Leiwen Jiang

Global demographic trends and future carbon emissions

Substantial changes in population size, age structure, and urbanization are expected in many parts of the world this century. Although such changes can affect energy use and greenhouse gas emissions, emissions scenario analyses have either left them out or treated them in a fragmentary or overly simplified manner. We carry out a comprehensive assessment of the implications of demographic change for global emissions of carbon dioxide. Using an energy–economic growth model that accounts for a range of demographic dynamics, we show that slowing population growth could provide 16–29% of the emissions reductions suggested to be necessary by 2050 to avoid dangerous climate change. We also find that aging and urbanization can substantially influence emissions in particular world regions.

Demographic change and carbon dioxide emissions

Relations between demographic change and emissions of the major greenhouse gas carbon dioxide (CO(2)) have been studied from different perspectives, but most projections of future emissions only partly take demographic influences into account. We review two types of evidence for how CO(2) emissions from the use of fossil fuels are affected by demographic factors such as population growth or decline, ageing, urbanisation, and changes in household size. First, empirical analyses of historical trends tend to show that CO(2) emissions from energy use respond almost proportionately to changes in population size and that ageing and urbanisation have less than proportional but statistically significant effects. Second, scenario analyses show that alternative population growth paths could have substantial effects on global emissions of CO(2) several decades from now, and that ageing and urbanisation can have important effects in particular world regions. These results imply that policies that slow population growth would probably also have climate-related benefits.

Internal consistency of demographic assumptions in the shared socioeconomic pathways

A new set of alternative socioeconomic scenarios for climate change researches—the shared socioeconomic pathways (SSPs)—includes for the first time a more comprehensive set of demographic conditions on population, urbanization, and education as the central scenario elements, along with other aspects of society, in order to facilitate better analyses of challenges to climate change mitigation and adaptation. However, it also raises a new question about the internal consistency of assumptions on different demographic and economic trends under each SSP. This paper examines whether the interactions between the demographic and economic factors implied by the assumptions in the SSP projections are consistent with the research literature, and whether they are consistently represented in the projection results. Our analysis shows that the interactions implied by the demographic assumptions in the SSPs are generally consistent with findings from the literature, and the majority of the assumed relationships are also evident in the projected trends. It also reveals some inconsistency issues, resulting mainly from the use of inconsistent definitions of regions and limitations in our understanding of future changes in the patterns of interactions at different stages of socioeconomic development. Finally, we offer recommendations on how to improve demographic assumptions in the extended SSPs, and how to use the projections of SSP central elements in climate change research.

Impact of climate change on heat-related mortality in Jiangsu Province, China ☆

A warming climate is anticipated to increase the future heat-related total mortality in urban areas. However, little evidence has been reported for cause-specific mortality or nonurban areas. Here we assessed the impact of climate change on heat-related total and cause-specific mortality in both urban and rural counties of Jiangsu Province, China, in the next five decades. To address the potential uncertainty in projecting future heat-related mortality, we applied localized urban- and nonurban-specific exposure response functions, six population projections including a no population change scenario and five Shared Socioeconomic Pathways (SSPs), and 42 temperature projections from 21 global-scale general circulation models and two Representative Concentration Pathways (RCPs). Results showed that projected warmer temperatures in 2016-2040 and 2041-2065 will lead to higher heat-related mortality for total non-accidental, cardiovascular, respiratory, stroke, ischemic heart disease (IHD), and chronic obstructive pulmonary disease (COPD) causes occurring annually during May to September in Jiangsu Province, China. Nonurban residents in Jiangsu will suffer from more excess heat-related cause-specific mortality in 2016-2065 than urban residents. Variations across climate models and RCPs dominated the uncertainty of heat-related mortality estimation whereas population size change only had limited influence. Our findings suggest that targeted climate change mitigation and adaptation measures should be taken in both urban and nonurban areas of Jiangsu Province. Specific public health interventions should be focused on the leading causes of death (stroke, IHD, and COPD), whose health burden will be amplified by a warming climate.

