RESUMEN

Improving water quality to provide freshwater is an urgent requirement for regional and even global social development. More accurate simulation of non-point sources pollution, monitored mainly by total nitrogen (TN) and total phosphorus (TP), has always been a challenge for InVEST water purification model, particularly in agricultural areas. This can be attributed to the fact that there is no reference data for TN and TP to rectify the outcomes modelled by this model. This paper provided these data to rectify simulation results of TN and TP to ensure their accuracy. The Huai River watershed (HRW) is an important grain production area with slow economic development, and non-point source pollution has exceeded point-source pollution. There is an urgent need for water management authorities to obtain complete spatio-temporal data on TN and TP loads and their exports to improve water quality. The reference data onloads and exports of TN and TP were estimated for the entire watershed and its sub-watersheds through an investigation-evaluation technique during 1980-2018. TN and TP loads generated from the agricultural sector were the major pollution sources in the HRW and had similar time trends during the same period. The spatial distribution of TN and TP exports was modelled byusingthe InVEST water purification model, and it was found that the temporal trends for the final exports of TN and TP into river systems were similar to those for TN and TP loads in the HRW for 1980-2018. Key driving factors were detected using the Geo-detector method to quantify the contribution rates of factors to the spatiotemporal exports of TN and TP. Our results showed that individual factors, such as precipitation and land use/cover, were the most important factors driving spatio-temporal variations in TN and TP exports in the HRW from 1980 to 2018. Meanwhile, the contribution rates of interactions between land use/cover and other factors were consistently highest in this watershed during the same period. In this study, we estimated the loads and exports of TN and TP, and modelled their spatial patterns in this watershed from 1980 to 2018, providing important information on TN and TP for water-related management authorities. We also provide a method for other river systems to calibrate the parameters in the biophysical table of InVEST water purification model based on final exports of TN and TP.

Asunto(s)

RESUMEN

In order to explore the spatial differentiation characteristics and variation law of soil Cd content in a high geological background area, 14 421 topsoil samples were collected from topsoil in the karst area of Guiyang City. Global Moran's I index, cold hot spot analysis, semi-variance function, and Kriging interpolation were used to reveal the spatial structure and distribution law of soil Cd content. The influence of environmental factors on soil Cd content and its main controlling factors were analyzed through analysis of variance and geographic detector. The results showed that： ① The Cd content of karst surface soil in Guiyang varied from 0.03 to 1.36 mg·kg-1, with an average of 0.440 mg·kg-1, which was 1.77 times and 5.95 times the Guizhou soil Cd background value and Chinese soil Cd background value, respectively. The over-standard rate of soil Cd was 30%, which was 4.29 times that of 7% of soil Cd in China. ② There was a significant spatial positive correlation of soil Cd content, showing an aggregation trend in the global space, whereas in the local region, the northeast and southwest were hot spots, and the north was a cold spot. The nugget coefficient of soil Cd content was 10.37%, indicating that soil Cd was mainly affected by structural factors. ③ In terms of spatial distribution, soil Cd showed different accumulation trends. In some massive soils, such as Xifeng County, Xiuwen County, Qingzhen City, Huaxi District, and Nanming District, the soil ω（Cd）was less than 0.3 mg·kg-1. The soil ω（Cd）was between 0.3 and 0.6 mg·kg-1,and soil Cd in Baiyun District, Wudang District, Guanshan Lake area, and Yunyan area as a whole lied within this range. The soil ω（Cd）between 0.6 and 0.9 mg·kg-1 was concentrated in the southwest of Qingzhen City, the south of Huaxi District, and the north of Kaiyang County, whereas soil ω（Cd） between 0.9 and 1.2 mg·kg-1 was mainly concentrated in the southwest of Qingzhen City. The extreme value of soil Cd content （ > 1.2 mg·kg-1） was mostly distributed in Kaiyang County, Xiuwen County, Qingzhen City, and Huaxi District. ④ The results of analysis of variance and geo-detector showed that different environmental factors had significant effects on the spatial differentiation of soil Cd, but their explanatory power on soil Cd content varied： stratum （0.176 5） > soil type （0.026 0） > organic matter （0.025 1） > altitude （0.010 5） > parent rock （0.007 3） > land use （0.006 4） > pH （0.001 3）, and the interaction between stratum and arbitrary environmental factors was the greatest. Therefore, stratum was the main factor affecting the spatial differentiation of soil Cd content.

