A Comparative Health Assessment of Occupationally Lead Exposed Individuals with Blood Lead Levels Range across Upper Acceptable Limit.

Context: Lead (Pb) smelting workers are exposed to high lead levels and its adverse health effects. Despite no biological role, regulatory bodies regard blood lead levels (BLL) ≤40 µg/dL as upper acceptable limit in occupationally lead exposed population. Objective: To explore the differences in general health status of individuals with BLL ≤40 µg/dL and >40 µg/dL. Methods: All workers (n = 803) of age >18 years employed in a Pb smelting plant were interviewed with a semi-structured questionnaire to obtain sociodemographics, occupational details, followed by detailed clinical examination. 5 ml of venous blood was collected and BLLs were determined as per standard NIOSH method using GF-AAS technic. A complete general health status was performed including hemoglobin and blood pressure (BP). Results: About 47.7% of the participants exhibited high BLL (>40 µg/dL), while the rest 52.3% were identified to have ≤40 µg/dL. Both groups were grossly similar in the majority of demographic and occupational parameters. Interestingly, both groups had substantially higher fraction of workers with elevated BP. Conclusions: Lead exposed workers with BLL ≤40 µg/dL are at equal risk of health hazards as those with BLL >40 µg/dL. There is a need to revisit the current guidelines on the BLL for workers to protect from the hazards of chronic lead exposure.

Responses of ecosystem services to natural and anthropogenic forcings: A spatial regression based assessment in the world's largest mangrove ecosystem.

Most of the Earth's Ecosystem Services (ESs) have experienced a decreasing trend in the last few decades, primarily due to increasing human dominance in the natural environment. Identification and categorization of factors that affect the provision of ESs from global to local scales are challenging. This study makes an effort to identify the key driving factors and examine their effects on different ESs in the Sundarbans region, India. We carry out the analysis following five successive steps: (1) quantifying biophysical and economic values of ESs using three valuation approaches; (2) identifying six major driving forces on ESs; (3) categorizing principal data components with dimensionality reduction; (4) constructing multivariate regression models with variance partitioning; (5) implementing six spatial regression models to examine the causal effects of natural and anthropogenic forcings on ESs. Results show that climatic factors, biophysical factors, and environmental stressors significantly affect the ESs. Among the six driving factors, climate factors are highly associated with the ESs variation and explain the maximum model variances (R2 = 0.75-0.81). Socioeconomic (R2 = 0.44-0.66) and development (R2 = 27-0.44) factors have weak to moderate effects on the ESs. Furthermore, the joint effects of the driving factors are much higher than their individual effects. Among the six spatial regression models, Geographical Weighted Regression (GWR) performs the most accurately and explains the maximum model variances. The proposed hybrid valuation method aggregates biophysical and economic estimates of ESs and addresses methodological biases existing in the valuation process. The presented framework can be generalized and applied to other ecosystems at different scales. The outcome of this study could be a reference for decision-makers, planners, land administrators in formulating a suitable action plan and adopting relevant management practices to improve the overall socio-ecological status of the region.

Ecosystem service value assessment of a natural reserve region for strengthening protection and conservation.

Ecosystem Services (ESs) refer to the direct and indirect contributions of ecosystems to human well-being and subsistence. Ecosystem valuation is an approach to assign monetary values to an ecosystem and its key ecosystem goods and services, generally referred to as Ecosystem Service Value (ESV). We have measured spatiotemporal ESV of 17 key ESs of Sundarbans Biosphere Reserve (SBR) in India using temporal remote sensing (RS) data (for years 1973, 1988, 2003, 2013, and 2018). These mangrove ecosystems are crucial for providing valuable supporting, regulatory, provisioning, and cultural ecosystem services. We have adopted supervised machine learning algorithms for classifying the region into different ecosystem units. Among the used machine learning models, Support Vector Machine (SVM) and Random Forest (RF) algorithms performed the most accurate and produced the best classification estimates with maximum kappa and an overall accuracy value. The maximum ESV (derived from both adjusted and non-adjusted units, million US$ year-1) is produced by mangrove forest, followed by the coastal estuary, cropland, inland wetland, mixed vegetation, and finally urban land. Out of all the ESs, the waste treatment (WT) service is the dominant ecosystem service of SBR. Additionally, the mangrove ecosystem was found to be the most sensitive to land use and land cover changes. The synergy and trade-offs between the ESs are closely associated with the spatial extent. Therefore, accurate estimates of ES valuation and mapping can be a robust tool for assessing the effects of poor decision making and overexploitation of natural resources on ESs.

