Surface mining caused multiple ecosystem service losses in China

The Ecological Restoration Strategies in Terrestrial Ecosystems Were Reviewed: A New Trend Based on Soil Microbiomics

Soil microorganisms play a pivotal role in the biogeochemical cycle and serve as crucial indicators of ecological restoration in terrestrial ecosystems. The soil microbial community is regarded as a pivotal participant in environmental processes, offering both positive and negative feedback to diverse media within the ecosystem. This community can serve as a potential indicator in ecological monitoring and restoration processes. Consequently, an increasing number of scholars are directing their research towards the field of soil microbial ecology in diverse ecosystems and fragile areas, with the aim of elucidating the intricate interactions between microbes and vegetation. However, the implementation of soil microbiome in ecological restoration remains in the experimental stage due to the interference of extreme events and the complexity of governance measures. Consequently, a comprehensive evaluation of existing research is imperative. This review aims to address the ecological crises currently experienced by diverse terrestrial ecosystems and to provide a comprehensive overview of the specific practices of soil microorganisms in the context of ecological restoration. We also incorporate them into fragile habitats and identify urgent issues that need to be addressed in the ecological restoration process of fragile areas.

Surface coal mining in drylands: A multiscale comparison of spatiotemporal patterns and environmental impacts between Inner Mongolia and Mongolia

Surface coal mining (SCM) poses a great threat to the environment. Previous studies have explored the speed and scale of SCM in the Mongolian Plateau, but landscape-based analysis is needed for creating actionable knowledge required for environmental policy-making. Thus, taking a landscape ecological approach, here we compared the spatiotemporal patterns and major environmental impacts of SCM between Inner Mongolia of China and Mongolia during 1975-2015 at multiple administrative levels. We found that the SCM area increased by nearly 40 times in Inner Mongolia and 11 times in Mongolia during the 40 years. The annual increase rate in terms of both area and number was greater in Inner Mongolia than in Mongolia during 1975-2010, but the order was reversed during 2010-2015. At the prefectural or aimag level, the SCM distribution exhibited considerable variations. In 2015, 44 % of the total SCM area was located in Baotou, Wuhai, and Ordos of Inner Mongolia and Ömnögovi of Mongolia in 2015. The spatiotemporal patterns of SCM were characterized by increases in patch size, shape complexity, clustering, and landscape fragmentation. We estimated that the surrounding ecosystems disturbed by mining were 14.72 times larger than the SCM sites themselves in Inner Mongolia and 21.10 times in Mongolia. More threatened species were potentially affected by SCM in Inner Mongolia than in Mongolia. The variations in the scope and speed of SCM between Inner Mongolia and Mongolia may be attributable to multiple factors, including the distribution of coal mines themselves, economic investments, and national and local policies. Our study provides scientific support for promoting China-Mongolia bilateral collaboration for curbing SCM expansion and mitigating its environmental impacts on the plateau.

Detecting the effects of opencast mining on ecosystem services value in arid and semi-arid areas based on time-series remote sensing images and Google Earth Engine (GEE)

Ecosystem Services Value (ESV) are the various beneficial functions and products that natural ecosystems provide to humans, and are important indicators for evaluating ecosystem conditions and human well-being. Opencast mining is one of the human activities that severely damage the surface environment, but its long-term impact on ecosystem services lacks systematic assessment. This study takes the Ordos opencast mining area as an example, and calculates the value of ESV from 1990 to 2020 based on the Google Earth Engine platform. Mann-Kendall Tau-b with Sen's Method (Sen + mk test) and Joinpoint regression model were used to analyzes its spatiotemporal variation characteristics. Further revealed the impacts of opencast mining on ESV as well as the trend of ESV changes. The results show that: (1) The dynamic ESV levels in the study area fluctuated considerably from 1990 to 2020 with an overall decreasing trend of 89.45%. (2) Among nine types ecosystem services, most of them were significantly different (p < 0.001) between mining areas and control areas, with biodiversity protection (BP), climate regulation (CR), gas regulation (GR), soil formation and retention (SFR), water supply (WS) and waste treatment (WT) showed a significant decrease between 1990 and 2020. (3) In the past 30 years, the ESV of the study area showed an overall improvement trend, where the improved area accounted for 48.45% of the total area of the study area. However, the degraded area also accounted for 21.28, and 17.19% of the area belonged to severe degradation. With 67% of the significantly degraded areas distributed within mining concessions. (4) The trend of ESV changes in the mining impact areas and the control area showed significant differences. The ESV of the control area increased continuously, with an average annual percentage change (AAPC) of 0.7(95%CI:0.50 ~ 0.9, P < 0.001) from 1990 to 2020; while the ESV of the mining impact areas first stabilized and then decreased significantly, with an AAPC of - 0.2(95%CI:- 0.3 ~ - 0.1,P < 0.001) from 1990 to 2020. This study provides scientific support for formulating ecosystem management, restoration plans, and payment for ecosystem service policies, which is conducive to achieving regional sustainable development and improving human well-being.