RESUMEN

The urban heat island (UHI) effect generated by the development of high-speed urbanization has become one of the major problems affecting the urban ecological environment. As the main body of urbanization in China, China's urban agglomerations are the core areas of urban heat island effect. The purpose of this study is to study the spatial-temporal characteristics and driving factors of surface urban heat island in 19 urban agglomerations in China, with a view to providing theoretical references for the prevention of urban thermal environmental risks. Based on Google Earth Engine (GEE), this paper estimated the surface urban heat island intensity (SUHII) of 19 urban agglomerations in China from 2003 to 2019 using MODIS land surface temperature (LST) data. Correlation analysis and regression analysis were used to explore the correlation between the change of SUHII and driving factors. Finally, the driving factors of SUHII were detected by the geo-detector model. Results showed that (1) the SUHII of 19 urban agglomerations in arid and semi-arid areas of northwestern China is higher than that in humid areas of eastern and southeastern China. (2) The SUHII of 19 urban agglomerations in China generally shows a decreasing trend, and the spatial variation of the change trend is significant. (3) There are positive correlations between SUHII and reference evapotranspiration (ET0), population density (POP), gross domestic product (GDP), nitrogen dioxide (NO2), ozone (O3), and ultraviolet aerosol index (UVAI); negative correlations with normalized difference vegetation index (NDVI), DEM, sulfur dioxide (SO2), carbon monoxide (CO), and formaldehyde (HCHO); the correlations all pass the significance test of P < 0.05 and are statistically significant. (4) The factor detection results showed that NDVI, land cover type (LC), and UVAI were the main driving factors of SUHII. The interaction detection results showed that the interaction between O3 and UVAI had the most significant impact on SUHII.

Asunto(s)

RESUMEN

In the context of rapid urbanization, metropolitan areas are facing the risk of supply-demand mismatches among ecosystem services. Investigating the patterns, relationships, and driving factors of multiple supply-demand risks is of great significance to support the efficient management of regional ecological risks. We quantified the single/comprehensive supply-demand risk rates of six ecosystem services in Wuhan Metropolitan Area at the township scale in 2000, 2010, and 2020. By applying the self-organizing feature map network and optimal parameter geo-detector, we identified supply-demand risks bundles of ecosystem services and influencing factors of comprehensive risks. The results showed significant spatial variations in the supply-demand risks of typical ecosystem services from 2000 to 2020. The supply-demand risk associated with grain production, water yield, carbon sequestration, and green space recreation increased, while soil conservation and water purification risks decreased. The comprehensive ecosystem services supply-demand risk increased from 0.41 to 0.45, indicating a 'core area increase and periphery decrease' trend. Throughout the study period, the area exhibited bundles of comprehensive extremely high-risk bundles (B1), comprehensive high-risk bundles (B2), water purification high-risk bundles (B3), and grain production-soil conservation risk bundles (B4). The transition of risk types from B3 to B2 and from B2 to B1 suggested an increase in the combination and intensity of supply-demand risk. Vegetation cover, nighttime light index, and population density were the main driving factors for spatial variations in comprehensive supply-demand risk. Ecologi-cal risk assessment based on ecosystem services supply-demand bundles could provide an effective and reliable way to regulate multiple regional risk issues.

Asunto(s)

