Nutrient contaminant on monitoring wells in agricultural areas of Kuala Langat, Selangor

Agricultural activities have become one of the prominent contributions to the level of groundwater quality. This paper aims to draw attention to the agricultural pollutants that are associated with the groundwater deterioration. The potential parameters distributions from agricultural areas into groundwater were found to be as nitrate, nitrite, phosphate, ammonia and phosphorous. MWD5 monitoring well shows the highest nitrate concentration. The lowest nitrate concentration recorded was in BKLTW12 monitoring well where this station is located at the North of Kuala Langat Reserve Forest. The nutrients contaminants from agricultural areas were also calculated to determine the accumulation in groundwater according to the different depth of aquifers. It was found that shallow aquifer was more susceptible to pollutants from agricultural areas where the nutrients contaminant will decrease with the increasing of depth. The result shows that nitrate to be below the recommended level for raw water guidelines of Ministry of Health Malaysia except for MWD5 monitoring well. Meanwhile, only BKLTW16, and MWD5 monitoring wells shows exceeded recommended level for ammonia concentration

The simulation and prediction of spatio - temporal urban growth trends using cellular automata models: a review

In recent years, several types of simulation and prediction models have been used within a GIS environment to determine a realistic future for urban growth patterns. These models include quantitative and spatio-temporal techniques that are implemented to monitor urban growth. The results derived through these techniques are used to create future policies that take into account sustainable development and the demands of future generations. The aim of this paper is to provide a basis for a literature review of urban Cellular Automata (CA) models to find the most suitable approach for a realistic simulation of land use changes. The general characteristics of simulation models of urban growth and urban CA models are described, and the different techniques used in the design of these models are classified. The strengths and weaknesses of the various models are identified based on the analysis and discussion of the characteristics of these models. The results of the review confirm that the CA model is one of the strongest models for simulating urban growth patterns owing to its structure, simplicity, and possibility of evolution. Limitations of the CA model, namely weaknesses in the quantitative aspect, and the inability to include the driving forces of urban growth in the simulation process, may be minimized by integrating it with other quantitative models, such as via the Analytic Hierarchy Process (AHP), Markov Chain and frequency ratio models. Realistic simulation can be achieved when socioeconomic factors and spatial and temporal dimensions are integrated in the simulation process

Monitoring and assessment of urban growth patterns using spatio-temporal built-up area analysis

The identification of spatio-temporal patterns of the urban growth phenomenon has become one of the most significant challenges in monitoring and assessing current and future trends of the urban growth issue. Therefore, spatio-temporal and quantitative techniques should be used hand in hand for a deeper understanding of various aspects of urban growth. The main purpose of this study is to monitor and assess the significant patterns of urban growth in Seremban using a spatio-temporal built-up area analysis. The concentric circles approach was used to measure the compactness and dispersion of built-up area by employing Shannon's Entropy method. The spatial directions approach was also utilised to measure the sustainability and speed of development, while the gradient approach was used to measure urban dynamics by employing landscape matrices. The overall results confirm that urban growth in Seremban is dispersed, unbalanced and unsustainable with a rapid speed of regional development. The main contribution of using existing methods with other methods is to provide several spatial and statistical dimensions that can help researchers, decision makers and local authorities understand the trend of growth and its patterns in order to take the appropriate decisions for future urban planning. For example, Shannon's Entropy findings indicate a high value of dispersion between the years 1990 and 2000 and from 2010 to 2016 with a growth rate of approximately 94 and 14%, respectively. Therefore, these results can help and support decision makers to implement alternative urban forms such as the compactness form to achieve an urban form that is more suitable and sustainable. The results of this study confirm the importance of using spatio-temporal built-up area and quantitative analysis to protect the sustainability of land use, as well as to improve the urban planning system via the effective monitoring and assessment of urban growth trends and patterns

Improving the capability of an integrated CA-Markov model to simulate spatio-temporal urban growth trends using an Analytical Hierarchy Process and Frequency Ratio

