Spatial dynamics and influencing factors of carbon rebound effect in tourism transport: Evidence from the Yangtze-river delta urban agglomeration

Economic efficiency gains in tourism are considered a crucial approach to reducing carbon emissions in the tourism sector, especially in tourism transport. However, as a significant source of carbon emissions from tourism activities, the total carbon emissions from tourism transport have not decreased proportionally to the reduction in the intensity, despite China's overall improvement in the tourism economic efficiency. This phenomenon is commonly known as the "rebound effect", which means that although technological progress can achieve emission reductions by efficiency improvement, but it can also indirectly stimulate socio-economic growth and creates new energy demands, results in expected emission reductions being offset by the additional economic growth effect. Based on the multi-source data structure, this paper takes Yangtze-river delta urban agglomeration as an example, quantitatively evaluated the carbon rebound effect of tourism transport through the rebound effect measurement model; simulated the spatiotemporal dynamics evolution pattern of the carbon rebound effect in tourism transport through the spatial kernel density; extracted and identified the dominant factors of carbon rebound effect in tourism transport by the geographic detector. The conclusions summarized as follow: (1) The overall carbon emissions from tourism transport in the agglomeration primarily exhibit a weak rebound effect. (2) The carbon rebound effect is significantly influenced by spatiotemporal factors, which impact its development trend and interaction relations. (3) The level of tourism consumption exerts the greatest influence on the carbon rebound effect of tourism transport, while environmental regulation intensity is commonly employed as a measure to address the rebound effect. This paper aims to enhance the diversity of research on carbon emissions in tourism transport while addressing the existing limitations in spatial-temporal extension. The objective is to restrain the spread of the carbon rebound effect at the regional level, thereby providing a novel decision-making reference for the sustainable development of regional tourism.

Distinguishing the relative contributions of landscape composition and configuration change on ecosystem health from a geospatial perspective

Understanding the impact mechanisms of landscape composition and configuration change on ecosystem health (EH) is critical to ecosystem conservation and human well-being. However, existing studies mainly focused on EH changes due to combined effects of landscape composition and configuration change, while the individual impacts and spatial heterogeneity of these factors on EH remain unclear. Thus, taking Chongqing as an example, this study distinguished the relative contributions of landscape configuration and composition on EH based on scenario analysis method, and further explored how these impacts change between and within different topographic, geological and urbanization zones. The results showed that EH displayed an improving trend during 2000-2020, with the increasing areas distributed in the mountainous of southeast and northeast in Chongqing, largely influenced by increased forest landscape cohesion and their synergistic effects with forest expansion, accounting for 91.05 % and 87.86 % of the study area respectively, while the decreasing areas were mostly located in urban cores, dominated by changes in landscape composition (e.g. farmland reclamation and urban sprawl), accounting for 50.95 % of area proportion. The scenario analysis of EH showed that the areas dominated by landscape configuration were 5.39 times greater than the landscape composition under the same climate scenario. In terms of zoning comparison, the influence of landscape composition change on EH displayed the greatest difference within urbanization zones, while topographic zones for landscape configuration change. This paper provides a novel perspective to explore the impact of landscape pattern on EH, which is important to regional ecosystem conservation and land use management.

Quantifying the contribution of local drivers to observed weakening of spring dust storm frequency over northern China (1982-2017)

Recent studies have suggested that spring dust storm (SDS) events in northern China (NC) have exhibited substantial decline over the past 30 years. However, it is unclear which local factors are most responsible for the decline in SDS events, and the contribution of each dominant factor remains to be determined. This study utilized high-density DS records and collocated homogenized surface meteorological observations from 1982 to 2017, in conjunction with land surface products, to examine the local drivers that influence the long-term variation in SDS frequency (SDSF) over the entire NC area and its three dust-source areas: northwestern China (NWC), north-central China (NCC), and northeastern China (NEC). Results indicated that the observed SDSF averaged over NC, NWC, NCC, and NEC has decreased by 144.4 %, 109.3 %, 166.4 %, and 92.2 %, respectively, during 1982-2017. The variation in SDSF is largely explained by variation in wind speed (WS), precipitation, volumetric soil moisture, and surface bareness. A multivariable linear regression model incorporating these local drivers accounted for 81.0 %, 74.0 %, and 46.9 % of the variance in SDSF in NWC, NCC, and NEC, respectively. Statistical analyses on the local drivers suggested that weakening of WS was the dominant factor in the reduction in SDSF over recent decades, contributing 76.9 %, 54.7 %, and 33.6 % of the variation in NWC, NCC, and NEC, respectively. More importantly, we revealed that the interannual variation in regional SDSF was not only controlled by local drivers, but also influenced by cross-regional transport of dust aerosols emitted from upstream source areas.

