40 research outputs found
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Ozone trends from two decades of ground level observation in Malaysia
We examine the change in surface ozone and its precursor behavior over 20 years at four locations in western Peninsular Malaysia which have undergone urban-commercial development. Trend and correlation analyses were carried out on ozone and oxides of nitrogen observation data over the periods of 1997–2016 as well as the decadal intervals of 1997–2006 and 2007–2016. Diurnal variation composites for decadal intervals were also plotted. Significant increasing ozone concentrations were observed at all locations for the 20-year period, with a range between 0.09 and 0.21 ppb yr−1. The most urbanized location (S3) showed the highest ozone trend. Decadal intervals show that not all stations record significant increasing trends of ozone, with S1 recording decreasing ozone at a rate of −0.44 ppb yr−1 during the latter decade. Correlation analysis showed that only oxides of nitrogen ratios (NO/NO2) had significant inverse relationships with ozone at all stations corresponding to control of ozone by photostationary state reactions. The diurnal composites show that decadal difference in NO/NO2 is mostly influenced by change in nitric oxide concentrations.</jats:p
Trend and status of air quality at three different monitoring stations in the Klang Valley, Malaysia
Over the last decades, the development of the Klang Valley (Malaysia), as an urban commercial and industrial area, has elevated the risk of atmospheric pollutions. There are several significant sources of air pollutants which vary depending on the background of the location they originate from. The aim of this study is to determine the trend and status of air quality and their correlation with the meteorological factors at different air quality monitoring stations in the Klang Valley. The data of five major air pollutants (PM10, CO, SO2, O3, NO2) were recorded at the Alam Sekitar Sdn Bhd (ASMA) monitoring stations in the Klang Valley, namely Petaling Jaya (S1), Shah Alam (S2) and Gombak (S3). The data from these three stations were compared with the data recorded at Jerantut, Pahang (B), a background station established by the Malaysian Department of Environment. Results show that the concentrations of CO, NO2 and SO2 are higher at Petaling Jaya (S1) which is due to influence of heavy traffic. The concentrations of PM10 and O3, however, are predominantly related to regional tropical factors, such as the influence of biomass burning and of ultra violet radiation from sunlight. They can, though, also be influenced by local sources. There are relatively stronger inter-pollutant correlations at the stations of Gombak and Shah Alam, and the results also suggest that heavy traffic flow induces high concentrations of PM10, CO, NO2 and SO2 at the three sampling stations. Additionally, meteorological factors, particularly the ambient temperature and wind speed, may influence the concentration of PM10 in the atmosphere
Future projections of extreme precipitation using Advanced Weather Generator (AWE-GEN) over Peninsular Malaysia
A stochastic downscaling methodology known as the Advanced Weather Generator, AWE-GEN, has been tested at four stations in Peninsular Malaysia using observations available from 1975 to 2005. The methodology involves a stochastic downscaling procedure based on a Bayesian approach. Climate statistics from a multi-model ensemble of General Circulation Model (GCM) outputs were calculated and factors of change were derived to produce the probability distribution functions (PDF). New parameters were obtained to project future climate time series. A multi-model ensemble was used in this study. The projections of extreme precipitation were based on the RCP 6.0 scenario (2081–2100). The model was able to simulate both hourly and 24-h extreme precipitation, as well as wet spell durations quite well for almost all regions. However, the performance of GCM models varies significantly in all regions showing high variability of monthly precipitation for both observed and future periods. The extreme precipitation for both hourly and 24-h seems to increase in future, while extreme of wet spells remain unchanged, up to the return periods of 10–40 years
Spatial patterns and trends of daily rainfall regime in Peninsular Malaysia during the southwest and northeast monsoons : 1975-2004
This study focuses on describing the patterns and trends of five selected rainfall indices in Peninsular Malaysia, based on daily rainfall data from 1975 to 2004. Five rainfall indices based on two main seasons, the northeast and southwest monsoons, were analyzed: total rainfall, frequency of wet days, rainfall intensity, frequency of wet days (extreme frequency), and rainfall intensity (extreme intensity) exceeding the long-term mean 95th percentile. The findings indicated that the eastern areas of the Peninsula were strongly influenced by the northeast monsoon, while the southwest monsoon had the greatest impact on the western part of the Peninsula, particularly the northwest. In studying the trends of these rainfall indices, the non-parametric Mann-Kendall test was used. The serial correlation and cross-correlation structure of the data were accounted for in determining the significance of the Mann-Kendall test results. It was found that there were differences in trend patterns over the Peninsula during both seasons, with a decrease in total rainfall and a significant decrease in frequency of wet days leading to a significant increase in rainfall intensity over the Peninsula, except in eastern areas, during the southwest monsoon. In contrast, a trend of significantly increasing total rainfall and an increase in frequencies of extreme rainfall events during the northeast monsoon caused a significantly increasing trend in rainfall intensity over the Peninsula to be observed. However, no significant trend was observed with respect to extreme intensity during both monsoons over the Peninsula. The findings of this study suggest that rainfall patterns in Peninsular Malaysia are very much affected by the northeast monsoon, based on the larger magnitude of changes observed in the rainfall indices