The concentrations and distributions of particle bound polycyclic aromatic hydrocarbons (PAHs) collected over a 10 month period in ambient environment, at street levels as well as during a hazy episode are reported. Ambient and street level distributions of PAHs were similar and their occurrence was attributed to vehicular emissions. However, in haze particles, a different pattern of PAHs was observed, characterized by relatively low levels of benzo[a]pyrene (BaP) and high levels of benzofluoranthenes (BFs). The BaP equivalency results showed that the potential health risk associated with haze smoke particles was 4 times higher than that of street level particles whereas the lowest health risk was associated with ambient atmospheric particles.
Plant (vegetable) oil has been evaluated as a substitute for mineral oil-based lubricants because of its natural and environmentally friendly characteristics. Availability of vegetable oil makes it a renewable source of bio-oils. Additionally, vegetable oil-based lubricants have shown potential for reducing hydrocarbon and carbon dioxide (CO2) emissions when utilized in internal combustion (IC) engines and industrial operations. In this study, sunflower oil was investigated to study its lubricant characteristics under different loads using the four-ball tribometer and the exhaust emissions were tested using a four-stroke, single-cylinder diesel engine. All experimental works conformed to American Society for Testing and Materials standard (ASTM D4172-B). Under low loads, sunflower oil showed adequate tribological characteristics (antifriction and antiwear) compared with petroleum oil samples. The results also demonstrated that the sunflower oil-based lubricant was more effective in reducing the emission levels of carbon monoxide (CO), CO2, and hydrocarbons under different test conditions. Therefore, sunflower oil has the potential to be used as lubricant of mating components.Implications: An experimental investigation of the characteristics of nonedible sunflower oil tribological behaviors and potential as a renewable source for biofluids alternative to the petroleum oils was carried out. The level of emissions of a four-stroke, single-cylinder diesel engine using sunflower oil as a biolubricant was evaluated.
The focus of this work is to investigate the emission characteristics of a stationary diesel engine while utilizing an emulsion fuel from a novel preparation process. The emulsion preparation was performed in real time without using any surfactant. Instead of mechanically breaking the water down into droplets, the water is delivered thermally, by changing its phase from gas to liquid. Steam is used in this proposed process, where it will be converted into suspended water droplets once it meets colder diesel. The product is called steam-generated water-in-diesel emulsion fuel (S/D). The method is expected to reduce the moving components of a previous surfactant-less system; therefore, reducing costs and increasing the system reliability. The emission characteristics of S/D were compared with EURO 2 diesel (D2), and a conventional emulsion denoted as E10. E10 was prepared using 10% water (volumetric) and SPAN80 as a surfactant. The emission characterizations were carried out based on the exhaust gas of a single cylinder naturally aspirated CI engine fueled with D2, S/D, and E10. Compared to D2, both emulsions significantly reduced the emissions of nitrogen oxides (NOx) (E10 max ↓58.0%, S/D max ↓40.0%) and particulate matter (PM) (E10 max ↓20.0%, S/D max ↓57.0%).
The devastating health effects of particulate matter (PM10) exposure by susceptible populace has made it necessary to evaluate PM10 pollution. Meteorological parameters and seasonal variation increases PM10 concentration levels, especially in areas that have multiple anthropogenic activities. Hence, stepwise regression (SR), multiple linear regression (MLR) and principal component regression (PCR) analyses were used to analyse daily average PM10 concentration levels. The analyses were carried out using daily average PM10 concentration, temperature, humidity, wind speed and wind direction data from 2006 to 2010. The data was from an industrial air quality monitoring station in Malaysia. The SR analysis established that meteorological parameters had less influence on PM10 concentration levels having coefficient of determination (R 2) result from 23 to 29% based on seasoned and unseasoned analysis. While, the result of the prediction analysis showed that PCR models had a better R 2 result than MLR methods. The results for the analyses based on both seasoned and unseasoned data established that MLR models had R 2 result from 0.50 to 0.60. While, PCR models had R 2 result from 0.66 to 0.89. In addition, the validation analysis using 2016 data also recognised that the PCR model outperformed the MLR model, with the PCR model for the seasoned analysis having the best result. These analyses will aid in achieving sustainable air quality management strategies.
