Attenuated backscatter profiles retrieved by the space borne active lidar CALIOP on-board CALIPSO satellite were used to measure the vertical distribution of smoke aerosols and to compare it against the ECMWF planetary boundary layer height (PBLH) over the smoke dominated region of Indo-Gangetic Plain (IGP), South Asia. Initially, the relative abundance of smoke aerosols was investigated considering multiple satellite retrieved aerosol optical properties. Only the upper IGP was selectively considered for CALIPSO retrieval based on prevalence of smoke aerosols. Smoke extinction was found to contribute 2-50% of the total aerosol extinction, with strong seasonal and altitudinal attributes. During winter (DJF), smoke aerosols contribute almost 50% of total aerosol extinction only near to the surface while in post-monsoon (ON) and monsoon (JJAS), relative contribution of smoke aerosols to total extinction was highest at about 8 km height. There was strong diurnal variation in smoke extinction, evident throughout the year, with frequent abundance of smoke particles at lower height (<4 km) during daytime compared to higher height during night (>4 km). Smoke injection height also varied considerably during rice (ON: 0.71 ± 0.65 km) and wheat (AM: 2.34 ± 1.34 km) residue burning period having a significant positive correlation with prevailing PBLH. Partitioning smoke AOD against PBLH into the free troposphere (FT) and boundary layer (BL) yield interesting results. BL contribute 36% (16%) of smoke AOD during daytime (nighttime) and the BL-FT distinction increased particularly at night. There was evidence that despite travelling efficiently to FT, major proportion of smoke AOD (50-80%) continue to remain close to the surface (<3 km) thereby, may have greater implications on regional climate, air quality, smoke transport and AOD-particulate modelling.
This paper provides detail on sequence analysis of hazy days based on eight monitoring stations from three states (Kelantan, Terengganu and Pahang) in the eastern region of Peninsular Malaysia. The dataset comprises of 1502 daily mean hazy days that had been measured for a decade. The meteorology data namely wind speed, wind direction, air temperature, relative humidity and particulate matter (PM10) were used to comprehend the variability, and the relationship existed amongst variables. The final dataset consists of a summary descriptive analysis and a boxplot, where all five variables were involved, including the minimum, maximum, mean, 1st quartile, median, 3rd quartile and standard deviation are presented. Apart from descriptive analysis, the normality test and histogram were performed as well.
The main aim of this article is to examine empirically the impact of urbanization on carbon dioxide emissions in Singapore from 1970 to 2015. The autoregressive distributed lags (ARDL) approach is applied within the analysis. The main finding reveals a negative and significant impact of urbanization on carbon emissions in Singapore, which means that urban development in Singapore is not a barrier to the improvement of environmental quality. Thus, urbanization enhances environmental quality by reducing carbon emissions in the sample country. The result also highlighted that economic growth has a positive and significant impact on carbon emissions, which suggests that economic growth reduces environmental quality through its direct effect of increasing carbon emissions in the country. Despite the high level of urbanization in Singapore, which shows that 100 % of the populace is living in the urban center, it does not lead to more environmental degradation. Hence, urbanization will not be considered an obstacle when initiating policies that will be used to reduce environmental degradation in the country. Policy makers should consider the country's level of economic growth instead of urbanization when formulating policies to reduce environmental degradation, due to its direct impact on increasing carbon dioxide emissions.
Environmental health in general is referring to the aspect of concern on healthy environment, and the interrelations between environment and human health. Due to the urbanization, urban development is changing the natural environment into a man-made environment. Along with the process, level of environmental quality and human health are decreased. Air quality as reference shows that urban ambient air is more polluted than rural. Due to high density of human population and their activities in urban areas, it produces air pollutants with higher rate as compared to less-developed areas. Air pollutants contribute to various health problems. People suffering from respiratory diseases are the most likely to be affected by air pollution. This paper aimed to examine the rate of respiratory infection among residents in an urban growth corridor (Petaling Jaya-Shah Alam-Klang) and the relationship with the urban land uses, traffic volume and air quality. There were four major types of data used in this study i.e., respiratory infection of the respondents, air quality, land use and traffic volume. A health questionnaire survey was carried out besides the secondary data collection from the various government departments. Relationship analysis was performed between respiratory health and the urban factors (air quality, traffic volume and land uses). The study found out that the relationship between the respiratory health and the urban factors is different in city-wide land use and traffic factors, as compared to the localised air quality and land use factors. To conclude, the urban factors are potentially affecting the respiratory health.
