Background Concentrations of Heavy Metals in Brown Algae from the Northwest Sea of Japan

Background concentrations of Fe, Mn, Cu, Zn, Pb, Cd, and Ni were calculated for brown algae Costaria costata from the northwest Sea of Japan. Also the paper contains refined data on heavy metal concentrations in the widespread distributed brown algae, such as Stephanocystis crassipes, Sargassum pallidum and S. miyabei. As the upper threshold levels of metal background concentrations, the median values plus double medians of absolute deviations from the medians were used (Me + 2MAD). The lower threshold level of the background concentration equal to the physiological need for an element is the median of 15% minimum values in the sampling minus the double median of absolute deviations from the median (Me15 - 2MAD15). The calculated ranges of the background concentrations of metals in algae were compared with concentrations of elements in mac-rophytes collected from habitats with background concentrations of metals in water.

Monitoring atmospheric nitrous oxide background concentrations at Zhongshan Station,east Antarctica

At present,continuous observation data for atmospheric nitrous oxide（N_2O） concentrations are still lacking,especially in east Antarctica.In this paper,nitrous oxide background concentrations were measured at Zhongshan Station（69°22′25″S,76°22′14″E）,east Antarctica during the period of 2008–2012,and their interannual and seasonal characteristics were analyzed and discussed.The mean N_2O concentration was 321.9 n L/L with the range of 320.5–324.8 n L/L during the five years,and it has been increasing at a rate of 0.29% year-1.Atmospheric N_2O concentrations showed a strong seasonal fluctuation during these five years.The concentrations appeared to follow a downtrend from spring to autumn,and then increased in winter.Generally the highest concentrations occurred in spring.This trend was very similar to that observed at other global observation sites.The overall N_2O concentration at the selected global sites showed an increasing annual trend,and the mean N_2O concentration in the Northern Hemisphere was slightly higher than that in the Southern Hemisphere.Our result could be representative of atmospheric N_2O background levels at the global scale.This study provided valuable data for atmospheric N_2O concentrations in east Antarctica,which is important to study on the relationships between N2 O emissions and climate change.

PRELIMINARY STUDY OF VARIATION OF SO_2 AND AEROSOL PARTICLE BACKGROUND CONCENTRATIONS IN THE EASTERN CHINA

The average concentrations of sulphur dioxide,sulfate aerosol and TSP were about 8—10 ppb,15.08 μg m^(-3),and 241.40 μg m^(-3) respectively,which were measured at the Lin'an regional background station during August— November,1991.The higher concentrations of SO_2 and SO_4^(2-) maybe acidify the rainfall.It has a great influence upon the human health and ecosystem.The simulated results indicate that the distributions of SO_2 and SO_4^(2-) were deter- mined by local emission sources.Average aerosol particle number density was 2.0×10~4 cm^(-3).It shows that social devel- opment and human activities strongly affect the atmospheric background level.

A land use regression for predicting NO_2 and PM_(10) concentrations in different seasons in Tianjin region,China

Land use regression （LUR） model was employed to predict the spatial concentration distribution of NO2 and PM10 in the Tianjin region based on the environmental air quality monitoring data. Four multiple linear regression （MLR） equations were established based on the most significant variables for NO2 in heating season （R2 = 0.74）, and non-heating season （R2 = 0.61） in the whole study area; and PM10 in heating season （R2 = 0.72）, and non-heating season （R2 = 0.49）. Maps of spatial concentration distribution for NO2 and PM10 were obtained based on the MLR equations （resolution is 10 krn）. Intercepts of MLR equations were 0.050 （NOz, heating season）, 0.035 （NO2, non-heating season）, 0.068 （PM10, heating season）, and 0.092 （PM10, non-beating season） in the whole study area. In the central area of Tianjin region, the intercepts were 0.042 （NO2, heating season）, 0.043 （NO2, non-heating season）, 0.087 （PM10, heating season）, and 0.096 （PMl0, non-heating season）. These intercept values might imply an area＇s background concentrations. Predicted result derived from LUR model in the central area was better than that in the whole study area. Rz values increased 0.09 （heating season） and 0.18 （non-heating season） for NO2, and 0.08 （heating season） and 0.04 （non-heating season） for PMl0. In terms of R2, LUR model performed more effectively in heating season than non-heating season in the study area and gave a better result for NOz compared with PM10.

Application of land use regression for estimating concentrations of major outdoor air pollutants in Jinan, China

SO2, NO2, and PM10 are the major outdoor air pollutants in China, and most of the cities in China have regulatory monitoring sites for these three air pollutants. In this study, we developed a land use regression (LUR) model using regulatory monitoring data to predict the spatial distribution of air pollutant concentrations in Jinan, China. Traffic, land use and census data, and meteorological and physical conditions were included as candidate independent variables, and were tabulated for buffers of varying radii. SO2, NO2, and PM10 concentrations were most highly correlated with the area of industrial land within a buffer of 0.5 km (R2=0.34), the distance from an expressway (R2=0.45), and the area of residential land within a buffer of 1.5 km (R2=0.25), respectively. Three multiple linear regression (MLR) equations were established based on the most significant variables (p<0.05) for SO2, NO2, and PM10, and R2 values obtained were 0.617, 0.640, and 0.600, respectively. An LUR model can be applied to an area with complex terrain. The buffer radii of independent variables for SO2, NO2, and PM10 were chosen to be 0.5, 2, and 1.5 km, respectively based on univariate models. Intercepts of MLR equations can reflect the background concentrations in a certain area, but in this study the intercept values seemed to be higher than background concentrations. Most of the cities in China have a network of regulatory monitoring sites. However, the number of sites has been limited by the level of financial support available. The results of this study could be helpful in promoting the application of LUR models for monitoring pollutants in Chinese cities.

Variation Characteristics of Ambient NMHCs at Shangdianzi and Lin’an Regional GAW Sites

In order to study the variation characteristics of concentration of the atmospheric non-methane hydrocarbons （NMHCs） in background area of China, the atmospheric concentrations of NMHCs were measured at Lin＇an （LA） regional GAW （Global Atmosphere Watch） Station （30°25＇N, 119°44＇E; 132.0 m ASL） and Shangdianzi （SDZ） regional GAW Station （40°19＇N, 117°07＇E; 286.5 m ASL） with the sorbent sorption/thermal desorption/gas chromatographic method. Totally 145 samples were collected during the period of October 2003 and July 2004. Among the 52 NMHC species of C2-C10 detected there were 26 alkanes, 17 alkenes, and 9 aromatics. The average concentrations of total NMHCs （TNMHCs） at LA and SDZ were （238.5±126.0） ×10^-9C and （278.7±185.5）×10^-9C, respectively. The results showed the ambient concentrations of TNMHCs at LA regional GAW Station increased notably over the last decade. The compositions of NMHCs at SDZ and LA were relatively similar. The proportions of alkanes, alkenes, and aromatics for SDZ and LA were in ranges of （27.3±4.0）%, （10.3±3.5）%, and （62.5±4.8）%, respectively, with features of vehicle exhaust emissions. The concentrations of NMHCs at the two sites showed obvious diurnal and seasonal variations. The TNMHC concentrations in October-November were high at the two sites, and relatively low in April and July. The diurnal variation patterns at the sites were different. The high TNMHC concentrations at SDZ normally appeared in evening and night, but appeared in morning at LA. The TNMHCs concentrations at the two sites were significantly influenced by the meteorological condition. The high TNMHC concentration associated with the local wind from the urban areas or traffic in upper reaches.