Abstract
Hydrofluorocarbons (HFCs) are strong greenhouse gases and regulated by the Montreal Protocol as substitutes of ozone depletion substances. Currently, Chinese HFC emissions keep increasing, and the inventory is only on a national or city level. A high-resolution gridded HFC emission inventory is needed to develop HFC reduction policy and phase-down schedule. We developed a method by integrating point sources with longitude and latitude information and area sources using the proxy factor to explore the distribution of R-410A [a mixture of HFC-32 (CH2F2) and HFC-125 (C2HF5)] emissions from the room air-conditioning sector on a 10 × 10 km2 grid scale. Variety of regression models (including the principal component analysis, multiple linear regressions, stepwise regressions, and linear regression), analysis scale (national level and provincial level), and data dimensions (the proxy factor and unit-area value) were tested. The gross domestic product was found as the optimal proxy factor and used to spatialize R-410A emissions at a high-resolution scale. Compared to the national-level analysis, model evaluation parameters were largely improved for the provincial-level regression analysis, including root-mean-square error (from 20.96 to 11.35), normalized mean bias (from 0.16 to − 0.01), normalized mean error (from 0.45 to 0.20), mean absolute error (from 11.27 to 4.97), correlation coefficient (from 0.91 to 0.97), and relative error (from 39% to 76%), suggesting a better performance for the provincial-level analysis. This study provides a cost-effective method to establish fine-resolution HFC inventory. Meanwhile, high-resolution emissions grid data could be further applied to implement site-specific management of low-carbon development.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability
The data and material that supporting the findings of this study are available from the corresponding author (Bo Yao) on request.
Abbreviations
- AAT:
-
Average annual temperature
- HDD18 & CDD26:
-
Heating degree days and cooling degree days
- CO2-eq:
-
Carbon dioxide-equivalent
- DMSP-OLS:
-
Defense Meteorological Satellite Program Operational Linescan System
- F-gas:
-
Fluorinated greenhouse gas
- GDP:
-
Gross domestic product
- GHG:
-
Greenhouse gas
- GWP:
-
Global warming potential
- HFC:
-
Hydrofluorocarbon
- R-410A:
-
Known as HFC-410A, a blend of HFC-32 (CH2F2) and HFC-125 (C2HF5)
- NTL:
-
Nighttime light
- ODS:
-
Ozone-depleting substance
- RAC:
-
Room air-conditioning
- RP:
-
Resident population
- \(E_{Inventory,i}\) :
-
R-410A emissions of the prefecture-level city i from emission inventory (kg)
- \(E_{model,i}\) :
-
R-410A emissions of the prefecture-level city i from the model prediction (kg)
- \(GDP_{grid,j}\) :
-
GDP value in each of the 10 × 10 km2 grid of the province or a province-level municipality j (1010 RMB)
- \(GDP_{province,j}\) :
-
Summed GDP value of the province or a province-level municipality j (1010 RMB)
- \(HFC - 410A_{grid,j}\) :
-
R-410A emissions in each of the 10 × 10 km2 grid of the province or a province-level municipality j (kg)
- \(HFC - 410A_{province,j}\) :
-
Total R-410A emissions of the province or a province-level municipality j (kg)
- \(N\) :
-
Number of prefecture-level cities, \(N\) = 330
- \(NMB\) :
-
Normalized mean bias
- \(NME\) :
-
Normalized mean error
- \(MAE\) :
-
Mean absolute error
- \(R\) :
-
Correlation coefficient
- \(RE\) :
-
Relative error
- \(RMSE\) :
-
Root-mean-square error
References
Cai, B. (2014). CO2 emissions in four urban boundaries of China—Case study of Chongqing. China Environmental Science, 34(9), 2439–2448.
Cai, B., Wang, J., Yang, S., Mao, X., & Cao, L. (2017). Carbon dioxide emissions from cities in China based on high resolution emission gridded data. Chinese Journal of Population Resources and Environment, 15(1), 58–70. https://doi.org/10.1080/10042857.2017.1286143
Cai, B., & Zhang, L. (2014). Urban CO2 emissions in China: Spatial boundary and performance comparison. Energy Policy, 66, 557–567. https://doi.org/10.1016/j.enpol.2013.10.072
Cao, Q., Wu, J., Tong, D., Zhang, X., Lu, Z., & Si, M. (2016). Drivers of regional agricultural land changes based on spatial autocorrelation in the Pearl River Delta. Resources Science, 38(4), 714–727. https://doi.org/10.18402/resci.2016.04.13
CAS Institute of Geographic Sciences and Natural Resources Research. (2021). Resource and Environment Science and Data Center. Retrieved November 7, 2019 from http://www.resdc.cn/.
