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International trade affects CO2 emissions by redistributing production activities to places where the emission intensities are different from the place of consumption. This study focuses on the net emission change as the result of the narrowing gap in emission intensities between the exporter and importer. Here we show that the relocation of production activities from the global North (developed countries) to the global South (developing countries) in the early 2000s leads to an increase in global emissions due to the higher emission intensities in China and India. The related net emissions are about one-third of the total emissions embodied in the South-North trade. However, the narrowing emission intensities between South-North and the changing trade patterns results in declining net emissions in trade in the past decade. The convergence of emission intensities in the global South alleviates concerns that increasing South-South trade would lead to increased carbon leakage and carbon emissions. The mitigation opportunity to green the supply chain lies in sectors such as electricity, mineral products and chemical products, but calls for a universal assessment of emission intensities and concerted effort. International trade redistributes production activities to regions with varying emission intensities. This study finds that the convergence of emission intensities between the global South - North and changes in trade patterns have resulted in declining net emissions in trade in the past decade. [ABSTRACT FROM AUTHOR]

Poverty, the quintessential denominator of a developing nation, has been traditionally defined against an arbitrary poverty line; individuals (or countries) below this line are deemed poor and those above it, not so! This has two pitfalls. First, absolute reliance on a single poverty line, based on basic food consumption, and not on total consumption distribution, is only a partial poverty index at best. Second, a single expense descriptor is an exogenous quantity that does not evolve from income-expenditure statistics. Using extensive income-expenditure statistics from India, here we show how a self-consistent endogenous poverty line can be derived from an agent-based stochastic model of market exchange, combining all expenditure modes (basic food, other food and non-food), whose parameters are probabilistically estimated using advanced Machine Learning tools. Our mathematical study establishes a consumption based poverty measure that combines labor, commodity, and asset market outcomes, delivering an excellent tool for economic policy formulation. Current inequality and market consumption modelling appears to be subjective. Here the authors combined all three axes of poverty modelling - Engel-Krishnakumar's microeconomics, Aoki-Chattopadhyay's mathematical precept and found that multivariate construction is a key component of economic data analysis, implying all modes of income and expenditure need to be considered to arrive at a proper weighted prediction of poverty. [ABSTRACT FROM AUTHOR]