Exploring the Spatial and Temporal Relationship between Air Quality and Urban Land-Use Patterns Based on an Integrated Method

Assessment of vegetation change using NDVI, LST, and carbon analyses in Çankırı Karatekin University, Turkey

Due to a rising population and urbanization, the green areas have been decreasing in cities, with a negative impact on air pollution, human health, and ecosystem. As part of the urban environment, university campuses contribute to urban ecosystem with their vegetation. This study aims to (1) assess the change of vegetative land cover of the Çankırı Karatekin University in Turkey and (2) evaluate its benefits to the ecosystem in terms of carbon sequestration, storage, and improvement of air quality by means of a simulation. In the study, the density and vegetation change were assessed with NDVI and LST analyses in ArcGIS; carbon emissions and air pollution benefits were estimated in i-Tree Canopy tool. The study showed that the healthy vegetation consisting of trees/shrubs and grass/herbaceous, which was 32.2% (28 ha) in 2000, increased to 85% (74 ha) in 2020 NDVI maps, and the surface temperature also increased between 2000 and 2020 in LST maps.The rise in vegetation as grass/herbaceous areas instead of trees/shrubs and the use of impervious buildings/roads on the land surface increased the land surface temperature. As a result of the analyses in the i-Tree-Canopy tool, it was estimated that the trees/shrubs and grass/herbaceous vegetation canopy covering 31.42% of the study area removed a total of 512,845.65 g of pollutant gas and particles from the air, 20.79 tonnes of carbon sequestered annually, and 522.01 tonnes of carbon stored by vegetative land cover. In the simulation, where 32.62% soil/bare ground areas were converted to trees/shrubs in order to improve vegetation cover in the area, it was determined that it contributed 5 times more to the ecosystem service value for removing pollutants from the air, carbon storage, and improving the ecosystem. It was revealed that the vegetative land cover formed by tree/shrub species should be increased in the campus in the future. The study method model serves as a tool for planning and designing eco-friendly urban environment.

Greenspace pattern, meteorology and air pollutant in Taiwan: A multifaceted connection

Air pollution is a global environmental concern that poses a significant threat to human health. Given the impact of urbanization and climate change, green planning is being encouraged to improve air quality. The study aims to examine the intricate relationships between greenspace pattern and outdoor air around 73 in-situ stations over Taiwan during the dry (November to April) and wet (May to December) seasons from 2015 to 2020. To achieve this, Partial Least Squares - Structural Equation Modeling was utilized to analyze the interactions among seven dimensions: greenspace - GS, gaseous pollutant - GP, particle pollutant - PP, O3 - OZONE, air temperature - TEMP, relative humidity - RH, and wind speed - WS. The GS involves seven landscape metrics: edge density, total edge, effective mesh size, largest patch area, percentage of landscape, total core area, and patch cohesion index. The results indicate that the GS has a stronger effect on the GP, whereas its effect on the PP is weaker during the dry season compared to the wet season. While its effect on the TEMP is weaker, it shows a slightly stronger effect on the RH during the dry season. Moreover, the GS mediates the air pollutant dimensions during the two seasons, with the RH acting as a primary mediator. The meteorological dimensions primarily have a greater influence on the air pollutant dimensions during the dry season than the wet season. Consequently, the GS explains 11.3 % more and 18.4 % less of the variances in the RH and TEMP during the dry season, respectively. Moreover, the GS and meteorological dimensions yield a seasonal difference in explained variance, with the highest value observed for the OZONE (R2 = 24.2 %), followed by the PP (R2 = 9.7 %) and GP (R2 = 7.7 %). Notably, seven landscape metrics serve as potential indicators for green strategies in urban planning to enhance outdoor air quality.

A novel Energy Resources Allocation Management model for air pollution reduction

Although air pollution has been reduced in various industrial and crowded cities during the COVID-19 pandemic, curbing the high concentration of the crisis of air pollution in the megacity of Tehran is still a challenging issue. Thus, identifying the major factors that play significant roles in increasing contaminant concentration is vital. This study aimed to propose a mathematical model to reduce air pollution in a way that does not require citizen participation, limitation on energy usage, alternative energies, any policies on fuel-burn style, extra cost, or time to ensure that consumers have access to energy adequately. In this study, we proposed a novel framework, denoted as the Energy Resources Allocation Management (ERAM) model, to reduce air pollution. The ERAM is designed to optimize the allocation of various energies to the recipients. To do so, the ERAM model is simulated based on the magnitude of fuel demand consumption, the rate of air pollution emission generated by each energy per unit per consumer, and the air pollution contribution produced by each user. To evaluate the reflectiveness and illustrate the feasibility of the model, a real-world case study, i.e., Tehran, was employed. The air pollution emission factors in Tehran territory were identified by considering both mobile sources, e.g., motorcycles, cars, and heavy-duty vehicles, and stationary sources, e.g., energy conversion stations, industries, and household and commercial sectors, which are the main contributors to particulate matter and nitrogen dioxide. An elaborate view of the results indicates that the ERAM model on fuel distribution could remarkably reduce Tehran's air pollution concentration by up to 14%.

