[Characteristics of Ozone Pollution and Relationships with Meteorological Factors in Jiangxi Province].

Based on the pollutant data provided by the environmental monitoring stations and the routine observation data of 11 national meteorological stations in Jiangxi Province from 2016 to 2019, the characteristics of ozone pollution and the relationships with meteorological factors were investigated in this study. The results showed that ozone pollution has become increasingly severe in Jiangxi Province in recent years. The annual mean concentration of ozone in Jiangxi Province (the maximum daily 8 h average) was 80.1 µg·m-3 in 2016 and reached up to 98.2 µg·m-3 in 2019, with an average annual growth rate of 6 µg·m-3. The number of over-standard days of ozone was 475 d, accounting for 72.6% of 2019 in Jiangxi Province. The average concentrations observed in summer were higher than those observed in the other seasons during 2016 to 2018, but in 2019, higher ozone concentrations were observed in autumn owing to the lower precipitation, more sufficient sunshine, and the resulting higher air temperature. Overall, the ozone concentrations were found to be positively correlated with air temperature and sunshine but negatively correlated with relative humidity in Jiangxi Province. A high ozone concentration usually appeared with an air temperature higher than 30℃, relative humidity of 20%-40%, and wind speed of 2-3 m·s-1. The spatial distribution of the ozone concentrations exhibited distinct characteristics with higher values observed in southern Jiangxi relative to those in the northern areas and lower values in northeastern Jiangxi compared with those in other regions. More serious ozone pollution was found in Ganzhou among the 11 cities in Jiangxi Province, with the highest annual concentration of 104.2 µg·m-3 observed in 2019. The results of the model analyses, including the HYSPLIT backward trajectory model and potential source contribution function model, indicated that there was a significant difference in the potential source contribution of ozone pollution in Ganzhou on seasonal scales, specifically in central Guangdong and the northwest of Jiangxi Province in spring, the northwest parts of Jiangxi Province in summer, and the north of Guangdong and central Anhui Province in autumn.

[In-situ measurement of atmospheric methyl chloroform at the Shangdianzi GAW regional background station].

An in-situ GC-ECD monitoring system was established at the Shangdianzi GAW regional background station (SDZ) for a 2-year atmospheric methyl chloroform (CH3CCl3) measurement experiment. Robust extraction of baseline signal filter was applied to the CH3CCl3 time series to separate the background and pollution data. The yearly averaged background mixing ratios of atmospheric CH3CCl3 were (9.03 +/- 0.53) x 10(-12) mol x mol(-1) in 2009 and (7.73 +/- 0.47) x 10(-12) in 2010, and the percentages of the background data in the whole data were 61.1% in 2009 and 60.4% in 2010, respectively. The yearly background CH3CCl3 mixing ratios at SDZ were consistent with the northern hemisphere background levels observed at Mace Head and Trinidad Head stations, but lower than the results observed at sites in southern China and some Chinese cities from 2001 to 2005. During the study period, background mixing ratios trends exhibited a decreasing rate of 1.39 x 10 12(-12) a(-1). The wind direction with the maximum CH3CCl3 mixing ratio was from the southwest sector and that with the minimum ratio was from the northeast sector. The differences between the maximum and the minimum average mixing ratios in the 16 wind directions were 0.77 x 10(-12) (2009) and 0.52 x 10(-12) (2010). In the 16 different wind directions, the averaged mixing ratio of CH3CCl3 in 2010 was lower than that in 2009 by 1.03 x 10(-12) -1.68 x 10(-12).

[Establishment and assessment of QA/QC method for sampling and analysis of atmosphere background CO2].

To strengthen scientific management and sharing of greenhouse gas data obtained from atmospheric background stations in China, it is important to ensure the standardization of quality assurance and quality control method for background CO2 sampling and analysis. Based on the greenhouse gas sampling and observation experience of CMA, using portable sampling observation and WS-CRDS analysis technique as an example, the quality assurance measures for atmospheric CO,sampling and observation in the Waliguan station (Qinghai), the glass bottle quality assurance measures and the systematic quality control method during sample analysis, the correction method during data processing, as well as the data grading quality markers and data fitting interpolation method were systematically introduced. Finally, using this research method, the CO2 sampling and observation data at the atmospheric background stations in 3 typical regions were processed and the concentration variation characteristics were analyzed, indicating that this research method could well catch the influences of the regional and local environmental factors on the observation results, and reflect the characteristics of natural and human activities in an objective and accurate way.

[Study on the in-situ measurement of greenhouse gas by an improved FTIR].

The real-time, automatic, highly accurate and efficient system for measuring the mixing ratios of CO2, CH4, CO and N2O has been developed by combining the commercial FTIR system (Wollongong University) with an auto-sampling system and a working standard module. Based on the tests conducted, the FTIR showed the high precision and a relatively low accuracy associated with its poor determination of correction factors. The absolute error of the mixing ratio of CO was above 38.8 x 10(-9), suggesting that FTIR alone could not meet the requirement for the real time measurement. Using the working standard gases to adjust results from the FTIR significantly improved the accuracy of measurements. For both static and dynamic conditions, the discrepancies between the measured results and the real values were below 0.11 x 10(-6), 1.8 x 10(-9), 0.15 x 10(-9) and 0.5 x 10(-9) for CO2, CH4, N2O and CO respectively, meeting the requirements for the atmospheric real-time measurements. During 6 days in-situ measurements of greenhouse gas outside the lab, the precision of target gas can reach 0.05 x 10(-6), 0.2 x 10(-9), 0.07 x 10(-9), 0.5 x 10(-9) for CO2, CH4, N2O, CO, and inaccuracy can be 0.09 x 10(-6), 0.4 x 10(-9), 0.14 x 10(-9), 0.5 x 10(-9), respectively.

[CH4 concentrations and the variation characteristics at the four WMO/GAW background stations in China].

Background CH4 concentrations were continuously measured at the 4 WMO/GAW stations [Waliguan in Qinghai (WLG), Lin'an in Zhejiang (LAN), Shangdianzi in Beijing (SDZ), and Longfengshan in Heilongjiang (LFS)] by Cavity Ring Down Spectroscopy system. From 2009 to 2010, the diurnal cycle of hourly average CH4 concentration at LAN was found to be similar in all four seasons, with the highest level detected at 05:00 (Beijing Time) and the lowest at about 14:00. Similar CH4 diurnal cycles were observed at LFS in the summer time. However, the daily amplitude was much higher than that at LAN and reached 216. 8 x 10(-9) (molar ratio). For SDZ station, there were similar trends in spring, autumn and winter. The daily average concentration in the summer was much higher than those of the other seasons and reached the highest at about 20:00. No apparent CH4 diurnal cycle was observed at the WLG station during the whole year. The seasonal variations were obvious at the three regional stations (LAN, SDZ, LFS). The background concentration was the lowest in July at LAN while reached the highest level in August at LFS. The yearly background concentration variation at LFS displayed a "W" pattern. At LFS and SDZ, the wintertime CH4 concentrations were higher than those in spring and autumn. WLG represented a clean area and its CH4 value was the lowest among the four stations with the monthly average amplitude to be about 11.5 x 10(-9). At all three regional stations, non-background data accounted for more than 70% of the whole data. Cluster analysis of 3 day backward trajectories corresponding to the high CH4 concentration (WLG: CH4 > 1 870 x 10(-9), LFS: CH4 > 2100 x 10(-9), LAN: CH4 > 2 150 x10(-9), SDZ: CH4 > 2050 x 10(-9)) data points suggested that the high CH4 level measured in summer might be associated with the air mass transportation.