Spatio-temporal evolutionary analysis of surface ecological quality in Pingshuo open-cast mine area, China

The open-pit mining area is highly affected by human activities, which aggravate soil erosion and disturb surface ecology, bringing many problems and challenges to its environmental management and restoration, which has received widespread attention. The establishment of an objective, timely and quantitative remote sensing monitoring, and evaluation system for the spatio-temporal evolution of the surface ecological environment in the open-pit mining area is of great significance for its environmental protection, management decisions, and sustainable social development. Based on the Google Earth Engine (GEE) platform, this paper uses Landsat images to construct and calculate the remote sensing ecological index (RSEI) of the Pingshuo open-cast mine area (POMA) from 1990 to 2020 and monitor and evaluate its surface ecological environment. Combined with the Theil-Sen median, Mann-Kendall test, and Hurst index, the spatio-temporal process was analyzed. The results showed that the ecological environmental quality of the mining area first decreased and then increased from 1990 to 2020. 1990-2000 was a period of serious ecological degradation, followed by improvement. The overall improvement area reached 87.03%, and the degradation was concentrated in the coal mining area. Between 1990 and 2020, the Hurst index of the mining area was 0.452, indicating that the region has a fragile ecological environment and has difficult maintaining its stability. The global Moran's I mean value of the RSEI of the study area is 0.92, which combined with Moran's scatter plot to indicate that there is a strong positive spatial correlation rather than a random distribution of its ecological environment. During the study period, the impact on the climate of the ecological environmental change of POMA was weak, and human factors such as coal mining, land reclamation, and social construction were the main driving forces for the change in ecological quality. The results of this study reveal the changing trend of surface ecology in the mining area over the past 30 years, which is helpful for understanding its impact mechanism on ecological quality and provides support for the management of the region.

How to synergize ecological restoration to co-benefit the beneficial contributions of nature to people on the Qinghai-Tibet Plateau?

Understanding the magnitude and spatial distribution of ecological restoration requires a precise assessment of the beneficial contributions of nature to people. However, where the restoration areas should be located and whether the natural contribution of a compensation area can satisfy people's needs in the context of ecological degradation remain unclear. To address these issues, we selected the Qinghai-Tibet Plateau as the study areas, utilizing the offset portfolio analyzer and locator model to identify the compensation sites that offset the losses of ecosystem services and biodiversity resulting from ecological degradation. These compensation sites were developed through two offset types: restoration and protection. Then, based on the offset sites, we assessed nature's contribution to people (NCP) under the current status and future scenarios in terms of various aspects, including the habitat (NCP1), climate change (NCP4), and water quantity and flow regulation (NCP6). This study found that the area impacted by agricultural development was 7.15 × 105 ha, and the required compensation area was 5.5 × 106 ha under the current status. The ratio of the impacted area to the required area was approximately 7.0 in the future scenarios. The average habitat qualities were 0.14 and 0.30, while the mean NCP1 values were 2.69 and 0.51 in the protection and restoration offset sites, respectively. Moreover, based on the offset sites, the high-value contributions in NCP4 accounted for 18.64%-22.69% and 38.87%-46.17% of the total offset sites in terms of the restoration and protection offset types, respectively. Additionally, the estimated high-value contributions in NCP6 accounted for 58.35%-59.02% and 84.40%-95.86% of the total offset sites in the restoration and protection offset types, respectively. Our findings highlighted the significance of ecological restoration in showcasing the role of NCPs. These results could aid conservation managers in developing more targeted ecological strategies to enhance human well-being.