The creation of an accurate simulation of future urban growth is considered one of the most important challenges in urban studies that involve spatial modeling. The purpose of this study is to improve the simulation capability of an integrated CA-Markov Chain (CA-MC) model using CA-MC based on the Analytical Hierarchy Process (AHP) and CA-MC based on Frequency Ratio (FR), both applied in Seremban, Malaysia, as well as to compare the performance and accuracy between the traditional and hybrid models. Various physical, socio-economic, utilities, and environmental criteria were used as predictors, including elevation, slope, soil texture, population density, distance to commercial area, distance to educational area, distance to residential area, distance to industrial area, distance to roads, distance to highway, distance to railway, distance to power line, distance to stream, and land cover. For calibration, three models were applied to simulate urban growth trends in 2010; the actual data of 2010 were used for model validation utilizing the Relative Operating Characteristic (ROC) and Kappa coefficient methods Consequently, future urban growth maps of 2020 and 2030 were created. The validation findings confirm that the integration of the CA-MC model with the FR model and employing the significant driving force of urban growth in the simulation process have resulted in the improved simulation capability of the CA-MC model. This study has provided a novel approach for improving the CA-MC model based on FR, which will provide powerful support to planners and decision-makers in the development of future sustainable urban planning

Effects of depth and land cover on soil properties as indicated by carbon and nitrogen-stable isotope analysis

The aim of this study was to evaluate the effect of soil depths (0-30, 30-60, and 60-90 cm) and landcover changes on selected physicochemical properties in soils transformed from a secondary forest status to plantation status for the cultivation of rubber and oil palm aged 5 and 15 years. Soil physicochemical properties; bulk density (Bd), pH, soil organic matter (SOM), total organic carbon (TOC), total organic nitrogen (TON), and their corresponding isotopes; and δ13C and δ15N were determined by conventional methods. The results showed that the content of SOM (3.39%) at 0-30 cm was signifi cantly greater than those of the 30-60 and 60-90 cm depths. The same pattern was demonstrated by the content of TOC and TON. With respect to land use, the secondary forest had signifi cantly greater SOM content than the rubber and oil palm plantations aged 5 years. The same pattern was also observed for the content of TOC and TON by land use. Similarly, the δ13C value of -26.85% was greatest at the 0-30 cm depth, while by land use the oil palm aged 5 years had the greatest δ13C. Conversely, the δ15N value of 4.21% was signifi cantly greater at the 60-90 cm depth compared to the 30-60 (1.78%) and the 0-30 cm (-2.03%) depths. The negative value of δ15N revealed the sources (N was a product of multiple variables such as N fi xation, precipitation, rainstorm, and the use of chemical fertilizers), and the limited nitrogen content in the study area. In conclusion, this study demonstrated that the conversion of secondary forest to plantation enhanced the mineralization of soil organic matter and increased SOC concentrations at the sub soil. Therefore, the conversion of the secondary forest to the oil palm plantations must have resulted in a positive effect by contributing to greater soil organic carbon content

Identification of heavy metals in particulate matter PM10 of traffic area, Cheras, Malaysia

This study was initiated to determine the heavy metals in particulate matter (PM10) in three sampling sites with different traffic density: high (CH), medium (CM) and low density (CL) density traffic, PM10 Samples were collected from June to July 2014 during the southwest monsoon using a high volume sampler. The results showed that the PM10 mean levels were significantly higher in CH and CM (207.63 and 164.92 μg/m3) than the CL (90.09 μg/m3). The mean quantity of heavy metals in PM10 was in the order Ba>Zn>Pb>Mn > Cr > As. The highest level of these heavy metals was recorded at CH followed by CM and CL except the mean level of As, which was recorded as being higher compared to CH. Based on the correlation and enrichment analyses, the heavy metals could be divided into two source emissions in the study area – Crustal and non-crustal. Among the heavy metals, As, Pb, Zn and Ba were found to be highly enriched in the atmospheric particulate matter, Cr showed a high EF in low density. Therefore, they were visibly affected by non-crustal sources (vehicular emission sources). In contrast, the EF calculated for Cr was lower in high and medium density suggesting chiefly crustal origin sources. This clearly indicates that traffic density is the main source in the study areas

Application of Frequency Analysis on Peak River Discharge toward the Cumulative Floatable Litter Load at Log Boom Sungai Batu

