Spatial Distribution In China Research Articles

Measurement and spatiotemporal characteristics of China's green finance.

To study the extent of green finance development in China, this article constructs a green finance index system and employs the entropy value method to measure China's green finance by using a yearly provincial panel data from 2001 to 2020. The Thiel and Moran indices are then used to systematically analyze the temporal and spatial distribution of China's regional green finance. The findings are summarized as follows. Firstly, the overall green finance index in China experiences an upward trend. The development of green finance in the eastern region is superior to that in other regions in terms of absolute value and growth rate. Moreover, the differences in China's green finance index have shown an increasing trend over the last two decades, which is mostly contributed by the intra-regional differences. Finally, the inter-regional distribution of green finance index demonstrates that green finance development has a spatial spillover effect.

Study on the Spatial Distribution Characteristics and Influencing Factors in the Reuse of National Industrial Heritage Sites in China

Industrial heritage is a valuable spatial resource for urban stock updates, and its preservation and reuse play an important role in the transmission of urban history and culture. Typological analysis, descriptive statistical analysis, relevant spatial analysis using ArcGIS 10.8, and geographic probes were employed to explore the spatial distribution characteristics and influencing factors regarding the current status of the reuse of 196 heritage sites selected from five batches of China’s National Industrial Heritage (NIH) lists. The results reveal the following: (1) The spatial distribution of China’s NIH sites is uneven and cohesive, forming a dense circle with the Yangtze River Delta region and the Beijing–Tianjin–Hebei region at its core. (2) Three-fourths of the NIH sites have entered the reuse stage, and high-density and relatively high-density clusters have formed in the eastern and central regions. (3) The conservation and reuse directions of China’s NIH sites are mainly divided into publicization and marketization. (4) The spatial distribution differentiation of the reuse of NIH sites is not due to a single cause but, rather, a combination of various contributing factors. Natural geographic and socio-economic factors exert varying degrees of influence on the spatial distribution of reused heritage sites, with tourism resources and government support playing primary roles in shaping this distribution. These findings establish a fundamental database of China’s NIH sites and provide guidance for the current conservation and reuse of industrial heritage.

Research on the Impact of Market Integration on Regional Productivity: A Spatial Econometric Approach for Chinese Regions

The process of market integration has a profound impact on regional output activities. This paper discusses the impact mechanism of market integration on regional productivity. Using China’s province-level panel data from 2006 to 2019, a spatial econometric model is constructed to empirically analyse the actual impact of China’s market integration process on regional productivity at this stage. The empirical study found that the spatial distribution of China’s regional productivity at the current stage exhibits the agglomeration characteristics of “high in the east and low in the west”. The process of market integration can not only significantly promote the productivity of the region, but also have a significant positive impact on the productivity of geographical and economic neighbouring regions. The subregional empirical results show that the marginal impact of the market integration process on productivity in different regions is heterogeneous, showing that the marginal impact on the eastern and coastal regions is stronger than that in the central and western regions. Altogether, this study provides empirical evidence of the positive impact of market integration on regional productivity in the spatial dimension, having significant implications for regional coordinated and sustainable development.

Impact of Spartina alterniflora Invasion in Coastal Wetlands of China: Boon or Bane?

Invasive plants, like Spartina alterniflora (SA), have a competitive advantage over native flora due to their rapid utilization of vital soil nutrients. This results in the depletion of resources for native plant species, significantly impacting ecosystem diversity and stability. This comprehensive review addresses several key aspects related to SA's spread and spatial distribution in China's wetlands. The rapid expansion of Spartina alterniflora is attributed to its high reproductive ability, adaptability to environmental factors like elevated salinity, and ability to disperse its seeds via tides. Spartina alterniflora mainly were found in Zhejiang, Jiangsu, Fujian, and Shanghai provinces, accounting for more than 90% of China's total Spartina alterniflora area. Spartina alterniflora rapid growth results in displacement of native species and loss of vital microbial, plant, and animal diversity. Some studies reported that Spartina alterniflora increases carbon storage, while others argue that it weakens this function. The impact of Spartina alterniflora on organic and inorganic carbon requires further research for better understanding dynamics of carbon in coastal wetlands. The controlled growth of Spartina alterniflora can be beneficial in many aspects of the coastal wetlands' ecosystem. In China, various methods have been employed to control the invasion of SA. Physical control, such as removing the plants and converting them into fertilizer or bioenergy, has been commonly used but has limitations like air pollution and the potential for re-invasion. Chemical herbicides like Imazapyr and Haloxyfop-R-methyl have effectively controlled and prevented re-invasion in specific areas, but their potential adverse impacts are still uncertain. Wetland Park construction, aquaculture development, and substituting native or exotic species with mangroves or reed communities have also been successful. It becomes evident that a long-standing and Contextual approach is necessary to effectively manage the advantages and curtail the drawbacks associated with S. alterniflora across China.

