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 Three Gorges Dam's construction and industrial transfer have resulted in a new air pollution pattern with the potential to threaten the reservoir eco-environment. To assess the impact of socioeconomic factors on the pattern of air quality vairation and economical risks, concentrations of SO2, NO2, and PM10, industry genres, and meteorological conditions were selected in the Three Gorges Reservoir of Chongqing (TGRC) during 2006-2015. Results showed that air quality had improved to some extent, but atmospheric NO2 showed an increased trend during 2011-2015. Spatially, higher atmospheric NO2 extended to the surrounding area. The primary industry, especially for agriculture, had shown to be responsible for the remarkable increase of atmospheric NO2 (p air pollutant reductions, but construction industries had inhibited the improvement of regional air quality. In the tertiary industry, the cargo industry at ports had significantly decreased atmospheric NO2 as a result of eliminating the obsoleted small ships. Contrarily, the highway transportation had brought more air pollutants. The relative humidity was shown to be the main meteorological factor, which had an extremely remarkable relation with atmospheric SO2 (p air quality improvement difficult, and atmospheric SO2, NO2, and PM10 deposition would aggravate regional soil and water acidification and reactivate heavy metal in soil and sediment, further to pose a high level of ecological risk in the TGRC and other countries with reservoirs in the world.
This study aimed to investigate the chemical composition and potential sources of PM10 as well as assess the potential health hazards it posed to school children. PM10 samples were taken from classrooms at a school in Kuala Lumpur's city centre (S1) and one in the suburban city of Putrajaya (S2) over a period of eight hours using a low volume sampler (LVS). The composition of the major ions and trace metals in PM10 were then analysed using ion chromatography (IC) and inductively coupled plasma-mass spectrometry (ICP-MS), respectively. The results showed that the average PM10 concentration inside the classroom at the city centre school (82µg/m(3)) was higher than that from the suburban school (77µg/m(3)). Principal component analysis-absolute principal component scores (PCA-APCS) revealed that road dust was the major source of indoor PM10 at both school in the city centre (36%) and the suburban location (55%). The total hazard quotient (HQ) calculated, based on the formula suggested by the United States Environmental Protection Agency (USEPA), was found to be slightly higher than the acceptable level of 1, indicating that inhalation exposure to particle-bound non-carcinogenic metals of PM10, particularly Cr exposure by children and adults occupying the school environment, was far from negligible.
In this study, we assess the intense pollution episode of June 2013, in Riau province, Indonesia from land clearing. We relied on satellite retrievals of aerosols and Carbon monoxide (CO) due to lack of ground measurements. We used both the yearly and daily data for aerosol optical depth (AOD), fine mode fraction (FMF), aerosol absorption optical depth (AAOD) and UV aerosol index (UVAI) for characterizing variations. We found significant enhancement in aerosols and CO during the pollution episode. Compared to mean (2008-2012) June AOD of 0.40, FMF-0.39, AAOD-0.45, UVAI-1.77 and CO of 200 ppbv, June 2013 values reached 0.8, 0.573, 0.672, 1.77 and 978 ppbv respectively. Correlations of fire counts with AAOD and UVAI were stronger compared to AOD and FMF. Results from a trajectory model suggested transport of air masses from Indonesia towards Malaysia, Singapore and southern Thailand. Our results highlight satellite-based mapping and monitoring of pollution episodes in Southeast Asia.
This study was carried out to determine the concentration of lead (Pb), anions, and cations at six primary schools located around Kuala Lumpur. Low volume sampler (MiniVol PM10) was used to collect the suspended particulates in indoor and outdoor air. Results showed that the concentration of Pb in indoor air was in the range of 5.18 ± 1.08 μg/g-7.01 ± 0.08 μg/g. All the concentrations of Pb in indoor air were higher than in outdoor air at all sampling stations. The concentrations of cations and anions were higher in outdoor air than in indoor air. The concentration of Ca(2+) (39.51 ± 5.01 mg/g-65.13 ± 9.42 mg/g) was the highest because the cation existed naturally in soil dusts, while the concentrations of NO3 (-) and SO4 (2-) were higher in outdoor air because there were more sources of exposure for anions in outdoor air, such as highly congested traffic and motor vehicles emissions. In comparison, the concentration of NO3 (-) (29.72 ± 0.31 μg/g-32.00 ± 0.75 μg/g) was slightly higher than SO4 (2-). The concentrations of most of the parameters in this study, such as Mg(2+), Ca(2+), NO3 (-), SO4 (2-), and Pb(2+), were higher in outdoor air than in indoor air at all sampling stations.
Nineteen pairs of air and seawater samples collected from the equatorial Indian Ocean onboard the Shiyan I from 4/2011 to 5/2011 were analyzed for PCBs and HCB. Gaseous concentrations of ∑(ICES)PCBs (ICES: International Council for the Exploration of the Seas) and HCB were lower than previous data over the study area. Air samples collected near the coast had higher levels of PCBs relative to those collected in the open ocean, which may be influenced by proximity to source regions and air mass origins. Dissolved concentrations of ∑(ICES)PCBs and HCB were 1.4-14 pg L⁻¹ and 0.94-13 pg L⁻¹, with the highest concentrations in the sample collected from Strait of Malacca. Fugacity fractions suggest volatilization of PCBs and HCB from the seawater to air during the cruise, with fluxes of 0.45-34 ng m⁻² d⁻¹ and 0.36-18 ng m⁻² d⁻¹, respectively.
This study aims to determine the composition and sources of particulate matter with an aerodynamic diameter of 10 μm or less (PM10) in a semi-urban area. PM10 samples were collected using a high volume sampler. Heavy metals (Fe, Zn, Pb, Mn, Cu, Cd and Ni) and cations (Na(+), K(+), Ca(2+) and Mg(2+)) were detected using inductively coupled plasma mass spectrometry, while anions (SO4 (2-), NO3 (-), Cl(-) and F(-)) were analysed using Ion Chromatography. Principle component analysis and multiple linear regressions were used to identify the source apportionment of PM10. Results showed the average concentration of PM10 was 29.5 ± 5.1 μg/m(3). The heavy metals found were dominated by Fe, followed by Zn, Pb, Cu, Mn, Cd and Ni. Na(+) was the dominant cation, followed by Ca(2+), K(+) and Mg(2+), whereas SO4 (2-) was the dominant anion, followed by NO3 (-), Cl(-) and F(-). The main sources of PM10 were the Earth's crust/road dust, followed by vehicle emissions, industrial emissions/road activity, and construction/biomass burning.
Nineteen pairs of gaseous and surface seawater samples were collected along the cruise from Malaysia to the south of Bay of Bengal passing by Sri Lanka between April 12 and May 4, 2011 on the Chinese research vessel Shiyan I to investigate the latest OCP pollution status over the equatorial Indian Ocean. Significant decrease of α-HCH and γ-HCH was found in the air and dissolved water phase owing to global restriction for decades. Substantially high levels of p,p'-DDT, o,p'-DDT, trans-chlordane (TC), and cis-chlordane (CC) were observed in the water samples collected near Sri Lanka, indicating fresh continental riverine input of these compounds. Fugacity fractions suggest equilibrium of α-HCH at most sampling sites, while net volatilization for DDT isomers, TC and CC in most cases. Enantiomer fractions (EFs) of α-HCH and o,p'-DDT in the air and water samples were determined to trace the source of these compounds in the air. Racemic or close to racemic composition was found for atmospheric α-HCH and o,p'-DDT, while significant depletion of (+) enantiomer was found in the water phase, especially for o,p'-DDT (EFs = 0.310 ± 0.178). 24% of α-HCH in the lower air over the open sea of the equatorial Indian Ocean is estimated to be volatilized from local seawater, indicating that long-range transport is the main source.
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.
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) 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.
A number of offensive odorants including volatile organic compounds (VOCs), reduced sulfur compounds (RSCs), carbonyls, and ammonia were measured along with several reference pollutants (like benzene (B), CS(2), SO(2), CO, and total hydrocarbon (THC)) from combusted fumes of barbecue charcoals produced from five different countries (Korea, China, Indonesia, Malaysia, and the US). Although the emission concentrations of most odorants were generally below the reference guideline set by the malodor prevention law in Korea, the mean concentration of some aldehydes (acetaldehyde, propionaldehyde, and isovaleraldehyde) and ammonia exceeded those guidelines. As such, aldehydes were the most dominant odorant released from charcoal combustion followed by VOC and ammonia. If odorant levels of charcoal products are compared, there are great distinctions between the products of different countries. If comparison is made using the concept of the sum of odor intensity (SOI), the magnitude of SOI for the charcoal products from the five different countries varied in the order of 4.30 (Korea), 3.10 (Indonesia), 2.97 (China), 2.76 (Malaysia), and 2.76 (the US).
