Atmosphere2015, 6(3), 209-233; doi:10.3390/atmos6030209 (registering DOI) - published 26 February 2015 Show/Hide Abstract
Abstract: Measurements at the Grand Bay National Estuarine Research Reserve support a range of research activities aimed at improving the understanding of the atmospheric fate and transport of mercury. Routine monitoring was enhanced by two intensive measurement periods conducted at the site in summer 2010 and spring 2011. Detailed meteorological data are required to properly represent the weather conditions, to determine the transport and dispersion of plumes and to understand the wet and dry deposition of mercury. To describe the mesoscale features that might influence future plume calculations for mercury episodes during the Grand Bay Intensive campaigns, fine-resolution meteorological simulations using the Weather Research and Forecasting (WRF) model were conducted with various initialization and nudging configurations. The WRF simulations with nudging generated reasonable results in comparison with conventional observations in the region and measurements obtained at the Grand Bay site, including surface and sounding data. The grid nudging, together with observational nudging, had a positive effect on wind prediction. However, the nudging of mass fields (temperature and moisture) led to overestimates of precipitation, which may introduce significant inaccuracies if the data were to be used for subsequent atmospheric mercury modeling. The regional flow prediction was also influenced by the reanalysis data used to initialize the WRF simulations. Even with observational nudging, the summer case simulation results in the fine resolution domain inherited features of the reanalysis data, resulting in different regional wind patterns. By contrast, the spring intensive period showed less influence from the reanalysis data.
Atmosphere2015, 6(2), 195-208; doi:10.3390/atmos6020195 - published 5 February 2015 Show/Hide Abstract
Abstract: Black carbon (BC) aerosol plays an important role in climate forcing. The net radiative effect is strongly dependent on the physical properties of BC particles. A single particle soot photometer and a carbon monoxide analyser were deployed during the Chinese Lunar Year (CLY) and on weekdays at Xi’an, China, to investigate the characteristics of refractory black carbon aerosol (rBC). The rBC mass on weekdays (8.4 μg·m−3) exceeds that during the CLY (1.9 μg·m−3), presumably due to the lower anthropogenic emissions during the latter. The mass size distribution of rBC shows a primary mode peak at ~205 nm and a small secondary mode peak at ~102-nm volume-equivalent diameter assuming 2 g·cm−3 in void-free density in both sets of samples. More than half of the rBC cores are thickly coated during the CLY (fBC = 57.5%); the percentage is slightly lower (fBC = 48.3%) on weekdays. Diurnal patterns in rBC mass and mixing state differ for the two sampling periods, which are attributed to the distinct anthropogenic activities. The rBC mass and CO mixing ratios are strongly correlated with slopes of 0.0070 and 0.0016 μg·m−3·ppbv−1 for weekdays and the CLY, respectively.
Atmosphere2015, 6(2), 183-194; doi:10.3390/atmos6020183 - published 26 January 2015 Show/Hide Abstract
Abstract: Tourism is a very important industry, and it is deeply affected by climate. This article focuses on the role of climate in tourism seasonality and attempts to assess the impacts of climate resources on China’s tourism seasonality by using the Tourism Climate Index (TCI). Seasonal distribution maps of TCI scores indicate that the climates of most regions in China are comfortable for tourists during spring and autumn, while the climate conditions differ greatly in summer and winter, with “excellent”, “good”, “acceptable” and “unfavorable” existing almost by a latitudinal gradation. The number of good months throughout China varies from zero (the Tibetan Plateau area) to 10 (Yunnan Province), and most localities have five to eight good months. Moreover, all locations in China can be classified as winter peak, summer peak and bi-modal shoulder peak. The results will provide some useful information for tourist destinations, travel agencies, tourism authorities and tourists.
Atmosphere2015, 6(2), 164-182; doi:10.3390/atmos6020164 - published 26 January 2015 Show/Hide Abstract
Abstract: Daily PM2.5 mass concentrations and chemical compositions together with the aerosol optical properties were measured from 8–28 November 2011 in Beijing. PM2.5 mass concentration varied from 15.6–237.5 μg∙m−3 and showed a mean value of 111.2 ± 73.4 μg∙m−3. Organic matter, NH4NO3 and (NH4)2SO4 were the major constituents of PM2.5, accounting for 39.4%, 15.4%, and 14.9% of the total mass, respectively, while fine soil, chloride salt, and elemental carbon together accounted for 27.7%. Daily scattering and absorption coefficients (σsc and σap) were in the range of 31.1–667 Mm−1 and 8.24–158.0 Mm−1, with mean values of 270 ± 200 Mm−1 and 74.3 ± 43.4 Mm−1. Significant increases in σsc and σap were observed during the pollution accumulation episodes. The revised IMPROVE algorithm was applied to estimate the extinction coefficient (bext). On average, organic matter was the largest contributor, accounting for 44.6% of bext, while (NH4)2SO4, NH4NO3, elemental carbon, and fine soil accounted for 16.3% 18.0%, 18.6%, and 2.34% of bext, respectively. Nevertheless, the contributions of (NH4)2SO4 and NH4NO3 were significantly higher during the heavy pollution periods than those on clean days. Typical pollution episodes were also explored, and it has been characterized that secondary formation of inorganic compounds is more important than carbonaceous pollution for visibility impairment in Beijing.
Atmosphere2015, 6(1), 150-163; doi:10.3390/atmos6010150 - published 9 January 2015 Show/Hide Abstract
Abstract: Daily average monitoring data for PM10, PM2.5 and PM1.0 and meteorological parameters at Chengdu from 2009 to 2011 are analyzed using statistical methods to replicate the effect of urban air pollution in Chengdu metropolitan region of the Sichuan Basin. The temporal distribution of, and correlation between, PM10, PM2.5 and PM1.0 particles are analyzed. Additionally, the relationships between particulate matter (PM) and certain meteorological parameters are studied. The results show that variations in the average mass concentrations of PM10, PM2.5 and PM1.0 generally have the same V-shaped distributions (except for April), with peak/trough values for PM average mass concentrations appearing in January/September, respectively. From 2009 to 2011, the inter-annual average mass concentrations of PM10, PM2.5 and PM1.0 fall year on year. The correlation coefficients of daily concentrations of PM10 with PM2.5, PM10 with PM1.0, and PM2.5 with PM1.0 were high, reaching 0.91, 0.83 and 0.98, respectively. In addition, the average ratios of PM2.5/PM10, PM1.0/PM10 and PM1.0/PM2.5 were 85%, 78% and 92%, respectively. From this, fine PM is determined to be the principal pollutant in the Chengdu region. Except for averaged air pressure values, negative correlations exist between other meteorological parameters and PM. Temperature and air pressure influenced the transport and accumulation of PM by affecting convection. Winds promoted PM dispersion. Precipitation not only accelerated the deposition of wet PM, but also inhibited surface dust transport. There was an obvious correlation between PM and visibility; the most important cause of visibility degradation was due to the light extinction of aerosol particles.