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Mitigation and Adaptation Strategies for Global Change

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01-02-2022 | Original article

Does population aging aggravate air pollution in China?

Authors: Donglan Zha, Pan Liu, Hui Shi

Published in: Mitigation and Adaptation Strategies for Global Change | Issue 2/2022

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Abstract

China is experiencing rapid population aging and environmental pollution problems. There is a strong body of evidence supporting the notion that population aging may increase energy demand and aggravate related emissions. In this paper, we construct an extended KAYA model with aging variables. Drawing on panel data of 82 cities in China from 2014 to 2017, we aim to investigate whether population aging affects air pollution. Our estimates show that population aging has a significant negative impact on air quality, whereby a 1% change in the proportion of the resident population aged 65 years or above is associated with a 0.121% change in Air Quality Index in the same direction. The implication is that the increase in population aging aggravates air pollution in China in our study periods. By introducing a mediation effect, we further analyze the possible pathways of population aging with regard to air quality. The results show that population aging aggravates air pollution by increasing fossil fuel consumption and increasing the consumption of medical products. Promoting the development of energy-efficient products and services related to elderly people’s consumption may be necessary to mitigate the environmental impact of population aging in China.

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The pollutants involved in the evaluation are PM_2.5, PM₁₀, SO₂, NO₂, O₃, and CO. The ambient air quality is up to the standard if the concentration of the six pollutants reaches the standard. PM_2.5, PM₁₀, SO₂, and NO₂ were evaluated according to the annual average concentration, while O₃ and CO were evaluated according to the percentile concentration.

The correlation matrix shows that there is no multicollinearity among independent variables.

The AQI data in 2013 is missing; in order to ensure the continuity of data, the actual sample ranges from 2014 to 2017.

AQI was calculated according to the publication standard in Environmental Air Quality Index (AQI) Technical Regulation (Trial) (HJ633-2012). A total of 367 cities were monitored in total, due to the absence of statistical data; 82 cities were finally available.

Andor MA, Schmidt CM, Sommer S (2018) Climate change, population ageing and public spending: evidence on individual preferences. Ecol Econ 151:173–183. https://doi.org/10.1016/j.ecolecon.2018.05.003CrossRef

Bardazzi R, Pazienza MG (2017) Switch off the light, please! Energy consumption, aging population and consumption habits. Energy Econ 65:161–171. https://doi.org/10.1016/j.eneco.2017.04.025CrossRef

Brounen D, Kok N, Quigley JM (2012) Residential energy use and conservation: economics and demographics. Eur Econ Rev 56:931–945. https://doi.org/10.1016/j.euroecorev.2012.02.007CrossRef

Chen H, Jia B, Lau S (2008) Sustainable urban form for Chinese compact cities: challenges of a rapid urbanized economy. Habitat Int 32:28–40. https://doi.org/10.1016/j.habitatint.2007.06.005CrossRef

Estiri H, Zagheni E (2019) Age matters: Ageing and household energy demand in the United States. Energy Res Soc Sci 55:62–70. https://doi.org/10.1016/j.erss.2019.05.006CrossRef

Hamza N, Gilroy R (2011) The challenge to UK energy policy: an ageing population perspective on energy saving measures and consumption. Energy Policy 39:782–789. https://doi.org/10.1016/j.enpol.2010.10.052CrossRef

Hassan K, Salim R (2015) Population ageing, income growth and CO2 emission: empirical evidence from high income OECD countries. J Econ Stud 42:54–67. https://doi.org/10.1108/JES-04-2013-0046CrossRef

Kaya Y (1989) Impact of carbon dioxide emission control on GNP growth: interpretation of proposed scenarios. IPCC energy and industry subgroup, response strategies working group, Paris, 1989, 76

Kim J, Jang M, Shin D (2020a) Examining the role of population age structure upon residential electricity demand: a case from Korea. Sustainability 11:3914. https://doi.org/10.3390/su11143914CrossRef

Kim J, Lim H, Jo H-H (2020b) Do Aging and Low Fertility Reduce Carbon Emissions in Korea? Evidence from IPAT Augmented EKC Analysis. Int J Environ Res Public Health 17:2972. https://doi.org/10.3390/ijerph17082972CrossRef

Li S, Zhou C (2019) What are the impacts of demographic structure on CO2 emissions? A regional analysis in China via heterogeneous panel estimates. Sci Total Environ 650:2021–2031. https://doi.org/10.1016/j.scitotenv.2018.09.304CrossRef

Li K, Fang L, He L (2019) How population and energy price affect China’s environmental pollution? Energy Policy 129:386–396. https://doi.org/10.1016/j.enpol.2019.02.020CrossRef

Li B, Li T (2014) An empirical study of the environmental Kuznets curve for China’s air pollution: by GMM model and threshold effect with dynamic panel data. On Economic Problems 4:17–22. (in Chinese) https://doi.org/10.16011/j.cnki.jjwt.2014.04.001

Loi TS, Loo SL (2016) The impact of Singapore’s residential electricity conservation efforts and the way forward. Insights from the bounds testing approach. Energy Policy 98:735–743. https://doi.org/10.1016/j.enpol.2016.02.045CrossRef