Economic and scale prediction of CO2 capture, utilization and storage technologies in China

In response to the lack of global quantitative research on the potential and scale prediction of CO2 capture, utilization and storage (CCUS) in China under the background of carbon peak and carbon neutrality goals, this study predicts the future economic costs of different links of CCUS technologies and the carbon capture needs of different industries in the scenario of fossil energy continuation. Based on the CO2 utilization and storage potential and spatial distribution in China, a cost-scale calculation model for different regions in China in 2060 is constructed to predict the whole-process economic cost and its corresponding scale potential of CCUS. The results show that a local + remote storage mode is preferred, together with a local utilization mode, to meet China's 27×108 t/a CO2 emission reduction demand under the scenario of fossil energy continuation. Specifically, about 5×108 t CO2 emission is reduced by capture utilization, and the whole-process cost is about −1400–200 RMB/t; about 22×108 t CO2 emission is reduced by capture storage, and the whole-process cost is about 200–450 RMB/t. According to the model results, it is recommended to develop the chemical utilization industry based on P2X (Power to X, where X is raw material) technology, construct the CCUS industrial cluster, and explore a multi-party win-win cooperation mode. A scheme of national trunk pipeline network connecting areas connecting intensive emission reduction demand areas and target storage areas is suggested. The emission reduction cost of thermal power based on CCUS is calculated to be 0.16 RMB/(kW·h).

Stability and Changes in the Spatial Distribution of China’s Population in the Past 30 Years Based on Census Data Spatialization

As the world’s most populous country, China has experienced massive population growth and dramatic regional migration over the past 30 years. From 1990 to 2020, the national population increased by 24.4%, the urban population tripled, and the rural population declined by 41.0%. Combined with complex topographic features, unique characteristics of the population distribution have emerged. Many studies have examined changes in the spatial distribution of the population. However, few studies have examined the stability of certain aspects of this distribution over the last 30 years, particularly at the raster scale, which may provide important information for future research and development plans. Based on land use maps and nighttime light images, China’s census data from 1990 to 2020 was scaled down to a resolution of 1 km using a method called multiple linear regression based on spatial covariates. The results show that there were some striking features of both stability and change in the spatial distribution of China’s population over the past three decades. The population shares divided by the Hu line, the Qinling-Huaihe line, and the three-step staircase have remained almost unchanged. In contrast, the population share of the coastal region has risen from 23.7% to 29.0% during the study period. The urban areas have expanded by 1.35 times and their population has doubled. In addition, for every 1 km2 increase in the urban areas, an area of 29.4 km2 has been depopulated on average. This suggests that urbanization can alleviate population pressure in larger areas. However, the coastal regions and urban and peri-urban areas were the main areas of population density growth, so they required a great deal of attention for ecological protection.

The spatial distribution of China's solar energy resources and the optimum tilt angle and power generation potential of PV systems

This study aims at filling the gaps and completing the missing global solar radiation and diffuse solar radiation data considering the limited radiation data of 85 meteorological observation stations and the routine meteorological data of 2001 meteorological observation stations. Employing the Inverse Distance Weighing model, the annual and seasonal spatial distributions of global solar radiation and diffuse solar radiation are obtained. A calculation method of the optimum tilt angle of photovoltaic systems for optimal utilization is established using the Collares-Pereira and Rabl hourly solar radiation model and the solar radiation on sloped surfaces model. The spatial distribution of the optimum tilt angle is obtained using the proposed method. The simplified calculation method of the optimum tilt angle based on latitude and altitude is established by introducing two factors of latitude and altitude. In addition, the annual and seasonal photovoltaic power of China is calculated, and the spatial distribution of China's solar resource utilization potential is obtained using the calculated optimum tilt angle, solar radiation data on sloped surfaces, and the photovoltaic power model. The results show that the annual global solar radiation in China is in the range of 3097–7311 MJm−2, and the annual diffuse solar radiation value ranges from 495 to 3036 MJm−2. Moreover, the optimum tilt angle value in different regions of China is found to range between 14.5°and 49.1°, and the theoretical optimum tilt angle value generally aligns with the law of angle increasing with latitude. The annual photovoltaic power generation is between 117 kWhm−2 and 483 kWhm−2. Compared with the solar energy utilization potential of a PV placed on the horizontal surface, the annual average power generation of a PV panel placed at the optimum tilt angle can increase by up to 144.76 kWhm−2, with an average increase of 10.41%.