Characteristic of water quality indicators and its response to climate conditions in the middle and lower reaches of Lijiang River, China

With global climate change and increasingly extreme weather conditions, the water quality of the Lijiang River Basin (LRB) is facing huge threats. At present, there is still a lack of systematic research on water quality indicators and the influence of indirect factors such as meteorological factors on it in the LRB. Therefore, this study is based on the meteorological, hydrological, and water quality data of the LRB from 2012 to 2018, using the Mann-Kendall test, Morlet wavelet method, Spearman's rank correlation coefficient, sensitivity, and contribution rate to quantitative analysis of the relationship between climate conditions and water quality indicators. The results show that the change trends of these hydrological and climatic conditions have almost no significant sudden change; precipitation and streamflow are decreasing each year; the streamflow trend exhibits time hysteresis; precipitation has a stronger influence downstream than on the local area; water quality indicators of both stations exhibited a change period of around 18 to 20 months, with the exception of pH. Water quality indicators are insensitive to precipitation and streamflow, and sensitive to humidity and wind speed; DO was negatively correlated with climate indicators apart from wind speed; almost all water quality indicators in Yangshuo are highly sensitive to air temperature, and the contribution rate of air temperature to ORP and TP reached 4.81% and 3.56%, respectively; sunshine duration has a positive impact on reducing NH₄-N and TP. The difference between Yangshuo and Guilin is mostly due to the input of external sources on both sides of the Lijiang River, which results in variations in climate conditions sensitivities.

Spatiotemporal heterogeneity and attributions of streamflow and baseflow changes across the headstreams of the Tarim River Basin, Northwest China

Understanding spatiotemporal heterogeneity of streamflow and baseflow and revealing their changes contributed by climatic factors and human activities in the alpine region of inland river basin are critical for regional water management. However, the hydrology heterogeneity in the alpine region has remained unclear, which limits the scientific understanding of the interaction mechanism between the hydrological cycle and terrain, and further constrains the effective utilization of regional water resources in the water-shortage areas. In this study, the hydrological process and regimes for headstreams of Tarim River Basin (HTRB) during 1985-2011 were simulated by the Soil and Water Assessment Tool. We systematically characterized the spatial and temporal patterns of streamflow and baseflow through geostatistical and trend analyses, and subsequently investigated their heterogeneity responses to climate change and human activities at different sub-basins and elevation zones. Results show that the spatial distributions of streamflow and baseflow are highly related to terrain and river direction. Increased trends in precipitation enhanced with altitude, whereas decreased trends in potential evapotranspiration (PET) weakened with altitude, meanwhile, increased trends in streamflow and baseflow of HTRB are most pronounced in mid-altitude areas during 1985-2011. The climate elasticities of streamflow and baseflow are highly reliant on the altitudinal gradient. Increases in streamflow and baseflow in high-lying areas are more sensitive to precipitation variation, while they are more sensitive to PET change in low-lying areas. The magnitude and change rate with altitude bands of the precipitation has greater effects on streamflow and baseflow variations than those of PET. Furthermore, the percentage of sub-basins where climate changes dominate streamflow variation in each elevation band increases with height but decreases abruptly at elevations above 5000 m. The percentage of sub-basins where climate changes dominate baseflow variations gradually decreases in elevation bands above 3000 m. Our results indicate that climate change rather than human activities dominants the variation in streamflow and baseflow in most sub-basins and elevation bands.

