Spatial and temporal distribution of the cloud optical depth over China based on MODIS satellite data during 2003–2016

The cloud optical depth(COD) is one of the important parameters used to characterize atmospheric clouds. We analyzed the seasonal variations in the COD over East Asia in 2011 using cloud mode data from the AERONET(Aerosol Robotic Network) ground-based observational network. The applicability of the MODIS(Moderate Resolution Imaging Spectroradiometer) COD product was verified and compared with the AERONET cloud mode dataset. There was a good correlation between the AERONET and the MODIS. The spatial and temporal distribution and trends in the COD over China were then analyzed using MODIS satellite data from 2003 to 2016. The seasonal changes in the AERONET data and the time sequence variation of the satellite data suggest that the seasonal variations in the COD are significant. The result shows that the COD first decreases and then increases with the season in northern China, and reaches the maximum in summer and minimum in winter.However, the spatial distribution change is just the opposite in southern China. The spatial variation trend shows the COD in China decreases first with time and gradually increases after 2014. And the trend of COD in the western and central China is consistent with that in China. While the trend of COD shows a continuously increasing over time in northeast China and the Pearl River Delta.     

Water quality monitoring in a slightly-polluted inland water body through remote sensing — Case study of the Guanting Reservoir in Beijing, China

This study focused on the water quality of the Guanting Reservoir, a possible auxiliary drinking water source for Beijing. Through a remote sensing (RS) approach and using Landsat 5 Thematic Mapper (TM) data, water quality retrieval models were established and analyzed for eight common water quality variables, including algae content, turbidity, and concentrations of chemical oxygen demand, total nitrogen, ammonia nitrogen, nitrate nitrogen, total phosphorus, and dissolved phosphorus. The results show that there exists a statistically significant correlation between each water quality variable and remote sensing data in a slightly-polluted inland water body with fairly weak spectral radiation. With an appropriate method of sampling pixel digital numbers and multiple regression algorithms, retrieval of the algae content, turbidity, and nitrate nitrogen concentration was achieved within 10% mean relative error, concentrations of total nitrogen and dissolved phosphorus within 20%, and concentrations of ammonia nitrogen and total phosphorus within 30%. On the other hand, no effective retrieval method for chemical oxygen demand was found. These accuracies were acceptable for the practical application of routine monitoring and early warning on water quality safety with the support of precise traditional monitoring. The results show that performing the most traditional routine monitoring of water quality by RS in relatively clean inland water bodies is possible and effective.     

Application of AERMOD on near future air quality simulation under the latest national emission control policy of China：A case study on an industrial city

Air quality model can be an adequate tool for future air quality prediction, also atmospheric observations supporting and emission control strategies responders. The influence of emission control policy (emission reduction targets in the national "China’s 12th Five-Year Plan (2011-2015)") on the air quality in the near future over an important industrial city of China, Xuanwei in Yunnan Province, was studied by applying the AERMOD modeling system. First, our analysis demonstrated that the AERMOD modeling system could be used in the air quality simulation in the near future for SO2 and NOx under average meteorology but not for PM10. Second, after evaluating the simulation results in 2008 and 2015, ambient concentration of SO2, NOx and PM10 (only 2008) were all centered in the middle of simulation area where the emission sources concentrated, and it is probably because the air pollutions were source oriented. Last but not least, a better air quality condition will happen under the hypothesis that the average meteorological data can be used in near future simulation. However, there are still heavy polluted areas where ambient concentrations will exceed the air quality standard in near future. In spatial allocation, reduction effect of SO2 is more significant than NOx in 2015 as the contribution of SO2 from industry is more than NOx. These results inspired the regulatory applications of AERMOD modeling system in evaluating environmental pollutant control policy     

Cluster analysis: A technique for estimating the synoptic meteorological controls on air and precipitation chemistry—Method and applications

Combining the pattern recognition capabilities of cluster analysis with isobaric air trajectory data is a useful way of quantifying the influence of synoptic meteorology on the pollution climatology at a site. A non-hierarchial clustering of 1000 mb isobaric trajectories, using squared Euclidean distance as a similarity measure, leads to the identification of a finite number of distinct synoptic patterns. Typical airbore and aqueous pollutant concentrations associated with each of these patterns may then be established. By considering 3-day air trajectories in this study, the “history” of an air parcel is captured in an improved manner, when compared with attempts to use individual day weather “types” to characterize meterological situations.     

Cluster analysis: A technique for estimating the synoptic meteorological controls on air and precipitation chemistry—Results from Eskdalemuir,South Scotland

Clustering of isobaric trajectories arriving at Eskdalemuir, south Scotland, enabled us to isolate the influences of atmospheric transport patterns and precipitation amount on gas, aerosol and precipitation chemistry at this site. We conclude that at Eskdalemuir, 55% of the variation in summer season non-sea-salt sulphate concentration in rain may be explained by upwind history defined by trajectory clustering and by precipitation amount. Each cluster of trajectories could be described by distinct synoptic weather conditions, leading to the interesting prospect of assigning a typical ion concentration in precipitation to a given synoptic weather pattern. The scale of the synoptic patterns identified in this study were shown to be able to explain the variation in sulphur dioxide concentrations observed across a network of 50 stations contributing to the European Monitoring and Evaluation Programme.There is greater confidence in Global Climate Model simulations of future circulation patterns as a result of climate change than of equivalent simulations of temperature and precipitation distributions. A first approximation of future levels of ion deposition may therefore best be inferred from circulation pattern-ion concentration relationships of the type developed in this paper. The influence of other less certain changes in precipitation type/amount, scavenging processes and emission levels should then be assessed against a background of changes in the frequency of circulation patterns.