Influence of peatland and land cover distribution on fire regimes in insular Southeast Asia

Anthropogenic biomass burning in insular Southeast Asia facilitates conversion and degradation of ecosystems and emits high amounts of carbon into the atmosphere. We analyzed the influence of peat soil and land cover distribution on the occurrence and characteristics of vegetation fires. Two years of satellite-based active fire detections over Peninsular Malaysia, Sumatra, Borneo and Java were examined together with land cover and peatland maps. Our results showed that fire occurrence nearly tripled (23,000 → 68,000) from a wet La Niña year (2008) to a drier El Niño year (2009). In both years, fires were concentrated in peatlands (in 2009 41% of fires vs. 10% of land area), and the majority of large-scale burning took place in peatlands. Variation in peatland land cover within the study area was noticed to create remarkable different fire regimes. Biomass burning in the intensely managed Sumatran peatlands was characterized by large-scale land clearance fires that took place annually to varying extent. The largely unmanaged degraded peatland ecosystems of Borneo, on the other hand, experienced very little fire activity in a wet year but were ravaged by large-scale wildfires when El Niño conditions arose. We conclude that fire regime characteristics in insular Southeast Asia are strongly connected to occurrence of peat soil and land management status. This leads to high variation of fire activity within this region both annually (depending on weather patters) and over longer time range (depending on land cover/management issues) and greatly complicates estimation of the effects of fires.     

Spatio-temporal characteristics of PM10 concentration across Malaysia

The recurrence of forest fires in Southeast Asia and associated biomass burning, has contributed markedly to the problem of trans-boundary haze and the long-range movement of pollutants in the region. Air pollutants, specifically particulate matter in the atmosphere, have received extensive attention, mainly because of their adverse effect on people's health. In this study, the spatial and temporal variability of the PM10 concentration across Malaysia was analyzed by means of the rotated principal component analysis. The results suggest that the variability of the PM10 concentration can be decomposed into four dominant modes, each characterizing different spatial and temporal variations. The first mode characterizes the southwest coastal region of the Malaysian Peninsular with the PM10 showing a peak concentration during the summer monsoon i.e. when the winds are predominantly southerlies or southwesterlies, and a minimal concentration during the winter monsoon. The second mode features the region of western Borneo with the PM10 exhibiting a concentration surge in August–September, which is likely to be the result of the northward shift of the Inter Tropical Convergence Zone (ITCZ) and the subsequent rapid arrival of the rainy season. The third mode delineates the northern region of the Malaysian Peninsular with strong bimodality in the PM10 concentration. Seasonally, this component exhibits two concentration maxima during the late winter and summer monsoons, as well as two minima during the inter-monsoon periods. The fourth dominant mode characterizes the northern Borneo region which exhibits weaker seasonality of the PM10 concentration. Generally, the seasonal fluctuation of the PM10 concentration is largely associated with the seasonal variation of rainfall in the country. However, in addition to this, the PM10 concentration also fluctuates markedly in two timescale bands i.e. 10–20 days quasi-biweekly (QBW) and 30–60 days lower frequency (LF) band of the intra-seasonal timescales. These intra-seasonal fluctuations show strong seasonality with the largest fraction of variance occurring during the boreal summer and the weakest variance during the winter. Generally, the LF intra-seasonal oscillation is stronger compared to the QBW intra-seasonal band.     

Approximating SWAT Model Using Artificial Neural Network and Support Vector Machine1

Abstract: With the popularity of complex, physically based hydrologic models, the time consumed for running these models is increasing substantially. Using surrogate models to approximate the computationally intensive models is a promising method to save huge amounts of time for parameter estimation. In this study, two learning machines [Artificial Neural Network (ANN) and support vector machine (SVM)] were evaluated and compared for approximating the Soil and Water Assessment Tool (SWAT) model. These two learning machines were tested in two watersheds (Little River Experimental Watershed in Georgia and Mahatango Creek Experimental Watershed in Pennsylvania). The results show that SVM in general exhibited better generalization ability than ANN. In order to effectively and efficiently apply SVM to approximate SWAT, the effect of cross‐validation schemes, parameter dimensions, and training sample sizes on the performance of SVM was evaluated and discussed. It is suggested that 3‐fold cross‐validation is adequate for training the SVM model, and reducing the parameter dimension through determining the parameter values from field data and the sensitivity analysis is an effective means of improving the performance of SVM. As far as the training sample size, it is difficult to determine the appropriate number of samples for training SVM based on the test results obtained in this study. Simple examples were used to illustrate the potential applicability of combining the SVM model with uncertainty analysis algorithm to save efforts for parameter uncertainty of SWAT. In the future, evaluating the applicability of SVM for approximating SWAT in other watersheds and combining SVM with different parameter uncertainty analysis algorithms and evolutionary optimization algorithms deserve further research.     

