Due to the increase of the human population and the rapid industrial growth in the past few decades, air quality monitoring is essential to assess the pollutant levels of an area. However, monitoring air quality in a high-density area like Sunway City, Selangor, Malaysia is challenging due to the limitation of the local monitoring network. To establish a comprehensive data for air pollution in Sunway City, a mobile monitoring campaign was employed around the city area with a duration of approximately 6 months, from September 2018 to March 2019. Measurements of air pollutants such as carbon dioxide (CO2) and nitrogen dioxide (NO2) were performed by using mobile air pollution sensors facilitated with a GPS device. In order to acquire a more in-depth understanding on traffic-related air pollution, the measurement period was divided into two different time blocks, which were morning hours (8 a.m.-12 p.m.) and afternoon hours (3 p.m.-7 p.m.). The data set was analysed by splitting Sunway City into different zones and routes to differentiate the conditions of each region. Meteorological variables such as ambient temperature, relative humidity, and wind speed were studied in line with the pollutant concentrations. The air quality in Sunway City was then compared with various air quality standards such as Malaysian Air Quality Standards and World Health Organisation (WHO) guidelines to understand the risk of exposure to air pollution by the residence in Sunway City.
The mechanistic modeling of the sulfation reaction between fly ash-based sorbent and SO2 is a challenging task due to a variety reasons including the complexity of the reaction itself and the inability to measure some of the key parameters of the reaction. In this work, the possibility of modeling the sulfation reaction kinetics using a purely data-driven neural network was investigated. Experiments on SO2 removal by a sorbent prepared from coal fly ash/CaO/CaSO4 were conducted using a fixed bed reactor to generate a database to train and validate the neural network model. Extensive SO2 removal data points were obtained by varying three process variables, namely, SO2 inlet concentration (500-2000 mg/L), reaction temperature (60-80 degreesC), and relative humidity (50-70%), as a function of reaction time (0-60 min). Modeling results show that the neural network can provide excellent fits to the SO2 removal data after considerable training and can be successfully used to predict the extent of SO2 removal as a function of time even when the process variables are outside the training domain. From a modeling standpoint, the suitably trained and validated neural network with excellent interpolation and extrapolation properties could have immediate practical benefits in the absence of a theoretical model.
Matched MeSH terms: Air Pollutants/isolation & purification*
High performance sorbents for flue gas desulfurization can be synthesized by hydration of coal fly ash, calcium sulfate, and calcium oxide. In general, higher desulfurization activity correlates with higher sorbent surface area. Consequently, a major aim in sorbent synthesis is to maximize the sorbent surface area by optimizing the hydration conditions. This work presents an integrated modeling and optimization approach to sorbent synthesis based on statistical experimental design and two artificial intelligence techniques: neural network and genetic algorithm. In the first step of the approach, the main and interactive effects of three hydration variables on sorbent surface area were evaluated using a full factorial design. The hydration variables of interest to this study were hydration time, amount of coal fly ash, and amount of calcium sulfate and the levels investigated were 4-32 h, 5-15 g, and 0-12 g, respectively. In the second step, a neural network was used to model the relationship between the three hydration variables and the sorbent surface area. A genetic algorithm was used in the last step to optimize the input space of the resulting neural network model. According to this integrated modeling and optimization approach, an optimum sorbent surface area of 62.2m(2)g(-1) could be obtained by mixing 13.1g of coal fly ash and 5.5 g of calcium sulfate in a hydration process containing 100ml of water and 5 g of calcium oxide for a fixed hydration time of 10 h.
Indoor air quality (IAQ) has been the object of several studies due to its adverse health effects on children. Methods. A cross-sectional comparative study was carried out among Malay children in Balakong (2 studied preschools) and Bangi (2 comparative preschools), Selangor, with the aims of determining IAQ and its association with respiratory health. 61 and 50 children aged 5-6 years were selected as studied and comparative groups. A questionnaire was used to obtain an exposure history and respiratory symptoms. Lung function test was carried out. IAQ parameters obtained include indoor concentration of particulate matter (PM), volatile organic compounds (VOCs), carbon monoxide (CO), carbon dioxide (CO2), temperature, air velocity (AV), and relative humidity. Results. There was a significant difference between IAQ in studied and comparative preschools for all parameters measured (P < 0.001) except for CO2 and AV. Studied preschools had higher PM and CO concentration. FVC, FEV1, FVC% and FEV1% predicted values were significantly lower among studied group. Exposures to PM, VOCs, and CO were associated with wheezing. Conclusion. The finding concluded that exposures to poor IAQ might increase the risk of getting lung function abnormality and respiratory problems among study respondents.
