Abstract
Environmental deprivation is an issue influencing the urban wellbeing of a city. However, there are limitations to spatiotemporally monitoring the environmental deprivation. Thus, recent studies have introduced the concept of “Smart City” with the use of advanced technology for real-time environmental monitoring. In this regard, this study presents an improved Integrated Environmental Monitoring System (IIEMS) with the consideration on nine environmental parameters: temperature, relative humidity, PM2.5, PM10, CO, SO2, volatile organic compounds (VOCs), UV index, and noise. This system was comprised of a mobile unit and a server-based platform with nine highly accurate micro-sensors in-coupling into the mobile unit for estimating these environmental exposures. A calibration test using existing monitoring station data was conducted in order to evaluate the systematic errors. Two applications with the use of the new system were also conducted under different scenarios: pre- and post-typhoon days and in areas with higher and lower vegetation coverage. Linear regressions were applied to predict the changes in environmental quality after a typhoon and to estimate the difference in environmental exposures between urban roads and green spaces. The results show that environmental exposures interact with each other, while some exposures are also controlled by location. PM2.5 had the highest change after a typhoon with an estimated 8.0 μg/m³ decrease that was controlled by other environmental factors and geographical location. Sound level and temperature were significantly higher on urban roads than in urban parks. This study demonstrates the potential to use IIEMS for environmental quality measurements under the greater framework of a Smart City and for sustainability research.
Highlights
Urban inhabitants are more exposed to adverse environments with diversified deprivation, including extremes in humiture, air pollutants, ultra-violet (UV) radiation, and noise
Advanced concepts such as “volunteered geographic information” [29] and “Smart City” [30] have been proposed for increasing the potential number of sensors across districts/areas in order to improve the real-time monitoring of environment exposure and to enhance the protocols for sustainable planning
These integrated systems were incomprehensive and ineffective for monitoring the urban environment due to critical environmental factors such as volatile organic compounds (VOCs), UV, and noise, which were commonly excluded from the system design. Some function modules such as GPS or network connections were independent of the whole monitoring system and caused redundancy in system structure. To resolve these technical issues for building a better environmental monitoring network under the framework of a Smart City, this study aims to develop an innovative platform based on the former development of a Personal Integrated Environmental Monitoring System from Wong et al [39]
Summary
Urban inhabitants are more exposed to adverse environments with diversified deprivation, including extremes in humiture (a combination of temperature and humidity), air pollutants, ultra-violet (UV) radiation, and noise These extremes in environmental deprivation can influence human health; for example, extremes in temperature have increased morbidity and mortality risk [1,2] and air pollution from carbon monoxide (CO), sulfur dioxide (SO2), and particulate matter (PM) have been found to be associated with cardiovascular and respiratory issues [3,4,5,6,7,8,9]. Advanced concepts such as “volunteered geographic information” [29] and “Smart City” [30] have been proposed for increasing the potential number of sensors across districts/areas in order to improve the real-time monitoring of environment exposure and to enhance the protocols for sustainable planning
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