Natural Factors Research Articles

Assessment of eco‐environmental changes along roads in the Qinghai‐Tibetan Plateau based on remote sensing data: A case study of the Sino‐Nepalese Transport Corridor

AbstractUnderstanding the evolutionary patterns of ecological quality in transport corridor areas and their driving mechanisms is essential for maintaining regional sustainable development. However, an integrated assessment of the ecology of plateau transport corridors is still lacking. This study focuses on the Sino‐Nepalese Transport Corridor (SNTC) and comprehensively evaluates the spatio‐temporal patterns and evolution of eco‐environmental quality from 2000 to 2021 based on remote sensing data and quantifies and explores the potential driving factors. The results indicate significant spatial heterogeneity in the eco‐environmental quality of the SNTC, with an overall bipolar “northeast‐southwest” distribution pattern. The area of poor and worse quality is the largest (32,471.75 km2), accounting for about 47.20% of the total area of the SNTC, distributed in the plateau bare land and the Yarlung Tsangpo River valley. From 2000 to 2021, the eco‐environmental quality showed an initial decline and then an increase, with a relatively gentle overall trend. The increase in the remote sensing ecological index in Region (I) from 0.314 in the first 10 years to 0.334 in the second 10 years, an increase of 6.37%, was mainly attributed to afforestation projects in the “One River and two tributaries Nature Reserve” region. The eco‐environmental quality of the SNTC is influenced by multiple factors including human activities, climate, and topography. Grazing intensity, population density, and digital elevation model are the main negative disturbance factors, while temperature, precipitation, gross domestic product, and afforestation areas promote eco‐environmental quality. In particular, afforestation projects partially offset the negative impact of human activities. These results will provide useful information for understanding the complex effects of human activities and natural factors on the eco‐environmental quality in the plateau transport corridor region and for formulating ecological conservation policies.

A vulnerability evaluation method of earthen sites based on entropy weight-TOPSIS and K-means clustering

The degradation of earthen sites due to natural and human factors has become a pressing issue, necessitating urgent protection measures. In this context, accurate assessment of the vulnerability of earthen sites is essential for the development of effective conservation strategies. In this study, a comprehensive evaluation framework that incorporates multiple indicators is proposed. In particular, the entropy weight- (Technique for Order Preference by Similarity to an Ideal Solution) TOPSIS method is employed for quantitative vulnerability assessment and combined with K-means clustering to define vulnerability levels for earthen sites. To validate the proposed approach, the vulnerability of 29 sections of the Ming Great Wall is evaluated. Eventually, the 29 earthen sites are categorized into three levels: high, medium, and low, according to their degree of vulnerability. The results of gray correlation analysis and entropy weight-TOPSIS method are compared using the ontology missing amount in the original data as the validation standard. The results show that the Pearson correlation coefficient value of the entropy weight-TOPSIS method with the ontology missing amount was 0.859, while the Pearson correlation coefficient value of the gray correlation analysis method with the ontology missing amount was 0.691, so that the results of the entropy weight-TOPSIS method can more accurately reflect the actual vulnerability of earthen sites.

Continuing benefits of the Montreal Protocol and protection of the stratospheric ozone layer for human health and the environment.

The protection of Earth's stratospheric ozone (O3) is an ongoing process under the auspices of the universally ratified Montreal Protocol and its Amendments and adjustments. A critical part of this process is the assessment of the environmental issues related to changes in O3. The United Nations Environment Programme's Environmental Effects Assessment Panel provides annual scientific evaluations of some of the key issues arising in the recent collective knowledge base. This current update includes a comprehensive assessment of the incidence rates of skin cancer, cataract and other skin and eye diseases observed worldwide; the effects of UV radiation on tropospheric oxidants, and air and water quality; trends in breakdown products of fluorinated chemicals and recent information of their toxicity; and recent technological innovations of building materials for greater resistance to UV radiation. These issues span a wide range of topics, including both harmful and beneficial effects of exposure to UV radiation, and complex interactions with climate change. While the Montreal Protocol has succeeded in preventing large reductions in stratospheric O3, future changes may occur due to a number of natural and anthropogenic factors. Thus, frequent assessments of potential environmental impacts are essential to ensure that policies remain based on the best available scientific knowledge.