Economic losses due to health-related implications of air pollution were huge and incurred significant burdens towards healthcare providers. The objective of this study is to systematically review published literature on the financial implications of air pollution on health in Asia. Four databases: PubMed, Scopus, NHS Economic Evaluation Database (NHS EED), and Web of Science (WoS) were used to identify all the relevant articles. It was limited to all articles that had been published in the respected databases from January 2007 until March 2017. Twenty-four articles were included in this review. Five of the 24 studies (20.8%) reported financial implications of air pollution-related disease through value of statistical life (VOSL) which ranged from USD180 million to USD2.2 billion, six (25%) studies used cost of illness (COI) to evaluate air pollution-related morbidity and found that the cost ranged from USD5.4 million to USD9.1 billion. Another six studies (25%) used a combination of VOSL and COI for both mortality and morbidity valuation and found that the financial implications ranging from USD253 million to USD2.9 billion. Thirteen (54.2%) studies reported healthcare cost associated with both hospital admission and outpatient visit, five (20.1%) on hospital admission only, and one (4.2%) on outpatient visit only. Economic impacts of air pollution can be huge with significant deterioration of health among the Asians.
Matched MeSH terms: Air Pollutants/analysis; Air Pollutants/economics
Introduction During haze, at what level should Air Pollutant Index (API) showed, public
or private school be closed is not without controversy and is very much
debated. Therefore, the aim of this paper is to objectively quantify the
potential inhaled dose of PM10 associated with exposure at school and home
microenvironments during haze. The result of the health risk assessment will
be used to propose the API level for closing the school during haze episode.
Methods A hypothetical haze exposure scenario was created using the breakpoints of
PM10 concentration for calculation of API and respective inhaled dose during
haze. To determine the potential inhaled dose, we have considered many
factors that include time spent for specific physical intensity at school and
home microenvironments, age-specific and physical intensity-specific
inhalation rate (m3/min), and the indoor/outdoor ratio of PM10. To calculate
risk quotient (RQ), the inhaled dose was compared with the health reference
dose computed based on the concentration of PM10 in the Malaysian
Ambient Air Quality Standard.
Results When considering the specific exposure at each microenvironment (school
and home), the potential inhaled dose of PM10 was substantially lower when
school is closed for both primary and secondary school. The calculated risk
quotient (RQ) indicates that primary school children are likely to be affected
at slightly lower PM10 concentration (equivalent to API of 197) as compared
to secondary school children. Short duration of high physical activity
intensity during school breaks has contributed to a large proportion of inhaled
dose among school children indicating the important to avoid physical
activities during haze.
Conclusion Based on the assessment, taking into account the uncertainty of risk
assessment methodology, we proposed school to be closed when API reach
190 for both primary and secondary schools. These findings and
recommendations are only valid for naturally ventilated school and applicable
in the context of the current API calculation system and the existing
Recommended Air Quality Guideline values in Malaysia.
The occurrence of n-alkanoic acids, amides, and nitriles in samples of aerosol particulate matter from Kuala Lumpur and Santiago suggests that emissions from cooking and biomass burning are the primary sources of these organic markers in the atmosphere. It is proposed that fatty acids react with ammonia during biomass burning or combustion to produce amides and nitriles, which can be applied as useful biomarker tracers. To test this hypothesis, nonadecanoic acid and hexadecanamide were used as reactants in hydrous pyrolysis experiments. These experiments produced amides and nitriles and indicated that ammonia is an essential agent in their formation. Thus amides and nitriles are of utility as indicators for input from combustion and biomass burning in the ambient atmosphere.
