Research

26 pages, 5050 KiB

Open AccessArticle

Spatial-Temporal Characteristics and Influencing Factors of Particulate Matter: Geodetector Approach

by Hansol Mun, Mengying Li and Juchul Jung

Land 2022, 11(12), 2336; https://doi.org/10.3390/land11122336 - 19 Dec 2022

Viewed by 1906

In 2019, South Korea’s Framework Act on The Management of Disasters and Safety was revised to include respirable particulate matter as a social disaster. Urban air pollution, especially particulate matter pollution, has been a serious threat to socioeconomic development and public health. In [...] Read more.

In 2019, South Korea’s Framework Act on The Management of Disasters and Safety was revised to include respirable particulate matter as a social disaster. Urban air pollution, especially particulate matter pollution, has been a serious threat to socioeconomic development and public health. In order to address this problem, strong climate crisis response strategies and policies to improve urban air quality are necessary. Therefore, it is of great importance to assess the frequency of urban air pollution occurrence and its influencing factors. The objective of this study is to develop consistent methodologies for the construction of an index system and for assessing the influencing factors of urban particulate matter pollution based on population, social welfare, land use, environmental, transportation, and economic governance considerations. We applied the local indicators of spatial association and geographical detector methods, and 35 influencing factors were selected to assess their influence on urban air pollution occurrence in 229 cities and counties in South Korea. The results indicated the spatial pattern of the particulate matter concentration in these locations showed strong spatial correlation, and it was confirmed that there was a difference in distribution according to the season. As a result of the analysis of influencing factors, it was found that environment and land use characteristics were the main influencing factors for PM₁₀ and PM_2.5. The explanatory power between the two influencing factors of particulate matter was greater than that of a single influencing factor. In addition, most influencing factors resulted in both positive and negative effects on urban fine particulate matter pollution. The interaction relationship of all factors showed a strong action effect in the case of both PM₁₀ and PM_2.5, so it was confirmed that all influencing factors were interdependent. In particular, the findings proved that combining the two factors would have a more pronounced effect on particulate matter than when they were independent. We confirmed the significant results for the factors affecting particulate matter. This study offers suggestions on reducing urban air pollution occurrence that can be used to provide a basis and reference for the government to form policies on urban air pollution control in cities and counties. Full article

(This article belongs to the Special Issue The Impact of Land Use on Atmospheric Environment)

► Show Figures

Figure 1

18 pages, 4710 KiB

Open AccessArticle

Spatiotemporal Evolution Characteristics of Carbon Emissions from Industrial Land in Anhui Province, China

by Ting Zhang, Longqian Chen, Ziqi Yu, Jinyu Zang and Long Li

Land 2022, 11(11), 2084; https://doi.org/10.3390/land11112084 - 18 Nov 2022

Cited by 1 | Viewed by 1457

Abstract

Carbon emissions (CE) in Anhui Province are closely related to carbon emissions from industrial land (CEIL). In this study, based on industrial land, industrial energy consumption, and related statistical data in Anhui Province from 2000 to 2016, the carbon emissions coefficient method and [...] Read more.

Carbon emissions (CE) in Anhui Province are closely related to carbon emissions from industrial land (CEIL). In this study, based on industrial land, industrial energy consumption, and related statistical data in Anhui Province from 2000 to 2016, the carbon emissions coefficient method and the standard deviational ellipse were used to measure and analyze the CEIL and their spatial and temporal evolution characteristics, aiming to provide a basis for the relevant government departments to formulate CE policies. The main results showed that: (1) The total amount of CEIL followed an inverted U-shaped trend of rapid increase followed by a decrease, while the overall carbon emission intensity from industrial land (CEIIL) followed a downward trend. (2) The CE had an evident spatial differentiation, with those from resource-based cities being much higher than those of industrial and tourism-based cities; (3) The overall pattern of CEIL in Anhui Province showed that the increase in the north-south direction is significantly higher than that in the east-west direction, and mainly expanded in the north-south direction. The overall industrial growth rate of Southern Anhui, represented by the Wanjiang City Belt, was higher than that of Northern Anhui, although its CEIL center showed to move towards Northern Anhui. Full article

(This article belongs to the Special Issue The Impact of Land Use on Atmospheric Environment)

► Show Figures

Figure 1

19 pages, 5176 KiB

Open AccessArticle

Prediction of the Spatial Pattern of Carbon Emissions Based on Simulation of Land Use Change under Different Scenarios

by Zhenhua Wu, Linghui Zhou and Yabei Wang

Land 2022, 11(10), 1788; https://doi.org/10.3390/land11101788 - 13 Oct 2022

Cited by 4 | Viewed by 1690

Abstract

Land use is an important factor in the change of carbon emissions, and predicting the spatial pattern of carbon emissions under different land use scenarios is of great significance to respond to the “double carbon” target of China. Based on the land use [...] Read more.