A novel approach to forecast dust concentration in open pit mines by integrating meteorological parameters and production intensity

Mine dust pollution poses a hindrance to achieving green and climate-smart mining. This paper uses weather forecast data and mine production intensity data as model inputs to develop a novel model for forecasting daily dust concentration values in open pit mines by employing and integrating multiple machine learning techniques. The results show that the forecast model exhibits high accuracy, with a Pearson correlation coefficient exceeding 0.87. The PM2.5 forecast model performs best, followed by the total suspended particle and PM10 models. The inclusion of production intensity significantly enhances model performance. Total column water vapor exerts the most significant impact on the model's predictive performance, while the impacts of rock production and coal production are also notable. The proposed daily forecast model leverages production intensity data to predict future dust concentrations accurately. This tool offers valuable insights for optimizing mine design parameters, enabling informed decisions based on real-time forecasts. It effectively prevents severe pollution in the mining area while maximizing the use of natural meteorological conditions for effective dust removal and diffusion.

A new pattern to quantitatively evaluate the value of ecosystem services in the large-scale open-pit coal mining area

Introduction

Open-pit coal mining could disrupt the ecosystem and lead to the loss of service values for the ecosystem through direct occupation or indirect impacts on adjacent ecosystems.

Methods

In this research, we combined a new accounting system, gross ecosystem product (GEP), with spatial–temporal analyses to quantify the ecological variation and explore its driving factors in Pingshuo, a large-scale open-pit coal mining area in China. GEP is an aggregate accounting system that can summarize the value of provisioning, regulating, and cultural ecosystem services (ES) in a single monetary metric. The spatial–temporal approaches used in our study were known as exploratory spatial data analyses and interpretable models in machine learning. Both spatial and non-spatial data, including remote sensing images, meteorological data, and official statistics, were applied in the research.

Results

The results indicated the following: (i) From 1990 to 2020, the annual average growth rates of GEP decreased from 30.78 to 9.1%. Furthermore, the classified results of GEP revealed that the regions with rich ES quality rapidly reduced from 51.90 to 32.18%. (ii) Spatial correlation of GEP was significant, and the degree of spatial clustering was relatively high in the mining areas. Moreover, the mining areas also continually presented concentrated high-density and hot spot areas of GEP changes. (iii) The spatial–temporal effects were notable in the relationship between GEP and three socioeconomic factors, i.e., the mining effects, human activity intensity, and gross domestic product (GDP). (iv) The win–win development for both the economy and ecological environment in Pingshuo could be realized by restricting the annual growth rate of mining areas to between 4.56 and 5.03%.

Discussion

The accounting results and spatial–temporal analyses of GEP will contribute to the future regional sustainable development and ecosystem management in Pingshuo.

Using POI and time series Landsat data to identify and rebuilt surface mining, vegetation disturbance and land reclamation process based on Google Earth Engine

The development of coal resources is necessary, but it has a huge negative impact on land, ecology, and the environment. With the increasing awareness of environmental protection and the requirements of related regulations, the design and practice of reclamation projects run through the mining life cycle and continue for a long time after the coal production. High-precision monitoring of mining disturbance and reclamation, quantifying the degree and time of vegetation disturbance and restoration, is of great significance to minimize the environmental effect of mining. Remote sensing, widely used as efficient monitoring tool, but there is not enough research on disturbance and reclamation monitoring taking into account large-scale areas and high temporal and spatial accuracy. Especially when mining sites remain unknown, how to distinguish the disturbance of coal mining and other human activities affecting the surface land cover has become a challenge. Therefore, this paper proposed a method to reconstruct the time series of mining disturbance and reclamation in a large area by using the POI (point of interest) and Landsat time series images using multiple buffer analysis methods. The process includes: (1) Retrieval of POI in the study area based on the public mining list using Python crawler, and buffering 100 km for preliminary extraction of potential mining areas; (2) Using spectral index mask and random forest algorithm to accurately extract the exposed coal on the Google Earth Engine (GEE) platform; (3) Buffering 10 km to identify the occurrence of disturbance and reclamation, using pixel-based temporal trajectory identification of LandTrendr algorithm under GEE. The method successful detect the change points of surface coal mining disturbance and reclamation in eastern Inner Mongolia of China. The results show that: (1) The method can effectively identify the extent of surface coal mining disturbance and reclamation, and the overall extraction accuracy is 81%. (2) Surface coal mining disturbance in eastern Inner Mongolia was concentrated in 2006-2011. By 2020, the total disturbed area is 627.8 km², with an average annual disturbance of 18.5 km², and the annual maximum disturbance to the ground reached 64.6 km² in 2008. With the total reclaimed area being 236.3 km², the reclamation rate is about 37.6%. This study provides a systematic solution and process for monitoring the disturbance and reclamation of surface coal mining in a large range with little known about the mines' location. It can effectively identify the mining disturbance and reclamation process which can also be extended to other areas, providing a quantitative assessment of mining disturbance and reclamation, which can support further ecological restoration decision-making.

