Influence of building spatial patterns on wind environment and air pollution dispersion inside an industrial park based on CFD simulation.

The "spatial pattern-wind environment-air pollution" within building clusters is closely interconnected, where different spatial pattern parameters may have varying degrees of impact on the wind environment and pollutant dispersion. Due to the complex spatial structure within industrial parks, this complexity may lead to the accumulation and retention of air pollutants within the parks. Therefore, to alleviate the air pollution situation in industrial parks in China and achieve the circular transformation and construction of parks, this study takes Hefei Circular Economy Demonstration Park as the research object. The microscale Fluent model in computational fluid dynamics (CFD) is used to finely simulate the wind flow field and the diffusion process of pollutants within the park. The study analyzes the triad relationship and influence mechanism of "spatial pattern-wind environment-air pollution" within the park and studies the influence of different spatial pattern parameters on the migration and diffusion of pollutants. The results show a significant negative correlation between the content of pollutants and wind speed inside the industrial park. The better the wind conditions, the higher the air quality. The spatial morphology parameters of the building complex are the main influences on the condition of its internal wind environment. Building coverage ratio and degree of enclosure have a significant negative correlation with wind conditions. Maintaining them near 0.23 and 0.37, respectively, is favorable to the quality of the surrounding environment. Moreover, the average height of the building is positively correlated with the wind environment condition. The rate of transport and dissipation of pollutants gradually increases as the average building height reaches 16 m. Therefore, a reasonable building planning strategy and arrangement layout can effectively improve the wind environment condition inside the park, thus alleviating the pollutant retention situation. The obtained results serve as a theoretical foundation for optimizing morphological structure design within urban industrial parks.

Delafossite CuGaO2-Based Chemiresistive Sensor for Sensitive and Selective Detection of Dimethyl Disulfide.

Dimethyl disulfide (DMDS) is a common odor pollutant with an extremely low olfactory threshold. Highly sensitive and selective detection of DMDS in ambient humid air background, by metal oxide semiconductor (MOS) sensors, is highly desirable to address the increased public concern for health risk. However, it has still been a critical challenge up to now. Herein, p-type delafossite CuGaO2 has been proposed as a promising DMDS sensing material owing to its striking hydrophobicity (revealed by water contact angle measurement) and excellent partial catalytic oxidation properties (indicated by mass spectroscopy). The present CuGaO2 sensor shows a selective DMDS response, with satisfied humidity resistance performance and long-term stability at a relatively low operation temperature of 140 °C. An ultrahigh response of 100 to 10 ppm DMDS and a low limit of detection of 3.3 ppb could be achieved via a pulsed temperature modulation strategy. A smart sensing system based on a CuGaO2 sensor has been developed, which could precisely monitor DMDS vapor in ambient humid air, even with the presence of multiple interfering gases, demonstrating the practical application capability of MOS sensors for environmental odor monitoring.

Retrieval and Analysis of Atmospheric Temperature Using a Rotational Raman Lidar Observation.

Due to the existence of the aerosol, the traditional method of measuring atmospheric temperature by using Rayleigh scattering technique has limitations in the low altitude. A pure rotational Raman lidar to get tropospheric temperature profiles is built. We carried out the atmospheric temperature observation in Beijing for two months. The atmospheric temperature profile was retrieved using the observed rotational Raman scattering signals. The effect of smooth window, calibration range and calibration constant on the retrieval precision of the atmospheric temperature was evaluated and analyzed. The results show that with the increase of smooth window, the mean absolute deviation between the lidar and radiosonde firstly decreases and then increases; in order to remove effectively the effect of random error in the return signals, while maintaining the fine vertical structure of temperature profile, it is better to choose the range between 600 and 1 200 m for smooth window. When calibration range is different, the mean absolute deviation between the lidar and radiosonde is varied, the relative variation of the deviation is about 0.07 K. When both calibration constant a and b increase or decrease, the mean deviation between the lidar and radiosonde increases; when one increases and another decreases, the mean deviation has a tendency to cancel each other out. The variance probability of a or b is not equal, and the variance of a and b is always contrary in the sign; the mean deviation is not sensitive to variance of a or b, and it is sensitive to the whole variance of a and b, about 91.7% of the mean deviation is in the range between -3 and 3 K. These results provide the theoretical basis for the selection of smooth window and calibration range in pure rotational Raman lidar data retrieval, and the reference for the error of actual temperature inversion result caused by lidar calibration constant.

[Measurement of path transverse wind velocity profile using light forward scattering scintillation correlation method].

A new method for path transverse wind velocity survey was introduced by analyzing time lagged covariance function of different separation sub-apertures of Hartmann wavefront sensor. A theoretical formula was logically deduced for the light propagation path transverse wind velocity profile. According to the difference of path weighting function for different sub apertures spacing, how to select reasonable path weighting functions was analyzed. Using a Hartmann wavefront sensor, the experiment for measuring path transverse velocity profile along 1 000 m horizontal propagating path was carried out for the first time to our knowledge. The experiment results were as follows. Path transverse averaged velocity from sensor had a good consistency with transverse velocity from the wind anemometer sited near the path receiving end. As the path was divided into two sections, the path transverse velocity of the first section had also a good consistency with that of the second one. Because of different specific underlaying surface of light path, the former was greater than the later over all experiment period. The averaged values were 1.273 and 0.952 m x s(-1) respectively. The path transverse velocity of second section and path transverse averaged velocity had the same trend of decrease and increase with time. The correlation coefficients reached 0.86.