Land use is an important factor in the change of carbon emissions, and predicting the spatial pattern of carbon emissions under different land use scenarios is of great significance to respond to the “double carbon” target of China. Based on the land use data of Nanjing city, Jiangsu Province, China in 2010, 2015 and 2020, this study used the Conversion of Land Use and its Effects at Small regional extent (CLUE-S) model to simulate the land use change pattern in 2030 under multiple scenarios, and predicted the carbon emissions of each subzone based on the simulation results. It also provides a carbon balance zoning from an economic and ecological point of view and proposes strategies tailored to each district. The results show that: (1) in 2030, under the ecological conservation scenario, ecological land all shows different degrees of increase, while under the cultivated land conservation scenario, construction land only increased by 1.47%. This indicates that the ecological and cultivated land protection perspectives can effectively curb the expansion of construction land. (2) The growth rate of carbon emissions in Nanjing from 2010–2030 decreased from 16.65–3.7%. This indicates that carbon emissions continue to rise, but the trend of growth is slowing down. (3) The spatial carbon emissions in Nanjing show an overall higher level in the north and lower in the center; the large expansion of building land and the concentration of industrial industries are the main reasons for the large increase in carbon emissions. Under the ecological protection scenario, the carbon emissions of Lishui, Pukou and Qixia districts were 11.05 × 10⁴ t, 19.437 × 10⁴ t and 10.211 × 10⁴ t lower than those under the natural growth scenario, mainly because these three districts have more ecological land and the ecological protection effect is more significant. Under the cultivated land conservation scenario, the growth rate of carbon emissions slows down significantly. This indicates that the future structure of carbon emissions in Nanjing will vary significantly, and that ecological protection and arable land conservation play an important role in reducing carbon emissions. This study shows that it is difficult to reduce emissions in a concerted manner. Therefore, for different districts, differentiated land use optimization measures should be developed according to local conditions, and ecological protection and cultivated land protection scenarios should both be taken into account. Full article

(This article belongs to the Special Issue The Impact of Land Use on Atmospheric Environment)

► Show Figures

Figure 1

16 pages, 2279 KiB

Open AccessArticle

Measurement and Influencing Factors of Low Carbon Urban Land Use Efficiency—Based on Non-Radial Directional Distance Function

by Han Chen, Chunyu Meng and Qilin Cao

Land 2022, 11(7), 1052; https://doi.org/10.3390/land11071052 - 11 Jul 2022

Cited by 17 | Viewed by 1556

Abstract

The development and use of urban land is a major source of carbon emissions. How to reduce carbon emissions in the process of urban land use without harming the economy has become an extremely important issue. This paper integrating carbon emissions into the [...] Read more.

The development and use of urban land is a major source of carbon emissions. How to reduce carbon emissions in the process of urban land use without harming the economy has become an extremely important issue. This paper integrating carbon emissions into the urban land use efficiency evaluation index system, measures low-carbon urban land use efficiency using a non-radial directional distance function and analyses its spatial and temporal evolution and its influencing factors using a combination of a kernel density estimation method and a Tobit model. The study found that: (1) China’s low-carbon urban land use efficiency shows a fluctuating development and tends to converge; (2) there is much room for reducing land input and carbon emissions in China, and in 2016 alone, land input and carbon emissions in the sample could be reduced by 10.38% and 5.31%, respectively; (3) at the national level, land finance, economic level and population density have a positive impact on low-carbon urban land use efficiency, while the traffic level has negative effects, and these effects show regional heterogeneity. Accordingly, the paper proposes corresponding policy recommendations. Full article

(This article belongs to the Special Issue The Impact of Land Use on Atmospheric Environment)