Lake Kinneret and Hula Valley Ecosystems under Climate Change and Anthropogenic Involvement

The long-term record of ecological, limnological and climatological parameters that were documented in the Kinneret drainage basin was statistically evaluated. The dependent relations between environmental parameters and a change in climate conditions open a consequence dispute between three optional definitions: long-term instability, climate change impact and ecosystem resiliency. The Kinneret drainage basin during the Anthropocene era is marked by intensive anthropogenic involvement: Increase in population size, drainage of the wetlands and old lake Hula, agricultural development, enhancement of lake Kinneret utilization for water supply, hydrological management, fishery and recreation. Therefore, the impact of a combination of natural and anthropogenic environmental factors confounded each other, and the uniqueness of climate change is unclear.

Application of Machine Learning in Ecological Red Line Identification: A Case Study of Chengdu–Chongqing Urban Agglomeration

China’s Ecological Protection Red Lines (ERLs) policy has proven effective in constructing regional ecological security patterns and protecting ecological space. However, the existing methods for the identification of high conservation value areas (HCVAs) usually use physical models, whose parameters and processes are complex and only for a single service, affecting the ERL delineation. In this study, the data-driven machine learning (ML) models were innovatively applied to construct a framework for ERL identification. First, the One-Class Support Vector Machine (OC-SVM) was used to generate negative samples from natural reserves and ecological factors. Second, the supervised ML models were applied to predict the HCVAs by using samples. Third, by applying the same ecological factors, the traditional physical models were used to assess the ecological services of the study area for reference and comparison. Take Chengdu–Chongqing Urban Agglomeration (CY) as a case study, wherein data from 11 factors and 1822 nature reserve samples were prepared for feasibility verification of the proposed framework. The results showed that the area under the receiver operating characteristic curve (AUC) of all ML models was more than 97%, and random forest (RF) achieved the best performance at 99.57%. Furthermore, the land cover had great contributions to the HCVAs prediction, which is consistent with the land use pattern of CY. High-value areas are distributed in the surrounding mountains of CY, with lush vegetation. All of the above results indicated that the proposed framework can accurately identify HCVAs, and that it is more suitable and simpler than the traditional physical model. It can help improve the effectiveness of ERL delimitation and promote the implementation of ERL policies.

Microplastics in Chinese coastal waters: A mini-review of occurrence characteristics, sources and driving mechanisms.

The oceans are facing global and irreversible pollution from microplastics, and China is not immune. In this mini-review, information on microplastics in four coastal waters of China and the natural and social environment of key basins were compiled. The results showed that microplastics were ubiquitous in the coastal waters, and the abundance and spatial distribution of microplastics varied significantly under different sampling methods. For trawl samples, microplastic abundance ranged from 0.045 to 1170.8 items m-3, among which the coastal waters of the East China Sea were the most polluted. For filtered samples, microplastic abundance ranged from 46 to 63,600 items m-3, and the coastal waters of the Yellow Sea were the most polluted. Meanwhile, human activities in basin were the key factors affecting microplastic pollution in coastal waters. The main terrestrial source in the coastal waters of the South China Sea was express packaging loss, whereas the main source in the other coastal waters was tyres and road markings wear from vehicle trip. The decoupling results of analytic hierarchy process showed that there was spatial heterogeneity in the impact of socio-economic and natural environmental factors in the basin on the distribution of microplastics in coastal waters. Among the five major basins, the impact weights of the latter were 20.00%, 83.34%, 66.66%, 50.00% and 25.00%, respectively. This study provides the first perspective of land-sea linkage to summarize the characteristics, sources and influencing factors of microplastics in Chinese coastal waters, providing ideas for reducing marine microplastic pollution from the source.