RESUMEN

The environmental pollution caused by mineral exploitation and energy consumption poses a serious threat to ecological security and human health, particularly in resource-based cities. To address this issue, a comprehensive investigation was conducted on potentially toxic elements (PTEs) in road dust from different seasons to assess the environmental risks and influencing factors faced by Datong City. Multivariate statistical analysis and absolute principal component score were employed for source identification and quantitative allocation. The geo-accumulation index and improved Nemerow index were utilized to evaluate the pollution levels of PTEs. Monte Carlo simulation was employed to assess the ecological-health risks associated with PTEs content and source orientation. Furthermore, geo-detector and random forest analysis were conducted to examine the key environmental variables and driving factors contributing to the spatiotemporal variation in PTEs content. In all PTEs, Cd, Hg, and Zn exhibited higher levels of content, with an average content/background value of 3.65 to 4.91, 2.53 to 3.34, and 2.15 to 2.89 times, respectively. Seasonal disparities were evident in PTEs contents, with average levels generally showing a pattern of spring (winter) > summer (autumn). PTEs in fine road dust (FRD) were primarily influenced by traffic, natural factors, coal-related industrial activities, and metallurgical activities, contributing 14.9-33.9 %, 41.4-47.5 %, 4.4-8.3 %, and 14.2-29.4 % to the total contents, respectively. The overall pollution and ecological risk of PTEs were categorized as moderate and high, respectively, with the winter season exhibiting the most severe conditions, primarily driven by Hg emissions from coal-related industries. Non-carcinogenic risk of PTEs for adults was within the safe limit, yet children still faced a probability of 4.1 %-16.4 % of unacceptable risks, particularly in summer. Carcinogenic risks were evident across all demographics, with children at the highest risk, mainly due to Cr and smelting industrial sources. Geo-detector and random forest model indicated that spatial disparities in prioritized control elements (Cr and Hg) were primarily influenced by particulate matter (PM10) and anthropogenic activities (industrial and socio-economic factors); variations in particulate matter (PM10 and PM2.5) and meteorological factors (wind speed and precipitation) were the primary controllers of seasonal disparities of Cr and Hg.

Asunto(s)

RESUMEN

The current energy crisis is worsening worldwide, and in China, urban expansion and per capita vehicle ownership have created a growing energy imbalance and increased pressure to reduce carbon emissions.The popularization of new energy vehicles (NEVs) can provide a step forward to solving energy shortage problems, environmental pollution, and global warming. In 2022, the average penetration rate, which is ratio of new energy vehicle sales to vehicle sales, is just 19.1 %. This paper analysed the reasons for the differences in the penetration rates of new energy vehicles in China's 269 prefecture-level cities, using a Geo Detector approach, and the results showed that the level of economic development, the average annual temperature difference, the density of charging piles, the charging price and the number of population all had significant effects(q＞0.12) on the penetration rate. Based on the above studies, a questionnaire was used to investigate the public's acceptance of new energy vehicles in Xinjiang Uygur Autonomous Region, and a PLS-SEM regression analysis was conducted. The results showed that men, young people and people with a certain level of basic education were 5 % more likely to accept new energy vehicles.Unlike previous studies, perceived cost had no significant correlation with the acceptance of new energy vehicles. Perceived risk had a significant negative correlation with the acceptance of new energy vehicles,the path coefficient is -0.1.The acceptance of new energy vehicles was significantly and positively correlated with vehicle quality and service, the public's understanding of new energy vehicles, and subjective norms, their average path coefficients are above 0.1. We argues that the government should maintain a certain level of promotion of new energy vehicles and accelerate the construction of charging piles, based on the aforementioned results.

RESUMEN

PM2.5 remote sensing data was applied in this study, and Theil-Sen Median trend analysis and the Mann-Kendall significance test were utilized to analyze the temporal and spatial variation in PM2.5 in the Shandong Province from 2000 to 2021. The influencing power of the influencing factors on the spatial differentiation of PM2.5 concentration in the Shandong Province was detected at the provincial-city-county levels based on Geo-detector data. The results showed that:① on the temporal scale, the mean ρ(PM2.5)in the Shandong Province ranged from 38.15 to 88.63 µg·m-3 from 2000 to 2021, which was slightly higher than the secondary limit of inhalable particulate matter (35 µg·m-3) in the Ambient Air Quality Standards. On the interannual scale, 2013 was the peak year for the variation in ρ(PM2.5) with a value of 83.36 µg·m-3, according to which the trend of PM2.5 concentrations in the Shandong Province was divided into two phases:a continuous increase and a rapid decrease. On the seasonal scale, PM2.5 concentration presented the distribution characteristics of "low in summer and high in winter and moderate in spring and autumn" and the U-shaped change rule of first decreasing and then increasing. ② On the spatial scale, the PM2.5 concentration in the Shandong Province presented a spatial distribution pattern of "high in the west and low in the east." The areas with high PM2.5 concentration were distributed in the western area of the Shandong Province, whereas the areas with low PM2.5 concentration were distributed in the eastern peninsula region. The spatial variation in the changing trend of PM2.5 concentration showed significant spatial heterogeneity, and the extremely significant decrease was mainly distributed in the eastern peninsula region. ③ The results of factor detection showed that climate factor was an important factor affecting the spatial differentiation of PM2.5 concentration in the Shandong Province. Mean temperature had the highest influence on the spatial differentiation of PM2.5 concentration in the Shandong Province, with a q value of 0.512. Provincial-city-county multi-scale detection results showed that the influencing factors affecting the spatial differentiation of PM2.5 concentration and their influencing power differed at different spatial scales. At the provincial scale, mean temperature, sunshine duration, and slope were the main factors affecting the spatial differentiation of PM2.5 concentration. At the city level, precipitation, elevation, and relative humidity were the main factors affecting the spatial differentiation of PM2.5. At the county level, precipitation, mean temperature, and sunshine duration were the main factors affecting the spatial variation in PM2.5 concentration.

