Correction: Combined use of principal component analysis/multiple linear regression analysis and artificial neural network to assess the impact of meteorological parameters on fluctuation of selected PM2.5-bound elements.

[This corrects the article DOI: 10.1371/journal.pone.0287187.].

Combined use of principal component analysis/multiple linear regression analysis and artificial neural network to assess the impact of meteorological parameters on fluctuation of selected PM2.5-bound elements.

Based on the data of the State of Global Air (2020), air quality deterioration in Thailand has caused ~32,000 premature deaths, while the World Health Organization evaluated that air pollutants can decrease the life expectancy in the country by two years. PM2.5 was collected at three air quality observatory sites in Chiang-Mai, Bangkok, and Phuket, Thailand, from July 2020 to June 2021. The concentrations of 25 elements (Na, Mg, Al, Si, S, Cl, K, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Ga, As, Se, Br, Sr, Ba, and Pb) were quantitatively characterised using energy-dispersive X-ray fluorescence spectrometry. Potential adverse health impacts of some element exposures from inhaling PM2.5 were estimated by employing the hazard quotient and excess lifetime cancer risk. Higher cancer risks were detected in PM2.5 samples collected at the sampling site in Bangkok, indicating that vehicle exhaust adversely impacts human health. Principal component analysis suggests that traffic emissions, crustal inputs coupled with maritime aerosols, and construction dust were the three main potential sources of PM2.5. Artificial neural networks underlined agricultural waste burning and relative humidity as two major factors controlling the air quality of Thailand.

Direct and indirect effects and feedbacks of biomass burning aerosols over Mainland Southeast Asia and South China in springtime.

Southeast Asia is one of the largest biomass burning (BB) source regions in the world. In order to promote our understanding of BB aerosol characteristics and environmental impacts, this study investigated the emission, composition, evolution, radiative effects, and feedbacks of BB aerosols from Mainland Southeast Asia during 15 March to 15 April 2019 by using an online-coupled regional chemistry/aerosol-climate model RIEMS-Chem. Model results are compared against a variety of ground and vertical observations, indicating a generally good model performance for meteorology, aerosol chemical compositions, and aerosol optical properties. It is found that BB aerosols contributed significantly to regional particulate matter (PM), accounting for up to 90 % of the near-surface PM2.5, BC, and OC concentrations over the BB source regions of north Mainland Southeast Asia and for approximately 30-70 % over wide downwind areas including most areas of southwest China and portions of south China. At the top of atmosphere (TOA), BB aerosols exerted a positive all-sky radiative effect (DREBB) up to 25 W/m2 over north Vietnam and south China, a negative DREBB up to -10 W/m2 over Myanmar, western Thailand, and southwest China. Meanwhile, the indirect radiative effect (IREBB) was consistently negative, with the maximum of -10 W/m2 over downwind areas with cloud coverage, e.g., from north Vietnam to most of south China. The subregional (95-125°E and 10-30°N) and period mean DREBB and IREBB at TOA were estimated to be 0.69 W/m2 and - 0.63 W/m2, respectively, leading a total radiative effect (TREBB) of 0.06 W/m2 at TOA. The radiative effects of BB aerosols led to decreases in sensible and latent heat fluxes, near-surface temperature, PBL height, and wind speed of 6.0 Wm-2, 9.0 Wm-2, 0.26 °C, 38.7 m, and 0.1 m/s, respectively, accompanied with an increase in RH of 1.9 %, averaged over the subregion and the study period. The accumulated precipitation during the study period was apparently reduced by BB aerosols from east Thailand to south China, with the maximum reduction up to 14 cm (exceeding 40 %) over north Vietnam and south China. TREBB tended to increase mean near-surface PM2.5 and its component concentrations, with the maximum percentage increase up to 24 % over the BB source regions of north Mainland Southeast Asia, resulting from the combined effects of dynamic and chemical feedbacks. DREBB generally dominated over IREBB in the feedback-induced PM2.5 concentration changes.

An application of aromatic compounds as alternative tracers of tsunami backwash deposits.

This manuscript provides some comprehensive technical insights regarding the application of polycyclic aromatic hydrocarbons (PAHs) characterized by using Gas-Chromatography Mass Spectrometry. Although numerous chemical species such as water soluble ionic species (e.g. Na+, K+, Cl-, Ca2+, Mg2+) and acid leachable heavy metal fractions (e.g. Fe, Cd, Al, Mo, Sb, As, Cu, Zn, Pb, and Mn) can be used to characterize tsunami deposits, the knowledge of PAH congeners as alternative chemical species for identifying tsunami backwash deposits is strictly limited. This manuscript is exclusive because it aims to find some alternative chemical proxies in order to distinguish tsunami backwash deposits from typical marine sediments. A wide range of diagnostic binary ratios of PAH congeners have been selected in order to characterize Typical Marine Sediments (TMS), Tsunami backwash deposits (TBD), Onshore Tsunami Deposits (OTD) and Coastal Zone Soils (CZS). The state of the art and future perspectives coupled with both advantages and disadvantages of above mentioned chemical tracers will be critically reviewed and further discussed.

