Water scarcity is a global concern, as the demand for water is increasing tremendously and poor management of water resources will accelerates dramatically the depletion of available water. The precise prediction of evapotranspiration (ET), that consumes almost 100% of the supplied irrigation water, is one of the goals that should be adopted in order to avoid more squandering of water especially in arid and semiarid regions. The capabilities of feedforward backpropagation neural networks (FFBP) in predicting reference evapotranspiration (ET0) are evaluated in this paper in comparison with the empirical FAO Penman-Monteith (P-M) equation, later a model of FFBP+Genetic Algorithm (GA) is implemented for the same evaluation purpose. The study location is the main station in Iraq, namely Baghdad Station. Records of weather variables from the related meteorological station, including monthly mean records of maximum air temperature (Tmax), minimum air temperature (Tmin), sunshine hours (Rn), relative humidity (Rh) and wind speed (U2), from the related meteorological station are used in the prediction of ET0 values. The performance of both simulation models were evaluated using statistical coefficients such as the root of mean squared error (RMSE), mean absolute error (MAE) and coefficient of determination (R2). The results of both models are promising, however the hybrid model shows higher efficiency in predicting ET0 and could be recommended for modeling of ET0 in arid and semiarid regions.
The statistical characteristics of wind direction that was recorded at maximum wind speed in Peninsular Malaysia for two monsoons from 1999 to 2008 for seven stations were analyzed in this study. Modeled by von Mises distribution, the change in parameters values namely mean direction and concentration parameter was measured. Statistical summary, graphical representations, Watson-William Test and linear-circular correlation are used in the analysis. It is found that there is a significant change in the mean direction of wind over the period of ten years for most stations in Peninsular Malaysia. However, there is a weak relationship between wind direction and wind speed. This study suggested the presence of prominent direction of wind that blows in Peninsular Malaysia by monsoon. This finding may provide useful information on giving a better understanding of the behavior of the wind in Peninsular Malaysia and the potential use of wind as an alternative source of energy.
Recently, there is strong interest on the subject of outlier problem in circular data. In this paper, we focus on detecting outliers in a circular regression model proposed by Down and Mardia. The basic properties of the model are available including the exact form of covariance matrix of the parameters. Hence, we intend to identify outliers in the model by looking at the effect of the outliers on the covariance matrix. The method resembles closely the COVRATIO statistic for the case of linear regression problem. The corresponding critical values and the performance of the outlier detection procedure are studied via simulations. For illustration, we apply the procedure on the wind data set.
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.
Gunshot residues, produced after shooting activity, have acquired their importance in analysis due to the notoriety of firearms-related crimes. In this study, solid-phase microextraction was performed to extract the headspace composition of spent cartridges using 85-μm polyacrylate fiber at 66°C for 21 min. Organic compounds, that is, naphthalene, 2,6-dinitrotoluene, 2,4-dinitrotoluene, diphenylamine, and dibutyl phthalate were detected and analyzed by gas chromatography-flame ionization detection technique. Evaluation of chromatograms for diphenylamine, dibutyl phthalate, and naphthalene indicates the period after a gunshot was discharged, whether it was 1 days, 2-4 days, <5 days, 10 days, 20 days, or more than 30 days ago. This study revealed the potential effects of environmental factors such as occasional wind blow and direct sunlight on the estimation of time after spent cartridges were discharged. In conclusion, we proposed reliable alternative in analyzing the headspace composition of spent cartridges in a simulated crime scene.
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.
A cylindrical data set consists of circular and linear variables. We focus on developing an outlier detection procedure
for cylindrical regression model proposed by Johnson and Wehrly (1978) based on the k-nearest neighbour approach.
The procedure is applied based on the residuals where the distance between two residuals is measured by the Euclidean
distance. This procedure can be used to detect single or multiple outliers. Cut-off points of the test statistic are generated
and its performance is then evaluated via simulation. For illustration, we apply the test on the wind data set obtained
from the Malaysian Meteorological Department.