► Show Figures

Figure 1

24 pages, 6483 KiB

Open AccessArticle

Coupling Coordination Development of New-Type Urbanization and Cultivated Land Low-Carbon Utilization in the Yangtze River Delta, China

by Yue Zhang, Yaqiang Dai, Yuanyuan Chen and Xinli Ke

Land 2022, 11(6), 919; https://doi.org/10.3390/land11060919 - 15 Jun 2022

Cited by 11 | Viewed by 1970

Abstract

Although urbanization greatly benefits economy-society development in China, it poses enormous challenges to cultivated land utilization. In the context of urbanization acceleration and carbon neutrality, it’s of significance to achieve high-quality economy-society development and sustainable agricultural development. Thus, the coupling coordination relationship between [...] Read more.

Although urbanization greatly benefits economy-society development in China, it poses enormous challenges to cultivated land utilization. In the context of urbanization acceleration and carbon neutrality, it’s of significance to achieve high-quality economy-society development and sustainable agricultural development. Thus, the coupling coordination relationship between new-type urbanization and cultivated land low-carbon utilization (CLLCU) needs to be examined. However, this topic has not been adequately addressed in previous studies. To fill the gap, this paper adopted a comprehensive evaluation model and a super-efficiency SBM (Slacked Based Measure) model to evaluate the level of new-type urbanization and the cultivated land low-carbon utilization efficiency (CLLCUE) of cities in the Yangtze River Delta in China from 2000 to 2018. Furthermore, the coupling coordination degree model (CCDM) and the relative development degree model (RDDM) were employed to measure the coupling coordination degree and the relative state of the new-type urbanization and CLLCU The results show that the coupling coordination degree between the new-type urbanization level and CLLCUE experienced a process of “rapid increase-steady develop” and presented a spatial pattern of “polarization-regional equilibrium”. In addition, the relative state of the new-type urbanization and CLLCU presented the “reversal” phenomenon. In other words, the relative state changed from the new-type urbanization lagging behind CLLCU to the new-type urbanization ahead of CLLCU. None of the cities were in the state of simultaneous development. Finally, this paper puts forward policy recommendations to explore differentiated CLLCU modes and improve the quality and efficiency of new-type urbanization. Full article

(This article belongs to the Special Issue The Impact of Land Use on Atmospheric Environment)

► Show Figures

Figure 1

15 pages, 1072 KiB

Open AccessArticle

Impact of Land Management Scale on the Carbon Emissions of the Planting Industry in China

by Jiake Li, Wei Wang, Meng Li, Qiao Li, Zeming Liu, Wei Chen and Yanan Wang

Land 2022, 11(6), 816; https://doi.org/10.3390/land11060816 - 31 May 2022

Cited by 9 | Viewed by 2067

Abstract

A change in agricultural land management scale leads to the recombination and adjustment of production factors, which have an important impact on agricultural carbon emissions. There are few studies on the connection between the scale of land management and agricultural carbon emissions. In [...] Read more.

A change in agricultural land management scale leads to the recombination and adjustment of production factors, which have an important impact on agricultural carbon emissions. There are few studies on the connection between the scale of land management and agricultural carbon emissions. In this study, we empirically examined the relationship between planting scale and agricultural carbon emissions using the threshold model, which allows the data to endogenously generate several regimes identified by the thresholds. The results showed that from 2003 to 2018, carbon emissions from planting first increased and then decreased, reaching their highest in 2015. Across the whole country in the main rice- and wheat-producing regions, the scale of planting land has a threshold effect on agricultural carbon emissions, showing an inverted “U” shape. Carbon sinks and natural disasters significantly affected planting carbon emissions in the above three regions. The amount of fiscal support for agriculture significantly affects planting carbon emissions in the national and main wheat-producing regions, while peasants’ per capita income significantly affects planting carbon emissions in the main rice- and wheat-producing regions. This study provides policy makers with new ideas, in that continuously expanding the scale of agricultural land management is conducive to reducing agricultural carbon emissions. Full article

(This article belongs to the Special Issue The Impact of Land Use on Atmospheric Environment)

► Show Figures

Figure 1

16 pages, 2408 KiB

Open AccessArticle

Do We Need More Urban Green Space to Alleviate PM_2.5 Pollution? A Case Study in Wuhan, China

by Yuanyuan Chen, Xinli Ke, Min Min, Yue Zhang, Yaqiang Dai and Lanping Tang

Land 2022, 11(6), 776; https://doi.org/10.3390/land11060776 - 25 May 2022

Cited by 9 | Viewed by 2901

Abstract

Urban green space can help to reduce PM_2.5 concentration by absorption and deposition processes. However, few studies have focused on the historical influence of green space on PM_2.5 at a fine grid scale. Taking the central city of Wuhan as an [...] Read more.

