Skip to main content
Log in

Investigation of indoor air quality in six office buildings in Chengdu, China based on field measurements

  • Research Article
  • Indoor/Outdoor Airflow and Air Quality
  • Published:
Building Simulation Aims and scope Submit manuscript

Abstract

Indoor air pollution is of a growing concern in China. The nation’s growing urban work force spends a majority of daily time in the office, thus office indoor air quality (IAQ) can be a key determinant of worker’s wellbeing. Yet, information on office IAQ in rapidly developing southwestern China remains scarce. To address this knowledge gap, we conducted an observational study based on continuous monitoring in six office buildings in Chengdu, Sichuan Province, to investigate the concentration and variability of indoor particulate matter (PM2.5) and carbon dioxide (CO2). Hourly indoor concentrations for PM2.5 and CO2 were 0–459 µg/m3 and 375–1102 ppm, respectively, with considerable intra-building and inter-building variability. Indoor PM2.5 exhibited temporal association with ambient PM2.5, while indoor CO2 exhibits both diurnal and weekly patterns. Four out of the six buildings showed a reduction in indoor PM2.5 during work hours, suggesting functional filtration systems. However, we observed daily accumulation of indoor CO2, suggesting ineffective ventilation. Indoor PM2.5 pollution could be of health concern as all buildings experienced days when indoor PM2.5 concentration was above WHO recommendation for at least 50% of the day. Multivariate linear model predicts that every 1 µg/m3 increase in ambient PM2.5 is associated with a 0.60 µg/m3 increase in indoor PM2.5. Building-specific multivariate models show work time, weekday, outdoor PM2.5 are significantly associated with indoor PM2.5 concentration. We hope findings from this study can inform future indoor pollution mitigation strategies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Abt E, Suh HH, Catalano P, Koutrakis P (2000). Relative contribution of outdoor and indoor particle sources to indoor concentrations. Environmental Science & Technology, 34: 3579–3587.

    Article  Google Scholar 

  • Al Horr Y, Arif M, Kaushik A, Mazroei A, Katafygiotou M, et al. (2016). Occupant productivity and office indoor environment quality: A review of the literature. Building and Environment, 105: 369–389.

    Article  Google Scholar 

  • Allen JG, MacNaughton P, Satish U, Santanam S, Vallarino J, et al. (2016). Associations of cognitive function scores with carbon dioxide, ventilation, and volatile organic compound exposures in office workers: A controlled exposure study of green and conventional office environments. Environmental Health Perspectives, 124: 805–812.

    Article  Google Scholar 

  • Bai L, Chen W, He Z, Sun S, Qin J (2020). Pollution characteristics, sources and health risk assessment of polycyclic aromatic hydrocarbons in PM2.5 in an office building in northern areas, China. Sustainable Cities and Society, 53: 101891.

    Article  Google Scholar 

  • Bluyssen PM, Oliveira Fernandes E, Groes L, Clausen G, Fanger PO, et al. (1996). European indoor air quality audit project in 56 office buildings. Indoor Air, 6: 221–238.

    Article  Google Scholar 

  • Bluyssen PM, Janssen S, van den Brink LH, de Kluizenaar Y (2011). Assessment of wellbeing in an indoor office environment. Building and Environment, 46: 2632–2640.

    Article  Google Scholar 

  • Burnett RT, Pope CAIII, Ezzati M, Olives C, Lim SS, et al. (2014). An integrated risk function for estimating the global burden of disease attributable to ambient fine particulate matter exposure. Environmental Health Perspectives, 122: 397–403.

    Article  Google Scholar 

  • Chen C, Zhao B (2011). Review of relationship between indoor and outdoor particles: I/O ratio, infiltration factor and penetration factor. Atmospheric Environment, 45: 275–288.

    Article  Google Scholar 

  • Cheng L, Li B, Cheng Q, Baldwin AN, Shang Y (2017). Investigations of indoor air quality of large department store buildings in China based on field measurements. Building and Environment, 118: 128–143.

    Article  Google Scholar 

  • Delfino RJ, Quintana PJE, Floro J, Gastañaga VM, Samimi BS, et al. (2004). Association of FEV1 in asthmatic children with personal and microenvironmental exposure to airborne particulate matter. Environmental Health Perspectives, 112: 932–941.

    Article  Google Scholar 

  • Fisk WJ, Rosenfeld AH (1997). Estimates of improved productivity and health from better indoor environments. Indoor Air, 7: 158–172.

    Article  Google Scholar 

  • GB 3095-2012 (2012). Ambient Air Quality Standard. Ministry of Environmental Protection. Available at http://www.codeofchina.com/standard/GB3095-2012XG1-2018.html. Accessed 4 Oct 2018.

  • GB/T 18883-2002 (2002). Indoor Air Quality Standard. Ministry of Health of China. Available at http://www.codeofchina.com/standard/GBT18883-2002.html. Accessed 4 Oct 2018.

  • Geng Y, Lin B, Yu J, Zhou H, Ji W, et al. (2019). Indoor environmental quality of green office buildings in China: Large-scale and long-term measurement. Building and Environment, 150: 266–280.

    Article  Google Scholar 

  • Hedge A (2009). Indoor environmental quality, health and productivity. In: Harris RG, Moore DP (eds), Indoor Work and Living Environments, Chapter 6. New York: Nova Science Publishers. pp. 247–262.

    Google Scholar 

  • Huang L, Pu Z, Li M, Sundell J (2015). Characterizing the indoor-outdoor relationship of fine particulate matter in non-heating season for urban residences in Beijing. PLoS ONE, 10: e0138559.

    Article  Google Scholar 

  • Jones AP (1999). Indoor air quality and health. Atmospheric Environment, 33: 4535–4564.

    Article  Google Scholar 

  • Liang C, Duan F, He K, Ma Y (2016). Review on recent progress in observations, source identifications and countermeasures of PM2.5. Environment International, 86: 150–170.

    Article  Google Scholar 

  • Lim JM, Jeong JH, Lee JH, Moon JH, Chung YS, et al. (2011). The analysis of PM2.5 and associated elements and their indoor/outdoor pollution status in an urban area. Indoor Air, 21: 145–155.

    Article  Google Scholar 

  • Lin B, Liu Y, Wang Z, Pei Z, Davies M (2016). Measured energy use and indoor environment quality in green office buildings in China. Energy and Buildings, 129: 9–18.

    Article  Google Scholar 

  • Lu F, Xu D, Cheng Y, Dong S, Guo C, et al. (2015). Systematic review and meta-analysis of the adverse health effects of ambient PM2.5 and PM10 pollution in the Chinese population. Environmental Research, 136: 196–204.

    Article  Google Scholar 

  • Maddalena R, Mendell MJ, Eliseeva K, Chan WR, Sullivan DP, et al. (2015). Effects of ventilation rate per person and per floor area on perceived air quality, sick building syndrome symptoms, and decision-making. Indoor Air, 25: 362–370.

    Article  Google Scholar 

  • Mendell MJ (1993). Non-specific symptoms in office workers: a review and summary of the epidemiologic literature. Indoor Air, 3: 227–236.

    Article  Google Scholar 

  • National Bureau of Statistics (2016). China Statistical Yearbook, 2006–2016. Available at http://www.stats.gov.cn/tjsj/ndsj/. Accessed 4 Oct 2018.

  • NOAA (2019). Recent Global CO2. National Oceanic and Atmospheric Administration. Available at https://www.esrl.noaa.gov/gmd/ccgg/trends/. Accessed 17 Aug 2019.

  • Pei Z, Lin B, Liu Y, Zhu Y (2015). Comparative study on the indoor environment quality of green office buildings in China with a long-term field measurement and investigation. Building and Environment, 84: 80–88.

    Article  Google Scholar 

  • Pinheiro J, Bates D, DebRoy S, Sarkar D, R Core Team (2018). nlme: Linear and Nonlinear Mixed Effects Models. R package version 3.1–137. Available at https://CRAN.R-project.org/package=nlme.

  • R Development Core Team (2008). R Version 3.5.1 R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Available at http://www.R-project.org.

    Google Scholar 

  • Ryan JA, Ulrich JM (2018). xts: extensible Time Series. R package version 0.11–1.

  • Sangiorgi G, Ferrero L, Ferrini BS, Lo Porto C, Perrone MG, et al. (2013). Indoor airborne particle sources and semi-volatile partitioning effect of outdoor fine PM in offices. Atmospheric Environment, 65: 205–214.

    Article  Google Scholar 

  • Satish U, Mendell MJ, Shekhar K, Hotchi T, Sullivan D, et al. (2012). Is CO2 an indoor pollutant? Direct effects of low-to-moderate CO2 Concentrations on human decision-making performance. Environmental Health Perspectives, 120:1671–1677.

