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Towards the Sustainable Development Goals: Monitoring, Assessment and Management of Eco-Environmental Space

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Environmental Sustainability and Applications".

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 20155

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Special Issue Editors

Dr. Chunyan Lu

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Guest Editor

College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Interests: remote sensing of environment and resources; eco-environment management; land cover change monitoring; landscape ecology
Special Issues, Collections and Topics in MDPI journals

Dr. Weidong Man

E-Mail Website
Guest Editor

College of Mining Engineering, North China University of Science and Technology, Tangshan 063210, China
Interests: digital soil mapping; terrestrial carbon cycle; exotic plant invasions; vegetation parameter retrieval; eco-environmental restoration; eco-environmental remote sensing

Prof. Dr. Tiantian Shao

E-Mail Website
Guest Editor

Key Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization, Henan University, Kaifeng 475001, China
Interests: environmental remote sensing; ecological assessment; geographical process

Special Issue Information

Dear Colleagues,

In the past century, the global eco-environment has witnessed unprecedented changes caused by both anthropogenic and natural disturbances. A wide range of threats have become serious challenges to the achievement of sustainable development, including global warming, land degradation, biodiversity destruction, environment pollution, resource depletion, and so on. The Sustainable Development Goals (SDGs), as outlined in the 2030 Agenda for Sustainable Development, provide a shared blueprint for sustainable development for humans and the eco-environment, for both the present day and the future. Currently, increasing degradation compounded by various destructive activities have led to an urgent demand for the maintenance of the eco-environment sustainability. The monitoring, assessment and management of eco-environmental space towards the SDGs is the prerequisite for and foundation of achieving the SDGs.

Eco-environmental sustainability development is the foundation of sustainable development. In recent years, the rapid development of theory and technology in quantitative, spatio-temporal and multi-dimensional aspects, as well as other aspects, has made it possible to attempt rapid dynamic monitoring and systematic assessment and provide management decision support for eco-environmental space. Although a few attempts have been reported, effective and systematic research into all kinds of ecosystems towards SDGs remains scarce.

Therefore, the aim of this Special Issue is to collect articles (original research papers, review articles and case studies) that will provide insight, theory, and technology regarding the monitoring, assessment and management of eco-environment space towards the SDGs, which involves innovative research, modeling, decision making, empirical studies and case studies in this research area.

Relevant topics include but are not limited to the following areas:

Eco-environment restoration and conservation;
The monitoring and assessment of eco-environments;
Emerging technologies for SDG analysis;
Carbon storage estimation of soil or vegetation;
Effects of exotic plant invasions on eco-environment;
The valuation of ecosystem services;
Carbon emissions and carbon exchange markets;
Abandoned mine land restoration and reconstruction;
Biodiversity monitoring and evaluation;
Decision making in sustainable urban development.

Dr. Chunyan Lu
Dr. Weidong Man
Prof. Dr. Tiantian Shao
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

eco-environment monitoring
sustainable management
environmental transition
comprehensive assessment
decision support

Published Papers (12 papers)

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Research

18 pages, 5310 KiB

Open AccessArticle

Spatio-Temporal Evolution of Ecological Sensitivity in the Desert of China from 1981 to 2022

by Chunwei Song, Geer Teni and Huishi Du

Sustainability 2023, 15(16), 12102; https://0-doi-org.brum.beds.ac.uk/10.3390/su151612102 - 8 Aug 2023

