The paper examines the propagation direction and speed of large scale travelling ionospheric disturbances (LSTIDs) obtained from GPS observations of extreme geomagnetic storms during the 23rd solar cycle; these are the October 2003 and November 2003 geomagnetic storms. In the analysis, the time delay between total electron content (TEC) structures at Scott Base station (SBA) (Lat. –77.85º, Long. 166.76º), McMurdo (McM4), (Lat. –77.84º, Long. 166.95º), Davis (DAV1), (Lat. –68.58º, Long. 77.97º) and Casey station (CAS1) (Lat. –66.28º, Long. 110.52º) GPS stations as well as the distance between these stations were employed in the analysis. The measurements during the October 2003 storm showed obvious time delay between the TEC enhancement occurrences at SBA/MCM4, DAV1 and CAS1 stations. The time delay indicated a movement of the ionospheric structures from higher to lower latitudes in a velocity ranging between 0.8 km/s – 1.2 km/s. The first sudden TEC enhancement was observed at SBA/McM4 (Lat. –75.84º) followed by CAS1 station (Lat. –66.28º) and the final TEC enhancement was seen at DAV1 station (Lat. –68.58º) with TEC magnitude decreasing while moving from higher to lower latitudes. One important observation was that although the latitude of the CAS1 station was lower than the DAV1 station, the TEC enhancement was firstly seen at the CAS1 station due to the shorter distance between SBA and CAS1 compared with the distance between SBA and CAS1 of about 500 km. The TEC measurements during the November 2003 storm showed an opposite propagation direction (i.e. poleward direction from lower to higher latitudes) which was seen with a velocity ranging between 0.3 km/s – 0.4 km/s. As similar response was observed using vertical TEC measurements obtained from individual PRN satellites but with higher velocity ranges (1.2 km/s – 2.4 km/s during October
and 0.5 km/s – 0.7 km/s during November). The equatorward or poleward expansion of LSTIDs during the October and November 2003 storms was probably caused by the disturbances in the neutral temperature which occurred close to the dayside convection throat or due to the neutral wind oscillation induced by atmospheric gravity waves launched from the aurora region.
Katabatic winds dramatically affect the polar climate. Their activity depends on density of air and temperature in the source region. This paper presents for first time an analysis of the precipitable water vapour (PWV) variability and its relation to a katabatic event at Scott Base station, Antarctica. A significant effect in their characteristics toward calculation of a reliable user accuracy in GPS applications is addressed. Our investigations using the data between 21st and 30th of November 2002 showed that the PWV profile exhibited an irregular pattern with a maximum value of 7.38 mm (~ 6 mm on average), and was more strongly influenced by relative humidity than by wind speed activity. The dominant wind flow during this period was from the North-Northeast (blowing from the Ross Sea) with a median speed of 4.96 ms–1. The PWV was high when the temperature was between –15ºC and –11ºC. During the dates identified as a katabatic event between 21:30 UT of 28th November and 18:40 UT on 29th November, the wind blew from the Southeast-South direction (from the Ross Ice Shelf) with a maximum speed of 10.92 ms–1. The PWV increased ~1.4 mm (23%) from the mean value, indicating severe wind during this event which had pronounced effect on GPS observations.
This paper introduces a method for modification of the formula of the fractal box counting dimension. The method is based on the utilization of the probability distribution formula in the fractal box count. The purpose of this method is to use it for the discrimination of oil spill areas from the surrounding features e.g. sea surface and look-alikes in RADARSAT-1 SAR data. The result showed that the new formula of the fractal box counting dimension was able to discriminate between oil spills and look-alike areas. The low wind area had the highest fractal dimension peak of 2.9, as compared to the oil slick and the surrounding rough sea. The maximum error standard deviation of the low wind area was 0.68 which performed with a 2.9 fractal dimension value.
