This study presents the development and evaluation of a next generation air monitoring system with both laboratory and field tests. A multi-parameter algorithm was used to correct for the impact of environmental conditions on the electrochemical sensors for carbon monoxide (CO) and nitrogen dioxide (NO 2 ) pollutants. The field evaluation in an urban roadside environment in comparison to designated monitors showed good agreement with measurement error within 5% of the pollutant concentrations. Multiple sets of the developed system were then deployed in the Hong Kong Marathon 2015 forming a sensor-based network along the marathon route. Real-time air pollution concentration data were wirelessly transmitted and the Air Quality Health Index (AQHI) for the Green Marathon was calculated, which were broadcast to the public on an hourly basis. The route-specific sensor network showed somewhat different pollutant patterns than routine air monitoring, indicating the immediate impact of traffic control during the marathon on the roadside air quality. The study is one of the first applications of a next generation sensor network in international sport events, and it demonstrated the usefulness of the emerging sensor-based air monitoring technology in rapid network deployment to supplement existing air monitoring. Sensors 2016, 16, 211 2 of 18 potentially including heat, cold, rain and hills, adding to the stress of energy output to complete these events [5] . Air pollution may be an added stressor that may at times be present at levels endangering or at least irritating to the runners and possibly the spectators. Especially for runners, during exercise, air intake increases, and most air is taken through the mouth instead of the nasal system, which can filter some particles and gases [6] . Hong Kong hosts many athletic events, including a signature event, the Standard Chartered Hong Kong Marathon, called the Marathon hereafter. The Marathon route covers a range of communities and streets including the West Harbor Crossing (a long sub-bay tunnel) in the city. These places are often quite polluted by traffic from the on-road trucks, diesel buses and light duty vehicle. Various measures have been implemented during the Marathon to improve the route-specific air quality for participants, including traffic control, closure of the tunnel to traffic and switching on the mechanic ventilation for the tunnel. The temporary traffic control measures are expected to improve the air quality along the Marathon route. Event organizers and government co-sponsors were interested in gathering and communicating facts regarding air quality during the event. However, the existing network of regulatory air monitors was determined to be inadequate to indicate actual air pollution concentrations along the Marathon route due to the highly heterogeneous nature of air pollutants in the urban environment, and the impact of the change in local traffic may not be directly captured in urban background air quality [7] . There was a need for site-specific air monitoring to provide in situ air quality [8] . However, the short-term duration of the sports event makes the ad hoc deployment of traditional equipment difficult or not possible because of the limitations of power supply and space. Recently, there has been an emerging trend of using the next generation air sensors to provide highly resolved air quality data as an alternative monitoring option [9, 10] . Due to their low cost, small size and low power consumption, the new technologies are very appealing for use in situations where traditional monitors are impractical [9, 11] . The sensor-based systems have been used by researchers in different programs for fixed, mobile and community air monitoring applications [11] [12] [13] [14] [15] [16] [17] . However, some applications of these new approaches to environmental sensing still pose some technical challenges. Chief among these is that the pollution data reported by sensors and sensor systems require critical and careful evaluation under different ambient conditions [11] . Among the important factors known to impact the data from various low cost sensors, such as the ones we employed (electrochemical cells for CO and NO 2 ), as well as for ozone, are positive and negative interferences with other common ambient co-pollutants, temperature and humidity impacts on reported pollutant responses, long-term drift and cell life time under extremely high and low humidity conditions. Further, it is apparent that cells for a given pollutant may be somewhat variable in response to the above factors. Investigation of how to provide robust calibration and to improve sensor data accuracy considering these factors has been performed by others [17, 18] . These include development of simple linear regression fitting of observed data, multiple regression estimations performed to further improve the fits taking factors, such as humidity, temperature and co-pollutants into account. Finally, recent studies have applied neural networking protocols, where multiple factors are included [19] [20] [21] [22] . The study presents our work in the development of a next generation air sensor system and its application in an ad hoc air monitoring network, in which the air sensors were placed and operated at the street level to monitor the air along the Marathon route in urban Hong Kong and the near-real time calculation and communication of health-indexed findings of air quality to the public. The deployment of the sensor network also provided a unique opportunity to investigate the impact of temporary traffic control measures on the local street level air quality in conditions that are somewhat more challenging than what has been evaluated in prior studies. The study also demonstrated the usefulness and potential of the air sensor-based monitoring approach for high temporal-spatial resolution air pollution measurement to meet environmental monitoring challenges.
In REF , a next generation air monitoring system was developed and evaluated with both laboratory and field tests.
Development and Application of a Next Generation Air Sensor Network for the Hong Kong Marathon 2015 Air Quality Monitoring
Sensors (Basel, Switzerland)
Sensors (Basel, Switzerland)
Engineering Medicine Computer Science