mdh.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Air pollution related externality of district heating - A case study of Changping, Beijing
Academy of Chinese Energy Strategy, China University of Petroleum(Beijing), Beijing 102249, China.
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0002-6279-4446
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0003-4589-7045
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0001-8191-4901
Show others and affiliations
2019 (English)In: Energy Procedia, Elsevier Ltd , 2019, p. 4323-4330Conference paper, Published paper (Refereed)
Abstract [en]

Air pollution, caused by the use of fossil fuel, has been an environmental plague in China. It has a strong negative impact on human health. Since the costs of damage to health are not born by the pollution producers, these costs translate to social externality. Policies have an important role in optimizing resource allocation, such as penalizing the pollutant producers and incentivizing clean energy development. Among others, replacing coal with natural gas for heating represents an important example of air quality improvement measures. This paper presents a study that evaluates the health impacts from air pollution and the external cost of the "Coal-To-Gas" policy in district heating using Changping District (Beijing, China) as an example. Four scenarios were considered based on the historical and standard PM2.5 concentration. Results show that PM2.5 is responsible for causing an increase of 40% premature deaths in 2015 and that the monetary value of damage to health is higher than 1.2 billion CNY. In 2016 and 2017, the reported air quality was better than that in 2015. As a result, 13.3% and 26% premature deaths caused by air pollution were avoided in 2016 and 2017 compared to 2015 respectively. If the PM2.5 concentration level were to be reduced to national standard, the number of premature deaths attributed to PM2.5 could further decrease to 47.7% compared to 2015. Overall, the Coal-To-Gas policy in district heating reduces 0.017%~0.45% of premature death caused by air pollution each year. Air pollution reduction policies, which are expected to improve air quality together in the future, and the specific policy of Coal-To-Gas in district heating, could make great contribution to reducing the premature death caused by environmental problem and need more attention from the government and the public.

Place, publisher, year, edition, pages
Elsevier Ltd , 2019. p. 4323-4330
Keywords [en]
Coal-To-Gas, District heating, Externality, Health effect, PM2.5
National Category
Medical Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-43140DOI: 10.1016/j.egypro.2019.01.789ISI: 000471031704105Scopus ID: 2-s2.0-85063905381OAI: oai:DiVA.org:mdh-43140DiVA, id: diva2:1305759
Conference
10th International Conference on Applied Energy (ICAE2018), 22-25 August 2018, Hong Kong, China
Available from: 2019-04-18 Created: 2019-04-18 Last updated: 2019-07-11Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Li, HailongWallin, FredrikAvelin, Anders

Search in DiVA

By author/editor
Li, HailongWallin, FredrikAvelin, Anders
By organisation
Future Energy Center
Medical Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 4 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf