RESUMEN
This paper examines how economic growth and renewable energy consumption are associated with air pollution using a dynamic panel approach. Focusing on several major air pollutants, namely, particulate matter, sulfur dioxide, nitrogen oxide, and carbon monoxide, this paper tests the environmental Kuznets hypothesis and determines whether the use of renewable energy sources contributes to a reduction in air pollution. Data from a balanced panel of 145 countries for the period between 2000 and 2014 was used for the estimation of the dynamic panel model. The results of the dynamic panel model showed inverted U-shaped curves for the relationship between economic development and particulate matter and sulfur dioxide emissions. The results also revealed that increasing renewable energy consumption contributes to an improvement in air quality. Moreover, it was found that urbanization tends to decrease sulfur dioxide and nitrogen oxide emissions, while trade openness reduces particulate matter and carbon monoxide emissions but increases sulfur dioxide emissions.
Asunto(s)
Contaminación del Aire , Desarrollo Económico , Dióxido de Carbono/análisis , Energía Renovable , UrbanizaciónRESUMEN
We investigate a method to improve the position decoding for thick crystal versions (i.e., ≥8 mm) of the continuous miniature crystal element (cMiCE) PET detector by more accurately modeling the detector light response function (LRF). The LRF for continuous detectors varies with the depth of interaction (DOI) of the detected photon. This variation in LRF can result in a positioning error for two-dimensional positioning algorithms. We explore a method to improve positioning performance by deriving two lookup tables, corresponding to the front and back regions of the crystal. The DETECT2000 simulation package was used to investigate the light response characteristics for a 48.8 mm by 48.8 mm by 10 (8) mm slab of LSO coupled to a 64-channel, flat-panel PMT. The data are then combined to produce the two-dimensional light collection histograms. Light collection histograms that have markedly non-Gaussian distributions are characterized as a combination of two Gaussian functions, where each Gaussian function corresponds to a DOI region of the crystal. The results indicate that modest gains in positioning accuracy are achieved near the central region of the crystal. However, significant improvements in spatial resolution and positioning bias are achieved for the corner section of the detector.