A three-dimensional Regional Ocean Modelling System is used to study the tidal characteristics and their dynamics in the Sunda Shelf of the southern South China Sea. In this model, the outer domain is set with a 25 km resolution and the inner one, with a 9 km resolution. Calculations are performed on the inner domain. The model is forced at the sea surface by climatological monthly mean wind stress, freshwater (evaporation minus precipitation), and heat fluxes. Momentum and tracers (such as temperature and salinity) are prescribed in addition to the tidal heights and currents extracted from the Oregon State University TOPEX/Poseidon Global Inverse Solution (TPXO7.2) at the open boundaries. The results are validated against observed tidal amplitudes and phases at 19 locations. Results show that the mean average power energy spectrum (in unit m2/s/cph) for diurnal tides at the southern end of the East Coast of Peninsular Malaysia is approximately 43% greater than that in the East Malaysia region located in northern Borneo. In contrast, for the region of northern Borneo the semidiurnal power energy spectrum is approximately 25% greater than that in the East Coast of Peninsular Malaysia. This implies that diurnal tides are dominant along the East Coast of Peninsular Malaysia while both diurnal and semidiurnal tides dominate almost equally in coastal East Malaysia. Furthermore, the diurnal tidal energy flux is found to be 60% greater than that of the semidiurnal tides in the southern South China Sea. Based on these model analyses, the significant tidal mixing frontal areas are located primarily off Sarawak coast as indicated by high chlorophyll-a concentrations in the area.
A three-dimensional Regional Ocean Modeling System is used to study the seasonal water circulations and transports of the Southern South China Sea. The simulated seasonal water circulations and estimated transports show consistency with observations, e.g., satellite altimeter data set and re-analysis data of the Simple Ocean Data Assimilation. It is found that the seasonal water circulations are mainly driven by the monsoonal wind stress and influenced by the water outflow/inflow and associated currents of the entire South China Sea. The intrusion of the strong current along the East Coast of Peninsular Malaysia and the eddies at different depths in all seasons are due to the conservation of the potential vorticity as the depth increases. Results show that the water circulation patterns in the northern part of the East Coast of Peninsular Malaysia are generally dominated by the geostrophic currents while those in the southern areas are due solely to the wind stress because of negligible Coriolis force there. This study clearly shows that individual surface freshwater flux (evaporation minus precipitation) controls the sea salinity balance in the Southern South China Sea thermohaline circulations. Analysis of climatological data from a high resolution Regional Ocean Modeling System reveals that the complex bathymetry is important not only for water exchange through the Southern South China Sea but also in regulating various transports across the main passages in the Southern South China Sea, namely the Sunda Shelf and the Strait of Malacca. Apart from the above, in comparision with the dynamics of the Sunda Shelf, the Strait of Malacca reflects an equally significant role in the annual transports into the Andaman Sea.
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.
Gymnodinium catenatum is a cosmopolitan, bloom-forming dinoflagellate known to produce a suite of potent paralytic shellfish poisoning (PSP) toxins. Here, we revisit two major blooms of G. catenatum along the Fujianese Coast, China, in 2017 and 2018. The impact area of the 2017 bloom was larger than that of the 2018 event. Field sampling and remote satellite sensing revealed that alongshore transport driven by the southwest wind, as well as physical accumulation driven by the northeast wind, played important roles in the development and distribution of the two bloom events. The relationship between wind-induced hydrodynamic conditions and the unprecedented HAB events established in this study adds greatly to our understanding of algal bloom dynamics along the Fujianese coast. These results improve our ability to detect, track, and forecast G. catenatum blooms, thereby potentially minimizing the negative impacts of future HAB events.
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.
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.