The Proposed New Environmental Quality (Clean Air) Regulation 201X (Draft), which replaces the Malaysia Environmental Quality (Clean Air) 1978, specifies limits to additional pollutants from power generation using fossil fuel. The new pollutants include Hg, HCl, and HF with limits of 0.03, 100, and 15 mg/N-m3 at 6% O2, respectively. These pollutants are normally present in very small concentrations (known as trace elements [TEs]), and hence are often neglected in environmental air quality monitoring in Malaysia. Following the enactment of the new regulation, it is now imperative to understand the TEs behavior and to assess the capability of the existing abatement technologies to comply with the new emission limits. This paper presents the comparison of TEs behavior of the most volatile (Hg, Cl, F) and less volatile (As, Be, Cd, Cr, Ni, Se, Pb) elements in subbituminous and bituminous coal and coal combustion products (CCP) (i.e., fly ash and bottom ash) from separate firing of subbituminous and bituminous coal in a coal-fired power plant in Malaysia. The effect of air pollution control devices configuration in removal of TEs was also investigated to evaluate the effectiveness of abatement technologies used in the plant. This study showed that subbituminous and bituminous coals and their CCPs have different TEs behavior. It is speculated that ash content could be a factor for such diverse behavior In addition, the type of coal and the concentrations of TEs in feed coal were to some extent influenced by the emission of TEs in flue gas. The electrostatic precipitator (ESP) and seawater flue gas desulfurization (FGD) used in the studied coal-fired power plant were found effective in removing TEs in particulate and vapor form, respectively, as well as complying with the new specified emission limits. Implications: Coals used by power plants in Peninsular Malaysia come from the same supplier (Tenaga Nasional Berhad Fuel Services), which is a subsidiary of the Malaysia electricity provider (Tenaga Nasional Berhad). Therefore, this study on trace elements behavior in a coal-fired power plant in Malaysia could represent emission from other plants in Peninsular Malaysia. By adhering to the current coal specifications and installation of electrostatic precipitator (ESP) and flue gas desulfurization, the plants could comply with the limits specified in the Malaysian Department of Environment (DOE) Scheduled Waste Guideline for bottom ash and fly ash and the Proposed New Environmental Quality (Clean Air) Regulation 201X (Draft).
Due to the rapid development of economy and society around the world, the most urban city is experiencing tropospheric ozone or commonly known as ground-level air pollutants. The concentration of air pollutants must be identified as an early precaution step by the local environmental or health agencies. This work aims to apply the artificial neural network (ANN) in estimating the ozone concentration forecast in Bangi. It consists of input variables such as temperature, relative humidity, concentration of nitrogen dioxide, time, UVA and UVB rays obtained from routine monitoring, and data recorded. Ten hidden layer is utilized to obtain the optimized ozone concentration, which is the output layer of the ANN framework. The finding showed that the meteorology condition and emission patterns play an important part in influencing the ozone concentration. However, a single network is sufficient enough to estimate the concentration despite any circumstances. Thus, it can be concluded that ANN is able to give reliable and satisfactory estimations of ozone concentration for the following day.
Dhaka and its neighboring areas suffer from severe air pollution, especially during dry season (November-April). We investigated temporal and directional variations in particulate matter (PM) concentrations in Dhaka, Gazipur, and Narayanganj from October 2012 to March 2015 to understand different aspects of PM concentrations and possible sources of high pollution in this region. Ninety-six-hour backward trajectories for the whole dry season were also computed to investigate incursion of long-range pollution into this area. We found yearly PM10 concentrations in this area about three times and yearly PM2.5 concentrations about six times greater than the national standards of Bangladesh. Dhaka and its vicinity experienced several air pollution episodes in dry season when PM2.5 concentrations were 8-13 times greater than the World Health Organization (WHO) guideline value. Higher pollution and great contribution of PM2.5 most of the time were associated with the north-westerly wind. Winter (November to January) was found as the most polluted season in this area, when average PM10 concentrations in Dhaka, Gazipur, and Narayanganj were 257.1, 240.3, and 327.4 μg m(-3), respectively. Pollution levels during wet season (May-October) were, although found legitimate as per the national standards of Bangladesh, exceeded WHO guideline value in 50 % of the days of that season. Trans-boundary source identifications using concentration-weighted trajectory method revealed that the sources in the eastern Indian region bordering Bangladesh, in the north-eastern Indian region bordering Nepal and in Nepal and its neighboring areas had high probability of contributing to the PM pollutions at Gazipur station.
