No abstract

The Mataloko geothermal system in Ngada-Flores Regency, East Nusa Tenggara, is located in three active volcanic mountains (Inerie, Ebulobo, and Inielika). The contribution of high levels of CH4 and exhaust emissions of SO2 due to its utilization as a geothermal power plant (GPP) impacts the environment. This study aims to analyze and spatially model the distribution and impact of SO2 and CH4 gas levels in the Mataloko GPP area. The quantitative descriptive method was used through direct measurement at gas wells and laboratory testing. The results showed a tendency to increase SO2 levels in the MT-4 gas-well with levels of 8.00 ppm exceeding the quality standard, which could disturb the environment in the Mataloko-GPP area. Impact of high SO2 will experience dry sediment because it is not combustible in the air, then it will drop slowly to be absorbed by soil and plants. Droplets of acid gas blown by the wind and left on trees and buildings are even inhaled into the breath. In addition, the advantages of model with surfer 12 software can help identify the distribution of SO2 and SO4 emissions in the generating area.

Road safety auditors are required to identify safety deficiencies that may lead to potential hazard on a road project. The available audit tools may only provide the prompt lists that should be followed. Auditors often become a design checker rather than an auditor. They may overlook the critical safety issues. The common oversights during road design have been identified. The experience in auditing a total of 24 road projects from 1998 to 2008 was referred and summarised. As a result, lack of or poor provision for vulnerable road users is the most common oversight done during the road designs.

The road safety statistics have shown a remarkable increase in number of injuries during the festive seasons in Malaysia. To anticipate the burden of the injuries, the police has carried out an advanced enforcement operations called “Ops Sikap” since 2001. Evaluations on the effectiveness of the operations are, however, found inconclusive. This study employed ARIMA and intervention model to further evaluate the effect of the Ops Sikap. The effect of an intervention on the number of accidents is measured using the pulse function. ARIMA model is used to forecast the series without such intervention and become the basis for the ARIMA(p,d,q) process of the intervention model. Forecasted accidents from the intervention model are then compared with the ARIMA one to attain how far the effect. The results show that the operations have reduced the number of accidents in many years. Out of twenty five Ops Sikap carried out, fourteen times (56%) have successfully brought the accidents down. The operations have provided the reduction of the monthly accidents up to 0.7% as compared with the accidents if there were no such operations taken.