Over the last decades, the development of the Klang Valley (Malaysia), as an urban commercial and industrial area, has elevated the risk of atmospheric pollutions. There are several significant sources of air pollutants which vary depending on the background of the location they originate from. The aim of this study is to determine the trend and status of air quality and their correlation with the meteorological factors at different air quality monitoring stations in the Klang Valley. The data of five major air pollutants (PM(10), CO, SO(2), O(3), NO(2)) were recorded at the Alam Sekitar Sdn Bhd (ASMA) monitoring stations in the Klang Valley, namely Petaling Jaya (S1), Shah Alam (S2) and Gombak (S3). The data from these three stations were compared with the data recorded at Jerantut, Pahang (B), a background station established by the Malaysian Department of Environment. Results show that the concentrations of CO, NO(2) and SO(2) are higher at Petaling Jaya (S1) which is due to influence of heavy traffic. The concentrations of PM(10) and O(3,) however, are predominantly related to regional tropical factors, such as the influence of biomass burning and of ultra violet radiation from sunlight. They can, though, also be influenced by local sources. There are relatively stronger inter-pollutant correlations at the stations of Gombak and Shah Alam, and the results also suggest that heavy traffic flow induces high concentrations of PM(10), CO, NO(2) and SO(2) at the three sampling stations. Additionally, meteorological factors, particularly the ambient temperature and wind speed, may influence the concentration of PM(10) in the atmosphere.
Riparian areas hold vast number of flora and fauna with exceptional contributions to the ecosystem. A study was conducted in Sungai Sepetang, Sungai Rembau and Sungai Chukai to identify the insect community in a riparian zone of Peninsular Malaysia. Sampling was conducted in six consecutive months from December 2017 to May 2018 during both day and night using sweep nets. Twenty sampling stations (S1-S20) had been assembled along the riverbanks with an average distance of 200 m between each station. The 17,530 collected insects were from 11 orders and consisted of Diptera, Coleoptera, Hemiptera, Hymenoptera, Lepidoptera, Neuroptera, Orthoptera, Blattodea, Thysanoptera, Mantodea and Odonata. The three most abundant orders were Diptera (33.84%; 5933 individuals), Coleoptera (28.82%; 5053 individuals) and Hemiptera (25.62%: 4491 individuals). The collected insect community consisted of different guilds such as the scavenger, predator, herbivore, pollinator and parasitoid. Sungai Sepetang and Sungai Rembau were dominated by mangrove flora, Sonneratia caseolaris (Myrtales: Lythraceae), while Sungai Chukai was dominated by Barringtonia racemosa. There was a significant difference (p < 0.05) in the composition of insects between the three rivers though clustering analysis showed that the insect communities in Sungai Sepetang and Sungai Rembau were 100% similar compared to Sungai Chukai which consisted of a totally different community. There is a significant negative correlation between abundance of insects with salinity and wind speed at Sungai Chukai and Sungai Sepetang.
Amplatzer Vascular Plug IV (Abbott, USA) is usually used for the occlusion of abnormal tortuous vessels and has not been tried for the transcatheter closure of perimembranous ventricular septal defects with wind-sock morphology. Here, we report on three successful cases of perimembranous ventricular septal defect transcatheter closure using Amplatzer Vascular Plug IV. We did not observe residual shunting or new onset of complications during follow up. These preliminary positive results advocate the application and suitability of Amplatzer Vascular Plug IV for closing wind-sock-like perimembranous ventricular septal defects.
The Changbai (also known as "Baekdu") Mountain, on the border between China and North Korea, is the highest mountain (2750 m) in northeastern China. Recently, this mountain region has experienced a dramatic increase in air pollution, not only because of increasing volumes of tourism-derived traffic but also because of the long-range transport of polluted westerly winds passing through major industrial and urban cities in the eastern region of China. To assess the relative importance of the two sources of pollution, 16 polycyclic aromatic hydrocarbons (PAHs) as model substances were determined in the mountain soil. A total of 32 soil samples were collected from different sides of the mountain at different latitudes between July and August of 2009. The ∑PAH concentrations were within the range 38.5-190.1 ng g(-1) on the northern side, 117.7-443.6 ng g(-1) on the southern side, and 75.3-437.3 ng g(-1) on the western side. A progressive increase in the level of ∑PAHs with latitude was observed on the southern and western sides that face the westerly wind with abundant precipitation. However, a similar concentration gradient was not observed on the northern side that receives less rain and is on the leeward direction of the wind. The high-molecular-weight PAH compounds were predominant in the soils on the southern and western sides, while low-molecular-weight PAHs dominated the northern side soils. These findings show that the distribution of PAHs in the mountain soil is strongly influenced by the atmospheric long-range transport and cold trapping.