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 (PM(10), CO, SO(2), O(3), NO(2)) 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, NO(2) and SO(2) are higher at Petaling Jaya (S1) which is due to influence of heavy traffic. The concentrations of PM(10) and O(3,) 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 PM(10), CO, NO(2) and SO(2) at the three sampling stations. Additionally, meteorological factors, particularly the ambient temperature and wind speed, may influence the concentration of PM(10) in the atmosphere.
This study assessed the economic value of health impacts of transboundary smoke haze pollution in Kuala Lumpur and adjacent areas in the state of Selangor, Malaysia. Daily inpatient data from 2005, 2006, 2008, and 2009 for 14 haze-related illnesses were collected from four hospitals. On average, there were 19 hazy days each year during which the air pollution levels were within the Lower Moderate to Hazardous categories. No seasonal variation in inpatient cases was observed. A smoke haze occurrence was associated with an increase in inpatient cases by 2.4 per 10,000 populations each year, representing an increase of 31 percent from normal days. The average annual economic loss due to the inpatient health impact of haze was valued at MYR273,000 ($91,000 USD).
Forecasting higher than expected numbers of health events provides potentially valuable insights in its own right, and may contribute to health services management and syndromic surveillance. This study investigates the use of quantile regression to predict higher than expected respiratory deaths. Data taken from 70,830 deaths occurring in New York were used. Temporal, weather and air quality measures were fitted using quantile regression at the 90th-percentile with half the data (in-sample). Four QR models were fitted: an unconditional model predicting the 90th-percentile of deaths (Model 1), a seasonal/temporal (Model 2), a seasonal, temporal plus lags of weather and air quality (Model 3), and a seasonal, temporal model with 7-day moving averages of weather and air quality. Models were cross-validated with the out of sample data. Performance was measured as proportionate reduction in weighted sum of absolute deviations by a conditional, over unconditional models; i.e., the coefficient of determination (R1). The coefficient of determination showed an improvement over the unconditional model between 0.16 and 0.19. The greatest improvement in predictive and forecasting accuracy of daily mortality was associated with the inclusion of seasonal and temporal predictors (Model 2). No gains were made in the predictive models with the addition of weather and air quality predictors (Models 3 and 4). However, forecasting models that included weather and air quality predictors performed slightly better than the seasonal and temporal model alone (i.e., Model 3 > Model 4 > Model 2) This study provided a new approach to predict higher than expected numbers of respiratory related-deaths. The approach, while promising, has limitations and should be treated at this stage as a proof of concept.
This study examines the three-way linkage relationships between CO2 emission, energy consumption and economic growth in Malaysia, covering the 1975-2015 period. An autoregressive distributed lag approach was employed to achieve the objective of the study and gauged by dynamic ordinary least squares. Additionally, vector error correction model, variance decompositions and impulse response functions were employed to further examine the relationship between the interest variables. The findings show that economic growth is neither influenced by energy consumption nor by CO2 emission. Energy consumption is revealed to be an increasing function of CO2 emission. Whereas, CO2 emission positively and significantly depends on energy consumption and economic growth. This implies that CO2 emission increases with an increase in both energy consumption and economic growth. Conclusively, the main drivers of CO2 emission in Malaysia are proven to be energy consumption and economic growth. Therefore, renewable energy sources ought to be considered by policy makers to curb emission from the current non-renewable sources. Wind and biomass can be explored as they are viable sources. Energy efficiency and savings should equally be emphasised and encouraged by policy makers. Lastly, growth-related policies that target emission reduction are also recommended.
Air pollution has been widely known to have an influence on health of the general population.
Air pollution can result from natural causes, human activities and transboundary air pollution.
Weather and climate play crucial role in determining the pattern of air quality. In recent years,
air pollution and recurrent episodes of haze has become a major concern in Malaysia.
