Factors associated with community volunteering among adults over the age of 50 in Malaysia.

BACKGROUND: Community volunteering is defined as voluntary participation in activities and services to benefit the local community. It has potential benefits to promote social, physical, and mental well-being, and it enhances productive, healthy, and active aging. The tendency to volunteer varies across individuals and communities. There is limited knowledge of contributing factors influencing volunteering among Malaysian adults over the age of 50. AIMS: The present study aims to assess the association of demographic, cultural, and social factors with volunteering among Malaysian adults over the age of 50. METHODS: A cross-sectional study was conducted in 2020 involving 3,034 Malaysians aged 50 years and above across Malaysia, selected using a multi-stratified random sampling technique based on National Census 2020 data. A validated survey questionnaire to determine the demographic factor (age, sex, education level, employment status, health status, physical disability, and location of residence), cultural factor (ethnicity and religion), and social factor (social support, marital status, living arrangement, mode of transportation) that influence voluntary participation was distributed and collected. The association between these factors and volunteer participation was analysed using logistic regression models to identify significant predictors of voluntary participation among Malaysian adults over the age of 50. RESULTS: A regression model indicates that living in rural areas (OR 2.03, 95% CI 1.63-2.53), having higher education level (Tertiary level: OR 2.77, 95% CI 1.86-4.13), being employed (OR 1.31, 95% CI 1.10-1.56), differences in ethnicity background (Chinese: OR 0.58, 95% CI 0.39-0.86) and ease of transportation (Driving private transport: OR 1.26, 95% CI 1.19-1.32; Public transport: OR 1.07, 95% CI 1.00-1.154) were significantly associated with volunteering with R2 Nagelkerke of 0.147. CONCLUSION: Recognising various factors towards community volunteering should be addressed by policymakers and volunteer organisations to increase volunteer participation from potential adults over the age of 50 in promoting healthy and active ageing.

The impact of climate change on coastal erosion in Southeast Asia and the compelling need to establish robust adaptation strategies.

Climate change alters the climate condition and ocean environment, leading to accelerated coastal erosion and a shift in the coastline shape. From previous studies, Southeast Asia's coastal region is suffering from severe coastal erosion. It is most sensitive and vulnerable to climate change, has broad and densely populated coastlines, and is under ecological pressure. Efforts to systematically review these studies are still insufficient despite many studies on the climate change linked to coastal erosion, the correlation between coastal erosion and coastal communities, and the adaptative measures to address these issues and their effectiveness in Southeast Asia. Therefore, by analyzing the existing literature, the purpose of this review was to bridge the knowledge gap and identify the link between climate change and coastal erosion in Southeast Asia in terms of sea-level rise, storm surge, and monsoon patterns. The RepOrting standards for Systematic Evidence Syntheses (ROSES) guided the study protocol, including articles from the Scopus and Dimension databases. There were five main themes considered: 1) climate change impact, 2) contributing factors to coastal erosion, 3) coastal erosion impact on coastal communities, 4) adaptation measure and 5) effectiveness of adaptation measure using thematical analysis. Subsequently, nine sub-themes were produced from the themes. Generally, in Southeast Asia, coastal erosion was reflected by the rising sea level. Throughout reviewing past literature, an interesting result was explored. Storm surges also had the potential to affect coastal erosion due to alterations of the atmospheric system and seasonal monsoon as the result of climate change. Meanwhile, an assessment of current erosion control strategies in relation to the relative hydrodynamic trend was required to avoid the failure of defence structures and the resulting danger to coastal communities. Systematically reviewing the existing literature was critical, hence it could significantly contribute to the body of knowledge. It provides valuable information for interested parties, such as authorities, the public, researchers, and environmentalists, while comprehending existing adaptation practices. This kind of review could strategize adaptation and natural resource management in line with coastal communities' needs, abilities, and capabilities in response to environmental and other change forms.

