An assessment of carbon stock for various land use system in Aravally mountains, Western India

Reducing carbon emissions from deforestation and degradation in developing countries is of the central importance in efforts to combat climate change. A study was conducted to measure carbon stocks in various land-use systems including forms and reliably estimates the impact of land use on carbon (C) stocks in the forest of Rajasthan, western India (23°3′–30°12′N longitude and 69°30′–78°17′E). 22.8% of India is forested and 0.04% is the deforestation rate of India. In Indian forest sector of western India of Aravally mountain range covered large area of deciduous forest and it’s very helpful in carbon sequestration at global level. The carbon stocks of forest, plantation (reforestation) and agricultural land in aboveground, soil organic and fine root within forest were estimated through field data collection. Results revealed that the amount of total carbon stock of forests (533.64?±?37.54 Mg·ha^?1, simplified expression of Mg (carbon) ·ha^?1) was significantly greater (P?<?0.05) than the plantation (324.37?±?15.0 Mg·ha^?1) and the agricultural land (120.50?±?2.17 Mg·ha^?1). Soil organic carbon in the forests (172.84?±?3.78 Mg·ha^?1) was also significantly greater (P?<?0.05) than the plantation (153.20?±?7.48 Mg·ha^?1) and the agricultural land (108.71?±?1.68 Mg·ha^?1). The differences in carbon stocks across land-use types are the primary consequence of variations in the vegetation biomass and the soil organic matter. Fine root carbon was a small fraction of carbon stocks in all land-use types. Most of the soil organic carbon and fine root carbon content was found in the upper 30-cm layer and decreased with soil depth. The aboveground carbon (ABGC): soil organic carbon (SOC): fine root carbon ratios (FRC), was 8:4:1, 4:5:1, and 3:37:1 for the forest, plantation and agricultural land, respectively. These results indicate that a relatively large proportion of the C loss is due to forest conversion to agricultural land.     

Valuing deaths or years of life lost? Economic benefits of avoided mortality from early heat warning systems

The study aims to explore the main drivers influencing the economic appraisal of heat warning systems by integrating epidemiological modelling and benefit-cost analysis. To shed insights on heat wave mortality valuation, we consider three valuation schemes: (i) a traditional one, where the value of a statistical life (VSL) is applied to both displaced and premature mortality; (ii) an intermediate one, with VSL applied for premature mortality and value of a life year (VOLY) for displaced mortality; and (iii) a conservative one, where both premature and displaced mortality are quantified in terms of loss of life expectancy, and then valued using the VOLY approach. When applying these three schemes to Madrid (Spain), we obtain a benefit-cost ratio varying from 12 to 3700. We find that the choice of the valuation scheme has the largest influence, whereas other parameters such as attributable risk, displaced mortality ratio, or the comprehensiveness and effectiveness of the heat warning system are less influential. The results raise the question of which is the most appropriate approach to value mortality in the context of heat waves, given that the lower bound estimate for the benefit-cost ratio (option iii using VOLY) is up to two orders of magnitude lower than the value based on the traditional VSL approach (option i). The choice of the valuation methodology has significant implications for public health authorities at the local and regional scale, which becomes highly relevant for locations where the application of the VOLY approach could lead to benefit-cost ratios significantly lower than 1. We propose that specific metrics for premature and displaced VOLYs should be developed for the context of heat waves. Until such values are available, we suggest testing the economic viability of heat warning systems under the three proposed valuation schemes (i–iii) and using values for VOLY commonly applied in air pollution as the health end points are similar. Lastly, periodical reassessment of heat alert plans should be performed by public health authorities to monitor their long-term viability and cost-effectiveness.     

Environmental Surveillance for Noroviruses in Selected South African Wastewaters 2015–2016: Emergence of the Novel GII.17

Norovirus (NoV) GII.4 is the predominant genotype associated with gastroenteritis pandemics and new strains emerge every 2–3 years. Between 2008 and 2011, environmental studies in South Africa (SA) reported NoVs in 63% of the sewage-polluted river water samples. The aim of this study was to assess whether wastewater samples could be used for routine surveillance of NoVs, including GII.4 variants. From April 2015 to March 2016, raw sewage and effluent water samples were collected monthly from five wastewater treatment plants in SA. A total of 108 samples were screened for NoV GI and GII using real-time RT-qPCR. Overall 72.2% (78/108) of samples tested positive for NoVs with 4.6% (5/108) GI, 31.5% (34/108) GII and 36.1% (39/108) GI + GII strains being detected. Norovirus concentrations ranged from 1.02 × 10² to 3.41 × 10⁶ genome copies/litre for GI and 5.00 × 10³ to 1.31 × 10⁶ genome copies/litre for GII. Sixteen NoV genotypes (GI.2, GI.3, GI.4, GI.5, GI.6, GII.2, GII.3, GII.4, GII.7, GII.9, GII.10, GII.14, GII.16, GII.17, GII.20, and GII.21) were identified. Norovirus GII.2 and GII.17 co-dominated and the majority of GII.17 strains clustered with the novel Kawasaki 2014 variant. Sewage surveillance facilitated detection of Kawasaki 2014 in SA, which to date has not been detected with surveillance in children with gastroenteritis <5 years of age. Combined surveillance in the clinical setting and environment appears to be a valuable strategy to monitor emergence of NoV strains in countries that lack NoV outbreak surveillance.