Biomass burning is an important global emission source of aerosols and trace gases, and has significant impacts on air quality, climate change and human health. Accurate estimation of trace gas and aerosol emissions from biomass burning is fundamental and important to further research about global climate change, regional air quality assessment and forecasting. Within the last 20 years, satellite-based instrumentation has been used to directly investigate the biomass burning emissions and has greatly achieved development. The research progress on estimating emissions from biomass burning based on satellite observations were introduced from four aspects: 1) two methods of emissions estimation for biomass burning using satellite products of burned areas (BA) and fire radiation power (FRP); 2) the method and products for the key variables of BA, FRP and active fire used for estimating emissions; 3) emissions inventory of biomass burning based on above two methods; 4) further work about emissions estimation for biomass burning in the near future.
The Korea Geostationary Ocean Color Imager (GOCI) onboard COMs-1 (Communication, Ocean & Meteorological Satellite-1) is mainly designed for ocean observation, and it has a good potential for land monitoring. Cross calibration between GOCI and the US Moderate Resolution Imaging Spectrometer (MODIS) can improve the land radiation characteristics of GOCI, which can expand its ability in land observation. In cross calibration, the effects from spectral response of two sensors are considered and the impacts of the differences between GOCI and MODIS viewing angles in calibration are revised by radiative transfer simulation. Meanwhile, satellite data in the same transit time of two sensors are chosen in order to reduce the effects from different sun zenith angles. Cross calibration results show that the simulated top of atmosphere (TOA) radiance from MODIS agrees well with GOCI measured TOA radiance, and the value of R2 is greater than 0.88. Preliminary validation of calibration results shows that the cross calibration method can meet the accuracy requirements of general quantitative remote sensing applications.
Motor fuel composition and physical properties are closely related to the vehicular emissions controlling. Development of monitoring vehicle, integrating sulfur content detection device, vapor pressure testing device and fast simulation equipment for detergency detection, is benefit for random sample survey. Many efficient measures are taken to control influencing factors to ensure that portable devices can provide reliable testing results. The main influencing factors such as vehicle vibration, essential resource supply, environment conditions control and data quality control have been studied. Solution of vibration model is used for guiding the design and selection of vibration damping unit. Sufficient electricity and gas supply provide favorable operation condition for devices. And split-phase circuit, voltage regulator and filter device are set up for decrease electrical signal interference. Temperature and air circulation are strictly controlled to ensure a safe and comfortable environment. Additionally, keeping good repeatability of instruments and a proper analysis method of pre-treatment and pre-assessment are effective to reach credible results.
To measure COx, NOx, THC and other gas components of vehicle high temperature exhaust accurately, based on the principle of cyclone, the high temperature exhaust pretreatment regimen is discussed in detail. An improved cyclone and vehicular high temperature exhaust pretreatment gas circuit are designed, taking particulate filter chamber, cyclones, fluid resistance and membrane dryers as the main device. Particulate filter chamber is used to remove dust, metal spiral is used to drop temperature, cyclone is used to remove water and dust, resistance dispenser is used to remove water and membrane dryer is used to remove water. Without changing the exhaust gas composition and content, the gas clarity is improved. Experimental results show that the relative humidity of pretreatment gas is less than 2.5%, temperature is below 40℃, particles diameter is less than 5 μm and the content is extremely low. The sampling pretreatment system meets requirements of motor vehicle exhaust composition analysis module.
With the increasing number of vehicles, the harm from vehicle exhaust to the environment becomes more and more serious. So the monitoring of the concentration of vehicle exhaust emissions is very important to assess the emission levels. The NO and NO2 quantitative detection system based on nondispersion ultra- violet (NDUV) for vehicle exhaust emissions is built, and the original data of the mixed tail gas is obtained. And then, the identification and quantitative analysis of NO and NO2 gas is carried out with fast independent component analysis (Fast ICA) and artificial neural network (ANN) recognition algorithms. It can be drawn from the results that using the two algorithms, the NO concentration (under 600 ppm) and NO2 concentration (under 200 ppm) can be detected accurately and the maximum relative error is 1.54%, and the minimum is 0.25%.
Nondispersive infrared (NDIR) gas sensor is the key component of vehicle exhaust testing system for CO and CO2, and the concentration of measured gas always is calculated by calibration method. The calibration curve generated by traditional calibration method can not fit very well when the gas concentration is lower than 10% of full scale and can not satisfy the measurement requirement. For this problem, a new calibration method based on weighted least square fit is presented. The method can improve the goodness of fit by giving bigger weight to data point at lower concentration and increasing the number of calibration points. The calibration result shows that the calibration curve generated by this method has relative error lower than 2% in the entire measuring scale. The calibration method presented is important in practical application.
Vehicle emission is the main culprit for the air pollution in the city. Through the camera capture and image recognition method, the information about vehicle volume is obtained. Combined with the information about vehicle emission factors that is published by the Ministry of Environmental Protection, the emission intensity of the streets is calculated. Then based on the model of turbulence and the theory of porous media, the flow field and pollutant concentration distribution in street canyon are obtained by computer numerical simulation. The data obtained can provide a scientific basis for the urban street design and exhaust pollution control measures.
With the development of China’s urbanization and the increase in the number of motor vehicles, motor vehicle exhaust has become the main killer of the clean air in cities. In order to effectively improve the air quality in cities, the motor vehicle emission should be strictly detected and effectively controlled. With the introduction of remote sensing technology, the data of the vehicle exhaust must be stored, managed and analyzed effectively and safely. In order to meet the demands of storing, displaying and processing remote sensing monitoring data, a vehicle exhaust data center platform is established to achieve the storage management of massive data and the function of displaying and querying on the Web.
Dieseloil detergency can drastically influence the performance of diesel engine, which has great effect on vehicle emissions. In order to control the diesel vehicles emission, it is necessary to supervise commercial diesel. Diesel detergency fast simulator can make the detergency evaluation easier, which is an important method to supervise diesel. Distillation range of diesel is the essential base parameter for detergency fast simulator to set working condition. Travelling controller is used to optimize distillation range determination device, which make the detergency detection more intelligent and more time saving. After optimization, distillation range determination device can automatically test and correct temperature, control heating and cooling, and test liquid level by infrared, etc. Therefore, it can reduce operator’s tasks and errors. These optimization designs make it more convenient to operate the detergency detector on mobile monitor vehicle, which is beneficial to supervise commercial diesel rapidly.
In conventional solar tracking system design, optical tracking method and visual tracking method were mainly used. A machine is designed to track the sun automatically based on a CMOS camera, and a virtual software developement is developed by NI company. The sun’s azimuth and elevation are calculated through the relevant algorithm in real time, converted into the desired motor running pulses, and transmitted to 51 single-chip through the RS232. The motor rotation is controlled by the microcontroller to appropriate angle, so that the sun is always in the center of the spot position of the image. The experimental apparatus has a high tracking accuracy and good stability, the minimum tracking error can reach 0.002°.