How Socio-economic Inequalities Cluster People with Diabetes in Malaysia: Geographic Evaluation of Area Disparities Using a Non-parameterized Unsupervised Learning Method.

Accurate assessments of epidemiological associations between health outcomes and routinely observed proximal and distal determinants of health are fundamental for the execution of effective public health interventions and policies. Methods to couple big public health data with modern statistical techniques offer greater granularity for describing and understanding data quality, disease distributions, and potential predictive connections between population-level indicators with areal-based health outcomes. This study applied clustering techniques to explore patterns of diabetes burden correlated with local socio-economic inequalities in Malaysia, with a goal of better understanding the factors influencing the collation of these clusters. Through multi-modal secondary data sources, district-wise diabetes crude rates from 271,553 individuals with diabetes sampled from 914 primary care clinics throughout Malaysia were computed. Unsupervised machine learning methods using hierarchical clustering to a set of 144 administrative districts was applied. Differences in characteristics of the areas were evaluated using multivariate non-parametric test statistics. Five statistically significant clusters were identified, each reflecting different levels of diabetes burden at the local level, each with contrasting patterns observed under the influence of population-level characteristics. The hierarchical clustering analysis that grouped local diabetes areas with varying socio-economic, demographic, and geographic characteristics offer opportunities to local public health to implement targeted interventions in an attempt to control the local diabetes burden.

GIS-Based Assessments of Neighborhood Food Environments and Chronic Conditions: An Overview of Methodologies.

The industrial revolution and urbanization fundamentally restructured populations' living circumstances, often with poor impacts on health. As an example, unhealthy food establishments may concentrate in some neighborhoods and, mediated by social and commercial drivers, increase local health risks. To understand the connections between neighborhood food environments and public health, researchers often use geographic information systems (GIS) and spatial statistics to analyze place-based evidence, but such tools require careful application and interpretation. In this article, we summarize the factors shaping neighborhood health in relation to local food environments and outline the use of GIS methodologies to assess associations between the two. We provide an overview of available data sources, analytical approaches, and their strengths and weaknesses. We postulate next steps in GIS integration with forecasting, prediction, and simulation measures to frame implications for local health policies. Expected final online publication date for the Annual Review of Public Health, Volume 45 is April 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Hydrological and climate impacts on river characteristics of pahang river basin, Malaysia.

The climate, geomorphological changes, and hydrological elements that have occurred have all influenced future flood episodes by increasing the likelihood and intensity of extreme weather occurrences like extreme precipitation events. River bank erosion is a natural geomorphic process that occurs in all channels. As modifications of sizes and channel shapes are made to transport the discharge, sediment abounds from the stream catchment, and floods are triggered dramatically. The aim of this study is to analyze the flood-sensitive regions along the Pahang River Basin and determine how climate and river changes would have an impact on flooding based on hydrometeorological data and information on river characteristics. The study is divided into three stages, namely the upstream, middle stream, and downstream of the Pahang River. The main primary hydrometeorological data and river characteristics, such as Sinuosity Index, Dominant Slope Range and Entrenchment Ratio collected as important inputs in the statistical analysis process. The statistical analyses, namely HACA, PCA, and Linear Regression applied in river classification. The result showed that the middle stream and downstream areas demonstrated the worst flooding affected by anthropogenic and hydrological factors. Rainfall distribution is one of the factors that contributed to the flood disaster. There are strong correlations between the Sinuosity Index (SI) and water level, which indicates that changes occurred at both planform and stream classification. The best management practices towards sustainability are based on the application of the outcomes that have been obtained after the analysis of Pahang River planform changes, Pahang River geometry, and the local rainfall pattern in the Pahang River Basin.

A practical illustration of spatial smoothing methods for disconnected regions with INLA: spatial survey on overweight and obesity in Malaysia.

