Temporal-Spatial Evolution of the Urban Ecological Footprint Based on Net Primary Productivity: A Case Study of Xuzhou Central Area, China

Impact of the Levels of COVID-19 Pandemic Prevention and Control Measures on Air Quality: A Case Study of Jiangsu Province, China

In order to control the spread of the COVID-19 pandemic, the prevention and control measures of public health emergencies were initiated in all provinces of China in early 2020, which had a certain impact on air quality. In this study, taking Jiangsu Province in China as an example, the air pollution levels in different regions under different levels of pandemic prevention and control (PPC) measures are evaluated. The implementation of the prevention and control policies of COVID-19 pandemic directly affected the concentration of air pollutants. No matter what level of PPC measures was implemented, the air quality index (AQI) and pollutant concentrations of NO2, CO, PM10 and PM2.5 were all reduced by varied degrees. The higher the level of PPC measures, the greater the reduction was in air pollutant concentrations. Specifically, NO2 was the most sensitive to PPC policies. The concentrations of CO and atmospheric particulate matter (PM10 and PM2.5) decreased most obviously under the first and second level of PPC. The response speed of air quality to different levels of PPC measures varied greatly among different cities. Southern Jiangsu, which has a higher level of economic development and is dominated by secondary and tertiary industries, had a faster response speed and a stronger responsiveness. The results of this study reflect the economic vitality of different cities in economically advanced regions (i.e., Jiangsu Province) in China. Furthermore, the results can provide references for the formulation of PPC policies and help the government make more scientific and reasonable strategies for air pollution prevention and control.

A New Perspective for Urban Development Boundary Delineation Based on the MCR Model and CA-Markov Model

In order to control the development of urban space, it is important to explore scientific methods to provide a reference for regional territorial space planning. On the basis of the minimum cumulative resistance (MCR) model and the cellular automaton (CA)-Markov model, we constructed a new technical method for delineating urban development boundaries, exploring the temporal and spatial distribution characteristic of land use in Wuhan from 2010 to 2020 through nighttime and remote sensing images, and simulating the urban development boundaries of Wuhan from 2025 to 2035. The results show that: (1) the scales of Wuhan City’s built-up areas in 2010, 2015, and 2020 were 500 km2, 566.13 km2, and 885.11 km2, respectively, and the trends of expansion run to the east and southeast, and (2) on the basis of the MCR model, the urban development boundary scale of Wuhan City in 2025, 2030, and 2035 from the perspective of actual supply will be 903.52 km2, 937.48 km2, and 1021.44 km2, respectively, and based on the CA-Markov model, the urban development boundary scales of Wuhan City in 2025, 2030, and 2035 from the perspective of ideal land demand will be 912.75 km2, 946.40 km2, and 1041.91 km2, respectively. By combining the results of the two methods, we determined areas of 901.62 km2, 944.39 km2, and 1015.36 km2 as the urban development boundaries of Wuhan City in 2025, 2030, and 2035, respectively. According to the principle of supply–demand balance, the urban development boundary delineated by the integration of the MCR model and CA-Markov model, which is in line with the spatial expansion trend of growing cities, could optimize the urban development pattern; solve the contradiction between urban development, farmland protection, and ecological protection; and provide a methodological reference and decision-making basis for planning practice.

Using Net Primary Productivity to Characterize the Spatio-Temporal Dynamics of Ecological Footprint for a Resource-Based City, Panzhihua in China

An ecological footprint is a primary indicator in measuring the sustainability of regional development, especially in resource-based cities. Here, we built an ecological footprint-based framework to assess the sustainability for a resource-based city of Panzhihua, in China. In this framework, a suite of long-term ecological parameters (2000–2020), essentially including Net Primary Productivity (NPP), land cover, as well as social statistical data, was used as the input indices of a provincial hectare ecological footprint model. The model outputs are composed of the ecological footprint (EF), ecological footprint per capita (PEF), ecological capacity (EC), ecological capacity per capita (PEC), ecological deficit/surplus (ED/S), and per capita ecological deficit/surplus (PED/S). Then the sustainable development capability of the city was comprehensively evaluated using a suite of ecological indices, including the ecological pressure index (EPI), ecological footprint per ten thousand GDP (EFG), ecological sustainability index (ESI), and ecological coordination index (ECI). The study reveals that, from 2000–2020, (1) PEC and PED/S presented an increasing trend (0.2401 hm2/person and 2.1421 hm2/person, respectively), while PEF decreased by 1.9 hm2/person. In the case of the ecological deficit, fossil energy land and forest were the dominant land types in controlling the ecological footprint and ecological capacity, (2) EPI and EFG decreased by 6.6381 hm2/person and 2.2462 hm2/person, respectively, and ESI and ECI increased by 0.3436 hm2/person and 0.2897 hm2/person, respectively. These indices also reflect that the utilization rate of natural resources in Panzhihua City has been improved, with enhanced sustainability, as well as a decline in ecological pressure. This ecological footprint-based framework could work as a template for evaluating the sustainability of resource-based cities from positive and negative ecological footprint indices.

Effect of income and energy efficiency on natural capital demand

This study explores the driving forces of natural capital demand to help solve the new problems faced by China's regional sustainable development and formulate relevant policies on resource utilization, ecological compensation, and energy structural adjustment. We find a significant and inverted U-shaped relationship between income and natural capital demand. Both economic development and environmental protection can only be improved beyond the inflection point. Energy efficiency is also closely related to natural capital demand, and its continuous improvement can slow down the rise in natural capital demand. This research provides important implications for the spread and allocation of natural capital regionally. It recommends the national allocation of natural capital, formulation of differentiated environmental policies, and improvement in energy efficiency by improving scale, technology, and structure.

