Asian Journal of Atmospheric Environment最新文献

The changes in air quality were investigated in six megacities during the shutdown phases in 2020 and were compared to the same time periods in the previous 10 years (2010–2019) using the data of Modern-Era Retrospective Analysis and Research and Application, version 2 (MERRA-2). The concentrations of PM₁₀ and PM_2.5 were greatly reduced in all megacities during the lockdown in 2020 when compared to the same period in 2019 and in the previous ten years. The highest reduction in PM₁₀ was recorded in Delhi, and São Paulo (21%, and 15% and by 27%, and 9%), when compared with the concentrations in 2019 and in the period 2010–2019, respectively. Similarly, levels of PM_2.5 in Delhi, São Paulo, Beijing, and Mumbai decreased by 20%, 14%, 12%, and 10%, respectively in 2020 when compared to the last ten years. Results indicated that the lockdown is an effective mitigation measure to improve air quality. The MERRA-2 reanalysis dataset could be a vital tool in air quality studies in places with a lack of In-situ observations.

The valence state and concentration of metallic pollutants are important factors contributing to the health effects of respirable particulate matter (PM); however, they have not been well studied. In this study, coarse and fine powder samples of atmospheric PM were collected using a cyclone system at Kanagawa (KO), Saitama (SA), and Fukuoka (FU) in Japan in 2017. Energy dispersive X-ray fluorescence spectroscopy (EDXRF) was used to measure the concentrations of nine metallic elements (Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, and Pb), and X-ray absorption fine structure (XAFS) spectroscopy was used to analyze the valence states of target elements (Cr, Mn, Fe, Cu, and Zn). The EDXRF results indicated that the average contents of Fe, Ti, and Zn were much higher than those of the other six elements in all samples. The XAFS results showed that the major valence states of the elements were Cr(III), Mn(II), Fe(III), Cu(II), and Zn(II). The percentages of Mn(IV), Fe(II), and Cu(0) were higher in KO and SA samples than in FU samples. Mn(0) and Zn(0) were detected in some samples only, and Cu(I) was not detected in any samples. Correlation analysis, principal component analysis, and cluster analysis were performed on the EDXRF and XAFS data of the target elements. The source identification results showed that the sources of metal contaminants in the samples varied considerably between sampling sites and depended on the industrial structure and geographical location of the sampling area. Our findings on the different valence states of the elements may be important for determining the toxicity of PM at different locations.

This study analyzed the BC associated with PM₁ and the contribution of biomass burning to the BC using a portable seven-channel Dual spot Aethalometer in and around Gangtok, the capital city of Sikkim, India, during April 2021. Additionally, CO₂ and meteorological parameters (Temperature, Pressure, and Relative Humidity) was measured. The minimum concentration of BC was found in rural areas where the contribution of biomass burning to the BC is highest. The observed spatial variability of BC over Gangtok Municipal Corporation (GMC) area is minimal. Five days back-trajectory analysis was done using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model to understand the regional influences of air masses at Gangtok. The air mass of the studied region is under influence of trans-regional transport from Indo-Gangetic Plains affecting the BC concentration over the studied region. The black carbon presence in the ambient air near the glacier heights in the Eastern Himalayan region may significantly cause localized warming, thereby enhancing glacier melts. The results have significant bearing for the policy-makers to take corrective steps in addressing the issue of rising BC concentration in high altitude regions. A further detailed study is needed to examine the effect of BC on radiative forcing and its large-scale effect on the East Asian summer monsoon using regional climate models.