Estimating global ecosystem service values and its response to land surface dynamics during 1995-2015.

Changes in land use due to the industrial revolution, increasing population, ever-increasing desire for economic growth is a global concern. The aforementioned changes can have a significant impact on global and regional ecosystem services which are indispensable for human well-being and their subsistence. This study identifies several approaches (Costanza et al., de Groot et al., and Xie et al.) to estimate the value of global terrestrial ecosystem services. High resolution (300 m) land use products provided by European Space Agency-Climate Change Initiative (ESA-CCI) were used to quantify the global ecosystem service values (ESV) for 1995, 2000, 2005, 2010 and 2015 respectively. The coefficient of elasticity (CE) and coefficient of sensitivity (CS) was calculated to compute the response of ESV's corresponding to land use land cover (LULC) change. The results estimated the mean global ESV's (Trillion US$ year-1) to be 58.97 in 1995 and 57.76 in 2015, indicating a net loss of ESV (1.21 Trillion US$ year-1) during the analysis period (1995-2015) due to depletion of forest cover and wetland/water surface. The overall ESV (Trillion US$ year-1) increased in cropland (4.8 in 1995 to 4.9 in 2015) and urban coverage (0.3 in 1995 to 0.59 in 2015) whereas, it reduced substantially in forests (17.59 in 1995 to 17.42 in 2015), grasslands (9.1 in 1995 to 8.9 in 2015), wetland (22.19 in 1995 to 21.11 in 2015) and water bodies (5.29 in 1995 to 5.27). The forestland, wetland, and water bodies are the highest sensitive eco-regions defined by all valuation methods. The current research provides a way to quantify the overall economic loss or gain due to changes in the past, present, and future land use. This will bridge the gap between economic evaluations of current assets concerning the changes in land use. It will also help planners to provide an in-depth thought to the changes in the overall economic value of a particular land use in future (keeping biodiversity in mind) while validating long-term policies concerning to ecological conservation of a country.

Assessment of 8-oxo-7,8-dihydro-2'-deoxyguanosine as a marker of oxidative DNA damage in gasoline filling station attendants.

OBJECTIVES: The urinary excretion of 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-oxodG) was used as a biomarker of oxidative DNA damage. The urinary 8-oxodG levels in petrol filling station attendants (exposed) at various petrol bunks were estimated as well as in the unexposed (cashier) population. MATERIALS AND METHODS: A total of 100 workers (79 petrol fillers and 21 cashiers) aged from 20 to 41 years participated in the study. An informed consent was taken from each participant. Information on personal habits and health was obtained through a questionnaire. After shifts, urine samples were collected analyzed for 8-oxodG using enzyme-linked immunosorbent assay (ELISA). RESULTS: Fifty-three percent of workers were in the 21-30 years age group. The maximum level of 8-oxodG was observed in the age group ≥ 41 years and the minimum in the age group of 31-40 years. The maximum level of 8-oxodG was observed among those workers who had ≥ 21 years of experience. The concentrations of 8-oxodG were significantly higher in petrol fillers than those in cashiers (p < 0.05). CONCLUSIONS: Despite the conflicting results obtained in our study it was shown that 8-oxodG is related to chemical exposure. Further research is needed embracing a bigger number of participants to highlight the correlations between the exposure and the effects.