[Raman Lidar measuring tropospheric temperature profiles with many rotational Raman lines].

Due to lower tropospheric aerosols, the Rayleigh and vibrational Raman methods can't measure lower tropospheric temperature profiles accurately. By using N2 and O2 molecular pure rotational Raman scattering signals, lower tropospheric temperature profiles can be gained without influence of lower tropospheric aerosols. So we decide to use a pure rotational Raman Lidar to get lower tropospheric temperature profiles. At present, because the most light-splitting systems of pure rotational Raman Lidar measure temperature by gaining a single rotational Raman line, the signal to noise ratio (SNR) of these Lidar systems are very low. So we design a new kind of Lidar light-splitting system which can sum different rotational Raman lines and it can improve SNR And we can find the sensitivity of the temperature of the ratios of multi rotational Raman lines is as same as single rotational Raman line's through theoretical analysis. Moreover, we can obtain the temperature profiles with good SNR fromthis new the system with a normal laser and a small telescope up to several kilometers. At last, with the new light-splitting system, the lower tropospheric temperature profiles are measured from 0.3 km to 5 km altitude. They agree well with radiosonde observations, which demonstrate the results of our rotational Raman lidar are reasonable.

[Measurement of atmospheric boundary layer pollutants by mobile lidar in Beijing].

The parameters of AML-2 mobile lidar were introduced, which was based on differential absorption principle and designed by our institute. In Yufa of Beijing, the pollutants including O3, NO2, SO2 in atmospheric boundary layer were monitored in August and September of 2006 under different weather conditions. Vertical profile and diurnal variation of concentrations of these pollutants were analyzed. If without the influence of pollution air transport from south region, the concentrations of these pollutants are low under the overcast weather condition. The concentrations of O3 and NO2 decrease with altitude, and this characteristic is not obvious for SO2, but there is a high concentration layer of SO2 near ground (about 0.6km). The quality of atmosphere Beijing is influenced significantly by air transportation from south region, and the altitude of the severe pollution air transport is about 1km to 1.5km in August 23rd to 25th. As a result, the characteristics of vertical profile and daily variation of the pollutants are changed, and the concentrations of O3, NO2, SO2 in atmospheric boundary layer of Yufa area increased obviously.

[Obtaining aerosol backscattering coefficient using pure rotational Raman spectrum].

Atmospheric aerosol backscattering coefficient ratio can be obtained with the ratio of elastic signal to the total rotational Raman backscattering signal without assuming the ratio of aerosol extinction to backscatter. Generally, the intensity ofpartial rotational Raman spectrum lines instead of the total rotational Raman spectrum lines is measured. The intensity of the total rotational Raman spectrum lines is not dependent on the temperature, but the intensity of the partialrotational Raman spectrumlines is dependent on the temperature. So calculating aerosol backscattering coefficient ratio with the intensity of the partial rotational Raman spectrum lines would lead to an error. In the present paper, the change in the intensity sums of different rotational Raman spectrum lines with temperature was simulated and the errors of aerosol backscattering coefficient ratio derived from them were discussed. A new method was presented for measuring aerosol backscattering coefficient ratio, which needed not to measure the intensity of the total rotational Raman spectrum lines. Aerosol backscattering coefficient ratio could be obtained with the atmospheric temperature and a single rotational Raman spectrum line. Finally, a erosol backscattering coefficient ratio profiles of the atmosphere were acquired with the combined Raman lidar of our lab. The results show that there is no need to assume any relation between aerosol backscattering and extinction or to consider any wavelength calibration to determine the aerosol scattering coefficient.

[Method for retrieving pollution gas concentration from Raman lidar return].

Raman lidar is an important tool for the detection of atmosphere pollution, and inversion for lidar returns is an important process. The key for inversion is to get transmission exponential function exp [integral of 0 (R) [alpha(lambda1, z) - alpha(lambda2, z)]]. Three methods with extinction coefficient as the center are presented. First, 532 nm atmospheric extinction coefficient was used to indirectly obtain alpha(lambda1, z) and alpha(lambda2, z). This method has been used generally by people. Two new methods were proposed: 1, reference gas with approximate Raman wavelength is used so that alpha(lambda1, z) = alpha(lambda2, z). 2, Mie-Rayleigh scattered return with wavelength lambda1 or lambda2 is used to compute exp [integral of 0 (R) [alpha(lambda1, z) - alpha(lambda2, z)]].

[Study on the nonlinear Raman lidar monitoring the CO2 gas].

It is a new skill to use SRS rays as emitting waves for the lidar monitoring CO2 gas, and the nonlinear Raman lidar based on the SRS process was devised. The third harmonic Nd: YAG laser wave (354.7 nm) was injected into the Raman cells filled with higher pressure gases, CO2 and N2. The first Stokes (S1) line 371.66 nm (CO2) and 386.7 nm (N2) were generated by stimulated Raman scattering. The variable S1 energy was measured by changing the gas pressure in the Raman cell andthe Nd:YAG laser system output energy. The optimum pressures of the CO2 and N2 in the Raman cell were achieved. Moreover, the principles of this physical process were put forward. This skill has been applied to the lidar for monitoring the CO2 gas.