The objective of this study is to identify spatial and temporal patterns in the air quality at three selected Malaysian air monitoring stations based on an eleven-year database (January 2000-December 2010). Four statistical methods, Discriminant Analysis (DA), Hierarchical Agglomerative Cluster Analysis (HACA), Principal Component Analysis (PCA) and Artificial Neural Networks (ANNs), were selected to analyze the datasets of five air quality parameters, namely: SO2, NO2, O3, CO and particulate matter with a diameter size of below 10 μm (PM10). The three selected air monitoring stations share the characteristic of being located in highly urbanized areas and are surrounded by a number of industries. The DA results show that spatial characterizations allow successful discrimination between the three stations, while HACA shows the temporal pattern from the monthly and yearly factor analysis which correlates with severe haze episodes that have happened in this country at certain periods of time. The PCA results show that the major source of air pollution is mostly due to the combustion of fossil fuel in motor vehicles and industrial activities. The spatial pattern recognition (S-ANN) results show a better prediction performance in discriminating between the regions, with an excellent percentage of correct classification compared to DA. This study presents the necessity and usefulness of environmetric techniques for the interpretation of large datasets aiming to obtain better information about air quality patterns based on spatial and temporal characterizations at the selected air monitoring stations.
Methane (CH₄) is one of the most relevant greenhouse gases and it has a global warming potential 25 times greater than that of carbon dioxide (CO₂), risking human health and the environment. Microbial CH₄ oxidation in landfill cover soils may constitute a means of controlling CH₄ emissions. The study was intended to quantify CH₄ and CO₂ emissions rates at the Sungai Sedu open dumping landfill during the dry season, characterize their spatial and temporal variations, and measure the CH₄ oxidation associated with the landfill cover soil using a homemade static flux chamber. Concentrations of the gases were analyzed by a Micro-GC CP-4900. Two methods, kriging values and inverse distance weighting (IDW), were found almost identical. The findings of the proposed method show that the ratio of CH₄ to CO₂ emissions was 25.4 %, indicating higher CO₂ emissions than CH₄ emissions. Also, the average CH₄ oxidation in the landfill cover soil was 52.5 %. The CH₄ and CO₂ emissions did not show fixed-pattern temporal variation based on daytime measurements. Statistically, a negative relationship was found between CH₄ emissions and oxidation (R(2) = 0.46). It can be concluded that the variation in the CH₄ oxidation was mainly attributed to the properties of the landfill cover soil.
Methane (CH₄) emissions and oxidation were measured at the Air Hitam sanitary landfill in Malaysia and were modeled using the Intergovernmental Panel on Climate Change waste model to estimate the CH₄ generation rate constant, k. The emissions were measured at several locations using a fabricated static flux chamber. A combination of gas concentrations in soil profiles and surface CH₄ and carbon dioxide (CO₂) emissions at four monitoring locations were used to estimate the CH₄ oxidation capacity. The temporal variations in CH₄ and CO₂ emissions were also investigated in this study. Geospatial means using point kriging and inverse distance weight (IDW), as well as arithmetic and geometric means, were used to estimate total CH₄ emissions. The point kriging, IDW, and arithmetic means were almost identical and were two times higher than the geometric mean. The CH₄ emission geospatial means estimated using the kriging and IDW methods were 30.81 and 30.49 gm(−2) day(−1), respectively. The total CH₄ emissions from the studied area were 53.8 kg day(−1). The mean of the CH₄ oxidation capacity was 27.5 %. The estimated value of k is 0.138 year(−1). Special consideration must be given to the CH₄ oxidation in the wet tropical climate for enhancing CH₄ emission reduction.
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
Carbon emissions from drained peatlands converted to agriculture in South-East Asia (i.e., Peninsular Malaysia, Sumatra and Borneo) are globally significant and increasing. Here, we map the growth of South-East Asian peatland agriculture and estimate CO2 emissions due to peat drainage in relation to official land-use plans with a focus on the reducing emissions from deforestation and degradation (REDD+)-related Indonesian moratorium on granting new concession licences for industrial agriculture and logging. We find that, prior to 2010, 35% of South-East Asian peatlands had been converted to agriculture, principally by smallholder farmers (15% of original peat extent) and industrial oil palm plantations (14%). These conversions resulted in 1.46-6.43 GtCO2 of emissions between 1990 and 2010. This legacy of historical clearances on deep-peat areas will contribute 51% (4.43-11.45 GtCO2 ) of projected future peatland CO2 emissions over the period 2010-2130. In Indonesia, which hosts most of the region's peatland and where concession maps are publicly available, 70% of peatland conversion to agriculture occurred outside of known concessions for industrial plantation development, with smallholders accounting for 60% and industrial oil palm accounting for 34%. Of the remaining Indonesian peat swamp forest (PSF), 45% is not protected, and its conversion would amount to CO2 emissions equivalent to 0.7%-2.3% (5.14-14.93 Gt) of global fossil fuel and cement emissions released between 1990 and 2010. Of the peatland extent included in the moratorium, 48% was no longer forested, and of the PSF included, 40%-48% is likely to be affected by drainage impacts from agricultural areas and will emit CO2 over time. We suggest that recent legislation and policy in Indonesia could provide a means of meaningful emission reductions if focused on revised land-use planning, PSF conservation both inside and outside agricultural concessions, and the development of agricultural practices based on rehabilitating peatland hydrological function.