Exploring the Effects of Industrial Land Transfer on Urban Air Quality Using a Geographically and Temporally Weighted Regression Model

This paper explores the spatial-temporal heterogeneity of the impact of industrial land transfer on urban air quality using the air quality index (AQI) and primary land market transaction data of 284 cities from 2015 to 2019 in China. Based on a three-dimensional conceptual framework including scale, price and style effect of industrial land transfer, we find that: (1) The scale effect shows an obvious characteristic of spatial agglomeration, and the agglomerations transfer from central and northern China to the western and southeast coastal regions. (2) Industrial land transfer price has a greater impact on air quality than transfer scale no matter whether the effect is positive or negative, which may be because the expansion scale of construction land is restricted strictly by indicators. (3) The scale of industrial land transferred by agreement in the west and northeast will reduce the air quality. (4) The impact of industrial land price transferred by bidding, auction and listing on AQI is gradually decreasing, but that of land transferred by agreement is still high in the northwest and northeast regions. Finally, we put forward policy recommendations based on the spatial and temporal heterogeneity of these effects, which will help alleviate or avoid environmental problems caused by land resources mismatch and industrial development.

Modeling the impacts of land use/land cover change on meteorology and air quality during 2000-2018 in the Yangtze River Delta region, China

The land use/land cover (LULC) change in the fast-developing city clusters of China exhibits impacts on both the meteorology and air quality. However, this effect, especially in the Yangtze River Delta (YRD), has not been well quantified. In this study, the LULC data are extracted from Landsat satellite imageries for year 2000 and 2018 for the YRD region. The Weather Research and Forecasting with Chemistry (WRF/Chem) model is applied to investigate the impact of historical LULC change on regional meteorology and air pollution over the YRD region during the past two decades. Two simulation scenarios are performed with two sets of LULC data to represent the pre-urbanization (LULC of year 2000) and the most recent urban pattern (LULC of year 2018). Results indicate that rapid urbanization leads to an increase of monthly mean 2-m temperature by 0.4-2.1 °C but decrease of the 10-m wind speed by 0.5-1.3 m/s in urban areas; the maximum increase of daytime planetary boundary layer height (PBLH) in July and November is 289 and 132 m, respectively. Affected by favorable changes in the meteorological conditions due to LULC change, the PM_2.5 concentrations in most urban areas show a decreasing trend, especially during the nighttime in summer. On the contrary, surface ozone (O₃) concentration in urban areas has increased by 7.2-9.8 ppb in summer and 1.9-2.1 ppb in winter. Changes in O₃ concentration are inversely proportional to changes in NO_x and the spatial distribution of PM_2.5. Areas with higher O₃ concentration are consistent with areas of higher temperature and lower wind speed. Our findings reveal that LULC changes during the past years bring observable changes in air pollutant concentrations, which should not be neglected in the YRD region regarding air quality trends as well as policy evaluations under the warming threat.

Relationships between urban form and air quality: A reconsideration based on evidence from China's five urban agglomerations during the COVID-19 pandemic

The outbreak of Coronavirus disease 2019 (COVID-19) led to the widespread stagnation of urban activities, resulting in a significant reduction in industrial pollution and traffic pollution. This affected how urban form influences air quality. This study reconsiders the influence of urban form on air quality in five urban agglomerations in China during the pandemic period. The random forest algorithm was used to quantitate the urban form-air quality relationship. The urban form was described by urban size, shape, fragmentation, compactness, and sprawl. Air quality was evaluated by the Air Quality Index (AQI) and the concentration of six pollutants (CO, O3, NO2, PM2.5, PM10, SO2). The results showed that urban fragmentation is the most important factor affecting air quality and the concentration of the six pollutants. Additionally, the relationship between urban form and air quality varies in different urban agglomerations. By analyzing the extremely important indicators affecting air pollution, the urban form-air quality relationship in Beijing-Tianjin-Hebei is rather complex. In the Chengdu-Chongqing and the Pearl River Delta, urban sprawl and urban compactness are extremely important indicators for some air pollutants, respectively. Furthermore, urban shape ranks first for some air pollutants both in the Triangle of Central China and the Yangtze River Delta. Based on the robustness test, the performance of the random forest model is better than that of the multiple linear regression (MLR) model and the extreme gradient boosting (XGBoost) model.