Waste management can be regarded as a cross-cutting environmental 'mega-issue'. Sound waste management practices support the provision of basic needs for general health, such as clean air, clean water and safe supply of food. In addition, climate change mitigation efforts can be achieved through reduction of greenhouse gas emissions from waste management operations, such as landfills. Landfills generate landfill gas, especially methane, as a result of anaerobic degradation of the degradable components of municipal solid waste. Evaluating the mode of generation and collection of landfill gas has posted a challenge over time. Scientifically, landfill gas generation rates are presently estimated using numerical models. In this study the Intergovernmental Panel on Climate Change's Waste Model is used to estimate the methane generated from a Malaysian sanitary landfill. Key parameters of the model, which are the decay rate and degradable organic carbon, are analysed in two different approaches; the bulk waste approach and waste composition approach. The model is later validated using error function analysis and optimum decay rate, and degradable organic carbon for both approaches were also obtained. The best fitting values for the bulk waste approach are a decay rate of 0.08 y(-1) and degradable organic carbon value of 0.12; and for the waste composition approach the decay rate was found to be 0.09 y(-1) and degradable organic carbon value of 0.08. From this validation exercise, the estimated error was reduced by 81% and 69% for the bulk waste and waste composition approach, respectively. In conclusion, this type of modelling could constitute a sensible starting point for landfills to introduce careful planning for efficient gas recovery in individual landfills.
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).
There are many factors that influence PM(10) concentration in the atmosphere. This paper will look at the PM(10) concentration in relation with the wet season (north east monsoon) and dry season (south west monsoon) in Seberang Perai, Malaysia from the year 2000 to 2004. It is expected that PM(10) will reach the peak during south west monsoon as the weather during this season becomes dry and this study has proved that the highest PM(10) concentrations in 2000 to 2004 were recorded in this monsoon. Two probability distributions using Weibull and lognormal were used to model the PM(10) concentration. The best model used for prediction was selected based on performance indicators. Lognormal distribution represents the data better than Weibull distribution model for 2000, 2001, and 2002. However, for 2003 and 2004, Weibull distribution represents better than the lognormal distribution. The proposed distributions were successfully used for estimation of exceedences and predicting the return periods of the sequence year.
As in many nations, air pollution linked to rapid industrialization is a public health and environmental concern in Malaysia, especially in cities. Understanding awareness of air pollution and support for environmental protection from the general public is essential for informing governmental approaches to dealing with this problem. This study presents a cross-sectional survey conducted in the Klang Valley and Iskandar conurbations to examine urban Malaysians' perception, awareness and opinions of air pollution. The survey was conducted in two languages, English and Malay, and administered through the online survey research software, Qualtrics. The survey consisted of three sections, where we collected sociodemographic information, information on the public perception of air quality and the causes of air pollution, information on public awareness of air pollution and its related impacts, and information on attitudes towards environmental protection. Of 214 respondents, over 60% were positive towards the air quality at both study sites despite the presence of harmful levels of air pollution. The air in the Klang Valley was perceived to be slightly more polluted and causing greater health issues. Overall, the majority of respondents were aware that motor vehicles represent the primary pollution source, yet private transport was still the preferred choice of transportation mode. A generally positive approach towards environmental protection emerged from the data. However, participants showed stronger agreement with protection actions that do not involve individual effort. Nonetheless, we found that certain segments of the sample (people owning more than three vehicles per household and those with relatives who suffered from respiratory diseases) were significantly more willing to personally pay for environmental protection compared to others. Implications point to the need for actions for spreading awareness of air pollution to the overall population, especially with regards to its health risks, as well as strategies for increasing the perception of behavioural control, especially with regards to motor vehicles' usage.
