Elevated levels of biomarkers of oxidative stress and renal injury linked to nitrogenous flame retardants exposure in e-waste dismantling site: A case study in China

Hormonal, liver, and renal function associated with electronic waste (e-waste) exposure in Dhaka, Bangladesh

Electronic waste (e-waste) contains numerous metals and organic pollutants that have detrimental impacts on human health. We studied 199 e-waste recycling workers and 104 non-exposed workers; analyzed blood, urine, and hair samples to measure heavy metals, hormonal, liver, and renal function. We used quantile regression models to evaluate the impact of Pb, Cd, and Hg on hormonal, liver and renal function, and the role of DNA oxidative damage in mediating the relationship between exposures and outcomes. Exposed workers had higher blood lead (Pb) (median 11.89 vs 3.63 µg/dL), similar blood cadmium (Cd) (1.04 vs 0.99 µg/L) and lower total mercury (Hg) in hair (0.38 vs 0.57 ppm) than non-exposed group. Exposed workers also had elevated median concentrations of total triiodothyronine (TT3), aspartate aminotransferase (AST), alanine aminotransferase (ALT), urinary albumin, albumin creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR) were significantly higher than non-exposed group (p≤0.05). Sex hormones including luteinizing hormone, follicle stimulating hormone, estrogen, progesterone and testosterone concentrations were not significantly different between exposed and non-exposed (all p≥0.05). The median concentration of ALT was 4.00 (95% CI: 0.23, 7.77), urinary albumin was 0.09 (95% CI: 0.06, 0.12) and ACR was 1.31 (95% CI: 0.57, 2.05) units higher in the exposed group compared to non-exposed group. Pb was associated with a 3.67 unit increase in the ALP (95% CI: 1.53, 5.80), 0.01 unit increase in urinary albumin (95% CI: 0.002, 0.01), and 0.07 unit increase in ACR (95% CI: 0.01, 0.13). However, no hormonal, renal, and hepatic parameters were associated with Cd or Hg. Oxidative DNA damage did not mediate exposure-outcome relationships (p≥0.05). Our data indicate e-waste exposure impairs liver and renal functions secondary to elevated Pb levels. Continuous monitoring, longitudinal studies to evaluate the dose-response relationship and effective control measure are required to protect workers from e-waste exposure.

Changing on the Concentrations of Neonicotinoids in Rice and Drinking Water through Heat Treatment Process

Neonicotinoids (NEOs) have become the most widely used insecticides in the world since the mid-1990s. According to Chinese dietary habits, rice and water are usually heated before being consumed, but the information about the alteration through the heat treatment process is very limited. In this study, NEOs in rice samples were extracted by acetonitrile (ACN) and in tap water, samples were extracted through an HLB cartridge, then, a high-performance liquid chromatography system and a triple quadrupole mass spectrometry (HPLC-MS/MS) were applied for target chemical analysis. The parents of NEOs (p-NEOs) accounted for >99% of the total NEOs mass (∑NEOs) in both uncooked (median: 66.8 ng/g) and cooked (median: 41.4 ng/g) rice samples from Guangdong Province, China, while the metabolites of NEOs (m-NEOs) involved in this study accounted for less than 1%. We aimed to reveal the concentration changes of NEOs through heat treatment process, thus, several groups of rice and water samples from Guangdong were cooked and boiled, respectively. Significant (p < 0.05) reductions in acetamiprid, imidacloprid (IMI), thiacloprid, and thiamethoxam (THM) have been observed after the heat treatment of the rice samples. In water samples, the concentrations of THM and dinotefuran decreased significantly (p < 0.05) after the heat treatment. These results indicate the degradation of p-NEOs and m-NEOs during the heat treatment process. However, the concentrations of IMI increased significantly in tap water samples (p < 0.05) after heat treatment process, which might be caused by the potential IMI precursors in those industrial pesticide products. The concentrations of NEOs in rice and water can be shifted by the heat treatment process, so this process should be considered in relevant human exposure studies.

Concepts of circular economy for sustainable management of electronic wastes: challenges and management options

The electronic and electrical industrial sector is exponentially growing throughout the globe, and sometimes, these wastes are being disposed of and discarded with a faster rate in comparison to the past era due to technology advancements. As the application of electronic devices is increasing due to the digitalization of the world (IT sector, medical, domestic, etc.), a heap of discarded e-waste is also being generated. Per-capita e-waste generation is very high in developed countries as compared to developing countries. Expansion of the global population and advancement of technologies are mainly responsible to increase the e-waste volume in our surroundings. E-waste is responsible for environmental threats as it may contain dangerous and toxic substances like metals which may have harmful effects on the biodiversity and environment. Furthermore, the life span and types of e-waste determine their harmful effects on nature, and unscientific practices of their disposal may elevate the level of threats as observed in most developing countries like India, Nigeria, Pakistan, and China. In the present review paper, many possible approaches have been discussed for effective e-waste management, such as recycling, recovery of precious metals, adopting the concepts of circular economy, formulating relevant policies, and use of advance computational techniques. On the other hand, it may also provide potential secondary resources valuable/critical materials whose primary sources are at significant supply risk. Furthermore, the use of machine learning approaches can also be useful in the monitoring and treatment/processing of e-wastes. HIGHLIGHTS: In 2019, ~ 53.6 million tons of e-wastes generated worldwide. Discarded e-wastes may be hazardous in nature due to presence of heavy metal compositions. Precious metals like gold, silver, and copper can also be procured from e-wastes. Advance tools like artificial intelligence/machine learning can be useful in the management of e-wastes.