BACKGROUND: National prevalence could mask subnational heterogeneity in disease occurrence, and disease mapping is an important tool to illustrate the spatial pattern of disease. However, there is limited information on techniques for the specification of conditional autoregressive models in disease mapping involving disconnected regions. This study explores available techniques for producing district-level prevalence estimates for disconnected regions, using as an example childhood overweight in Malaysia, which consists of the Peninsular and Borneo regions separated by the South China Sea. We used data from Malaysia National Health and Morbidity Survey conducted in 2015. We adopted Bayesian hierarchical modelling using the integrated nested Laplace approximation (INLA) program in R-software to model the spatial distribution of overweight among 6301 children aged 5-17 years across 144 districts located in two disconnected regions. We illustrate different types of spatial models for prevalence mapping across disconnected regions, taking into account the survey design and adjusting for district-level demographic and socioeconomic covariates. RESULTS: The spatial model with split random effects and a common intercept has the lowest Deviance and Watanabe Information Criteria. There was evidence of a spatial pattern in the prevalence of childhood overweight across districts. An increasing trend in smoothed prevalence of overweight was observed when moving from the east to the west of the Peninsular and Borneo regions. The proportion of Bumiputera ethnicity in the district had a significant negative association with childhood overweight: the higher the proportion of Bumiputera ethnicity in the district, the lower the prevalence of childhood overweight. CONCLUSION: This study illustrates different available techniques for mapping prevalence across districts in disconnected regions using survey data. These techniques can be utilized to produce reliable subnational estimates for any areas that comprise of disconnected regions. Through the example, we learned that the best-fit model was the one that considered the separate variations of the individual regions. We discovered that the occurrence of childhood overweight in Malaysia followed a spatial pattern with an east-west gradient trend, and we identified districts with high prevalence of overweight. This information could help policy makers in making informed decisions for targeted public health interventions in high-risk areas.

Spatial clustering of colorectal cancer in Malaysia.

INTRODUCTION: The rise in colorectal cancer (CRC) incidence becomes a global concern. As geographical variations in the CRC incidence suggests the role of area-level determinants, the current study was designed to identify the spatial distribution pattern of CRC at the neighbourhood level in Malaysia. METHOD: Newly diagnosed CRC cases between 2010 and 2016 in Malaysia were identified from the National Cancer Registry. Residential addresses were geocoded. Clustering analysis was subsequently performed to examine the spatial dependence between CRC cases. Differences in socio-demographic characteristics of individuals between the clusters were also compared. Identified clusters were categorized into urban and semi-rural areas based on the population background. RESULT: Most of the 18 405 individuals included in the study were male (56%), aged between 60 and 69 years (30.3%) and only presented for care at stages 3 or 4 of the disease (71.3%). The states shown to have CRC clusters were Kedah, Penang, Perak, Selangor, Kuala Lumpur, Melaka, Johor, Kelantan, and Sarawak. The spatial autocorrelation detected a significant clustering pattern (Moran's Index 0.244, p< 0.01, Z score >2.58). CRC clusters in Penang, Selangor, Kuala Lumpur, Melaka, Johor, and Sarawak were in urbanized areas, while those in Kedah, Perak and Kelantan were in semi-rural areas. CONCLUSION: The presence of several clusters in urbanized and semi-rural areas implied the role of ecological determinants at the neighbourhood level in Malaysia.  Such findings could be used to guide the policymakers in resource allocation and cancer control.

Statistical and spatial analysis for soil heavy metals over the Murray-Darling river basin in Australia.