Metal ferrites nanoparticles for catalytic and photocatalytic ozonation in wastewater treatment: a review

Environmental Chemistry Letters - The discharge of various pollutant-rich wastewater in large volumes without adequate treatment seriously endangers the environment. Catalytic and photocatalytic...     

Physicochemical factors and sources of particulate matter at residential urban environment in Kuala Lumpur

Long-term measurements (2004–2011) of PM₁₀ (particulate matter with an aerodynamic diameter <10 μm) and trace gases (carbon monoxide [CO], ozone [O₃], nitrogen oxide [NO], oxides of nitrogen [NO_x], nitrogen dioxide [NO₂], sulfur dioxide [SO₂], methane [CH₄], nonmethane hydrocarbon [NMHC]) have been conducted to study the effect of physicochemical factors on the PM₁₀ concentration. In addition, this study includes source apportionment of PM₁₀ in Kuala Lumpur urban environment. An advanced principal component analysis (PCA) technique coupled with absolute principal component scores (APCS) and multiple linear regression (MLR) has been applied. The average annual concentration of PM₁₀ for 8 yr is 51.3 ± 25.8 μg m^?3, which exceeds the Recommended Malaysian Air Quality Guideline (RMAQG) and international guideline values. Detail analysis shows the dependency of PM₁₀ on the linear changes of the motor vehicles in use and the amount of biomass burning, particularly from Sumatra, Indonesia, during southwesterly monsoon. The main sources of PM₁₀ identified by PCA-APCS-MLR are traffic combustion (28%), ozone coupled with meteorological factors (20%), and windblown particles (1%). However, the apportionment procedure left 28.0 μg m^?3, that is, 51% of PM₁₀ undetermined.

Implications: Air quality is always a top concern around the globe. Especially in the South Asian regions, measures are not yet sufficient; as revealed in our studies, the concentrations of particulate matters exceed the tolerable limits. Long-term data analysis and characterization of particular matters and their sources will aid the policy makers and the concerned authority to adapt measures and policies according to the circumstances. Additionally, similar intensive studies will give insight about future implications of air quality management.     

Formation and control of nitrogenous DBPs from Western Australian source waters: Investigating the impacts of high nitrogen and bromide concentrations

We studied the formation of four nitrogenous DBPs(N-DBPs) classes(haloacetonitriles,halonitromethanes, haloacetamides, and N-nitrosamines), as well as trihalomethanes and total organic halogen(TOX), after chlorination or chloramination of source waters. We also evaluated the relative and additive toxicity of N-DBPs and water treatment options for minimisation of N-DBPs. The formation of halonitromethanes, haloacetamides, and N-nitrosamines was higher after chloramination and positively correlated with dissolved organic nitrogen or total nitrogen. N-DBPs were major contributors to the toxicity of both chlorinated and chloraminated waters. The strong correlation between bromide concentration and the overall calculated DBP additive toxicity for both chlorinated and chloraminated source waters demonstrated that formation of brominated haloacetonitriles was the main contributor to toxicity. Ozone–biological activated carbon treatment was not effective in removing N-DBP precursors. The occurrence and formation of N-DBPs should be investigated on a case-by-case basis, especially where advanced water treatment processes are being considered to minimise their formation in drinking waters, and where chloramination is used for final disinfection.     

Tertiary recycling of plastics waste: an analysis of feedstock,chemical and biological degradation methods

Journal of Material Cycles and Waste Management - Globally, there is rising awareness of the severity of the plastic waste problem, and the implications of plastics accumulation in the environment....     

Synthesis and applications of carbon quantum dots derived from biomass waste: a review

Environmental Chemistry Letters - In the context of the circular economy and decreasing earth resources, waste should be converted into value-added materials such as carbon quantum dots, which are...     

Microplastic emissions from household washing machines: preliminary findings from Greater Kuala Lumpur (Malaysia)

Environmental Science and Pollution Research - Microplastics have been recognized as emerging pollutants with potential ecotoxicological impact. The contribution of washing machine use to...