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.
Lichen is a symbiotic organism that exists as a single composite body consisting of a mycobiont (fungus) and a photobiont (algae or a cyanobacterium). Many lichen species are considered as extremophiles due to their tolerance to radiation, desiccation, temperature and pollution. However, not all lichen species are tolerant to harsh environmental conditions as several species are sensitive for example to nitrogen, sulphur, acidity, heavy metals, halogens (e.g. fluoride) and ozone. Thus, to better understand why some lichens can withstand exposure to pollutants as opposed to those that are susceptible, we focused on the lichen species of Dirinaria known for their wide distribution in the tropics, subtropics and pantropical, and moderate tolerance to air pollution. Their moderate tolerance to air pollution affords them to thrive in good air quality environments as well as polluted air environments. Lichen samples of Dirinaria sp., UKM-J1 and UKM-K1, were respectively collected from two areas with different levels of air quality based on Air Pollutant Index or API (with index pollutant criteria of PM10, carbon monoxide, ozone, nitrogen dioxide and sulfur dioxide) in the outskirt of Jerantut (UKM-J1), a rural area in the middle of Peninsular Malaysia and the township of Klang (UKM-K1), in a busy area of the Klang Valley, Malaysia. API was monitored throughout 2012-2013 whereby the sample collection site in Klang showed markedly higher concentrations of pollutants in all the index pollutant criteria as compared to that of Jerantut. We performed transcriptome sequencing using Illumina RNA-seq technology and de novo assembly of the transcripts from the lichen samples. Raw reads from both libraries were deposited in the NCBI database with the accession number SRP138994.
The emission of sulphur dioxide (SO2) gas from power plants and factories to the atmosphere has been an environmental challenge globally. Thus, there is a great interest to control the SO2 gas emission economically and effectively. This study aims to use and convert abundantly available oil palm fiber (OPF) biomass into an adsorbent to adsorb SO2 gas. The preparation of OPF biochar and activated biochar was optimised using the Response Surface Methodology (RSM) based on selected parameters (i.e., pyrolysis temperature, heating rate, holding time, activation temperature, activation time and CO2 flowrate). The best adsorbent was found to be the OPF activated biochar (OPFAB) compared to OPF biochar. OPFAB prepared at 753 °C for 73 min of activation time with 497 ml/min of CO2 flow yields the best adsorption capacity (33.09 mg/g) of SO2. Meanwhile, OPF pyrolysed at 450 °C of heating temperature, 12 °C/min of heating rate and 98 min of holding time yield adsorption capacity at 18.62 mg/g. Various characterisations were performed to investigate the properties and mechanism of the SO2 adsorption process. Thermal regeneration shows the possibilities for the spent adsorbent to be recycled. The findings imply OPFAB as a promising adsorbent for SO2 adsorption.
Palm oil sludge (POS) is an organic waste generated from the palm oil industry. POS causes environmental pollution if it is improperly disposed. In this study, the potential of activated POS biochar, as an adsorbent for the removal of SO2 gas was tested. POS biochar was physically activated using CO2 gas. The effects of activation preparation variables i.e. activation temperature (300-700 °C), activation time (30-150 min) and CO2 flow rate (100-500 ml/min) were investigated using design expert version 8.0.7.1 software. Central Composite Design (CCD) was used to develop a quadratic model to correlate the operating variables with the activated biochar adsorption capacity. Analysis of variance (ANOVA) was performed to identify the significant factors on the experimental design response. The optimum preparation conditions of activated POS biochar were found to be at activation temperature of 442 °C, activation time of 63 min and CO2 flow rate of 397 ml/min. The maximum adsorption capacity at the optimum conditions was recorded as 16.65 mg/g. The adsorption capacity increased significantly after the activation process. Characteristics of the activated POS biochar proposed that SO2 was physically adsorbed. Furthermore, it was found that the adsorption capacity can be further enhanced by increasing the reaction temperature to 100 °C or with 15% of relative humidity in the inlet gas. The prepared adsorbents can be regenerated by thermal treatment.
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.
