The increasing applications of low-cost air sensors promises more convenient and cost-effective systems for air monitoring in many places and under many conditions. However, the data quality from such systems has not been fully characterized and may not meet user expectations in research and regulatory uses, or for use in citizen science. In our study, electrochemical sensors (Alphasense B4 series) for carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO2), and oxidants (Ox) were evaluated under controlled laboratory conditions to identify the influencing factors and quantify their relation with sensor outputs. Based on the laboratory tests, we developed different correction methods to compensate for the impact of ambient conditions. Further, the sensors were assembled into a monitoring system and tested in ambient conditions in Hong Kong side-by-side with regulatory reference monitors, and data from these tests were used to evaluate the performance of the models, to refine them, and validate their applicability in variable ambient conditions in the field. The more comprehensive correction models demonstrated enhanced performance when compared with uncorrected data. One over-arching observation of this study is that the low-cost sensors may promise excellent sensitivity and performance, but it is essential for users to understand and account for several key factors that may strongly affect the nature of sensor data. In this paper, we also evaluated factors of multi-month stability, temperature, and humidity, and considered the interaction of oxidant gases NO2 and ozone on a newly introduced oxidant sensor.

Abstract. We present two-dimensional scanning Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations of nitrogen dioxide (NO2) and formaldehyde (HCHO) in Munich. Vertical columns and vertical distribution profiles of aerosol extinction coefficient, NO2 and HCHO are retrieved from the 2D MAX-DOAS observations. The measured surface aerosol extinction coefficients and NO2 mixing ratios derived from the retrieved profiles are compared to in situ monitoring data, and the surface NO2 mixing ratios show a good agreement with in situ monitoring data with a Pearson correlation coefficient (R) of 0.91. The aerosol optical depths (AODs) show good agreement as well (R = 0.80) when compared to sun photometer measurements. Tropospheric vertical column densities (VCDs) of NO2 and HCHO derived from the MAX-DOAS measurements are also used to validate Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI) satellite observations. Monthly averaged data show a good correlation; however, satellite observations are on average 30 % lower than the MAX-DOAS measurements. Furthermore, the MAX-DOAS observations are used to investigate the spatiotemporal characteristic of NO2 and HCHO in Munich. Analysis of the relations between aerosol, NO2 and HCHO shows higher aerosol-to-HCHO ratios in winter, which reflects a longer atmospheric lifetime of secondary aerosol and HCHO during winter. The analysis also suggests that secondary aerosol formation is the major source of these aerosols in Munich.

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 (NO2) 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.

Abstract. In this paper we present an investigation of the spatial and temporal variability of street-level concentrations of NO2 in Hong Kong as an example of a densely populated megacity with heavy traffic. For the study we use a combination of open-path remote sensing and in situ measurement techniques that allows us to separate temporal changes and spatial patterns and analyse them separately. Two measurement campaigns have been conducted, one in December 2010 and one in March 2017. Each campaign lasted for a week which allowed us to examine diurnal cycles, weekly patterns as well as spatially resolved long-term changes. We combined a long-path differential optical absorption spectroscopy (DOAS) instrument with a cavity-enhanced DOAS and applied several normalizations to the data sets in order to make the different measurement routes comparable. For the analysis of long-term changes we used the entire unfiltered data set and for the comparison of spatial patterns we filtered out the accumulation of NO2 when stopping at traffic lights for focusing on the changes of NO2 spatial distribution instead of comparing traffic flow patterns. For the generation of composite maps the diurnal cycle has been normalized by scaling the mobile data with coinciding citywide path-averaged measurement results. An overall descending trend from 2010 to 2017 could be observed, consistent with the observations of the Ozone Monitoring Instrument (OMI) and the Environment Protection Department (EPD) air quality monitoring network data. However, long-term difference maps show pronounced spatial structures with some areas, e.g. around subway stations, revealing an increasing trend. We could also show that the weekend effect, which for the most part of Hong Kong shows reduced NO2 concentrations on Sundays and to a lesser degree on Saturdays, is reversed around shopping malls. Our study shows that spatial differences have to be considered when discussing citywide trends and can be used to put local point measurements into perspective. The resulting data set provides a better insight into on-road NO2 characteristics in Hong Kong, which helps to identify heavily polluted areas and represents a useful database for urban planning and the design of pollution control measures.

In this paper, two half-scaled test tower models for a typical 110 kV single-circuit power transmission tower were designed and fabricated. The scaled test tower models were tested under the horizontal support's stretching (tensile) and compressive movements with the normal working loading conditions. The deformations of the tested tower models and stresses within the different bracing members were fully measured. A large amount of comprehensive test data was generated. Also a finite element (FE) model using software ANSYS was developed and validated by the test data. The research indicated that the designed half-scaled test tower model can reasonably represent the behaviour of the whole transmission tower under the horizontal support's movements. The magnitude of the stresses was reduced from the bracing members at lower part to the bracing members at higher part of the tower. The effect of the ground surface deformations is more significant on the truss members closed to the supports. Hence, for the design of transmission tower against the horizontal support's movements, it is important to reduce the slenderness of those bracing members.Keywords：Power transmission tower; horizontal support's movements; scaled test tower model; FE analysis.  Develop a FE model using ANSYS for modelling the 110 kV power transmission tower.3