Study on atmospheric visibility variations and the impacts of meteorological parameters using high temporal resolution data: an application of Environmental Internet of Things in China

Abstract

Atmospheric visibility degradation in China is an important environmental issue because it has been demonstrated to be associated with air pollution. One-year of high temporal resolution visibility data and meteorological parameters including precipitation, relative humidity (RH), wind speed (WS), and wind direction (WD) during June 2011–May 2012 were obtained at Long-term Urban Ecosystems Observation and Research Station in Xiamen (Xiamen LUEORS) by means of Environmental Internet of Things (EIoT) technology. The visibility and meteorological data were analyzed to study the temporal variation of atmospheric visibility and its relationship with meteorological parameters in this region. Optimal empirical regression models were also developed to predict visibility based on meteorological parameters. The annual average visibility during the study period is 8969 m, with 63.2% of the total measurements less than 10 km. ‘Bad’ visibility (i.e., visibility < 10 km) is prone to occur in late winter to early spring. Visibility exhibited a distinct diurnal variation with the minimum of 6508 m at 6:00 Local Time (LT) and the maximum of 11,378 m at 13:00 LT. Visibility is higher in summer (11,410 m) and autumn (10,589 m) than in winter (7070 m) and spring (6807 m), with the highest (12,141 m) and lowest (5376 m) value occurred in August and February, respectively. During hazy, foggy, and rainy periods, the average visibilities were 5020 m, 1044 m, and 3967 m, respectively, much lower than those during normal period (15,970 m). Precipitation decreased the frequency of ‘good’ visibility (i.e., visibility ≥ 10 km) by 1.4% and increased the frequency of ‘extremely bad’ visibility (i.e., visibility < 2 km) by 1.5% during the year. Visibility was mostly below 10 km when the 10-min precipitation was larger than 0.6 mm. No significant correlation exists between visibility change and precipitation. For RH ≥ 80%, over 90% of the visibilities are below 10 km. The average visibility is below 8 km for RH ≥ 70%. For WS < 1.0 m/s, over 80% of the visibilities are below 10 km. When WS < 2.0 m/s, the average visibility is below 9 km. Visibility is negatively correlated with RH and positively correlated with WS, with the annual correlation coefficients of –0.507 and 0.494, respectively. It is prone to have ‘bad’ visibility when the wind is blowing from west and northwest. An optimal empirical multiple regression model based on meteorological parameters can moderately simulate the visibility. The results provide new knowledge for better understanding the characteristics of visibility and its relationship with meteorological parameters, based on which a statistical model for predicting the visibility in this region was developed.

Keywords:

• atmospheric visibility
• meteorological parameter
• diurnal variation
• Environmental Internet of Things (EIoT)
• LUEORS

Acknowledgments

The authors thank the following agencies that provided funds/support for this research: Knowledge Innovation Program of the Chinese Academy of Sciences (No. KZCX2-EW-408 and KZCX2-YW-453), Fujian Distinguished Young Scholar Career Award (No. 2011J06018), Public Interest Program of Chinese Ministry of Environmental Protection (No. 201009004), and State Key Laboratory of Loess and Quaternary Geology Program (No. SKLLQG1104). The authors also thank Xiamen Meteorology Bureau and Xiamen LUEORS for providing meteorological and visibility data.