This paper examines the projected changes in rainfall in Southeast Asia (SEA) in the twenty-first century based on the multimodel simulations of the Southeast Asia Regional Climate Downscaling/Coordinated Regional Climate Downscaling Experiment-Southeast Asia (SEACLID/CORDEX-SEA). A total of 11 General Circulation Models (GCMs) have been downscaled using 7 Regional Climate Models (RCMs) to a resolution of 25 km × 25 km over the SEA domain (89.5° E-146.5° E, 14.8° S-27.0° N) for two different representative concentration pathways (RCP) scenarios, RCP4.5 and RCP8.5. The 1976-2005 period is considered as the historical period for evaluating the changes in seasonal precipitation of December-January-February (DJF) and June-July-August (JJA) over future periods of the early (2011-2040), mid (2041-2070) and late twenty-first century (2071-2099). The ensemble mean shows a good reproduction of the SEA climatological mean spatial precipitation pattern with systematic wet biases, which originated largely from simulations using the RegCM4 model. Increases in mean rainfall (10-20%) are projected throughout the twenty-first century over Indochina and eastern Philippines during DJF while a drying tendency prevails over the Maritime Continent. For JJA, projections of both RCPs indicate reductions in mean rainfall (10-30%) over the Maritime Continent, particularly over the Indonesian region by mid and late twenty-first century. However, examination of individual member responses shows prominent inter-model variations, reflecting uncertainty in the projections.

We investigated the performance of RegCM4 in simulating rainfall over Southeast Asia with different combinations of deep-convection and air−sea flux parameterization schemes. Four different gridded rainfall datasets were used for the model assessment. In general, the simulations produced dry biases over the equatorial region and slightly wet biases over mainland Indo-China, except those experiments with the MIT Emanuel cumulus schemes, in which large positive rainfall biases were simulated. However, simulations with the MIT schemes were generally better at reproducing annual rainfall variations. The simulations were not sensitive to the treatment of air−sea fluxes. While the simulations generally produced the rainfall climatology well, all simulations showed stronger inter-annual variability compared to observations. Nevertheless, the time evolution of the inter-annual variations was well reproduced, particularly over the eastern Maritime Continent. Over mainland Southeast Asia, all simulations produced unrealistic rainfall anomaly responses to surface temperature. The lack of summer air−sea interactions in the model resulted in enhanced oceanic forcing over the regions, leading to positive rainfall anomalies during years with warm ocean temperature anomalies. This shortcoming in turn caused much stronger atmospheric forcing on the land surface processes compared to that of the observation. A robust score-ranking system was designed to rank the simulations according to their performance in reproducing different aspects of rainfall characteristics. The results suggest that the simulation with the MIT Emanuel convective scheme and the BATS1e air−sea flux scheme performs better overall compared to the rest of the simulations.

The health implications of PM 2.5 in the tropical region of Southeast Asia (SEA) are significant as PM 2.5 can pose serious health concerns. PM 2.5 concentration and sources here are strongly influenced by changes in the monsoon regime from the south-west quadrant to the north-east quadrant in the region. In this work, PM 2.5 samples were collected at a semi-urban area using a high-volume air sampler at different seasons on 24 h basis. Analysis of trace elements and water-soluble ions was performed using inductively coupled plasma mass spectroscopy (ICP-MS) and ion chromatography (IC), respectively. Apportionment analysis of PM 2.5 was carried out using the United States Environmental Protection Agency (US EPA) positive matrix factorization (PMF) 5.0 and a mass closure model. We quantitatively characterized the health risks posed to human populations through the inhalation of selected heavy metals in PM 2.5 . 48 % of the samples collected exceeded the World Health Organization (WHO) 24 h PM 2.5 guideline but only 19 % of the samples exceeded 24 h US EPA National Ambient Air Quality Standard (NAAQS). The PM 2.5 concentration was slightly higher during the north-east monsoon compared to south-west monsoon. The main trace metals identified were As, Pb, Cd, Ni, Mn, V, and Cr while the main ions were SO 2− 4 , NO − 3 , NH + 4 , and Na. The mass closure model identified four major sources of PM 2.5 that account for 55 % of total mass balance. The four sources are mineral matter (MIN) (35 %), secondary inorganic aerosol (SIA) (11 %), sea salt (SS) (7 %), and trace elements (TE) (2 %). PMF 5.0 elucidated five potential sources: motor vehicle emissions coupled with biomass burning (31 %) were the most dominant, followed by marine/sulfate aerosol (20 %), coal burning (19 %), nitrate aerosol (17 %), and mineral/road dust (13 %). The hazard quotient (HQ) for four selected metals (Pb, As, Cd, and Ni) in PM 2.5 mass was highest in PM 2.5 mass from the coal burning source and least in PM 2.5 mass originating from the mineral/road dust source. The main carcinogenic heavy metal of concern to health at the current location was As; the other heavy metals (Ni, Pb, and Cd) did not pose a significant cancer risk in PM 2.5 mass concentration. Overall, the associated lifetime cancer risk posed by the exposure of hazardous metals in PM 2.5 is 3-4 per 1 000 000 people at this location. Published by CopernicusPublications on behalf of the European Geosciences Union. 598 M. F. Khan et al.: Fine particulate matter in the tropical environment Atmos. Chem. Phys., 16, 597-617, 2016 www.atmos-chem-phys.net/16/597/2016/

Haze is a common phenomenon afflicting Southeast Asia (SEA), including Malaysia, and has occurred almost every year within the last few decades. Haze is associated with high level of air pollutants; it reduces visibility and affects human health in the affected SEA countries. This manuscript aims to review the potential origin, chemical compositions, impacts and mitigation strategies of haze in Malaysia. "Slash and burn" agricultural activities, deforestation and oil palm plantations on peat areas, particularly in Sumatra and Kalimantan, Indonesia were identified as the contributing factors to high intensity combustions that results in transboundary haze in Malaysia. During the southwest monsoon (June to September), the equatorial SEA region experiences a dry season and thus an elevated number of fire events. The prevailing southerly and south-westerly winds allow the cross-boundary transportation of pollutants from the burning areas in Sumatra and Kalimantan in Indonesia, to Peninsular Malaysia and Malaysian Borneo, respectively. The dry periods caused by the El Niño-Southern Oscillation (ENSO) prolong the duration of poor air quality. The size range of particulate matter (PM) in haze samples indicates that haze is dominated by fine particles. Secondary inorganic aerosols (SIA, such as SO42-and NH4+) and organic substances (such as levoglucosan, LG) were the main composition of PM during haze episodes. Local vehicular emissions and industrial activities also contribute to the amount of pollutants and can introduce toxic material such as polyaromatic hydrocarbons (PAHs). Haze episodes have contributed to increasing hospital visits for treatments related to chronic obstructive pulmonary diseases, upper respiratory infections, asthma and rhinitis. Respiratory mortality increased 19% due to haze episodes. Children and senior citizens are more likely to suffer the health impacts of haze. The inpatient cost alone from haze episodes was estimated at around USD 91,000 per year in Malaysia. Almost all economic sectors also experienced losses, with the heaviest losses in the agriculture and tourism sectors. This review suggests several ways forward to reduce haze episodes in SEA and Malaysia. These include economic approaches, research collaborations and science-policy interface. Improving forecasting capabilities can help reduce response time to burning events and subsequently reduce its impacts. Lastly, commitment and involvement by individuals, government agencies, and the entrepreneurial private sectors are crucial to reduce biomass burning (BB) and haze episodes in SEA.