With a growing awareness of environmental protection, the dust pollution caused by automobile foundry work has become a serious and urgent problem. This study aimed to explore contamination levels and health effects of automobile foundry dust. A total of 276 dust samples from six types of work in an automobile foundry factory were collected and analysed using the filter membrane method. Probabilistic risk assessment model was developed for evaluating the health risk of foundry dust on workers. The health risk and its influencing factors among workers were then assessed by applying the Monte Carlo method to identify the most significant parameters. Health damage assessment was conducted to translate health risk into disability-adjusted life year (DALY). The results revealed that the mean concentration of dust on six types of work ranged from 1.67 to 5.40 mg/m3. The highest health risks to be come from melting, cast shakeout and finishing, followed by pouring, sand preparation, moulding and core-making. The probability of the risk exceeding 10−6 was approximately 85%, 90%, 90%, 75%, 70% and 45%, respectively. The sensitivity analysis indicated that average time, exposure duration, inhalation rate and dust concentration (C) made great contribution to dust health risk. Workers exposed to cast shakeout and finishing had the largest DALY of 48.64a. These results can further help managers to fully understand the dust risks on various types of work in the automobile foundry factories and provide scientific basis for the management and decision-making related to health damage assessment.
Signalized intersections have been identified as vehicle emission hotspots, where drivers decelerate, idle, and accelerate their vehicles in response to signal changes. Advanced traffic signal status warning systems (ATSSWSs) can be applied to reduce traffic emissions at intersections by mitigating unnecessary braking and acceleration. In this study, two types of ATSSWSs, variable message sign (VMS) based and vehicle-to-infrastructure (V2I) based, were designed, and their environmental effectiveness was evaluated through driving simulator-based experiments. Three scenarios were designed and tested: (1) baseline without an ATSSWS, (2) with the VMS-based ATSSWS, and (3) with the V2I-based ATSSWS. The Motor Vehicle Emission Simulator model was used to evaluate and compare the environmental effectiveness of these two types of ATSSWSs. The results indicate that the proposed ATSSWSs can reduce traffic emissions at signalized intersections. In particular, the V2I-based ATSSWS can substantially reduce CO2, NOx, CO, and HC emissions. The results will help transportation practitioners with implementing advanced driver information systems and decision making on emission reduction policies.
Implications: Signalized intersection has been identified as one of hottest spots for vehicle emissions where signal control causes vehicles to frequently decelerate, idle, and accelerate. Advanced Traffic Signal Status Warning Systems (ATSSWS) can be applied to reduce traffic emission at intersections by decreasing vehicles’ unnecessary brakes and accelerations. The results of this study will assist transportation practitioners in implementing advanced driver information systems and making decisions on emission reduction policies. 相似文献