Study on the Evaluation of Urban Park Landscape Pattern Index and Its Driving Mechanisms in Nanchang City

Urban planning is often influenced by industrial and construction activities, leading to a lack of attention to the planning and construction of urban parks, which results in prominent spatial layout problems. Urban parks, as an important part of the urban green space system, play a significant role in improving the ecological environment, promoting urban economic development, and enhancing the daily living standards of the people. As a typical representative of China’s second and third-tier cities, Nanchang’s analysis of the evolution process of urban landscape patterns has reference significance for other similar cities in China. This paper is based on the theoretical foundations of landscape ecology, human geography, and urban planning, and analyzes the evolution of the park landscape pattern in the central urban area of Nanchang from 1999 to 2019 from the perspective of urban context, revealing the driving mechanisms. It provides important references and bases for the further optimization and construction development of the park landscape pattern in Nanchang. The results show that the park area and number in the central urban area of Nanchang have significantly increased, with the overall layout evolving from “central aggregation” to “core aggregation in each area”, and from “central scarcity, more on the periphery” to “inward concentration, outward diffusion”. However, the distribution of various types of parks is uneven, and there is a lack of green corridor links between parks. The park landscape pattern is driven by multiple factors such as natural factors of urban context, socio-economic factors, urban construction factors, historical policies, and related planning, which can have positive or negative effects. Incorporating relevant urban factors into the park planning system analysis can promote the benign development of urban context and park landscape layout, thereby achieving the “parkification” of the city.

Identification of Important Wetlands and Optimization of Landscape Patterns Based on Human Pressure Index: The Case of the Linghekou Wetland in China

The Linghekou wetland is a rich repository of ecological resources and serves as an important habitat for numerous rare and protected animals. However, due to a confluence of natural and anthropogenic factors, the ecological environment of the Linghekou wetland is facing a multitude of threats, including the reduction in wetland area, the degradation of wetland resources, and the instability of ecological structure. This paper employs an anthropogenic focus, utilizing the human pressure index (HPI), spatial autocorrelation, and cold and hot spot methods to identify crucial wetlands. These identified wetlands are then utilized as ecological source sites to optimize the landscape pattern of the Linghekou wetland, employing the minimum cumulative resistance (MCR) model. The final results indicated the identification of 6 ecological sources, 8 ecological corridors, and 42 ecological nodes. These were primarily concentrated in the southern region of the study area and were distributed in a reasonable manner. The method of identifying ecological sources when optimizing the landscape pattern with the MCR model was enriched by this approach. Additionally, the paper offers recommendations for the optimization of the landscape pattern of the Linghekou wetland and establishes a foundation for the protection and restoration of other similar wetlands.

Response mechanism of rodent burrow density to natural environmental factors in desert areas based on multisource data

Timely and accurate prediction and early warning of rodent infestation are highly important for the sustainable development of desert ecosystems. This study combines data from 1376 UAV images of actual rodent burrows with natural environmental factor data, aiming to reveal the mechanism through which these factors affect rodent burrow density in the desert areas. The relationships between rodent burrow density and the 9 plant communities and 34 plant species in this area were analyzed by the K-W test and Spearman rank correlation analysis, respectively. The Boruta algorithm and the boosted regression trees (BRT) model were used to determine the six main factors influencing rodent burrow density from a total of 32 factors and to determine the distribution pattern of the burrows. The results show that (1) the density of rodent burrows in the Junggar Basin desert area gradually decreases from south to north and from west to east. (2) There were significant differences in rodent burrow density across the different plant community types (P = 0.048**). A total of 50.0 % of the species significantly influenced rodent burrow density at at least one level. (3) Among the 17 factors with lag effects, nine had the most significant correlation with rodent burrow density in April. Only two natural environmental factors demonstrated lag effects of less than one month. (4) The soil clay content, elevation, Normalized Difference Salinity Index (NDSI), vegetation cover, precipitation, and soil bulk density were the most important influencing factors on rodent burrow density. Considering the pairwise interactions among factors, the collective impact of these factors on rodent burrow density is at least sevenfold greater than the independent effect of a single factor. This study provides a theoretical basis for obtaining a timely and accurate understanding of the spatial distribution of rodent burrows, mitigating the degradation trend of desert ecosystems, and ensuring healthy and sustainable development.