    Article  Google Scholar 

  • Shi G, Yang F, Zhang L, Zhao T, Hu J (2019). Impact of atmospheric circulation and meteorological parameters on wintertime atmospheric extinction in Chengdu and Chongqing of southwest China during 2001–2016. Aerosol and Air Quality Research, 19: 1538–1554.

    Article  Google Scholar 

  • Shriram S, Ramamurthy K, Ramakrishnan S (2019). Effect of occupant-induced indoor CO2 concentration and bioeffluents on human physiology using a spirometric test. Building and Environment, 149: 58–67.

    Article  Google Scholar 

  • Steinle S, Reis S, Sabel CE, Semple S, Twigg MM, et al. (2015). Personal exposure monitoring of PM2.5 in indoor and outdoor microenvironments. Science of the Total Environment, 508: 383–394.

    Article  Google Scholar 

  • Szigeti T, Kertész Z, Dunster C, Kelly FJ, Záray G, Mihucz VG (2014). Exposure to PM2.5 in modern office buildings through elemental characterization and oxidative potential. Atmospheric Environment, 94: 44–52.

    Article  Google Scholar 

  • Tham KW (2016). Indoor air quality and its effects on humans—A review of challenges and developments in the last 30 years. Energy and Buildings, 130: 637–650.

    Article  Google Scholar 

  • Trapletti A, Hornik K (2018). tseries: Time series analysis and computational finance. R package version 0.10–45. Available at https://CRAN.R-project.org/package=xts

  • Wang F, Meng D, Li X, Tan J (2016). Indoor-outdoor relationships of PM2.5 in four residential dwellings in winter in the Yangtze River Delta, China. Environmental Pollution, 215: 280–289.

    Article  Google Scholar 

  • WHO (2006). WHO Air Quality Guidelines for Paticulate Matter, Ozone, Nitrogen Dioxide and Sulfur Dioxide, global update 2005. World Health Organization. Available at https://apps.who.int/iris/bitstream/handle/10665/69477/WHO_SDE_PHE_OEH_06.02_eng.pdf;sequence=1. Accessed 4 Oct 2018.

  • Wickham H (2009). ggplot2: Elegant Graphics for Data Analysis. New York: Springer-Verlag.

    Book  Google Scholar 

  • Wickham H (2017). tidyverse: Easily Install and Load the “Tidyverse”. R package version 1.2.1. Available at https://CRAN.R-project.org/package=tidyverse

  • Yu CKH, Li M, Chan V, Lai ACK (2014). Influence of mechanical ventilation system on indoor carbon dioxide and particulate matter concentration. Building and Environment, 76: 73–80.

    Article  Google Scholar 

  • Yuan Y, Luo Z, Liu J, Wang Y, Lin Y (2018). Health and economic benefits of building ventilation interventions for reducing indoor PM2.5 exposure from both indoor and outdoor origins in urban Beijing, China. Science of the Total Environment, 626: 546–554.

    Article  Google Scholar 

  • Zhang Y, Jia Y, Li M, Hou L (2017). Indoor PM2.5 and its morphology in a naturally ventilated office in Xi’an, China. Environmental Forensics, 18: 153–161.

    Article  Google Scholar 

  • Zhou Z, Liu Y, Yuan J, Zuo J, Chen G, Xu L, Rameezdeen R (2016). Indoor PM2.5 concentrations in residential buildings during a severely polluted winter: A case study in Tianjin, China. Renewable and Sustainable Energy Reviews, 64: 372–381.

    Article  Google Scholar 

Download references

Acknowledgements

This study is supported by the National Natural Science Foundation of China (41628102, 71742004), Sichuan University Campuses (SCU2015CC0001). The authors would like to thank representatives of PureLiving Environmental Solutions (Shanghai), Ltd. for providing the DST monitors and for assisting in setting up the monitors. Dr. Yu Zhan from Sichuan University provided ambient air quality monitoring and national weather data.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yang Qiu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Qiu, Y., Wang, Y. & Tang, Y. Investigation of indoor air quality in six office buildings in Chengdu, China based on field measurements. Build. Simul. 13, 1009–1020 (2020). https://doi.org/10.1007/s12273-020-0663-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12273-020-0663-9

Keywords

Navigation