Analysis of urbanisation, industrialization, irrigation activities, and ground water quality in Indonesia

There is a growing need to address groundwater quality on a global scale, particularly in countries that heavily rely on urbanisation and industrialization. This has led to an increased focus on dedicated research efforts. This study aims to examine the impact of urbanisation, industrialization, and irrigation activities on groundwater quality in Rengel District, Tuban Regency, Indonesia. Additionally, the research explores the moderating influence of government support in the context of urbanization, industrialization, irrigation activities, and groundwater quality in Indonesia. Primary data were gathered through surveys conducted with officials from the Ministry of National Development Planning in Indonesia, and the reliability of the data and interrelationships among variables were assessed using SPSS-AMOS. The results suggest that there is a link between urbanisation and irrigation activities and groundwater quality in Indonesia. On the other hand, industrialization seems to have a negative impact on groundwater quality. Furthermore, the study highlights the important role of government support in influencing the connections between urbanisation, industrialization, irrigation activities, and groundwater quality in Indonesia.Nurkholis (Environmental Health Study Program, Faculty of Public Health, Airlangga University), Azizah (Faculty of Public Health, Airlangga University), Mohd Talib Latif (Faculty of Science and Technology, Universiti Kebangsaan Malaysia)Includes bibliographical reference

Carbon emission from vehicular source in selected industrial areas in Malaysia

Vehicle emission has been the major source of environmental pollution for the past 30 years. The urbanization, industrialization and traffic systems growth are causing more air pollution problem in the city creating an uncomfortable atmosphere to live in. Carbon emission is one of the main air pollutants causing problems in the local and global community. This paper discusses the effect of increasing vehicular traffic on the road in a few industrial sites within cities in Malaysia to the release of carbon dioxide and carbon monoxide in the atmosphere. This paper studies the traffic trend using census data from JKJR and converted into carbon emission using DEFRA GHG Conversion Factors and air quality trend from Alam Sekitar Malaysia in three selected industrial area in Malaysia, which are Shah Alam Industrial Area, Seremban-Senawang Industrial Area and Kuantan-Pekan Industrial Area. Carbon monoxide concentration trend in Shah Alam and Seremban-Senawang fluctuates with the highest concentration of 1.78ppm for Shah Alam and 0.77ppm in Seremban-Senawang in the earlier years and becoming lower in 2010 and 2011 compared to the trend in Kuantan-Pekan, which increased since 2001 to 2011 with the highest concentration of 0.54ppm. Carbon dioxide concentration is highest at Shah Alam ranging from 18067.17 to 88150.01 kg CO2 /km travelled compared to Kuantan-Pekan ranging from 3520.39 to 6953.69 kg CO2 /km travelled and Seremban-Senawang ranging from 3783.29 to 5734.30 kg CO2 /km travelled. Based on the early findings, the increasing vehicular traffic resulted in increment of carbon emission in the atmosphere

Levoglucosan as an Indicator of Biomass Burning from Selected Tropical Plants

South East Asia has been recognized as one of the region most affected by atmospheric haze from biomass burning and the combustion of various plants. The distribution of atmospheric aerosols from biomass burning itself can be determined through the level of levoglucosan found in the atmosphere. In this study, the amount of levoglucosan produced by five selected tropical plants after combustion processes was determined using the modified anthrone-sulfuric colorimetric method. The results showed that the concentration of levoglucosan in the plant soot (after combustion) ranged from between 0.49 ± 0.28 mg/g to 10.51 ± 4.47 mg/g. Among the five plants, Oryza sativa was found to have the highest levoglucosan content and the amount of levoglucosan produced by biomass burning was found to be influenced by the photo oxidation processes e.g. by ultra violet radiation and ozonization

Composition and sources of Sterols in Pulau Tinggi, Johor, Malaysia.

This study explores the role of sterols as lipid biomarkers to indicate their input which originates from various sources in the marine environment. Sterols and their ratios were investigated in sediments taken from sixteen sampling stations at Pulau Tinggi, Johor in order to assess the sources of organic matter. The compounds extracted from the sediments were quantified using a gas chromatography-mass spectrometry (GC-MS). The distributions of sterols indicated that organic matter at all sampling stations originated from a mixture of marine source and terrestrial origins at different proportions. A total of eleven sterols were quantified, with the major compounds being phytosterols (44% of total sterols), cholesterol (11%), brassicasterol (11%) and fecal sterols (12%)

Correlation between hotspots and air quality in Pekanbaru-Riau, Indonesia in 2006-2007

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

Determination of polycyclic aromatic hydrocarbons in human blood samples using solid phase extraction and gas chromatography mass spectrometry- a review

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous pollutants with toxic effects and adverse health impacts on general population. Several methods of extraction had been applied to extract PAHs from human blood samples such as solid phase extraction (SPE). The SPE represents one of the most common techniques for extraction and clean-up procedures as it needs low quantity of solvents with less manual efforts. Similarly, various analytical instruments like gas chromatography coupled to mass spectrometry (GC-MS) was used to measure the PAHs levels. Gas chromatography is a simple, fast, and very efficient method for solvents and small organic molecules. This review provides an overview of the measured concentrations of PAHs in human blood samples through the application of SPE and GC-MS during the last ten years. While these studies used various solvents, their application of SPE method and GC-MS revealed rewarding results about the determination of PAHs levels in the human samples