RESUMEN

Identifying high-risk factors (heavy metals (HMs) and pollution sources) by coupling receptor models and health risk assessment model (HRA) is a novel approach within the field of risk assessment. However, this coupled model ignores the contribution of spatial differentiation to high-risk factors, resulting in the assessment being subjective. Taking Dongting Plain (DTP) as an example, a coupling framework by jointly using the positive matrix factorization model (PMF), HRA, Monte Carlo simulation, and geo-detector was developed, aiming to identify high-risk factors in groundwater, and further explore key environmental variables influencing the spatial heterogeneity of high-risk factors. The results showed that at least 82.86 % of non-carcinogenic risks and 97.41 % of carcinogenic risks were unacceptable for people of all ages, especially infants and children. According to the relationships among HMs, pollution sources, and health risks, As and natural sources were defined as high-risk HMs and sources, respectively. The interactions among Holocene thickness, oxidation-reduction potential, and dissolved organic carbon emerged as the primary drivers of spatial variability in high-risk factors, with their combined explanatory power reaching up to 74%. This proposed framework provides a scientific reference for future studies and a practical reference for environmental authorities in developing effective pollution management measures.

Asunto(s)

RESUMEN

Despite the widespread occurrence of regolith-hosted rare earth elements (REEs) across South China, their spatial distribution characteristics in soils and their impact factors remain largely uncertain. This knowledge gap impedes the exploration of regolith-hosted REE deposits and the assessment of the environmental risks associated with REEs. To address this issue, 180 soil samples were collected from Meizhou City, Guangdong Province, a region known for its high abundance of regolith-hosted REEs. Subsequently, the correlations between REE enrichment/fractionation and various factors, i.e., topography, climate conditions, land use, and landform were analysed using the geo-detector method. The results revealed a highly uneven spatial distribution of REEs and their fractionation features with some regions displaying distinct spatial patterns. Elevation was the dominant factor influencing this distribution, and showed strong correlations with the concentrations of REEs, light REEs (LREEs) and heavy REEs (HREEs); the LREE/HREE ratio; and the positive Ce anomaly (δCe). The negative Eu anomaly (δEu) showed a good correlation with rock type. The enrichment and fractionation of REEs indicated a coupling among the abovementioned factors. For REE enrichment, areas with elevations of 138-148 m, precipitation levels of 1553-1574 mm, annual average land surface temperatures of 30.4-30.5 °C, leaf area index values of 22-29 and surface cutting degree of 21.5-29.9 m showed the highest average abundance within each type (scope) of the predominant factors. These findings highlight the key factors affecting REE distribution, thereby aiding the efficient utilization of regolith-hosted REE resources and the evaluation of their environmental risks.

Asunto(s)

RESUMEN

An in-depth study of the spatiotemporal variation characteristics and driving factors of ecosystem service values in the Liaohe River Delta is of great significance to its ecological environment governance and protection. Based on the land use data of the Liaohe River Delta for seven periods from 1990 to 2020, the ecosystem service value (ESV) was evaluated according to the equivalent factor coefficient correction method, establishing models for estimating the value of ecosystem services; the spatial and temporal evolution characteristics of the ESV in the study area were comprehensively analyzed; and the driving influencing factors and mechanisms of the ESV were explored. The results showed that:① From 1990 to 2020, the most common land use type in the Liaohe River Delta was cultivated land, and the areas of forest land, wetland, and unutilized land showed a decreasing trend; grassland, water, and construction land showed an increasing trend; and the area of cultivated land was basically unchanged during the 30 year period. ② In terms of the temporal evolution, the ESV in the study area showed a trend of first decreasing, then increasing, and then decreasing. In terms of the spatial distribution of ESV, the total value of ecosystem services as a whole showed a spatial divergence pattern of a high value in the southwest and low value in the northeast. ③ The sensitivity index of all land use types in the Liaohe River Delta was less than 1, indicating that the ESV was inelastic. ④ The value of ecosystem services in the Liaohe River Delta showed positive spatial coherence. On the whole, the Liaohe River Delta was dominated by HH and LL clusters, with HL clusters mostly distributed at the boundaries of LL clusters and LH clusters distributed at the boundaries of HH clusters. ⑤ Among the factors influencing the evolution of ESV in the Liaohe River Delta, DEM had the least influence, and HAI had the greatest influence on the ESV, followed by precipitation. The interaction results of all influencing factors had an enhancing effect on the spatial distribution of the ESV, among which HAI and precipitation had the strongest interaction effect, reaching 95.58%.

