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Zhang L, Zhou S, Qi L, Deng Y. Nonlinear Effects of the Neighborhood Environments on Residents' Mental Health. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:16602. [PMID: 36554482 PMCID: PMC9778789 DOI: 10.3390/ijerph192416602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 12/04/2022] [Accepted: 12/05/2022] [Indexed: 06/17/2023]
Abstract
In the context of rapid urbanization and the "Healthy China" strategy, neighborhood environments play an important role in improving mental health among urban residents. While an increasing number of studies have explored the linear relationships between neighborhood environments and mental health, much remains to be revealed about the nonlinear health effects of neighborhood environments, the thresholds of various environmental factors, and the optimal environmental exposure levels for residents. To fill these gaps, this paper collected survey data from 1003 adult residents in Guangzhou, China, and measured the built and social environments within the neighborhoods. The random forest model was then employed to examine the nonlinear effects of neighborhood environments on mental health, evaluate the importance of each environmental variable, as well as identify the thresholds and optimal levels of various environmental factors. The results indicated that there are differences in the importance of diverse neighborhood environmental factors affecting mental health, and the more critical environmental factors included greenness, neighborhood communication, and fitness facility density. The nonlinear effects were shown to be universal and varied among neighborhood environmental factors, which could be classified into two categories: (i) higher exposure levels of some environmental factors (e.g., greenness, neighborhood communication, and neighborhood safety) were associated with better mental health; (ii) appropriate exposure levels of some environmental factors (e.g., medical, fitness, and entertainment facilities, and public transport stations) had positive effects on mental health, whereas a much higher or lower exposure level exerted a negative impact. Additionally, this study identified the exact thresholds and optimal exposure levels of neighborhood environmental factors, such as the threshold (22.00%) and optimal exposure level (>22.00%) of greenness and the threshold (3.80 number/km2) and optimal exposure level (3.80 number/km2) of fitness facility density.
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Affiliation(s)
- Lin Zhang
- Institute of Studies for the Greater Bay Area (Guangdong, Hong Kong, Macau), Guangdong University of Foreign Studies, Guangzhou 510006, China
| | - Suhong Zhou
- School of Geography and Planning, Sun Yat-sen University, Guangzhou 510006, China
- Guangdong Provincial Engineering Research Center for Public Security and Disaster, Guangzhou 510275, China
| | - Lanlan Qi
- School of Management, Guangdong Industry Polytechnic, Guangzhou 510300, China
| | - Yue Deng
- School of Architecture and Civil Engineering, Chengdu University, Chengdu 610106, China
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Li H, Wu Y, Liu S, Xiao J, Zhao W, Chen J, Alexandrov G, Cao Y. Decipher soil organic carbon dynamics and driving forces across China using machine learning. GLOBAL CHANGE BIOLOGY 2022; 28:3394-3410. [PMID: 35253325 DOI: 10.1111/gcb.16154] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 02/28/2022] [Accepted: 02/28/2022] [Indexed: 06/14/2023]
Abstract
The dynamics of soil organic carbon (SOC) play a critical role in modulating global warming. However, the long-term spatiotemporal changes of SOC at large scale, and the impacts of driving forces remain unclear. In this study, we investigated the dynamics of SOC in different soil layers across China through the1980s to 2010s using a machine learning approach and quantified the impacts of the key factors based on factorial simulation experiments.Our results showed that the latest (2000-2014) SOC stock in the first meter soil (SOC100 ) was 80.68 ± 3.49 Pg C, of which 42.6% was stored in the top 20 cm, sequestrating carbon with a rate of 30.80 ± 12.37 g C m-2 yr-1 since the 1980s. Our experiments focusing on the recent two periods (2000s and 2010s) revealed that climate change exerted the largest relative contributions to SOC dynamics in both layers and warming or drying can result in SOC loss. However, the influence of climate change weakened with soil depth, while the opposite for vegetation growth. Relationships between SOC and forest canopy height further confirmed this strengthened impact of vegetation with soil depth and highlighted the carbon sink function of deep soil in mature forest. Moreover, our estimates suggested that SOC dynamics in 71% of topsoil were controlled by climate change and its coupled influence with environmental variation (CE). Meanwhile, CE and the combined influence of climate change and vegetation growth dominated the SOC dynamics in 82.05% of the first meter soil. Additionally, the national cropland topsoil organic carbon increased with a rate of 23.6 ± 7.6 g C m-2 yr-1 since the 1980s, and the widely applied nitrogenous fertilizer was a key stimulus. Overall, our study extended the knowledge about the dynamics of SOC and deepened our understanding about the impacts of the primary factors.
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Affiliation(s)
- Huiwen Li
- Department of Earth & Environmental Science, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory of Degraded and Unused Land Consolidation Engineering, The Ministry of Natural Resources of China, Xi'an, China
| | - Yiping Wu
- Department of Earth & Environmental Science, Xi'an Jiaotong University, Xi'an, China
- Technology Innovation Center for Land Engineering and Human Settlements, Shaanxi Land Engineering Construction Group Co. Ltd, Xi'an Jiaotong University, Xi'an, China
| | - Shuguang Liu
- National Engineering Laboratory for Applied Technology of Forestry and Ecology in South China, Central South University of Forestry and Technology, Changsha, China
| | - Jingfeng Xiao
- Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, New Hampshire, USA
| | - Wenzhi Zhao
- Key Laboratory of Ecohydrology and River Basin Science, Northwest Institute of Eco-environment and Resources, Chinese Academy of Sciences, Lanzhou, China
| | - Ji Chen
- Department of Civil Engineering, The University of Hong Kong, Hong Kong, China
| | - Georgii Alexandrov
- A. M. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences, Moscow, Russian Federation
| | - Yue Cao
- Xi'an Institute for Innovative Earth Environment Research, Xi'an, China
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Terrestrial carbon sinks in China and around the world and their contribution to carbon neutrality. SCIENCE CHINA. LIFE SCIENCES 2022; 65:861-895. [PMID: 35146581 DOI: 10.1007/s11427-021-2045-5] [Citation(s) in RCA: 48] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 12/13/2021] [Indexed: 01/04/2023]
Abstract
Enhancing the terrestrial ecosystem carbon sink (referred to as terrestrial C sink) is an important way to slow down the continuous increase in atmospheric carbon dioxide (CO2) concentration and to achieve carbon neutrality target. To better understand the characteristics of terrestrial C sinks and their contribution to carbon neutrality, this review summarizes major progress in terrestrial C budget researches during the past decades, clarifies spatial patterns and drivers of terrestrial C sources and sinks in China and around the world, and examines the role of terrestrial C sinks in achieving carbon neutrality target. According to recent studies, the global terrestrial C sink has been increasing from a source of (-0.2±0.9) Pg C yr-1 (1 Pg=1015 g) in the 1960s to a sink of (1.9±1.1) Pg C yr-1 in the 2010s. By synthesizing the published data, we estimate terrestrial C sink of 0.20-0.25 Pg C yr-1 in China during the past decades, and predict it to be 0.15-0.52 Pg C yr-1 by 2060. The terrestrial C sinks are mainly located in the mid- and high latitudes of the Northern Hemisphere, while tropical regions act as a weak C sink or source. The C balance differs much among ecosystem types: forest is the major C sink; shrubland, wetland and farmland soil act as C sinks; and whether the grassland functions as C sink or source remains unclear. Desert might be a C sink, but the magnitude and the associated mechanisms are still controversial. Elevated atmospheric CO2 concentration, nitrogen deposition, climate change, and land cover change are the main drivers of terrestrial C sinks, while other factors such as fires and aerosols would also affect ecosystem C balance. The driving factors of terrestrial C sink differ among regions. Elevated CO2 concentration and climate change are major drivers of the C sinks in North America and Europe, while afforestation and ecological restoration are additionally important forcing factors of terrestrial C sinks in China. For future studies, we recommend the necessity for intensive and long term ecosystem C monitoring over broad geographic scale to improve terrestrial biosphere models for accurately evaluating terrestrial C budget and its dynamics under various climate change and policy scenarios.