Indoor air quality assessment in residential areas of Al-Hofuf city/Eastern region of Saudi Arabia is investigated through a multi-week multiple sites sampling survey. Critical air pollution indicators, including nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), carbon dioxide (CO2) and total volatile organic compounds (TVOC) as well as temperatures were measured and analyzed during the study period from January to May 2014. Three site-types - roadside, urban and rural - were selected and within each site type, six locations were selected to study the varying indoor/outdoor air quality. The results indicated that NO2 and CO concentrations increased at the starting hours of the day. SO2 concentrations were relatively low and constant. In addition, a strong association between outdoor and indoor air quality was found. Measurements showed that indoor/outdoor ratio for TVOC ranged from 0.8 to 0.99. For CO2, NO2 and SO2, this was 0.92-1.15, 0.5-0.7 and 0.52-0.9, respectively. Finally, the effects of activated carbon (AC) were investigated to assess the extent of the improvement in the indoor air quality. The analysis of data obtained indicated that using locally prepared AC from date stones was an effective way to reduce the indoor air pollution with an overall efficiency of 85.5, while the use of industrial granular AC reduced the air pollutants with an efficiency of less than 0.6. In addition, AC was exposed to an exhaust gas flow to evaluate its elimination potential for high concentrated pollutants. The obtained results demonstrated that AC was also functioning as an efficient absorbent with an overall removal efficiency of 77.8%, even when it was exposed to high concentrations.
In recent years, Malaysia has experienced quite a few number of chronic air pollution problems and it has become a
major contributor to the deterioration of human health and ecosystems. This study aimed to assess the air quality data
and identify the pattern of air pollution sources using chemometric analysis through hierarchical cluster analysis (HCA),
discriminant analysis (DA), principal component analysis (PCA) and multiple linear regression analysis (MLR). The air
quality data from January 2016 until December 2016 was obtained from the Department of Environment Malaysia. Air
quality data from eight sampling stations in Selangor include the selected variables of nitrogen dioxide (NO2
), ozone (O3
),
sulfur dioxide (SO2
), carbon monoxide (CO) and particulate matter (PM10). The HCA resulted in three clusters, namely low
pollution source (LPS), moderate pollution source (MPS) and slightly high pollution source (SHPS). Meanwhile, DA resulted
in two and four variables for the forward stepwise mode and the backward stepwise mode, respectively. Through PCA,
it was identified that the main pollutants of LPS, MPS and SHPS came from industrial and vehicle emissions, agricultural
systems, residential factors and natural emission sources. Among the three models yielded from the MLR analysis, it was
found that SHPS is the most suitable model to be used for the prediction of Air Pollution Index. This study concluded that
a clearer review and practical design of air quality monitoring network would be beneficial for better management of
air pollution. The study also suggested that chemometric techniques have the ability to show significant information on
spatial variability for large and complex air quality data.
In July 1997 at 7 pm , 49 members 0f the public complained of dizziness, sore throat, eyes irritation and tightness of chest after exposed to sulphur dioxide while traveling on the road about 100 meter 90m the sulphuric acid factory in Teluk Kalong Kemaman. The incident was caused by leaking sulfur dioxide from return pipe of scrubber circulation. tank in the factory. The problem had occurred due to carelessness of the operator to inspect the level of water in the scrubber circulation tank during the operation.
In this study, palm oil mill sludge was used as a precursor to prepare biochar using conventional pyrolysis. Palm oil mill sludge biochar (POSB) was prepared at different preparation variables, i.e., heating temperature (300-800 °C), heating rate (10-20 °C/min) and holding time (60-120 min). The prepared biochars were tested for sulfur dioxide (SO2) adsorption in a fixed bed reactor using 300 ppm of SO2 gas at 300 ml/min (with N2 gas as balance). Response surface central composite experimental design was used to optimize the production of biochar versus SO2 removal. A quadratic model was developed in order to correlate the effect of variable parameters on the optimum adsorption capacity of SO2 gas. The experimental values and the predicted results of the model were found to show satisfactory agreement. The optimum conditions for biochar preparation to yield the best SO2 removal was found to be at 405 °C of heating temperature, 20 °C/min of heating rate and 88 min of holding time. At these conditions, the average yield of biochar and adsorption capacity for SO2 gas was reported as 54.25 g and 9.75 mg/g, respectively. The structure of biochar and their roles in SO2 adsorption were investigated by surface area, morphology images, infrared spectra, and proximate analysis, respectively. The characterization findings suggested that POSB adsorbs SO2 mainly by the functional groups.
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.
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.
An electron beam (EB) flue gas test rig and a dielectric barrier discharge (DBD) reactor were tested for the removal of nitric oxide (NO) from gas stream in separate experiments. In both systems, energised electrons were used to produce radicals that reacted with the pollutants. The EB system was a laboratory scale test rig used to treat emission from a diesel run generator. At 1.0 MeV and 10 mA more than 90% NO removal from flue gases flowing at 120 Nm3/h can be achieved. For higher removal percentage, higher beam current was required. In a related effort, a table top, two tubes DBD reactor was used to process bottled gases containing 106 ppm NO. Total removal (>99%) was achieved when the inlet gas contained only NO and N2. Additional SO2 in the in let gas stream lowered the removal rate but was overcame by scaling up the system to 10 DBD tubes. The system was operated with input AC voltage of 35 kV peak to peak. In the EB treatment system, the amount of NO2 increased at high beam current, showing that the NO was also oxidised in the process. Whereas in the DBD reactor, the amount of NO2 remained insignificant throughout the process. This leads to the conclusion that the DBD reactor is capable of producing total removal of NO. This is highly desirable as post treatment will not be necessary.