Heavy metals (HMs) are a vital elements for investigating the pollutant level of sediments and water bodies. The Murray-Darling river basin area located in Australia is experiencing severe damage to increased crop productivity, loss of soil fertility, and pollution levels within the vicinity of the river system. This basin is the most effective primary production area in Australia where agricultural productivity is increased the gross domastic product in the entire mainland. In this study, HMs contaminations are examined for eight study sites selected for the Murray-Darling river basin where the inverse Distance Weighting interpolation method is used to identify the distribution of HMs. To pursue this, four different pollution indices namely the Geo-accumulation index (Igeo), Contamination factor (CF), Pollution load index (PLI), single-factor pollution index (SPLI), and the heavy metal pollution index (HPI) are computed. Following this, the Pearson correlation matrix is used to identify the relationships among the two HM parameters. The results indicate that the conductivity and N (%) are relatively high in respect to using Igeo and PLI indexes for study sites 4, 6, and 7 with 2.93, 3.20, and 1.38, respectively. The average HPI is 216.9071 that also indicates higher level pollution in the Murray-Darling river basin and the highest HPI value is noted in sample site 1 (353.5817). The study also shows that the levels of Co, P, Conductivity, Al, and Mn are mostly affected by HMs and that these indices indicate the maximum HM pollution level in the Murray-Darling river basin. Finally, the results show that the high HM contamination level appears to influence human health and local environmental conditions.

Extensive assessment of climate change impacts on coastal zone paddy growth using multispectral analysis and hydrodynamic modeling.

Global warming has led to sea levels raise (SLRs) and Malaysia is no exception to this problem. Especially for low-lying coastal areas including the Kuala Kedah area which is active in agricultural and fisheries activities. Farmers have had to bear up to 75 % of yield losses due to seawater breaches since 2016. Therefore, this study is designed to assess the impact of seawater encroachment on water quality through spatial technology approaches and hydrodynamic modeling related to the growth of paddy trees. The study was conducted during two different paddy cultivation seasons namely Season 1-2019 and Season 2-2019 which take place in the southwest and northeast monsoon in Kuala Kedah, Malaysia. The study involved three phases, which are the assessment of salinity and pH concentration levels, the assessment of the health of paddy crops through multispectral image analysis involving three plant indices (VI), namely Normalized Difference Vegetation Index (NDVI), Blue Normalized Difference Vegetation Index (BNDVI) and Normalized Difference Red Edge (NDRE), and finally, the assessment of the impact of SLR through the numerical method in MIKE 21 for hydrodynamic modeling considering two conditions that are without mitigation factor (K1) and with existing mitigating factor (K2). According to the findings, the salinity concentration trend is decreasing across the growth stage during Season 1-2019, whereas it is the contrary during Season 2-2019. It was discovered that during the study period for both tidal events, 73 % of the 44 sampling points in Season 1-2019, as opposed to just 3 % in Season 2-2019, were categorized as Class 4 and Class 5. Even though there were fluctuations throughout the observation, the pH reading is still within the allowed range of 6.5 to 9.0 for the estuary area. Following that, the ANOVA analysis proved that salinity concentration a statistically significant difference with tidal variations and pH levels. Moreover, the multispectral image analysis findings revealed that the VI value was correlated with both the yield and the health of the rice crop, with R-square values of 0.842 compared to 0.706 and 0.575 for NDVI and BNDVI values, respectively. It confirmed that NDRE granted a more accurate and reliable measurements. Additionally, the hydrodynamic simulation results demonstrated that, if the mitigation factors were considered in the modeling, overflow seawater to the mainland could be reduced by up to 20 %, reducing the impact of coastal flooding on the local area as well as the nearby rice cultivation area. Ultimately, these three elements-water quality, vegetation index, and hydrodynamic modeling-can assist in identifying the underlying cause of the problem and develop short and long-term solutions.

Relationships of Local Food and Physical Activity Environments With Overweight in 5- to 17-Year-Old Malaysian Children.

Evidence on the associations between built environment and overweight in children outside developed countries is scarce. We examined associations between access to local food and physical activity environments and overweight in 5- to 17-year-old Malaysians in two states with differing overweight levels. Information on children was measured in the National Health and Morbidity Survey 2015 and combined with Geographic Information System-derived data on local food and physical activity environments. Access to the built environment was measured by presence and distance from child's residence. Complete data were available for 880 children. Access to local food outlets and parks was higher and associated with higher occurrence of overweight in children living in the state with higher overweight prevalence. When adjusted for sociodemographic factors, higher presence of and shorter distance to convenience stores and parks were associated with overweight. Both built environment and children's sociodemographic backgrounds should be considered when planning interventions to curb the overweight epidemic in Malaysia.