Analysis of surface deformation and related factors over mining areas based on InSAR: A case study of Fengcheng mine

Abstract. Ground surface deformation in mines affects mining production, damages the ecological environment, and endangers human safety. Mastering the detailed time series deformation and related triggering factors can provide key information for the safety of the mining area. Therefore, the Fengcheng mining area, a large and ancient coal mine in Jiangxi Province, China, was selected as the study area in this work, and the following research was conducted: 1. The accuracy and applicability of the Stacking, Small-Baseline Subset InSAR (SBAS-InSAR), and Interferometric Point Target Analysis (IPTA) methods were preliminarily explored while monitoring the annual deformation rate based on Sentinel-1A data from October 2019 to November 2022. 2. The time-series deformation of the Fengcheng mining area was obtained with SBAS-InSAR technology, and the sedimentation was validated with leveling results. 3. The correlation factors of deformation, such as rainfall and land cover, were studied, and the relationship between the influencing factors, such as coal mining dip angle, digital elevation, coal mining elevation, and deformation, was quantitatively explored with the Grey correlation model and Pearson correlation analysis method. The following conclusions were drawn: The SBAS method has the best adaptability in the dense vegetation mining area, and the root-mean-square error of the difference between deformation results and leveling data does not exceed 4mm. The evolution process of deformation centers is mainly divided into the stages of initial deformation, constant velocity deformation, accelerated deformation, and stable condition. Compared with the natural factors, the settlement of the Fengcheng mining area is mainly affected by human-induced mining and construction of artificial facilities.

Determination of the Radioactive Nature of the Sediments of the Bays of the Ebrié Lagoon of Abidjan, Ivory Coast

In Ivory Coast, the lagoons represent the transit point for the majority of continental inputs. They are thus increasingly vulnerable and their ecological balance is rapidly modified under the influence of certain natural or anthropogenic factors. The objective of this study is to evaluate the level of presence of lead 210 in sediments. The sediments were sampled during the campaigns of the National Water Quality Observation Network on the bays spread over thirteen study sites. Analysis by alpha spectrometry was carried out in three stages (mineralization with concentrated acids, self-deposition on a silver disk, counting in an alpha detector with a silicone surface barrier). The highest lead-210 activities were obtained in the bays of Koumassi 1 (228.57 ± 12.21 Bq/kg) and Marcory (198.91 ± 9.46 Bq/kg). However, no seasonal variation in lead-210 contamination of sediments in the bays of Abidjan was observed. We wish to extend this study to other aquatic matrices.

Review on Design and Fabrication of Solar Panel Cleaning Mechanism

Today energy demands are increasing sharply therefore as a Renewable source of power, solar energy has an important role in producing the electricity direct from sunlight. The surface of solar panel in solar power plants becomes dirty due to natural factors such as dust and bird droppings. This project aims at increasing the efficiency of solar power plants by solving the problem of accumulation of dust on the surface of solar panel which leads to reduction in plant output and overall plant efficiency. It proposes to develop a Solar Panel Cleaning System which could remove the accumulated dust on its surface on a regular basis and maintain the solar power plant output.[8]

Interrelationship Among Soil Parameters and their Alteration with Seasonal Changes in the Soil of Bawal Town, Haryana

