Road Traffic Air Quality Monitoring: Building a Data - Driven Pollution Control Network

Air quality monitoring stations for road traffic primarily aim to conduct real - time monitoring of air quality in traffic - intensive areas. They integrate data from environmental monitoring networks, meteorological parameters, and vehicle - related information. By doing so, these stations analyze the impact of vehicle emissions on the atmospheric environment, providing essential data support for pollution control initiatives.

With the acceleration of urbanization and the increasing number of motor vehicles, traffic - related pollution has emerged as a prominent issue. Air pollution on urban roads accounts for a significant proportion, posing threats to public health and undermining the urban ecosystem. To implement the Air Pollution Prevention and Control Law, local authorities have installed intelligent monitoring terminals at major traffic arteries. These terminals monitor pollution around the clock, enabling full - process control over air pollution.

Currently, in the context of urban air pollution control, the prevention and control of mobile - source pollution are of crucial importance. In addition to fixed - site monitoring stations, road dust mobile monitoring technology offers a flexible regulatory solution. The combination of multiple monitoring methods can effectively control pollutant concentrations and provide a basis for traffic planning.

Key cities in China have established a new traffic - environment monitoring system. This system routinely monitors six core parameters, and can be extended with additional monitoring modules. Monitoring devices use either suction - type or diffusion - type sampling methods, analyzing samples based on a variety of detection principles. Relying on the Internet of Things (IoT) and big data technologies, monitoring data can be presented in real - time across multiple terminals, facilitating environmental decision - making.

The construction and application of road traffic Air quality monitoring stations mainly focus on six major air pollutants, namely “four gases and two dusts” (sulfur dioxide - SO₂, nitrogen dioxide - NO₂, carbon monoxide - CO, ozone - O₃, fine particulate matter - PM2.5, and inhalable particulate matter - PM10). Based on this fundamental monitoring framework, the system is highly flexible. It can be further expanded to include monitoring modules for other pollutants such as carbon dioxide (CO₂) and volatile organic compounds (VOCs) according to actual needs, enabling more comprehensive air quality monitoring.

Monitoring instruments use either pump - suction or diffusion sampling methods to efficiently collect ambient air samples. During sample analysis, high - precision sensor modules analyze samples in depth based on scientific monitoring principles such as electrochemistry, light scattering, photoionization detection (PID), and non - dispersive infrared spectroscopy (NDIR). This allows for accurate determination of the concentration values of various pollutants.

Data is transmitted via a stable and reliable network to an analysis platform that integrates big data and IoT technologies. On this platform, data undergoes strict integration, analysis, and comparison. Ultimately, the thoroughly processed air quality data can be presented intuitively and in real - time on multiple terminal devices, including mobile phones, web platforms, and large - screen displays. This provides convenient data - querying and usage experiences for different user groups, including environmental managers and the general public, and contributes to the accurate monitoring and effective control of air quality.