Households' perceptions and socio-economic determinants of climate change awareness: Evidence from Selangor Coast Malaysia.

Households living in the close vicinity of shoreline are constantly threatened by various climate change impacts. Community awareness towards climate change is a subject of considerable study as adequate knowledge is a preliminary step for adaptation decision making. An important question is how coastal communities perceive climatic variation, sea level rise and coastal hazard impacts and the socio-economic factors that affect their level of awareness. Thus, this research measures the level of awareness and the factors influencing it based on a household survey (n = 1016) that was conducted 10 critically eroded coastal areas in Selangor. Descriptive statistical analysis reveals that more than half of the households have high level of awareness about climatic variation and sea level, however, there is moderate awareness about the coastal hazard impacts such as human causalities and disease transmission. Even though households are more aware of direct coastal hazard impact such as damages to properties and disruption of daily activities. An independent sample T test indicates that respondents who are male, at working age, educated, involve in natural resource dependent occupations, and had prior exposure to extreme coastal hazards have higher levels of awareness. Research indicated about 55% of all sampled households reflected awareness of climate change, 60% households were aware of sea level rise and 47% households were aware of coastal hazard impact. This study recommends that households in Selangor coast need capacity building and climate change awareness initiatives which would assist household to build adaptive capacity, increase resilience and reduce vulnerability to climate change.

El Niño driven haze over the Southern Malaysian Peninsula and Borneo.

The Southeast Asian (SEA) region is no stranger to forest fires - the region has been suffering from severe air pollution (known locally as 'haze') as a result of these fires, for decades. The fires in SEA region are caused by a combination of natural (the El Niño weather pattern) and manmade (slash-and-burn and land clearing for plantations) factors. These fires cause the emissions of toxic aerosols and pollutants that can affect millions of people in the region. Thus, this study aims to identify the impact of the SEA haze on the Southern region of the Malaysian Peninsula and Borneo region of East Malaysia using the entire air quality observation data at surface level in 2015. Overall, the concentration of PM10 was about two-fold higher during the haze period compared to non-haze period. The concentrations of CO, flux of CO and flux of BC were aligned with PM10 during the entire observation period. The wind field and cluster of trajectory indicated that the Southern Malaysian Peninsula and Borneo were influenced mainly from the wildfires and the combustion of peat soil in the Indonesian Borneo. This study finds that wildfires from Borneo impacted the Southern Malaysian Borneo more seriously than that from Sumatra region.

Estimating the Impact of Daily Weather on the Temporal Pattern of COVID-19 Outbreak in India.

The COVID-19 pandemic has spread obstreperously in India. The increase in daily confirmed cases accelerated significantly from ~ 5 additional new cases (ANC)/day during early March up to ~ 249 ANC/day during early June. An abrupt change in this temporal pattern was noticed during mid-April, from which can be inferred a much reduced impact of the nationwide lockdown in India. Daily maximum (T Max), minimum (T Min), mean (T Mean) and dew point temperature (T Dew), wind speed (WS), relative humidity, and diurnal range in temperature and relative humidity during March 01 to June 04, 2020 over 9 major affected cities are analyzed to look into the impact of daily weather on COVID-19 infections on that day and 7, 10, 12, 14, 16 days before those cases were detected (i.e., on the likely transmission days). Spearman's correlation exhibits significantly lower association with WS, T Max, T Min, T Mean, T Dew, but is comparatively better with a lag of 14 days. Support Vector regression successfully estimated the count of confirmed cases (R 2 > 0.8) at a lag of 12-16 days, thus reflecting a probable incubation period of 14 ± 02 days in India. Approximately 75% of total cases were registered when T Max, T Mean, T Min, T Dew, and WS at 12-16 days previously were varying within the range of 33.6-41.3 °C, 29.8-36.5 °C, 24.8-30.4 °C, 18.7-23.6 °C, and 4.2-5.75 m/s, respectively. Thus, we conclude that coronavirus transmission is not well correlated (linearly) with any individual weather parameter; rather, transmission is susceptible to a certain weather pattern. Hence multivariate non-linear approach must be employed instead.

