Sediment cores are optimal mediums for investigating the historical presence of offshore microplastics (MPs). In this study, two sediment cores were collected at varying water depths, i.e., XS2 (10 m) and XS3 (20 m), from the Xiangshan offshore (XSO) in Ningbo. We focused on the spatiotemporal distribution characteristics of MPs within two sediment cores and explored the response differences of MPs abundance to natural factors and human activities. The results showed that the MPs abundance in sediments has gradually increased since the late 1960s, but with interannual fluctuations. MPs abundance in XS2 and XS3 were 1133-8700 and 633-11433 items/kg dry weight, respectively. The predominant polymers were PA, PU, PET and ACR, with fragmented particles being the most prevalent shape of MPs. The MPs abundance in XS2 and XS3 had a similar response to natural factors, mainly including (i) MPs abundance significantly correlated with the sediment load of the Qiantang River (p < 0.01), indicating that sediment load might be an important factor affecting the MPs abundance and that MPs transported by rivers had characteristics of near-source sedimentation; (ii) typhoons had the effect of weakening the MPs abundance; and (iii) geological activities might be potential contributing factors to variations in MPs\' abundance in deep sediments. Correlation analyses demonstrated that MPs in XSO was the result of multiple sources, stemming from plastic production, sewage discharge, marine fisheries and shipping activities. Notably, XS3 exhibited higher sensitivity to human activities compared to XS2, owing to differences in sampling locations. This study underscores the significance of employing two sediment cores, rather than a single core, as it provides a more comprehensive insight into the overarching trends and disparities in the historical pollution of MPs. Our findings contribute to a deeper understanding of the history of offshore MPs pollution, shedding new light on this critical environmental issue.

Changes in the air temperature tend to indirectly affect soil erosion by influencing rainfall, vegetation growth, economic development, and agricultural activities. In this study, the partial least squares-structural equation model (PLS-SEM) was used to decouple the impacts of temperature change on soil erosion in Northeast China from 2001 to 2019, and the indirect effect of temperature change on the pathways of natural and socioeconomic factors was analyzed. The results showed that temperature increase in Northeast China caused an increase in soil erosion by increasing rainfall and promoting economic development. Under the pathway of natural factors, in spring, the promoting effect on soil erosion under the influence of temperature change on rainfall was greater than the inhibiting effect on soil erosion under by the influence of temperature change on vegetation. In summer, the opposite effect was observed. Under the pathway of natural factors, over time, the promoting effect of temperature increase on soil erosion increased by 22.7%. Under the pathway of socioeconomic factors, temperature change not only aggravated soil erosion by promoting economic development, but also indirectly increased investments in agriculture and water conservation by improving the economy, thus inhibiting soil erosion to a certain extent. Over time, the contribution of temperature change to soil erosion through socioeconomic pathway was reduced by 44.4%. When the pathway of natural factors is compared with that of socioeconomics factors, temperature change imposed a more notable effect on the change in soil erosion through the socioeconomic pathway, indicating that human activities are the driving factors with a greater effect on soil erosion. Based on this, reasonable human intervention is an important means to alleviate soil erosion aggravation caused by rising temperatures.

Soil quality is essential for maintaining the sustainability of agroecosystems, especially under intensified agricultural activities and rapid land use change. The sampling and analysis of soil properties to assess the status of agricultural land is widely practiced at the field scale; however, the spatiotemporal variations in soil quality and its influencing factors at a large scale remain unclear. Here, we quantified spatiotemporal variations in the soil quality of agricultural land in China during 1980-2018 by using the soil quality index (SQI) area approach, and explored the drivers with a geographical detector method. The results showed that the distribution of the SQI in the two periods had a similar spatial trend, except for that in the southwest (SWC), and the SQI decreased from north to south regardless of land use type. The soil quality of woodland was comparatively good with mean SQI values of 1.55 and 1.53 in 1980 and 2018, respectively, followed by that in grassland and cropland. Soil organic carbon, total nitrogen and cation exchange capacity were the dominant soil indicators explaining the spatial heterogeneity of the SQI in all land uses; moreover, climatic factors (i.e., temperature and precipitation) showed a stronger effect on woodland. From 1980 to 2018, the SQI of grassland decreased deeply, especially in the SWC, which showed a severe decline of 12.5 %. The changes in precipitation and temperature were identified as the largest drivers of SQI temporal changes in woodland and grassland, respectively, and their interaction achieved the highest impact across all land uses. In addition, the bidirectional conversion between cropland and grassland in recent decades has aggravated the deterioration of soil quality. Therefore, quantifying spatiotemporal changes in the SQI and elucidating the role of factors influencing soil quality in agroecosystems can provide a guide for designing sustainable agriculture policies and improving environmental quality.

