Probabilistic population forecasting: Short to very long-term

Global population: from Super-Malthus behavior to Doomsday criticality

The report discusses global population changes from the Holocene beginning to 2023, via two Super Malthus (SM) scaling equations. SM-1 is the empowered exponential dependence: P t = P 0 e x p ± t / τ β , and SM-2 is the Malthus-type relation with the time-dependent growth rate r ( t ) or relaxation time τ ( t ) = 1 / r ( t ) : P t = P 0 e x p r t × t = P 0 e x p τ t / t . Population data from a few sources were numerically filtered to obtain a 'smooth' dataset, allowing the distortions-sensitive and derivative-based analysis. The test recalling SM-1 equation revealed the essential transition near the year 1970 (population: ~ 3 billion): from the compressed exponential behavior ( β > 1 ) to the stretched exponential one ( β < 1 ). For SM-2 dependence, linear changes of τ T during the Industrial Revolutions period, since ~ 1700, led to the constrained critical behavior P t = P 0 e x p b ' t / T C - t , whereT C ≈ 2216 is the extrapolated year of the infinite population. The link to the 'hyperbolic' von Foerster Doomsday equation is shown. Results are discussed in the context of complex systems physics, the Weibull distribution in extreme value theory, and significant historic and prehistoric issues revealed by the distortions-sensitive analysis.

Long-term population projections: Scenarios of low or rebounding fertility

The size of the human population is projected to peak in the 21st century. But quantitative projections past 2100 are rare, and none quantify the possibility of a rebound from low fertility to replacement-level fertility. Moreover, the most recent long-term deterministic projections were published a decade ago; since then there has been further global fertility decline. Here we provide updated long-term cohort-component population projections and extend the set of scenarios in the literature to include scenarios in which future fertility (a) stays below replacement or (b) recovers and increases. We also characterize old-age dependency ratios. We show that any stable, long-run size of the world population would persistently depend on when an increase towards replacement fertility begins. Without such an increase, the 400-year span when more than 2 billion people were alive would be a brief spike in history. Indeed, four-fifths of all births-past, present, and future-would have already happened.

Surface Functionalization of Sugarcane-Bagasse-Derived Cellulose Nanocrystal for Pickering Emulsion Gel: Microstructural Properties and Stability Efficiency

An environmentally friendly Pickering stabilizer was developed by upcycling sugarcane bagasse (SCB) into a cellulose nanocrystal (CNC), which was subjected to surface modification by using quaternary ammonium compound to enhance its amphiphilic characteristics. The changes in microstructural properties of modified cellulose nanocrystal (m-CNC), such as surface functional group, thermal stability, surface morphology, elemental composition, and particle size distribution were investigated. Results indicated the success of quaternary ammonium compound grafting with the presence of a trimethyl-alkyl chain on the cellulose structure, while the m-CNC preserves the needle-like nanoparticles in length of ~534 nm and width of ~20 nm. The colloidal profile of m-CNC-stabilized oil-water emulsion gels with different concentrations of m-CNC (1-5 wt%), and oil:water (O:W) ratios (3:7, 5:5, 7:3) were examined. The emulsion gel stability study indicated that the optimal concentration of m-CNC (3 wt%) was able to stabilize all the emulsion gels at different O:W ratios with an emulsion index of >80% for 3 months. It is the minimum concentration of m-CNC to form a robust colloidal network around the small oil droplets, leading to the formation of stable emulsion gels. The emulsion gel with O:W ratio (3:7) with 3 wt% of m-CNC rendered the best m-CNC-oil-droplets dispersion. The m-CNC effectively retained the size of oil droplets (<10 μm for 3 months storage) against coalescence and creaming by creating a steric barrier between the two immiscible phases. Furthermore, the emulsion gel exhibited the highest viscosity and storage modulus which was able to prevent creaming or sedimentation of the emulsion gels.

The Social Cost of Ozone-Related Mortality Impacts From Methane Emissions

Atmospheric methane directly affects surface temperatures and indirectly affects ozone, impacting human welfare, the economy, and environment. The social cost of methane (SC-CH4) metric estimates the costs associated with an additional marginal metric ton of emissions. Current SC-CH4 estimates do not consider the indirect impacts associated with ozone production from changes in methane. We use global model simulations and a new BenMAP webtool to estimate respiratory-related deaths associated with increases in ozone from a pulse of methane emissions in 2020. By using an approach consistent with the current SC-CH4 framework, we monetize and discount annual damages back to present day values. We estimate that the methane-ozone mechanism is attributable to 760 (95% CI: 330-1200) respiratory-related deaths per million metric tons of methane globally, for a global net present damage of $1800/mT (95% CI: $760-$2800/Mt CH4; 2% Ramsey discount rate); this would double the current SC-CH4 if included. These physical impacts are consistent with recent studies, but comparing direct costs is challenging. Economic damages are sensitive to uncertainties in the exposure and health risks associated with tropospheric ozone, assumptions about future projections of NOx emissions, socioeconomic conditions, and mortality rates, monetization parameters, and other factors. Our estimates are highly sensitive to uncertainties in ozone health risks. We also develop a reduced form model to test sensitivities to other parameters. The reduced form tool runs with a user-supplied emissions pulse, as well as socioeconomic and precursor projections, enabling future integration of the methane-ozone mechanism into the SC-CH4 modeling framework.

