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 PM_2.5 concentrations was investigated. Precipitation was negatively correlated with PM_2.5 concentrations. However, winds showed both positive and negative correlations with PM_2.5 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 PM_2.5 by perturbing the emission inputs of the model. Overall, local and non-local sources contributed equally to the total PM_2.5 in Hanoi. Local emission sources comprised 57% of the total PM_2.5 concentrations for the high PM_2.5 pollution levels, while only comprising 42% of the total PM_2.5 for low levels of PM_2.5 concentrations. In Hanoi’s urban areas, local sources contributed more to the total PM_2.5 than non-local sources. In contrast, non-local sources were the main contributors to the PM_2.5 in Hanoi’s rural areas. Additional sensitivity simulations were conducted to identify the main local emission sources of PM_2.5 concentrations in December 2010. The industrial and residential sectors collectively comprised 79% of the total PM_2.5 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 PM_2.5 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 PM_2.5 concentrations in Hanoi.

A multi-model ensemble from the new CMIP6 models was utilized to determine the future changes in precipitation over Southeast Asia (SEA; longitude: 90°E–140°E, latitude: 15°S–30°N). The changes are computed for the three (3) future time slices (2021–2040, 2041–2060, and 2081–2100) under four (4) different scenarios based on the Shared Socioeconomic Pathways (SSPs): 1-2.6, 2-4.5, 3-7.0, and 5-8.5. Our results indicate that future rainfall in the SEA-averaged region could increase by about 4%, 5%, 6%, and 9% towards the end of the century relative to the present-day average (1995–2014) under SSP1-2.6, 2-4.5, 3-7.0, and 5-8.5, respectively. Among all scenarios, SSP3-7.0 widely shows remarkably dry conditions whereas SSP5-8.5 suggests extremely wet conditions on different time scales. A clear dissociation of wet and dry areas is expected in the far-term period (2081–2100). Changes in the annual cycle indicate that monsoon rainfall could experience significant increases. The study also emphasizes the importance of moisture flux convergence (MFC) in determining precipitation patterns across different seasons and regions. The results suggest that MFC plays a crucial role in the projected increase or decrease of rainfall in SEA regions. Spatial correlation of future global mean temperature (GMT) and rainfall have a high positive (negative) correlation in the north (south) latitudes. Changes in rainfall are found to be sensitive to GMT. The responses to future rainfall changes per degree Celsius of warming are at the rate of 8.9%, 6.3%, 3.6%, and 2.7% under SSP1-2.6, 2-4.5, 3-7.0, and 5-8.5, respectively.