The accumulation of floatable litter in the river is mainly influenced by the increasing number of human population, rapid urbanization and development which indirectly lead to the changes of hydrological processes in river discharge, decreasing the water quality and aesthetical value of the river. The main objective of this paper is to determine the cumulative floatable litter load captured at the log boom during the extreme events by using the Gumbel distribution method for frequency analysis in river discharge of Sungai Batu. The annual maximum river discharge for a period of 35 years (1982 to 2016) was used in Gumbel distribution method to obtain the discharge for different return period (2, 5, 10, 25, 50, 100, and 200). The result shows that the estimated discharge (103.17 m³/s) can estimate the cumulative floatable litter load (53267.27 kg/day) at 50 years return period. The R2 value obtained from non – linear regression analysis is 0.9986 indicate that Gumbel distribution is suitable to predict the expected discharge of the river. This study is very crucial for the related agencies in highlighting this environmental issues for their future references which can be used as a guidelines during the decision making process in making better improvement

A GIS-based emission inventory at 1 KM -1KM spatial resolution for particular matter (PM10) in Klang Valley, Malaysia

Traffic has greatly contributed to the socio-economic development as well as its inherent environmental impacts. This study estimated the emission of PM10 from the exhaust and nonexhaust, particularly from the use different type of vehicles in Klang valley region. The total PM10 emission from the region was calculated based on US-EPA and the EEA methodologies. Arc GIS is one of the most suitable methods to estimate the total PM10 emission and split between different vehicle types as it is determined by the kilometer covered for each vehicle category. The inventory is further used for traffic account, activity data and a domain size of 50 km×50 km, with cell resolution of 1km × 1km to spatially disaggregate these emissions. The results show that nearly 54% of the PM10 emitted in the region emitted from cars. The results also revealed that nearly 61% of the PM emissions emitted from exhaust. Exhaust and Non-exhaust PM10 emissions are higher in the central part of the Klang Valley, an area with higher volume of vehicles

Source identification of heavy metals in Particulate Matter (PM10) in a Malaysian traffic area using multivariate techniques

This study was conducted to determine heavy metal concentrations in particulate matter (PM10) and the source identification in the areas affected by traffic during the southwest monsoon from June to July 2014. Collection of the particulate samples was done at three sampling sites that have varying traffic densities (high, medium, and low). Samples were collected using a high-volume air sampler. Heavy metals in the particulate matter (PM10) were assessed with inductively coupled plasma mass spectrometry. The results show that the mean concentrations of PM10 for high-, medium-, and low-density traffic were found to be 207.63±7.82, 164.92±10.68, and 90.09±20.70 µg m⁻³, respectively. The concentrations in high- and medium-density areas were found to be significantly higher than 150 µg m⁻³ for 24 hrs as per Recommended Malaysian Air Quality Guidelines (RMAQG). The heavy metals found were dominated by Ba and Fe, followed by Cu > V> Zn > Pb > Mn > Cr> As > Ni >Cd > Co. A comparison of the concentrations of heavy metals with the United State Environmental Protection Agency (USEPA) and World Health Organization (WHO) guidelines revealed that As was higher than the standards in high- and medium-density areas. Cluster analysis (CA) and principal component analysis (PCA) were employed in the identification of the sources of metals for high-, medium-, and low-traffic densities. The CA identified three clusters for high-, medium-, and low-traffic densities, while PCA extracted four sources for high-, medium-, and low-traffic densities and the major pollution sources identified were vehicle exhaust emission, non-exhaust emission (brake and tire wear), and re-suspension dust

The influence of land use activities towards Mass Rapid Transit (MRT) feeder bus service ridership

The Mass Rapid Transit (MRT) feeder bus service is a complementary public transport service provided to encourage ridership of MRT rail services in Malaysia. In brief, this feeder bus service plays a role in connecting people to and from MRT stations. The objective of this study is to determine the passenger volume generated at each MRT feeder bus stop location in the study area, and relate it to surrounding land use activities. Using the rule of thumb in public transportation systems, 200 m and 400 m radial buffers were identified as catchment areas of the bus stops. The key finding from this study is the relationship between volume of passenger and land use activities. This study concludes that land use activities influence MRT ridership, and that the presence of shelters or waiting poles is important to encourage ingress or egress