Women’s Education, Family Planning, or Both? Application of Multistate Demographic Projections in India

Is education the best contraceptive? Using the multistate human capital projection model, our analysis shows that the projected changes in India population vary depending on investments in education and helping women reduce unwanted fertility rates, that investments in both education and helping women in each education category—but particularly less educated women—meet their wanted fertility will have the largest impacts on India’s population projections, and that the impact from investment in reducing unwanted fertility will be much more immediate and significant than only investments in education. Our analysis also reveals that an increasing education transition rate in India will not only help to achieve a population age structure that is favorable for economic growth, but also result in a larger share of skilled labor force that help to achieve higher economic growth rate. More importantly, investment in girls’ education and achieving gender equality in education will be the most effective measure to increase India’s population education level and improve its overall values of human capital.

Plausible reductions in future population growth and implications for the environment

Bradshaw and Brook (1) conclude that a substantial slowing of global population growth is infeasible over this century short of drastic reductions in fertility, and therefore could not contribute much to lessening pressure on the environment. However, their methodology is too crude to produce credible results.

The Influence of Internal Migration on Exposure to Extreme Weather Events in Mexico

ABSTRACT Between 2005 and 2010, 6.3 million migrants (approximately 6% of the population) moved domestically within Mexico. These shifts have potential implications for exposure to natural disasters. To examine this relationship, we use census microdata in conjunction with information on natural disaster events. The populations exposed to extreme weather events are first calculated based on observed disasters and demographic change between 2005 and 2010. This is compared to a hypothetical scenario with no migration between 2005 and 2010. The results presented in this research note demonstrate that while migration has slightly decreased overall exposure within Mexico, this influence is highly localized in select areas, with internal migration increasing exposure in key urban destinations. This highlights the need to better understand the interacting roles of household-scale migratory decision making and economic/urban growth policy in climate change mitigation, and provides guidance on geographic regions to target for more detailed analysis.

Future ozone-related acute excess mortality under climate and population change scenarios in China: A modeling study

Background Climate change is likely to further worsen ozone pollution in already heavily polluted areas, leading to increased ozone-related health burdens. However, little evidence exists in China, the world’s largest greenhouse gas emitter and most populated country. As China is embracing an aging population with changing population size and falling age-standardized mortality rates, the potential impact of population change on ozone-related health burdens is unclear. Moreover, little is known about the seasonal variation of ozone-related health burdens under climate change. We aimed to assess near-term (mid-21st century) future annual and seasonal excess mortality from short-term exposure to ambient ozone in 104 Chinese cities under 2 climate and emission change scenarios and 6 population change scenarios. Methods and findings We collected historical ambient ozone observations, population change projections, and baseline mortality rates in 104 cities across China during April 27, 2013, to October 31, 2015 (2013–2015), which included approximately 13% of the total population of mainland China. Using historical ozone monitoring data, we performed bias correction and spatially downscaled future ozone projections at a coarse spatial resolution (2.0° × 2.5°) for the period April 27, 2053, to October 31, 2055 (2053–2055), from a global chemistry–climate model to a fine spatial resolution (0.25° × 0.25°) under 2 Intergovernmental Panel on Climate Change Representative Concentration Pathways (RCPs): RCP4.5, a moderate global warming and emission scenario where global warming is between 1.5°C and 2.0°C, and RCP8.5, a high global warming and emission scenario where global warming exceeds 2.0°C. We then estimated the future annual and seasonal ozone-related acute excess mortality attributable to both climate and population changes using cause-specific, age-group-specific, and season-specific concentration–response functions (CRFs). We used Monte Carlo simulations to obtain empirical confidence intervals (eCIs), quantifying the uncertainty in CRFs and the variability across ensemble members (i.e., 3 predictions of future climate and air quality from slightly different starting conditions) of the global model. Estimates of future changes in annual ozone-related mortality are sensitive to the choice of global warming and emission scenario, decreasing under RCP4.5 (−24.0%) due to declining ozone precursor emissions but increasing under RCP8.5 (10.7%) due to warming climate in 2053–2055 relative to 2013–2015. Higher ambient ozone occurs under the high global warming and emission scenario (RCP8.5), leading to an excess 1,476 (95% eCI: 898 to 2,977) non-accidental deaths per year in 2053–2055 relative to 2013–2015. Future ozone-related acute excess mortality from cardiovascular diseases was 5–8 times greater than that from respiratory diseases. Ozone concentrations increase by 15.1 parts per billion (10−9) in colder months (November to April), contributing to a net yearly increase of 22.3% (95% eCI: 7.7% to 35.4%) in ozone-related mortality under RCP8.5. An aging population, with the proportion of the population aged 65 years and above increased from 8% in 2010 to 24%–33% in 2050, will substantially amplify future ozone-related mortality, leading to a net increase of 23,838 to 78,560 deaths (110% to 363%). Our analysis was mainly limited by using a single global chemistry–climate model and the statistical downscaling approach to project ozone changes under climate change. Conclusions Our analysis shows increased future ozone-related acute excess mortality under the high global warming and emission scenario RCP8.5 for an aging population in China. Comparison with the lower global warming and emission scenario RCP4.5 suggests that climate change mitigation measures are needed to prevent a rising health burden from exposure to ambient ozone pollution in China.

