Fifteen-year trends in carbon species and PM2.5 in Seoul, South Korea (2003-2017)

Examining trends and variability of PM2.5-associated organic and elemental carbon in the megacity of Beijing, China: Insight from decadal continuous in-situ hourly observations

Organic carbon (OC) and elemental carbon (EC) in fine particulate matter (PM2.5) play pivotal roles in impacting human health, air quality, and climate change dynamics. Long-term monitoring datasets of OC and EC in PM2.5 are indispensable for comprehending their temporal variations, spatial distribution, evolutionary patterns, and trends, as well as for assessing the effectiveness of clean air action plans. This study presents and scrutinizes a comprehensive 10-year hourly dataset of PM2.5-bound OC and EC in the megacity of Beijing, China, spanning from 2013 to 2022. Throughout the entire study period, the average concentrations of OC and EC were recorded at 8.8 ± 8.7 and 2.5 ± 3.0 μg/m3, respectively. Employing the seasonal and trend decomposition methodology, specifically the locally estimated scatter plot smoothing method combined with generalized least squares with the autoregressive moving average method, the study observed a significant decline in OC and EC concentrations, reducing by 5.8 % yr-1 and 9.9 % yr-1 at rates of 0.8 and 0.4 μg/m3 yr-1, respectively. These declining trends were consistently verified using Theil-Sen method. Notably, the winter months exhibited the most substantial declining trends, with rates of 9.3 % yr-1 for OC and 10.9 % yr-1 for EC, aligning with the positive impact of the implemented clean air action plan. Weekend spikes in OC and EC levels were attributed to factors such as traffic regulations and residential emissions. Diurnal variations showcased higher concentrations during nighttime and lower levels during daytime. Although meteorological factors demonstrated an overall positive impact with average reduction in OC and EC concentrations by 8.3 % and 8.7 %, clean air action plans including the Air Pollution Prevention and Control Action Plan (2013-2017) and the Three-Year Action Plan to Win the Blue Sky War (2018-2020) have more contributions in reducing the OC and EC concentrations with mass drop rates of 87.1 % and 89.2 % and 76.7 % and 96.7 %, respectively. Utilizing the non-parametric wind regression method, significant concentration hotspots were identified at wind speeds of ≤2 m/s, with diffuse signals recorded in the southwestern wind sectors at wind speeds of approximately 4-5 m/s. Interannual disparities in potential source regions of OC and EC were evident, with high potential source areas observed in the southern and northwestern provinces of Beijing from 2013 to 2018. In contrast, during 2019-2022, potential source areas with relatively high values of potential source contribution function were predominantly situated in the southern regions of Beijing. This analysis, grounded in observational data, provides insights into the decadal changes in the major atmospheric composition of PM2.5 and facilitates the evaluation of the efficacy of control policies, particularly relevant for developing countries.

Long-term evolution of carbonaceous aerosols in PM2.5 during over a decade of atmospheric pollution outbreaks and control in polluted central China

Against the backdrop of an uncertain evolution of carbonaceous aerosols in polluted areas over the long term amid air pollution control measures, this 11-year study (2011-2021) investigated fine particulate matter (PM2.5) and carbonaceous components in polluted central China. Organic carbon (OC) and elemental carbon (EC) averaged 16.5 and 3.4 μg/m3, constituting 16 and 3 % of PM2.5 mass. Carbonaceous aerosols dominated PM2.5 (35 and 27 %) during periods of excellent and good air quality, while polluted days witnessed other components as dominants, with a significant decrease in primary organic aerosols and increased secondary pollution. From 2011 to 2021, OC and EC decreased by 53 and 76 %, displaying a high-value oscillation phase (2011-2015) and a low-value fluctuation phase (post-2016). A substantial reduction in high OC and EC concentrations in 2016 marked a milestone in significant air quality improvement attributed to effective control measures, especially targeting OC and EC, evident from their decreased proportion in PM2.5. Primary OC (POC) in winter exhibited the most pronounced reduction (8 % per year), and the seasonal disparities in PM2.5 and carbonaceous components were reduced, showcasing the effectiveness of control measures. Contrary to the more pronounced reduction of EC, which decreased in proportion to PM2.5, secondary OC (SOC) in PM2.5 exhibited an increasing trend. Along with rising OC/EC, SOC/OC, and SOC/EC ratios, this indicates a growing prominence of secondary pollution compared to the decrease in primary pollution. SOC shows an increasing trend with NO2 rise (r = 0.53), without O3 promoting SOC. Positive correlations of SOC with SO2, CO (r = 0.41, 0.59), also highlight their influence on atmospheric conditions, oxidative capacity, and chemical reactions, indirectly impacting SOC formation. The implementation of precise precursor emission reduction measures holds the key to future efforts in mitigating SOC pollution and reducing PM2.5 concentrations, thereby contributing to improved air quality.

