# A New Indicator to Assess Public Perception of Air Pollution Based on Complaint Data
## 5 Conclusions  
This paper put forward the air pollution perception index APPI according to the complaint density and complaint emotion intensity based on the air pollution complaint data. APPI uses the piecewise function model to assess the public's perception of air pollution comprehensively. The proposed APPI was then applied to the air pollution complaint data of Shandong Province from 2012 to 2017, and the results were also verified by word cloud analysis and POI data.  
(1) the statistical analysis and spatial distribution of air pollution complaint density and public complaint emotion intensity are not entirely consistent. The proposed APPI can more reasonably evaluate the public perception of air pollution.  
(2) The public perception of air pollution tends to the southwest of Shandong Province, and coastal cities are relatively weak.  
(3) The content of public complaints about air pollution mainly focuses on enterprises' exhaust emissions. Moreover, in inland cities with dense industrial enterprises, the value of APPI is higher, the public perception of air pollution is stronger.  
Given the above conclusions, some suggestions can be put forward for the relevant air quality management departments in this paper. Firstly, to maintain economic development. It is necessary to strengthen enterprises' supervision in the Southwest Shandong Province to meet the pollution discharge standards. Although industries and enterprises drive the city's economic development, they still have to balance the relationship between industrial development and air quality. Secondly, enhance the public's enthusiasm to participate in air pollution control and cooperate to optimize air quality.  
In conclusion, the air pollution perception index (APPI) proposed in this paper has high feasibility and practical application value and can be extended to other cities' air pollution perception evaluation. It can also test the effectiveness of government air pollution control to a certain extent and has significant supervision value for improving air quality. Moreover, for the objective monitoring station data, it is also a supplement of subjective data analysis. Because where there is pollution, the public will have dissatisfaction and expectation. The complaint data directly reflect the dissatisfaction of the people. The dissatisfaction of the people is an intuitive evaluation of air quality, which is the most convincing.  
However, it should be noted that the proposed indicator APPI in this paper is primarily meant for the public's historical perception. In future research, we need to use meteorological data and social media data for in-depth analysis to predict the public's perception of air pollution more reliably.  
**Author Contributions:** Conceptualization, Y.S.; methodology, Y.S.; software, Y.S.; validation, Y.S., and H.W.; formal analysis, Y.S. and Y.Z.; investigation, Y.S. and H.W.; resources, M.J.; data curation, M.J.; writing--original draft preparation, Y.S.; writing--review and editing, F.J.; visualization, H.W.; supervision, F.J.; project administration, M.J. and H.W.; funding acquisition, F.J. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work was supported by the Major Scientific and Technological Innovation Projects in Shandong Province (2019)ZZY020103) and a grant from State Key Laboratory of Resources and Environmental Information System.  
**Data Availability Statement:** The data presented in this study are available on request from the corresponding author. The data are not publicly available due to the data also forms part of an ongoing study.  
**Conflicts of Interest:** The authors declare no conflict of interest.