Cited by 3 | Viewed by 1033

Abstract

The northern desert of China plays an important strategic role in land resource security and national economic development. Research on the spatio-temporal changes of ecological sensitivity can provide a scientific reference for desert management and ecological restoration in arid and semi-arid areas in northern China. This paper takes the northern desert of China as the research area, uses the spatial distance model to build a comprehensive ecological sensitivity evaluation index system, and discusses the spatio-temporal evolution characteristics of ecological sensitivity in the area from 1981 to 2022. The results show the following: (1) The land use types in the northern desert of China are mainly sandy land, grassland and other lands. The changing areas of grassland and other lands are 74,353.14 km² and 50,807.97 km², which is an important factor affecting the ecological sensitivity in the northern desert of China. (2) Five aspects, including terrain, climate, hydrology, soil and vegetation, influence and restrict each other, and jointly create the background conditions for the distribution and change of ecological sensitivity in the northern desert of China. Climate and terrain are the most important influencing factors affecting the ecological sensitivity of northern desert of China. Vegetation is the most active and basic factor affecting the ecological sensitivity of northern desert of China. Hydrology and soil have a certain limiting effect on the ecological sensitivity of northern desert of China. (3) The spatial heterogeneity of ecological sensitivity in the northern desert of China is significant, showing the characteristics of high volatility in the west, low volatility in the central region and low volatility in the east. (4) For nearly 42 years, ecological sensitivity of the northern desert of China shows first increasing and then decreasing characteristics. The area of the fluctuation reduction zone accounts for 26.34% of the total research area, of which the area of extreme sensitivity and mild sensitivity varies by 11.84% and 65.28%, respectively. (5) The spatial aggregation characteristics of ecological sensitivity have changed significantly, and the area of high–high and low–low agglomeration areas has also been decreasing, indicating that the environment is obviously improving. In the future, we should pay attention to the efficient use of natural resources in the northern desert of China and strengthen the protection of all kinds of land to achieve the sustainable development of the regional environment. Full article

(This article belongs to the Special Issue Towards the Sustainable Development Goals: Monitoring, Assessment and Management of Eco-Environmental Space)

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14 pages, 5450 KiB

Open AccessArticle

Evaluation and Analysis of the Gross Ecosystem Product towards the Sustainable Development Goals: A Case Study of Fujian Province, China

by Qingping Hu, Chunyan Lu, Tingting Chen, Wanting Chen, Huimei Yuan, Mengxing Zhou, Zijing Qiu and Lingxin Bao

Sustainability 2023, 15(5), 3925; https://0-doi-org.brum.beds.ac.uk/10.3390/su15053925 - 21 Feb 2023

Cited by 3 | Viewed by 1786

Abstract

Achieving sustainable development is an issue of global concern. Accounting for the gross ecosystem product (GEP) value can specifically quantify the value of ecosystems for people, which is conducive to the formulation of sustainable eco-management decisions. Multi-source data, including remote sensing images, geospatial data, and statistical bulletin information, were used to quantify the GEP value of material products, regulating services, and cultural services for Fujian Province, China, during 2000–2020. On this basis, the spatio-temporal characteristics of GEP and the coupling relationship between GEP and GDP were analyzed. The results showed that: (1) the value of GEP in Fujian Province increased by 27.9% from CNY 3589.04 billion in 2000 to CNY 4590.25 billion in 2020. Among the service values, the contribution rate of regulating services to GEP was always the highest during the study period. (2) The spatial distribution pattern of GEP in Fujian Province was higher in the west and lower in the east. Comparing prefecture-level cities, Nanping maintained its GEP at the maximum value level over the past 21 years, while Xiamen and Putian maintained their GEP at the minimum value level. (3) GDP grew faster relative to GEP over the past 21 years, and the difference between GEP and GDP decreased. GEP had a long-term positive effect on GDP, while GDP had a smaller effect on GEP in the short term. The research was not only enriched in relation to GEP accounting, but also the policy recommendations for improving the mechanisms related to the optimization of sustainable development goals have some practical significance. Full article

(This article belongs to the Special Issue Towards the Sustainable Development Goals: Monitoring, Assessment and Management of Eco-Environmental Space)

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21 pages, 4043 KiB

Open AccessArticle

Ecological Environmental Quality in China: Spatial and Temporal Characteristics, Regional Differences, and Internal Transmission Mechanisms

by Jiehua Lv and Wen Zhou

Sustainability 2023, 15(4), 3716; https://0-doi-org.brum.beds.ac.uk/10.3390/su15043716 - 17 Feb 2023

