RISK PERCEPTION TOWARDS ATMOSPHERIC ENVIRONMENT BASED ON TEXT DATA MINING OF PUBLIC OPINIONS
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摘要: 基于2015—2019年环境舆情信息,采用大数据挖掘与分析技术识别出公众对大气环境质量风险感知影响因素,建立了风险感知指标评价体系,分析了风险感知水平的时空变化特征。结果表明:1)影响公众风险感知的首要因素是个体健康担忧,其次是环境质量变化。2)公众风险感知水平具有显著的时空差异性;从时间上看,风险感知水平整体呈现波动上升趋势;从空间上看,风险感知水平呈现北方高南方低、东部高西部低的特征。3)河南、四川两省的风险感知水平在研究时间段内最高,且风险感知具有空间溢出效应。Abstract: According to the public opinions on air quality during the period of 2015—2019, big data mining and analysis techniques were used to identify the factors influencing the public’s risk perception, establish a risk perception indicator system, and investigate the temporal and spatial characteristics regarding risk perception level. The results showed that: 1) The primary factor affecting public risk perception was the worry of individual health impact, followed by the impact of environmental quality change. 2) The level of risk perception had significant temporal and spatial differences. It fluctuated and raised in the defined time period. From a spatial perspective, the level of risk perception was high in the north and low in the south, while high in the east and low in the west. 3) The risk perception level in Henan Province and Sichuan Province was the highest in the defined time period, and the risk perception had apparently spatial spillover effect.
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Key words:
- public opinions on environment /
- big data /
- data mining /
- risk perception /
- spatiotemporal distribution
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[1] HANKEY S, MARSHALL J D. Urban form, air pollution, and health[J]. Current Environmental Health Reports, 2017, 4(4):491-503. [2] WANG M C, ZHANG B B. Examining the impact of polycentric urban form on air pollution:evidence from China[J]. Environmental Science and Pollution Research, 2020, 27(34):43359-43371. [3] SONG C B, WU L, XIE Y C, et al. Air pollution in China:status and spatiotemporal variations[J]. Environmental Pollution, 2017, 227:334-347. [4] SLOVIC P. Perception of risk[J]. Science, 1987, 236(4799):280-285. [5] WWI J C, ZHAN W L, GUO X M, et al. Public attention to the great smog event:a case study of the 2013 smog event in Harbin, China[J]. Natural Hazards, 2017, 89(2):923-938. [6] 张海燕,葛怡,李凤英,等.环境风险感知的心理测量范式研究述评[J].自然灾害学报, 2010,19(1):78-83. [7] BRENKERT-SMITH H, DICKINSON K L, CHAMP P A, et al. Social amplification of wildfire risk:the role of social interactions and information sources[J]. Risk Analysis:An International Journal, 2013, 33(5):800-817. [8] LIU X S, VEDLITZ A, SHI L. Examining the determinants of public environmental concern:evidence from national public surveys[J]. Environmental Science&Policy, 2014, 39:77-94. [9] HUANG L, RAO C, KUIJP T J, et al. A comparison of individual exposure, perception, and acceptable levels of PM2.5 with air pollution policy objectives in China[J]. Environmental Research, 2017, 157:78-86. [10] PU S S, SHAO Z J, FANG M R, et al. Spatial distribution of the public's risk perception for air pollution:a nationwide study in China[J]. Science of The Total Environment, 2019, 655:454-462. [11] QIAN X J, XU G Z, LI L, et al. Knowledge and perceptions of air pollution in Ningbo, China[J]. BMC Public Health, 2016, 16(1):1138. [12] JIANG L, HILTUNEN E, HE X L, et al. A questionnaire case study to investigate public awareness of smog pollution in China's rural areas[J]. Sustainability, 2016, 8(11):1111. [13] RAJPER S A, ULLAH S, LI Z Q. Exposure to air pollution and self-reported effects on Chinese students:a case study of 13 megacities[J]. PLoS One, 2018, 13(3):e0194364. [14] 赵锐,闵雪峰,孟祥雨.基于SEM的城市地铁建设公众风险感知研究[J].