Quantifying the contributions of local emissions and regional transport to elemental carbon in Thailand.

We used the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) to simulate elemental carbon (EC) concentrations in Thailand in 2017. The goals were to quantify the respective contributions of local emissions and regional transport outside Thailand to EC pollution in Thailand, and to identify the most effective emission control strategy for decreasing EC pollution. The simulated EC concentrations in Chiang Mai, Bangkok, and Phuket were comparable with the observation data. The correlation coefficient between the simulated and observed EC concentrations was 0.84, providing a good basis for evaluating EC sources in Thailand. The simulated mean EC concentration over the whole country was the highest (1.38 µg m-3) in spring, and the lowest (0.51 µg m-3) in summer. We conducted several sensitivity simulations to evaluate EC sources. Local emissions (including anthropogenic and biomass burning emissions) and regional transport outside Thailand contributed 81.2% and 18.8% to the annual mean EC concentrations, respectively, indicating that local sources played the dominant role for EC pollution in Thailand. Among the local sources, anthropogenic emissions (including the industry, power plant, residential, and transportation sectors) and biomass burning contributed 75.1% and 6.1% to the annual mean EC concentrations, respectively. As the anthropogenic emissions dominated the EC pollution, we performed four sensitivity simulations by reducing 30% of the emissions from each of the industry, power plant, residential, and transportation sectors in Thailand. The results indicated that controlling transportation emissions in Thailand was the most effective way in reducing the EC pollution. The 30% reduction of transportation emissions decreased the annual mean EC concentrations by 12.1%. In contrast, 30% reductions of the residential, industry, and power plant emissions caused 8.4%, 6.4%, and 4.0% decreases in the annual mean EC concentrations, respectively. The model results could potentially provide useful information for air pollution control strategies in Thailand.

Data relating to spatial distribution of polycyclic aromatic hydrocarbons in terrestrial soils of Pakistan and King George Island, Antarctica.

Over the past few decades, polycyclic aromatic hydrocarbons (PAHs) have been analysed in various environmental compartments, however, only limited information is available associated with their terrestrial concentrations in Pakistan and Antarctica. All terrestrial soils from Pakistan (n = 120) were collected from 14th to 2nd April 2017 at Islamabad (n = 30), Abbotabad (n = 10), Taxilla (n = 5), and other places from north to south (n = 75). All Antarctic terrestrial soils (n = 11) were collected from 1st to 25th February 2018 in the southwestern part of King George Island. It is crucial to underline that all samples were both qualitatively and quantitatively identified by using a Shimadzu GCMS-QP2010 Ultra system coupled with a high-speed performance system with ASSP function (i.e., achieving maximum scan speed of 20,000 u sec-1) and having ultra-fast data acquisition speed for comprehensive two-dimensional gas chromatography (GC × GC). Analytical results implicate the influences of vehicle exhausts as a major contributor of PAHs in terrestrial soils of Pakistan. It seems rationale to conclude that 3-ring PAHs display the majority of PAH congeners in terrestrial soils of King George Island.

Application of the AERMOD modeling system for environmental impact assessment of NO2 emissions from a cement complex.

We applied the model of American Meteorological Society-Environmental Protection Agency Regulatory Model (AERMOD) as a tool for the analysis of nitrogen dioxide (NO2) emissions from a cement complex as a part of the environmental impact assessment. The dispersion of NO2 from four cement plants within the selected cement complex were investigated both by measurement and AERMOD simulation in dry and wet seasons. Simulated values of NO2 emissions were compared with those obtained during a 7-day continuous measurement campaign at 12 receptors. It was predicted that NO2 concentration peaks were found more within 1 to 5 km, where the measurement and simulation were in good agreement, than at the receptors 5 km further away from the reference point. The Quantile-Quantile plots of NO2 concentrations in dry season were mostly fitted to the middle line compared to those in wet season. This can be attributed to high NO2 wet deposition. The results show that for both the measurement and the simulation using the AERMOD, NO2 concentrations do not exceed the NO2 concentration limit set by the National Ambient Air Quality Standards (NAAQS) of Thailand. This indicates that NO2 emissions from the cement complex have no significant impact on nearby communities. It can be concluded that the AERMOD can provide useful information to identify high pollution impact areas for the EIA guidelines.