Cited by 2 | Viewed by 2025

Abstract

In recent years, ecological environmental problems such as the greenhouse effect, soil erosion, climate change, and biodiversity reduction have become more and more salient, and ecological environmental quality has gradually become a research hotspot. This paper constructs an index system for evaluating ecological environment quality based on the pressure–state–response (PSR) model, which contains three elemental layers, natural resources, ecological environment, and government inputs, measures the ecological environment quality index by using the “vertical and horizontal layer by layer” scatter degree method, and discusses the spatial and temporal evolution trends of ecological environment quality in each province and six regions in China during 2005–2020. This paper further measures the regional ecological environment quality differences by using the Thiel index and analyzes the transmission mechanism within the pressure–state–response model by using the mediation models. The results show that the ecological environment quality of all Chinese provinces and six regions has improved significantly during the period under study, the response system and state system scores have improved significantly, the unbalanced development of ecological environment quality within north China has improved the most, and there are significant direct and mediation effects among the subsystems within the ecological environment quality with high system transmission efficiency. Therefore, the government should improve the quality of the ecological environment by seeking cross-provincial linkage development, improving the level of pollution control, and formulating relevant standards and laws and regulations. Full article

(This article belongs to the Special Issue Towards the Sustainable Development Goals: Monitoring, Assessment and Management of Eco-Environmental Space)

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24 pages, 5313 KiB

Open AccessArticle

Influence of Landscape Pattern Evolution on Soil Conservation in a Red Soil Hilly Watershed of Southern China

by Xiangqun Xie, Xinke Wang, Zhenfeng Wang, Hong Lin, Huili Xie, Zhiyong Shi, Xiaoting Hu and Xingzhao Liu

Sustainability 2023, 15(2), 1612; https://0-doi-org.brum.beds.ac.uk/10.3390/su15021612 - 13 Jan 2023

Cited by 5 | Viewed by 1744

Abstract

The Tingjiang Watershed is a typical mountainous area with red soil in the south of China. Due to the high rainfall intensity, significant cultivated land expansion, and accelerated urbanization, ecological problems such as soil erosion are prominent in the study area. Based on the land use, precipitation, digital elevation model (DEM), normalized difference vegetation Index (NDVI), and soil types in 2000, 2010, and 2020, the landscape pattern and soil conservation in the Tingjiang Watershed were assessed at the sub-watershed scale. The spatial correlation between soil conservation and landscape pattern was analyzed using GeoDA software. The results show the following: (1) From 2000 to 2020, the total amount of soil conservation decreased by 4.15 × 10⁸ t. In terms of spatial analysis, the amount of soil conservation in the Tingjiang Watershed showed an upward and then downward trend in the north and a downward trend in the south, with the most obvious downward trend in the southeast and the northeast. (2) Fragmentation of the overall landscape pattern in the Tingjiang Watershed has increased. The discrete degree and homogeneity of patches decreased in Changting County, while landscape heterogeneity and homogeneity increased in Shanghang, Liancheng, and Yongding Counties. (3) Soil conservation was significantly correlated with the landscape indices patch density (PD), landscape shape index (LSI), mean patch area (AREA_MN), patch cohesion index (COHESION), splitting index (SPLIT), and Shannon evenness index (SHEI). Sub-watersheds with low soil conservation had landscape splitting index, landscape dispersion, patch type richness, and boundary complexity. These areas were mainly distributed in the southern part of the watershed. Sub-watersheds with higher soil conservation were characterized by low patch fragmentation and strong connectivity of dominant patches, which were mainly located in the northern part of the watershed. (4) The spatial error model (SEM) fit better in 2000, 2010, and 2020 compared with the spatial lag model (SLM) and ordinary least squares regression (OLS). The diagnostic results of the SEM model show that among the six landscape indices, PD, SHEI, and AREA_MN are the main influencing factors affecting soil conservation in the watershed to different degrees. The purpose of this study was to investigate the response state of soil conservation capacity as landscape patterns evolve in the Tingjiang Watershed, with the goal of providing a reference for landscape planning and management as well as soil erosion management in the watershed. Full article

(This article belongs to the Special Issue Towards the Sustainable Development Goals: Monitoring, Assessment and Management of Eco-Environmental Space)

