Hotter and sicker: External energy expenditure and the tangled evolutionary roots of anthropogenic climate change and chronic disease.

BACKGROUND: The dual crises of climate change and chronic, or non-communicable, disease (NCD) have emerged worldwide as the global economy has industrialized over the past two centuries. AIMS: In this synthesis I examine humans' dependence on external (non-metabolic) energy expenditure (e.g., fire, fossil fuels) as a common, root cause in these modern crises. MATERIALS AND METHODS: Using fossil, archeological, and historical evidence I show that the human lineage has been dependent on external energy sources since the control of fire in the Paleolithic. This reliance has grown with the development of agriculture, the use of wind- and water-power, and the most recently with industrialization and the transition to fossil fuels. To place industrialization in context I develop a Rule of 50, whereby individuals in industrialized economies consume roughly 50-times more external energy and manufacture roughly 50-times more material than do hunter-gatherers. RESULTS: Industrialization and mechanization, powered by fossil fuels, have promoted centralization and processing in food production, reduced physical activity, and increased air pollution (including greenhouse gas emissions). These developments have led in turn to NCD and climate change. DISCUSSION AND CONCLUSION: Climate change and NCD are connected both to one another and to our species' deep evolutionary dependence on external energy. Transitioning to carbon-free energy is essential to reduce the existential risks of climate change, but will likely have only modest effects on NCD. With the impending exhaustion of oil, coal, and natural gas reserves, developing replacements for fossil fuels is also critical to maintaining our species' external energy portfolio.

Reductions in NO2 burden over north equatorial Africa from decline in biomass burning in spite of growing fossil fuel use, 2005 to 2017.

Socioeconomic development in low- and middle-income countries has been accompanied by increased emissions of air pollutants, such as nitrogen oxides [NOx: nitrogen dioxide (NO2) + nitric oxide (NO)], which affect human health. In sub-Saharan Africa, fossil fuel combustion has nearly doubled since 2000. At the same time, landscape biomass burning-another important NOx source-has declined in north equatorial Africa, attributed to changes in climate and anthropogenic fire management. Here, we use satellite observations of tropospheric NO2 vertical column densities (VCDs) and burned area to identify NO2 trends and drivers over Africa. Across the northern ecosystems where biomass burning occurs-home to hundreds of millions of people-mean annual tropospheric NO2 VCDs decreased by 4.5% from 2005 through 2017 during the dry season of November through February. Reductions in burned area explained the majority of variation in NO2 VCDs, though changes in fossil fuel emissions also explained some variation. Over Africa's biomass burning regions, raising mean GDP density (USD⋅km-2) above its lowest levels is associated with lower NO2 VCDs during the dry season, suggesting that economic development mitigates net NO2 emissions during these highly polluted months. In contrast to the traditional notion that socioeconomic development increases air pollutant concentrations in low- and middle-income nations, our results suggest that countries in Africa's northern biomass-burning region are following a different pathway during the fire season, resulting in potential air quality benefits. However, these benefits may be lost with increasing fossil fuel use and are absent during the rainy season.

Detection of fossil-fuel CO2 plummet in China due to COVID-19 by observation at Hateruma.

The COVID-19 pandemic caused drastic reductions in carbon dioxide (CO2) emissions, but due to its large atmospheric reservoir and long lifetime, no detectable signal has been observed in the atmospheric CO2 growth rate. Using the variabilities in CO2 (ΔCO2) and methane (ΔCH4) observed at Hateruma Island, Japan during 1997-2020, we show a traceable CO2 emission reduction in China during February-March 2020. The monitoring station at Hateruma Island observes the outflow of Chinese emissions during winter and spring. A systematic increase in the ΔCO2/ΔCH4 ratio, governed by synoptic wind variability, well corroborated the increase in China's fossil-fuel CO2 (FFCO2) emissions during 1997-2019. However, the ΔCO2/ΔCH4 ratios showed significant decreases of 29 ± 11 and 16 ± 11 mol mol-1 in February and March 2020, respectively, relative to the 2011-2019 average of 131 ± 11 mol mol-1. By projecting these observed ΔCO2/ΔCH4 ratios on transport model simulations, we estimated reductions of 32 ± 12% and 19 ± 15% in the FFCO2 emissions in China for February and March 2020, respectively, compared to the expected emissions. Our data are consistent with the abrupt decrease in the economic activity in February, a slight recovery in March, and return to normal in April, which was calculated based on the COVID-19 lockdowns and mobility restriction datasets.

