Road environments significantly affect in cabin concentration of particulate matter (PM). This study conducted measurements of in-vehicle and on-road concentrations of PM10, PM2.5, PM1, and particle number (PN) in size of 0.02–1 µm, under six ventilation settings in different urban road environments (tunnels, surface roads and elevated roads). Linear regression was then used to analyze the contributions of multiple predictor variables (including on-road concentrations, temperature, relative humidity, time of day, and ventilation settings) to measured variations. On-road measurements of PM2.5, PM1, and PN concentrations from the open surface roads were 5.5%, 3.7%, and 16% lower, respectively, than those measured in tunnels, but 7.6%, 7.1% and 24% higher, respectively, than those on elevated roads. The highest on-road PM10 concentration was observed on surface roads. The time series pattern of in-vehicle particle concentrations closely tracked the on-road concentrations outside of the car and exhibited a smoother profile. Irrespective of road environment, the average I/O ratio of particles was found to be the lowest when air conditioning was on with internal recirculation, the highest purification efficiency via ventilation was obtained by switching on external air recirculation and air conditioning. Statistical models showed that on-road concentration, temperature, and ventilation setting are common factors of significance that explained 58%-80%, 64%-97%, and 87%-98% of the variations in in-vehicle PM concentrations on surface roads, on elevated roads, and in tunnels, respectively.
Implications: Inside vehicles, both driver and passengers will be exposed to elevated particle concentrations. However, for in-vehicle particles, there has been no comprehensive comparative study of the three-dimensional traffic environment including tunnels surface roads and elevated roads. This study focuses on the analysis of the trends and main influencing factors of particle concentrations in different road environments. The results can provide suggestions for the driver's behavior, and provide data support for the environmental protection department to develop pollutant concentration limits within the vehicle. 相似文献
Oil transfer stations of PetroChina mostly scatter in Gobi, mountain areas or other sparsely populated areas, inconvenient transportation and absent professional engineers often delay the best time to repair the machines. Time-or interval-based maintenance (TBM) accounts for almost 100%, while, On-condition maintenance and other proactive maintenance are seldom adopted. TBM not only can't prevent happens of equipment fault but also cause the waste of the maintenance resource. In order to allocate maintenance resources reasonably, ascertain the minimum preventive maintenance requirement, ensure the reliability, availability and safety, this paper carries out a research on Risk and Condition Based Maintenance (RCBM) task optimization technology. Utilizing the internet of things (IOT), real-time database, signal-processing, Gray Neural Network, probability statistical analysis and service oriented architecture (SOA) technology, a Risk and Condition Based Indicator Decision-making System (RCBIDS) is built. RCBIDS integrates RCM, condition monitoring system (CMS), key performance management module, file management module, fault and defect management module, maintenance management module together, which aims to realize remote condition monitoring, maintenance technical support services (TSS), quantitative maintenance decision-making, and to ensure the Reliability, Availability, Maintainability and Safety (RAMS). The Predictive Maintenance Indicator model, reliability prediction model and Key Performance Indicator (KPI) model, which are embedded in the RCBIDS, are constructed separately. An engineering case shows that the risk and condition based maintenance task optimization technology can be used to optimize maintenance content and maintenance period, to minimize maintenance deficiencies and maintenance surplus, and to prolong the lifespan of equipment. 相似文献