Mapping nationwide concentrations of sulfate and nitrate in ambient PM2.5 in South Korea using machine learning with ground observation data

Particulate matter (PM) is a major air pollutant in Northeast Asia, with frequent high PM episodes. To investigate the nationwide spatial distribution maps of PM2.5 and secondary inorganic aerosols in South Korea, prediction models for mapping SO42- and NO3- concentrations in PM2.5 were developed using machine learning with ground-based observation data. Specifically, the random forest algorithm was used in this study to predict the SO42- and NO3- concentrations at 548 air quality monitoring stations located within the representative radii of eight intensive air quality monitoring stations. The average concentrations of PM2.5, SO42-, and NO3- across the entire nation were 17.2 ± 2.8, 3.0 ± 0.6, and 3.4 ± 1.2 μg/m3, respectively. The spatial distributions of SO42- and NO3- concentrations in 2021 revealed elevated concentrations in both the western and central regions of South Korea. This result suggests that SO42- concentrations were primarily influenced by industrial activities rather than vehicle emissions, whereas NO3- concentrations were more associated with vehicle emissions. During a high PM2.5 event (November 19-21, 2021), the concentration of SO42- was primarily influenced by SOX emissions from China, while the concentration of NO3- was affected by NOX emissions from both China and Korea. The methodology developed in this study can be used to explore the chemical characteristics of PM2.5 with high spatiotemporal resolution. It can also provide valuable insights for the nationwide mitigation of secondary PM2.5 pollution.

Variations of oxidative potential of PM2.5 in a medium-sized residential city in South Korea measured using three different chemical assays

Although it is evident that PM2.5 has serious adverse health effects, there is no consensus on what the biologically effective dose is. In this study, the intrinsic oxidative potential (OPm) and the extrinsic oxidative potential (OPv) of PM2.5 were measured using three chemical assays including dithiothreitol (DTT), ascorbic acid (AA), and reduced glutathione (GSH), along with chemical compositions of PM2.5 in South Korea. Among the three chemical assays, only OPmAA showed a statistically significant correlation with PM2.5 while OPmGSH and OPmDTT were not correlated with PM2.5 mass concentration. When the samples were categorized by PM2.5 mass concentrations, the variations in the proportion of Ni, As, Mn, Cd, Pb, and Se to PM2.5 mass closely coincided with changes in OPm across all three assays, suggesting a potential association between these elements and PM2.5 OP. Multiple linear regression analysis identified the significant PM components affecting the variability in extrinsic OPv. OPvAA was determined to be significantly influenced by EC, K+, and Ba while OC and Al were common significant factors for OPvGSH and OPvDTT. It was also found that primary OC was an important variable for OPvDTT while secondary OC significantly affected the variability of OPvGSH.

Strategies for the coordinated control of particulate matter and carbon dioxide under multiple combined pollution conditions