The indoor and outdoor radon concentrations in Cameron Highlands (Peninsular Malaysia) and Ranau (East Malaysia) were measured. The measurements were carried out using passive method based on CR-39 solid state nuclear track detector (SSNTD) (for indoor measurements in Cameron Highlands) and active method using continuous radon/thoron progeny monitor (for indoor and outdoor measurements in Ranau and outdoor measurements in Cameron Highlands). The mean indoor radon concentrations in Cameron Highlands and Ranau were 50 Bqm-3 and 1.5 Bqm-3, respectively. The mean indoor radon concentration in Cameron Highlands was slightly higher compare to the world average. The maximum value recorded was 97 Bqm-3 which is almost similar to WHO reference level. The mean outdoor radon concentrations in Cameron Highlands and Ranau were 7.4 Bqm-3and 1.7 Bqm-3, respectively. The outdoor concentrations were low and comparable to world outdoor average.
In this era, most of us are suffering some level of respiratory problem. Respiratory system of our children is even more sensitive compare to adults. As our children spending an average of 8 hours in school, indoor air quality of the classroom become an important element. Many studies have shown that indoor air quality not only affecting the respiratory system of schoolchildren but their performance in academy as well.
This study emphasizes on near surface observation of chemically active trace gases such as nitrogen dioxide (NO2) over Islamabad on a regular basis. Absorption spectroscopy using backscattered extraterrestrial light source technique was used to retrieve NO2 differential slant column densities (dSCDs). Mini multi-axis-differential optical absorption spectroscopy (MAX-DOAS) instrument was used to perform ground-based measurements at Institute of Environmental Sciences and Engineering (IESE), National University of Sciences and Technology (NUST) Islamabad, Pakistan. Tropospheric vertical column densities (VCDs) of NO2 were derived from measured dSCDs by using geometric air mass factor approach. A case study was conducted to identify the impact of different materials (glass, tinted glass, and acrylic sheet of various thicknesses used to cover the instrument) on the retrieval of dSCDs. Acrylic sheet of thickness 5 mm was found most viable option for casing material as it exhibited negligible impact in the visible wavelength range. Tropospheric NO2 VCD derived from ground-based mini MAX-DOAS measurements exceeded two times the Pak-NEQS levels and showed a reasonable comparison (r (2) = 0.65, r = 0.81) with satellite observations (root mean square bias of 39 %) over Islamabad, Pakistan.
Like other developing countries, Pakistan is also facing changes in temperature per decade and other climatic abnormalities like droughts and torrential rains. In order to assess and identify the extent of temperature change over Pakistan, the whole Pakistan was divided into five climatic zones ranging from very cold to hot and dry climates. Similarly, seasons in Pakistan are defined on the basis of monsoon variability as winter, pre-monsoon, monsoon, and post-monsoon. This study primarily focuses on the comparison of surface temperature observations from Pakistan Meteorological Department (PMD) network with PRECIS (Providing Regional Climates for Impacts Studies) model simulations. Results indicate that PRECIS underestimates the temperature in Northern Pakistan and during the winter season. However, there exists a fair agreement between PRECIS output and observed datasets in the lower plain and hot areas of the country. An absolute increase of 0.07 °C is observed in the mean temperature over Pakistan during the time period of 1951-2010. Especially, the increase is more significant (0.7 °C) during the last 14 years (1997-2010). Moreover, SCIAMACHY observations were used to explore the evolution of atmospheric CO2 levels in comparison to temperature over Pakistan. CO2 levels have shown an increasing trend during the first decade of the twenty-first century.
