Study on the Total Amount Control of Atmospheric Pollutant Based on GIS

To provide effective environmental management for total amount control of atmospheric pollutants. Methods An atmospheric diffusion model of sulfur dioxide on the surface of the earth was established and tested in Shantou of Guangdong Province on the basis of an overall assessment of regional natural environment, social economic state of development, pollution sources and atmospheric environmental quality. Compared with actual monitoring results in a studied region, simulation values fell within the range of two times of error and were evenly distributed in the two sides of the monitored values. Predicted with the largest emission model method, the largest emission of sulfur dioxide would be 54 279.792 tons per year in 2010. Conclusion The mathematical model established and revised on the basis of GIS is more rational and suitable for the regional characteristics of total amount control of air pollutants.

Using Longwave Infrared Hyperspectral Imaging for a Quantitative Atmospheric Tracer Monitoring in Outdoor Environments

Quantitative real-time retrieval of concentration-lengths (CL) through gaseous plumes is an important tool for environmental monitoring, enabling remote monitoring of emissions from industrial facilities and risk assessment in scenarios of toxic gas releases. The adoption of LWIR (Long Wave InfraRed) hyperspectral imaging as a leading technique for remote gas plume detection paved the way for an introduction of a precise CL estimation and two-dimensional (2D) mapping. A novel methodology for evaluating and characterizing the performance of a retrieval algorithm is presented. The algorithm utilizes state-of-the-art retrieved hyperspectral 2D mapping and is applied on a series of localized atmospheric tracer gas (SF6) releases in monitored environmental conditions. The retrieved CL distributions are compared to a numeric atmospheric T&D (Transport and Diffusion) model. Satisfactory agreement between retrieved and simulated CL prediction is manifested, and the uncertainty involved is quantified. Possible sources for the remained discrepancies between retrieved and simulated CL values are characterized, and methods to minimize them are discussed.