COVID-19 and excess mortality in Russia: Regional estimates of life expectancy losses in 2020 and excess deaths in 2021

Accurately counting the human cost of the COVID-19 at both the national and regional level is a policy priority. The Russian Federation currently reports one of the higher COVID-19 mortality rates in the world; but estimates of mortality differ significantly. Using a statistical method accounting for changes in the population age structure, we present the first national and regional estimates of excess mortality for 2021; calculations of excess mortality by age, gender, and urban/rural status for 2020; and mean remaining years of life expectancy lost at the regional level. We estimate that there were 351,158 excess deaths in 2020 and 678,022 in 2021 in the Russian Federation; and, in 2020, around 2.0 years of life expectancy lost. While the Russian Federation exhibits very high levels of excess mortality compared to other countries, there is a wide degree of regional variation: in 2021, excess deaths expressed as a percentage of expected deaths at the regional level range from 27% to 52%. Life expectancy loss is generally greater for males; while excess mortality is greater in urban areas. For Russia as whole, an average person who died due to the pandemic in 2020 would have otherwise lived for a further 14 more years (and as high as 18 years in some regions), disproving the widely held view that excess mortality during the pandemic period was concentrated among those with few years of life remaining-especially for females. At a regional level, less densely populated, more remote regions, rural regions appear to have fared better regarding excess mortality and life expectancy loss-however, a part of this differential could be owing to measurement issues. The calculations demonstrate more clearly the true degree of the human cost of the pandemic in the Russian Federation.

Comprehensive evidence implies a higher social cost of CO2

The social cost of carbon dioxide (SC-CO2) measures the monetized value of the damages to society caused by an incremental metric tonne of CO2 emissions and is a key metric informing climate policy. Used by governments and other decision-makers in benefit-cost analysis for over a decade, SC-CO2 estimates draw on climate science, economics, demography and other disciplines. However, a 2017 report by the US National Academies of Sciences, Engineering, and Medicine1 (NASEM) highlighted that current SC-CO2 estimates no longer reflect the latest research. The report provided a series of recommendations for improving the scientific basis, transparency and uncertainty characterization of SC-CO2 estimates. Here we show that improved probabilistic socioeconomic projections, climate models, damage functions, and discounting methods that collectively reflect theoretically consistent valuation of risk, substantially increase estimates of the SC-CO2. Our preferred mean SC-CO2 estimate is $185 per tonne of CO2 ($44-$413 per tCO2: 5%-95% range, 2020 US dollars) at a near-term risk-free discount rate of 2%, a value 3.6 times higher than the US government's current value of $51 per tCO2. Our estimates incorporate updated scientific understanding throughout all components of SC-CO2 estimation in the new open-source Greenhouse Gas Impact Value Estimator (GIVE) model, in a manner fully responsive to the near-term NASEM recommendations. Our higher SC-CO2 values, compared with estimates currently used in policy evaluation, substantially increase the estimated benefits of greenhouse gas mitigation and thereby increase the expected net benefits of more stringent climate policies.

Impact of Agroclimatic Variables on Proteogenomics in Sugar Cane (Saccharum spp.) Plant Productivity

Sugar cane (Saccharum spp. hybrids) is a major crop for sugar and renewable bioenergy worldwide, grown in arid and semiarid regions. China, the world's fourth-largest sugar producer after Brazil, India, and the European Union, all share ∼80% of the global production, and the remaining ∼20% of sugar comes from sugar beets, mostly grown in the temperate regions of the Northern Hemisphere, also used as a raw material in production of bioethanol for renewable energy. In view of carboxylation strategies, sugar cane qualifies as one of the best C₄ crop. It has dual CO₂ concentrating mechanisms located in its unique Krantz anatomy, having dimorphic chloroplasts located in mesophylls and bundle sheath cells for integrated operation of C₄ and C₃ carbon fixation cycles, regulated by enzymes to upgrade/sustain an ability for improved carbon assimilation to acquire an optimum carbon economy by producing enhanced plant biomass along with sugar yield under elevated temperature and strong irradiance with improved water-use efficiency. These superior intrinsic physiological carbon metabolisms encouraged us to reveal and recollect the facts for moving ahead with the molecular approaches to reveal the expression of proteogenomics linked with plant productivity under abiotic stress during its cultivation in specific agrizones globally.