Spatial and temporal risk quotient based river assessment for water resources management.

Malaysia depends heavily on rivers as a source for water supply, irrigation, and sustaining the livelihood of local communities. The evolution of land use in urban areas due to rapid development and the continuous problem of illegal discharge have had a serious adverse impact on the health of the country's waterways. Klang River requires extensive rehabilitation and remediation before its water could be utilised for a variety of purposes. A reliable and rigorous remediation work plan is needed to identify the sources and locations of streams that are constantly polluted. This study attempts to investigate the feasibility of utilising a temporal and spatial risk quotient (RQ) based analysis to make an accurate assessment of the current condition of the tributaries in the Klang River catchment area. The study relies on existing data sets on Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Total Suspended Solids (TSS), and Ammonia (NH3) to evaluate the water quality at thirty strategic locations. Analysis of ammonia pollution is not only based on the limit established for river health but was expanded to include the feasibility of using the water for water intake, recreational activities, and sustaining fish population. The temporal health of Klang River was evaluated using the Risk Matrix Approach (RMA) based on the frequency of RQ > 1 and associated colour-coded hazard impacts. By using the developed RMA, the hazard level for each parameter at each location was assessed and individually mapped using Geographic Information System (GIS). The developed risk hazard mapping has high potential as one of the essential tools in making decisions for a cost-effective river restoration and rehabilitation.

Airborne particles in the city center of Kuala Lumpur: Origin, potential driving factors, and deposition flux in human respiratory airways.

Equatorial warming conditions in urban areas can influence the particle number concentrations (PNCs), but studies assessing such factors are limited. The aim of this study was to evaluate the level of size-resolved PNCs, their potential deposition rate in the human respiratory system, and probable local and transboundary inputs of PNCs in Kuala Lumpur. Particle size distributions of a 0.34 to 9.02 µm optical-equivalent size range were monitored at a frequency of 60 s between December 2016 and January 2017 using an optical-based compact scanning mobility particle sizer (SMPS). Diurnal and correlation analysis showed that traffic emissions and meteorological confounding factors were potential driving factors for changes in the PNCs (Dp ≤1 µm) at the modeling site. Trajectory modeling showed that a PNC <100/cm3 was influenced mainly by Indo-China region air masses. On the other hand, a PNC >100/cm3 was influenced by air masses originating from the Indian Ocean and Indochina regions. Receptor models extracted five potential sources of PNCs: industrial emissions, transportation, aged traffic emissions, miscellaneous sources, and a source of secondary origin coupled with meteorological factors. A respiratory deposition model for male and female receptors predicted that the deposition flux of PM1 (particle mass ≤1 µm) into the alveolar (AL) region was higher (0.30 and 0.25 µg/h, respectively) than the upper airway (UA) (0.29 and 0.24 µg/h, respectively) and tracheobronchial (TB) regions (0.02 µg/h for each). However, the PM2.5 deposition flux was higher in the UA (2.02 and 1.68 µg/h, respectively) than in the TB (0.18 and 0.15 µg/h, respectively) and the AL regions (1.09 and 0.91 µg/h, respectively); a similar pattern was also observed for PM10.

Physicochemical factors and their potential sources inferred from long-term rainfall measurements at an urban and a remote rural site in tropical areas.

