Assessing the Impact of Land-Use Planning on the Atmospheric Environment through Predicting the Spatial Variability of Airborne Pollutants

Chen, Longgao; Li, Long; Yang, Xiangdong; Chen, Longqian; Ma, Xinping

doi:10.3390/ijerph16020172

Cited by 9 publications

(8 citation statements)

References 52 publications

(57 reference statements)

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“…The articles included were published between the years 1993 [24] and 2023 [54][55][56]. Studies were conducted in Canada [24,35], the USA [25,27,33,40], the UK [26,46], Denmark [28], Germany [29,43], Iran [30,31,42,49,50,54], Italy [32,36], China [34,37,45,47,56], Australia [38,48], Republic of Korea [39,52], Ghana [41], Spain [44], Greece [51], Thailand [53], and Egypt [55].…”

Section: Goodmentioning

confidence: 99%

Evaluating the Environmental Impact of Anthropogenic Activities on Human Health: A Systematic Review

Cofone,

Sabato,

Di Rosa

et al. 2024

Urban Science

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Due to major global urbanisation, a careful evaluation of plans (town planning and mobility) and projects (industrial and development) is required in order to measure their impact on health and environmental matrices. In Italy, Legislative Decree No 152/06 introduced two procedures: the EIA (Environmental Impact Assessment) and SIA (Strategic Impact Assessment). Their focus, however, does not consider human health. Recently, the Integrated Environmental and Health Impact Assessment (IEHIA) was introduced; this defines the parameters necessary to provide an EIA that includes human health as a factor. This systematic review was conducted, including both the population impacted by new facilities and the method used to define their impact. Our database search produced 724 articles, of which 33 were eligible. Studies included landfill plans, manufacturing industries, mobility policies, energy production, and the environmental health of an area. All studies show how an approach encompassing multiple parameters can analyse the impact of a new facility in a comprehensive manner. This review shows that the use of health-related environmental impact parameters is essential for the integration of a project into a community, and can allow a wider understanding of the possible impacts on human health, both direct and indirect.

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Section: Goodmentioning

confidence: 99%

Evaluating the Environmental Impact of Anthropogenic Activities on Human Health: A Systematic Review

Cofone,

Sabato,

Di Rosa

et al. 2024

Urban Science

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“…Its PM 2.5 concentration increases from east to west, and the western part of Shandong is heavily polluted [84], including the four Shandong cities of the Zone. Secondly, the northeastern part of the Zone is in the Yimeng Mountain area (the high-elevation areas in Figure 1b), which is not conducive to the diffusion of pollutants and therefore results in serious local air pollution [85]. Lastly, air pollution from polluted neighboring regions, such as the Beijing-Tianjin-Hebei region and the Yangtze River Delta region should be not ignored.…”

Section: Trend Analysismentioning

confidence: 99%

Random Forest Estimation and Trend Analysis of PM2.5 Concentration over the Huaihai Economic Zone, China (2000–2020)

Chen

et al. 2022

Sustainability

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Consisting of ten cities in four Chinese provinces, the Huaihai Economic Zone has suffered serious air pollution over the last two decades, particularly of fine particulate matter (PM2.5). In this study, we used multi-source data, namely MAIAC AOD (at a 1 km spatial resolution), meteorological, topographic, date, and location (latitude and longitude) data, to construct a regression model using random forest to estimate the daily PM2.5 concentration over the Huaihai Economic Zone from 2000 to 2020. It was found that the variable expressing time (date) had the greatest characteristic importance when estimating PM2.5. By averaging the modeled daily PM2.5 concentration, we produced a yearly PM2.5 concentration dataset, at a 1 km resolution, for the study area from 2000 to 2020. On comparing modeled daily PM2.5 with observational data, the coefficient of determination (R2) of the modeling was 0.85, the root means square error (RMSE) was 14.63 μg/m3, and the mean absolute error (MAE) was 10.03 μg/m3. The quality assessment of the synthesized yearly PM2.5 concentration dataset shows that R2 = 0.77, RMSE = 6.92 μg/m3, and MAE = 5.42 μg/m3. Despite different trends from 2000–2010 and from 2010–2020, the trend of PM2.5 concentration over the Huaihai Economic Zone during the 21 years was, overall, decreasing. The area of the significantly decreasing trend was small and mainly concentrated in the lake areas of the Zone. It is concluded that PM2.5 can be well-estimated from the MAIAC AOD dataset, when incorporating spatiotemporal variability using random forest, and that the resultant PM2.5 concentration data provide a basis for environmental monitoring over large geographic areas.

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“…As the largest developing country with about 20% of the global population [29], China has limited natural resources per capita, particularly arable and built-up land, thus increasing socioeconomic pressure on the eco-environmental system [30]. Efficient land use seems to be the most feasible solution to the challenge [31,32]. Located in the east of Asia (73 • 3 -135 • 3 E, 3 • 31 -53 • 33 N), China has a varied climate-from tropic in the south to subfrigid in the north-and terrain, mostly mountains, high plateaus, and deserts in the west and plains, deltas, and hills in the east (https://www.indexmundi.com/china/terrain.…”

Section: Introductionmentioning

confidence: 99%

The Natural and Socioeconomic Influences on Land-Use Intensity: Evidence from China

Chen

Yang

et al. 2021

Land

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Intensive land use can support sustainable socioeconomic development, especially in the context of limited land resources and high population. It is measured by land-use intensity that reflects the degree of land-use efficiency. In order to support decision-making for efficient land use, we investigated the mechanism whereby natural and socioeconomic factors influence land-use intensity from the perspectives of overall, region-, and city-based analysis, respectively. This investigation was conducted in Chinese cities using the multiple linear stepwise regression method and geographic information system techniques. The results indicate that: (1) socioeconomic factors have more positive impact on land-use intensity than natural factors as nine of the top 10 indicators with the highest SRC values are in the socioeconomic category according to the overall assessment; (2) education input variously contributes to land-use intensity because of the mobility of a well-educated workforce between different cities; (3) the increase in transportation land may not promote intensive land use in remarkably expanding cities due to the defective appraisal system for governmental achievements; and that (4) in developed cities, economic structure contributes more to land-use intensity than the total economic volume, whereas the opposite is the case in less-developed cities. This study can serve as a guide for the government to prepare strategies for efficient land use, hence promoting sustainable socioeconomic development.

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Assessing the Impact of Land-Use Planning on the Atmospheric Environment through Predicting the Spatial Variability of Airborne Pollutants

Cited by 9 publications

References 52 publications

Evaluating the Environmental Impact of Anthropogenic Activities on Human Health: A Systematic Review

Evaluating the Environmental Impact of Anthropogenic Activities on Human Health: A Systematic Review

Random Forest Estimation and Trend Analysis of PM2.5 Concentration over the Huaihai Economic Zone, China (2000–2020)

The Natural and Socioeconomic Influences on Land-Use Intensity: Evidence from China

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