Adsorption of Natural Gas in Metal-Organic Frameworks: Selectivity, Cyclability, and Comparison to Methane Adsorption.

Evaluation of metal-organic frameworks (MOFs) for adsorbed natural gas (ANG) technology employs pure methane as a surrogate for natural gas (NG). This approximation is problematic, as it ignores the impact of other heavier hydrocarbons present in NG, such as ethane and propane, which generally have more favorable adsorption interactions with MOFs compared to methane. Herein, using quantitative Raman spectroscopic analysis and Monte Carlo calculations, we demonstrate the adsorption selectivity of high-performing MOFs, such as MOF-5, MOF-177, and SNU-70, for a methane and ethane mixture (95:5) that mimics the composition of NG. The impact of selectivity on the storage and deliverable capacities of these adsorbents during successive cycles of adsorption and desorption, simulating the filling and emptying of an ANG tank, is also demonstrated. The study reveals a gradual reduction in the storage performance of MOFs, particularly with smaller pore volumes, due to ethane accumulation over long-term cycling, until a steady state is reached with substantially degraded storage performance.

Returning personal genetic information on susceptibility to arsenic toxicity to research participants in Bangladesh.

BACKGROUND: There is growing consensus that researchers should offer to return genetic results to participants, but returning results in lower-resource countries has received little attention. In this study, we return results on genetic susceptibility to arsenic toxicity to participants in a Bangladeshi cohort exposed to arsenic through naturally-contaminated drinking water. We examine the impact on behavioral changes related to exposure reduction. METHODS: We enrolled participants from the Health Effects of Arsenic Longitudinal Study who had (1) high arsenic (≥150 µg/g creatinine) in a recent urine sample and (2) existing data on genetic variants impacting arsenic metabolism efficiency (AS3MT and FTCD). We used genetic data to recruit three study groups, each with n = 103: (1) efficient metabolizers (low-risk), (2) inefficient metabolizers (high-risk), and (3) a randomly-selected control group (NCT05072132). At baseline, all participants received information on the effects of arsenic and how to reduce exposure by switching to a low arsenic well. The two intervention groups also received their arsenic metabolism efficiency status (based on their genetic results). Changes in behavior and arsenic exposure were assessed using questionnaires and urine arsenic measures after six months. RESULTS: Clear decreases in urine arsenic after six months were observed for all three groups. The inefficient group self-reported higher levels of attempted switching to lower arsenic wells than the other groups; however, there was no detectable difference in urine arsenic reduction among the three groups. Participants showed strong interest in receiving genetic results and found them useful. The inefficient group experienced higher levels of anxiety than the other groups. Among the efficient group, that receiving genetic results did not appear to hinder behavioral change. CONCLUSION: Returning genetic results increased self-reported exposure-reducing behaviors but did not have a detectable impact on reducing urine arsenic over and above a one-on-one educational intervention.

Evaluation of occupational health and safety intervention for the waste and sanitation workers in Bangladesh during COVID-19.

Waste and sanitation workers in South-Asian countries are vulnerable to injuries and diseases, including COVID-19. In Bangladesh, an intervention was implemented during COVID-19 to lower these workers' occupational health risks through training and PPE distribution. We assessed how the intervention affected their occupational health behaviors using a randomized cluster trial in 10 Bangladeshi cities, including seven intervention and three control areas. We conducted 499 surveys (Control-152, Intervention-347) and 47 structured observations (Control:15, Intervention:32) at baseline and 499 surveys (Control:150, Intervention:349) and 50 structured observations (Control:15, Intervention:35) at endline. To evaluate the impact of intervention at the endline, we used the difference in difference (DID) method. Compared to control, workers from intervention areas were more likely to have increased knowledge of using/maintaining PPEs (adjusted DID: 21%, CI: 8, 33), major COVID-19 transmission causes (adjusted DID: 27%, CI: 14, 40), and preventive measures (adjusted DID: 12%, CI: -0.6, 25), and improved attitude about using PPEs (adjusted DID: 36%, CI: 22, 49), washing PPEs (adjusted DID: 20%, CI: 8, 32). The intervention was more likely to improve workers' self-reported practice of taking adequate precautions after getting back from work (adjusted DID: 37%, CI: 27, 47) and changing/cleaning masks every day (adjusted DID: 47%, CI: 0.03, 94), and observed practices of maintaining coughing etiquette (DID: 20%, CI: 0.2, 40) at workplace and handwashing before wearing PPEs (DID: 27%, CI: 2, 52), after finishing work (DID: 31%, CI: -7, 69) & during work intervals (DID: 30%, CI: -33, 93). There was not much improvement in observed practices of mask use (DID: 1%, CI: -40, 42), handwashing before meals (DID: 2%, CI: -61, 65), and after toilet (DID: 7%, CI: -41, 55). This intervention has improved the knowledge, attitude and practice of the workers about critical occupational risk mitigation, which may be replicated in similar settings. Future interventions need to address occupational health-related injuries and health complications, introduce regular health checkups/insurance for the workers, create a balance between the quality and comfort of the PPEs and ensure a mechanism to ensure a regular supply of PPEs.