Air pollution can be detected through rainwater composition. In this study, long-term measurements (2000-2014) of wet deposition were made to evaluate the physicochemical interaction and the potential sources of pollution due to changes of land use. The rainwater samples were obtained from an urban site in Kuala Lumpur and a highland-rural site in the middle of Peninsular Malaysia. The compositions of rainwater were obtained from the Malaysian Meteorological Department. The results showed that the urban site experienced more acidity in rainwater (avg=277mm, range of 13.8 to 841mm; pH=4.37) than the rural background site (avg=245mm, range of 2.90 to 598mm; pH=4.97) due to higher anthropogenic input of acid precursors. The enrichment factor (EF) analysis showed that at both sites, SO42-, Ca2+ and K+ were less sensitive to seawater but were greatly influenced by soil dust. NH4+ and Ca2+ can neutralise a larger fraction of the available acid ions in the rainwater at the urban and rural background sites. However, acidifying potential was dominant at urban site compared to rural site. Source-receptor relationship via positive matrix factorisation (PMF 5.0) revealed four similar major sources at both sites with a large variation of the contribution proportions. For urban, the major sources influence on the rainwater chemistry were in the order of secondary nitrates and sulfates>ammonium-rich/agricultural farming>soil components>marine sea salt and biomass burning, while at the background site the order was secondary nitrates and sulfates>marine sea salt and biomass burning=soil components>ammonia-rich/agricultural farming. The long-term trend showed that anthropogenic activities and land use changes have greatly altered the rainwater compositions in the urban environment while the seasonality strongly affected the contribution of sources in the background environment.

Local and transboundary factors' impacts on trace gases and aerosol during haze episode in 2015 El Niño in Malaysia.

Southeast Asian haze is a semi-natural phenomenon that chokes the region each year during the dry monsoon season. Smoke-haze episodes caused by the vegetation and peat fires in Indonesia severely affected large parts of Malaysia during the 2015 El Niño phenomenon. This study aimed to evaluate the factors that influenced the concentrations of aerosol and trace gases during the 2015 haze and non-haze period on a semi-urban site in the southern part of Malaysian peninsula that facing Sumatra (Muar, Site A), and on an urban site near to Kuala Lumpur, influenced by the city centre (Cheras, Site B). Local land use data and the cluster of air mass weighted backward trajectory were used to identify the potential factors from local sources and the transboundary region, respectively. The annual median concentrations of PM10 for semi-urban and urban sites were 45.0µg/m3 and 47.0µg/m3, respectively for the study period (Jan-Dec 2015) from the hourly observation dataset. The highest PM10 concentrations during the haze were 358µg/m3 and 415µg/m3 for the two sites, respectively, representing absolutely unhealthy air. However, the trace gases were within the safe threshold. The average concentrations of PM10 and carbon monoxide were two fold higher during the haze than the non-haze episodes on both sites. Nitrogen dioxide was more influenced by haze compared with sulphur dioxide and ozone. The results of the land use change suggest that the local factor can also partially affect the air pollution on the urban area (Site B) but more visible in 2015. The results of the backward trajectory and the wildfire radiative power showed that the smoke-haze episodes that affected Malaysia in 2015 were mainly initiated in the Indonesian Sumatra and Kalimantan regions. This study provides a very useful information towards the impacted region during El Niño haze episode.

Spatial-temporal variations in surface ozone over Ushuaia and the Antarctic region: observations from in situ measurements, satellite data, and global models.

