How does technological progress affect low carbon economic growth? Evidence from regional heterogeneity in China.

The rapid economic development leads to excessive consumption of fossil energy, resulting in a large number of carbon emissions, which makes the sustainable development of China's economy and society face great challenges. Under the background of global warming and environmental deterioration, developing low-carbon economy has become an inevitable choice for China to change its development model and improve its international competitiveness. Technological progress is the first driving force to promote economic growth. However, the influence degree and mechanism of technological progress on the development of low-carbon economy are still unclear. Based on this, the paper proposes the concept of low-carbon GDP, which is used to measure the low-carbon economic development of 30 Chinese provinces. Then, the panel fixed effect model is used to study the effect degree and mechanism of technological progress on low-carbon GDP and the moderating effect of other factors on the relationship between them. The results show that, first, economically developed provinces and regions have higher per capita low-carbon GDP and low-carbon GDP index, but the speed and quality of low-carbon economic development are not necessarily higher. Second, technological progress can promote the growth of low-carbon GDP and make greater contributions to resources-poor regions. Third, improving local education can make technological progress more effective in low-carbon economic development. China needs to upgrade technological development by developing new and high-tech technologies, promoting new urbanization and strengthening education in order to promote low-carbon economic development.

Simultaneous All-Parameters Calibration and Assessment of a Stereo Camera Pair Using a Scale Bar.

Highly accurate and easy-to-operate calibration (to determine the interior and distortion parameters) and orientation (to determine the exterior parameters) methods for cameras in large volume is a very important topic for expanding the application scope of 3D vision and photogrammetry techniques. This paper proposes a method for simultaneously calibrating, orienting and assessing multi-camera 3D measurement systems in large measurement volume scenarios. The primary idea is building 3D point and length arrays by moving a scale bar in the measurement volume and then conducting a self-calibrating bundle adjustment that involves all the image points and lengths of both cameras. Relative exterior parameters between the camera pair are estimated by the five point relative orientation method. The interior, distortion parameters of each camera and the relative exterior parameters are optimized through bundle adjustment of the network geometry that is strengthened through applying the distance constraints. This method provides both internal precision and external accuracy assessment of the calibration performance. Simulations and real data experiments are designed and conducted to validate the effectivity of the method and analyze its performance under different network geometries. The RMSE of length measurement is less than 0.25 mm and the relative precision is higher than 1/25,000 for a two camera system calibrated by the proposed method in a volume of 12 m × 8 m × 4 m. Compared with the state-of-the-art point array self-calibrating bundle adjustment method, the proposed method is easier to operate and can significantly reduce systematic errors caused by wrong scaling.

[Characteristics and Risk Assessment of Heavy Metals in Core Sediments from Lakes of Tibet].

To explore the source of heavy metals in lake sediments and their hazard to environment on Tibetan Plateau, China, heavy metal (Cu, Zn, Cd, Pb, Cr, Co, Ni and As) levels in surface sediments of 18 lakes were investigated. Inductively Coupled Plasma Mass Spectrometry (ICP-MS, X-7 series) was used to determine the contents of heavy metals and the concentrations of carbon and nitrogen in sediment samples were analyzed by element analyzer (Vario Max CN, Elementar, Germany). The average concentrations for Cu, Zn, Cd, Pb, Cr, Co, Ni and As were 24.61 mg x kg(-1), 70.14 mg x kg(-1), 0.26 mg x kg(-1), 25.43 mg x kg(-1), 74.12 mg x kg(-1), 7.93 mg x kg(-1), 33.85 mg x kg(-1), 77.69 mg x kg(-1). It was found that heavy-metal concentrations in Tibet sediments were higher than those in Antarctic, but lower than those in the regions affected by anthropogenic activities. The contents of Cu, Zn, Pb, Cr and Co in the samples were lower than the background values of Tibet. Correlation analysis and principal components analysis (PCA) were used to analyze the origins of heavy metals. The result showed that Cu, Zn, Cd, Pb, Co, Ni and As came from soil in drainage basin and atmospheric deposition. Cr was mainly affected by human activities. Assessment on ecological risk of heavy metals was carried out using Hakanson's method and cluster analysis (CA). Assessment on ecological risk indicated that Pumoyum Co, Longmo Co and Bangong Co were at low risks, Bieruoze Co was at high ecological risk level and the other lakes were at different risk levels.