Renewable energy assessments for resort islands in the South China Sea were conducted that involves the collection and analysis of meteorological and topographic data. The meteorological data was used to assess the PV, wind and hydropower system potentials on the islands. Furthermore, the reconnaissance study for hydro-potentials were conducted through topographic maps in order to determine the potential sites suitable for development of run-of-river hydropower generation. The stream data was collected for 14 islands in the South China Sea with a total of 51 investigated sites. The data from this study are related to the research article "Optimal combination of solar, wind, micro-hydro and diesel systems based on actual seasonal load profiles for a resort island in the South China Sea" published in Energy (Khan et al., 2015) [1].
The data consists of actual generation-side auditing including the distribution of loads, seasonal load profiles, and types of loads as well as an analysis of local development planning of a resort island in the South China Sea. The data has been used to propose an optimal combination of hybrid renewable energy systems that able to mitigate the diesel fuel dependency on the island. The resort island selected is Tioman, as it represents the typical energy requirements of many resort islands in the South China Sea. The data presented are related to the research article "Optimal Combination of Solar, Wind, Micro-Hydro and Diesel Systems based on Actual Seasonal Load Profiles for a Resort Island in the South China Sea" [1].
The measurement of this data aims to evaluate the wind shear variability at three selected sites in Malaysia. The sites are Kudat in Sabah, Kijal in Terengganu and Langkawi in Kedah. Both sites in Kudat and Kijal is located in coastal areas with few buildings or trees, while the site in Langkawi is a coastal area with many buildings or trees. The variables were measured using the sensors that mounted on the wind mast with the maximum height from 55 m to 70 m from ground level. The variables measured were wind speed, wind direction, temperature, and pressure, while the wind shear data were directly generated using the power law equation. The averaged wind shear based on measured multiple height wind speed at selected sites is larger than the 1/7 law (0.143). Also, the value of wind shear was higher in order Langkawi > Kudat > Kijal. Ultimately, the wind shear data are essential and can be reused in the wind energy potential study, especially for data extrapolation to desired wind turbine hub height.
This paper provides detail on sequence analysis of hazy days based on eight monitoring stations from three states (Kelantan, Terengganu and Pahang) in the eastern region of Peninsular Malaysia. The dataset comprises of 1502 daily mean hazy days that had been measured for a decade. The meteorology data namely wind speed, wind direction, air temperature, relative humidity and particulate matter (PM10) were used to comprehend the variability, and the relationship existed amongst variables. The final dataset consists of a summary descriptive analysis and a boxplot, where all five variables were involved, including the minimum, maximum, mean, 1st quartile, median, 3rd quartile and standard deviation are presented. Apart from descriptive analysis, the normality test and histogram were performed as well.
The aim of the measurement of this data is to evaluate the Indoor Air Quality (IAQ) in terms of chemical and physical parameters. Data were collected at three different kindergartens having different surrounding activities (industrial, institutional, residential area). The chemical parameters measured were respirable suspended particulates of PM10, PM2.5, PM1, carbon monoxide and carbon dioxide, and the concentrations are within the acceptable limit. Physical parameters of wind speed are within the standard, while temperature and relative humidity exceeded the acceptable limit. A strong correlation was found between the chemical IAQ parameters with thermal comfort parameters (temperature and relative humidity). The concentration of IAQ pollutants is higher in order of residential > institutional > industrial.
Intensive land expansion of commercial oil palm agricultural lands results in reducing the size of peat swamp forests, particularly in Southeast Asia. The effect of this land conversion on macrofungal biodiversity is, however, understudied. We quantified macrofungal biodiversity by identifying mushroom sporocarps throughout four different habitats; logged peat swamp forest, large-scale oil palm plantation, monoculture, and polyculture smallholdings. We recorded a total of 757 clusters of macrofungi belonging to 127 morphospecies and found that substrates for growing macrofungi were abundant in peat swamp forest; hence, morphospecies richness and macrofungal clusters were significantly greater in logged peat swamp forest than converted oil palm agriculture lands. Environmental factors that influence macrofungi in logged peat swamp forests such as air temperature, humidity, wind speed, soil pH, and soil moisture were different from those in oil palm plantations and smallholdings. We conclude that peat swamp forests are irreplaceable with respect to macrofungal biodiversity. They host much greater macrofungal biodiversity than any of the oil palm agricultural lands. It is imperative that further expansion of oil palm plantation into remaining peat swamp forests should be prohibited in palm oil producing countries. These results imply that macrofungal distribution reflects changes in microclimate between habitats and reduced macrofungal biodiversity may adversely affect decomposition in human-modified landscapes.