Observed trends in extreme temperature over the Klan

This study investigates the recent extreme temperature trends across 19 stations in the Klang Valley, Malaysia, over the period 2006−16. Fourteen extreme index trends were analyzed using the Mann−Kendall non-parametric test, with Sen’s slope as a magnitude estimator. Generally, the annual daily mean temperature, daily mean maximum temperature, and daily mean minimum temperature in the Klang Valley increased significantly, by 0.07°C yr−1, 0.07°C yr−1 and 0.08°C yr−1 , respectively. For the warm temperature indices, the results indicated a significant upward trend for the annual maximum of maximum temperature, by 0.09°C yr−1, and the annual maximum of minimum temperature, by 0.11°C yr−1. The results for the total number of warm days and warm nights showed significant increasing trends of 5.02 d yr−1 and 6.92 d yr−1 , respectively. For the cold temperature indices, there were upward trends for the annual minimum of maximum temperature, by 0.09°C yr−1, and the annual minimum of minimum temperature, by 0.03°C yr−1, concurrent with the decreases in the total number cold days (TX10P), with −3.80 d yr−1, and cold nights (TN10P), with −4.33 d yr−1. The 34°C and 37°C summer days results showed significant upward trends of 4.10 d yr−1 and 0.25 d yr−1, respectively. Overall, these findings showed upward warming trends in the Klang Valley, with the minimum temperature rate increasing more than that of the maximum temperature, especially in urban areas

Impact of covid-19 pandemic on traffic volume and air quality in urban areas

The large transmission of COVID-19 has resulted in a deep impact on the surrounding urban environments, especially on air quality and traffic flows. The objective of this study was to analyze air pollutant concentrations (PM10, SO2, NO2, CO, and O3) and traffic volumes at five congested districts (Bundaran HI, Kelapa Gading, Jagakarsa, Lubang Buaya, and Kebon Jeruk) within Jakarta city impacted by the large-scale social restriction (LSSR) policy. Air quality data during three periods; before, during, and after the LSSR at five observed districts was obtained from the Department of Environment of Jakarta using the Air Quality Monitoring (AQMS) tool. While vehicle speed data were obtained from the waze data during the study period. In this study, air pollutant data during three periods; before, during, and after the LSSR were compared with vehicle speed and meteorological data using a statistical analysis. Results revealed the mean traffic volume at all five districts has greatly reduced by 19% from before to during the LSSR period. It was consistent with the mean PM10, NO2, CO, and SO2 concentrations which also dropped about 46%, 45%, 30%, and 23% respectively. In contrast, the concentrations of air pollutants significantly increased after the LSSR period. During the LSSR period, the traffic volume was negatively associated with the O3 concentration (r = −.86, p < .01), it was different with before the LSSR periods where the traffic volume associated with CO (r = .88, p < .01) and NO2 (r = .89, p < .01). The broad analysis of changes in air pollutants and traffic volumes can be used by the authorities to arrange a good air quality management and an effective way for current and future scenarios

Contribution of aerosol species to the 2019 smoke episodes over the east coast of peninsular Malaysia.

Large-scale biomass burning (BB) emits large amounts of aerosols that lead to transboundary smoke events and adversely impacts human health, whilst causing societal and environmental issues. High ambient PM2.5 concentration in the year 2019 based on New Malaysia Ambient Air Quality Standard (NMAAQS) was identified as high pollution episodes, HP1 and HP2 on the east coast Peninsular Malaysia (ECPM). Meanwhile, the low PM2.5 concentration episodes are known as LP1 and LP2. The transboundary smoke events in Indochina and Indonesia are linked to HP1 (March–April) and HP2(August–September), respectively from backward trajectory and MERRA-2 model re-analyses weather data. The correlation analysis showed a significantly strong positive correlation (r) of black carbon (HP1: 0.91; HP2: 0.96), organic carbon (HP1: 0.90; HP2: 0.94), and sulphate (HP1: 0.80; HP2: 0.61) with the aerosol optical depth (AOD) levels during high pollution episodes. The synoptic weather condition and inter-monsoon in HP1 and southwest monsoon in HP2 introduce strong wind speed and favourable wind pattern that can initiate the long-range transport of high AOD and PM2.5 to the ECPM region. In conclusion, this study demystified the sources of BB emissions, the transport route of transboundary smoke events, their influence factors during different high pollution periods, and the links between aerosol species from local and non-local emissions with AOD levels and PM2.5 concentrations along the ECPM, which altogether provide crucial information on climate variability signal and can help in developing a corresponding strategy for high pollution episodes

Rules Discovery of High Ozone in Klang Areas using Data Mining Approach

Ground level ozone (O3) is one of the common pollution issues that has a negative influence on human health. However, the increasing trends in O3 level nowadays which due to rapid development has become a great concern over the world. Thus, developing an accurate O3 forecasting model is necessary. However, the interesting pattern from the data should be identified beforehand. Association rules is a data mining technique that has an advantage to discover frequent patterns in a dataset, which subsequently will be useful in the research domain. Therefore, this paper presents the discovering knowledge based on association rules and clustering technique towards a climatological O3 dataset. In this study, the data was analysed to find the behaviour of each precursors. Later K-means clustering technique was used to find the suitable range for each chosen variable independently, then applied Apriori based association rules technique to present the behaviours in a meaningful and understandable format. The climatological O3 time series data has been collected from Department of Environment for Klang station from year 1997 to 2012. However, the proposed method only applied on high O3 concentration data during stated years to find the association pattern. The outcome has discovered 17 strong rules.  The patterns and behaviours of the selected variables during high O3 concentration has been discovered. The rules are benefit to the government on how to control the air quality later