Xiaoting Liu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Xiaoting Liu has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Lei Yu
Shandong Jiaotong Univ
1 shared publication - Qi Zhao
Beijing Key Laboratory of Urban Intelligent Traffic Control Technology, North China University of Technology, Beijing 100144, China
1 shared publication - Sicong Zhu
Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, Beijing Jiaotong University, Haidian District, Beijing 100044, China
1 shared publication - Wenjie Peng
Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, Beijing Jiaotong University, Haidian District, Beijing 100044, China
1 shared publication
Latest Publications
- 23 June 2020
- Published by Springer Nature in Environmental Monitoring and Assessment
- Vol. 192 (7) , 1-15
An experimental application of laser-scattering sensor to estimate the traffic-induced PM2.5 in Beijing
Traffic-induced air pollutant emissions are currently rising rapidly. However, measurement of the roadside environment and calculation of the emission factors for traffic-induced PM2.5 are restricted to certain locations and periods due to the limitations of conventional air monitoring techniques. This paper introduces a portable sensor package with a laser light-scattering PM2.5 sensor and an electrochemical CO sensor to measure roadside PM2.5 and CO concentrations. The low-cost sensor package underwent local calibration using reference instruments at the Chinese Research Academy of Environmental Sciences (CRAES). The results showed a high level of correlation (r in the range of 0.94–0.95 and 0.81–0.83 for PM2.5 and CO, respectively) between measurements using the sensor packages and those measured by the reference equipment. The study found that the low-cost sensor packages were able to deliver reliable measurements of PM2.5 and CO concentrations. Four low-cost sensor packages were deployed along a short section of an expressway to measure roadside PM2.5 and CO concentrations. The directly measured concentrations were firstly calibrated with the temperature and humidity. The corrected PM2.5 concentrations from each side of the road were different, while the corrected CO concentrations were similar on both sides of the road. Therefore, only the PM2.5 measurements were applied in this study’s box model. The assumption of perfect mixing in order for the box model to be applied was shown by the results to be valid to some extent. The PM2.5 emission factors for opposite sides of the road should be calculated separately based on the direction of traffic flow. The PM2.5 emission factors calculated in this study were variable, being impacted by traffic conditions and meteorological conditions. The paper presents a method for obtaining PM2.5 emission factors based on a box model. This method is a promising way of monitoring air pollution in the roadside environment.
- 23 June 2020
- Published by Springer Nature in Environmental Monitoring and Assessment
- Vol. 192 (7) , 1-15
An experimental application of laser-scattering sensor to estimate the traffic-induced PM2.5 in Beijing
Traffic-induced air pollutant emissions are currently rising rapidly. However, measurement of the roadside environment and calculation of the emission factors for traffic-induced PM2.5 are restricted to certain locations and periods due to the limitations of conventional air monitoring techniques. This paper introduces a portable sensor package with a laser light-scattering PM2.5 sensor and an electrochemical CO sensor to measure roadside PM2.5 and CO concentrations. The low-cost sensor package underwent local calibration using reference instruments at the Chinese Research Academy of Environmental Sciences (CRAES). The results showed a high level of correlation (r in the range of 0.94–0.95 and 0.81–0.83 for PM2.5 and CO, respectively) between measurements using the sensor packages and those measured by the reference equipment. The study found that the low-cost sensor packages were able to deliver reliable measurements of PM2.5 and CO concentrations. Four low-cost sensor packages were deployed along a short section of an expressway to measure roadside PM2.5 and CO concentrations. The directly measured concentrations were firstly calibrated with the temperature and humidity. The corrected PM2.5 concentrations from each side of the road were different, while the corrected CO concentrations were similar on both sides of the road. Therefore, only the PM2.5 measurements were applied in this study’s box model. The assumption of perfect mixing in order for the box model to be applied was shown by the results to be valid to some extent. The PM2.5 emission factors for opposite sides of the road should be calculated separately based on the direction of traffic flow. The PM2.5 emission factors calculated in this study were variable, being impacted by traffic conditions and meteorological conditions. The paper presents a method for obtaining PM2.5 emission factors based on a box model. This method is a promising way of monitoring air pollution in the roadside environment.