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.
The aim of this study is to examine the impact of air pollutants, including mono-nitrogen oxides (NOx), nitrous oxide (N2O), sulfur dioxide (SO2), carbon dioxide emissions (CO2), and greenhouse gas (GHG) emissions on ecological footprint, habitat area, food supply, and biodiversity in a panel of thirty-four developed and developing countries, over the period of 1995-2014. The results reveal that NOx and SO2 emissions both have a negative relationship with ecological footprints, while N2O emission and real GDP per capita have a direct relationship with ecological footprints. NOx has a positive relationship with forest area, per capita food supply and biological diversity while CO2 emission and GHG emission have a negative impact on food production. N2O has a positive impact on forest area and biodiversity, while SO2 emissions have a negative relationship with them. SO2 emission has a direct relationship with per capita food production, while GDP per capita significantly affected per capita food production and food supply variability across countries. The overall results reveal that SO2, CO2, and GHG emissions affected potential habitat area, while SO2 and GHG emissions affected the biodiversity index. Trade liberalization policies considerably affected the potential habitat area and biological diversity in a panel of countries.
In the early days of abundant resources and minimal development pressures, little attention was paid to growing environmental concerns in Malaysia. The haze episodes in Southeast Asia in 1983, 1984, 1991, 1994, and 1997 imposed threats to the environmental management of Malaysia and increased awareness of the environment. As a consequence, the government established Malaysian Air Quality Guidelines, the Air Pollution Index, and the Haze Action Plan to improve air quality. Air quality monitoring is part of the initial strategy in the pollution prevention program in Malaysia. Review of air pollution in Malaysia is based on the reports of the air quality monitoring in several large cities in Malaysia, which cover air pollutants such as Carbon monoxide (CO), Sulphur Dioxide (SO2), Nitrogen Dioxide (NO2), Ozone (O3), and Suspended Particulate Matter (SPM). The results of the monitoring indicate that Suspended Particulate Matter (SPM) and Nitrogen Dioxide (NO2) are the predominant pollutants. Other pollutants such as CO, O(x), SO2, and Pb are also observed in several big cities in Malaysia. The air pollution comes mainly from land transportation, industrial emissions, and open burning sources. Among them, land transportation contributes the most to air pollution. This paper reviews the results of the ambient air quality monitoring and studies related to air pollution and health impacts.
A study on 30 asthmatic children was conducted in Kuala Lumpur. The objective of this study was to study the relationship between respirable particulate (PM10), sulphur dioxide, ozone and various meteorological factors such as humidity, level ofrainfall and temperature with asthma attacks. This study was conducted from 1st September to 31 December 1994. Patients were selected from the Paediatric Unit, Kuala Lumpur Hospital. Questionnaires were used to obtain information from their parents on the history and severity ofasthmatic attacks ofthese patients. Questionnaires were also used to determine if the indoor sources contributed to the attack. Diary cards were used to collect information on the frequency of asthmatic attacks. Each patient's progress was followed through every week during the study period and the attacks were recorded. The data on air quality on the PM10, sulphur dioxide, nitrogen dioxide, carbon monoxide and ozone were collected hourly using the microcomputer system of air monitoring unit from the Universiti Pertanian Malaysia air quality monitoring station located at the City Hall, Kuala Lumpur. The meteorological parameters such as temperature, relative humidity and rain-fall levels were also monitored daily. The asthmatic attack percentage was obtained by dividing the number of attacks in a day with the total number of sample and multiplying by a hundred. Statistical tests indicated that there was a significant correlation between asthmatic attacks and the PM10 concentrations (r=0.73), nitrogen dioxide (r=0.57) and.carbon monoxide (r=0.53) throughout the study period. During the haze episode, more significant correlations between asthmatic attacks, PM10 concentra-tions (0.86), carbon monoxide (0.79) and nitrogen oxide (0.53) were found. Multiple regression statistical test showed that PM10 had the greatest influence on the asthmatic attack rate. The minute respirable particulate which entered the respiratory system of the asthmatics triggered attacks on these patients.