工业安全与环保, 2019, 45(8):18-21. [15] ZHANG J J, MU Q. Air pollution and defensive expenditures:evidence from particulate-filtering facemasks[J]. Journal of Environmental Economics and Management, 2018, 92(11):517-536. [16] LIU T, HE G J, LAU A, et al. Avoidance behavior against air pollution:evidence from online search indices for anti-PM2.5 masks and air filters in Chinese cities[J]. Environmental Economics and Policy Studies, 2018, 20(2):325-363. [17] LU Y L, WANG Y, ZUO J, et al. Characteristics of public concern on haze in China and its relationship with air quality in urban areas[J]. Science of The Total Environment, 2018, 637/638:1597-1606. [18] DONG D X, XU X W, XU W, et al. The relationship between the actual level of air pollution and residents'concern about air pollution:evidence from Shanghai, China[J]. International Journal of Environmental Research and Public Health, 2019, 16(23):4784. [19] SUN X, YANG W T, SUN T, et al. Negative emotion under haze:an investigation based on the microblog and weather records of Tianjin, China[J]. International Journal of Environmental Research and Public Health, 2019, 16(1):86. [20] QIN Y, ZHU H J, et al. Run away?Air pollution and emigration interests in China[J]. Journal of Population Economics, 2018, 31(1):235-266. [21] KAHN M E, KOTCHEN M J. Business cycle effects on concern about change:the chilling effect of recession[J]. Climate Change Economics, 2011, 2(3):257-273. [22] 易善君,李君轶,李秀琴,等.基于微博大数据的空气质量与居民情感相关性对比研究:以西安市和上海市为例[J].干旱区资源与环境, 2017, 31(5):39-44. [23] 丁晓阳,王兰成.网络论坛文本特征词权重计算优化方法研究[J].情报理论与实践, 2021, 44(5):187-192. [24] ALAM S, YAO N M, DALIAN U T. Big data analytics, text mining and modern English language[J]. Journal of Grid Computing, 2019, 17(2):357-366. [25] WU K J, LIAO C J, TSENG M L, et al. Toward sustainability:using big data to explore the decisive attributes of supply chain risks and uncertainties[J]. Journal of Cleaner Production, 2017, 142:663-676. [26] 李勇,丛怡,贾佳.基于熵权法的汾渭平原城市空气质量模糊综合评价[J].环境工程, 2020, 38(8):236-243. [27] JOHNSON B B, DECIS R. Experience with urban air pollution in Paterson, New Jersey and implications for air Pollution communication[J]. Risk Analysis:An International Journal, 2012, 32(1):39-53. [28] PALMIOTTO M, FATTORE E, PAIANO V, et al. Influence of a municipal solid waste landfill in the surrounding environment:toxicological risk and odor nuisance effects[J]. Environment International, 2014, 68:16-24. [29] GUO Y, LI Y W. Online amplification of air pollution risk perception:the moderating role of affect in information[J]. Information, Communication&Society, 2018, 21(1):80-93. [30] 殷俊,胡登全,邓若伊.我国受众风险感知情况及对策研究:基于媒介使用的视角[J].现代传播(中国传媒大学学报), 2014, 36(3):41-45. [31] WANG Y G, YING Q, HU J L, et al. Spatial and temporal variations of six criteria air pollutants in 31 provincial capital cities in China during 2013-2014[J]. Environment International, 2014, 73:413-422. [32] YANG L X, CHENG S H, WANG X F, et al. Source identification and health impact of PM2.5 in a heavily polluted urban atmosphere in China[J]. Atmospheric Environment, 2013, 75:265-269. [33] 于振东,许为.汾渭平原焦化行业大气污染控制现状及控制对策[J].环境工程, 2021, 39(1):111-116. [34] 李名升,任晓霞,于洋,等.中国大陆城市PM2.5污染时空分布规律[J].中国环境科学, 2016, 36(3):641-650. [35] 于彩霞,石春娥,凌新锋,等.基于综合观测的中国中东部地区一次严重污染过程分析[J].环境科学学报, 2020, 40(7):2346-2355. [36] 史聆聆,李小敏,刘静,等.河南省大气污染现状及其控制对策分析[J].环境工程, 2015, 33(5):104-108. [37] 肖丹华,王式功,张莹,等.四川盆地城市群6种大气污染物的时空分布[J].兰州大学学报(自然科学版), 2018, 54(5):662-669. [38] 罗昕,支庭荣.中国网络社会治理研究报告(2019)[M].北京:社会科学文献出版社,2019. [39] 王东,范龙,王彬洁,等.四川2010-2019年突发环境事件时空分布特征分析[J].四川环境, 2021, 40(2):204-207. [40] 虢清伟,邴永鑫,陈思莉,等.我国突发环境事件演变态势、应对经验及防控建议[J].环境工程学报, 2021, 15(7):2223-2232. [41] 杨阳,王杰.情绪因素影响下的突发事件网络舆情演化研究[J].情报科学, 2020, 38(3):35-41,69.
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