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. We identify the spatial distribution of social, environmental, and economic stressors across Louisiana parishes using hot spot analysis to develop aggregate stressors. Further, we examine the correlation between stressors, cumulative health risks, COVID-19 mortality, and the size of Black populations throughout Louisiana. We hypothesized that parishes with larger Black populations (percentages) would have larger stressor values and higher cumulative health risks as well as increased COVID-19 mortality rates. Our results suggest two categories of parishes. The first group has moderate levels of aggregate stress, high population densities, predominately Black populations, and high COVID-19 mortality. The second group of parishes has high aggregate stress, lower population densities, predominantly Black populations, and initially low COVID-19 mortality that increased over time. Our results suggest that structural racism and inequities led to severe disparities in initial COVID-19 effects among highly populated Black Louisiana communities and that as the virus moved into less densely populated Black communities, similar trends emerged.

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. By contrast, the percentage of Hispanic or Latino has a positive relationship with toxic risk, and the relationship varies locally and is only significant in eastern areas of Texas. Statistical associations between toxic risk and socioeconomic variables are not stationary across the state, showing sub-state patterns of spatial variation in terms of the sign, significant level, and magnitude of the coefficient. Income has a significant negative association with toxic risk around the Dallas-Fort Worth-Arlington Metropolitan Statistical Area. Proportions of people without high school diploma and the unemployment rate both have positive relationships with toxic risk in the eastern area of Texas. Our findings highlight the importance of identifying the spatial patterns of the association between toxic chemical hazard risks and community characteristics at the census block group level for addressing environmental inequality.

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. Based on the derivation, the system is established, and the interferogram with a small shift is sampled. The phase and wind speed are calculated under various window types and window width values. We conclude that, by choosing the Nuttall window with a small width, the wind retrieving error can be minimized.

[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. Then the effect of window type and window width on phase difference of interferogram and the wind error curve are simulated through software. On basis of this the wind error curve under the noise of system and flat field factor are simulated by choosing appropriate window function. The window function simulation indicates that although the joining of window leads to a distortion of the interferogam and phase, the wind speed error can be less than 0.5% with Hanning window in the appropriate optical path difference. The noise of the system simulation indicates that the wind speed error increases with the noise, so it is necessary to control the system noise and preprocess the sampling data. The research on data processing method has great theoretical significance and practical value for designing the system parameter and improving the precision of spatial heterodyne wind detection.

[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. The basic theory of standoff SHRS has been described briefly while a breadboard has been designed, built and calibrated. On the basis, the Raman spectra of some inorganic solids, organic liquids and some natural minerals have been achieved at a distance of 10 m, the SNR of the breadboard has been estimated. Due to the poor adjustment and the defects of the optical elements, the breadboard is far away from an ideal system. But the results show that the SNR is better than 5 for most of the main Raman peaks of the samples, which can meet the basic requirement of clear positive detection of typical Raman peaks and the feasibility of standoff SHRS has been proved. SHRS can overcome the main defects of dispersive grating Raman spectrometers and Fourier transform Raman spectrometers and it has a great application prospect on the detection and analysis of the planetary surface. The work of the authors can prove the potentiality of SHRS on standoff detection and can provide reference for the engineering realization of standoff SHRS.

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.S. multi-regional input-output (MRIO) model with toxic chemical release data in 2017 to conduct the production- and consumption-based accounting of toxic release by each state, and the inter-regional transfer of embodied toxic release between states. In addition, this paper analyzed how the toxic releases and inter-state transfer of embodied toxic release have been driven by income groups across states. The results showed that the toxic release from production was highly concentrated on the central states and the Great Lakes Region, while the consumption-based accounting of toxic release was more equally distributed across regions in the US. The non-metallic and metallic products manufacturing sectors were the most important sectors for most states from both production and consumption-based perspectives and were also the most essential sectors for interregional flows of embodied toxic release from Great Lake Region to Southeast, Mid-Atlantic and Northeast. Our results also showed that the largest portion (41.88%) of embodied toxic releases were triggered by households' final demand, and that the consumption of the richest 35% of households contributed to more than 50% of the total toxic chemical releases triggered by total final demand of all households.

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. It is already well-known that SHRS has the characteristics of high spectral resolution, a large field-of-view, and high throughput. Thus, it is inherently suitable for the analysis and detection of these toxic chemicals and simulants. The in situ and standoff detection of some typical simulants of CWAs, such as dimethyl methylphosphonate (DMMP), diisopropyl methylphosphonate (DIMP), triethylphosphate (TEP), diethyl malonate (DEM), methyl salicylate (MES), 2-chloroethyl ethyl sulfide (CEES), and malathion, were tried. The achieved results show that SHRS does have the ability of in situ analysis or standoff detection for simulants of CWAs. When the laser power was set to as low as 26 mW, the SHRS still has a signal-to-noise ratio higher than 5 in in situ detection. The standoff Raman spectra detection of CWAs simulants was realized at a distance of 11 m. The potential feasibility of standoff detection of SHRS for CWAs simulants has been proved.