Changes in China's food security driven by nutrition security and resource constraints.

Food security and the utilization of natural resources in a sustainable manner are vital to the expansion of China's agricultural system. The relationship between environmental pressure and dietary structure has influenced the quantity and spatial distribution of China's food supply and demand, but it has not been evaluated. Our research centered on the security of China's food nutrition-resources-food (NRF) system, considering the inherent relationship between food security, nutritional health, and resource security. The following are the study's findings: (1) The Chinese population is rapidly changing from a diet focused on grains to a more diverse diet. Between 1990 and 2019, the dietary quality and nutritional status of Chinese individuals have vastly improved. In terms of nutrient levels, discrepancies between urban and rural resident persist, with urban residents consuming a diet that is closer to the ideal structure. However, the structure of rural residents' food consumption is diversifying, and the gap between urban and rural residents is gradually narrowing. (2) From 2000 to 2019, the pressure, status, and response indices of China's NRF system all show an upward trend, and the security of the NRF system has steadily grown. The magnitude of change in the response index exceeded that of the state index, which exceeded that of the pressure index. This indicates that the increase in the pressure and state indices of the NRF system was primarily attributable to the effectiveness of policy efforts.

Spatial effect of industrial policy on regional energy efficiency in China

ABSTRACT Puppeteer crawler technology is used to obtain regional industrial policy documents, and we make classification and assignment from the perspective of the legal effect of industrial policy documents to quantify industrial policy variable. At the same time, Super-SBM model is used to measure energy efficiency in different areas, and spatial Durbin model is constructed according to the panel data of 30 provinces in China from 2006 to 2018. The main conclusions are as follows : (1) The spatial distribution of China’s energy efficiency has a remarkable positive correlation from the global perspective. (2) The local industrial policy has a significant positive effect on its energy efficiency, while a negative spatial effect on energy efficiency in neighbouring regions.

Air Pollution (PM2.5) Negatively Affects Urban Livability in South Korea and China.

This study investigated the effect of the concentration of ambient fine particulate matter , a transboundary air pollutant, on the livability of neighboring areas of China and South Korea with the aim of informing common policy development. Grey relational analysis (GRA) and panel regression analysis were performed to examine the effect of concentration on various livability indicators. The results revealed that urban living infrastructure was an indicator of effect in both South Korea and China. Based on the high correlation between urban living infrastructure and concentration, it can be seen that clearly affects livability, shown by panel regression analysis. Other key livability indicators were traffic safety, culture and leisure, and climate indicators. Spatial analysis of the livability index revealed that from 2015 to 2019, livability improved in both South Korea and China, but there was a clear difference in the spatial distribution in China. High-vulnerability areas showed potential risks that can reduce livability in the long run. In South Korea and China, areas surrounding large cities were found to be highly vulnerable. The findings of this research can guide the establishment of policies grading pollution at the regional or city macro-level.

Research on Carbon Emission Efficiency Measurement and Regional Difference Evaluation of China’s Regional Transportation Industry

From a global perspective, carbon emissions are a global problem that needs to be solved urgently. At present, 61% of countries have committed to achieving net zero emissions. Compared with industry and construction, the transportation sector has become the focus and challenge for countries to achieve carbon neutrality due to the characteristics of strong mobility, scattered emission sources, and complex social behaviors. Therefore, the issue of carbon emissions in the transportation industry has become the focus of academic attention. This paper first calculates the carbon emission efficiency (CEE) of the regional transportation industry through the super-efficiency SBM model and then evaluates its regional differentiation characteristics through the Theil index, which has important practical significance for reducing regional carbon emissions. The results show that the national transportation CEE average value is 0.612, a relatively low level. The spatial distribution of China’s transportation CEE shows an obvious characteristic of “east highest and west lowest”. The regional differences in the transportation industry CEE are larger than those between regions. The differences in the transportation industry CEE among the eastern, central, and western regions are on the downward trend as a whole, and intra-regional differences are greater than inter-regional. The intra-regional differences cause the overall differences in transportation industry CEE; the eastern region contributed the most to the Theil index, while the central contributed the least. The biggest factor affecting the transportation industry CEE is the regional energy structure, and the smallest factor is the per capita GDP. This research has important reference significance on the target of carbon neutrality.