RESUMEN

Studying the spatiotemporal variation in vegetation net primary productivity (NPP) and exploring its influencing factors are of considerable practical significance for understanding the spatiotemporal variation in vegetation and for guiding ecological restoration and management projects based on local conditions. Based on MODIS NPP data, combined with in situ meteorological data, land use data, and vegetation type data, this study explores the spatiotemporal variation in different types of vegetation NPP in southwest China via the Mann-Kendall significance test and Theil-Sen Median slope estimator. It reveals the influencing factors of spatial differentiation of different types of vegetation NPP and the interaction between influencing factors in combination with stability analysis and Geo Detectors. The results revealed that on the temporal scale, from 2000 to 2021, vegetation NPP, NPPPre (vegetation NPP exclusively under the influence of climate change), and NPPRes (vegetation NPP exclusively under the influence of human activities) in southwest China showed a fluctuating upward trend. Among different vegetation types, NPP, NPPPre, and NPPRes exhibited an upward trend, except for a minor decline in NPPRes of tree vegetation at a rate of -0.183 g·(m2·a)-1. Among them, NPP, NPPPre, and NPPRes of economic vegetation showed the most significant upward rates, 5.96, 3.09, and 2.94 g·(m2·a)-1, respectively. On the spatial scale, the tree vegetation NPP with the most significant downward trend was mainly distributed in Tibet and southern Yunnan, while the economic vegetation NPP with the highest upward trend was primarily distributed in eastern Sichuan Province. The stability of vegetation NPP in southwest China presented a spatial distribution pattern of "low in the south and high in the north," and the average value of the correlation coefficient increased in the ascending order of arbor vegetation (0.101), shrub vegetation (0.105), herb vegetation (0.110), and economic vegetation (0.114). The interaction between surface temperature and relative humidity was the main influencing factor for spatial differentiation of vegetation NPP, while the interaction between sunshine duration and warmth index had the most significant impact on vegetation in southwest China, with an increasing percentage of 30.91%. Different types of vegetation had different requirements for different climatic factors, but their requirements for surface temperature and warmth index were significantly consistent. When the surface temperature was 21.03-28.49℃, and the warmth index was 106.46-167.2, the NPP of different vegetation types peaked. Under natural succession, the impact of climate change on vegetation was inversely proportional to the stability of the vegetation community. The arbor vegetation community with high stability was less affected, while the herb vegetation community with low stability was highly affected by climate. In contrast, the stability of economic vegetation was directly proportional to the impact of climate due to the influence of human activities. This study establishes a theoretical foundation for evaluating the impact of regional climate on the growth of different vegetation types and can be crucial for formulating ecological restoration and management strategies in southwest China that are adapted to the local conditions.

Asunto(s)

RESUMEN

Ili Valley is an important ecological barrier in western China and an important economic zone of the Belt and Road Initiative. Exploring the driving factors of ecosystem service value (ESV) based on land use change is of great significance for optimizing regional ecological environment and coordinating human-land relationship. Based on three periods of land use data from 2000 to 2020 in Yili Valley, we used ArcGIS 10.8 and Origin to analyze the characteristics of land use change, temporal and spatial variations of ESV, and the synergy and trade-offs of ecosystem services, and explored the driving factors affecting the spatial differentiation of ESV and the interaction among factors by using Geo-Detector. The results showed that land use change in the study area was obvious from 2000 to 2020, with the area of grassland and water area being greatly reduced and the largest increase for the area of construction land. The ESV of grassland and water area and the service function of water resource supply decreased significantly. ESV high value areas were transformed to low value areas. Synergy was the dominant relationship among ecosystem services in the study area, which showed an increasing trend. Elevation was the main driving factor of ESV spatial differentiation in Yili Valley, and the low elevation plain area suitable for human activities on both sides of the basin was the low ESV value area. The interaction between all factors was manifested as enhanced relationship, while the explanatory power of natural factors was higher than that of social and economic factors.