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Song Z, Wu Y, Yang Y, Zhang X, Van Zwieten L, Bolan N, Li Z, Liu H, Hao Q, Yu C, Sun X, Song A, Wang W, Liu C, Wang H. High potential of stable carbon sequestration in phytoliths of China's grasslands. GLOBAL CHANGE BIOLOGY 2022; 28:2736-2750. [PMID: 35060227 DOI: 10.1111/gcb.16092] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 01/10/2022] [Indexed: 06/14/2023]
Abstract
Phytolith carbon (C) sequestration plays a key role in mitigating global climate change at a centennial to millennial time scale. However, previous estimates of phytolith-occluded carbon (PhytOC) storage and potential in China's grasslands have large uncertainties mainly due to multiple data sources. This contributes to the uncertainty in predicting long-term C sequestration in terrestrial ecosystems using Earth System Models. In this study, we carried out an intensive field investigation (79 sites, 237 soil profiles [0-100 cm], and 61 vegetation assessments) to quantify PhytOC storage in China's grasslands and to better explore the biogeographical patterns and influencing factors. Generally, PhytOC production flux and soil PhytOC density in both the Tibetan Plateau and the Inner Mongolian Plateau had a decreasing trend from the Northeast to the Southwest. The aboveground PhytOC production rate in China's grassland was 0.48 × 106 t CO2 a-1 , and the soil PhytOC storage was 383 × 106 t CO2 . About 45% of soil PhytOC was stored in the deep soil layers (50-100 cm), highlighting the importance of deep soil layers for C stock assessments. Importantly, the Tibetan Plateau had the greatest contribution (more than 70%) to the PhytOC storage in China's grasslands. The results of multiple regression analysis indicated that altitude and soil texture significantly influenced the spatial distribution of soil PhytOC, explaining 78.1% of the total variation. Soil phytolith turnover time in China's grasslands was mainly controlled by climatic conditions, with the turnover time on the Tibetan Plateau being significantly longer than that on the Inner Mongolian Plateau. Our results offer more accurate estimates of the potential for phytolith C sequestration from ecological restoration projects in degraded grassland ecosystems. These estimates are essential to parameterizing and validating global C models.
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Affiliation(s)
- Zhaoliang Song
- School of Earth System Science, Institute of Surface-Earth System Science, Tianjin University, Tianjin, China
| | - Yuntao Wu
- School of Earth System Science, Institute of Surface-Earth System Science, Tianjin University, Tianjin, China
| | - Yuanhe Yang
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China
| | - Xiaodong Zhang
- School of Earth System Science, Institute of Surface-Earth System Science, Tianjin University, Tianjin, China
| | - Lukas Van Zwieten
- NSW Department of Primary Industries, Wollongbar, New South Wales, Australia
| | - Nanthi Bolan
- School of Agriculture and Environment, Institute of Agriculture, University of Western Australia, Crawley, Western Australia, Australia
| | - Zimin Li
- Université catholique de Louvain (UCLouvain), Earth and Life Institute, Soil Science, Louvain-La-Neuve, Belgium
| | - Hongyan Liu
- College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Qian Hao
- School of Earth System Science, Institute of Surface-Earth System Science, Tianjin University, Tianjin, China
| | - Changxun Yu
- Department of Biology and Environmental Science, Linnaeus University, Kalmar, Sweden
| | - Xiaole Sun
- Baltic Sea Center, Stockholm University, Stockholm, Sweden
| | - Alin Song
- Key Laboratory of Crop Nutrition and Fertilization, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Wenying Wang
- Academy of Plateau Science and Sustainability, People's Government of Qinghai Province & Beijing Normal University, Qinghai, China
| | - Congqiang Liu
- School of Earth System Science, Institute of Surface-Earth System Science, Tianjin University, Tianjin, China
| | - Hailong Wang
- School of Environment and Chemical Engineering, Foshan University, Guangdong, China
- Key Laboratory of Soil Contamination Bioremediation of Zhejiang Province, College of Environmental and Resource Sciences, Zhejiang A & F University, Zhejiang, China
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Multi-Temporal Mapping of Soil Total Nitrogen Using Google Earth Engine across the Shandong Province of China. SUSTAINABILITY 2020. [DOI: 10.3390/su122410274] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Nitrogen plays an important role in improving soil productivity and maintaining ecosystem stability. Mapping and monitoring the soil total nitrogen (STN) content is the basis for modern soil management. The Google Earth Engine (GEE) platform covers a wide range of available satellite remote sensing datasets and can process massive data calculations. We collected 6823 soil samples in Shandong Province, China. The random forest (RF) algorithm predicted the STN content in croplands from 2002 to 2016 in Shandong Province, China on the GEE platform. Our results showed that RF had the coefficient of determination (R2) (0.57), which can predict the spatial distribution of the STN and analyze the trend of STN changes. The remote sensing spectral reflectance is more important in model building according to the variable importance analysis. From 2002 to 2016, the STN content of cropland in the province had an upward trend of 35.6%, which increased before 2010 and then decreased slightly. The GEE platform provides an opportunity to map dynamic changes of the STN content effectively, which can be used to evaluate soil properties in the future long-term agricultural management.