Climate change and city size: the role of temperature difference in the spatial distribution of China's population.

This paper examines the relationship between climate change and the spatial distribution of population in China. We establish a two-way fixed effects model to investigate the role of temperature difference in the spatial distribution of China's population. We find that the annual variation of temperature has an impact on city size in both large and small cities, and that city size tends to shrink as the temperature difference increases. Meanwhile, we also find that the population in the cities located south of Qinling-Huaihe Line and Aihui-Tengchong Line (Hu's Line) is more sensitive to temperature effects, and that the temperature difference has a significant negative effect on city size. Similarly, the same results are found for prefecture-level cities with low administrative levels. Considering the endogeneity between temperature change and city size, we adopt an instrumental variable using latitude to perform a more robust empirical analysis, the results of a series of robustness tests support these conclusions.

Identifying urban candidate brownfield sites using multi-source data: The case of Changchun City, China

Over the past 40 years, brownfield remediation has become an important issue of urban economic transition and revival, providing many social, economic, and environmental benefits to cities. Identifying urban candidate brownfield sites is an essential task of brownfield projects, but few attempts have been made to create a comprehensive dataset of their spatial distribution in China. This paper presents a new method for identifying urban candidate brownfield sites using multi-source data, including current urban land use maps, Baidu heat maps, business data, and Baidu street view. Our method for identifying urban candidate brownfield sites consists of four steps: (1) preparing and processing the basic data while screening potential contaminated sites using a current urban land use map, mapping the geographical coordinates of operating and non-operating businesses, and calculating the Baidu heat index; (2) integrating spatial multi-source data; (3) screening the intensity of use and the degree of abandonment for suspected sites in Baidu street view; and (4) conducting field surveys. The method was proposed and tested using a case study in the central region of Changchun, China, and 146 candidate brownfield sites were identified. The new data that we collected and our methodology can be used as quantitative and universally applicable tools within a discriminant analytical model framework, for urban geography, urban design, and landscape architecture. The resulting maps for urban candidate brownfields could also provide local government agencies with a technical reference for brownfield remediation.

Spatial distribution analysis of seismic activity based on GMI, LMI, and LISA in China

Abstract Recently, all kinds of geological disasters happen frequently on the earth. In China, there are countless earthquakes every year, which greatly affect the country’s economic level and development as well as the people’s life and health. The analysis of seismic activity is becoming more and more significant. In this article, the spatial distribution of China’s seismic activities was analyzed by using the provincial seismic data from 1970 to 2013. On the basis of spatial autocorrelation analysis theory, Global Moran’s I, Local Moran’s I, and the Local Indicators of Spatial Association are used to measure the geospatial distribution characteristics of China’s seismic activities. The research results show that earthquakes in mainland China have significant global autocorrelation characteristics as a whole, and the global autocorrelation coefficients are all positive. And the Z-value test (P < 0.05) shows that earthquakes in mainland China present a spatial agglomeration pattern. Furthermore, we observed a reduction trend in disparities of seismic activity among regions in China.