Association between Land Use Mix and Respiratory Symptoms and Asthma in Children from the Generation XXI Birth Cohort

Land use mix (LUM) in the neighbourhoods has been associated with healthier lifestyles. However, less is known about the association between LUM and health outcomes, namely during childhood. The objective of this study was to evaluate the association between different LUM indexes for Porto Metropolitan Area and asthma and respiratory symptoms in children. A cross-sectional analysis was performed involving 6260 children enrolled in Generation XXI. Land use around the child's residence was assessed with the Portuguese official map of land cover using a GIS. Generalized linear mixed-effects models were fitted to estimate the association between LUM and respiratory symptoms and asthma at 7 years of age. Adjusted associations were quantified using odds ratio (OR) and 95% confidence interval (95% CI). After adjustment, LUM was associated with a lower odds of wheezing in the last 12 months [OR (95% CI) = 0.37 (0.15; 0.93) using Shannon's Evenness Index within 500 m; and OR = 0.93 (0.89; 0.98) using the number of different land use types within 250 m]. Living in neighbourhoods with high LUM has a protective effect on current wheezing symptoms. Our results highlight the association between LUM and respiratory symptoms among children, suggesting that public health considerations should be incorporated in land use decision-making.

Study on Coupled Relationship between Urban Air Quality and Land Use in Lanzhou, China

The intensification of global urbanization has exacerbated the negative impact of atmospheric environmental factors in urban areas, thus threatening the sustainability of future urban development. In order to ensure the sustainability of urban atmospheric environments, exploring the changing laws of urban air quality, identifying highly polluted areas in cities, and studying the relationship between air quality and land use have become issues of great concern. Based on AQI data from 340 air quality monitoring stations and urban land use data, this paper uses inverse distance weight (IDW), Getis-Ord Gi*, and a negative binomial regression model to discuss the spatiotemporal variation of air quality in the main urban area of Lanzhou and its relationship with urban land use. The results show that urban air quality has characteristics of temporal and spatial differentiation and spatially has characteristics of agglomeration of cold and hot spots. There is a close relationship between urban land use and air quality. Industrial activities, traffic pollution, and urban construction activities are the most important factors affecting urban air quality. Green spaces can reduce urban pollution. The impact of land use on air quality has a seasonal effect.

Multi-Temporal Arable Land Monitoring in Arid Region of Northwest China Using a New Extraction Index

Development of a high-accuracy method to extract arable land using effective data sources is crucial to detect and monitor arable land dynamics, servicing land protection and sustainable development. In this study, a new arable land extraction index (ALEI) based on spectral analysis was proposed, examined by ground truth data, and then applied to the Hexi Corridor in northwest China. The arable land and its change patterns during 1990–2020 were extracted and identified using 40 Landsat TM/OLI images acquired in 1990, 2000, 2010, and 2020. The results demonstrated that the proposed method can distinguish arable land areas accurately, with the User’s (Producer’s) accuracy and overall accuracy (kappa coefficient) exceeding 0.90 (0.88) and 0.89 (0.87), respectively. The mean relative error calculated using field survey data obtained in 2012 and 2020 was 0.169 and 0.191, respectively, indicating the feasibility of the ALEI method in arable land extracting. The study found that arable land area in the Hexi Corridor was 13217.58 km2 in 2020, significantly increased by 25.33% compared to that in 1990. At 10-year intervals, the arable land experienced different change patterns. The study results indicate that ALEI index is a promising tool used to effectively extract arable land in the arid area.

The Complexity of Space Utilization and Environmental Pollution Control in the Main Corridor of Makassar City, South Sulawesi, Indonesia

Population mobility, increasing demand for transportation, and the complexity of land use have an impact on environmental quality degradation and air quality pollution. This study aims to analyze (1) the effect of population mobility, increased traffic volume, and land use change on air quality pollution, (2) direct and indirect effects of urban activities, transportation systems, and movement patterns on environmental quality degradation and air pollution index, and (3) air pollution strategy and sustainable urban environmental management. The research method used is a sequential explanation design. Data were obtained through observation, surveys, in-depth interviews, and documentation. The results of the study illustrate that the business center and Daya terminal with a value of 0.18 µgram/m3 is polluted, the power plant and Sermani industrial area with a value of 0.16 µgram/m3 is polluted, the Makassar industrial area with a value of 0.23 is heavily polluted, and the Hasanuddin International Airport area with a value of 0.04 µgram/m3 is not polluted. Population mobility, traffic volume, and land use changes have a significant effect on environmental quality degradation, with a determination coefficient of 94.1%. The direct effect of decreasing environmental quality on the air pollution index is 66.09%. This study recommends transportation management on the main road corridor of Makassar City, which is environmentally friendly with regard to sustainable environmental management.