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Climate change is a major issue across the globe. Therefore, carbon (C) assimilation and storage is the key management strategy for mitigating climate change. The present investigation was carried out in two riparian sites i.e., Maini and Machhli river of northern Chhattisgarh, India, through stratified random sampling. Results reveal that vegetation beside Maini river was represented by 22 species of tree, 17 species of saplings, 12 species of seedlings, 5 shrub species and 15 herb species and total density value was 1410–460,000 individuals/ha. The vegetation in Machhli river was represented by 14 species of tree, 15 species of sapling, 14 species of seedling, 10 shrub and herb species each and the total density value was 830–440,000 individuals/ha. The diversity indices were higher for tree and herb layer in Maini river while in Machhli river the diversity indices value were higher for sapling, seedling and shrub layer. Terminalia arjuna, Shorea robusta and Mangifera indica contributed maximum total biomass (58.23%) at Maini river. In Machhli river, 73% of total biomass was contributed by Terminalia arjuna, Leucana leucocephala and Ficus heterophylla. Higher biomass accumulation, C stock and CO2 mitigation were found in 30–50 cm girth class in both sites. The total C stock and CO2 mitigation ranged between 60.54–77.58 t/ha and 222.10–284.84 t/ha for both the sites, respectively. Results reveal significant contribution of riparian vegetation towards biomass accumulation, C storage and CO2 mitigation. Such study under tropical condition would help to formulate policy towards restoring degraded riparian vegetation and combating climate change. [ABSTRACT FROM AUTHOR]

Summary: This paper looks at the human health impacts from urban air pollution in India. Such pollution is especially harmful to poor people, so the co-benefits from global climate change policies in terms of reduced local air pollution can have positive equity impacts. Health impacts (mortality and morbidity) of PM10 pollution are quantified for different socio-economic groups in Delhi. The spatial PM10 concentration levels are overlaid with spatial socio-economic data. Improvement in air quality would result in bigger health benefits for the poor. Most measures that reduce PM10 pollutants also reduce CO2 emissions while simultaneously imposing more costs on the better-off. [ABSTRACT FROM AUTHOR]