Modelling Economic Growth, Carbon Emissions, and Fossil Fuel Consumption in China: Cointegration and Multivariate Causality.

Most authors apply the Granger causality-VECM (vector error correction model), and Toda-Yamamoto procedures to investigate the relationships among fossil fuel consumption, CO2 emissions, and economic growth, though they ignore the group joint effects and nonlinear behaviour among the variables. In order to circumvent the limitations and bridge the gap in the literature, this paper combines cointegration and linear and nonlinear Granger causality in multivariate settings to investigate the long-run equilibrium, short-run impact, and dynamic causality relationships among economic growth, CO2 emissions, and fossil fuel consumption in China from 1965-2016. Using the combination of the newly developed econometric techniques, we obtain many novel empirical findings that are useful for policy makers. For example, cointegration and causality analysis imply that increasing CO2 emissions not only leads to immediate economic growth, but also future economic growth, both linearly and nonlinearly. In addition, the findings from cointegration and causality analysis in multivariate settings do not support the argument that reducing CO2 emissions and/or fossil fuel consumption does not lead to a slowdown in economic growth in China. The novel empirical findings are useful for policy makers in relation to fossil fuel consumption, CO2 emissions, and economic growth. Using the novel findings, governments can make better decisions regarding energy conservation and emission reductions policies without undermining the pace of economic growth in the long run.

How Energy Consumption and Pollutant Emissions Affect the Disparity of Public Health in Countries with High Fossil Energy Consumption.

Public health issues are a global focus, but recent research on the links between fossil energy consumption, pollutant emissions, and public health in different regions have presented inconsistent conclusions. In order to quantify the effect of fossil energy use and pollutant emissions on public health from the global perspective, this paper investigates 33 countries with high GDP and fossil energy consumption from 1995 to 2015 using a fixed effect model. Further, this paper utilizes heterogeneity analysis to characterize the disparity of countries with different features. Empirical results indicate that total fossil energy consumption is beneficial to the life expectancy of the population (LEP), but pollutant emissions (PM10 concentration and greenhouse gas scale) have a negative effect on LEP. Moreover, the heterogeneity test indicates that pollutant emissions lowers LEP in net energy importers more than in net energy exporters, and the effect of such emissions in low- and middle-income countries on public health is more harmful than that in high-income countries. These findings suggest that it is a greater priority for governments to strengthen the control of pollutant emissions through enhancing the efficiency of energy consumption, rather than by reducing its scale of use in low- and middle-income, and net energy importing countries. Additionally, governments also need to focus on the volatility of pollutant emissions in high-income countries with necessary control measures.

Is skewed income distribution good for environmental quality? A comparative analysis among selected BRICS countries.

A large number of studies have examined the linkage between income inequality and environmental quality at the individual country levels. This study attempts to examine the linkage between the two factors for the individual BRICS economies from a comparative perspective, which is scarce in the literature. It examines the selected countries (Brazil, India, China and South Africa) by endogenising the patterns of primary energy consumption (coal use and petroleum use), total primary energy consumption, economic growth, and urbanisation as key determining factors in CO2 emission function. The long-run results based on ARDL bounds testing revealed that income inequality leads to increase in CO2 emissions for Brazil, India and China, while the same factor leads to reduction in CO2 emissions for South Africa. However, it observes that while coal use increases CO2 emissions for India, China and South Africa, it has no effect for Brazil. In contrast, the use of petroleum products contributes to CO2 emissions in Brazil, while the use of the same surprisingly results in reduction of carbon emissions in South Africa, India and China. The findings suggest that given the significance of income inequality in environmental pollution, the policy makers in these emerging economies have to take into consideration the role of income inequality, while designing the energy policy to achieve environmental sustainability.