A thick foggy weather and worst visibility in Fukuoka, Japan and Busan, South Korea occurred from the late July to early August 2020 due to the Nishinoshima volcanic eruption. In this study, an intensive measurement was made to clarify the chemical nature of the ambient particulate matter (PM) and rain water collected in Fukuoka and Busan during the Nishinoshima volcanic eruption (episode period) and non-eruption (non-episode period). In this study, one week after volcanic eruption, which recorded the usual PM concentration, was defined as the non-episode period. Compared to non-episode period, the PM_2.5 concentration during the episode period increased 4.32 times in Busan and 6.03 times in Fukuoka. The sulfur and chlorine concentrations in the total suspended particles (TSP) and rainwater of episode period were particularly higher than those of non-episode period. The sulfate concentration in PM_2.5 was 1.81 and 27.98 µg/m³ in non-episode and episode periods, respectively. The sulfate concentration during the episode period accounted for 55.4% of PM_2.5 (50.45 µg/m³). Strong correlation between trace elements in TSP and those in rainwater during the episode period indicates that the volcanic ashes could be incorporated into raindrops.

Satellite data is a collection of various atmospheric environmental information through continuous earth observations. Those data observed for a long time-series provide detailed information on environmental changes which has been processed as two-dimensional information representing the atmospheric columnar integrated properties or multi-dimensional data combining space and time. In this review, we investigate the characteristics of various earth observing satellites that have been deriving the global atmospheric information up to date. In terms of applications, the patterns of global atmospheric environmental changes based on statistical and comparative analysis with the long-term observations are also addressed. The spatio-temporal changes in the atmospheric environmental parameters are discussed, in order to provide a quantitative grasp of the statistical relationship. Finally, future developments are put forward. This information will help to understand the atmospheric environment and climate-related interactions.

WRF wind forecasts from four operative schemes used by OHMC (Observatorio HidroMeteorológico de Córdoba), a test scheme (WRF-E) and two daily runs with 4 km horizontal resolution were analyzed. Wind simulations were compared with measurements from eight ground stations with anemometers at 10 m high during the period from June, 2019 to June, 2020. WRF-E incorporates more vertical levels, and an activated topo_wind option. The wind speed results show that WRF overestimates wind speed at most stations and the WRF-E model reduces the BIAS and the RMSE when compared with the operational models. The wind direction analysis shows that the higher the wind speed is, the more accurate the models are. In addition, a wind gust forecasting has been implemented and evaluated in this work. Wind gust correlation coefficient values are between 0.3 and 0.6, RMSE is between 3 and 5 m/s, and a positive BIAS(<2 m/s) at most stations.

This study present the factors controlling the aldehyde emission (formaldehyde, acetaldehyde, propionaldehyde, etc.) from plant species such as Pinus densiflora, Pinus koraiensis, Quercus acutissima, Quercus variabilis, Ginkgo biloba, and Oryza sativa. Even in the same tree species illustrate the emission rate variation of as much as 30 ~ 40%. The β-value, a parameter quantifying the temperature and emission correlation, were assessed as 0.07, 0.05 for formaldehyde and acetaldehyde, respectively. The coefficient of correlation was 0.4 and 0.5. for Quercus variabilis. In addition, the correlation between PAR (photosynthetically active radiation) and the emission is assessed close to the temperature impact on the emission. The emission of formaldehyde and acetaldehyde from P. densiflora, P. koraiensis, and Q. variabilis also depends on temperature and PAR. The ERs of total aldehydes of P. koraiensis are assessed at the level of 357.2 ng gdw⁻¹ h⁻¹, followed by propionaldehyde (110.6 ng gdw⁻¹ h⁻¹), acetaldehyde (102.5 ng gdw⁻¹ h⁻¹), and formaldehyde (73.66 ng gdw⁻¹ h⁻¹).