Urban green space can help to reduce PM_2.5 concentration by absorption and deposition processes. However, few studies have focused on the historical influence of green space on PM_2.5 at a fine grid scale. Taking the central city of Wuhan as an example, this study has analyzed the spatiotemporal trend and the relationship between green space and PM_2.5 in the last two decades. The results have shown that: (1) PM_2.5 concentration reached a maximum value (139 μg/m³) in 2010 and decreased thereafter. Moran’s I index values of PM_2.5 were in a downward trend, which indicates a sparser distribution; (2) from 2000 to 2019, the total area of green space decreased by 25.83%. The reduction in larger patches, increment in land cover diversity, and less connectivity led to fragmented spatial patterns of green space; and (3) the regression results showed that large patches of green space significantly correlated with PM_2.5 concentration. The land use/cover diversity negatively correlated with the PM_2.5 concentration in the ordinary linear regression. In conclusion, preserving large native natural habitats can be a supplemental measure to enlarge the air purification function of the green space. For cities in the process of PM_2.5 reduction, enhancing the landscape patterns of green space provides a win-win solution to handle air pollution and raise human well-being. Full article

(This article belongs to the Special Issue The Impact of Land Use on Atmospheric Environment)

► Show Figures

Figure 1

17 pages, 10894 KiB

Open AccessArticle

Evaluation and Improvement of Cultivated Land Leisure Service Function Based on Multisource Spatial Data

by Yiming Yang, Xiuli Wang, Jian Wang, Yiwei Geng, Weiqiang Chen, Qun Wu and Xiaoke Guan

Land 2022, 11(2), 303; https://doi.org/10.3390/land11020303 - 16 Feb 2022

Cited by 3 | Viewed by 1838

Abstract

The leisure service function is an important component of the derivative function and non-market function of cultivated land. Therefore, exploring the strength of the cultivated land leisure service function with the help of spatial information technology is significant in guiding the proper utilization [...] Read more.

The leisure service function is an important component of the derivative function and non-market function of cultivated land. Therefore, exploring the strength of the cultivated land leisure service function with the help of spatial information technology is significant in guiding the proper utilization and protection of cultivated land resources. This paper constructed an evaluation system based on the three dimensions of ecological landscape, social activities, and economic performance, explored the spatial difference of the cultivated land leisure service function in Yuanyang County, the major grain-producing area along the Yellow River through spatial weighted overlay, classified the hot spots of leisure services and presented suggestions for improvement. Results show the following: (1) the landscape resources in the northern part are relatively monotonous, while those in the southern part are rich and evenly distributed. Spatial accessibility presents a distribution of “one core with multiple subcores”. The distribution of leisure service supply capacity is characterized by “multiple cores and multiple circles.” (2) The hot spots of the cultivated land leisure service function are the Urban Agricultural Central Area and the Ecological Agriculture Core Area in the middle of the county, and the Suburban Agritourism Development Area, the Yellow River Agritourism Transitional Area, and the Leisure Agriculture Connection Area on the periphery of the county. (3) The agricultural landscape should be fully protected and utilized in the Urban Agricultural Central Area. The spatial accessibility and regional reputation of the Ecological Agriculture Core Area need to be improved. The landscape diversity and landscape quality should be improved in the Suburban Agritourism Development Area. The Yellow River Agritourism Transitional Area needs to overcome the loss of tourists. The Leisure Agriculture Connection Area should increase the number of leisure and tourism facilities. Full article

(This article belongs to the Special Issue The Impact of Land Use on Atmospheric Environment)

► Show Figures

Figure 1

Journal Menu

Journal Browser

The Impact of Land Use on Atmospheric Environment

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Published Papers (8 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI