more efficiently to quickly mitigate the O3 pollution across the Yunlin County.

Fine and ultrafine particle- and gas-polycyclic aromatic hydrocarbons affecting southern Thailand air quality during transboundary haze and potential health effects.

Distribution of PM0.1, PM1 and PM2.5 particle- and gas-polycyclic aromatic hydrocarbons (PAHs) during the 2019 normal, partial and strong haze periods at a background location in southern Thailand were investigated to understand the behaviors and carcinogenic risks. PM1 was the predominant component, during partial and strong haze periods, accounting for 45.1% and 52.9% of total suspended particulate matter, respectively, while during normal period the contribution was only 34.0%. PM0.1 concentrations, during the strong haze period, were approximately 2 times higher than those during the normal period. Substantially increased levels of particle-PAHs for PM0.1, PM1 and PM2.5 were observed during strong haze period, about 3, 5 and 6 times higher than those during normal period. Gas-PAH concentrations were 10 to 36 times higher than those of particle-PAHs for PM2.5. Average total Benzo[a]Pyrene Toxic Equivalency Quotients (BaP-TEQ) in PM0.1, PM1 and PM2.5 during haze periods were about 2-6 times higher than in the normal period. The total accumulated Incremental Lifetime Cancer Risks (ILCRs) in PM0.1, PM1 and PM2.5 for all the age-specific groups during the haze effected scenario were approximately 1.5 times higher than those in non-haze scenario, indicating a higher potential carcinogenic risk. These observations suggest PM0.1, PM1 and PM2.5 were the significant sources of carcinogenic aerosols and were significantly affected by transboundary haze from peatland fires. This leads to an increase in the volume of smoke aerosol, exerting a significant impact on air quality in southern Thailand, as well as many other countries in lower southeast Asia.

Long-term air pollution exposure and decreased kidney function: A longitudinal cohort study in Bangkok Metropolitan Region, Thailand from 2002 to 2012.

BACKGROUND: Kidney dysfunction is considered a cardiovascular risk factor. However, few longitudinal studies have examined the effects of air pollution on kidney function. We evaluated associations between long-term air pollution exposure and estimated glomerular filtration rate (eGFR) using data from a cohort of the Electricity Generating Authority of Thailand (EGAT) study in Bangkok Metropolitan Region, Thailand. METHODS: This longitudinal study included 1839 subjects (aged 52-71 years in 2002) from the EGAT1 cohort study during 2002-2012. eGFR, based on creatinine, was measured in 2002, 2007, and 2012. Annual mean concentrations of air pollutants (i.e., particulate matter with an aerodynamic diameter ≤10 µm (PM10), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO)) prior to a measurement of creatinine were assessed with the ordinary kriging method. Mixed-effect linear regression models were used to assess associations between air pollutants and eGFR, while controlling for potential covariates. eGFR values are expressed as percent change per interquartile range (IQR) increments of each pollutant. RESULTS: Lower eGFR was associated with higher concentrations of PM10 (-1.99%, 95% confidence interval (CI): -3.33, -0.63), SO2 (-4.89%, 95%CI: -6.69, -3.07), and CO (-0.97%, 95%CI: -1.96, 0.03). However, after adjusting for temperature, relative humidity, PM10, and SO2, no significant association was observed between CO and eGFR. CONCLUSIONS: Our findings support the hypothesis that long-term exposure to high concentrations of PM10 and SO2 is associated with the progression of kidney dysfunction in subjects of the EGAT cohort study.

Impact of transport of fine and ultrafine particles from open biomass burning on air quality during 2019 Bangkok haze episode.

Transboundary and domestic aerosol transport during 2018-2019 affecting Bangkok air quality has been investigated. Physicochemical characteristics of size-segregated ambient particles down to nano-particles collected during 2017 non-haze and 2018-2019 haze periods were analyzed. The average PM2.5 concentrations at KU and KMUTNB sites in Bangkok, Thailand during the haze periods were about 4 times higher than in non-haze periods. The highest average organic carbon and elemental carbon concentrations were 4.6 ± 2.1 µg/m3 and 1.0 ± 0.4 µg/m3, respectively, in PM0.5-1.0 range at KU site. The values of OC/EC and char-EC/soot-EC ratios in accumulation mode particles suggested the significant influence of biomass burning, while the nuclei and coarse mode particles were from mixed sources. PAH concentrations during 2018-2019 haze period at KU and KMUTNB were 3.4 ± 0.9 ng/m3 and 1.8 ± 0.2 ng/m3, respectively. The PAH diagnostic ratio of PM2.5 also suggested the main contributions were from biomass combustion. This is supported by the 48-hrs backward trajectory simulation. The higher PM2.5 concentrations during 2018-2019 haze period are also associated with the meteorological conditions that induce thermal inversions and weak winds in the morning and evening. Average values of benzo(a)pyrene toxic equivalency quotient during haze period were about 3-6 times higher than during non-haze period. This should raise a concern of potential human health risk in Bangkok and vicinity exposing to fine and ultrafine particulate matters in addition to regular exposure to traffic emission.

Physicochemical and toxicological characteristics of nanoparticles in aerosols in southern Thailand during recent haze episodes in lower southeast Asia.

Transboundary haze from biomass burning is one of the most important air pollutions in Southeast Asia. The most recent serious haze episode occurred in 2015. Southern Thailand was affected by the haze during September to October when the particulate matter concentration hit a record high. We investigated physical and chemical characteristics of aerosols, including concentration and aerosol size distribution down to sub-micron sizes during haze episodes in 2013 and 2015 and, for reference, an insignificant haze period in 2017. The highest total suspended particulates and PM10 levels in Hat Yai city were 340.1 and 322.5 µg/m3. The mass fractions were nanoparticles (< 100 nm) 3.1%-14.8% and fine particles (< 1 µm) 54.6%-59.1%. Polycyclic aromatic hydrocarbon size distributions in haze periods peaked at 0.75 µm and the concentrations are 2-30 times higher than the normal period. High molecular weight (4-6 ring) PAHs during the haze episode contribute to about 56.7%-88.0% for nanoparticles. The average values of benzo(a)pyrene toxic equivalency quotient were 3.34±2.54ng/m3 in the 2015 haze period but only 0.89±0.17 ng/m3 in 2017. It is clear that particles smaller than 1 µm, were highly toxic. Nanoparticles contributed 19.4%-26.0% of total BaP-TEQ, whereas the mass fraction is 13.1%-14.8%. Thus the nanoparticles were more carcinogenic and can cause greater health effect than larger particles. The fraction of BaP-TEQ for nanoparticles during 2017 non-haze period was nearly the same, while the mass fraction was lower. This indicates that nanoparticles are the significant source of carcinogenic aerosols both during haze and non-haze periods.