The spatial monitoring of submicron particles has become an essential issue due to their negative effects on human health. However, the use of high-cost and high-grade measurement instruments is a challenging investment cost. Thus, a cost-effective optical particle counter (OPC), which is improved measurement quality, has become a good candidate. In this study, two cost-effective OPCs, coupled with a heated inlet tube to reduce the effect of humidity on its measurements, were applied in the field to measure ambient PM₁₀, PM_2.5, and PM₁ over 1 month. Their 1-h-average and 24-h-average data were compared with those obtained from a reference-grade OPC and a beta attenuation monitor (BAM). In particular, the correlations between the measurement data obtained from them, the differences in the mean values of these data, and the relative errors were evaluated. The PM_2.5 data obtained from cost-effective OPCs were comparable to those from BAM at even under high humidity conditions, except for rainy days. The data obtained from the cost-effective OPCs also showed good correlations and low relative errors (i.e., < 7%) compared to the reference-grade OPC, with no significant difference in mean values in terms of the PM_2.5 and PM₁ data. Although the measurement of PM₁₀ by the cost-effective OPCs showed lower quality than PM_2.5 and PM₁, the relative errors were still acceptable (i.e., < 18%) compared with those in other studies. Therefore, the cost-effective OPC coupled with a heated inlet tube has the potential to serve as a real-time monitoring instrument for ambient PM_2.5 and PM₁.

This study presents an analysis of the atmospheric footprint sensitivities and CO₂ enhancements measured at three in situ stations in South Korea (Anmyeondo (AMY), Gosan (JGS), Ulleungdo (ULD)) using the KIM-STILT and WRF-STILT atmospheric transport models. Monthly aggregated footprints for each station were compared between the models for July and December 2020. The footprints revealed major source regions and the sensitivity of atmospheric mole fractions at the receptor to upstream surface fluxes. In July, both models showed similar major source regions for the AMY station, including Korea, the Yellow Sea, and Japan. However, a discrepancy was observed in the Eastern Pacific Ocean, with KIM-STILT showing larger sensitivity compared to WRF-STILT. In December, both models indicated strong sensitivity over Northeast and Eastern China, but KIM-STILT exhibited smaller sensitivities towards Northwestern China and Mongolia compared to WRF-STILT. At station ULD in July, both models exhibited comparable source regions, but a notable difference was found in Southeast China, where KIM-STILT showed stronger sensitivity. For the JGS station, both models agreed on major sources, but WRF-STILT demonstrated stronger sensitivity over North and Northeastern China. Regarding CO₂ enhancements, both models generally underestimated the amplitude of CO₂ enhancements, especially in July. However, in December, there was better agreement with observed data. The models were able to reproduce the phase of measured ΔCO₂ reasonably well despite the underestimation of CO₂ amplitudes. The contribution of biospheric CO₂ to the observed enhancements, along with fossil-fuel emissions, was highlighted. In specific cases with significant CO₂ enhancements, the models provided varying estimates of CO₂ff values, particularly in the source regions of Eastern China. The differences in sensitivity estimations emphasize the need for further investigation to understand the underlying factors causing disparities. Overall, this study provides valuable insights into the potential advantages of each model in capturing dispersion patterns in specific regions, highlighting the importance of understanding these differences to improve the accuracy of atmospheric transport models. Further work is necessary to address the observed disparities and enhance our understanding of the transport models in the studied regions.

Behind their role as carbon sinks, mangrove soil can also emit greenhouse gases (GHG) through microbial metabolism. GHG flux measurments of mangroves are scarce in many locations, including Indonesia, which has one of the world’s most extensive and carbon-rich mangrove forests. We measured GHG fluxes (CO₂, CH₄, and N₂O) during the wet season in Benoa Bay, Bali, a bay with considerable anthropogenic pressures. The mangroves of this Bay are dominated by Rhizophora and Sonneratia spp and have a characteristic zonation pattern. We used closed chambers to measure GHG at the three mangrove zones within three sites. Emissions ranged from 1563.5 to 2644.7 µmol m⁻² h⁻¹ for CO₂, 10.0 to 34.7 µmol m⁻² h⁻¹ for CH₄, and 0.6 to 1.4 µmol m⁻² h⁻¹ for N₂O. All GHG fluxes were not significantly different across zones. However, most of the GHG fluxes decreased landward to seaward. Higher soil organic carbon was associated with larger CO₂ and CH₄ emissions, while lower redox potential and porewater salinity were associated with larger CH₄ emissions. These data suggest that soil characteristics, which are partially determined by location in the intertidal, significantly influence GHG emissions in soils of these mangroves.