Indirectly Estimating International Net Migration Flows by Age and Gender

Abstract Although data for the total number of international migrant flows is now available, no global dataset concerning demographic characteristics, such as the age and gender composition of migrant flows, exists. This article reports on the methods used to generate the CDM-IM dataset of age- and gender-specific profiles of bilateral net (not gross) migrant flows. The researchers employ raw data from the United Nations Global Migration Database and estimate net migrant flows by age and gender between two time points around the year 2000, accounting for various demographic processes (fertility, mortality). The dataset contains information on 3,713 net migrant flows. Validation analyses against existing datasets and the historical, geopolitical context demonstrate that the CDM-IM dataset is of reasonably high quality.

An update of Indonesian household-level income and consumption patterns as an input to the iPETS model

The integrated Population-Economy-Technology-Science (iPETS) model is a global integrated assessment model developed and used by NCAR’s Integrated Assessment Modeling (IAM) group to understand how key aspects of society may evolve in the future and how they might interact with a changing climate. Income and consumption patterns of households by demographic characteristics are used to calibrate parameters in iPETS for each of nine world regions. These income and consumption patterns are obtained from analysis of country-specific socioeconomic household surveys. iPETS parameters based on these results are combined with demographic projections of expected changes in population size, age structure, education, household structure, and urbanization to improve economic, energy, land use, and emissions projections. Because household income and consumption patterns can change substantially over time, particularly in developing countries, periodic updates of the household-level data used in iPETS are needed. This paper describes an updated analysis of Indonesian household data, based on the 2013 SUSENAS National Social Economic Survey. This analysis further classified households by education level, in addition to previously analyzed demographic characteristics, and also differentiated results by income deciles and access to electricity. Results indicated that higher incomes and expenditures were associated with higher levels of education, lower household sizes, residence in urban areas, and access to electricity. A comparison between 2002 and 2013 SUSENAS data showed that the share of expenditures on food decreased during this time, while the share spent on other goods and services and particularly on transportation increased, consistent with changes commonly observed in developing countries. Acknowledgments The authors would like to acknowledge University of Colorado students Michely Tenardi and Nikolas Setiawan for their work translating the 2013 Indonesia dataset, and NCAR senior scientist Brian O’Neill for his review of this paper and thoughtful feedback. This work was supported in part by the DOE Office of Science program on Integrated Assessment of Global Climate Change, award DE-SC0006704. The National Center for Atmospheric Research (NCAR) is sponsored by the U.S. National Science Foundation (NSF).