Soil is the backbone of agriculture and original source of nutrient that are needed by plants and crops to grow and survival. It is governed by various factors like anthropogenic and natural factors. In this study we aim to interpret the effect of climatic changes mainly seasonal variations on the soil health of Bawal industrial area. Samples were collected at the depth of 15 cm, from three different sites in three different seasons; summer, winter and monsoon. Samples were analyzed for pH, Electrical conductivity (EC), Organic matter (OM), Available nitrogen (N), potassium (K), phosphorus (P) Magnesium (Mg) and Sodium (Na). Results revealed that the OM, K, P, and Na concentration of the soil were found to follow the order; winter>rainy>summer. In contrast to this, Soil pH and Mg content were reported their highest concentration in summer followed by winter and least in monsoon season. EC and N content were found to follow the order; rainy season > winter > summer. Statistical analysis concluded the significant variation in physiochemical parameters of soil with variation in seasons except pH and EC (in summer and winter season). Interdependency of soil parameters was interpreted using multiple linear regression and results highlight that, Soil pH and Mg content were showing a significant linear regression with R2 (0.890). Na showed a significant R2 with K (0.855), P (0.827) and OM (0.803). Nitrogen content had found to show good regression with EC and soil pH. Organic matter and Potassium were also reporting significant R2 values (0.931). Soil fertility was found to get affected by climatic change but the variations could be utilized by cultivating the suitable crops according to soil parameter contents in a particular season.

Spatial variability and source analysis of soil heavy metals: A case study of the key planting area of special agricultural products in Cangxi County, China.

Heavy metal pollution in farmland soil represents a considerable risk to ecosystems and human health, constituting a global concern. Focusing on a key area for the cultivation of special agricultural products in Cangxi County, we collected 228 surface soil samples. We analyzed the concentration, spatial distribution, and pollution levels of six heavy metals (Cr, Cu, Pb, Ni, Zn, and Hg) in the soil. Moreover, we investigated the sources and contribution rates of these heavy metals using Principal Component Analysis/Absolute Principal Component Scores (PCA/APCS) and Positive Matrix Factorization (PMF) models. Our findings indicate that none of the six metals exceeded the pollution thresholds for farmland soils. However, the mean concentrations of Cr and Ni surpassed the background levels of Sichuan Province. A moderate spatial correlation existed between Pb and Ni, attributable to both natural and anthropogenic factors, whereas Zn, Cu, Hg, and Cr displayed a strong spatial correlation, mainly due to natural factors. The spatial patterns of Cr, Cu, Zn, Pb, and Ni were similar, with higher concentrations in the northern and eastern regions and lower concentrations centrally. Hg's spatial distribution differed, exhibiting a broader range of lower values. The single pollution index evaluation showed that Cr and Ni were low pollution, and the other elements were no pollution. The average value of comprehensive pollution index is 0.994, and the degree of pollution is close to light pollution. Predominantly, higher pollution levels in the northern and eastern regions, lower around reservoirs. The PCA/APCS model identified two main pollution sources: agricultural traffic mixed source (65.2%) and natural parent source (17.2%). The PMF model delineated three sources: agricultural activities (32.59%), transportation (30.64%), and natural parent sources (36.77%). Comparatively, the PMF model proved more accurate and reliable, yielding findings more aligned with the study area's actual conditions.

The spatial differentiation of human-environment relationship in mountain tourism destination, based on the image data of Landsat-8

Mountain is the most traditional tourism destination in China. On the basis of analyzing the particularity and its spatial differentiation of human-environment relationship in mountain tourism destination, this paper conducts empirical analysis in Yulong Snow Mountain by land use type classification. Firstly, ENVI is used to preprocess the Landsat-8 images of the research area. Then the visual interpretation is performed by ArcGIS to classify land use types. Based on the above, the differentiation status of human-environment relationship is analyzed. It concluded that: (1) Under the influence of natural factors such as piedmont, climate, altitude, gradient, slope, geological environment, and geomorphic characteristics, the uneven spatial distribution of human-environment relationship in mountain tourism destination is greatly affected by vegetation, rainfall, heat distribution, wind direction, suitability for human activities, and especially the topography; (2) The Yulong Snow Mountain forms three distinct levels of spatial differentiation in human-environment relationships between the east and west slopes, between high, medium and low elevations, and between different gradients.