The aim of the present study was to investigate the potential sources of heavy metals in fine air particles (PM2.5) and benzene, toluene, ethylbenzene, and isomeric xylenes (BTEX) in gas phase indoor air. PM2.5 samples were collected using a low volume sampler. BTEX samples were collected using passive sampling onto sorbent tubes and analyzed using gas chromatography-mass spectrometry (GC-MS). For the lower and upper floors of the evaluated building, the concentrations of PM2.5 were 96.4 ± 2.70 μg/m3 and 80.2 ± 3.11 μg/m3, respectively. The compositions of heavy metals in PM2.5 were predominated by iron (Fe), zinc (Zn), and aluminum (Al) with concentration of 500 ± 50.07 ng/m3, 466 ± 77.38 ng/m3, and 422 ± 147.38 ng/m3. A principal component analysis (PCA) showed that the main sources of BTEX were originated from vehicle emissions and exacerbate because of temperature variations. Hazard quotient results for BTEX showed that the compounds were below acceptable limits and thus did not possess potential carcinogenic risks. However, a measured output of lifetime cancer probability revealed that benzene and ethylbenzene posed definite carcinogenic risks. Pollutants that originated from heavy traffic next to the sampling site contributed to the indoor pollution.
Biomonitoring of multi-element atmospheric deposition using terrestrial moss is a well-established technique in Europe. Although the technique is widely known, there were very limited records of using this technique to study atmospheric air pollution in Malaysia. In this present study, the deposition of 11 trace metals surrounding the main petroleum refinery plant in Kerteh Terengganu (eastern part of peninsular Malaysia) has been evaluated using two local moss species, namely Hypnum plumaeforme and Taxithelium instratum as bioindicators. The study was also done by means of observing whether these metals are attributed to work related to oil exploration in this area. The moss samples have been collected at 30 sampling stations in the vicinity of the petrochemical industrial area covering up to 15 km to the south, north, and west in radius. The contents of heavy metal in moss samples were analyzed by energy dispersive x-ray fluorescence technique. Distribution of heavy metal content in all mosses is portrayed using Surfer software. Areas of the highest level of contaminations are highlighted. The results obtained using the principal components analysis revealed that the elements can be grouped into three different components that indirectly reflected three different sources namely anthropogenic factor, vegetation factor, and natural sources (soil dust or substrate) factor. Heavy metals deposited mostly in the distance after 9 km onward to the western part (the average direction of wind blow). V, Cr, Cu, and Hg are believed to have originated from local petrochemical-based industries operated around petroleum industrial area.
There are few studies on associations between respiratory health and allergens, fungal and bacterial compounds in schools in tropical countries. The aim was to study associations between respiratory symptoms in pupils and ethnicity, chemical microbial markers, allergens and fungal DNA in settled dust in schools in Malaysia. Totally 462 pupils (96%) from 8 randomly selected secondary schools in Johor Bahru, Malaysia, participated. Dust was vacuumed from 32 classrooms and analysed for levels of different types of endotoxin as 3-hydroxy fatty acids (3-OH), muramic acid, ergosterol, allergens and five fungal DNA sequences. Multiple logistic regression was applied. Totally 13.1% pupils reported doctor's diagnosed asthma, 10.3% wheeze and 21.1% pollen or pet allergy. Indian and Chinese children had less atopy and asthma than Malay. Carbon dioxide levels were low (380-690 ppm). No cat (Fel d1), dog (Can f 1) or horse allergens (Ecu cx) were detected. The levels of Bloomia tropicalis (Blo t), house dust mite allergens (Der p 1, Der f 1, Der m 1) and cockroach allergens (Per a 1 and Bla g 1) were low. There were positive associations between levels of Aspergillus versicolor DNA and daytime breathlessness, between C14 3-OH and respiratory infections and between ergosterol and doctors diagnosed asthma. There were negative (protective) associations between levels of C10 3-OH and wheeze, between C16 3-OH and day time and night time breathlessness, between cockroach allergens and doctors diagnosed asthma. Moreover there were negative associations between amount of fine dust, total endotoxin (LPS) and respiratory infections. In conclusion, endotoxin at school seems to be mainly protective for respiratory illness but different types of endotoxin could have different effects. Fungal contamination measured as ergosterol and Aspergillus versicolor DNA can be risk factors for respiratory illness. The ethnical differences for atopy and asthma deserve further attention.
This review discusses how climate undergo changes and the effect of climate change on air quality as well as public health. It also covers the inter relationship between climate and air quality. The air quality discussed here are in relation to the 5 criteria pollutants; ozone (O3), carbon dioxide (CO2), nitrogen dioxide (NO2), sulfur dioxide (SO2), and particulate matter (PM). Urban air pollution is the main concern due to higher anthropogenic activities in urban areas. The implications on health are also discussed. Mitigating measures are presented with the final conclusion.