Poverty and income inequality are problems faced by many countries including China. Since the implementation of Targeted Poverty Alleviation (TPA), absolute poverty has been eradicated, meanwhile, Chinese rural residents' income and inequality have experienced unprecedented new dynamics, but still, very few studies have focused on them. Hence, we attempt to examine the new trends in Chinese farmers' income inequality and to understand its causes during this period. We observe that China's urban-rural income ratio has been shrinking and the urban-rural inequality has been decreasing from 2014 to 2021. The reduction in the Theil index indicates a decrease in the regional inequality of farmers' income as well, and the decline in inter-regional inequality among eight economic zones contributes about 80% to increased equality. These new trends are caused by the fact that, with the TPA, the incomes of rural residents especially that in destitute areas, grew faster than that of urban residents and farmers in prosperous areas. The higher share of non-agricultural industry and agricultural mechanization level have significant positive impact on regional equality of farmers' income, while urban-rural dual structure has significant negative inhibitory effects. The lowest farmers' income and the highest inequality in the Northwest, and the slowest growth in the Northeast deserve more attention in rural Revitalization. From these findings, we propose four policy implications that would be applied to improve Chinese farmers' income equality, govern relative poverty, and achieve common prosperity in the post-poverty era.

In the context of global research in snow-affected regions, research in the Australian Alps has been steadily catching up to the more established research environments in other countries. One area that holds immense potential for growth is hydrological modelling. Future hydrological modelling could be used to support a range of management and planning issues, such as to better characterise the contribution of the Australian Alps to flows in the agriculturally important Murray-Darling Basin despite its seemingly small footprint. The lack of recent hydrological modelling work in the Australian Alps has catalysed this review, with the aim to summarise the current state and to provide future directions for hydrological modelling, based on advances in knowledge of the Australian Alps from adjacent disciplines and global developments in the field of hydrologic modelling. Future directions proffered here include moving beyond the previously applied conceptual models to more physically based models, supported by an increase in data collection in the region, and modelling efforts that consider non-stationarity of hydrological response, especially that resulting from climate change.

Black carbon (BC) is a distinct type of carbonaceous aerosol that has a significant impact on the environment, human health, and climate. A non-BC material coating on BC can alter the mixing state of the BC particles, which considerably enhances the mass absorption efficiency of BC by directing more energy toward the BC cores (lensing effect). A lot of methods have been reported for quantifying the enhancement factor (Eabs), with diverse results. However, to the best of our knowledge, a comprehensive review specific to the quantification methods for Eabs has not been systematically performed, which is unfavorable for the evaluation of obtained results and subsequent radiative forcing. In this review, quantification methods are divided into two broad categories, direct and indirect, depending on whether experimental removal of the coating layer from an aged carbonaceous particle is required. The direct methods described include thermal peeling, solvent dissolution, and optical virtual exfoliation, while the indirect methods include intercept-linear regression fitting, minimum R squared, numerical simulation, and empirical value. We summarized the principles, procedures, virtues, and limitations of the major Eabs quantification methods and analyzed the current problems in the determination of Eabs. We pointed out what breakthroughs are needed to improve or innovate Eabs quantification methods, particularly regarding the need to avoid the influence of brown carbon, develop a broadband Eabs quantification scheme, quantify the Eabs values for the emissions of low-efficiency combustions, measure the Eabs of particles in a highhumidity environment, design a real-time monitor of Eabs by a proper combination of mature techniques, and make more use of artificial intelligence for better Eabs quantification. This review deepens the understanding of Eabs quantification methods and benefits the estimation of the contribution of BC to radiative forcing using climate models.

Groundwater (GW) is sensitive to climate change (CC), and the effects have become progressively more evident in recent years. Many studies have examined the effects of CC on GW quantity. Still, there is growing interest in assessing the qualitative impacts of CC, especially on GW temperature (GWT), and the consequences of these impacts. This study aimed to systematically review recently published papers on CC and GWT, determine the impacts of CC on GWT, and highlight the possible consequences. The Scopus and Web of Science databases were consulted, from which 144 papers were obtained. After an initial screening for duplicate papers, a second screening based on the titles and abstracts, and following an analysis of topic applicability to this subject after examining the full text, 44 studies were included in this review. The analysed scientific literature, published in 29 different journals, covered all five continents from 1995 to 2023. This review indicated that the subject of GWT variations due to CC is of global interest and has attracted significant attention, especially over the past two decades, with many studies adopting a multidisciplinary approach. A general increase in GWT was noted as a primary effect of CC (especially in urban areas); furthermore, the implications of this temperature increase for contaminants and GW-dependent ecosystems were analysed, and various applications for this increase (e.g. geothermal) were evaluated. This review highlights that GWT is vulnerable to CC and that the consequences can be serious and worthy of further investigation.

