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Meteorology and emission sources are the two main factors determining concentrations of air pollutants, including fine particulate matter. A regional air quality modeling system was used to analyze the sources of fine-particulate air pollution in Hanoi, Vietnam, in December 2010. The impacts of precipitation and winds on PM2.5 concentrations was investigated. Precipitation was negatively correlated with PM2.5 concentrations. However, winds showed both positive and negative correlations with PM2.5 concentrations, depending on wind direction (WD) and the level of upwind concentrations. Sensitivity simulations were conducted to investigate the contribution of local and non-local emissions sources on total PM2.5 by perturbing the emission inputs of the model. Overall, local and non-local sources contributed equally to the total PM2.5 in Hanoi. Local emission sources comprised 57% of the total PM2.5 concentrations for the high PM2.5 pollution levels, while only comprising 42% of the total PM2.5 for low levels of PM2.5 concentrations. In Hanoi’s urban areas, local sources contributed more to the total PM2.5 than non-local sources. In contrast, non-local sources were the main contributors to the PM2.5 in Hanoi’s rural areas. Additional sensitivity simulations were conducted to identify the main local emission sources of PM2.5 concentrations in December 2010. The industrial and residential sectors collectively comprised 79% of the total PM2.5 concentrations while the transport and power sectors comprised only 2% and 3%, respectively. This is the first case study which used a regional air quality modeling system to provide new and informative insights into PM2.5 air pollution in Hanoi by estimating the contributions of local and non-local emissions sources, as well as the contribution of local emission sectors to PM2.5 concentrations in Hanoi.

In this study, the results for nitrate (NO3−) aerosol during winter from the first-phase model inter-comparison study of Japan’s Study for Reference Air Quality Modeling (J-STREAM) were analyzed. To investigate the models’ external and internal settings, the results were limited to Community Multiscale Air Quality (CMAQ) models. All submitted models generally underestimated NO3− over the urban areas in Japan (e.g., Osaka, Nagoya, and Tokyo); however, some model settings showed distinct behavior. The differences due to the model external settings were larger than the model internal settings. Emissions were an important factor, and emissions configured with lower NOx emissions and higher NH3 emissions led to a higher NO3− concentration as the NH3 was consumed under NH3-rich conditions. The model internal settings of the chemical mechanisms caused differences over China, and this could affect western Japan; however, the difference over Tokyo was lower. To obtain a higher NO3− concentration over the urban areas in Japan, the selection of the HONO option for the heterogenous reaction and the inline calculation of photolysis was desired. For future studies, the external settings of the boundary condition and the meteorological field require further investigation.

A model inter-comparison of secondary pollutant simulations over urban areas in Japan, the first phase of Japan’s study for reference air quality modeling (J-STREAM Phase I), was conducted using 32 model settings. Simulated hourly concentrations of nitric oxide (NO) and nitrogen dioxide (NO2), which are primary pollutant precursors of particulate matter with a diameter of 2.5 µm or less (PM2.5), showed good agreement with the observed concentrations, but most of the simulated hourly sulfur oxide (SO2) concentrations were much higher than the observations. Simulated concentrations of PM2.5 and its components were compared to daily observed concentrations by using the filter pack method at selected ambient air pollution monitoring stations (AAPMSs) for each season. In general, most models showed good agreement with the observed total PM2.5 mass concentration levels in each season and provided goal or criteria levels of model ensemble statistics in warmer seasons. The good performances of these models were associated with the simulated reproducibility of some dominant components, sulfates (SO42−) and ammonium (NH4+). The other simulated PM2.5 components, i.e., nitrates (NO3−), elemental carbon (EC), and organic carbon (OC), often show clear deviations from the observations. The considerable underestimations (approximately 30 µg/m3 for total PM2.5) of all participant models found on heavily polluted days with approximately 40−50 µg/m3 for total PM2.5 indicated some problems in the simulated local meteorology such as the atmospheric stability. This model inter-comparison suggests that these deviations may be owing to a need for further improvements both in the emission inventories and additional formation pathways in chemical transport models, and meteorological conditions also require improvement to simulate elevated atmospheric pollutants. Additional accumulated observations are likely needed to further evaluate the simulated concentrations and improve the model performance.

Climate change, air pollution, and the rapidly aging population are important public health challenges. An understanding of air pollution impacts is imperative for preventing air-pollution-related deaths and illnesses, particularly in vulnerable subgroups such as the increasing population of older adults. To assess the effects of short-term air-pollution exposure on the elderly, we conducted a time-series analysis (1996−2015) of the associations between particulate matter with an aerodynamic diameter of 10) and deaths among elderly residents of Seoul, South Korea, which has a rapidly aging population. We also investigated the synergistic effects of temperature and the lag structures of the effects by sex, cause of death, and season. A 10 μg/m3 rise in the 4-day moving average concentration of PM10 was associated with 0.31% (95% confidence interval (CI): 0.18% to 0.44%), 0.32% (95% CI: 0.09% to 0.55%), and 0.22% (95% CI: −0.23% to 0.66%) increases in non-accidental, cardiovascular, and respiratory mortalities, respectively. We found a significant and strong synergistic effect of PM10 concentration and ambient temperature on mortality in elderly people. PM10 posed an increased risk of non-accidental or cardiovascular mortality with increasing temperature, whereas the associated risk of respiratory death was highest on very cold days. The shape and length of the lag structure varied with the cause of death, sex, and season. Results indicate that elderly people exposed to PM10 are at increased risk of premature death. In the near future, these risks are likely to increase in step with the temperature rise associated with climate change and the continued population aging. Stronger emission controls will be needed to minimize the increased health risks associated with air pollution, especially in regions with high populations of elderly individuals.