The influence of local background climate on the dominant factors and threshold-size of the cooling effect of urban parks

Urban parks can mitigate the urban heat island (UHI) by creating microclimates that lower in temperature than their surroundings, which are known as park cooling effect (PCE). The local background climate has a significant impact on the PCE, however the dominant factors and threshold value of efficiency (TVoE) of the PCE under different local background climates are still uncertain. Here, we selected 207 urban parks in 27 cities in East China with four different local background climates, warm temperate sub-humid monsoon (WTC), northern subtropical sub-humid monsoon (NSC), northern subtropical humid monsoon (NHC), and middle subtropical humid monsoon climate (MSC), for comparative studies. The relative contributions of multi-influencing factors to the PCE and TVoE of urban parks were quantified through a multivariate stepwise regression model and curve fitting. The results show that: (1) PCE increases from WTC, NSC, NHC to MSC, and urban parks at low latitudes have a greater cooling effect in general than those at high latitudes; (2) the area of the park is the dominant factor of PCE under four different local background climates (the explanation rate exceeds 50%) and water bodies within urban parks play a more significant role in the cooling effect in high latitudes, dry areas; (3) the TVoE of park on WTC, NSC, NHC, and MSC are 0.81, 0.71, 0.70, and 0.66 ha, respectively, revealing that the background climate significantly affects the TVoE. These findings are essential to decision-makers and can provide actionable knowledge for climate adaptation planning on a regional (climate) scale.

Factors dominating the horizontal and vertical variability of soil water vary with climate and plant type in loess deposits

Identifying the variability and predominant factors affecting soil water (SW) is essential in regions with thick vadose zones and deep-rooted plants. This information is needed to clarify the balance between water availability and plant water demand. We collected 9263 soil samples from 128 profiles of 7-25 m deep soil under different climates (arid, semiarid and subhumid), soil textures and plant types (shallow or deep roots) in China's Loess Plateau. The factors dominating the horizontal and vertical variability of SW were identified using a multimodel inference approach and stepwise regression analysis. Horizontally, the mean water content and storage increased while the water deficits decreased from the northwest to the southeast. Vertically, mean water content and storage are highest in the relatively stable layer, followed by rapidly changing layers and active layers. Plant age and soil clay content dominate the horizontally varied SW, while plant age and normalized difference vegetation index (NDVI) dominate the vertical variability of SW. However, the dominant factors appeared to differ with climate and plant type. It was determined that for climate, soil clay content and plant age in arid regions, precipitation and plant age in semiarid regions, NDVI and plant age in subhumid regions were important factors. For plants, the dominant factors are NDVI and precipitation under shallow-rooted plants; however, NDVI and plant age were dominant under deep-rooted plants. The dominance of plant age highlighted the impact of vegetation patterns on SW, especially for deep-rooted plants, which should be taken into account when managing water resources and ecosystem rehabilitation in degraded regions.

Attribution of streamflow changes across the globe based on the Budyko framework

Differentiating and clarifying the driving factors behind streamflow changes are critical for highlighting hydrological responses to changing environments. However, due to the limited number of hydrological stations, the dominant factor controlling global observed streamflow change remains unclear and intensely debated. Here, we revisit this scientific issue by using the most comprehensive dataset to attribute the observed global streamflow changes during 1960-2014. The results suggest that other factors than precipitation (P) and potential evaporation (E₀) are the most important contributors to global observed streamflow changes, which dominate streamflow change for 48.9-50.9% of the stations. In contrast, the dominant factor translated into P in 72.3-72.9% of stations when using reconstructed streamflow datasets, in agreement with most previous global assessments. These differences indicate that streamflow attributions using reconstructed streamflow might overestimate the effects of P while underestimating the roles of other factors, such as the vegetation and human impact. At the global scale, the other factors affected by many catchment characteristics and their impacts on streamflow change have remarkable regional differences. This study highlights the necessity to apply the observed data in streamflow attribution to avoid biased conclusions regarding the dominant factor of streamflow changes.