2000年以来中国潜在植被NPP的时空分布模拟

PDF HTML阅读 XML下载 导出引用 引用提醒 2000年以来中国潜在植被净初级生产力的时空分布模拟 DOI: 10.5846/stxb202111053112 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（42071216）；甘肃省自然科学基金项目（21JR7RA145） Estimation of temporal and spatial distribution of potential vegetation net primary productivity in China since 2000 Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:潜在植被的净初级生产力（PNPP）是在无人类干扰情况下，立地所能发育形成最稳定成熟植被的净初级生产力，PNPP能够直接反映自然生态系统的质量状况，是分离人类活动对生态环境影响的重要指标。研究改进了CASA （Carnegie-Ames-Stanford Approach）模型，引入潜在光合有效辐射吸收比例（PFPAR）模拟了2000-2020年中国植被PNPP的时空分布格局。结果表明：中国PNPP空间分布差异较大，东南沿海和东北大、小兴安岭地区PNPP较高，新疆、西藏等西部干旱、高寒地区PNPP较低，呈现以400 mm等降水量线为界的空间分异格局。2000-2020年，中国PNPP总体上呈现递增趋势，年际波动小，PNPP减少的区域与增加的区域面积基本相等。PNPP波动较大的地区主要位于青藏高原、四川盆地和贵州高原。研究结果量化了气候变化背景下真实的生态状况和潜在生态状况的差异，可分离出人类活动对自然生态系统的直接影响，为制定针对性的生态修复对策提供了科学依据。 Abstract:Potential vegetation net primary productivity (PNPP) is the NPP of the most stable and mature vegetation type without human interference in the current climate conditions. PNPP can directly reflect the quality of natural ecosystems, which is an important index to separate the impact of human activities on ecological environment. This paper improves the CASA model and introduces the potential fraction of photosynthetically active radiation (PFPAR) to simulate the temporal and spatial distribution pattern of PNPP in China's vegetation from 2000 to 2020. The results show that the spatial distribution of China's PNPP is quite different. The PNPP is higher in the coastal areas of southeast China and the Greater and Lesser Khingan Range in northeast China, and lower in the arid and alpine regions of western China such as Xinjiang and Tibet, presenting a spatial differentiation pattern with 400 mm isoprecipitation line as the boundary. From 2000 to 2020, China's PNPP generally showed an increasing trend over time, but the interannual fluctuation was small. The area of PNPP decreased and increased was almost the same. The changes of PNPP in most regions are small, and the areas with large PNPP fluctuation are mainly located on Qinghai-Tibet Plateau, Sichuan Basin and Guizhou. The research results can separate the impact of human activities and climate change on natural ecosystem, and quantify the difference between real ecological status and potential ecological status under external pressure. It provides a scientific basis for formulating differentiated Ecological Restoration Countermeasures. 参考文献 相似文献 引证文献

Analysis of Spatial–Temporal Characteristics of Industrial Land Supply Scale in Relation to Industrial Structure in China

Taking China’s industrial land transfer data as the data source, this study quantitatively analyzes the transfer structure and spatial distribution of China’s industrial land from 2010 to 2019. By constructing the information entropy and the equilibrium degree model of industrial land-use structure, this study evaluates the transfer characteristics of industrial land of different functional types in various provinces of China, analyzes the scale advantages of various types of transferred industrial land by using the land transfer scale advantage index, and summarizes the spatial distribution characteristics of different types of industrial land transfer in China through the spatial center of gravity analysis and cold/hot spot regional distribution mapping. The following results were obtained. (1) There are significant differences in the transfer scale of industrial land among provinces in China. The transfer scale of Eastern and Central China is large, whereas that of Western China is small. (2) From the perspective of land-use structure, the transfer scale of industrial land in the central and western regions is more balanced than that in the east. (3) From the gravity center distribution of the standard deviation ellipse, the land transfer direction of the energy industry, and the mining industry, and other types of industries is more significant than that of the culture and sports hygiene industries, modern manufacturing industry, and high-tech industry. (4) From the analysis of cold and hot spots, the mining industry, the energy industry, and other types of industries in the western region with rich mineral resources are the hot spots of industrial land transfer, and the southeast coast is the cold spot; the eastern coastal area is a hot area for land transfer of modern manufacturing, the high-tech industry, and the culture and sports hygiene industries. The results reveal the regional differences and spatial distribution characteristics of industrial transfer in China and provide a reference for authorities to formulate industrial planning and industrial land collection, storage, and transfer plans.

From efficiency to equity: Changing patterns of China's regional transportation systems from an in‐use steel stocks perspective

AbstractTransportation serves as a bridge for social production, distribution, exchange, and consumption and, thus, plays an important role in boosting the economy. In recent years, the rapid development of China's transportation system has driven a continuous accumulation of steel. In this study, we estimated the in‐use steel stocks of 32 types of infrastructure and vehicles in three subsystems (railway, road, and subway) in 31 provinces of China from 1990 to 2019 based on a bottom‐up approach. The results show that China's in‐use steel stock in the transportation system has increased to 575 Mt in 2019 (34.4% for infrastructure, 65.6% for vehicle). Spatially, this increasing trend shows six diversified patterns among 31 provinces; steel stocks tend to decrease from the east to central and western inland areas. The Gini coefficient curve of the provinces’ stocks shows an inverted “U” shape over time, indicating a shrinking regional gap in recent years; this reflects a transition from efficiency to equity. We also measured the steel stock productivity (GDP per stock) in different regions and observed its diverse evolution types. The stock productivities in all regions climbed up initially, but have dropped in recent years, and the most obvious decrease is observed in western China. For eastern regions, vehicles have been the main growth point in recent years, while western regions are vigorously developing infrastructure. Our results help to illustrate the development status and spatial distribution of China's transportation system and could facilitate improved efficiency and the management of future challenges in China's transformation and development.