Oil palm (Elaeis guineensis) agriculture is rapidly expanding and requires large areas of land in the tropics to meet the global demand for palm oil products. Land cover conversion of peat swamp forest to oil palm (large- and small-scale oil palm production) is likely to have negative impacts on microhabitat conditions. This study assessed the impact of peat swamp forest conversion to oil palm plantation on microclimate conditions and soil characteristics. The measurement of microclimate (air temperature, wind speed, light intensity and relative humidity) and soil characteristics (soil surface temperature, soil pH, soil moisture, and ground cover vegetation temperature) were compared at a peat swamp forest, smallholdings and a large-scale plantation. Results showed that the peat swamp forest was 1.5-2.3 °C cooler with significantly greater relative humidity, lower light intensities and wind speed compared to the smallholdings and large-scale plantations. Soil characteristics were also significantly different between the peat swamp forest and both types of oil palm plantations with lower soil pH, soil and ground cover vegetation surface temperatures and greater soil moisture in the peat swamp forest. These results suggest that peat swamp forests have greater ecosystem benefits compared to oil palm plantations with smallholdings agricultural approach as a promising management practice to improve microhabitat conditions. Our findings also justify the conservation of remaining peat swamp forest as it provides a refuge from harsh microclimatic conditions that characterize large plantations and smallholdings.
Coral spawning times have been linked to multiple environmental factors; however, to what extent these factors act as generalized cues across multiple species and large spatial scales is unknown. We used a unique dataset of coral spawning from 34 reefs in the Indian and Pacific Oceans to test if month of spawning and peak spawning month in assemblages of Acropora spp. can be predicted by sea surface temperature (SST), photosynthetically available radiation, wind speed, current speed, rainfall or sunset time. Contrary to the classic view that high mean SST initiates coral spawning, we found rapid increases in SST to be the best predictor in both cases (month of spawning: R(2) = 0.73, peak: R(2) = 0.62). Our findings suggest that a rapid increase in SST provides the dominant proximate cue for coral mass spawning over large geographical scales. We hypothesize that coral spawning is ultimately timed to ensure optimal fertilization success.
Wind turbines are massive electrical structures. They produce large returns when illuminated by radar waves. These
scatterings have a great impact on the operation of surveillance, air traffic control and weather radars. This paper presents
two geometric modelling methods for reshaping wind turbine towers so that the Radar Cross Section (RCS) of wind turbines
is reduced. In the proposed reshaping methods, bump structures are created on the surface of the conventional cylinder
wind turbine tower. When a reshaped tower is illuminated by radar waves, the bump structures scatter incident radar
waves into insignificant directions so that the strength of back-scattering is declined and the RCS of the wind turbine is
decreased. The test results confirmed that the proposed methodssignificantly reduce bi-static RCS values of wind turbines.
The proposed reshaping methods are practical, flexible and effective in alleviating the scatterings of wind turbines.
Fluxes and composition dynamics of atmospheric nitrogen deposition play key roles in better balancing economic development and ecological environment. However, there are some knowledge gaps and difficulties in urban ecosystems, especially for small and medium-sized cities. In this study, both flux and composition (ratio of NH4+-N to NO3--N, RN) of wet-deposited dissolved inorganic nitrogen (DIN, sum of NO3--N and NH4+-N) were estimated and sources were identified at a long-term urban observation station in Tongling, a typical medium-sized city in eastern China during 2010-2016, respectively. Results showed that wet-deposited DIN fluxes were 33.20 and 28.15 kgN ha-1 yr-1 in Tongling city during 2010-2011 and 2015-2016, respectively. Compared to these two periods, both DIN and NO3--N fluxes decreased by 15.2% and 31.8% for a series of NOx abatement measures applied effectively, respectively. At the same time, the NH4+-N flux remained stable and ranged from 19.53 to 20.62 kgN ha-1 yr-1, and the RN increased from 1.7 to 2.2. Seasonally, winds from the southwest and west-southwest with higher frequencies and speeds in spring and summer brought more NH4+-N and DIN wet deposition from an ammonia plant, which could threaten the safety of regional hydrosphere ecosystems. On the whole, the wet-deposited NH4+-N was threatening regional ecosystems of both the hydrosphere and forest. The wet-deposited DIN including NH4+-N in Tongling city stemmed mainly from a combined source of coal combustion and dust from Cu extraction and smelting, ammonia production, and roads. Therefore, production lines should be updated for Cu extraction and smelting industries, thermal power generations and the ammonia plant, old vehicles should be eliminated, and the use of new energy vehicles should be promoted for regional sustainable development and human health in the medium-sized city.