Surveillance data on concentrations of main air pollutants such as carbon dioxide, (CO2),
Nitrogen Dioxide (NO2), Ozone (O3), sulphur dioxide (SO2) and particulate matter (PM10)
were found to be higher during the haze days and this may have an impact on health of the
community as reflected by an increase in hospital admissions particularly the respiratory and
cardiovascular diseases.
The main purpose of this work is to analyze the impact of environmental degradation proxied by CO2 emissions per capita along with some other explanatory variables namely energy use, trade, and human capital on economic growth in selected higher CO2 emissions economies namely China, the USA, India, and Japan. For empirical analysis, annual data over the period spanning between 1971 and 2013 are used. After using relevant and suitable tests for checking data properties, the panel fully modified ordinary least squares (FMOLS) method is employed as an analytical technique for parameter estimation. The panel group FMOLS results reveal that almost all variables are statistically significant, whereby test rejects the null hypotheses of non cointegration, demonstrating that all variables play an important role in affecting the economic growth role across countries. Where two regressors namely CO2 emissions and energy use show significantly negative impacts on economic growth, for trade and human capital, they tend to show the significantly positive impact on economic growth. However, for the individual analysis across countries, the panel estimate suggests that CO2 emissions have a significant positive relationship with economic growth for China, Japan, and the USA, while it is found significantly negative in case of India. The empirical findings of the study suggest that appropriate and prudent policies are required in order to control pollution emerging from areas other than liquefied fuel consumption. The ultimate impact of shrinking pollution will help in supporting sustainable economic growth and maturation as well as largely improve society welfare.
Matched MeSH terms: Air Pollutants/analysis; Air Pollutants/economics*
It is important to assess indoor air quality in school classrooms where the air quality may significantly influence school children's health and performance. This study aims to determine the concentrations of PM2.5 and dust chemical compositions in indoor and outdoor school classroom located in Kuala Lumpur City Centre. The PM2.5 concentration was measured from 19th September 2017-16th February 2018 using an optical PM2.5 sensor. Indoor and outdoor dust was also collected from the school classrooms and ion and trace metal concentrations were analysed using ion chromatography (IC) and inductively couple plasma-mass spectrometry (ICP-MS) respectively. This study showed that the average indoor and outdoor 24 h PM2.5 was 11.2 ± 0.45 µg m-3 and 11.4 ± 0.44 µg m-3 respectively. The 8 h PM2.5 concentration ranged between 3.2 and 28 µg m-3 for indoor and 3.2 and 19 µg m-3 for outdoor classrooms. The highest ion concentration in indoor dust was Ca2+ with an average concentration of 38.5 ± 35.0 µg g-1 while for outdoor dust SO42- recorded the highest ion concentration with an average concentration of 30.6 ± 9.37 µg g-1. Dominant trace metals in both indoor and outdoor dust were Al, Fe and Zn. Principle component analysis-multiple linear regression (PCA-MLR) demonstrated that the major source of indoor dust was road dust (69%), while soil dominated the outdoor dust (74%). Health risk assessment showed that the hazard quotient (HQ) value for non-carcinogenic trace metals was
We report measurements of atmospheric composition over a tropical rainforest and over a nearby oil palm plantation in Sabah, Borneo. The primary vegetation in each of the two landscapes emits very different amounts and kinds of volatile organic compounds (VOCs), resulting in distinctive VOC fingerprints in the atmospheric boundary layer for both landscapes. VOCs over the Borneo rainforest are dominated by isoprene and its oxidation products, with a significant additional contribution from monoterpenes. Rather than consuming the main atmospheric oxidant, OH, these high concentrations of VOCs appear to maintain OH, as has been observed previously over Amazonia. The boundary-layer characteristics and mixing ratios of VOCs observed over the Borneo rainforest are different to those measured previously over Amazonia. Compared with the Bornean rainforest, air over the oil palm plantation contains much more isoprene, monoterpenes are relatively less important, and the flower scent, estragole, is prominent. Concentrations of nitrogen oxides are greater above the agro-industrial oil palm landscape than over the rainforest, and this leads to changes in some secondary pollutant mixing ratios (but not, currently, differences in ozone). Secondary organic aerosol over both landscapes shows a significant contribution from isoprene. Primary biological aerosol dominates the super-micrometre aerosol over the rainforest and is likely to be sensitive to land-use change, since the fungal source of the bioaerosol is closely linked to above-ground biodiversity.