Global climate change and revegetation programs have significantly changed the ecological quality (EQ) in the Chinese mainland after 1999. Monitoring and assessing the changes in the regional EQ and analyzing their drivers are crucial for ensuring ecological restoration and rehabilitation. However, it is challenging to carry out a long-term and large-scale quantitative assessment of the EQ of a region based on traditional field investigations and experiment methods alone; notably, in previous studies, the effects of carbon and water cycles and human activities on the variations in EQ have not been studied comprehensively. Therefore, in addition to remote sensing data and principal component analysis, we used the remote sensing-based ecological index (RSEI), to assess the EQ changes in the Chinese mainland during 2000-2021. Additionally, we also analyzed the impacts of carbon and water cycles and anthropological activities on the changes in the RSEI. The main conclusions of this study were: since the beginning of the 21st century, we observed a fluctuating upward trend in the EQ changes in the Chinese mainland and eight climatic regions. From 2000 to 2021, in terms of the EQ, North China (NN) portrayed the highest increase rate (2.02 × 10-3 year-1, P < 0.05). There was a breaking point in 2011, the EQ in the region experienced a change, from a downward trend to an upward one. Northwest China, Northeast China, and NN portrayed an overall significant increasing trend in the RSEI, whereas the southwest part of the Southwest Yungui Plateau (YG) and a part of the plain region of the Changjiang (Yangtze) River (CJ) river region portrayed a significant decreasing trend in the EQ. Overall, the carbon and water cycles and human activities played a pivotal role in determining the spatial patterns and trends of the EQ in the Chinese mainland. In particular, the self-calibrating Palmer Drought Severity Index, actual evapotranspiration (AET), gross primary productivity (GPP), and soil water content (Soil_w) were identified as the key drivers of the RSEI. In the central and western Qinghai-Tibetan Plateau (QZ) and the northwest region of NW, the changes in RSEI were dominated by AET; however, in central NN, southeastern QZ, northern YG, and central NE, the changes were driven by GPP, and in the southeast region of NW, south region of NE, northern region of NN, middle YG region, and a part of the middle CJ region, the changes were driven by Soil_w. The population-density-related change in the RSEI was positive in the northern regions (NN and NW) but negative in the southern regions (SE), whereas the RSEI change related to ecosystem services was positive in the NE, NW, QZ, and YG regions. These results are beneficial for the adaptive management and protection of the environment and the realization of green and sustainable developmental strategies in the Chinese mainland.

The middle and lower reaches of Hanjiang River Basin (MLHB), areas that have an important ecological function in China, have experienced great changes in the vegetation ecosystem driven by natural environmental change and human activity. Here, we explored the spatio-temporal dynamics of fractional vegetation coverage (FVC) and quantitatively analyzed its driving factors to advance current understanding of how the ecological environment has changed. Specifically, we used the dimidiate pixel model to calculate the FVC of the MLHB from 2001 to 2018 based on Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) data. We then used Theil-Sen median slope (Sen\'s slope) and coefficient of variation (CV) to explore spatial and temporal variations, as well as characteristics in fluctuations. Finally, we utilized a geographical detector model (with spatial scale effects and spatial data discretization tests) to quantify the influence of the detected natural and human factors. Results showed that average annual FVC was 0.30-0.75 for ~90% of the study area over the 19-year study period with a heterogeneous spatial distribution. FVC variation trend displayed stability and improvement. Areas with higher FVC displayed greater stability. All 10 detected natural and anthropogenic factors were responsible for changes in FVC. The primary factors causing FVC to change were precipitation (in 2001) and slope (in 2018), followed by landform type, distance to water, and nighttime light (NTL) (in 2018). Precipitation and slope consistently displayed the largest interaction across all years. The interaction between human and topographical factors had gradually increasing significance on changes in FVC over the research period. The range and type of factors suitable for promoting vegetation growth were detected in the study area. Results of this study can provide a scientific basis for developing effective strategies for local vegetation protection, restoration, and land resource management.

The State Council of China had issued the Air Pollution Prevention and Control Action Plan (abbreviated as \"Clean Air Actions\"), which ended in 2017. To evaluate the implementation effect of the clean air actions and provide the scientific basis on the future control policy, a Geographical Detector was used to quantify the impact of natural and socioeconomic factors on the PM2.5 concentration and its reductions in China from the years of 2014-2017. In terms of the impact on PM2.5 reduction, the industrial sulfur dioxide (SO2) and industrial soot emissions are the only two factors shown significant influences. So the controls of industrial emission were the major policies during the implementation of the Clean Air Actions. In terms of the impact on the PM2.5 concentrations, industrial emission was the strongest socioeconomic factor in the beginning of the Clean Air Actions, but its dominance was then declining. In contrast, the influences of population density had been enhancing and became the greatest factor in the final year. So the new control measures should focus on the urbanization regulation. In addition, the interactions between different socioeconomic factors are proved to bivariate enhance the influences on the PM2.5 concentration levels. Multiple factors should thus be taken into account when any new control policies are going to be established.