Energy consumption habits and human health nexus in Sub-Saharan Africa.

This study explores the impact of fossil fuels consumption, solid fuels consumption for cooking purposes, economic growth, and carbon emissions on human health, with a key emphasis on the occurrence of tuberculosis and the high mortality rate in Sub-Saharan Africa. For its practical insights, the study develops a system Generalized Method of Moment (GMM) for a panel of 34 middle- and lower-middle-income countries from 1995 to 2015. The study adopts a flexible methodology to tackle endogeneity in the variables. The robust results report that the use of solid fuels (charcoal, peat, wood, wood pellets, crop residues) for cooking purposes and the consumption of fossil fuels (oil, coal, gas) are significantly increasing the occurrence of tuberculosis. In addition, the results highlight that the consumption of both solid fuels and fossil fuels has adverse affects on life expectancy by increasing the mortality rate in Sub-Saharan African countries. Results report that renewable energy sources like sun, wind, and water (all with potential to prevent households from direct exposure to particulate matters and harmful gases) as well as a rise in economic growth serve as helping factors to control the occurrence of tuberculosis and to decrease the mortality rate. Moreover, the use of renewable energy sources is serving to lessen emissions of carbon dioxide, nitrogen dioxides, and particulate matters, which can ultimately decrease the mortality rate and extend the life expectancy in Sub-Saharan Africa.

Limited emission reductions from fuel subsidy removal except in energy-exporting regions.

Hopes are high that removing fossil fuel subsidies could help to mitigate climate change by discouraging inefficient energy consumption and levelling the playing field for renewable energy. In September 2016, the G20 countries re-affirmed their 2009 commitment (at the G20 Leaders' Summit) to phase out fossil fuel subsidies and many national governments are using today's low oil prices as an opportunity to do so. In practical terms, this means abandoning policies that decrease the price of fossil fuels and electricity generated from fossil fuels to below normal market prices. However, whether the removal of subsidies, even if implemented worldwide, would have a large impact on climate change mitigation has not been systematically explored. Here we show that removing fossil fuel subsidies would have an unexpectedly small impact on global energy demand and carbon dioxide emissions and would not increase renewable energy use by 2030. Subsidy removal would reduce the carbon price necessary to stabilize greenhouse gas concentration at 550 parts per million by only 2-12 per cent under low oil prices. Removing subsidies in most regions would deliver smaller emission reductions than the Paris Agreement (2015) climate pledges and in some regions global subsidy removal may actually lead to an increase in emissions, owing to either coal replacing subsidized oil and natural gas or natural-gas use shifting from subsidizing, energy-exporting regions to non-subsidizing, importing regions. Our results show that subsidy removal would result in the largest CO2 emission reductions in high-income oil- and gas-exporting regions, where the reductions would exceed the climate pledges of these regions and where subsidy removal would affect fewer people living below the poverty line than in lower-income regions.

A framework for energy use indicators and their reporting in life cycle assessment.

Energy use is a common impact category in life cycle assessment (LCA). Many different energy use indicators are used in LCA studies, accounting for energy use in different ways. Often, however, the choice behind which energy use indicator is applied is poorly described and motivated. To contribute to a more purposeful selection of energy use indicators and to ensure consistent and transparent reporting of energy use in LCA, a general framework for energy use indicator construction and reporting in LCA studies will be presented in this article. The framework differentiates between 1) renewable and nonrenewable energies, 2) primary and secondary energies, and 3) energy intended for energy purposes versus energy intended for material purposes. This framework is described both graphically and mathematically. Furthermore, the framework is illustrated through application to a number of energy use indicators that are frequently used in LCA studies: cumulative energy demand (CED), nonrenewable cumulative energy demand (NRCED), fossil energy use (FEU), primary fossil energy use (PFEU), and secondary energy use (SEU). To illustrate how the application of different energy use indicators may lead to different results, cradle-to-gate energy use of the bionanomaterial cellulose nanofibrils (CNF) is assessed using 5 different indicators and showing a factor of 3 differences between the highest and lowest results. The relevance of different energy use indicators to different actors and contexts will be discussed, and further developments of the framework are then suggested. Integr Environ Assess Manag 2016;12:429-436. © 2015 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of SETAC.

