Air pollution has become increasingly significant in the last few decades as a major potential risk to public health in Malaysia due to rapid economic development, coupled with seasonal trans-boundary pollution. Over the years, air pollution in Malaysia has been characterised by large seasonal variations, which are significantly attributed to trans-boundary pollution. The aim of this study is to analyse the long-term temporal dynamic (1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015) of CO, NO x and PM 10 at 20 monitoring stations across Malaysia. Long-term pollutant trends were analysed using the Mann-Kendall test. For potential pollutant source analysis, satellite data and Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) backward trajectories model were employed. In all monitoring sites, we observed that the annual average concentrations of PM 10 were varied, with large coefficient variations. Meanwhile, CO and NOx were found to be less varied, with smaller coefficient variations, except in certain monitoring sites. Long-term analysis trends for CO attested to insignificant decreasing trends in 11 monitoring stations and increasing trends in seven stations. Meanwhile, NO x showed no significant trends in most stations. For PM 10 , five monitoring stations showed increasing trends, whereas 15 other stations showed decreasing trends. HYSPLIT backward trajectory analyses have shown that high seasonal PM 10 levels in most parts of Malaysia are due to trans-boundary pollution. Large-scale intense biomass burning in Indonesia, particularly during the southwest monsoon, has been identified as the main potential source. Long-term air pollution in Malaysia is characterised largely by trans-boundary pollution and is highly seasonal. In urban areas of Malaysian Peninsula, combinations of trans-boundary pollution and local emission sources were notably identified as important sources. Long-term PM 10 pollution in Malaysia shows small but significant decreasing trends. Therefore, to ensure that the effect of air pollution on human health is minimised, special attention needs to be focused on short-term pollution episodes, particularly during trans-boundary pollution events and extreme weather conditions such as El Niño.
Particulate matter (PM10) is an important pollutant particularly in urban environments in Malaysia. In addition, the level of this pollutant was also seasonally significant in most parts of Malaysia, and therefore concern of its effect towards human health is relevant and crucial. Based on a long-term series of PM10 measurement at 20 monitoring locations in Malaysia, this study analysed the spatial and temporal characteristics of PM10 from 1997 to 2015 using standard deviation ellipse and trend analyses. Satellite data and HYSPLIT model were applied to investigate the seasonal potential sources of the pollutant. Results show that annual PM10 average concentrations were greatly varied with large coefficient variation. In term of trend analysis, 11 monitoring sites had shown significant but small decreasing trends. Meanwhile, 7 monitoring sites had shown no significant trends and only 2 monitoring sites showed increasing trends. Trajectory analysis using the HYSPLIT model for the investigation of potential sources of pollutant has shown that high pollution levels of PM10 in Malaysia corresponded to the biomass burning in neighbouring countries. During the southwest monsoon, high PM levels were observed in the central and southern parts of Peninsular Malaysia and Malaysian Borneo, which corresponded to the biomass burning in Indonesia. Based on the long-term analysis, PM10 pollution in Malaysia was characterised by transboundary pollution as well as local sources, especially in urban areas. Despite the recognition of small but significant decreasing trends of PM10 pollution over long-term period, special attention need to be focused on short-term pollution episode, particularly related to transboundary pollution during extreme weather condition such as El Niño event to ensure that human health on a wider population is protected.
Southeast Asia is one of the world’s regions most vulnerable to climate change impacts with low-lying land, more severe floods and droughts, larger populations, higher dependency on agriculture for the economic sector, and low resilience of communities. Therefore, a study on how future climate change will affect this region has been conducted, and the results are provided in this paper. Projected surface temperatures and total precipitation from the baseline period of 2013 up to 2100 for Southeast Asia were investigated using the Global Climate Model (GCM) and the Weather Research Forecast (WRF) v3.9.1.1 modelling systems under RCP4.5 and RCP8.5 future climate scenarios. The results showed that future temperatures were projected to increase under both climate scenarios RCP4.5 and RCP8.5; however, precipitation was projected to decrease. The temperature was projected to increase by 0.93C and 2.50C under RCP4.5 and 8.5. Meanwhile, precipitation greatly varied under the RCP4.5 and RCP8.5 climate scenarios in both monsoonal seasons. We conclude that the change in climate variables, particularly the temperature and precipitation, could potentially increase the vulnerability of this region.
Soil erosion is one of the major issues in the tropics. The erosion is highly affected by the changes in climate and land cover. Future changes in tropical climate, particularly precipitation are expected to influence the potential risks of soil erosion. In the face of rapid changes in rural land cover for agricultural purposes, the combined forcings of land cover and climate changes have been to be a major threat to the soil conservation due to soil erosion. In this study, climate change scenarios at the northern part of Borneo were developed based on the RCP 4.5 and RCP 8.5 climate scenarios using Weather Research Forecast Model (WRF). The future climate projection scenarios of the total precipitation were used to simulate the potential erosion risks in varying land covers in a rural area of Sabah, Malaysia. The RUSLE model was used for soil erosion modelling, which was integrated with IDRISI Selva that allow the analysis and assessment of erosion risk. The variability of future total precipitations in the area of varying land cover types have resulted in varying degree of potential soil erosion risk The average soil loss at the studied area has increased by 262 t/ha/yr with 35.94 % increment in annual precipitation under RCP 8.5 emission scenario. However, under RCP 4.5, 26.65 % decrement in precipitation has reduced the soil loss by 315.1 t/ha/yr. In this rural area, exceptionally high soil erosion was found at steep slopes and thin vegetation covers. Therefore, an appropriate land use planning, soil conservation practices, and strategic adaptation options plan should be created and developed to ensure the sustainability of the soil conservation and enhance rural agricultural productivity.
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