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18 pages, 8330 KiB

Open AccessArticle

Evaluating Environmental Quality and Its Driving Force in Northeastern China Using the Remote Sensing Ecological Index

by Enjun Gong, Fangxin Shi, Zhihui Wang, Qingfeng Hu, Jing Zhang and Hongxin Hai

Sustainability 2022, 14(23), 16304; https://0-doi-org.brum.beds.ac.uk/10.3390/su142316304 - 6 Dec 2022

Cited by 7 | Viewed by 2078

Abstract

As one of the three major black soil regions in the world, northeastern China has an important strategic position there. Since the 20th century, the local environment has undergone great changes under the influence of the natural economy, and it is particularly important to quantitatively assess the degree of change. However, there have been few long-term quantitative studies of environmental spatial-temporal variances in the three northeastern provinces. Therefore, in this study, four typical remote sensing indices of the normalized difference vegetation index (NDVI), land surface temperature (LST), normalized differential building–soil index (NDBSI) and wetness (WET) were employed to construct the remote sensing ecological index (RSEI) using a principal component analysis (PCA) method based on the Google Earth Engine (GEE) platform in northeastern China. The spatiotemporal variations in the eco-environmental quality were detected using linear slope and M–K test, and the direct and interactive effects of different influencing factors on the RSEI changes during 2000–2020 were explored based on geographic detection. The results show that the interannual variations in the RSEI show a fluctuating upward trend, with an increase percentage of 12.45% in the last two decades, indicating that the ecological quality of northeast China has gradually improved. Furthermore, that the western and eastern Heilongjiang provinces and western Jilin provinces contributed substantially to the improvement of environmental quality, while the environmental quality of Jilin provinces and central Liaoning provinces decreased to varying degrees. Compared with 2000, the area with a fair environmental quality grade had the greatest change, and had decreased by 60.69%. This was followed by the area with an excellent quality grade, which increased by 117%. Land-use type had the greatest impact on environmental changes in northeastern China, but the impact degree gradually decreased, while the impact of socioeconomic factors such as the gross production of agriculture, forestry, animal husbandry and fishery and population density on environmental quality gradually increased. The major reason for the decline of environmental quality in central Jilin and central Liaoning is that urbanization development had occupied a large amount of cropland. This shows that taking into account the virtuous cycle of an ecological environment while promoting urban and rural development may be an important task for northeastern China in the future. Full article

(This article belongs to the Special Issue Towards the Sustainable Development Goals: Monitoring, Assessment and Management of Eco-Environmental Space)

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16 pages, 6297 KiB

Open AccessArticle

Comprehensive Evaluation of the Level of Water Ecological Civilization Construction in the Min River Basin, China

by Yuanyao Wen, Tiange You, Yihan Xu, Shuhui Lin, Jing Ning, Xuemin You and Yanglan Xiao

Sustainability 2022, 14(23), 15753; https://0-doi-org.brum.beds.ac.uk/10.3390/su142315753 - 26 Nov 2022

Cited by 1 | Viewed by 1510

Abstract

Water Ecological Civilization Construction (WECC) is critical for promoting long-term resource, economic, and social development. The Min River is the longest in Fujian Province, China, and is known as the “golden canal” for shipping. In this study, data from cities around the Min River were used to build an evaluation index system for WECC in the Min River, incorporating the Pressure–State–Response model, and the matter element extension model was used to examine the WECC level in the Min River Basin. The results indicate that notable progress has been made for WECC in the Min River Basin, despite evident regional variation. The upper parts of the Min River have seen the most development; however, the downstream regions have been mainly stable and retained a high WECC level. Changes in industrial structure and government actions substantially affect the degree of WECC. This study can act as a reference for river basin WECC. Full article

(This article belongs to the Special Issue Towards the Sustainable Development Goals: Monitoring, Assessment and Management of Eco-Environmental Space)

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20 pages, 1017 KiB

Open AccessArticle

Do Firms That Are Disadvantaged by Unilateral Climate Policy Receive Compensation? Evidence from China’s Energy-Saving Quota Policy

by Weiming Lin, Jianling Chen, Jianbang Gan and Yongwu Dai

Sustainability 2022, 14(22), 15375; https://0-doi-org.brum.beds.ac.uk/10.3390/su142215375 - 18 Nov 2022