Spatial Allocation Based on Physiological Needs and Land Suitability Using the Combination of Ecological Footprint and SVM (Case Study: Java Island, Indonesia)

Indonesia currently has 269 million people or 3.49% of the world’s total population and is ranked as the fourth most populous country in the world. Analysis by the Ministry of Public Works and Public Housing of Indonesia in 2010 shows that Java’s biocapacity is already experiencing a deficit. Therefore, optimization needs to be done to reduce deficits. This study aims to optimize and assess spatial allocation accuracy based on land-use/land cover suitability. In this study, the ecological footprint (EF) is utilized as a spatial allocation assessment based on physiological needs. The concept of land suitability aims for optimal and sustainable land use. Moreover, the land suitability model was conducted using the support vector machine (SVM). SVM is used to find the best hyperplane by maximizing the distance between classes. A hyperplane is a function that can be used to separate land-use/land cover types. The land suitability model’s overall-accuracy model was 86.46%, with a kappa coefficient value of 0.812. The final results show that agricultural land, plantations, and pastureland are still experiencing deficits, but there is some reduction. The deficit reduction for agricultural land reached 510,588.49 ha, 18,986.14 ha for plantations, and 1015.94 ha for pastures. The results indicate that the SVM algorithm is efficient in mapping the land-use suitability and optimizing spatial allocation.

Dynamics of the surface thermal landscape (STL) in northern slope of central Tianshan mountains, Xinjiang, NW China from 2000 to 2018

Using the 2000-2018 MODIS Land Surface Temperature (LST) data and taking 11 cities (counties) in the northern slope of the central Tianshan Mountains in northwestern China as the study area, the spatial-temporal characteristics, landscape indices, centroid, and geo-information Tupu (carto-methodology in geo-information, CMGI) of surface thermal landscape (STL) were analyzed, and the paper draws the following results: (1) There are great differences in the diurnal and seasonal STL. The higher thermal levels are distributed more northerly in spring, summer, and autumn, and more southerly in winter. (2) In terms of class type level and landscape level, different landscape indices show different characteristics in diurnal and seasonal thermal landscapes. (3) Centroids at different thermal levels during the daytime are more dispersed than at nighttime in spring and summer, while the opposite is found in autumn. In winter, centroids of different thermal levels are concentrated in the southern and central-southern regions. During the period of 2000-2018, centroids of different thermal levels tend to move with the varying of STL. (4) The whole STL in same seasons changed little, transition usually happens between adjacent thermal levels. Overall, compared with the eastern monsoon area, there are similarities and differences in the characteristics of the STL.

An Integrated Indicator System and Evaluation Model for Regional Sustainable Development

Regional sustainable development has become a worldwide issue in recent years, but there is no single and universally agreed method of choosing indicators for sustainable development assessment. The subjective selection of indicators will affect the results of assessment. Each evaluation method has its own advantages and disadvantages, and the methods used to determine indicator weight also differ. Regional sustainable development is a complex system, which is difficult to evaluate objectively and scientifically using a single method. Therefore, a new integrated indicator system and evaluation model is constructed here to more accurately reflect regional sustainable development level. The indicator system and evaluation model were constructed using a case study of 17 cities in Shandong Province, China. The indicator system includes 4 subsystems, i.e., economy, society, resource, and environment. These indicators were selected through correlation analysis and discrimination analysis. A back propagation neural network was applied to evaluate the respective scores of the 4 subsystems. The comprehensive score for regional sustainable development was evaluated using the analytic hierarchy process with entropy correction. The results show that sustainable development levels in these 17 cities show a gradually decreasing trend from east to west and from coast to inland. Cities with an underdeveloped economy usually display poor levels of social development and serious environmental pollution. Through the improvement of indicator screening, evaluation model, and result correction, the error caused by a single evaluation method can be reduced significantly. This new methodology for indicator selection and comprehensive evaluation provides a new perspective for the assessment of regional sustainable development.

Henan Ecological Security Evaluation Using Improved 3D Ecological Footprint Model Based on Emergy and Net Primary Productivity

The ecological footprint (EF) model is an effective tool for determining whether natural assets are over-utilized. The traditional EF (TEF) model and its improved model which include the emergy ecological footprint (EEF) and net primary productivity ecological footprint (NPPEF) have been widely used, but some emergy data are hard to obtain and NPP data is not stable. Therefore, in this paper, a novel three-dimensional (3D) EF model with emergy and net primary productivity (3DEF-ENPP) is proposed. The Henan province of China was chosen as the research area and commonly used statistical yearbook data and NPP data were used which are easy to obtain. We expanded a 2D EF model to a 3D EF model and took advantage of emergy analysis and net primary productivity because they have stable energy parameters, can reflect the difference in bioproductivity of different land types, and are suitable for spatial and temporal analysis. Based on our model, we obtained a rectified emergy-based ecological footprint (REEF), an ecological capacity based on net primary productivity (RNPPEC), a rectified ecological deficit (RED), an ecological footprint intensity (EFI), an ecological coordination coefficient, and a 3D-EF, which can comprehensively reflect Henan’s ecological security status. The results show that: (1) The REEF and RNPPED obtained by our proposed model are more stable than those of the former method. (2) Henan’s RED has been negative and has a downward trend, which indicates the burden of human activities on the natural environment are becoming increasingly serious. (3) The EF is increasing with time, indicating that the consumption of natural resources in Henan is gradually increasing. High EF regions are mainly distributed in the northwestern area. Southeastern regions have relatively low EFs. (4) Capital flows cannot meet the needs of current social development in Henan province and it is in a state of unsustainable development. (5) The ecological stress index is at a safe state but is still at an ecological security warning level and Henan has good ecological coordination.