Chen, W. X., Li, J. F., Zeng, J., Ran, D., & Yang, B. (2019). Spatial heterogeneity and formation mechanism of ecoenvironmental effect of land use change in China. Geographical Research, 38(9), 2173–2187.
China Ministry of Ecology and Environment. (2018). China Second Biennial Update Report on Climate Change. Retrieved September 15, 2021 from https://unfccc.int/sites/default/files/resource/China2BUR_English.pdf.
De Matteis, A. (2017). Decomposing the anthropogenic causes of climate change. Environment, Development and Sustainability, 21(1), 165–179. https://doi.org/10.1007/S10668-017-0028-4
Doll, C. N. H., & Pachauri, S. (2010). Estimating rural populations without access to electricity in develo** countries through night-time light satellite imagery. Energy Policy, 38(10), 5661–5670. https://doi.org/10.1016/j.enpol.2010.05.014
Fang, X., Ravishankara, A. R., Velders, G. J. M., Molina, M. J., Su, S., Zhang, J., et al. (2018). Changes in emissions of ozone-depleting substances from China due to implementation of the Montreal protocol. Environmental Science & Technology, 52(19), 11359–11366. https://doi.org/10.1021/acs.est.8b01280
Fang, X., Velders, G. J. M., Ravishankara, A. R., Molina, M. J., Hu, J., & Prinn, R. G. (2016). Hydrofluorocarbon (HFC) emissions in china: an inventory for 2005–2013 and projections to 2050. Environmental Science & Technology, 50(4), 2027–2034. https://doi.org/10.1021/acs.est.5b04376
Gao, Y., Gao, X., & Zhang, X. (2017). The 2 °C global temperature target and the evolution of the long-term goal of addressing climate change—From the United Nations Framework Convention on Climate Change to the Paris Agreement. Engineering, 3(2), 272–278. https://doi.org/10.1016/J.ENG.2017.01.022
IPCC. (2013). AR5 Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press. Cambridge. Retrieved June 29, 2021 from https://www.ipcc.ch/report/ar5/wg1/.
IPCC. (2019). 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories. Retrieved December 28, 2020 from https://www.ipcc.ch/report/2019-refinement-to-the-2006-ipcc-guidelines-for-national-greenhouse-gas-inventories/.
Keller, C. A., Hill, M., Vollmer, M. K., Henne, S., Brunner, D., Reimann, S., et al. (2012). European emissions of halogenated greenhouse gases inferred from atmospheric measurements. Environmental Science & Technology, 46(1), 217–225. https://doi.org/10.1021/es202453j
Letu, H., Hara, M., Yagi, H., Naoki, K., Tana, G., Nishio, F., & Shuhei, O. (2010). Estimating energy consumption from night-time DMPS/OLS imagery after correcting for saturation effects. International Journal of Remote Sensing, 31(16), 4443–4458. https://doi.org/10.1080/01431160903277464
Li, Y. F. (1999). Global gridded technical hexachlorocyclohexane usage inventories using a global cropland as a surrogate. Journal of Geophysical Research: Atmospheres, 104(D19), 23785–23797. https://doi.org/10.1029/1999JD900448
Li, Y. F. (2001). Toxaphene in the United States: 1. Usage gridding. Journal of Geophysical Research: Atmospheres, 106(16), 17919–17927. https://doi.org/10.1029/2000JD900824
Li, Y. F., Scholtz, M. T., & van Heyst, B. J. (2000). Global gridded emission inventories of α-hexachlorocyclohexane. Journal of Geophysical Research: Atmospheres, 105(D5), 6621–6632. https://doi.org/10.1029/1999JD901081
Liu, B. (2017). Analysis of occupant window and air-conditioner behaviour on building’s energy consumption. Retrieved January 17, 2020 from http://cdmd.cnki.com.cn/Article/CDMD-10016-1017169677.htm (in Chinese with English Abstract).
Liu, L., Dou, Y., Yao, B., Bie, P., Wang, L., Peng, M., & Hu, J. (2019). Historical and projected HFC-410A emission from room air conditioning sector in China. Atmospheric Environment, 212, 194–200. https://doi.org/10.1016/j.atmosenv.2019.05.022
Liu, M., Yan, L., Li, J., Xu, Z., & Du, S. (2020). Analysis of operation schedule of room air conditioners in Chongqing based on data monitoring platform. Heating Ventilating & Air Conditioning. Retrieved January 17, 2020 from http://cdmd.cnki.com.cn/Article/CDMD-10611-1018853908.htm (in Chinese with English Abstract).
