Multiscale Analysis of the Relationship between Toxic Chemical Hazard Risks and Racial/Ethnic and Socioeconomic Groups in Texas, USA.

Although quantitative environmental (in)justice research demonstrates a disproportionate burden of toxic chemical hazard risks among racial/ethnic minorities and people in low socioeconomic positions, limited knowledge exists on how racial/ethnic and socioeconomic groups across geographic spaces experience toxic chemical hazards. This study analyzed the spatial non-stationarity in the associations between toxic chemical hazard risk and community characteristics of census block groups in Texas, USA, for 2017 using a multiscale geographically weighted regression. The results showed that the percentage of Black or Asian population has significant positive associations with toxic risk across block groups in Texas, meaning that racial minorities suffered more from toxic risk wherever they are located in the state.

Tracing toxic chemical releases embodied in U.S. interstate trade and their unequal distribution.

Toxic chemicals have severe impacts on ecosystem, climate change and human health, and the current toxic releases are inequitably distributed across regions. Investigating the toxic release embodied in final demand by states and income groups can reveal the responsibility transfer of different entities. In this paper, we extended the U.

Assessing inequities underlying racial disparities of COVID-19 mortality in Louisiana parishes.

High COVID-19 mortality among Black communities heightened the pandemic's devastation. In the state of Louisiana, the racial disparity associated with COVID-19 mortality was significant; Black Americans accounted for 50% of known COVID-19-related deaths while representing only 32% of the state's population. In this paper, we argue that structural racism resulted in a synergistic framework of cumulatively negative determinants of health that ultimately affected COVID-19 deaths in Louisiana Black communities.

Raman Spectroscopic Detection for Simulants of Chemical Warfare Agents Using a Spatial Heterodyne Spectrometer.

Raman spectroscopic detection is one of the suitable methods for the detection of chemical warfare agents (CWAs) and simulants. Since the 1980s, many researchers have been dedicated to the research of chemical characteristic of CWAs and simulants and instrumental improvement for their analysis and detection. The spatial heterodyne Raman spectrometer (SHRS) is a new developing instrument for Raman detection that appeared in 2011.

Data processing error analysis based on Doppler asymmetric spatial heterodyne measurement.

The Doppler asymmetric spatial heterodyne (DASH) interferometer provides the capability to retrieve wind speed in the upper atmosphere. The data processing leads to a significant retrieving error with the development of wind precision. The influence of window parameters on the isolated interferogram is analyzed theoretically.

[The Research of Spatial Heterodyne Raman Spectroscopy with Standoff Detection].

Spatial heterodyne Raman spectroscopy (SHRS) is a new type of Raman spectroscopic detection technique with characteristics of high optical throughout, high spectral resolution, and no moving parts. SHRS is very suitable for the planetary exploration missions, which can be used to the analysis of minerals and find the biomarkers maybe exist on the surface of planetary. The authors have applied the technique to the standoff Raman spectroscopic detection, analyzed the main characteristics, including spectral resolution, bandpass and signal to noise (SNR), of standoff SHRS and proved it through experiments.

[Data Processing Method of Asymmetric Spatial Heterodyne Interferogram for Wind Measurement].

By using doppler asymmetric spatial heterodyne spectroscopy and doppler effect, the wind speed can be achieved through detecting the interferogram of airglow in the upper atmosphere. This paper mainly analyses the data processing method of the interferogram and then derive the interferometer phase in order to get the wind speed. Comparing with the traditional spatial heterodyne spectroscopy, not only the noise and error of the system should be taken into consideration, but the window function that used to isolate the spectrum has a great influence during the data processing.