This study investigated the potential relationship between dengue cases and air quality - as measured by the Air Pollution Index (API) for five zones in the state of Selangor, Malaysia. Dengue case patterns can be learned using prediction models based on feedback (lagged terms). However, the question whether air quality affects dengue cases is still not thoroughly investigated based on such feedback models. This work developed dengue prediction models using the autoregressive integrated moving average (ARIMA) and ARIMA with an exogeneous variable (ARIMAX) time series methodologies with API as the exogeneous variable. The Box Jenkins approach based on maximum likelihood was used for analysis as it gives effective model estimates and prediction. Three stages of model comparison were carried out for each zone: first with ARIMA models without API, then ARIMAX models with API data from the API station for that zone and finally, ARIMAX models with API data from the zone and spatially neighbouring zones. Bayesian Information Criterion (BIC) gives goodness-of-fit versus parsimony comparisons between all elicited models. Our study found that ARIMA models, with the lowest BIC value, outperformed the rest in all five zones. The BIC values for the zone of Kuala Selangor were -800.66, -796.22, and -790.5229, respectively, for ARIMA only, ARIMAX with single API component and ARIMAX with API components from its zone and spatially neighbouring zones. Therefore, we concluded that API levels, either temporally for each zone or spatio- temporally based on neighbouring zones, do not have a significant effect on dengue cases.
Frequent haze occurrences in Malaysia have made the management of PM10 (particulate matter with aerodynamic less than 10 μm) pollution a critical task. This requires knowledge on factors associating with PM10 variation and good forecast of PM10 concentrations. Hence, this paper demonstrates the prediction of 1-day-ahead daily average PM10 concentrations based on predictor variables including meteorological parameters and gaseous pollutants. Three different models were built. They were multiple linear regression (MLR) model with lagged predictor variables (MLR1), MLR model with lagged predictor variables and PM10 concentrations (MLR2) and regression with time series error (RTSE) model. The findings revealed that humidity, temperature, wind speed, wind direction, carbon monoxide and ozone were the main factors explaining the PM10 variation in Peninsular Malaysia. Comparison among the three models showed that MLR2 model was on a same level with RTSE model in terms of forecasting accuracy, while MLR1 model was the worst.
Activated carbons have been reported to be useful for adsorptive removal of the volatile anaesthetic sevoflurane from a vapour stream. The surface functionalities on activated carbons could be modified through aqueous oxidation using oxidising solutions to enhance the sevoflurane adsorption. In this study, an attempt to oxidise the surface of a commercial activated carbon to improve its adsorption capacity for sevoflurane was conducted using 6 mol/L nitric acid, 2 mol/L ammonium persulfate, and 30 wt per cent (wt%) of hydrogen peroxide (H2O2). The adsorption tests at fixed conditions (bed depth: 10 cm, inlet concentration: 528 mg/L, and flow rate: 3 L/min) revealed that H2O2 oxidation gave desirable sevoflurane adsorption (0.510 ± 0.005 mg/m2). A parametric study was conducted with H2O2 to investigate the effect of oxidation conditions to the changes in surface oxygen functionalities by varying the concentration, oxidation duration, and temperature, and the Conductor-like Screening Model for Real Solvents (COSMO-RS) was applied to predict the interactions between oxygen functionalities and sevoflurane. The H2O2 oxidation incorporated varying degrees of both surface oxygen functionalities with hydrogen bond (HB) acceptor and HB donor characters under the studied conditions. Oxidised samples with enriched oxygen functionalities with HB acceptor character and fewer HB donor character exhibited better adsorption capacity for sevoflurane. The presence of a high amount of oxygen functional groups with HB donor character adversely affected the sevoflurane adsorption despite the enrichment of oxygen functional groups with HB acceptor character that have a higher tendency to adsorb sevoflurane.