Liu, X., Zhu, X., Pan, Y., Ma, Y., Li, T., & Chen, S. (2015). Map** population distribution by integrating night-time light satellite imagery and land-cover data. In International geoscience and remote sensing symposium (IGARSS) (Vol. 2015-November, pp. 2186–2189). Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/IGARSS.2015.7326238
Ma, T., Zhou, C., Pei, T., Haynie, S., & Fan, J. (2012). Quantitative estimation of urbanization dynamics using time series of DMSP/OLS nighttime light data: A comparative case study from China’s cities. Remote Sensing of Environment, 124, 99–107. https://doi.org/10.1016/j.rse.2012.04.018
Oda, T., & Maksyutov, S. (2011). A very high-resolution (1 km × 1 km) global fossil fuel CO2 emission inventory derived using a point source database and satellite observations of nighttime lights. Atmospheric Chemistry and Physics, 11(2), 543–556. https://doi.org/10.5194/acp-11-543-2011
Olivier, J. G., Schure, K. M., & Peters, J. A. H. W. (2018). Trends in global CO2 and total greenhouse gas emissions: 2018 report. PBL Netherlands Environmental Assessment Agency. Retrieved November 7, 2019 from https://www.pbl.nl/en/publications/trends-in-global-co2-and-total-greenhouse-gas-emissions-2018-report.
Stanley, K. M., Say, D., Mühle, J., Harth, C. M., Krummel, P. B., Young, D., O’Doherty, S. J., Salameh, P. K., Simmonds, P. G., Weiss, R. F., & Prinn, R. G. (2020). Increase in global emissions of HFC-23 despite near-total expected reductions. Nature Communications, 11(1), 1–6. https://doi.org/10.1038/s41467-019-13899-4
Stohl, A., Kim, J., Li, S., O’Doherty, S., Mühle, J., Salameh, P. K., Saito, T., Vollmer, M. K., Wan, D., Weiss, R. F., & Yao, B. (2010). Hydrochlorofluorocarbon and hydrofluorocarbon emissions in East Asia determined by inverse modeling. Atmospheric Chemistry and Physics, 10(8), 3545–3560. https://doi.org/10.5194/acp-10-3545-2010
Su, S., Fang, X., Li, L., Wu, J., Zhang, J., Xu, W., & Hu, J. (2015). HFC-134a emissions from mobile air conditioning in China from 1995 to 2030. Atmospheric Environment, 102, 122–129. https://doi.org/10.1016/j.atmosenv.2014.11.057
The Hot Spot Grid Work Promotion Office of Cangzhou City. (2019). The integration between the technology and grid management: taking the atmospheric hot grid management in Cangzhou City as an example. Environment and Sustainable Development, 44(2), 53–56. https://doi.org/10.19758/j.cnki.issn1673-288x.201902053 (in Chinese).
U.S. EIA. (2021). Degree days. Retrieved April 17, 2021 from https://www.eia.gov/energyexplained/units-and-calculators/degree-days.php.
UNEP. (2016). The Kigali Amendment (2016): The amendment to the Montreal Protocol agreed by the Twenty-Eighth Meeting of the Parties. Kigali. Retrieved November 18, 2019 from https://ozone.unep.org/treaties/montreal-protocol/amendments/kigali-amendment-2016-amendment-montreal-protocol-agreed.
UNFCCC. (2015). What is the Paris Agreement? Retrieved November 7, 2019 from https://unfccc.int/process-and-meetings/the-paris-agreement/what-is-the-paris-agreement.
US EPA. (2021). Inventory of U.S. Greenhouse Gas Emissions and Sinks. Retrieved November 7, 2019 from https://www.epa.gov/ghgemissions/inventory-us-greenhouse-gas-emissions-and-sinks.