Development potential of Chinese smart cities and its spatio‐temporal pattern: A new hybrid MADM method using combination weight

AbstractTaking advantage of information communication technology, a smart city is a city that has its critical urban infrastructure upgraded to optimise resources allocation and maintenance activities. It serves as a new technology‐based solution to mitigate urban diseases and to improve urban development in China. However, unbalanced and uncoordinated smart city development potential (SCDP) would impede the future construction of the smart city. Consequently, this study aims to measure SCDP and further examine the equality of its spatial distribution in China. In this regard, a brand‐new hybrid multiple attribute decision‐making (MADM) model is proposed to evaluate SCDP. Subsequently, a series of spatial analyses are introduced to uncover the spatial differentiation of SCDP. The results suggest that (a) overall SCDP in China has a continuous upward tendency, and the SCDP compositions of six subsystems contribute variously; (b) over time high‐SCDP cities agglomerated in the east, whereas most of the low‐SCDP cities clustered in the west. This feature indicates that SCDP in China is unevenly distributed; (c) high‐SCDP cities preferred to cooperate in coordinated efforts rather than develop independently. This study makes new contributions to smart city development research in terms of methodology and empirical evidence.

Characteristics and influencing factors of Airbnb spatial distribution in China's rapid urbanization process: A case study of Nanjing.

As in other countries, short-term rentals for tourism services are growing rapidly in China’s tourist cities, which are mainly operated through Airbnb. This paper explores whether the spatial distribution of Airbnb in China’s rapid urbanization process exhibits characteristics, paths, and drivers that are different from those of cities in other countries. Airbnb is a model for the global sharing economy, but it is increasingly influenced by other functions and facilities in cities as it grows. In this paper, the zero-expansion negative binomial regression was used to study the factors affecting the spatial distribution of Airbnb in Nanjing, China. The results showed that the spatial distribution of Airbnb listings was correlated with the distribution of cultural attractions, universities, public transport accessibility, shopping centers, and business apartments. By analyzing the driving forces of Airbnb’s development in Nanjing, this paper found that a large number of business apartments developed in cities were essential providers of Airbnb listings, and affected its spatial distribution. The gap between short-term and long-term rentals was also correlated with the distribution of Airbnb. In addition, similar to the previous literature findings, the increase in the proportion of professional hosts changes the original intention of Airbnb for sharing and communication. Our empirical results applies to the current situation of Airbnb in Chinese cities, which is conducive to the government’s more intelligent management and effective promotion of the Airbnb market. Our findings also provide positive references for urban renewal policies and public participation methods in China.

Evaluation of potential amounts of crop straw available for bioenergy production and bio-technology spatial distribution in China under ecological and cost constraints

A comprehensive evaluation model is built to analyze the potential of straw resources and suitability distribution of technology in China under environment and cost constraints. First, from the perspective of soil erosion prevention, soil organic carbon maintenance, and long-term crop yield, the ecological return amount of straw in different provinces is calculated using scenario design, literature review, and analytic hierarchy process. These processes, combined with technical and economic parameters of different technologies, are employed to analyze the appropriate spatial distribution of straw-fired generation (SFC), biomass gasification power generation (BGPG), cellulose ethanol technology (CEP), and biomass briquette fuel (BBF) under different policy and technological progress scenarios from the project level. The changes in planting area, crop unit yield, and wage are also considered in the evaluation; the obtained results indicate the following. First, if priority is given to agricultural ecological environment, the amount of straw available is less than that determined by the existing research, i.e., approximately 2.48 × 108, 1.55 × 108, and 8.68 × 107 t under low, medium, and high return scenarios, respectively. Second, Inner Mongolia is not suitable for planning any projects, and planned projects should compensate for the local agricultural ecological environment. Third, under the current policy and technical level scenario, resources for the BBF and CEP projects should be employed to prioritize the SFC and BGPG projects. Fourth, in combination with China’s current poverty alleviation policies, the planning of biomass energy projects in Gansu, Qinghai, Sichuan, Chongqing, and Guizhou should be prioritized because of their lower labor cost.