Is China approaching the inflection point of the ecological Kuznets curve? Analysis based on ecosystem service value at the county level

Accounting for the ecosystem service values (ESVs) and discussing the relationship between the ESVs and economic development can help achieve sustainable ecological development. Therefore, this paper evaluates the county-level ESVs of various land types in China, and depicts the distribution of ESVs in various urban agglomerations. In addition, the nonlinear relationship between ESVs and economic development is revealed. The main findings are as follows: (1) From 2000 to 2018, the ESVs in China decreased, and the decline rate of ESVs in urban agglomerations is much higher than that of China as a whole. (2) The decline rate of ESVs in core cities is much higher than in urban agglomerations, and the decline rate of ESVs is higher in areas close to core cities and lower in areas far from core cities. (3) The ecological Kuznets curve of China has a positive "U" shape, and the ecological Kuznets curve of urban agglomerations has an "N" shape; the ecological Kuznets curve of core cities has a positive "U" shape, while the ESVs of other cities decreases monotonically with the increase of the economic level.

Improvement of ecosystem quality in National Key Ecological Function Zones in China during 2000-2015

Improving ecosystem quality is the ultimate goal of ecological restoration projects and sustainable ecosystem management. However, previous results of ecosystem quality lack comparability among different regions when assessing the effectiveness of ecological restoration projects on the regional or national scales, due to the influence of geographical and climatic background conditions. Here we proposed a new index, ecosystem quality ratio (EQR), by integrating the status of landscape structure, ecosystem services, ecosystem stability, and human disturbance relative to their reference conditions, and assessed the EQR changes in China's counties and National Key Ecological Function Zones (NKEFZs) from 1990 to 2015. The results showed that the average ecosystem quality of China's counties deviated from the reference condition by 28%. EQR decreased by 1.2% during 1990-2000 but increased by 3.7% during 2000-2015. Those counties with increasing EQR in 2000-2015 occupy 64.7%, with obviously increasing counties mainly located in the water conservation, biodiversity maintenance, and water and soil conservation types of NKEFZs. The EQR increase in counties within NKEFZs was 3.65 times that outside of NKEFZs. Remarkable improvement of ecosystem quality occurred in the forest region in Changbai Mountain, biodiversity and soil conservation region in Wuling Mountains, and hilly and gully region of Loess Plateau, where EQR increases mainly resulted from the conversion of farmland to forest or grassland and consequent increases in ecosystem services and stability. The magnitude of EQR enhancement showed a positive relationship with the increase in forest and grassland coverage in NKEFZs. Our results highlight the important role of ecological restoration projects in improving ecosystem quality in China, and demonstrate the feasibility of the new index (EQR) for the assessment of ecosystem quality in terms of ecosystem management and restoration.

Mapping seasonal sentiments of people visiting blue spaces in urban wetlands: A pilot study on inland cities of China

To evoke positive human emotions is a critical goal of blue spaces in urban wetland parks. However, information is still scarce on how people self-express across the spatiotemporal spectrum when they come across wetlands which include varying levels of elevation in a single landscape and microclimate. In this study, 30 urban wetland parks were selected from 17 cities in Central China, where a total of 1,184 portrait photos of visitors were obtained from a social media platform (Sina Weibo) to analyze their expressed sentiments by rating facial expression scores of happy and sad emotions and net positive emotion index (NPE; happy-score minus sad-score) in 2020. Landscape metrics were remotely evaluated for every wetland park, and microclimatic factors were obtained for the days when the photos were taken. Based on regressions of park-level data, blue-space areas could be perceived as a positive driver to trigger happiness in spring (regression coefficient [RC] of 0.20), but it triggered negative emotions in autumn (RC of −2.98). The higher elevation areas triggered positive emotions in summer and autumn (RC of 1.35 × 10−3), but extreme daily temperature, air humidity, and wind velocity together triggered sadness (RC of 0.11, 0.03, and 0.51, respectively). Mapped distribution of the area and corresponding emotions showed that visiting blue space evoked more smiles in wetland parks of northern Hunan, southern Hubei, and eastern Anhui in spring. Blue spaces in Shanxi and northwestern Hebei evoked better moods in autumn. Smaller blue spaces in wetlands located at higher elevations were recommended for nature enthusiasts in warm seasons to overcome the prevalent sadness characteristic of that time of the year and location.