Background: Prolonged exposure of heavy metals in the respirable particulate matter (PM10) from municipal solid waste (MSW) landfills may affect children health. Objective: To investigate the association of reported respiratory symptom with heavy metals in PM10, with heavy metals in fingernails among children residing close to MSW landfills. Methods: Two groups of children age 7 to 12 years old were involved in this cross-sectional study. Those residing within 3 km radius from a landfill were the exposed group and those residing more than 3 km radius as the unexposed group. Questionnaires adapted from American Thoracic Society were applied in the survey. Fingernails were used as biomarker. Ten heavy metals elements in PM and fingernail samples were analysed using inductively coupled plasma mass spectrometry (ICP-MS). Results: The cadmium, chromium, copper, manganese, nickel and lead concentrations in PM around the MSW landfills and residential areas exceeded the Canada and USEPA standard permissible limit. Heavy metals in fingernails (p
In this study, a systematic procedure for establishing the relationship between particulate matter (PM) and microbial counts in four operating rooms (ORs) was developed. The ORs are located in a private hospital on the western coast of Peninsular Malaysia. The objective of developing the systematic procedure is to ensure that the correlation between the PMs and microbial counts are valid. Each of the procedures is conducted based on the ISO, IEST, and NEBB standards. The procedures involved verifying the operating parameters are air change rate, room differential pressure, relative humidity, and air temperature. Upon verifying that the OR parameters are in the recommended operating range, the measurements of the PMs and sampling of the microbes were conducted. The TSI 9510-02 particle counter was used to measure three different sizes of PMs: PM 0.5, PM 5, and PM 10. The MAS-100ECO air sampler was used to quantify the microbial counts. The present study confirms that PM 0.5 does not have an apparent positive correlation with the microbial count. However, the evident correlation of 7% and 15% were identified for both PM 5 and PM 10, respectively. Therefore, it is suggested that frequent monitoring of both PM 5 and PM 10 should be practised in an OR before each surgical procedure. This correlation approach could provide an instantaneous estimation of the microbial counts present in the OR.
This study aims to determine the concentrations of surfactants in the surface microlayer (SML), subsurface water (SSW) and fine mode aerosol (diameter size
Numerous mitigation techniques have been incorporated to capture or remove SO2 with flue gas desulfurization (FGD) being the most common method. Regenerative FGD method is advantageous over other methods due to high desulfurization efficiency, sorbent regenerability, and reduction in waste handling. The capital costs of regenerative methods are higher than those of commonly used once-through methods simply due to the inclusion of sorbent regeneration while operational and management costs depend on the operating hours and fuel composition. Regenerable sorbents like ionic liquids, deep eutectic solvents, ammonium halide solutions, alkyl-aniline solutions, amino acid solutions, activated carbons, mesoporous silica, zeolite, and metal-organic frameworks have been reported to successfully achieve high SO2 removal. The presence of other gases in flue gas, e.g., O2, CO2, NOx, and water vapor, and the reaction temperature critically affect the sorption capacity and sorbent regenerability. To obtain optimal SO2 removal performance, other parameters such as pH, inlet SO2 concentration, and additives need to be adequately governed. Due to its high removal capacity, easy preparation, non-toxicity, and low regeneration temperature, the use of deep eutectic solvents is highly feasible for upscale utilization. Metal-organic frameworks demonstrated highest reported SO2 removal capacity; however, it is not yet applicable at industrial level due to its high price, weak stability, and robust formulation.
Malaysia has experienced several haze events since the 1980s as a consequence of the transboundary movement of air pollutants emitted from forest fires and open burning activities. Hazy episodes can result from local activities and be categorized as "localized haze". General probability distributions (i.e., gamma and log-normal) were chosen to analyze the PM(10) concentrations data at two different types of locations in Malaysia: industrial (Johor Bahru and Nilai) and residential (Kota Kinabalu and Kuantan). These areas were chosen based on their frequently high PM(10) concentration readings. The best models representing the areas were chosen based on their performance indicator values. The best distributions provided the probability of exceedances and the return period between the actual and predicted concentrations based on the threshold limit given by the Malaysian Ambient Air Quality Guidelines (24-h average of 150 μg/m(3)) for PM(10) concentrations. The short-term prediction for PM(10) exceedances in 14 days was obtained using the autoregressive model.