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.
This study examines the three-way linkage relationships between CO2 emission, energy consumption and economic growth in Malaysia, covering the 1975-2015 period. An autoregressive distributed lag approach was employed to achieve the objective of the study and gauged by dynamic ordinary least squares. Additionally, vector error correction model, variance decompositions and impulse response functions were employed to further examine the relationship between the interest variables. The findings show that economic growth is neither influenced by energy consumption nor by CO2 emission. Energy consumption is revealed to be an increasing function of CO2 emission. Whereas, CO2 emission positively and significantly depends on energy consumption and economic growth. This implies that CO2 emission increases with an increase in both energy consumption and economic growth. Conclusively, the main drivers of CO2 emission in Malaysia are proven to be energy consumption and economic growth. Therefore, renewable energy sources ought to be considered by policy makers to curb emission from the current non-renewable sources. Wind and biomass can be explored as they are viable sources. Energy efficiency and savings should equally be emphasised and encouraged by policy makers. Lastly, growth-related policies that target emission reduction are also recommended.
Dhaka and its neighboring areas suffer from severe air pollution, especially during dry season (November-April). We investigated temporal and directional variations in particulate matter (PM) concentrations in Dhaka, Gazipur, and Narayanganj from October 2012 to March 2015 to understand different aspects of PM concentrations and possible sources of high pollution in this region. Ninety-six-hour backward trajectories for the whole dry season were also computed to investigate incursion of long-range pollution into this area. We found yearly PM10 concentrations in this area about three times and yearly PM2.5 concentrations about six times greater than the national standards of Bangladesh. Dhaka and its vicinity experienced several air pollution episodes in dry season when PM2.5 concentrations were 8-13 times greater than the World Health Organization (WHO) guideline value. Higher pollution and great contribution of PM2.5 most of the time were associated with the north-westerly wind. Winter (November to January) was found as the most polluted season in this area, when average PM10 concentrations in Dhaka, Gazipur, and Narayanganj were 257.1, 240.3, and 327.4 μg m(-3), respectively. Pollution levels during wet season (May-October) were, although found legitimate as per the national standards of Bangladesh, exceeded WHO guideline value in 50 % of the days of that season. Trans-boundary source identifications using concentration-weighted trajectory method revealed that the sources in the eastern Indian region bordering Bangladesh, in the north-eastern Indian region bordering Nepal and in Nepal and its neighboring areas had high probability of contributing to the PM pollutions at Gazipur station.
A comprehensive study of the chemical composition of rainwater was carried out from October 2016 to September 2017 in the equatorial tropical rainforest region of northwestern Borneo. Monthly cumulative rainwater samples were collected from different locations in the Limbang River Basin (LRB) and were later categorized into seasonal samples representing northeast monsoon (NEM), southwest monsoon (SWM), and inter-monsoon (IM) periods. Physical parameters (pH, EC, TDS, DO, and turbidity), major ions (HCO3-, Cl-, Ca2+, Mg2+, Na+, and K+) and trace metals (Co, Ni, Cd, Fe, Mn, Pb, Zn, and Cu) were analyzed from collected rainwater samples. Rainwater is slightly alkaline with mean pH higher than 5.8. Chloride and bicarbonate are the most abundant ions, and the concentration of major ions in seasonal rainwater has shown slight variation which follows a descending order of HCO3-> Cl-> Na+ > Ca2+ > Mg2+ > K+ in NEM and Cl- > HCO3- > Na+ > Ca2+ > K+ > Mg2+ in SWM and Cl- > HCO3- > Na+ > Ca2+ > Mg2+ > K+ in IM period. Trace metals such as Fe and Ni have shown dominance in seasonal rainwater samples, and all the metals have shown variation in concentration in different seasons. Variation in chemical characteristic of seasonal rainwater samples identified through piper diagram indicates dominance of Ca2+-Mg2+-HCO3- and mixed Ca2+-Mg2+-Cl- facies during NEM, SWM, and IM periods. Statistical analysis of the results through two-way ANOVA and Pearson's correlation also indicates significant variation in physico-chemical characteristics. This suggests a variation in contributing sources during the monsoon seasons. Factor analysis confirmed the source variation by explaining the total variance of 79.80%, 90.72%, and 90.52% with three factor components in NEM, SWM, and IM rainwater samples with different loading of parameters. Enrichment factor analysis revealed a combined contribution of marine and crustal sources except K+ which was solely from crustal sources. Sample analysis of backward air mass trajectory supports all these findings by explaining seasonal variation in the source of pollutants reaching the study area. Overall, the results show that the chemical composition of seasonal rainwater samples in LRB was significantly influenced by natural as well as anthropogenic processes. These include (long-range and local) industrial activities, fossil fuel combustion, forest burning, transportation activities including road transport and shipping activities, and land-derived soil dust along with chemical constituents carried by seasonal wind.