Viewed by 1273

Abstract

Inequities caused by a unilateral climate policy may threaten the sustainability of CO₂ emission reduction efforts by countries and firms, thus endangering sustainable development for humans and the eco-environment. However, few studies have conducted ex-post evaluations on whether environmentally regulated firms receive external compensation such as subsidies, tax reductions, and loan support. Thus, this study investigates whether firms experiencing inequitable conditions under China’s Energy-Saving Quota Policy (ESQP) are financially compensated. It develops a balanced panel of data from 6189 ESQP-regulated and 6189 unregulated firms from 2010 to 2013, and combines a probit model with the difference-in-differences method to conduct empirical analysis. The results show that ESQP-regulated firms receive more subsidy income and lower tax rates than unregulated firms. Of the ESQP-regulated firms, companies with higher energy-saving burdens receive larger subsidies and lower financial expense ratios than those with lower burdens. Additionally, firms that complete their energy-saving quotas are compensated with larger subsidies and/or lower financial expense ratios and tax rates than those that fail to complete them. Finally, state-owned firms receive more subsidies than private ones. Unlike the emission trading schemes implemented worldwide that formulate an exemption mechanism (i.e., free or over-allocated allowances), the ESQP does not exempt regulated firms from their energy-saving responsibilities. Rather, regulated firms receive a greater amount of external compensation in exchange for their reductions in energy consumption. Full article

(This article belongs to the Special Issue Towards the Sustainable Development Goals: Monitoring, Assessment and Management of Eco-Environmental Space)

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16 pages, 33410 KiB

Open AccessArticle

AWS-DAIE: Incremental Ensemble Short-Term Electricity Load Forecasting Based on Sample Domain Adaptation

by Shengzeng Li, Yiwen Zhong and Jiaxiang Lin

Sustainability 2022, 14(21), 14205; https://0-doi-org.brum.beds.ac.uk/10.3390/su142114205 - 31 Oct 2022

Cited by 5 | Viewed by 1410

Abstract

Short-term load forecasting is a prerequisite and basis for power system planning and operation and has received extensive attention from researchers. To address the problem of concept drift caused by changes in the distribution patterns of electricity load data, researchers have proposed regular or quantitative model update strategies to cope with the concept drift; however, this may involve a large number of invalid updates, which not only have limited improvement in model accuracy, but also insufficient model response timeliness to meet the requirements of power systems. Hence, this paper proposes a novel incremental ensemble model based on sample domain adaptation (AWS-DAIE) for adapting concept drift in a timely and accurate manner and solves the problem of inadequate training of the model due to the few concept drift samples. The main idea of AWS-DAIE is to detect concept drift on current electricity load data and train a new base predictor using Tradaboost based on cumulative weighted sampling and then dynamically adjust the weights of the ensemble model according to the performance of the model under current electricity load data. For the purposes of demonstrating the feasibility and effectiveness of the proposed AWS-DAIE algorithm, we present the experimental results of the AWS-DAIE algorithm on electricity load data from four individual households and compared with several other excellent algorithms. The experimental results demonstrated that the proposed AWS-DAIE not only can adapt to the changes of the data distribution faster, but also outperforms all compared models in terms of prediction accuracy and has good practicality. Full article

(This article belongs to the Special Issue Towards the Sustainable Development Goals: Monitoring, Assessment and Management of Eco-Environmental Space)

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25 pages, 3509 KiB

Open AccessArticle

Efficiency Evaluation of a Forestry Green Economy under a Multi-Dimensional Output Benefit in China—Based on Evidential Reasoning and the Cross Efficiency Model

by Yan Huang, Xiao He, Shizhen He and Yongwu Dai

Sustainability 2022, 14(21), 13881; https://0-doi-org.brum.beds.ac.uk/10.3390/su142113881 - 26 Oct 2022