Significant progress in permafrost carbon science made over the past decades include the identification of vast permafrost carbon stocks, the development of new pan-Arctic permafrost maps, an increase in terrestrial measurement sites for CO2 and methane fluxes, and important factors affecting carbon cycling, including vegetation changes, periods of soil freezing and thawing, wildfire, and other disturbance events. Process-based modeling studies now include key elements of permafrost carbon cycling and advances in statistical modeling and inverse modeling enhance understanding of permafrost region C budgets. By combining existing data syntheses and model outputs, the permafrost region is likely a wetland methane source and small terrestrial ecosystem CO2 sink with lower net CO2 uptake toward higher latitudes, excluding wildfire emissions. For 2002-2014, the strongest CO2 sink was located in western Canada (median: -52 g C m-2 y-1) and smallest sinks in Alaska, Canadian tundra, and Siberian tundra (medians: -5 to -9 g C m-2 y-1). Eurasian regions had the largest median wetland methane fluxes (16-18 g CH4 m-2 y-1). Quantifying the regional scale carbon balance remains challenging because of high spatial and temporal variability and relatively low density of observations. More accurate permafrost region carbon fluxes require: (a) the development of better maps characterizing wetlands and dynamics of vegetation and disturbances, including abrupt permafrost thaw; (b) the establishment of new year-round CO2 and methane flux sites in underrepresented areas; and (c) improved models that better represent important permafrost carbon cycle dynamics, including non-growing season emissions and disturbance effects. Climate change and the consequent thawing of permafrost threatens to transform the permafrost region from a carbon sink into a carbon source, posing a challenge to global climate goals. Numerous studies over the past decades have identified important factors affecting carbon cycling, including vegetation changes, periods of soil freezing and thawing, wildfire, and other disturbance events. Overall, studies show high wetland methane emissions and a small net carbon dioxide sink strength over the terrestrial permafrost region but results differ among modeling and upscaling approaches. Continued and coordinated efforts among field, modeling, and remote sensing communities are needed to integrate new knowledge from observations to modeling and predictions and finally to policy. Rapid warming of northern permafrost region threatens ecosystems, soil carbon stocks, and global climate targets Long-term observations show importance of disturbance and cold season periods but are unable to detect spatiotemporal trends in C flux Combined modeling and syntheses show the permafrost region is a small terrestrial CO2 sink with large spatial variability and net CH4 source

Satellite-derived Land Surface Temperature (LST) dynamics have been increasingly used to study various geophysical processes. This review provides an extensive overview of the applications of LST in the context of global change. By filtering a selection of relevant keywords, a total of 164 articles from 14 international journals published during the last two decades were analyzed based on study location, research topic, applied sensor, spatio-temporal resolution and scale and employed analysis methods. It was revealed that China and the USA were the most studied countries and those that had the most first author affiliations. The most prominent research topic was the Surface Urban Heat Island (SUHI), while the research topics related to climate change were underrepresented. MODIS was by far the most used sensor system, followed by Landsat. A relatively small number of studies analyzed LST dynamics on a global or continental scale. The extensive use of MODIS highly determined the study periods: A majority of the studies started around the year 2000 and thus had a study period shorter than 25 years. The following suggestions were made to increase the utilization of LST time series in climate research: The prolongation of the time series by, e.g., using AVHRR LST, the better representation of LST under clouds, the comparison of LST to traditional climate change measures, such as air temperature and reanalysis variables, and the extension of the validation to heterogenous sites.