Determination of the temporal–spatial distribution patterns of ancient heritage sites in China and their influencing factors via GIS

In this paper, we analysed the temporal and spatial distributions of ancient archaeological sites in China as well as their influencing factors. Our aim was to reveal the developmental trajectory of Chinese civilisation and to explore the natural and cultural factors affecting human distribution, with the goal of providing insights for the conservation and development of ancient relics. We employed spatial analysis methods using ArcGIS 10.8 software, such as kernel density analysis and trend surface analysis, to analyse 1194 historical ancient sites listed in the National Cultural Relics Protection Units of China. The research findings are as follows: (1) the distribution of ancient sites demonstrates an agglomerative spatial pattern. The nearest neighbour index (R < 1) for sites from various historical periods indicates an agglomerative spatial distribution of ancient sites across historical periods, with the clustering degree being relatively poor for sites from the Wei-Jin, Northern and Southern Dynasties and in the Ming and Qing periods. The regions with a concentration of ancient sites are the middle and lower reaches of the Yangtze River and Yellow River Basins. Furthermore, there is a higher abundance of ancient sites in the southeastern region than in the northwestern region. (2) The distribution of ancient sites in different historical periods also exhibits an imbalance, with an overall decreasing trend in the number of ancient sites in China. Notably, more ancient sites were found for the prehistoric and pre-Qin periods. The temporal trend of ancient sites during historical periods follows a trajectory from northeast to northwest, northeast to southwest, etc. (3) The temporal and spatial distributions of ancient sites are influenced by multiple factors, including social development, the natural environment, geographical elements, and socioeconomic and political factors. Finally, based on an understanding of the spatiotemporal distribution pattern of ancient sites and the factors that influence this pattern, recommendations for conservation and development can be proposed and supported by modern technological methods, with the aim of offering insights for the protection and sustainable development of heritage sites.

Exploring Ecological Management Plans for Typical Systems in Arid Areas from the Perspective of Ecosystem Service Value Evolution

Ecological management zoning plays a significant role in optimizing resource utilization, improving ecosystem service function, and promoting coordinated regional development. Taking Hexi Corridor as a representative region of the Mountain–Oasis–Desert composite system in arid regions of Asia, this study analyzed the spatial and temporal evolution of ecosystem service values and explored the influencing mechanism based on the optimal parameters-based geographical detector model. We have comprehensively divided ecological management zones and proposed corresponding control strategies. The results show that (1) the Hexi Corridor is characterized by regional differentiation, which is composed of three systems: The southern mountain system, central oasis system, and northern desert system. The mountain system is mainly composed of forestland and grassland, the oasis system is mainly composed of cropland, and the desert system is mainly composed of unused land. The conversion of land use mainly involves the conversion of unused land to cropland and grassland, while grassland is mainly converted to cropland. (2) The ecosystem service value of the Hexi Corridor increased significantly and demonstrated agglomeration characteristics in space. The highest value areas are mainly distributed in the southern mountain, with higher value and medium areas mainly distributed in the central oasis, and the lowest value areas are mainly located in the northern desert. (3) Socio-economic factors greatly influence the spatial differentiation of ecosystem service values in the Hexi Corridor, with natural environmental factors having less impact. Additionally, the internal interaction of natural environmental factors is the most significant. (4) The Hexi Corridor is divided into three ecological management zones: Ecological function protection zone, ecological and agricultural coordinated development zone, and ecological and urbanization coordinated development zone. This research has important reference value for global ecological management in arid regions.

Challenges for sustainable development goal of land degradation neutrality in drylands: Evidence from the Northern Slope of the Tianshan Mountains, China