Cited by 2 | Viewed by 1327

Abstract

The efficiency evaluation of forestry green economy development is related to the direction of forestry development and plays an important role in balancing the economic and environmental issues within that forestry development. The existing research faces three challenges: first, the output indicator is singular; second, the perspective of a self-assessment is extremely limited; and third, the multi perspective fusion method is not in line with the mechanism of the cross efficiency evaluation model. To address these challenges and the characteristics of forestry development output, we constructed multi-level output indicators from four aspects: ecology, economy, society, and sustainability and used evidence reasoning to combine the output indicators. Based on the perspective of a cross evaluation among peers, four different cross efficiency values are defined from the evaluation relationship between the different decision-making units to obtain economic–aggressive, social–neutral, ecological–benevolent, sustainable–neutral, and comprehensive–neutral cross efficiencies. According to the relationship between self- and cross evaluation, an order conditional entropy cross efficiency aggregation model has been proposed and used to analyze the development efficiency of the forestry green economy in 31 Chinese provinces in 2019. Considering the uneven distribution of the forestry resources in China, the development in the 31 provinces and cities is divided into four types by discussing the relationship between the output indicators and efficiency, while the reasons for the unbalanced development and the poor comprehensive development are discussed according to five cross efficiencies. Full article

(This article belongs to the Special Issue Towards the Sustainable Development Goals: Monitoring, Assessment and Management of Eco-Environmental Space)

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24 pages, 14101 KiB

Open AccessArticle

A Study on the Difference of LULC Classification Results Based on Landsat 8 and Landsat 9 Data

by Haotian You, Xu Tang, Weixi Deng, Haoxin Song, Yu Wang and Jianjun Chen

Sustainability 2022, 14(21), 13730; https://0-doi-org.brum.beds.ac.uk/10.3390/su142113730 - 23 Oct 2022

Cited by 5 | Viewed by 1899

Abstract

Landsat 9 enhances the radiation resolution of the operational land imager from the 12 bits of Landsat 8 to 14 bits. The higher radiation resolution improves the sensitivity of the sensor to detect many subtler differences, especially in the case of dense forests or water. However, it remains unclear whether the difference in radiation resolution between Landsat 8 and Landsat 9 actually affects the classification results of water and tree species. Accordingly, the spectral reflectance and vegetation indices were extracted in this study, based on Landsat 8 and Landsat 9 images. Then, the classification models of land use and land cover (LULC) and tree species were developed by using a gradient tree boosting algorithm. Subsequently, the results were analyzed to further investigate how the differences in radiation resolution affect the classification results of LULC and tree species. It is shown that the LULC classification results of Landsat 8 and Landsat 9 are relatively favorable in most cases. However, the LULC classification results are relatively poor in test areas with a lower classification accuracy of water. Further analysis, in the case of test areas with poor classification results, indicates that there are significant differences in the water classification results between the two datasets. In other words, Landsat 9 produces better water classification results than Landsat 8 in most test areas. However, a temperature close to zero may lead to inverse water classification results. In addition, it indicates that the difference in forest classification results between the two datasets is small, but the results of forest tree species classification based on Landsat 9 are superior to those based on Landsat 8, with an improvement in overall accuracy of 6.01%. The results demonstrate that the difference in radiation resolution between Landsat 8 and Landsat 9 has little impact on the results of LULC classification in most cases. Nevertheless, in the case of some test areas, Landsat 9 is better suited for enhancing the classification accuracy of water and tree species. Full article

(This article belongs to the Special Issue Towards the Sustainable Development Goals: Monitoring, Assessment and Management of Eco-Environmental Space)

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13 pages, 3820 KiB

Open AccessArticle

Particulate Matter and Trace Metal Retention Capacities of Six Tree Species: Implications for Improving Urban Air Quality

by Weikang Zhang, Yu Li, Qiaochu Wang, Tong Zhang, Huan Meng, Jialian Gong and Zhi Zhang

Sustainability 2022, 14(20), 13374; https://0-doi-org.brum.beds.ac.uk/10.3390/su142013374 - 17 Oct 2022

