With the increasingly prominent problem of atmospheric photochemical pollution, the harm of photochemical pollutants such as ozone and volatile organic compounds (VOCs) to the ecological environment and human health has received increasing attention. As a core infrastructure for accurately capturing the characteristics of photochemical pollution, tracing pollution sources, and supporting pollution control decisions, the construction quality of the photochemical component monitoring network directly determines the scientificity and effectiveness of photochemical pollution control.
1、 Core functional system
The photochemical component monitoring network is not a simple combination of single monitoring devices, but a comprehensive monitoring system with the full chain capabilities of "real-time monitoring, data quality control, source analysis, early warning and forecasting, and decision support". Its core functions revolve around the core requirements of "identification traceability control" of photochemical pollution, which can be divided into the following five dimensions.
（1） Real time monitoring of all components: precise capture of pollution characteristics
Real time monitoring of all components and high resolution is the fundamental core function of the monitoring network, with the core goal of mastering the concentration levels and spatiotemporal variation patterns of key components in photochemical pollution within the monitoring area. The monitoring objects cover the core participants of photochemical pollution, including precursors, reaction intermediates, and products. To achieve full component monitoring, the monitoring network needs to integrate multiple high-precision monitoring technologies and select suitable monitoring equipment based on the physical and chemical properties of different components.
（2） Data Quality Control and Calibration: Ensuring Accurate and Reliable Data
The accuracy of monitoring data is a prerequisite for the effectiveness of monitoring networks, therefore data quality control and calibration functions are the core guarantee functions. This function achieves full lifecycle control of monitoring data by establishing a quality control system for the entire process, from equipment calibration, sample collection, data transmission to abnormal data processing. In terms of equipment calibration, the monitoring network needs to regularly perform zero point calibration, span calibration, and multi-point calibration on the instruments at each monitoring station, using nationally recognized standard substances to ensure that the instrument monitoring accuracy meets relevant standard requirements; For cross site monitoring equipment, comparative tests are also required to ensure the comparability of data between different sites.
In the process of sample collection and transmission, the monitoring network needs to standardize the material selection, sampling flow control, and sample storage methods of the sampling pipeline to avoid adsorption, degradation, or contamination of the samples during the collection process; The data transmission adopts encrypted transmission protocol to ensure that the data is not lost or tampered with during the transmission process. At the same time, the monitoring network is equipped with a specialized data quality control system, which automatically identifies abnormal data (such as numerical mutations caused by instrument failures and abnormal fluctuations caused by environmental interference) by setting reasonable threshold ranges, change rates, and other parameters. The abnormal data is marked, removed, or corrected, and effective data that has been quality controlled is output, providing reliable guarantees for subsequent analysis and application.
（3） Source Analysis of Pollution: Tracing the Key Sources of Pollution
Accurately tracing the source of photochemical pollution is the core prerequisite for achieving precise pollution control, and it is also one of the core functions of the photochemical component monitoring network. This function is based on full component monitoring data, combined with statistical methods, model simulations, and other techniques, to qualitatively and quantitatively analyze the sources of precursor materials for photochemical pollution.
（4） Pollution warning and forecasting: enhancing emergency control capabilities
Photochemical pollution has the characteristics of suddenness and regionalism, and timely warning and forecasting are the key to improving pollution emergency control capabilities. This function is based on real-time monitoring data, historical data, and meteorological data, combined with a photochemical kinetic model, to predict the trend of photochemical pollution concentration changes in the monitoring area in the future. By setting different levels of warning thresholds, when the predicted concentration reaches the warning threshold, the monitoring network can automatically issue warning information to remind relevant departments to take emergency control measures in a timely manner.
（5） Decision support and effectiveness evaluation: helping to improve the quality and efficiency of pollution control
The goal of the monitoring network is to provide scientific support for decision-making on photochemical pollution control and to accurately evaluate the effectiveness of the control, which is a concentrated manifestation of its core value. By integrating monitoring data, source analysis results, and warning and forecasting information, the monitoring network can provide accurate basis for relevant departments to formulate pollution control plans, clarify key areas, industries, and pollutants for control.
Meanwhile, the monitoring network can dynamically evaluate the implementation effect of pollution control measures. By comparing the concentration changes and source contribution ratios of photochemical pollutants before and after the implementation of control measures, the emission reduction effect of the control measures can be quantified, and the effectiveness of the control plan can be judged. If the governance effect does not meet expectations, further analysis of the reasons can be conducted based on monitoring data to optimize control measures. In addition, the long-term monitoring data from the monitoring network can also be used to evaluate the overall effectiveness of regional photochemical pollution control, providing data support for the adjustment and improvement of environmental management policies.
The core function and coverage layout of the photochemical component monitoring network complement each other. The core function determines the construction goals and technical routes of the monitoring network, while the coverage layout determines the implementation effect of the core function. By constructing a full chain core functional system of "whole component monitoring data quality control source analysis warning and forecasting decision support", combined with a three-level coverage layout of "core zone buffer zone background zone", the monitoring network can accurately capture the characteristics of photochemical pollution and provide scientific and effective data support for photochemical pollution control.