Velders, G. J. M., Fahey, D. W., Daniel, J. S., Andersen, S. O., & McFarland, M. (2015). Future atmospheric abundances and climate forcings from scenarios of global and regional hydrofluorocarbon (HFC) emissions. Atmospheric Environment, 123, 200–209. https://doi.org/10.1016/j.atmosenv.2015.10.071
Velders, G. J. M., Fahey, D. W., Daniel, J. S., McFarland, M., & Andersen, S. O. (2009). The large contribution of projected HFC emissions to future climate forcing. Proceedings of the National Academy of Sciences of the United States of America, 106(27), 10949–10954. https://doi.org/10.1073/pnas.0902817106
Vollmer, M. K., Zhou, L. X., Greally, B. R., Henne, S., Yao, B., Reimann, S., et al. (2009). Emissions of ozone-depleting halocarbons from China. Geophysical Research Letters, 36(15), L15823. https://doi.org/10.1029/2009GL038659
Wan, D., Xu, J., Zhang, J., Tong, X., & Hu, J. (2009). Historical and projected emissions of major halocarbons in China. Atmospheric Environment, 43(36), 5822–5829. https://doi.org/10.1016/j.atmosenv.2009.07.052
Wang, J., Cai, B., Cao, D., Liu, L., Zhou, Y., Zhang, Z., & Xue, W. (2014). China 10km carbon dioxide emissions grid dataset and spatial characteristic analysis. China Environmental Science, 34(1), 1–6.
Wang, Z., Fang, X., Li, L., Bie, P., Li, Z., Hu, J., et al. (2016). Historical and projected emissions of HCFC-22 and HFC-410A from China’s room air conditioning sector. Atmospheric Environment, 132, 30–35. https://doi.org/10.1016/j.atmosenv.2016.02.029
World Meteorological Organization. (2018). Executive Summary: Scientific Assessment of Ozone Depletion: 2018, Global Ozone Research and Monitoring Project–Report. Geneva, Switzerland. Retrieved November 7, 2019 from https://www.esrl.noaa.gov/csd/assessments/ozone/2018/executivesummary/.
Xu, E. (2017a). Spatial variation in drivers of karst rocky desertification based on geographically weighted regression model. Resources Science, 39(10), 1975–1988. https://doi.org/10.18402/resci.2017.10.16
Xu, X. (2017b). China GDP spatial distribution kilometer grid dataset. Resource and Environment Data Cloud Platform, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. https://doi.org/10.12078/2017121102
Xu, X., & Liu, L. (2014). 1 km grid GDP data of China (2005, 2010). Acta Geographica Sinica, 69(s1), 45–48.
Yao, B., Fang, X., Vollmer, M. K., Reimann, S., Chen, L., Fang, S., & Prinn, R. G. (2019). China’s hydrofluorocarbon emissions for 2011–2017 inferred from atmospheric measurements. Environmental Science & Technology Letters, 6(8), 479–486. https://doi.org/10.1021/acs.estlett.9b00319
Yilmaz, V., & Can, Y. (2019). Impact of knowledge, concern and awareness about global warming and global climatic change on environmental behavior. Environment, Development and Sustainability, 22(7), 6245–6260. https://doi.org/10.1007/S10668-019-00475-5
Zeng, C., Zhou, Y., Wang, S., Yan, F., & Zhao, Q. (2011). Population spatialization in China based on night-time imagery and land use data. International Journal of Remote Sensing, 32(24), 9599–9620. https://doi.org/10.1080/01431161.2011.569581
Zhao, S. (2018). Analysis and enlightenment on atmospheric hot grid construction in **g-**-Ji Region. Journal of EMCC, 28(05), 67–69. https://doi.org/10.13358/j.issn.1008-813x.2018.0825.03 (in Chinese).
Zhuo, L., Ichinose, T., Zheng, J., Chen, J., Shi, P. J., & Li, X. (2009). Modelling the population density of China at the pixel level based on DMSP/OLS non-radiance-calibrated night-time light images. International Journal of Remote Sensing, 30(4), 1003–1018. https://doi.org/10.1080/01431160802430693
Acknowledgements
This work was supported by the National Key R&D Program of China (Grant No. 2019YFC0214502) and the National Natural Science Foundation of China (Grant No. 72074154 and No. 72174125).
Author information
Authors and Affiliations
Contributions
PW and LZ performed research, analyzed data, and wrote the paper; BY, YZ, and BC designed research, performed research and provided the part on policy implication; HL and ZX organized the literature review; HY, YD, PW, LL and YR provided and verified the data; LP, LC, XB, and YL organized and formatted the paper.
Corresponding authors
Ethics declarations
Conflict of interest
All authors declare that they have no conflict of interest or financial conflicts to disclose in the outcome of this study.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Wu, P., Zhang, L., Yao, B. et al. Spatialization of Chinese R-410A emissions from the room air-conditioning sector. Environ Dev Sustain 25, 5263–5281 (2023). https://doi.org/10.1007/s10668-022-02264-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10668-022-02264-z