Cited by 1 | Viewed by 1350

Abstract

As effective filters for natural particulate matter (PM), plants play an important role in the reduction of PM, thus improving air quality. However, research on the relationship between leaf functional traits and PM retention capacity in different polluted environments remains limited. In this study, six tree species (Abies holophylla, Pinus tabuliformis, Juniperus chinensis, Populus berolinensis, Salix babylonica, Robinia pseudoacacia) in Shenyang city, China were selected as research objects to analyze their PM retention capacity in three different polluted environments (i.e., a busy road, an industrial area of the urban center, and a green space). Additionally, we determined the composition of trace elements associated with the different polluted environments; we also evaluated the impact of different polluted environments on leaf surface traits. The results showed that the actual amounts of PM and trace elements that accumulated on leaf surfaces differed considerably between pollution sites and plant species. The greatest accumulation of PM₁₀ and PM_2.5 deposited on the leaves of tested plants was at a traffic-related pollution site and the smallest accumulation was at a park site. There were significant differences in the PM₁₀ and PM_2.5 retention capacities of leaves among the different tree species (p < 0.05), in the following order: Abies holophylla > Pinus tabuliformis > Juniperus chinensis > Populus berolinensis > Salix babylonica > Robinia pseudoacacia. The average PM₁₀ and PM_2.5 accumulation amounts of Abies holophylla were 1.28–8.74 times higher than these of the other plants (p < 0.05). Trace element analysis showed that the elemental composition of PM accumulated on leaf surfaces was location-dependent. In conclusion, a highly polluted environment can increase the average groove width, stomatal density, and roughness compared to a low-polluted environment. In contrast, the average value of contact angle is higher at low-pollution sites than at other sites. These results suggest that Abies holophylla is the most suitable greening tree species and that its widespread use could significantly reduce PM pollution in urban environments. Full article

(This article belongs to the Special Issue Towards the Sustainable Development Goals: Monitoring, Assessment and Management of Eco-Environmental Space)

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14 pages, 3304 KiB

Open AccessArticle

The Spatial-Temporal Differentiation of Aerosol Optical Properties and Types in the Beijing–Tianjin–Hebei Region Based on the Ecological Functional Zones

by Jianyong Dong, Xiaohong Wang, Jinlong Li, Chenxi Hao and Linlin Jiao

Sustainability 2022, 14(19), 12656; https://0-doi-org.brum.beds.ac.uk/10.3390/su141912656 - 5 Oct 2022

Cited by 2 | Viewed by 1239

Abstract

Atmospheric aerosol pollution has seriously affected the ecological environment and human health in recent years. There are great differences in aerosol optical properties and types due to the influence of environmental conditions, meteorology, industrial and agricultural activities, and other factors of each ecological functional zones. Using MODIS aerosol products (including MCD19A2 and MOD04_3K), this study discussed the temporal and spatial distribution of aerosol optical depth (AOD), Ångström wavelength index (AE) and aerosol types in the Beijing–Tianjin–Hebei region (BTH region) based on the ecological functional zones from 2015 to 2020. The results showed as follows: (1) The AOD in BTH region showed an obviously spatial pattern of low in the north and high in the south, while the spatial pattern of AE was opposite to that of AOD. In addition, the dominant aerosol type of the north part was clean aerosol, the dominant aerosol type of the middle part was biomass burning or urban-industrial aerosol, while that of the other part was mixed aerosols. (2) The seasonal changes of AOD and AE indexes in each ecological functional area had obvious seasonal changes, and the AOD and AE values were highest in summer. At the same time, the proportion of biomass combustion or urban industrial aerosol was the highest in summer. (3) The ecological functional areas with fewer human activities were dominated by clean aerosols, with lower AOD and higher AE value. The ecological functional areas dominated by cities were dominated by mixed aerosols, with higher AOD. The ecological functional areas dominated by agriculture and heavy industry were dominated by biomass combustion or urban industrial aerosols, with the largest AOD. (4) Compared with 2015, the average AOD of each ecological functional area decreased significantly to 2020, and biomass combustion or urban industrial aerosols changed to mixed aerosols. Full article

(This article belongs to the Special Issue Towards the Sustainable Development Goals: Monitoring, Assessment and Management of Eco-Environmental Space)

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