Air pollutants represented by fine particulate matter (PM2.5) and the greenhouse effect caused by carbon dioxide (CO2), are both urgent threats to public health. Tackling the synergistic reduction of PM2.5 and CO2 is critical to achieving improvements in clean air worldwide. A persistent issue is the identification of their common sources and integrated impacts under different environmental conditions. In this study, we investigated the characteristics of the pollution types captured by combined analysis through a comprehensive observational dataset for 2017-2020, and applied machine learning algorithms to quantify the effects of drivers on air pollutants and CO2 formation. More importantly, detailed conclusions were drawn for the joint control of PM2.5-CO2 in multiple pollution types by using ensemble traceability technique. We demonstrated that reducing coal combustion emissions was an effective measure to maximize the benefits of PM2.5-CO2 in weather with low CO2 levels and no PM2.5 pollution. Correspondingly, on days with severe PM2.5 episodes, prioritizing control of vehicle emissions can simultaneously mitigate PM2.5 and CO2. Similar conclusions were found at high CO2 levels, accompanied by a more extensive role of vehicle emissions. Furthermore, a comparison of the differences in source impacts between PM2.5-CO2 and individual species suggests that focusing only on the sources that contribute significantly to one species may result in an underestimation or overestimation of PM2.5-CO2 source impacts. One such implication, as evidenced by our findings, is that synergistic controlling common sources of pollutants should be efficient. Thereby, common source management targeting PM2.5-CO2 under multiple pollution types is a more workable solution to alleviate environmental pollution.

Factors affecting recent PM2.5 concentrations in China and South Korea from 2016 to 2020

This study used observational data and a chemical transport model to investigate the contributions of several factors to the recent change in air quality in China and South Korea from 2016 to 2020. We focused on observational data analysis, which could reflect the annual trend of emission reduction and adjust existing emission amounts to apply it into a chemical transport model. The observation data showed that the particulate matter (PM_2.5) concentrations during winter 2020 decreased by -23.4 % (-14.68 μg/m³) and - 19.5 % (-5.73 μg/m³) in China and South Korea respectively, compared with that during winter 2016. Meteorological changes, the existing national plan for a long-term emission reduction target, and unexpected events (i.e., Coronavirus disease 2019 (COVID-19) in China and South Korea and the newly introduced special winter countermeasures in South Korea from 2020) are considered major factors that may affect the recent change in air quality. The impact of different meteorological conditions on PM_2.5 concentrations was assessed by conducting model simulations by fixing the emission amounts; the results indicated changes of +7.6 % (+4.77 μg/m³) and + 9.7 % (+2.87 μg/m³) in China and South Korea, respectively, during winter 2020 compared to that during winter 2016. Due to the existing and pre-defined long-term emission control policies implemented in both countries, PM_2.5 concentration significantly decreased from winter 2016-2020 in China (-26.0 %; -16.32 μg/m³) and South Korea (-9.1 %; -2.69 μg/m³). The unexpected COVID-19 outbreak caused the PM_2.5 concentrations in China to decrease during winter 2020 by another -5.0 % (-3.13 μg/m³). In South Korea, the winter season special reduction policy, which was introduced and implemented in winter 2020, and the COVID-19 pandemic may have contributed to -19.5 % (-5.92 μg/m³) decrease in PM_2.5 concentrations.

Fossil and non-fossil sources of the carbonaceous component of PM2.5 in forest and urban areas

Atmospheric particulate matter (PM_2.5) can damage human health. Biogenic organic compounds emitted from trees may increase the concentration of PM_2.5 via formation of secondary aerosols. Therefore, the role of biogenic emissions in PM_2.5 formation and the sources of PM_2.5 need to be investigated. Dual carbon isotope and levoglucosan analyses are powerful tools to track the sources of total carbon (TC) in PM_2.5. We collected a total of 47 PM_2.5 samples from 2019 to 2020 inside a pine forest and in urban areas in South Korea. The average δ¹³C and Δ¹⁴C of TC in PM_2.5 at the Taehwa Research Forest (TRF) were - 25.7 and - 380.7‰, respectively, which were not significantly different from those collected at Seoul National University (SNU) in urban areas. Contribution of fossil fuel, C₃-, and C₄- plants to carbonaceous component of PM_2.5 were 52, 27, and 21% at SNU, whereas those were 46, 35, and 19% at TRF, respectively. The biomass burning tracer, levoglucosan, was most abundant in winter and correlated with the contribution of C₄ plants derived carbon. Results indicate that biogenic aerosols emitted from trees is less likely to be an important source of PM_2.5 and that trees can act as a bio-filter to reduce PM_2.5.

