Title: WSN-aided haze pollution governance: modelling public willingness based on structural equations

Authors: Jibo Chen; Yingxi Song; Guizhi Wang; Qi Liu

Addresses: School of Mathematics and Statistics, Nanjing University of Information Science and Technology, 219 Ningliu Road, Nanjing Jiangsu, 210044, China ' School of Mathematics and Statistics, Nanjing University of Information Science and Technology, 219 Ningliu Road, Nanjing Jiangsu, 210044, China ' School of Mathematics and Statistics, Nanjing University of Information Science and Technology, 219 Ningliu Road, Nanjing Jiangsu, 210044, China ' School of Computing, Edinburgh Napier University, 10 Colinton Road, Edinburgh, EH10 5DT, UK

Abstract: Wireless sensor networks (WSNs) have been well investigated and widely used in environmental surveillance, climate data collection, etc. However, research on statistical analysis and decision making aided by WSNs, especially in the area of environmental hazards and risk governance, are rarely presented. In this paper, common factors are extracted, among which the optimal model of haze governance willingness is designed using structural equation modelling (SEM). The relationships between the influencing factors of public haze governance willingness are then analysed. The results show that haze governance and willingness will be affected by the perception of haze risk, quality, measurements and economic expenditure factors. The life impact, travel inconvenience, maximum duration, and the suffering times from haze are the most basic factors affecting haze governance willingness. To achieve the governance of haze, haze measurement and monitoring via a WSN-based network with the collaboration from the public will be feasible and effective.

Keywords: haze pollution; wireless sensor networks-aided measurement; SEM; structural equation modelling; haze governance willingness; policy suggestions.

DOI: 10.1504/IJSNET.2019.097807

International Journal of Sensor Networks, 2019 Vol.29 No.2, pp.111 - 120

Received: 24 Jul 2018
Accepted: 24 Jul 2018
Published online: 11 Feb 2019 *

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