Glaciers are attracting increasing attention in the context of climate change, and glacier tourism has also become a popular tourist product. However, few studies have been conducted concerning the image of glacier tourism destinations. To address this gap in the literature, in this study, we extracted destination images from 138,709 visitor reviews of 107 glacier tourism destinations on TripAdvisor using latent Dirichlet allocation (LDA) topic modeling, identified destination image characteristics using salience-valence analysis (SVA), and analyzed the differences in glacier tourism destination image characteristics across seasons and regions. According to the findings, the image of a glacier tourism destination consists of 14 dimensions and 53 attributes, with landscapes and specific activities representing the core image and viewing location and necessity representing the unique image. We identified significant seasonal and regional differences in the image of glacier tourism destinations. Finally, we discussed the unique image of glacier tourism destinations, the reasons for differences in the images, and the characteristics of different glacier tourism regions. This research could assist in the scientific management of their core images by glacier tourism destinations, as well as in the rational selection of destinations and travel timing by glacier tourists.

A characteristic of frozen ground is a tendency to form banded sequences of particle-free ice lenses separated by layers of ice-infiltrated soil, which produce frost heave. In permafrost, the deformation of the ground surface caused by segregated ice harms engineering facilities and has considerable influences on regional hydrology, ecology, and climate changes. For predicting the impacts of permafrost degradation under global warming and segregated ice transformation on engineering and environmental, establishing appropriate mathematical models to describe water migration and ice behavior in frozen soil is necessary. This requires an essential understanding of water migration and segregated ice formation in frozen ground. This article reviewed mechanisms of water migration and ice formation in frozen soils and their model construction and introduced the effects of segregated ice on the permafrost environment included landforms, regional hydrological patterns, and ecosystems. Currently, the soil water potential has been widely accepted to characterize the energy state of liquid water, to further study the direction and water flux of water moisture migration. Models aimed to describe the dynamics of ice formation have successfully predicted the macroscopic processes of segregated ice, such as the rigid ice model and segregation potential model, which has been widely used and further developed. However, some difficulties to describe their theoretical basis of microscope physics still need further study. Besides, how to describe the ice lens in the landscape models is another interesting challenge that helps to understand the interaction between soil ice segregation and the permafrost environment. In the final of this review, some concerns overlooked by current research have been summarized which should be the central focus in future study.

The concentration of ice nucleating particles (INPs) in the atmosphere is critical for understanding cloud microphysics and predicting the climate system. In this study, we collected surface snow samples along a traverse route from the coastal to the inland of East Antarctica to analyze INP concentrations and identify their spatial variations using a drop-let freezing device. The overall concentration of INPs was found to be considerably low along the route, averaging at 0.8 & PLUSMN; 0.8 x 105 L-1 in water and 4.2 & PLUSMN; 4.8 x 10-3 L-1 in air at -20 & DEG;C. Although coastal areas had higher levels of sea salt species compared to inland regions, the concentration of INPs remained consistent along the route suggesting less important origination of INPs from the around ocean. Additionally, the heating experiment revealed the important contribution of proteinaceous INPs indicating the presence of biological INPs (bio-INPs). The fraction of bio-INPs was 0.52 on average at -20 & DEG;C and ranged from 0.1 to 0.7 from -30 & DEG;C to -15 & DEG;C. Finally, we parameterize the atmo-spheric INP concentrations as a function of freezing temperature which can be useful for modeling INP concentrations in this region.

Rapid climate warming has widely been considered as the main driver of recent increases in Arctic tundra productivity. Field observations and remote sensing both show that tundra greening has been widespread, but heterogeneity in regional and landscape-scale trends suggest that additional controls are mediating the response of tundra vegetation to warming. In this study, we examined the relationship between changes in vegetation productivity in the western Canadian Arctic and biophysical variables by analyzing trends in the Enhanced Vegetation Index (EVI) obtained from nonparametric regression of annual Landsat surface reflectance composites. We used Random Forests classification and regression tree modelling to predict the trajectory and magnitude of greening from 1984 to 2016 and identify biophysical controls. More than two-thirds of our study area showed statistically significant increases in vegetation productivity, but observed changes were heterogeneous, occurring most rapidly within areas of the Southern Arctic that were: (1) dominated by dwarf and upright shrub cover types, (2) moderately sloping, and (3) located at lower elevation. These findings suggest that the response of tundra vegetation to warming is mediated by regional- and landscape-scale variation in microclimate, topography and soil moisture, and physiological differences among plant functional groups. Our work highlights the potential of the joint analysis of annual remotely sensed vegetation indices and broad-scale biophysical data to understand spatial variation in tundra vegetation change.