Asunto(s)

RESUMEN

The contamination of potentially toxic elements (PTEs) in road dust of large industrial cities is extremely serious. Determining the priority risk control factors of PTE contamination in road dust is critical to enhance the environmental quality of such cities and mitigate the risk of PTE pollution. The Monte Carlo simulation (MCS) method and geographical models were employed to assess the probabilistic pollution levels and eco-health risks of PTEs originating from different sources in fine road dust (FRD) of large industrial cities, and to identify key factors affecting the spatial variability of priority control sources and target PTEs. It was observed that in FRD of Shijiazhuang, a typical large industrial city in China, more than 97% of the samples had an INI > 1 (INImean = 1.8), indicating moderately contaminated with PTEs. The eco-risk was at least considerable (NCRI >160) with more than 98% of the samples, mainly caused by Hg (Ei (mean) = 367.3). The coal-related industrial source (NCRI(mean) = 235.1) contributed 70.9% to the overall eco-risk (NCRI(mean) = 295.5) of source-oriented risks. The non-carcinogenic risk of children and adults are of less importance, but the carcinogenic risk deserves attention. The coal-related industry is a priority control pollution source for human health protection, with As corresponding to the target PTE. The major factors affecting the spatial changes of target PTEs (Hg and As) and coal-related industrial sources were plant distribution, population density, and gross domestic product. The hot spots of coal-related industrial sources in different regions were strongly interfered by various human activities. Our results illustrate spatial changes and key-influencing factors of priority source and target PTEs in Shijiazhuang FRD, which are helpful for environmental protection and control of environmental risks by PTEs.

Asunto(s)

RESUMEN

Studies on the spatio-temporal variation and driving mechanism of PM2.5 concentration in the Chengdu-Chongqing urban agglomeration are of great significance for regional atmospheric environment protection and national economic sustainable development. Based on PM2.5 remote sensing data, DEM data, in situ meteorological data, MODIS NDVI data, population density data, nighttime lighting data, road network data, and land use type data, a series of mathematical methods such as Theil-Sen Medium analysis and Mann-Kendall significance test, combined with the Geo-detector model were used to analyze the spatio-temporal variation and multi-dimensional detection of the driving mechanism of PM2.5 concentration in the Chengdu-Chongqing urban agglomeration. The results showed that the overall PM2.5 concentration showed a fluctuating downward trend in the Chengdu-Chongqing urban agglomeration from 2000 to 2021, and the PM2.5 pollution was the most prominent in winter. PM2.5 concentration exhibited obvious spatial heterogeneity with "high in the middle and low in the surrounding areas." The high-PM2.5 concentration areas were mainly concentrated in Zigong, Neijiang, Ziyang, and Guang'an, and the areas with a PM2.5 concentration decrease were mainly concentrated in the west of Chongqing. Influencing detection results showed that the spatial heterogeneity of PM2.5 concentration in the Chengdu-Chongqing urban agglomeration was influenced by the combined effects of climate factors, topographic factors, vegetation cover, and anthropogenic factors. Furthermore, elevation, slope, and road network density were regarded as the dominant factors influencing the spatial heterogeneity of PM2.5 concentration in the study area. Topographic factors and climate factors showed the highest and lowest contribution rate to the spatial heterogeneity of PM2.5 concentration, respectively. The contribution rate of topographic factors and anthropogenic factors had gradually increased, and the contribution rate of climate factors and vegetation cover had gradually decreased in the study area from 2000 to 2021. Interaction detection results showed that the spatial heterogeneity of PM2.5 concentration in the Chengdu-Chongqing urban agglomeration was mostly affected by the interaction effects of elevation and road network density, slope, precipitation, sunshine duration, and land use type. The interaction detection results exhibited obvious regional differences on the city level. For instance, the spatial heterogeneity of PM2.5 concentration in Chengdu, Deyang, and Leshan was mostly affected by the interaction between different influencing types, and the spatial heterogeneity of PM2.5 concentration in Dazhou, Meishan, Ya'an, Ziyang, Neijiang, and Zigong was mostly affected by the interaction within a single influencing type.