Menz T, Kuhling J (2011) Population aging and environmental quality in OECD countries: evidence from sulfur dioxide emissions data. Popul Environ 33:55–79. https://doi.org/10.1007/s11111-011-0132-6CrossRef

Menz T, Welsch H (2012) Population aging and carbon emissions in OECD countries: accounting for life-cycle and cohort effects. Energy Econ 34:842–849. https://doi.org/10.1016/j.eneco.2011.07.016CrossRef

Ministry of Ecological Environment of the People’s Republic of China (2019) Bulletin on ecological and environmental conditions of China [N]. (2019-05-29). https://www.mee.gov.cn/hjzl/sthjzk/zghjzkgb/201905/P020190619587632630618.pdf

Poumanyvong P, Kaneko S (2010) Does urbanization lead to less energy use and lower CO₂ emissions? A cross-country analysis. Ecol Econ 70:434–444. https://doi.org/10.1016/j.ecolecon.2010.09.029CrossRef

Shi K, Wu L (2020) Forecasting air quality considering the socio-economic development in Xingtai. Sustain Cities Soc 61.https://doi.org/10.1016/j.scs.2020.102337

Sninate I, Bennana A (2020) Impact of population ageing on medical consumption: compulsory health insurance in Morocco. Pan Afr Med J 35:93. https://doi.org/10.11604/pamj.2020.35.93.20716CrossRef

The United Nations (2015) The world population prospects: 2015 revision [N]. (2015-07-29). https://www.un.org/en/development/desa/publications/world-population-prospects-2015-revision.html

Tobin J (1958) Estimation of relationships for limited dependent variables. Econometrica 26:24–36. https://doi.org/10.2307/1907382CrossRef

Tonn BE, Waidley G, Petrich C (2001) The ageing US population and environmental policy. J Environ Plann Manag 44:851–876. https://doi.org/10.1080/09640560120087606CrossRef

Wang S et al (2017a) The characteristics and drivers of fine particulate matter (PM2.5) distribution in China. J Clean Prod 142:1800–1809. https://doi.org/10.1016/j.jclepro.2016.11.104CrossRef

Wang Y et al (2017b) Panel estimation for the impacts of population-related factors on CO₂ emissions: a regional analysis in China. Ecol Ind 78:322–330. https://doi.org/10.1016/j.ecolind.2017.03.032CrossRef

Wang S, Li G, Fang C (2018) Urbanization, economic growth, energy consumption, and CO₂ emissions: empirical evidence from countries with different income levels. Renew Sustain Energy Rev 81:2144–2159. https://doi.org/10.1016/j.rser.2017.06.025CrossRef

Wei T, Zhu Q, Glomsrøda S (2018) How will demographic characteristics of the labor force matter for the global economy and carbon dioxide emissions? Ecol Econ 147:197–207. https://doi.org/10.1016/j.ecolecon.2018.01.017CrossRef

Wen Z, Ye B (2014) Analyses of mediating effects: the development of methods and models. Adv Psychol Sci 22:731–745. (in Chinese) https://doi.org/10.3724/SP.J.1042.2014.00731

Wen L, Li ZK (2019) Driving forces of national and regional CO₂ emissions in China combined IPAT-E and PLS-SEM model. Sci Total Environ 690:237–247. https://doi.org/10.1016/j.scitotenv.2019.06.370CrossRef

Yang Y, Deng YR, Chen FF (2018) Impact of population aging and industrial structure on CO₂ emissions and emissions trend prediction in China. Atmos Pollut Res 9:446–454. https://doi.org/10.1016/j.apr.2017.11.008CrossRef

Zha D, Zhao T, Kavuri AS, Wu F, Wang Q (2018) An event study analysis of price adjustment of refined oil and air quality in China. Environ Sci Pollut Res 25:236–246. https://doi.org/10.1007/s11356-018-3374-3CrossRef

Zhang C, Tan Z (2016) The relationships between population factors and China’s carbon emissions: does population aging matter? Renew Sustain Energy Rev 65:1018–1025. https://doi.org/10.1016/j.rser.2016.06.083CrossRef

Zhao J et al (2017) The influence of land intensive use and urbanization to air pollution: evidence from China. IOP Conf Ser: Earth Environ Sci 94:012139. https://doi.org/10.1088/1755-1315/94/1/012139CrossRef

Zhou Y, Liu Y (2016) Does population have a larger impact on carbon dioxide emissions than income? Evidence from a cross-regional panel analysis in China. Appl Energy 180:800–809. https://doi.org/10.1016/j.apenergy.2016.08.035CrossRef

Zhu Q, Peng X (2012) The impacts of population change on carbon emissions in China during 1978–2008. Environ Impact Assess Rev 36:1–8. https://doi.org/10.1016/j.eiar.2012.03.003CrossRef

Title: Does population aging aggravate air pollution in China?
Authors: Donglan Zha
Pan Liu
Hui Shi
Publication date: 01-02-2022
Publisher: Springer Netherlands
Published in: Mitigation and Adaptation Strategies for Global Change / Issue 2/2022
Print ISSN: 1381-2386
Electronic ISSN: 1573-1596
DOI: https://doi.org/10.1007/s11027-021-09993-y

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