The inhalational anaesthetic agent - sevoflurane is widely employed for the induction and maintenance of surgical anaesthesia. Sevoflurane possesses a high global warming potential that imposes negative impact to the environment. The only way to resolve the issue is to remove sevoflurane from the medical waste gas before it reaches the atmosphere. A continuous adsorption study with a fixed-bed column was conducted using two commercial granular activated carbons (E-GAC and H-GAC), to selectively remove sevoflurane. The effect of bed depth (Z, 5-15 cm), gas flow rate (Q, 0.5-6.0 L/min) and inlet sevoflurane concentration (C0, ∼55-700 mg/L) was investigated. E-GAC demonstrated ∼60% higher adsorption capacity than H-GAC under the same operating conditions. Varying the levels of Z, Q and C0 showed significant differences in the adsorption capacities of E-GAC, whereas only changing the C0 level had significant differences for H-GAC. Three breakthrough models (Adams-Bohart, Thomas, and Yoon-Nelson) and Bed-depth/service time (BDST) analysis were applied to predict the breakthrough characteristics of the adsorption tests and determine the characteristic parameters of the column. The Yoon-Nelson and Thomas model-predicted breakthrough curves were in good agreement with the experimental values. In the case of the Adams-Bohart model, a low correlation was observed. The predicted breakthrough time (tb) based on kinetic constant (kBDST) in BDST analysis showed satisfactory agreement with the measured values. The results suggest the possibility of designing, scaling up and optimising an adsorption system for removing sevoflurane with the aid of the models and BDST analysis.
Climate change and global warming as the key human societies' threats are essentially associated with energy consumption and CO2 emissions. A system dynamic model was developed in this study to model the energy consumption and CO2 emission trends for Iran over 2000-2025. Energy policy factors are considered in analyzing the impact of different energy consumption factors on environmental quality. The simulation results show that the total energy consumption is predicted to reach 2150 by 2025, while that value in 2010 is 1910, which increased by 4.3% yearly. Accordingly, the total CO2 emissions in 2025 will reach 985million tonnes, which shows about 5% increase yearly. Furthermore, we constructed policy scenarios based on energy intensity reduction. The analysis show that CO2 emissions will decrease by 12.14% in 2025 compared to 2010 in the scenario of 5% energy intensity reduction, and 17.8% in the 10% energy intensity reduction scenario. The results obtained in this study provide substantial awareness regarding Irans future energy and CO2 emission outlines.
A new home-made diffusive bag-type passive sampler called Lanwatsu was developed for benzene, toluene, ethylbenzene and xylene monitoring in roadside air. The passive samplers were outdoor validated and deployed together with two commercial passive samplers, Ultra I SKC Inc. and Radiello, for daily roadside air monitoring in East Asian cities including HoChiMinh, Hanoi, Cantho, Danang, Vungtau, Hue (Vietnam), Kuala Lumpur (Malaysia), Kyoto, Osaka (Japan), Nanjing (China) and Singapore in 2011. High daily benzene concentrations of 87, 52, 32, 23, 13, 12 and 48 µg/m³ were observed in HoChiMinh, Hanoi, Cantho, Danang, Hue, Vung Tau (Vietnam), and Kuala Lumpur (Malaysia), respectively. Kyoto and Osaka (Japan) were clean with daily benzene concentrations below 2.3 μg/m³. The daily benzene concentrations in Nanjing (China) and Singapore were 5.6 and 6.9 μg/m³, respectively. The three passive samplers were equivalent. Passive sampling by the Lanwatsu passive sampler is acceptable for daily outdoor benzene monitoring.
Satellite observations for regional air quality assessment rely on comprehensive spatial coverage, and daily monitoring with reliable, cloud-free data quality. We investigated spatiotemporal variation and data quality of two global satellite Aerosol Optical Depth (AOD) products derived from MODIS and VIIRS imagery. AOD is considered an essential atmospheric parameter strongly related to ground Particulate Matter (PM) in Southeast Asia (SEA). We analyze seasonal variation, urban/rural area influence, and biomass burning effects on atmospheric pollution. Validation indicated a strong relationship between AERONET ground AOD and both MODIS AOD (R2 = 0.81) and VIIRS AOD (R2 = 0.68). The monthly variation of satellite AOD and AERONET AOD reflects two seasonal trends of air quality separately for mainland countries including Myanmar, Laos, Cambodia, Thailand, Vietnam, and Taiwan, Hong Kong, and for maritime countries consisting of Indonesia, Philippines, Malaysia, Brunei, Singapore, and Timor Leste. The mainland SEA has a pattern of monthly AOD variation in which AODs peak in March/April, decreasing during wet season from May-September, and increasing to the second peak in October. However, in maritime SEA, AOD concentration peaks in October. The three countries with the highest annual satellite AODs are Singapore, Hong Kong, and Vietnam. High urban population proportions in Singapore (40.7%) and Hong Kong (21.6%) were associated with high AOD concentrations as expected. AOD values in SEA urban areas were a factor of 1.4 higher than in rural areas, with respective averages of 0.477 and 0.336. The AOD values varied proportionately to the frequency of biomass burning in which both active fires and AOD peak in March/April and September/October. Peak AOD in September/October in some countries could be related to pollutant transport of Indonesia forest fires. This study analyzed satellite aerosol product quality in relation to AERONET in SEA countries and highlighted framework of air quality assessment over a large, complicated region.
