Insights into adsorbable organic halogen analysis: Two overlooked factors impacting water quality assessment.

Adsorbable organic halogen (AOX) represents the total amount of halogenated organics that can be adsorbed on activated carbon (AC) from samples. Measuring AOX is crucial for assessing water quality, and any erroneous estimation of AOX risks misleading decision-makers. This study demonstrated two overlooked factors that may introduce biases to AOX measurement. The first one relates to impurities in the gas transfer tubes of AOX combustion system and in the pressurized gas of AOX separation system, which resulted in significant fluctuations and high blank values (8.5-118.0 µg-Cl/L). The solutions of above issues are to warming up the combustor for several runs and replacing the pressurized air with argon gas in the separator, which could drop the blank AOX values to 9.1-10.0 µg-Cl/L. The second one involves coexisting chloride ion (Cl-) during AOX analysis, which interfered with AOX measurements (T. test, p < 0.05) even at low concentration levels (e.g., 10 mg/L Cl- in samples with 100 µg-Cl/L p-chlorophenol). Results show that AC captured 0.02-0.11 % of Cl-, resulting in 17.7-24.5 µg-Cl/L AOX responses in control samples containing 15-130 mg/L Cl- only. Furthermore, a significant mass imbalance of Cl- (3.58-8.39 %) during analysis process suggests a potential impact of residual Cl- on subsequent samples. By comparing synthetic and actual waters, samples with low dissolved organic carbon (DOC) were more susceptible to interference from Cl- on AOX measurement than those with high DOC. These findings underscore the pressing need to optimize existing AOX methods or develop alternative analytical methods to ensure accurate water quality assessment.

Integrated assessment of the pollution and risk of heavy metals in soils near chemical industry parks along the middle Yangtze River.

Industrialization in riparian areas of critical rivers has caused significant environmental and health impacts. Taking eight industrial parks along the middle Yangtze River as examples, this study proposes a multiple-criteria approach to investigate soil heavy metal pollution and associated ecological and health risks posed by industrial activities. Aiming at seven heavy metals, the results show that nickel (Ni), cadmium (Cd), and copper (Cu) exhibited the most significant accumulation above background levels. The comprehensive findings from Pearson correlation analysis, cluster analysis, principal component analysis, and industrial investigation uncover the primary sources of Cd, arsenic (As), mercury (Hg), and lead (Pb) to be chemical processing, while Ni and chromium (Cr) are predominantly derived from mechanical and electrical equipment manufacturing. In contrast, Cu exhibits a broad range of origins across various industrial processes. Soil heavy metals can cause serious ecological and carcinogenic health risks, of which Cd and Hg contribute to >70 % of the total ecological risk, and As contributes over 80 % of the total health risk. This study highlights the importance of employing multiple mathematical and statistical models in determining and evaluating environmental hazards, and may aid in planning the environmental remediation engineering and optimizing the industry standards.

The impact of the COVID-19 pandemic on the global dynamic spillover of financial market risk.

The COVID-19 outbreak has greatly impacted the stability of the global financial markets. In the post-COVID-19 pandemic era, the risk contagion patterns of the global financial markets may change. This paper utilizes the conditional value-at-risk (ΔCoVaR) model to measure the risk level of the financial markets in various economies and uses the TVP-VAR-CONNECTEDNESS approach to construct a time-varying spillover index. Based on the dimensions of time and space, we explored the contagion path, contagion status, and contagion structure characteristics of global financial market risk before and during the COVID-19 pandemic. The results entail several conclusions. (i) The COVID-19 pandemic increased the spillover level of global financial market risk and the risk connectedness of financial markets in different countries. In addition, during the concentrated outbreak period of COVID-19, the risk spillover level in developing countries rose rapidly, while the financial risk spillover level in developed countries decreased significantly. (ii) The impact of the COVID-19 pandemic on the spillover of the global financial market risk is time-varying, and there is a strong correlation between the risk spillover level of the financial markets of the world and the severity of the COVID-19 pandemic. (iii) Due to the impact of the COVID-19 pandemic, Brazil, Canada, and Russia have become new risk spillover centers; in the post-COVID-19 pandemic era, China's spillover to developed countries has increased, and the financial influence of China has also gradually increased. In addition, the risk contagion capacity of financial markets among European countries is gradually converging. (iv) During the concentrated outbreak of the COVID-19 pandemic, the Americas were the main exporter of global financial market risk, while Europe played a role in risk absorption.

Robust path planning for flexible needle insertion using Markov decision processes.

PURPOSE: Flexible needle has the potential to accurately navigate to a treatment region in the least invasive manner. We propose a new planning method using Markov decision processes (MDPs) for flexible needle navigation that can perform robust path planning and steering under the circumstance of complex tissue-needle interactions. METHODS: This method enhances the robustness of flexible needle steering from three different perspectives. First, the method considers the problem caused by soft tissue deformation. The method then resolves the common needle penetration failure caused by patterns of targets, while the last solution addresses the uncertainty issues in flexible needle motion due to complex and unpredictable tissue-needle interaction. RESULTS: Computer simulation and phantom experimental results show that the proposed method can perform robust planning and generate a secure control policy for flexible needle steering. Compared with a traditional method using MDPs, the proposed method achieves higher accuracy and probability of success in avoiding obstacles under complicated and uncertain tissue-needle interactions. Future work will involve experiment with biological tissue in vivo. CONCLUSION: The proposed robust path planning method can securely steer flexible needle within soft phantom tissues and achieve high adaptability in computer simulation.