RESUMEN

Comprehensive analysis of spatiotemporal distribution characteristics of potentially toxic elements (PTEs) in soils of China, and associated driving mechanism and health risks is crucial for soil pollution prevention and risk control. In this study, a total of 8 PTEs in agricultural soils of 236 city case data from 31 provinces of China were collected from literatures published between 2000 and 2022. The pollution level, dominant drivers and probabilistic health risks of PTEs were analyzed using geo-accumulation index (Igeo), geo-detector model, and Monte Carlo simulation, respectively. The results indicated a notably accumulation of Cd and Hg, with Igeo of 1.13 and 0.63, respectively. Cd, Hg and Pb showed strong spatial heterogeneity, whereas As, Cr, Cu, Ni, and Zn has no significant differentiation. PM10 was the dominant driver for accumulation of Cd (0.248), Cu (0.141), Pb (0.108), and Zn (0.232), and PM2.5 has a significant effect on accumulation of Hg (0.245); however, soil parent material was primary driver for accumulation of As (0.066), Cr (0.113), and Ni (0.149). PM10 ∩ wind speed accounted for 72.6 % of Cd accumulation, and mining industry ∩ soil parent materials for 54.7 % of As accumulation. Approximately 38.53 %, 23.90 %, and 12.08 % of the hazard index values exceeded 1 for the minors aged 3- < 6, 6- < 12, and 12- < 18 years, respectively; whereas approximately 0.22 %, 0.21 %, 0.20 %, 0.54 % and 0.42 % of the carcinogenic risk values were greater than 1E-04 for individuals aged 3- < 6, 6- < 12, 12- < 18, 18- < 44, and 44- < 70 years, respectively. As and Cd were considered as priority elements for soil pollution prevention and risk control in China. Moreover, the hotspots of PTE pollution and associated health risks were mainly observed in southern, southwestern and central China. The results of this study provided a scientific basis for developing strategies for pollution prevention and risk control of soil PTEs in China.

Asunto(s)

RESUMEN

Japanese encephalitis (JE) is a major global public health threat. Using Japanese encephalitis incidence data from 2004 to 2010 in Guangxi Province, China, this study comprehensively explored the driving forces and the interactive effects between environmental and social factors of Japanese encephalitis using the Geo-detector method. The results indicated that the incidence of Japanese encephalitis showed a fluctuating downward trend from 2004 to 2010. The onset of JE was seasonal, mainly concentrated in June-July, and highly aggregated in northwestern Guangxi. Among the factors associated with Japanese encephalitis, days with temperatures >30 °C, accumulated temperatures >25 °C, slope, the normalized difference vegetation index, the gross domestic product of tertiary industries, the gross domestic product of primary industries and the number of pigs slaughtered showed higher contributions to Japanese encephalitis incidence. An enhanced interactive effect was found between environmental and social factors, and the interaction between days with humidity levels >80% and the gross domestic product of tertiary industries had the greatest combined effect on JE. These findings enhanced the understanding of the combined effect of social and environmental factors on the incidence of Japanese encephalitis and could help improve Japanese encephalitis transmission control and prevention strategies.

Asunto(s)

RESUMEN

The rise of mass tourism has encouraged rapid economic growth; meanwhile, the eco-environmental system has come under increasing pressure. To achieve sustainable development, it is critical to deeply explore the relationship and evolution characteristics between three subsystems: tourism, the economy, and the eco-environment. This study aims to develop a more comprehensive indicator system for evaluating the coupling coordination degree (CCD) of the tourism-economy-environment (TEE) system using statistical data from nine cities in the Pearl River Delta (PRD) urban agglomeration from 2010 to 2019. We investigated the spatial-temporal evolution characteristics and driving forces of the TEE system in the PRD using the CCD model and the geo-detector model. The research results show the following: (1) The comprehensive benefits of the TEE system have increased steadily over the past 10 years, whereas the benefits of the eco-environment subsystem have fluctuated and been relatively unstable. (2) Spatially, in terms of tourism development, the eastern regions of the PRD are more developed than the western regions, and the regions with the greatest tourism benefits have gradually shifted to the northeastern regions of the PRD. Economic development presented an imbalanced but relatively stable spatial pattern. Guangzhou and Shenzhen have been the two most economically developed cities over the past 10 years. The eco-environment development has fluctuated over time, revealing a spatial pattern of cities with low environmental benefits in the center and cities with high eco-environmental benefits in the surrounding regions. (3) The PRD's TEE system has become more integrated, moving from moderate disorder to a model of high-quality coordinated development, demonstrating a spatial pattern in which the cities of high development coordination are located near the Pearl River Estuary, and the coordination decreases the further away they are from the estuary. (4) The major driving factors of heterogeneous TEE coordination development include eco-environment protection, opening-up policies, education investment, technological innovation level, and the regional economic development level. The results are expected to effectively promote economic, tourism, and environmental improvement in the PRD, as well as to provide policy recommendations for coordinated TEE development in other similar urban agglomerations.