This study performed an assessment on the beneficial of the Clean Development Mechanism (CDM) application on waste treatment system in a local palm oil industry in Malaysia. Life cycle assessment (LCA) was conducted to assess the environmental impacts of the greenhouse gas (GHG) reduction from the CDM application. Calculations on the emission reduction used the methodology based on AM002 (Avoided Wastewater and On-site Energy Use Emissions in the Industrial Sector) Version 4 published by United Nations Framework Convention on Climate Change (UNFCC). The results from the studies showed that the introduction of CDM in the palm oil mill through conversion of the captured biogas from palm oil mill effluent (POME) treatment into power generation were able to reduce approximate 0.12 tonnes CO2 equivalent concentration (tCO2e) emission and 30 kW x hr power generation per 1 tonne of fresh fruit bunch processed. Thus, the application of CDM methodology on palm oil mill wastewater treatment was able to reduce up to 1/4 of the overall environment impact generated in palm oil mill.
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.
The main objective of this cross-sectional comparative study is to observe the relationship between traffic-related air pollutants, particularly particulate matter (PM) of total suspended particulate (TSP) and PM of size 10 µm (PM10), and vehicle traffic in Amman, Jordan. Two study areas were chosen randomly as a high-polluted area (HPA) and low-polluted area (LPA). The findings indicate that TSP and PM10 were still significantly correlated with traffic count even after controlling for confounding factors (temperature, relative humidity, and wind speed): TSP, r = 0.726, P < .001; PM10, r = 0.719, P < .001). There was a significant positive relationship between traffic count and PM level: TSP, P < .001; PM10, P < .001. Moreover, there was a significant negative relationship between temperature and PM10 level (P = .018). Traffic volume contributed greatly to high concentrations of TSP and PM10 in areas with high traffic count, in addition to the effect of temperature.
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.
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.
This study aims to determine the composition of surfactants in the lake surface microlayer, rainwater, and atmospheric aerosols in the area surrounding Lake Chini, Pahang. Surfactants in the lake surface microlayer were taken from seven different stations around the lake, while samples of rainwater were taken from five different sampling stations. The samples of atmospheric aerosols were collected from the Lake Chini Research Centre which is in close proximity to the lake. The colorimetric analysis method was used to determine the composition and concentration of anionic surfactants as methylene blue active substances (MBAS) and cationic surfactants as disulphine blue active substances (DBAS). The concentration of anionic surfactants, as MBAS, in the surface microlayer ranged between 0.08 to 0.23 μmol L(-1), while the range of concentration of cationic surfactants as DBAS ranged from 0.09 to 0.11 μmol L(-1). The concentration of MBAS was higher in rainwater when compared to surfactants in the lake surface microlayer. The high concentration of surfactants in the fine mode of atmospheric aerosols suggests that natural and anthropogenic sources of surfactants contribute to the atmospheric surfactants.
The problems of global warming and the unstable price of petroleum oils have led to a race to develop environmentally friendly biofuels, such as palm oil or ethanol derived from corn and sugar cane. Biofuels are a potential replacement for fossil fuel, since they are renewable and environmentally friendly. This paper evaluates the combustion performance and emission characteristics of Refined, Bleached, and Deodorized Palm Oil (RBDPO)/diesel blends B5, B10, B15, B20, and B25 by volume, using an industrial oil burner with and without secondary air. Wall temperature profiles along the combustion chamber axis were measured using a series of thermocouples fitted axially on the combustion chamber wall, and emissions released were measured using a gas analyzer. The results show that RBDPO blend B25 produced the maximum emission reduction of 56.9% of CO, 74.7% of NOx, 68.5% of SO(2), and 77.5% of UHC compared to petroleum diesel, while air staging (secondary air) in most cases reduces the emissions further. However, increasing concentrations of RBDPO in the blends also reduced the energy released from the combustion. The maximum wall temperature reduction was 62.7% for B25 at the exit of the combustion chamber.
Conventional aerobic and low-rate anaerobic processes such as pond and open-tank systems have been widely used in wastewater treatment. In order to improve treatment efficacy and to avoid greenhouse gas emissions, conventional treatment can be upgraded to a high performance anaerobic granular-sludge system. The anaerobic granular-sludge systems are designed to capture the biogas produced, rendering a potential for claims of carbon credits under the Kyoto Protocol for reducing emissions of greenhouse gases. Certified Emission Reductions (CERs) would be issued, which can be exchanged between businesses or bought and sold in international markets at the prevailing market prices. As the advanced anaerobic granular systems are capable of handling high organic loadings concomitant with high strength wastewater and short hydraulic retention time, they render more carbon credits than other conventional anaerobic systems. In addition to efficient waste degradation, the carbon credits can be used to generate revenue and to finance the project. This paper presents a scenario on emission avoidance based on a methane recovery and utilization project. An example analysis on emission reduction and an overview of the global emission market are also outlined.