Modeling impacts of mining activity-induced landscape change on local climate

As a major energy source, coal has been mined on an increasingly larger scale as the social economy has continuously developed, resulting in drastic land type changes. These changes in turn cause changes in the local climate and affect the local ecological environment. Therefore, for coal cities, mining activities are an important factor influencing the local climate, and clarifying the impact of mining activities on the ecological environment is important for guiding regional development. In this paper, the impact of land use/cover changes (LUCCs) on local temperature in the spring and summer seasons from 1980 to 2018 was simulated using the Weather Research and Forecasting (WRF) model with Xilinhot city as the study area, and the regional distribution of local surface energy was analyzed in conjunction with the ground-air energy transfer process. The results show that the grassland area in Xilinhot remained above 85% from 1980 to 2018, so mining activities had a small impact on the average temperature of the whole region. However, in the mining area, the warming effect caused by mining activities was more obvious, with an average temperature increase of 0.822 K. Among other land transformation types, the conversion to water bodies had a very obvious cooling effect, lowering the temperature by an average of 2.405 K. By comparing the latent heat flux (LH), sensible heat flux (SH), and ground heat flux (GRD) under different land use types, it was found that in 2018, the LH decreased by 0.487 W/m², the SH decreased by 0.616 W/m², and the GRD decreased by 0.753 W/m². The conversion to built-up urban land caused a significant decrease in the LH in the corresponding area, allowing more energy to be used to increase SH values, which resulted in significantly higher urban temperatures than in other areas.

Dust pollution in cold region Surface Mines and its prevention and control

The application of traditional dust reduction methods in surface mines is limited, particularly during winter due to long-term drought and a rainless environment. Therefore, it is essential to investigate dust pollution in cold region mines and get insights into its scientific prevention and control. This research analyzed dust pollution (concentration of TSP, PM10, PM2.5) from a combined perspective of production and metrological conditions in the Haerwusu open pit coal mine located in northwest China to provide the basis for prevention and control. The main findings indicate that the dust concentration in the pit exceeds the national regulatory limit of 50 μg/m for PM10 and 35 μg/m for PM2.5. According to the air quality index, PM10 was the primary pollutant at the bottom of the pit where coal mining was occurring. The order of the factors influencing dust concentration was as follows: coal production > boundary layer height > wind speed > temperature difference > temperature > humidity. Our study revealed that mining activity polluted the surrounding areas, mostly in December and January. The southeastern and eastern regions of the mine site were found to be the most polluted areas. The implications of this study could be used to optimize mining operations and develop dust prevention and control strategies.

The Grain for Green Program Intensifies Trade-Offs between Ecosystem Services in Midwestern Shanxi, China

Ecological engineering is a widely used strategy to address environmental degradation and enhance human well-being. A quantitative assessment of the impacts of ecological engineering on ecosystem services (ESs) is a prerequisite for designing inclusive and sustainable engineering programs. In order to strengthen national ecological security, the Chinese government has implemented the world’s largest ecological project since 1999, the Grain for Green Program (GFGP). We used a professional model to evaluate the key ESs in Lvliang City. Scenario analysis was used to quantify the contribution of the GFGP to changes in ESs and the impacts of trade-offs/synergy. We used spatial regression to identify the main drivers of ES trade-offs. We found that: (1) From 2000 to 2018, the contribution rates of the GFGP to changes in carbon storage (CS), habitat quality (HQ), water yield (WY), and soil conservation (SC) were 140.92%, 155.59%, −454.48%, and 92.96%, respectively. GFGP compensated for the negative impacts of external environmental pressure on CS and HQ, and significantly improved CS, HQ, and SC, but at the expense of WY. (2) The GFGP promotes the synergistic development of CS, HQ, and SC, and also intensifies the trade-off relationships between WY and CS, WY and HQ, and WY and SC. (3) Land use change and urbanization are significantly positively correlated with the WY–CS, WY–HQ, and WY–SC trade-offs, while increases in NDVI helped alleviate these trade-offs. (4) Geographically weighted regression explained 90.8%, 94.2%, and 88.2% of the WY–CS, WY–HQ, and WY–SC trade-offs, respectively. We suggest that the ESs’ benefits from the GFGP can be maximized by controlling the intensity of land use change, optimizing the development of urbanization, and improving the effectiveness of afforestation. This general method of quantifying the impact of ecological engineering on ESs can act as a reference for future ecological restoration plans and decision-making in China and across the world.