Th is study empirically analyses the impact of family life cycles on the family farm scale of rural households in Southern China. Th e ordered Probit modelling is applied to examine the survey data that comprise 2040 valid questionnaires distributed in 88 villages of the Fujian province in China. Th e family life cycle has a remarkable infl uence on the family farm scale as a whole. Th e numbers of children and farming people in a family have a positive signifi cant eff ects on the family farm scale. In addition, the individual characteristics of female householders have signifi cant eff ects on the family farm scale. Meanwhile, the family characteristics diff er at fi ve defi ned stages of the family life cycle. Th e study covers the gap in the literature on the eff ects of family structure on the rural household economic behaviour, in particular, on the impact of the family life cycles on the family farm scale.

Abstract. In order to study the spatial and temporal variation of characteristics of drought and flood in Dian-Qian-Gui Karst Areas of China, TRMM 3B43 precipitation data from 1998 to 2017 and 72 rain gauge station data from 1998 to 2012 were used to verify the TRMM 3B43 data on monthly scale by correlation coefficient and relative deviation. The TRMM-Z index was taken as an index of drought and flood to quantitatively analyze the drought and flood characteristics. The results show that: (1) there was a significant positive correlation between TRMM 3B43 precipitation data and the measured data of meteorological stations on the monthly scale, with a correlation coefficient of 0.92, passing the significance test of 0.01 level. The calculated result of relative Bias is -0.058, indicating that TRMM 3B43 precipitation is slightly higher than the actual precipitation. (2) From 1998 to 2017, the TRMM-Z index in the research area fluctuated between −1.160 and 1.678, among which the Z index in July 1999 reached the maximum value of 1.678, and in February 2010 the Z index reached the minimum value of −1.160. (3) During the past 20 years, the flood months in the study areas were 47 months, accounting for 19.58% of the study time, and 40 months were drought months, accounting for 16.67% of the study time. Floods mainly occurred in the summer with abundant rainfall, while droughts mainly occurred in the winter with less rainfall. (4) Taking 2008–2009 as typical representative of drought and flood, the spatial variation of drought and flood were researched.

Abstract. This paper was based on Japan's new generation of geostationary satellite Himawari-8 2016 Aerosol Optical Depth (AOD) data and near-ground monitoring station PM2.5 mass concentration data, boundary layer height (BLH), relative humidity (RH), normalized vegetation index (NDVI) data to establish a multivariate linear regression model (MLR) and a geographically weighted regression model (GWR) in Beijing.This provided data and scientific basis for the treatment of air pollution.The results show that: (1) The fitting determination coefficient R2 of the MLR was 0.5244, indicating that there was a significant correlation between PM2.5 and AOD. After GWR model introduced BLH, RH and NDVI in turn, R2 increased from 0.3945 to 0.5403, indicating that the introduction of relevant influencing factors can improve the accuracy of the model, that was, PM2.5 was affected by BLH, RH and NDVI. (2) The regression coefficients of the MLR and GWR of the BLH, RH and NDVI were statistically analyzed. The regression coefficients of the two models were close to each other, but the standard deviation of the GWR regression coefficients was larger than the MLR, indicating that the local information of the GWR model was more abundant. It reflected the difference characteristics of the regression coefficients of each parameter.

Abstract. The paper analyzed the variation characteristics of AQI and its correlation with PM2.5 and PM10 of in Beijing-Tianjin-Hebei region from July 2015 to July 2018 based on hours of pollutants in Beijing-Tianjin-Hebei region, using AQI calculation method and statistical correlation evaluation method. Results showed that:(1) The air quality compliance rate in Beijing-Tianjin-Hebei region was 67%, the average AQI was 97.6577, and the air quality was good. The distribution frequency of primary pollutants was PM2.5, followed by PM10, which accounts for 78.9% of the distribution frequency of the six major pollutants, indicated that PM2.5 and PM10 had a greater impact on the air quality of Beijing-Tianjin-Hebei. (2) The correlation between AQI and PM2.5 and PM10 was significantly positively correlated. R2 was 0.8225 and 0.7749, respectively, P < 0.01, indicated that both showed a greater impact on air quality. (3) AQI and PM2.5 and PM10 showed a gradual decrease trend at 9h–16h, ie 9h highest and 16h lowest. The AQI fluctuated between 94.2816 and 103.3562, indicated that the air quality at 9h–16h was good or slightly polluted. (4) The spatial distribution of AQI, PM2.5 and PM10 was characterized by low northwest and high southeast, and the southeastern part was gradually decreasing from 9h–16h. AQI was negatively correlated with elevation. The higher the elevation, the better the air quality, and the worse the air quality.

Soil moisture is a comprehensive reflection of soil moisture status and is an important parameter for land surface conditions. It is very important to study the distribution characteristics of soil moisture for ecological environment protection, scientific and rational utilization of soil water resources, and climate research. Using the soil layer humidity data sets of GLDAS-Noah v2.0 and v2.1, we analyzed the spatial-temporal distribution of soil moisture in China in a layer from 0 to 200 cm over 71 years from 1948 to 2018. Firstly, the Mann-Kendall trend test was used to analyze the trend of the changes and the spatial variation characteristics of soil moisture over the 71 years. Secondly, the coefficient of variation was used to analyze the temporal and spatial fluctuation of soil moisture in each layer of the study area over the 71 years. Finally, the Hurst index was used to predict the future trend of soil moisture changes in each layer. In addition, the correlation between soil moisture and the spatial-temporal variation of soil temperature in China was explored. The results show that the annual variation trend of soil moisture in the 0-200 cm soil layer has been consistent, that is, the soil humidity in most parts of east China has been decreasing, especially in northeast China, central China, the area surrounding the Yunnan Guizhou Plateau, and Taiwan Island, while it has been increasing in most of the western regions. Also, the change in soil layer humidity from 0 to 200 cm in southern China was greater than that in the northern region, and the humidity of the soil layer in the Pearl River Delta region was the most unstable. In addition, the spatial variation of soil moisture in the study area was relatively small from 1948 to 2001, but from 2002, the soil moisture throughout the study area became uneven. In the future, the trend of the change in soil moisture in most areas of China will remain consistent with that in the past 71 years, i.e., the soil in most parts of the east will gradually dry out and the soil moisture in most parts of the west will gradually increase; the soil humidity from 0 to 200 cm in most of the study area is inversely related to the soil temperature, and is mainly concentrated in northeast and central China, central and northern Inner Mongolia, the Qinghai Tibet Plateau, and Taiwan Island.