The geographical distribution of fossil fuels unused when limiting global warming to 2 °C.

Policy makers have generally agreed that the average global temperature rise caused by greenhouse gas emissions should not exceed 2 °C above the average global temperature of pre-industrial times. It has been estimated that to have at least a 50 per cent chance of keeping warming below 2 °C throughout the twenty-first century, the cumulative carbon emissions between 2011 and 2050 need to be limited to around 1,100 gigatonnes of carbon dioxide (Gt CO2). However, the greenhouse gas emissions contained in present estimates of global fossil fuel reserves are around three times higher than this, and so the unabated use of all current fossil fuel reserves is incompatible with a warming limit of 2 °C. Here we use a single integrated assessment model that contains estimates of the quantities, locations and nature of the world's oil, gas and coal reserves and resources, and which is shown to be consistent with a wide variety of modelling approaches with different assumptions, to explore the implications of this emissions limit for fossil fuel production in different regions. Our results suggest that, globally, a third of oil reserves, half of gas reserves and over 80 per cent of current coal reserves should remain unused from 2010 to 2050 in order to meet the target of 2 °C. We show that development of resources in the Arctic and any increase in unconventional oil production are incommensurate with efforts to limit average global warming to 2 °C. Our results show that policy makers' instincts to exploit rapidly and completely their territorial fossil fuels are, in aggregate, inconsistent with their commitments to this temperature limit. Implementation of this policy commitment would also render unnecessary continued substantial expenditure on fossil fuel exploration, because any new discoveries could not lead to increased aggregate production.

Sustainable emergency medical service systems: how much energy do we need?

OBJECTIVE: Modern emergency medical service (EMS) systems are vulnerable to both rising energy prices and potential energy shortages. Ensuring the sustainability of EMS systems requires an empirical understanding of the total energy requirements of EMS operations. This study was undertaken to determine the life cycle energy requirements of US EMS systems. METHODS: Input-output-based energy requirement multipliers for the US economy were applied to the annual budgets for a random sample of 19 metropolitan or county-wide EMS systems. Calculated per capita energy requirements of the EMS systems were used to estimate nationwide EMS energy requirements, and the leading energy sinks of the EMS supply chain were determined. RESULTS: Total US EMS-related energy requirements are estimated at 30 to 60 petajoules (10(15) J) annually. Direct ("scope 1") energy consumption, primarily in the form of vehicle fuels but also in the form of natural gas and heating oil, accounts for 49% of all EMS-related energy requirements. The energy supply chain-including system electricity consumption ("scope 2") as well as the upstream ("scope 3") energy required to generate and distribute liquid fuels and natural gas-accounts for 18% of EMS energy requirements. Scope 3 energy consumption in the materials supply chain accounts for 33% of EMS energy requirements. Vehicle purchases, leases, maintenance, and repair are the most energy-intense components of the non-energy EMS supply chain (23%), followed by medical supplies and equipment (21%). CONCLUSION: Although less energy intense than other aspects of the US healthcare system, ground EMS systems require substantial amounts of energy each year.

Investigation of carbon dioxide emission in China by primary component analysis.