Spatiotemporal distribution, trend, forecast, and influencing factors of transboundary and local air pollutants in Nagasaki Prefecture, Japan

The study of PM_2.5 and NO₂ has been emphasized in recent years due to their adverse effects on public health. To better understand these pollutants, many studies have researched the spatiotemporal distribution, trend, forecast, or influencing factors of these pollutants. However, rarely studies have combined these to generate a more holistic understanding that can be used to assess air pollution and implement more effective strategies. In this study, we analyze the spatiotemporal distribution, trend, forecast, and factors influencing PM_2.5 and NO₂ in Nagasaki Prefecture by using ordinary kriging, pearson's correlation, random forest, mann-kendall, auto-regressive integrated moving average and error trend and seasonal models. The results indicated that PM_2.5, due to its long-range transport properties, has a more substantial spatiotemporal variation and affects larger areas in comparison to NO₂, which is a local pollutant. Despite tri-national efforts, local regulations and legislation have been effective in reducing NO₂ concentration but less effective in reducing PM_2.5. This multi-method approach provides a holistic understanding of PM_2.5 and NO₂ pollution in Nagasaki prefecture, which can aid in implementing more effective pollution management strategies. It can also be implemented in other regions where studies have only focused on one of the aspects of air pollution and where a holistic understanding of air pollution is lacking.

Identification of decadal trends and associated causes for organic and elemental carbon in PM2.5 at Canadian urban sites

Chemically resolved data for fine particulate matter (PM_2.5) have been collected across Canada since 2003 through the National Air Pollution Surveillance (NAPS) network. Seven urban sites that have 10-17 years (2003-2019) of PM_2.5 organic carbon (OC) and elemental carbon (EC) data were selected for analysis of decadal trends of OC, EC, and OC/EC ratio using the Ensemble Empirical Mode Decomposition method. Results showed that OC and EC decreased by 0.009-0.072 μg m^-3 yr^-1 and 0.028-0.049 μg m^-3 yr^-1, or 0.77-3.1 % yr^-1 and 3.2-6.7 % yr^-1, respectively, depending on the location. The more rapid decrease in EC than OC resulted in an increasing trend in the OC/EC ratio of 0.03-0.19 yr^-1 across the sites. Macro-tracer approach was used to estimate source attributions of OC and EC from wood burning, fossil fuel combustion, and secondary aerosol formation. Using this approach, it was identified that the significant decrease in EC during the past decade was predominately caused by reduced on-road emissions. The decreased emissions from wood burning and transportation dominated the decline of OC, but such a decline was largely offset by the enhanced secondary organic aerosol (SOA) formation, resulting in much weaker decline of OC than EC. The enhanced SOA formation was due to the increased biogenic emissions fully offsetting the decreased anthropogenic emissions for volatile organic compounds. These findings highlight the need for quantifying biogenic sources of VOCs and other oxidants that are involved in OC formation at the national scale.

Impact of Meteorological Changes on Particulate Matter and Aerosol Optical Depth in Seoul during the Months of June over Recent Decades

The effects of meteorological changes on particulate matter with a diameter of 10 microns or less (PM10, referred to as PM in this study) and aerosol optical depth (AOD) in Seoul were investigated using observational and modeling analysis. AOD satellite data were used, obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS), and PM concentration data were used from in-situ observations. The Modern-Era Retrospective Analysis for Research and Applications (MERRA) and MERRA Version 2 (MERRA-2) were used for meteorological field analysis in modeling and observation data. The results from this investigation show that meteorological effects on PM and AOD were strong in the month of June, revealing a clear decreasing trend in recent decades. The investigation focused on the underlying mechanisms influencing the reduction in PM resulting from meteorological changes during the months of June. The results of this study reveal that decreases in atmospheric stability and humidity induced the aerosol change observed in recent decades. The changes in atmospheric stability and humidity are highly correlated with changes in the intensity of the East Asian summer monsoon (EASM). This suggests that the unstable and drying atmosphere by weakening of the EASM in recent decades has improved PM air quality in Seoul during the summer. The effects of atmospheric stability and humidity were also observed to vary depending on the aerosol species. Humidity only affects hydrophilic aerosols such as sulfate, nitrate, and ammonium, whereas atmospheric stability affects all species of aerosols, including carbonaceous aerosols.