Principal component analysis (PCA) and correlation have been used to study the variability of particle mass and particle number concentrations (PNC) in a tropical semi-urban environment. PNC and mass concentration (diameter in the range of 0.25->32.0 μm) have been measured from 1 February to 26 February 2013 using an in situ Grimm aerosol sampler. We found that the 24-h average total suspended particulates (TSP), particulate matter ≤10 μm (PM10), particulate matter ≤2.5 μm (PM2.5) and particulate matter ≤1 μm (PM1) were 14.37 ± 4.43, 14.11 ± 4.39, 12.53 ± 4.13 and 10.53 ± 3.98 μg m(-3), respectively. PNC in the accumulation mode (<500 nm) was the most abundant (at about 99 %). Five principal components (PCs) resulted from the PCA analysis where PC1 (43.8 % variance) predominates with PNC in the fine and sub-microme tre range. PC2, PC3, PC4 and PC5 explain 16.5, 12.4, 6.0 and 5.6 % of the variance to address the coarse, coarser, accumulation and giant fraction of PNC, respectively. Our particle distribution results show good agreement with the moderate resolution imaging spectroradiometer (MODIS) distribution.
In this study, we proposed integrated tools to evaluate the wind power potential, economic viability, and prioritize 15 proposed sites for the installation of wind farms. Initially, we used modified Weibull distribution model coupled with power law to assess the wind power potential. Secondly, we employed value cost method to estimate per unit cost ($/kWh) of proposed sites. Lastly, we used Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (F-TOPSIS) to rank the best alternatives. The results indicate that Pakistan has enormous wind power potential that cost varies from 0.06 $/kWh to 0.58 $/kWh; thus, sites S12, S13, S14, and S15 are considered as the most economic viable locations for the installation of wind power project, while remaining sites are considered to be less important, due to other complexities. The further analysis using Fuzzy-TOPSIS method reveals that site S13 is the most optimal location followed by S12, S14, and S14 for the development of wind power project. We proposed that government should formulate wind power policy for the implementation of wind power projects in order to meet energy demand of the country.
Energy security and environmental measurements are incomplete without renewable energy; therefore, there is a dire need to explore new energy sources. Hence, this study aimed to measure the wind power potential to generate renewable hydrogen (H2), including its production and supply cost. This study used first-order engineering model and net present value to measure the levelized cost of wind-generated renewable hydrogen by using the data source of the Pakistan Meteorological Department and State Bank of Pakistan. Results showed that the use of surplus wind and renewable hydrogen energy for green economic production is suggested as an innovative project option for large-scale hydrogen use. The key annual running expenses for hydrogen are electricity and storage costs, which have a significant impact on the costs of renewable hydrogen. The results also indicated that the project can potentially cut carbon dioxide (CO2) pollution by 139 million metric tons and raise revenue for wind power plants by US$2998.52 million. The renewable electrolyzer plants avoided CO2 at a rate of US$24.9-36.9/ton under baseload service, relative to US$44.3/ton for the benchmark. However, in the more practical mid-load situation, these plants have significant benefits. Further, the wind-generated renewable hydrogen delivers 6-11% larger annual rate of return than the standard CO2 catch plant due to their capacity to remain running and supply hydrogen to the consumer through periods of plentiful wind and heat. Also, the measured levelized output cost of hydrogen (LCOH) was US$6.22/kgH2, and for the PEC system, it was US$8.43/kgH2. Finally, it is a mutually agreed consensus among environmental scientists that the integration of renewable energy is the way forward to increase energy security and environmental performance by ensuring uninterrupted clean and green energy. This application has the potential to address Pakistan's urgent issues of large-scale surplus wind- and solar-generated energy, as well as rising energy demand.