The Antarctic continent is known to be an unpopulated region due to its extreme weather and climate conditions. However, the air quality over this continent can be affected by long-lived anthropogenic pollutants from the mainland. The Argentinian region of Ushuaia is often the main source area of accumulated hazardous gases over the Antarctic Peninsula. The main objective of this study is to report the first in situ observations yet known of surface ozone (O3) over Ushuaia, the Drake Passage, and Coastal Antarctic Peninsula (CAP) on board the RV Australis during the Malaysian Antarctic Scientific Expedition Cruise 2016 (MASEC'16). Hourly O3 data was measured continuously for 23 days using an EcoTech O3 analyzer. To understand more about the distribution of surface O3 over the Antarctic, we present the spatial and temporal of surface O3 of long-term data (2009-2015) obtained online from the World Meteorology Organization of World Data Centre for greenhouse gases (WMO WDCGG). Furthermore, surface O3 satellite data from the free online NOAA-Atmospheric Infrared Sounder (AIRS) database and online data assimilation from the European Centre for Medium-Range Weather Forecasts (ECMWF)-Monitoring Atmospheric Composition and Climate (MACC) were used. The data from both online products are compared to document the data sets and to give an indication of its quality towards in situ data. Finally, we used past carbon monoxide (CO) data as a proxy of surface O3 formation over Ushuaia and the Antarctic region. Our key findings were that the surface O3 mixing ratio during MASEC'16 increased from a minimum of 5 ppb to ~ 10-13 ppb approaching the Drake Passage and the Coastal Antarctic Peninsula (CAP) region. The anthropogenic and biogenic O3 precursors from Ushuaia and the marine region influenced the mixing ratio of surface O3 over the Drake Passage and CAP region. The past data from WDCGG showed that the annual O3 cycle has a maximum during the winter of 30 to 35 ppb between June and August and a minimum during the summer (January to February) of 10 to 20 ppb. The surface O3 mixing ratio during the summer was controlled by photochemical processes in the presence of sunlight, leading to the depletion process. During the winter, the photochemical production of surface O3 was more dominant. The NOAA-AIRS and ECMWF-MACC analysis agreed well with the MASEC'16 data but twice were higher during the expedition period. Finally, the CO past data showed the surface O3 mixing ratio was influenced by the CO mixing ratio over both the Ushuaia and Antarctic regions. Peak surface O3 and CO hourly mixing ratios reached up to ~ 38 ppb (O3) and ~ 500 ppb (CO) over Ushuaia. High CO over Ushuaia led to the depletion process of surface O3 over the region. Monthly CO mixing ratio over Antarctic (South Pole) were low, leading to the production of surface O3 over the Antarctic region.

Characterization of rainwater chemical composition after a Southeast Asia haze event: insight of transboundary pollutant transport during the northeast monsoon.

Open biomass burning in Peninsula Malaysia, Sumatra, and parts of the Indochinese region is a major source of transboundary haze pollution in the Southeast Asia. To study the influence of haze on rainwater chemistry, a short-term investigation was carried out during the occurrence of a severe haze episode from March to April 2014. Rainwater samples were collected after a prolonged drought and analyzed for heavy metals and major ion concentrations using inductively coupled plasma mass spectroscopy (ICP-MS) and ion chromatography (IC), respectively. The chemical composition and morphology of the solid particulates suspended in rainwater were examined using a scanning electron microscope coupled with energy-dispersive X-ray spectroscopy (SEM-EDS). The dataset was further interpreted using enrichment factors (EF), statistical analysis, and a back trajectory (BT) model to find the possible sources of the particulates and pollutants. The results show a drop in rainwater pH from near neutral (pH 6.54) to acidic (

Textural characteristics and sedimentary environment of sediment at eroded and deposited regions in the severely eroded coastline of Batu Pahat, Malaysia.

This study investigates the textural characteristics of sediments collected at eroded and deposited areas of highly severed eroded coastline of Batu Pahat, Malaysia. Samples were taken from systematically selected 23 locations along the 67km stretch of coastline and are extended to the fluvial sediments of the main river of Batu Pahat. Grain size distribution analysis was conducted to identify its textural characteristics and associated sedimentary transport behaviours. Sediments obtained along the coastline were fine-grained material with averaged mean size of 7.25 ϕ, poorly sorted, positively skewed and has wide distributions. Samples from eroded and deposition regions displayed no distinctive characteristics and exhibited similar profiles. The high energy condition transported the sediments as suspension, mostly as pelagic and the sediments were deposited as shallow marine and agitated deposits. The fluvial sediments of up to 3km into the river have particularly similar profile of textural characteristics with the neighbouring marine sediments from the river mouth. Profiles were similar with marine sediments about 3km opposite the main current and can go up to 10km along the current of Malacca Straits.