Sensitivity and uncertainties assessment in radiative forcing due to aerosol optical properties in diverse locations in China.

Aerosol optical properties play an important role in affecting direct aerosol radiative forcing (DARF). However, DARF estimation is still uncertain due to the complexity of aerosol optical properties. Therefore, in this study, the spatiotemporal distributions of aerosol properties and their effects on DARF in China from 2004 to 2020 are investigated using the Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) model. The results show that the aerosol optical parameters vary greatly and change with seasonal regularity, which is greatly affected by human activities. The control variable method was employed on aerosol optical properties for better estimation of DARF. Single scattering albedo (SSA) has the greatest effect on DARF, followed by aerosol optical depth (AOD) and the asymmetric factor (ASY) among the seven examined stations in China. The average DARF decreases by 4.2 % when the SSA increases by 0.3 % but increases by 34.7 % when the SSA decreases by 3 % in mainland China. When the AOD changes from -60 to +60 %, DARF changes from -54.7 % to +58.4 %. The variation in DARF is between -3 % and +3 % when the ASY varies from -30 % to +30 %. The instability in DARF resulted from the complicated and volatile nature of aerosol optical properties in the region; the aerosol optical properties are greatly affected by the aerosol types and relative humidity. The results of this study have important reference significance for understanding the variation of DARF and formulating pollution prevention and control policies in the region.

Modeling impacts of mining activity-induced landscape change on local climate.

As a major energy source, coal has been mined on an increasingly larger scale as the social economy has continuously developed, resulting in drastic land type changes. These changes in turn cause changes in the local climate and affect the local ecological environment. Therefore, for coal cities, mining activities are an important factor influencing the local climate, and clarifying the impact of mining activities on the ecological environment is important for guiding regional development. In this paper, the impact of land use/cover changes (LUCCs) on local temperature in the spring and summer seasons from 1980 to 2018 was simulated using the Weather Research and Forecasting (WRF) model with Xilinhot city as the study area, and the regional distribution of local surface energy was analyzed in conjunction with the ground-air energy transfer process. The results show that the grassland area in Xilinhot remained above 85% from 1980 to 2018, so mining activities had a small impact on the average temperature of the whole region. However, in the mining area, the warming effect caused by mining activities was more obvious, with an average temperature increase of 0.822 K. Among other land transformation types, the conversion to water bodies had a very obvious cooling effect, lowering the temperature by an average of 2.405 K. By comparing the latent heat flux (LH), sensible heat flux (SH), and ground heat flux (GRD) under different land use types, it was found that in 2018, the LH decreased by 0.487 W/m2, the SH decreased by 0.616 W/m2, and the GRD decreased by 0.753 W/m2. The conversion to built-up urban land caused a significant decrease in the LH in the corresponding area, allowing more energy to be used to increase SH values, which resulted in significantly higher urban temperatures than in other areas.

The role of boundary layer height in India on transboundary pollutions to the Tibetan Plateau.

The aerosols over the Tibetan Plateau (TP) play an important role in radiative budget and hydrologic cycle over Asia even the northern hemisphere. Adjacent to the major emission sources of air pollutants, transboundary pollutions transported to the TP due to the unique geographical location and climatic characteristics, is an important exogenous driver of multi-layer changes over the TP. The influence of boundary layer height (BLH) in India to the transboundary pollution over the TP from 1980 to 2018 was investigated in the study. Results showed that air pollutants transported to the TP is more efficient within the boundary layer compared with free troposphere. The BLH decreases with the rate of 1.8 m/season in these decades. Moreover, it also has a significant correlation with AOD (-0.4). Accompanied with westerly wind and the topographic forcing in the higher boundary layer, dust particles were uplifted from the northern India to the high altitude. Compared with a higher BLH, the lower BLH is difficult for the long transport of pollutants with weaker westerly wind over the TP and its difference of dust concentration with 0.2 µg m-3 in the upper troposphere. The solar radiation enhancement increases the sensible heat and accelerate the upward of the atmosphere in high BLH events, which uplifts the pollutants accumulated in lower troposphere to higher altitudes and provides thermodynamic conditions for the pollutants transorted to the TP with westerly winds. This study provides confidence for the source, long-term transport of the TP aerosol, and its environmental and climatic impacts on climate systems in the Northern Hemisphere.

Environmental factors and spatiotemporal distribution characteristics of the global outbreaks of the highly pathogenic avian influenza H5N1.

The spread of highly pathogenic avian influenza H5N1 has posed a major threat to global public health. Understanding the spatiotemporal outbreak characteristics and environmental factors of H5N1 outbreaks is of great significance for the establishment of effective prevention and control systems. The time and location of H5N1 outbreaks in poultry and wild birds officially confirmed by the World Organization for Animal Health from 2005 to 2019 were collected. Spatial autocorrelation analysis and multidistance spatial agglomeration analysis methods were used to analyze the global outbreak sites of H5N1. Combined with remote sensing data, the correlation between H5N1 outbreaks and environmental factors was analyzed using binary logistic regression methods. We analyzed the correlation between the H5N1 outbreak and environmental factors and finally made a risk prediction for the global H5N1 outbreaks. The results show that the peak of the H5N1 outbreaks occurs in winter and spring. H5N1 outbreaks exhibit aggregation, and a weak aggregation phenomenon is noted on the scale close to 5000 km. Water distance, road distance, railway distance, wind speed, leaf area index (LAI), and specific humidity were protective factors for the outbreak of H5N1, and the odds ratio (OR) were 0.985, 0.989, 0.995, 0.717, 0.832, and 0.935, respectively. Temperature was a risk factor with an OR of 1.073. The significance of these ORs was greater than 95%. The global risk prediction map was obtained. Given that the novel coronavirus (COVID-19) is spreading globally, the methods and results of this study can provide a reference for studying the spread of COVID-19.