Odors due to the emission of hydrogen sulfide (H2S) have been a concern in the sewage treatment plants over the last decades. H2S fate and emissions from extended aeration activated sludge (EAAS) system in Muharram Aisha-sewage treatment plant (MA-STP) were studied using TOXCHEM model. Sensitivity analysis at different aeration flowrate, H2S loading rate, wastewater pH, wastewater temperature and wind speed were studied. The predicted data were validated against actual results, where all the data were validated within the limits, and the statistical evaluation of normalized mean square error (NMSE), geometric variance (VG), and correlation coefficient (R) were close to the ideal fit. The results showed that the major processes occurring in the system were degradation and emission. During summer (27 °C) and winter (12 °C), about 25 and 23%, 1 and 2%, 2 and 2%, and 72 and 73% were fated as emitted to air, discharged with effluent, sorbed to sludge, and biodegraded, respectively. At summer and winter, the total emitted concentrations of H2S were 6.403 and 5.614 ppm, respectively. The sensitivity results indicated that aeration flowrate, H2S loading rate and wastewater pH highly influenced the emission and degradation of H2S processes compared to wastewater temperature and wind speed. To conclude, TOXCHEM model successfully predicted the H2S fate and emissions in EAAS system.
Natural ventilation is defined as the number of air exchanges per hour per unit floor area necessary
to reduce high indoor air temperature and humidity. In addition, it maintains the concentration of carbon dioxide. Natural ventilation is preferred in mechanical system as the ventilation opening is built into the greenhouse, with lower construction cost and no energy and maintenance inputs are required. A mathematical model to quantify natural ventilation rates was developed and verified in large-scale greenhouse structures. For this purpose, four Naturally Ventilated Tropical Greenhouse Structures were designed and constructed at the Malaysian Agricultural Research and Development Institute (MARDI). These were single, double, triple, and quadruple span structures with floor areas of 500 m2, 1000 m2, 1500 m2 and 2000 m2, respectively. This paper presents the validation of a mathematical model which was developed to quantify natural ventilation rates which are very crucial to reduce high in-house temperature built up in the tropics. Regression equations of natural ventilation against wind speed were found to be Φw = 0.0632V, Φw= 0.0395V, Φw= 0.0316Vand Φw=0.0276V for the single, double, triple and quadruple spans, respectively. Meanwhile, coefficients of determination showed strong relationships between ventilation rate and wind speed, with R2 = 0.9999 for all structures. Larger floor area was found to have higher in-house temperature than smaller ones. Ventilation rate inside the single-span structure was found to be higher compared to the multi-span structures, which increased linearly with the increasing wind speed at the eaves of structure.
Solar energy is a major type of renewable energy, and its estimation is important for decision-makers. This study introduces a new prediction model for solar radiation based on support vector regression (SVR) and the improved particle swarm optimization (IPSO) algorithm. The new version of algorithm attempts to enhance the global search ability for the PSO. In practice, the SVR method has a few parameters that should be determined through a trial-and-error procedure while developing the prediction model. This procedure usually leads to non-optimal choices for these parameters and, hence, poor prediction accuracy. Therefore, there is a need to integrate the SVR model with an optimization algorithm to achieve optimal choices for these parameters. Thus, the IPSO algorithm, as an optimizer is integrated with SVR to obtain optimal values for the SVR parameters. To examine the proposed model, two solar radiation stations, Adana, Antakya and Konya, in Turkey, are considered for this study. In addition, different models have been tested for this prediction, namely, the M5 tree model (M5T), genetic programming (GP), SVR integrated with four different optimization algorithms SVR-PSO, SVR-IPSO, Genetic Algorithm (SVR-GA), FireFly Algorithm (SVR-FFA) and the multivariate adaptive regression (MARS) model. The sensitivity analysis is performed to achieve the highest accuracy level of the prediction by choosing different input parameters. Several performance measuring indices have been considered to examine the efficiency of all the prediction methods. The results show that SVR-IPSO outperformed M5T and MARS.