The SDG 15.3.1 target of Land Degradation Neutrality (LDN) only has 15 years from conception (in 2015) to realization (in 2030). Therefore, investigating the effectiveness and challenges of LDN has become a priority, especially in drylands, where fragile ecosystems intersect with multiple disturbances. In this study, solutions are proposed and validated based on the challenges of LDN. We chose the Northern Slope of the Tianshan Mountains as a case study and set baselines in 2005 and 2010. The region and degree of land change (including degraded, stable, and improved) were depicted at the pixel scale (100 × 100 m), and LDN realization was assessed at the regional scale (including administrative districts and 5000 × 5000 m grids). The results showed a significant disparity between the two baselines. The number of areas that realized the LDN target was rare, regardless of the scale of the administrative districts or grids. Chord plots, Spearman's correlation, and curve estimation were employed to reveal the relationship between LDN and seven natural or socioeconomic factors. We found that substantial degradation was closely related to the expansion of unused, urban, and mining land and reduction in water, glaciers, and forests. Further evidence suggests that agricultural development both positively and negatively affects LDN, whereas urbanization and mining activities are undesirable for LDN. Notably, the adverse effects of glacier melting require additional attention. Therefore, we consider the easy-to-achieve and hard-to-achieve baselines as the mandatory and desirable targets of LDN, respectively, and focus further efforts in three aspects: preventing agricultural exploitation from occupying ecological resources, defining reasonable zones for urbanization and mining, and reducing greenhouse gas emissions to mitigate warming. Overall, this study is expected to be a beneficial addition to existing LDN theoretical systems and serve as a case validation of the challenges of LDN in drylands.

Spatio-temporal Variation in NEP in Ecological Zoning on the Loess Plateau and Its Driving Factors from 2000 to 2021

Net ecosystem productivity (NEP) is an important index for the quantitative evaluation of carbon sources and sinks in terrestrial ecosystems. Based on MOD17A3 and meteorological data, the vegetation NEP was estimated from 2000 to 2021 in the Loess Plateau (LP) and its six ecological subregions of the LP (loess sorghum gully subregions:A1, A2; loess hilly and gully subregions:B1, B2; sandy land and agricultural irrigation subregion:C; and earth-rock mountain and river valley plain subregion:D). Combined with the terrain, remote sensing, and human activity data, Theil-Sen Median trend analysis, correlation analysis, multiple regression residual analysis, and geographic detector were used, respectively, to explore the spatio-temporal characteristics of NEP and its response mechanism to climate, terrain, and human activity. The results showed that:① On the temporal scale, from 2000 to 2021 the annual mean NEP of the LP region (in terms of C) was 104.62 g·(m2·a)-1. The annual mean NEP for both the whole LP and each of the ecological subregions showed a significant increase trend, and the NEP of the LP increased by 6.10 g·(m2·a)-1 during the study period. The highest growth rate of the NEP was 9.04 g·(m2·a)-1, occurring in the A2 subregion of the loess sorghum gully subregions. The subregion C had the lowest growth rate of 2.74 g·(m2·a)-1. Except for the C subregion, all other ecological subregions (A1, A2, B1, B2, and D) were carbon sinks. ② On the spatial scale, the spatial distribution of annual NEP on the LP was significantly different, with the higher NEP distribution in the southeast of the LP and the lower in the northwest of the LP. The high carbon sink area was mainly distributed in the southern part of the loess sorghum gully subregions, and the carbon source area was mainly distributed in the northern part of the loess sorghum gully subregions and most of the C subregion. The high growth rate was mainly distributed in the central and the southern part of the A2 subregion and the southwest part of the B2 subregion. ③ Human activities had the greatest influence on the temporal variation in NEP in the LP and all the ecological subregions, with the correlation coefficient between human activity data and NEP being above 0.80, and the relative contribution rates of human factors was greater than 50%. The spatial distribution was greatly affected by meteorological factors, among which the precipitation and solar radiation were the main factors affecting the spatial changes in the NEP of the LP. The temporal and spatial variations in the NEP in the LP were influenced by natural and human social factors. To some extent, these results can provide a reference for the terrestrial ecosystem in the LP to reduce emissions and increase sinks and to achieve the goal of double carbon.

Understanding the spatiotemporal distribution of aerosols and their association with natural and anthropogenic factors over Saudi Arabia using multi-sensor remote sensing data

Understanding the spatiotemporal distribution of aerosols and their association with natural and anthropogenic factors over Saudi Arabia using multi-sensor remote sensing data