Mastering the spatial distribution of heavy metals in the soil plays an important supporting role in the scientific formulation of soil pollution risk management and control strategies. Few factors were considered and multiple collinearity between parallel variables existed,resulting in low prediction accuracy. OK (common Kriging method), NRK (regressive Kriging method based on natural factors only), and NARK (regressive Kriging based on natural-human factors)were used to simulate the spatial distribution of soil Cd by selecting 23 natural-artificial influencing factors. The prediction accuracy was evaluated based on an empirical study of the area around Shaoguan Qujiang smelter. The results showed that the above-standard rate of soil cadmium in this area reached 85.93%, and the effect on the spatial heterogeneity of soil cadmium was shown as air emissions from smelters > air emissions from steel plants > pH > organic matter > Euclidean distance to road > Euclidean distance to river. The root-mean-square error and average absolute error of NARK\'s prediction results for soil cadmium were 26.86% and 30.56% lower than that of the OK method, respectively. The model determination coefficient R2 increased from 0.78 to 0.88. Compared with that of NRK, it was reduced by 24.15% and 24.23% and R2 increased from 0.81 to 0.88. The NRK combining natural and human factors significantly improved the simulation accuracy of the spatial distribution of soil cadmium, and the addition of human factors as auxiliary variables, especially atmospheric point source pollution emissions, greatly contributed to the improvement of the model accuracy.

China\'s energy use has increased significantly in recent years with the country\'s rapid economic growth and large-scale urbanization. Therefore, air pollution has become a major issue. In this study, we conducted spatial autocorrelation and spatial panel regression analyses of sulfur dioxide (SO2) and nitrogen oxide (NOX) emissions using the panel data of 31 provincial-level administrative units in China during the period 2011-2017 to comprehensively understand the factors affecting air pollutant emissions. This study contributes to the literature by considering comprehensive factors and spatial effects in the panel-data econometric framework of the whole country of China. The analysis of spatial characteristics shows that during the study period, pollutant emissions in China declined, although emissions in northern regions were still relatively high. Furthermore, SO2 and NOX emissions showed significant positive spatial autocorrelations. The results of a fixed-effect spatial lag model showed that both socioeconomic and natural factors were statistically significant for air pollutant emissions, although the degree differed by the type of pollutant. The population, the urbanization rate, the share of added value of secondary industry, and heating and cooling degree days positively affected emissions, while population density, per-capita gross regional product, precipitation, and relative humidity negatively affected emissions. Based on these results, we have put forward suggestions to address the issue of air pollution and achieve environmental sustainability, such as the promotion of regional cooperation and a transition of the economic structure.

The rapid development of urbanization and agriculture poses serious impacts on groundwater in arid and semi-arid areas, which typically have high groundwater depletion rates. In this study, chemical and isotopic analyses combined with different data interpretation methods (diagrams, bivariate analyses, principal component analysis (PCA), and hierarchical cluster analysis (HCA)) were used to identify the major factors controlling groundwater chemistry in an arid and semi-arid region of North China. Sixty-four groundwater samples (35 from unconfined aquifer, 29 from confined aquifer) were collected in Baotou City, North China, and 17 chemical variables were detected for each sample. The complex hydrochemical types in unconfined groundwater (e.g., HCO3-Ca·Mg, HCO3·Cl-Na·Mg, SO4-Na·Mg, and Cl·SO4-Na types) may be related to anthropogenic activities, while the main hydrochemical types in confined groundwater are HCO3-Ca·Mg, HCO3-Na·Mg, HCO3·Cl-Na·Ca, SO4·HCO3-Na·Mg, and Cl·SO4-Na types. Three component models for unconfined and confined groundwater were revealed using PCA, which explained approximately 79.69% and 80.68% of the data variance, respectively, providing a deeper insight into groundwater composition controlled by geochemistry and anthropogenic activities. Three clusters were yielded from HCA. The factors and identified clusters were verified with hydrochemical investigations. Among the natural factors, the main hydrochemical processes involve the dissolution of various minerals (halite, gypsum, feldspar, fluorite, mirabilite, biotite, dolomite, and calcite), cation exchange, evaporation, and mixing. The anthropogenic factors include domestic sewage intrusion and agricultural activities, which are most likely to lead to further declines in groundwater quality. These findings may be useful for improving groundwater resource management for sustainable development in arid and semi-arid areas.

Global change, which refers to large-scale changes in the earth system and human society, has been changing the outbreak and transmission mode of many infectious diseases. Climate change affects infectious diseases directly and indirectly. Meteorological factors including temperature, precipitation, humidity and radiation influence infectious disease by modulating pathogen, host and transmission pathways. Meteorological disasters such as droughts and floods directly impact the outbreak and transmission of infectious diseases. Climate change indirectly impacts infectious diseases by altering the ecological system, including its underlying surface and vegetation distribution. In addition, anthropogenic activities are a driving force for climate change and an indirect forcing of infectious disease transmission. International travel and rural-urban migration are a root cause of infectious disease transmission. Rapid urbanization along with poor infrastructure and high disease risk in the rural-urban fringe has been changing the pattern of disease outbreaks and mortality. Land use changes, such as agricultural expansion and deforestation, have already changed the transmission of infectious disease. Accelerated air, road and rail transportation development may not only increase the transmission speed of outbreaks, but also enlarge the scope of transmission area. In addition, more frequent trade and other economic activities will also increase the potential risks of disease outbreaks and facilitate the spread of infectious diseases.