Long-term exposure to air pollution has been associated with several adverse health effects including cardiovascular, respiratory diseases and cancers. However, underlying molecular alterations remain to be further investigated. The aim of this study is to investigate the effects of long-term exposure to air pollutants on (a) average DNA methylation at functional regions and, (b) individual differentially methylated CpG sites. An assumption is that omic measurements, including the methylome, are more sensitive to low doses than hard health outcomes. This study included blood-derived DNA methylation (Illumina-HM450 methylation) for 454 Italian and 159 Dutch participants from the European Prospective Investigation into Cancer and Nutrition (EPIC). Long-term air pollution exposure levels, including NO2, NOx, PM2.5, PMcoarse, PM10, PM2.5 absorbance (soot) were estimated using models developed within the ESCAPE project, and back-extrapolated to the time of sampling when possible. We meta-analysed the associations between the air pollutants and global DNA methylation, methylation in functional regions and epigenome-wide methylation. CpG sites found differentially methylated with air pollution were further investigated for functional interpretation in an independent population (EnviroGenoMarkers project), where (N=613) participants had both methylation and gene expression data available. Exposure to NO2 was associated with a significant global somatic hypomethylation (p-value=0.014). Hypomethylation of CpG island's shores and shelves and gene bodies was significantly associated with higher exposures to NO2 and NOx. Meta-analysing the epigenome-wide findings of the 2 cohorts did not show genome-wide significant associations at single CpG site level. However, several significant CpG were found if the analyses were separated by countries. By regressing gene expression levels against methylation levels of the exposure-related CpG sites, we identified several significant CpG-transcript pairs and highlighted 5 enriched pathways for NO2 and 9 for NOx mainly related to the immune system and its regulation. Our findings support results on global hypomethylation associated with air pollution, and suggest that the shores and shelves of CpG islands and gene bodies are mostly affected by higher exposure to NO2 and NOx. Functional differences in the immune system were suggested by transcriptome analyses.
Atmospheric deposition nitrogen (ADN) increases the N content in soil and subsequently impacts microbial activity of soil. However, the effects of ADN on paddy soil microbial activity have not been well characterized. In this study, we studied how red paddy soil microbial activity responses to different contents of ADN through a 10-months ADN simulation on well managed pot experiments. Results showed that all tested contents of ADN fluxes (27, 55, and 82kgNha-1 when its ratio of NH4+/NO3--N (RN) was 2:1) enhanced the soil enzyme activity and microbial biomass carbon and nitrogen and 27kgNha-1 ADN had maximum effects while comparing with the fertilizer treatment. Generally, increasing of both ADN flux and RN (1:2, 1:1 and 2:1 with the ADN flux of 55kgNha-1) had similar reduced effects on microbial activity. Furthermore, both ADN flux and RN significantly reduced soil bacterial alpha diversity (p<0.05) and altered bacterial community structure (e.g., the relative abundances of genera Dyella and Rhodoblastus affiliated to Proteobacteria increased). Redundancy analysis demonstrated that ADN flux and RN were the main drivers in shaping paddy soil bacteria community. Overall, the results have indicated that increasing ADN flux and ammonium reduced soil microbial activity and changed the soil bacterial community. The finding highlights how paddy soil microbial community response to ADN and provides information for N management in paddy soil.