Asunto(s)

RESUMEN

Human demand for natural resources has grown, leading to ecological debasement and related ecological system administration. Using Dalian as an example, we estimated the changes in the ecosystem service value (ESV) in 2005 and 2020. We used ArcGIS and spatial statistics to conduct estimations and change analyses of the ESV. Based on the results of the ESV, the geographical detector and geographically weighted regression (GWR) elucidated the contributions of different driving factors of the ESV in a 2 km grid. In summary, these results indicated that: (1) from a holistic perspective, the ESV of Dalian fell by 206.8009 billion CNY over 15 years, and the hot spots were concentrated in both the northern and the western parts, whereas the cold spots were distributed in the central part; (2) according to the results from the geographical detector, land use structure factors influenced the ESV most significantly, followed by socio-economic factors, and the impact of natural factors was relatively small; and (3) according to the results of the GWR, land use structure factors negatively affected the ESV, and the positive impact of the proportion of the natural land area was the most obvious. We conclude that the decline in the ESV reflects the impact of human activities on the ecosystem in the studied landscape. Understanding ESV changes should be made a priority in ecosystem management, and evaluating ESV drivers can contribute to developing land use strategies for policy-making.

Asunto(s)

RESUMEN

Recently, with the rapid development of China's economy, the pollution of trace metal(loid)s (TMs) in soils has become increasingly severe and attracted widespread attention. Based on 1,402 published papers from 2000 to 2021, this study aimed to analyze the pollution intensity, ecological risk and driving factors for eight TMs (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) in Chinese soils. Results showed that the average concentrations of eight TMs in Chinese soils all exceeded background values, and the pollution of Cd and Hg was the most serious. Based on Principal component analysis of pollution intensity and ecological risk, the priority control TMs were identified for the heavily polluted provinces. The results of Geo-detector model suggested that Urban development factors contributed most to the TM accumulation in Chinese soils. Further, spatial analysis using bivariate Moran's I indicated that industrial activities contributed most to soil TM accumulation in the middle and lower reaches of the Yangtze River, while soil TM pollution in the southwest and northwest provinces was mainly caused by mining and metal smelting. This study investigated the relationship between soil TM pollution and anthropogenic activities, thus providing a scientific basis for controlling soil TM pollution at a large-scale level.

Asunto(s)

RESUMEN

Special consideration should be given to the differential coupling relationships between natural and anthropogenic factors on ecological degradation and ecological restoration. However, few studies have focused on how to quantify the contribution rate of social-ecological interactions to vegetation growth and determine the impact thresholds of vegetation coverage at the county scale. Notably, it is more conducive to evaluating the impact of anthropogenic factors on vegetation coverage by integrating ecological land use policy into the research framework. This study combined remote sensing technology, as well as the Geo-detector model and elasticity coefficient to identify the key factors affecting ecological degradation and ecological restoration and quantitatively determine the impact thresholds from the aspects of climate change, topography, hydrological condition, human disturbance, and ecological land use policy. The results showed that ecosystems shifted from severe degradation (1990-2000) to restoration (2000-2010) and then to slight degradation (2010-2020). Meteorological factors and topographic factors revealed a stronger impact on ecological degradation and ecological restoration before the implementation of large-scale ecological engineering, and then they were most affected by ecological land use policy. In addition, the ecological thresholds of some factors were found in this study. Specifically, when average annual precipitation and slope reached the threshold of 523 mm and 5° respectively under ecological degradation, they had the greatest influence on vegetation coverage. Under ecological degradation and ecological restoration, the threshold of altitude was 1500 mm, and the threshold of drainage density was 10 and 14, respectively. The information from this study is expected to enhance the practical value of ecological research and provide an important reference for ecological standards and sustainable environmental management.

Asunto(s)