Principal component analysis (PCA) is employed to investigate the relationship between CO2 emissions (COEs) stemming from fossil fuel burning and cement manufacturing and their affecting factors. Eight affecting factors, namely, Population (P), Urban Population (UP); the Output Values of Primary Industry (PIOV), Secondary Industry (SIOV), and Tertiary Industry (TIOV); and the Proportions of Primary Industry's Output Value (PPIOV), Secondary Industry's Output Value (PSIOV), and Tertiary Industry's Output Value (PTIOV), are chosen. PCA is employed to eliminate the multicollinearity of the affecting factors. Two principal components, which can explain 92.86% of the variance of the eight affecting factors, are chosen as variables in the regression analysis. Ordinary least square regression is used to estimate multiple linear regression models, in which COEs and the principal components serve as dependent and independent variables, respectively. The results are given in the following. (1) Theoretically, the carbon intensities of PIOV, SIOV, and TIOV are 2573.4693, 552.7036, and 606.0791 kt per one billion $, respectively. The incomplete statistical data, the different statistical standards, and the ideology of self sufficiency and peasantry appear to show that the carbon intensity of PIOV is higher than those of SIOV and TIOV in China. (2) PPIOV, PSIOV, and PTIOV influence the fluctuations of COE. The parameters of PPIOV, PSIOV, and PTIOV are -2706946.7564, 2557300.5450, and 3924767.9807 kt, respectively. As the economic structure of China is strongly tied to technology level, the period when PIOV plays the leading position is characterized by lagging technology and economic developing. Thus, the influence of PPIOV has a negative value. As the increase of PSIOV and PTIOV is always followed by technological innovation and economic development, PSIOV and PTIOV have the opposite influence. (3) The carbon intensities of P and UP are 1.1029 and 1.7862 kt per thousand people, respectively. The carbon intensity of the rural population can be inferred to be lower than 1.1029 kt per thousand people. The characteristics of poverty and the use of bio-energy in rural areas result in a carbon intensity of the rural population that is lower than that of P.

Behavioral economic analysis of demand for fuel in North America.

Emerging research clearly indicates that human behavior is contributing to climate change, notably, the use of fossil fuels as a form of energy for everyday behaviors. This dependence on oil in North America has led to assertions that the current level of demand is the social equivalent to an "addiction." The purpose of this study was to apply behavioral economic demand curves-a broadly applicable method of evaluating relative reinforcer efficacy in behavioral models of addiction-to North American oil consumption to examine whether such claims of oil addiction are warranted. Toward this end, we examined government data from the United States and Canada on per capita energy consumption for transportation and oil prices between 1995 and 2008. Our findings indicate that consumption either persisted or simultaneously increased despite sharp increases in oil price per barrel over the past decade.

Childhood illness in households using biomass fuels in India: secondary data analysis of nationally representative national family health surveys.

BACKGROUND: Half of the world's population uses solid fuels for energy and cooking, resulting in 1.5 million deaths annually, approximately one-third of which occur in India. Most deaths are linked to childhood pneumonia or acute lower respiratory tract infection (ALRI), conditions that are difficult to diagnose. The overall effect of biomass combustion on childhood illness is unclear. OBJECTIVES: To evaluate whether type of household fuel is associated with symptoms of ALRI (cough and difficulty breathing), diarrhea or fever in children aged 0-36 months. METHODS: We analyzed nationally representative samples of households with children aged 0-36 months from three national family health surveys conducted between 1992 and 2006 in India. Households were categorized as using low (liquid petroleum gas/electricity), medium (coal/kerosene) or high polluting fuel (predominantly wood/agricultural waste). Odds ratios adjusted for confounders for exposure to high and medium polluting fuel were compared with low polluting fuel (LPF). RESULTS: Use of high polluting fuel (HPF) in India changed minimally (82 to 78 %), although LPF use increased from 8% to 18%. HPF was consistently associated with ALRI [adjusted odds ratio (95% confidence interval) 1.48 (1.08-2.03) in 1992-3; 1.54 (1.33-1.77) in 1998-9; and 1.53 (1.21-1.93) in 2005-6). Fever was associated with HPF in the first two surveys but not in the third survey. Diarrhea was not consistently associated with HPF. CONCLUSIONS: There is an urgent need to increase the use of LPF or equivalent clean household fuel to reduce the burden of childhood illness associated with IAP in India.