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Evaluating, ranking, and clustering (ERC) stand as fundamental tasks in scientific research, each requiring a mathematical foundation. This study presents an ERC system anchored in the CCHZ-DISO (Chen, Chen, Hu, and Zhou-Distance between Indices of Simulation and Observation) system. Previous research underscores the optimality achieved by the CCHZ-DISO system (Hu et al., 2022). Since the inception of CCHZ- DISO-series research by Hu et al. (2019), DISO has found extensive applications across various domains including geography, hydrology, and economics. Analogous to the CCHZ-DISO system's construction, the ERC system employs the Euclidean distance to perform evaluating, ranking, and clustering tasks. Furthermore, illustrative examples are provided to elucidate the application of the ERC system. In fact, the ERC system unified the evaluating, ranking, and clustering tasks in one simple equation which is more flexible and simpler than the present system. It will have a more widely application than CCHZ-DISO in diverse scientific domains. [ABSTRACT FROM AUTHOR]

Light absorption and radiative forcing of black carbon (BC) is influenced by both BC itself and its interactions with other aerosol chemical compositions. Although the changes in BC concentrations in response to emission reduction measures have been well documented, the influence of emission reductions on the light absorption properties of BC and its influence on BC-boundary-layer interactions has been less explored. In this study, we used the online coupled WRF-Chem model to examine how emission control measures during the Asia-Pacific Economic Cooperation (APEC) summit affect the mixing state and light absorption of BC, and the associated implications for BC-PBL interactions. We found that both the mass concentration of BC and the BC coating materials declined during the APEC week, which reduced the light absorption and light absorption enhancement (Eab) of BC. The reduced absorption aerosol optical depth (AAOD) during APEC was caused by both the decline in the mass concentration of BC itself (52.0 %), and the lensing effect of BC (48.0 %). The reduction in coating materials (39.4 %) contributed the most to the influence of the lensing effect, and the reduced light absorption capability (Eab) contributed 3.2 % to the total reduction in AAOD. Reduced light absorption of BC due to emission control during APEC enhanced planetary boundary layer height (PBLH) by 8.2 m. PM 2.5 and O 3 were found to have different responses to the changes in the light absorption of BC. Reduced light absorption of BC due to emission reductions decreased near-surface PM 2.5 concentrations but near-surface O 3 concentrations were enhanced in the North China Plain. These results suggest that current measures to control SO 2 , NO x , etc. would be effective in reducing the absorption enhancement of BC and in inhibiting the feedback of BC on the boundary layer. However, enhanced ground O 3 might be a side effect of current emission control strategies. How to control emissions to offset this side effect of current emission control measures on O 3 should be an area of further focus. [ABSTRACT FROM AUTHOR]

Accurate information of crop rotation in large basin is essential for policy decisions on land, water and nutrient resources around the world. Crop area estimation using low spatial resolution remote sensing data is challenging in a large heterogeneous basin having more than one cropping seasons. This study aims to evaluate the accuracy of two phenological datasets individually and in combined form to map crop rotations in complex irrigated Indus basin without image segmentation. Phenology information derived from Normalized Difference Vegetation Index (NDVI) and Leaf Area Index (LAI) of Moderate Resolution Imaging Spectroradiometer (MODIS) sensor, having 8-day temporal and 1000 m spatial resolution, was used in the analysis. An unsupervised (temporal space clustering) to supervised (area knowledge and phenology behavior) classification approach was adopted to identify 13 crop rotations. Estimated crop area was compared with reported area collected by field census. Results reveal that combined dataset (NDVI*LAI) performs better in mapping wheat-rice, wheat-cotton and wheat-fodder rotation by attaining root mean square error (RMSE) of 34.55, 16.84, 20.58 and mean absolute percentage error (MAPE) of 24.56%, 36.82%, 30.21% for wheat, rice and cotton crop respectively. For sugarcane crop mapping, LAI produce good results by achieving RMSE of 8.60 and MAPE of 34.58%, as compared to NDVI (10.08, 40.53%) and NDVI*LAI (10.83, 39.45%). The availability of major crop rotation statistics provides insight to develop better strategies for land, water and nutrient accounting frameworks to improve agriculture productivity. [ABSTRACT FROM AUTHOR]