Six different approaches are applied in the present study to apportion the sources of precipitation nitrogen making use of precipitation data of dissolved inorganic nitrogen (DIN, including NO3- and NH4+), dissolved organic nitrogen (DON) and δ15N signatures of DIN collected at six sampling sites in the mountain region of Southwest China. These approaches include one quantitative approach running a Bayesian isotope mixing model (SIAR model) and five qualitative approaches based on in-situ survey (ISS), ratio of NH4+/NO3- (RN), principal component analysis (PCA), canonical-correlation analysis (CCA) and stable isotope approach (SIA). Biomass burning, coal combustion and mobile exhausts in the mountain region are identified as major sources for precipitation DIN while biomass burning and volatilization sources such as animal husbandries are major ones for DON. SIAR model results suggest that mobile exhausts, biomass burning and coal combustion contributed 25.1 ± 14.0%, 26.0 ± 14.1% and 27.0 ± 12.6%, respectively, to NO3- on the regional scale. Higher contributions of both biomass burning and coal combustion appeared at rural and urban sites with a significant difference between Houba (rural) and the wetland site (p
This study aimed to determine the spatial distribution of PM2.5 and PM10 collected in four regions (North, Central, South and East Coast) of Peninsular Malaysia during the southwest monsoon. Concurrent measurements of PM2.5 and PM10 were performed using a high volume sampler (HVS) for 24 h (August to September 2018) collecting a total of 104 samples. All samples were then analysed for water soluble inorganic ions (WSII) using ion chromatography, trace metals using inductively coupled plasma-mass spectroscopy (ICP-MS) and polycyclic aromatic hydrocarbon (PAHs) using gas chromatography-mass spectroscopy (GC-MS). The results showed that the highest average PM2.5 concentration during the sampling campaign was in the North region (33.2 ± 5.3 μg m-3) while for PM10 the highest was in the Central region (38.6 ± 7.70 μg m-3). WSII recorded contributions of 22% for PM2.5 and 20% for PM10 mass, with SO42- the most abundant species with average concentrations of 1.83 ± 0.42 μg m-3 (PM2.5) and 2.19 ± 0.27 μg m-3 (PM10). Using a Positive Matrix Factorization (PMF) model, soil fertilizer (23%) was identified as the major source of PM2.5 while industrial activity (25%) was identified as the major source of PM10. Overall, the studied metals had hazard quotients (HQ) value of <1 indicating a very low risk of non-carcinogenic elements while the highest excess lifetime cancer risk (ELCR) was recorded for Cr VI in the South region with values of 8.4E-06 (PM2.5) and 6.6E-05 (PM10). The incremental lifetime cancer risk (ILCR) calculated from the PAH concentrations was within the acceptable range for all regions.
Double perovskite-type catalysts including La2CoMnO6 and La2CuMnO6 are first evaluated for the effectiveness in removing volatile organic compounds (VOCs), and single perovskites (LaCoO3, LaMnO3, and LaCuO3) are also tested for comparison. All perovskites are tested with the gas hourly space velocity (GHSV) of 30,000hr-1, and the temperature range of 100-600°C for C7H8 removal. Experimental results indicate that double perovskites have better activity if compared with single perovskites. Especially, toluene (C7H8) can be completely oxidized to CO2 at 300°C as La2CoMnO6 is applied. Characterization of catalysts indicates that double perovskites own unique surface properties and are of higher amounts of lattice oxygen, leading to higher activity. Additionally, apparent activation energy of 68kJ/mol is calculated using Mars-van Krevelen model for C7H8 oxidation with La2CoMnO6 as catalyst. For durability test, both La2CoMnO6 and La2CuMnO6 maintain high C7H8 removal efficiencies of 100% and 98%, respectively, at 300°C and 30,000hr-1, and they also show good resistance to CO2 (5%) and H2O(g) (5%) of the gas streams tested. For various VOCs including isopropyl alcohol (C3H8O), ethanal (C2H4O), and ethylene (C2H4) tested, as high as 100% efficiency could be achieved with double perovskite-type catalysts operated at 300-350°C, indicating that double perovskites are promising catalysts for VOCs removal.