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Yang B, Gong J, Zhang Z, Wang B, Zhu C, Shi J, Liu M, Liu Y, Li X. Stabilization of carbon sequestration in a Chinese desert steppe benefits from increased temperatures and from precipitation outside the growing season. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 691:263-277. [PMID: 31323572 DOI: 10.1016/j.scitotenv.2019.06.481] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2019] [Revised: 06/27/2019] [Accepted: 06/27/2019] [Indexed: 06/10/2023]
Abstract
The carbon (C) dynamics of desert steppes play an important role in the C budget of temperate steppes. Using the Terrestrial Ecosystem Regional model (TECO-R) model for desert steppes, we examined the dynamics and potential driving mechanisms for C stocks at different temporal and spatial scales from 2000 to 2017 in northern China. The ecosystem C density averaged 2.73 kg C m-2 and soil organic C accounted for 91.6%. The grassland biome stored 2.85 kg C m-2, which is higher than the shrub biome (2.19 kg C m-2). The ecosystem storage increased by an average of 27.75 g C m-2 yr-1, with the fastest increase in the southeastern part of the study area. The grassland biome storage increased by an average of 33.54 g C m-2 yr-1, versus 25.74 g C m-2 yr-1 for the shrub biome. The desert steppe C stock totaled 288.29 Tg C, and increased at 3.09 Tg C yr-1. An average of >45% of the aboveground biomass was browsed by livestock. The growing season precipitation was significantly positively correlated with changes in the C stock. Increasing temperature was negatively correlated with the C stock, especially for soil carbon. Precipitation was an important driving factor, but warming interacted with precipitation to affect C sequestration during the growing season. Outside the growing season, the increased precipitation and temperature stabilized C sequestration in the desert steppe. This improved understanding of feedbacks between the desert steppe's C cycle and climate will improve predictions of C dynamics in terrestrial ecosystems and of the impacts of climate change.
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Affiliation(s)
- Bo Yang
- State Key Laboratory of Surface Processes and Resource Ecology, School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Jirui Gong
- State Key Laboratory of Surface Processes and Resource Ecology, School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China.
| | - Zihe Zhang
- State Key Laboratory of Surface Processes and Resource Ecology, School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Biao Wang
- State Key Laboratory of Surface Processes and Resource Ecology, School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Chenchen Zhu
- State Key Laboratory of Surface Processes and Resource Ecology, School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Jiayu Shi
- State Key Laboratory of Surface Processes and Resource Ecology, School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Min Liu
- State Key Laboratory of Surface Processes and Resource Ecology, School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Yinghui Liu
- State Key Laboratory of Surface Processes and Resource Ecology, School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Xiaobin Li
- State Key Laboratory of Surface Processes and Resource Ecology, School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China.
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Climate change, human impacts, and carbon sequestration in China. Proc Natl Acad Sci U S A 2018; 115:4015-4020. [PMID: 29666313 DOI: 10.1073/pnas.1700304115] [Citation(s) in RCA: 146] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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