Proper identification of environment's air quality based on limited observations is an essential task to meet the goals of environmental management. Various classification methods have been used to estimate the change of air quality status and health. However, discrepancies frequently arise from the lack of clear distinction between each air quality, the uncertainty in the quality criteria employed and the vagueness or fuzziness embedded in the decision-making output values. Owing to inherent imprecision, difficulties always exist in some conventional methodologies when describing integrated air quality conditions with respect to various pollutants. Therefore, this paper presents two fuzzy multiplication synthetic techniques to establish classification of air quality. The fuzzy multiplication technique empowers the max-min operations in "or" and "and" in executing the fuzzy arithmetic operations. Based on a set of air pollutants data carbon monoxide, sulfur dioxide, nitrogen dioxide, ozone, and particulate matter (PM(10)) collected from a network of 51 stations in Klang Valley, East Malaysia, Sabah, and Sarawak were utilized in this evaluation. The two fuzzy multiplication techniques consistently classified Malaysia's air quality as "good." The findings indicated that the techniques may have successfully harmonized inherent discrepancies and interpret complex conditions. It was demonstrated that fuzzy synthetic multiplication techniques are quite appropriate techniques for air quality management.
Biomass burning is one of the main sources of air pollution in South East Asia, predominantly during the dry period between June and October each year. Sumatra and Kalimantan, Indonesia, have been identified as the regions connected to biomass burning due to their involvement in agricultural activities. In Sumatra, the Province of Riau has always been found to have had the highest number of hotspots during haze episodes. This study aims to determine the concentration of five major pollutants (PM10, SO2, NO2, CO and O3) in Riau, Indonesia, for 2006 and 2007. It will also correlate the level of air pollutants to the number of hotspots recorded, using the hotspot information system introduced by the Malaysian Centre for Remote Sensing (MACRES). Overall, the concentration of air pollutants recorded was found to increase with the number of hotspots. Nevertheless, only the concentration of PM10 during a haze episode is significantly different when compared to its concentration in non-haze conditions. In fact, in August 2006, when the highest number of hotspots was recorded the concentration of PM10 was found to increase by more than 20% from its normal concentration. The dispersion pattern, as simulated by the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT), showed that the distribution of PM10 was greatly influenced by the wind direction. Furthermore, the particles had the capacity to reach the Peninsular Malaysia within 42 hours of emission from the point sources as a consequence of the South West monsoon.
The air pollution index (API) is an important figure used for measuring the quality of air in the environment. The API is determined based on the highest average value of individual indices for all the variables which include sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3), and suspended particulate matter (PM10) at a particular hour. API values that exceed the limit of 100 units indicate an unhealthy status for the exposed environment. This study investigates the risk of occurrences of API values greater than 100 units for eight urban areas in Peninsular Malaysia for the period of January 2004 to December 2014. An extreme value model, known as the generalized Pareto distribution (GPD), has been fitted to the API values found. Based on the fitted model, return period for describing the occurrences of API exceeding 100 in the different cities has been computed as the indicator of risk. The results obtained indicated that most of the urban areas considered have a very small risk of occurrence of the unhealthy events, except for Kuala Lumpur, Malacca, and Klang. However, among these three cities, it is found that Klang has the highest risk. Based on all the results obtained, the air quality standard in urban areas of Peninsular Malaysia falls within healthy limits to human beings.
Since its first appearance in Wuhan, China at the end of 2019, the new coronavirus (COVID-19) has evolved a global pandemic within three months, with more than 4.3 million confirmed cases worldwide until mid-May 2020. As many countries around the world, Malaysia and other southeast Asian (SEA) countries have also enforced lockdown at different degrees to contain the spread of the disease, which has brought some positive effects on natural environment. Therefore, evaluating the reduction in anthropogenic emissions due to COVID-19 and the related governmental measures to restrict its expansion is crucial to assess its impacts on air pollution and economic growth. In this study, we used aerosol optical depth (AOD) observations from Himawari-8 satellite, along with tropospheric NO2 column density from Aura-OMI over SEA, and ground-based pollution measurements at several stations across Malaysia, in order to quantify the changes in aerosol and air pollutants associated with the general shutdown of anthropogenic and industrial activities due to COVID-19. The lockdown has led to a notable decrease in AOD over SEA and in the pollution outflow over the oceanic regions, while a significant decrease (27% - 30%) in tropospheric NO2 was observed over areas not affected by seasonal biomass burning. Especially in Malaysia, PM10, PM2.5, NO2, SO2, and CO concentrations have been decreased by 26-31%, 23-32%, 63-64%, 9-20%, and 25-31%, respectively, in the urban areas during the lockdown phase, compared to the same periods in 2018 and 2019. Notable reductions are also seen at industrial, suburban and rural sites across the country. Quantifying the reductions in major and health harmful air pollutants is crucial for health-related research and for air-quality and climate-change studies.